Documents published in 2025 : Scipedia

Function-calling Schemas as De Facto Governance: Measuring Agency Reallocation through a Compiled Rule
A. Startari

Function-calling Schemas as De Facto Governance: Measuring Agency Reallocation through a Compiled Rule (2025). https://zenodo.org/records/17533080

Abstract
Function-calling schemas, presented in practitioner guides as mechanisms for structured output, operate as de facto governance instruments within model–tool ecosystems. While most documentation focuses on syntactic validity and schema adherence, little attention has been paid to how parameter defaults, validators, and enforced signatures redistribute agency among the operator, the model, and the external tool. This paper introduces the Agency Reallocation Index (ARI), a quantitative measure that captures this redistribution through entropy reduction and Shapley attribution across three control dimensions: operator, model, and tool. Treating the schema as a regla compilada (a compiled rule that pre-structures permissible actions), the study demonstrates how defaults and validation layers govern results as effectively as explicit human instruction. A factorial experiment over controlled tool-calling tasks isolates the effects of validator strictness, default intensity, and signature breadth on agency allocation. The findings show that higher validator rigidity or hard defaults consistently increase tool agency while compressing model autonomy, exposing a governance gradient encoded in interface design. The paper concludes that schema architecture not only constrains model behavior but also formalize a programmable distribution of authority that should be audited alongside conventional metrics of accuracy and reliability. DOI Primary archive: https://doi.org/10.5281/zenodo.17533080 Secondary archive: https://doi.org/10.6084/m9.figshare.30541049 SSRN: Pending assignment (ETA: Q4 2025)
Abstract
Function-calling schemas, presented in practitioner guides as mechanisms for structured output, operate as de facto governance instruments within model–tool ecosystems. [...]
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Modeling and Thermal Analysis of a Ground Cooling System for Drilling Fluids in Ultra-Deep Wells
J. Wang, Z. Song, Y. Chen, B. Zheng, S. Deng, K. Xu, B. Wang, Q. Ren

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. Online First, 74

Abstract
Elevated downhole temperatures in ultra-deep wells (>8000 m) accelerate thermal degradation of drilling fluids and tools, reducing operational safety and efficiency. The reduction of wellbore temperature is an important issue. In this paper, a cooling system model for a drilling fluid was designed. Additionally, a comprehensive analysis of the heat transfer behavior within ultra-deep wells was conducted. A miniaturized heat exchange cooling device was used to simulate various conditions, including fluid media, flow rate, drilling fluid/coolant temperature, and heat exchanger structure. This analysis elucidates the impact of various factors on cooling efficiency. The experimental results show that the cooling effect is best at a medium flow rate, with a refrigerant temperature of−10°C reducing the temperature of pure water from 60°C to 32°C. The experiment also found that the higher the temperature of the pure water and the lower the temperature of the coolant, the better the heat transfer efficiency. For water-based drilling fluid, the optimum cooling flow rate is around 0.52 m/s, with an average Reynolds number of 4966, and the maximum cooling range can exceed 30°C. Furthermore, the coil heat exchanger significantly improves the cooling rate compared to the straight-tube heat exchanger, although the pressure difference also increases. The cooling rate of oil-based drilling fluid at high flow rates is greater than that of water-based drilling fluid, and the pressure difference in the coil heat exchanger for oil-based drilling fluid, which has higher viscosity, increases significantly. This research provides an experimental basis for the design and optimization of drilling fluid surface cooling systems, which is crucial for improving the safety and efficiency of deep and ultra-deep wells drilling.OPEN ACCESS Received: 10/06/2025 Accepted: 15/08/2025
Abstract
Elevated downhole temperatures in ultra-deep wells (>8000 m) accelerate thermal degradation of drilling fluids and tools, reducing operational safety and efficiency. The [...]
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The Effect of Salvia miltiorrhiza on the Memory of Dugesia dorotocephala
V. Lin

Vicky Lin's personal collection (2025). 2

Abstract
In this experiment, the ability of sage, Salvia miltiorrhiza on memory retention and the organism population was assessed. Sage shows effects by aromatherapy, with active chemical properties to improve cognitive and neurological performance. This experiment used planarians as a neurological template to show the effects of the properties of sage. The planarians were separated into groups A, B, C, D, and E, each with ten individuals. Group A was the control, B was 0.001g/mL, C was 0.002g/mL, D was 0.003g/mL, and E was 0.004g/mL. It was predicted that the higher the concentration, the better the memory retention performance. This experiment compared the after-treatment results of the memory retention examination and to the before-treatment values through Excel, ANOVA with Tukey HSD, and t-tests. Results from trial 1 demonstrated that the sage solution improved the planarians' ability to retain information. Groups B and C performed better when compared to control group A and pre-treatment values. In trial 2, almost all the experimental groups outperformed the control group equally. After trial 3, group E showed the most significant results after treatment. In conclusion, sage was able to improve the memory retention of the planarians. Group A has the least change in memory retention; groups C and D showed effect after two days from treatment; groups B and E showed the most immediate effect. However, future research should be conducted to address more specific patterns between sage solution concentrations and memory retention of the planarians.
Abstract
In this experiment, the ability of sage, Salvia miltiorrhiza on memory retention and the organism population was assessed. Sage shows effects by aromatherapy, with active [...]
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Successive approximation method for solving (1+1)-dimensional dispersive long wave equations
B. ali

Successive approximation method for solving (1+1)-dimensional dispersive long wave equations (2017). International Journal of Advanced and Applied Sciences

Abstract
In this paper, we study the (1+1)-dimensional dispersive long wave equations which describe the evolution of horizontal velocity component u(
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On Observer-Based Control of One-Sided Lipschitz ω-Tempered Fractional-Order Systems under Input Saturation
S. Afli, A. Jmal, O. Naifar

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 71

Abstract
This paper addresses the critical challenge of observer-based control for one-sided Lipschitz (OSL) nonlinear systems governed by tempered fractional-order dynamics under input saturation constraints. We introduce a novel stability framework combining ω-tempered Caputo derivatives with Mittag-Leffler stability theory, enabling significantly faster exponential error decay compared to classical fractional operators. The proposed methodology features three key innovations: (1) a tempered Mittag-Leffler stability theorem incorporating sector-bounded saturation nonlinearities, (2) linear matrix inequality (LMI) conditions accommodating arbitrary OSL constants (ρ∈ R), and (3) a Cone Complementary Linearization (CCL) algorithm resolving gain synthesis challenges in tempered fractional systems. Numerical validation demonstrates 62% faster convergence than classical fractional approaches while maintaining saturation constraints. The CCL algorithm provides guaranteed convergence with computational efficiency, overcoming initialization sensitivity through regularization techniques.OPEN ACCESS Received: 05/06/2025 Accepted: 15/08/2025 Published: 27/10/2025
Abstract
This paper addresses the critical challenge of observer-based control for one-sided Lipschitz (OSL) nonlinear systems governed by tempered fractional-order dynamics under [...]
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Numerical Simulation, Physical Modeling and Plant Trail on the Slag Entrapment Behavior in a Four-Strand Tundish
B. Qin, J. Zhang, J. Chen, C. Gao, X. Zuo, Q. Liu

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 70

Abstract
The continuous casting process yields more than 96% crude steel worldwide. Numerical simulation and physical modeling were employed to investigate the slag entrainment behavior during the final casting stage in a four-strand continuous casting tundish. It is demonstrated that the numerical and physical modelling results agree well. Vortex formation in the final casting stage can be divided into four distinct stages: surface rotation, vortex generation, vortex development, and vortex penetration, with significant variations in critical slag entrainment depths observed among different outlets. Increasing casting speed increases slag entrainment risks, while employing vortex inhibitors could reduce the critical slag entrainment height by up to 29%. Through optimized casting termination procedures in a plant trial, the tundish residual depth decreased from 400 to 200 mm; The tail-end billet cleanliness significantly improved to reach a normal billet quality level in the end billet range of 2–3 m. This study provides theoretical and technical support for reducing slag entrainment defects and improving steel cleanliness in continuous casting.OPEN ACCESS Received: 15/05/2025 Accepted: 10/07/2025 Published: 27/10/2025
Abstract
The continuous casting process yields more than 96% crude steel worldwide. Numerical simulation and physical modeling were employed to investigate the slag entrainment behavior [...]
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A Comparative Analysis of the Boundary Condition Schemes for an Immersed Cylinder in a Water Stream with the Lattice Boltzmann Method
F. Garzeri, I. Martins, L. Cabezas-Gómez

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 69

Abstract
In this paper, we investigate the performance of different boundary condition (BC) schemes for curved walls within the framework of the Lattice Boltzmann Method (LBM). A canonical benchmark problem—the flow past a circular cylinder in a channel—is considered, with Reynolds numbers ranging from 50 to 300. While prior studies have examined similar configurations, this work provides a novel comparative analysis under realistic conditions—using dimensional LBM simulations with actual fluid properties and consumer-grade hardware, rather than idealized lattice units. Additionally, we introduce an in-house GPU-accelerated solver, enabling efficient high-fidelity simulations without reliance on specialized computational resources. Four wall boundary conditions—the standard bounce-back scheme, the non-equilibrium extrapolation scheme, the fictitious equilibrium scheme and a one-point scheme—are implemented and analyzed through their influence on the time-averaged drag coefficient of the cylinder. The results are compared against both experimental and Navier-Stokes-based numerical data to assess accuracy. Additionally, the study evaluates the relative impact of outlet BC selection on simulation fidelity. The findings show that all tested solid wall boundary schemes can produce reasonable predictions under suitable conditions. Furthermore, based on our results, the accuracy of LBM simulations is notably more sensitive to the choice of the outlet boundary condition when compared to the choice of the ones used at the immersed body.OPEN ACCESS Received: 08/05/2025 Accepted: 24/06/2025 Published: 27/10/2025
Abstract
In this paper, we investigate the performance of different boundary condition (BC) schemes for curved walls within the framework of the Lattice Boltzmann Method (LBM). A canonical [...]
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Dynamic and Control in a Three-Variable Chemical Reaction Model
M. Martinez, F. Chavarette

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 68

Abstract
Chaotic behavior in nonlinear chemical systems presents significant challenges for stability and control, particularly in practical applications. This study investigates the suppression of chaos in a three-variable reaction system through an optimal linear feedback strategy, formulated via the solution of an algebraic Riccati equation. The proposed control approach effectively eliminates chaotic oscillations, guiding the system to equilibrium even under parameter uncertainties of up to 20%. Numerical simulations confirm that the control action maintains high robustness, ensuring convergence with minimal effort. The stabilization time for x
Abstract
Chaotic behavior in nonlinear chemical systems presents significant challenges for stability and control, particularly in practical applications. This study investigates the [...]
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Optimum Analysis and Parameter Inference of a New Improved Adaptive Progressive Unit-Weibull Model Censoring with Two Physical Applications
H. Mohammed, O. Abo-Kasem, A. Elshahhat

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 67

Abstract
Recently, a new bounded version of the Weibull lifetime has been introduced, retaining the flexibility of the standard Weibull model while restricting it to the unit interval, making it particularly useful for betalike modeling in various fields. This paper investigates the improved adaptive Type-II progressively censored plan by applying it to the bounded unit Weibull distribution. From a frequentist perspective, both maximum likelihood and maximum product of spacings methods are used, along with appropriate approximate confidence intervals. Bayesian point estimates, along with Bayesian credible intervals, are obtained using classical procedures that involve Markov-Chain Monte Carlo sampling, with two separate posterior distributions based on the squared error loss. The proposed estimation frameworks encompass both distribution parameters and key reliability metrics, notably the reliability and failure rate functions. Extensive simulations are conducted to evaluate the accuracy and efficiency of the estimators under various censoring levels, sample sizes, and thresholds. To determine the optimal removal strategy under both frequentist estimation paradigms, several metrics are proposed. Additionally, the model is applied to two real-world datasets from engineering reliability; one contains core samples from petroleum reservoirs collected across four cross-sections, and the other pertains to the tensile strength of polyester fibers, illustrating its practical utility and flexibility in modeling. The novelty of this study lies in integrating the bounded support of the unit-Weibull model with an improved adaptive censoring scheme, providing enhanced robustness and adaptability in reliability analysis across different fields.OPEN ACCESS Received: 21/06/2025 Accepted: 19/08/2025 Published: 27/10/2025
Abstract
Recently, a new bounded version of the Weibull lifetime has been introduced, retaining the flexibility of the standard Weibull model while restricting it to the unit interval, [...]
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Approximate Calculation of the Generalized Erdélyi-Kober Operator Using a Cubic Spline
S. Karimov, E. Islamov, E. Shishkina

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 66

Abstract
This article investigates the problem of approximating the generalized Erdélyi-Kober fractional operator (often referred to as the Lowndes operator) using cubic splines. A method based on cubic spline interpolation is proposed for approximating the operator on a non-uniform grid. The convergence rate of the proposed method is proven, and its stability is analyzed. Error bounds are established for functions in the class C4[0; b], providing a mathematical justification for the accuracy of the approximation. The efficiency of the method is validated through practical examples using test functions such as f (x)= x4.7and f (x)= cos x, with results presented in graphical and numerical forms. This approach ensures high accuracy and flexibility in computing fractional integrals, which is of significant importance for solving fractional models used in physics, engineering, and other sciences. The article also provides an overview of the role of the generalized Erdélyi-Kober operator in modern fractional calculus and its applications.OPEN ACCESS Received: 06/06/2025 Accepted: 08/09/2025 Published: 27/10/2025
Abstract
This article investigates the problem of approximating the generalized Erdélyi-Kober fractional operator (often referred to as the Lowndes operator) using cubic splines. [...]
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Fundamental Mechanics and Precision Control of Optical Axis Stability and Parallelism in Multi-Sensor Electro-Optical Pods
Z. Huang, S. Chi, L. Zhu

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 65

Abstract
Modern electro-optical pods incorporatemulti-spectral sensors for reconnaissance, target acquisition, and laser designation, where sub-milliradian optical axis stability and inter-sensor parallelism are critical for mission success. This paper establishes a unified theoretical framework combining rigid-body kinematics and deformable body mechanics to develop a physics-based stability metric through screw theory formulation, expressing the optical axis dynamics as ˙O = [ω]×O+v, with thermo-mechanical constraints [ω]×O < ω, v < v for engineering implementation. A novel computational geometry method evaluates multi-sensor alignment errors by solving Ei = si − (si · ˆO) ˆO + JTT + Jgg, where JT and Jg represent thermal and gravitational Jacobians. The rigid-flexible coupling model with multi-point constraints (MPC) reveals thermal dominance (0.49 mrad IR sensor pitch displacement at 60◦C, 272× gravitational effect), material sensitivity (CTE mismatch contributing 68% of TV sensor’s azimuthal error), and cross-axis coupling (19% LD error amplification under thermal gradients). However, due to the limitations of current experimental conditions, the experimental validation ismainly carried out in controlled environments. The current experimental validation shows <5% deviation between predicted andmeasured parallelismerrors across −20◦C to 60◦C. In the future, we will supplement the evaluation of the robustness of the control method through existing simulation verifications (such as adding vibration and temperature disturbance models) in the “experimental discussion” or “prospect” section, and clarify the research plan for actual environment testing. The framework provides design guidelines for optimal sensor placement minimizing JT F, temperaturedependent calibration protocols, and 0.1 mrad allocable margin for manufacturing tolerances. This methodology advances electro-optical system engineering fromempirical tuning tomodel-driven optimization, demonstrating 0.12 mrad (3σ) stability in field tests under ISO 9022 environmental stress profiles, with key innovations including the first integration of Lie algebra kinematics with FEM-based deformation analysis for optical systems and physics-informed error budgeting separating thermal, mechanical, and alignment components.
Abstract
Modern electro-optical pods incorporatemulti-spectral sensors for reconnaissance, target acquisition, and laser designation, where sub-milliradian optical axis stability [...]
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On Nonlinear Monge-Ampère Equations and Their Symmetry Classifications
Z. Izgi, Ö. Avit, D. Baleanu, M. Yousif, M. Alharthi, P. Mohammed

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 64

Abstract
The Monge-Ampère equation (MAE) plays a pivotal role across a broad spectrum of theoretical and applied sciences, with its solutions being essential for advancing various fields. This study explores all forms of the fully nonlinear MAE using Lie group transformations to reduce the equation into solvable forms. Analytical solutions are derived using ansatzbased methods, yielding novel and generalized results that enhance the existing body of knowledge. In particular, solutions for cases with diverse source functions and boundary conditions are obtained, addressing gaps in the literature. Stability of the solutions is studied through both analytical and numerical approaches. Comparisons with existing solutions demonstrate the efficiency and generality of the proposed methods. The results presented in this work are poised to impact numerous applications, providing a robust framework for further research on MAEs.OPEN ACCESS Received: 24/05/2025 Accepted: 07/08/2025 Published: 27/10/2025
Abstract
The Monge-Ampère equation (MAE) plays a pivotal role across a broad spectrum of theoretical and applied sciences, with its solutions being essential for advancing various [...]
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RCS Simulation of Double S-Shaped Inlet with Radar Absorbing Materials Shedding Using Iterative Physical Optics with Impedance Boundary Condition
X. Guo, X. Xia, Z. Zhao, M. Wu, Y. Liu

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 63

Abstract
The inlet of an aircraft engine is a primary contributor to the aircraft’s forward electromagnetic scattering. S-shaped inlet and radar absorbing materials (RAM) coatings have been widely adopted as effective measures to reduce forward radar cross section (RCS). To investigate the influence of RAM shedding on the RCS reduction efficiency, the electromagnetic scattering characteristics of the inlet under five different shedding probabilities were calculated using the iterative physical optics (IPO) combined with impedance boundary condition (IBC). Numerical simulation results demonstrate that the forward RCS of the S-shaped inlets increases monotonically with shedding probability. In the yaw plane, intact non-magnetic RAM exhibits better RCS reduction efficiency (RRE) than that in the pitch plane across all scenarios. Specifically, at a shedding probability of 0.7, the remaining non-magnetic RAM maintains an RRE exceeding 40% in the pitch plane. Collectively, these results suggest that recoating the nonmagnetic RAM is recommended when the shedding probability exceeds 0.7 in either detection plane to sustain critical stealth performance.OPEN ACCESS Received: 20/05/2025 Accepted: 13/08/2025 Published: 27/10/2025
Abstract
The inlet of an aircraft engine is a primary contributor to the aircraft’s forward electromagnetic scattering. S-shaped inlet and radar absorbing materials (RAM) coatings [...]
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Deep Learning Approaches for Hydrological Forecasting: A Systematic Review
L. Singh, K. Singh, K. Singh, N. Hoque, D. Bhattacharyya

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 62

Abstract
Machine learning (ML) techniques, especially Deep Learning (DL) techniques, have been applied for flood risk analysis and prediction on spatial historical data to minimize the risk of the loss of lives and properties associated with floods. In recent years, various studies have established DL as an effective approach for building potential flood prediction models. However, a thorough, systematic integration of recent advancements in DL for hydrological forecasting, their reported performance, and challenges is essential for guiding future work effectively. This paper presents a systematic survey of various DL models applied to flood prediction. This systematic review integrates studies published between 2018 and 2025 that used DL models in hydrological forecasting, such as flood prediction, streamflow forecasting, and runoff modeling. A systematic search of major electronic databases was performed using pre-defined inclusion and exclusion criteria. The overall search provided 647 records, which were narrowed down to a final collection of 45 studies after screening and full-text examination based on factors like study design, hydrological forecasting relevance, and application of DL. The review quantitatively summarizes the reported performances of various DL models, including RNN variants (LSTM, GRU), CNN, GAN, and hybrid architectures, across different hydrological forecasting tasks and datasets. Findings indicate that DL models consistently achieve high performance metrics such as NSE of (0.99), RMSE of (24.61) and MAPE of (1.73) for certain applications. Despite these advancements, significant research gaps remain, particularly concerning the scarcity of high-quality, publicly available datasets with detailed spatial information, the need for more robust real-time prediction systems with minimized false alarms, and the development of more generalized models applicable across diverse geographical regions. this review highlights the significant potential of DL in hydrological prediction as well as clearly stating the fundamental challenges that need to be overcome in order to achieve more robust and generalizable flood prediction systems.OPEN ACCESS Received: 25/04/2025 Accepted: 22/07/2025 Published: 27/10/2025
Abstract
Machine learning (ML) techniques, especially Deep Learning (DL) techniques, have been applied for flood risk analysis and prediction on spatial historical data to minimize [...]
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Inference of the Exponentiated Rayleigh Distribution on Step-Stress Accelerated Life Testing under Type-I Hybrid Censored Data with Physical Application
M. Fawzy, I. Alasbahi, T. Alof, A. Ahmad, H. Taha, A. El-Bary, K. Lofty

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 61

Abstract
This paper aims to estimate the unknown parameters for the exponentiated Rayleigh distribution using Type-I hybrid censored data under a step-stress model. The maximum likelihood and Bayes methods estimate the parameters and acceleration factor. The parameters’ approximate confidence intervals are created. The Bayes estimates of the parameters for the squared error and linear exponential loss functions are computed using the Markov Chain Monte Carlo (MCMC) method. Finally, we perform a simulation study to evaluate the effectiveness of the proposed estimators. We provide a real-life data example (Strength data measurement in GPA, for single and impregnated carbon fibers) to explain the obtained results.OPEN ACCESS Received: 15/04/2025 Accepted: 21/08/2025 Published: 27/10/2025
Abstract
This paper aims to estimate the unknown parameters for the exponentiated Rayleigh distribution using Type-I hybrid censored data under a step-stress model. The maximum likelihood [...]
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Effects of the Trapezoidal Embedded Loading Berm on the Stability of Soft-Soil Foundation Embankment
F. Xiong, Y. Wang, F. Yang, L. Zhou, C. Hu, X. Wang, F. Li

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (4), 60

Abstract
The traditional loading berm is effective in reinforcing soft-soil foundation embankments, however, it is found that its large footprint limits its application in some narrow construction sites in recent years. Therefore, to address this limitation, the trapezoidal embedded loading berm (TELB) has been introduced, and its feasibility was examined in this paper. Firstly, an analytical model was developed to investigate the mechanical behavior of the TELB. Then, a numerical approach was employed to assess the TELB’s efficacy in enhancing the stability of soft-soil foundation embankments. The study elucidates the impact of various TELB parameters— such as slope angle, lower edge width, height, density, internal friction angle, and cohesion—on the embankment stability coefficient. Finally, an orthogonal test was conducted to evaluate the sensitivity of each parameter concerning embankment stability. The results demonstrate that the TELB substantially improves the stability of soft-soil foundation embankments, with stability coefficients increasing as the geometric and physicalmechanical parameters of the loading berm are enhanced. Among the parameters, height and density exert a more pronounced effect on the stability coefficient compared to cohesion and internal friction angle. This research provides valuable insights for the design and construction of TELBs and contributes to mitigating the environmental impact of road construction in soft soil regions.OPEN ACCESS Received: 23/03/2025 Accepted: 10/06/2025 Published: 27/10/2025
Abstract
The traditional loading berm is effective in reinforcing soft-soil foundation embankments, however, it is found that its large footprint limits its application in some narrow [...]
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Optimizing peridynamic microparameters for accurate representation of elasticity, plasticity, and shear localization in geomaterials
S. Nandwal, S. Sinha

Particles 2025.

Abstract
Geomaterials exhibit complex failure mechanisms characterized by strain localization and discontinuities (such as micro-crack formation and propagation), posing substantial challenges in their numerical modelling using the continuum-based methods. These limitations are typically addressed through algorithmic interventions or by using a non-local formulation. Peridynamic is one such method that inherently overcomes these limitations by replacing the partial differentials with non-local integral equations, enabling material points to interact with neighbouring points within a defined horizon. Similar to other numerical approaches, the application of peridynamic in geomechanics necessitates precise calibration of elastic parameters, as they play a crucial role in governing the plastic behavior of geomaterials. In this context, the present investigation studied the optimization of non-ordinary state-based peridynamic formulations using a geomaterial test specimen with a 1:2 aspect ratio under compression to evaluate the influence of critical numerical parameters, namely horizon size and material points discretization, on the accuracy of predicted elastic modulus. The results highlighted the necessity of selecting optimal combinations of mesh density and horizon size to achieve convergence toward input elastic properties. Furthermore, the obtained optimized parameters were used to simulate a series of plane strain compression tests on geomaterials to gain insight into plastic deformation and shear band formation. The study affirmed that parameter calibration is fundamental for accurately capturing both elastic and plastic behaviors of geomaterials. This calibrated model can offer significant potential for modelling failure surfaces below foundations, behind a retaining wall, and on a slope.
Abstract
Geomaterials exhibit complex failure mechanisms characterized by strain localization and discontinuities (such as micro-crack formation and propagation), posing substantial [...]
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Diversidad florística y factores agroclimáticos en los Montes de María en Colombia: una revisión de la literatura. Floristic diversity and agroclimatic factors in the Montes de María, Colombia: a literature review
J. Olaya

Julio Olaya's personal collection (2025). 1

Abstract
The tropical dry forest (Bs-T) is one of the most fragile habitats in Colombia, threatened by deforestation, the expansion of poor agricultural and livestock practices, and the fragmentation of the ecosystem. In the Montes de María, which spans territories of the departments of Bolívar and Sucre, a remnant of Bs-T of great relevance is preserved due to its biological and sociocultural value. This article provides a review of the current knowledge of floristic diversity and the agroclimatic factors that condition its composition and distribution. Several studies are analyzed that expose the role of climatic seasonality, the richness of plant species, as well as the main warnings facing this ecosystem. On the other hand, advancements in conservation, restoration, and participation are examined, highlighting the need to combine science with local knowledge to strengthen the planning of its territorial viability. The collected information provides an important resource to verify the execution of existing environmental policies and allows for the search for elements that contribute to the protection of biodiversity in the context of climate change, and the weight that human activities impose on ecosystems and natural resources.
Abstract
The tropical dry forest (Bs-T) is one of the most fragile habitats in Colombia, threatened by deforestation, the expansion of poor agricultural and livestock practices, and [...]
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IberGIS v1. User’s start guide and tutorial. Iber-SWMM calculation module
M. Sanz-Ramos, E. Sañudo, S. Maspons, M. Guzman, P. Vazquez, Ò. Pueyo, N. Karki, X. Torret, O. García-Feal, D. Dehghan-Souraki, C. Montalvo, L. Cea, E. Bladé

Iber. More than 2D Hydraulic modelling (2025). 3

Abstract
Urban drainage systems are facing increasing challenges due to climate change, urban growth, and the need for more sustainable water management. To address these issues, the Digital DRAIN project has developed an open-source tool that integrates different models within a GIS environment to analyse the performance of drainage systems. The tool helps assess both water flows and pollution, while also supporting the design of sustainable solutions and adaptation strategies. Delivered as the QGIS plugin IberGIS, it provides an accessible framework to improve urban water management and enhance resilience against floods and environmental impacts.
Abstract
Urban drainage systems are facing increasing challenges due to climate change, urban growth, and the need for more sustainable water management. To address these issues, the [...]
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Real-Time Detection of Authority-Bearing Constructions Under Strict Causal Masking
A. Startari

Real-Time Detection of Authority-Bearing Constructions Under Strict Causal Masking (2025). https://zenodo.org/records/17465070

Abstract
This datasheet defines a benchmark for real-time detection of authority-bearing constructions under strict causal masking, where models access only left context. It measures how accurately and quickly a system identifies linguistic signals of authority without future tokens. Authority-bearing constructions are treated as Type-0 productions within a regla compilada, binding syntactic and operational constraints to decisions. Three hypotheses guide the study: a compact causal detector with an authority lexicon can achieve reliable precision at low latency; performance depends on construction family and register rather than sentiment; limited buffers can improve stability without breaking causality. Multilingual datasets (English, Spanish, optional French, German, Portuguese) include transcripts, hearings, and policy texts segmented into token streams. Tasks involve streaming span detection and stance classification, evaluated at multiple latency checkpoints and causal budgets (b ∈ {32, 64, 128}). Metrics cover streaming F1, AUCL, and stability index.Baselines (oracle, lexicon-only, sentiment) and strict no-lookahead validation ensure isolation of causal effects. The benchmark shows how form, not intent, governs real-time authority recognition, enabling evaluation of models for compliance and human-in-the-loop systems without right-context access. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book AI Syntactic Power and Legitimacy. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained.
Abstract
This datasheet defines a benchmark for real-time detection of authority-bearing constructions under strict causal masking, where models access only left context. It measures [...]
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Study the Wear Resistance and Corrosion of Ni-P/ PTFE Composite Coatings Prepared by Electrodeposition Method
Z. Wetwet

High Temperature Materials and Processes (2025).

Abstract
Coating is one of the effective ways to increase the corrosion resistance and wear of metallic substrates. Additionally, the composite coatings using nanoparticles can also further protect the substrate. In this study, using electrodeposition process and polytetrafluoroethylene (PTFE) particles (with concentrations of 10, 20 or 30 g /L), NiPTFE coatings were prepared and their corrosion and wear properties were investigated and compared with Ni-P coating. Using scanning electron microscopy (SEM) and X-ray diffraction (EDS) method, the surface morphology and elemental composition of the coatings were analyzed and finally, by using open circuit potential (OCP) techniques, electrochemical impedance spectroscopy (EIS) and TAFEL polarization techniques, the corrosion resistance of the resulting coatings in 3/5 wt.% NaCl solution were evaluated. Microhardness and pin on disk tests were also utilized to investigate the effect of PTFE concentration on the tribological properties of the coatings. The results of SEM and EDS studies confirmed the formation of nanocomposites. Electrochemical studies also showed that Ni-PTFE coatings, at a concentration of 20 g/L PTFE, had the highest electrochemical corrosion resistance. Microhardness also decreased with increasing PTFE particles in the coating and reached its lowest value. By using the wear test, the lowest coefficient of friction obtained in composite coatings with concentration of 20 g/L, which shows the applicability of PTFE particles as a solid lubricant in Ni-P coatings.
Abstract
Coating is one of the effective ways to increase the corrosion resistance and wear of metallic substrates. Additionally, the composite coatings using nanoparticles can also [...]
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Level of Compliance of School Buildings on DepEd Order No. 6, S. 2021: A Basis for Policy Formulation
M. Aguinaldo(1), L. Suanson(2), J. Estorel(3), R. Estiller(2*)

JSC Matls. Proj. Mangt. (2025). Vol. 1, (Issue-2, December), 12

Abstract
In developing educational infrastructure, adherence to regulatory standards is vital to ensuring safe, conducive learning environments. This study evaluated the compliance of public-school buildings in the DepEd Division of Tuguegarao with DepEd Order No. 6, s. 2021. Using both quantitative and qualitative approaches, researchers conducted actual observations with a structured tool patterned after the DepEd Order. They surveyed school physical facilities coordinators and school heads to measure awareness levels. Findings revealed varied levels of compliance across five building groups. Groups 1 and 3 recorded weighted means of 1.54 and 1.65, respectively, indicating non-compliance, whereas Groups 2 and 4 showed partial compliance, with weighted means of 1.68 and 1.83, respectively. Group 5 achieved better compliance with a mean of 2.57. Meanwhile, awareness levels among coordinators and school heads were high, ranging from 2.63 to 2.97. Interestingly, the study found significant negative correlations between compliance and awareness for non-donated buildings, particularly in stairways (-0.72871) and corridor railings (-0.68859). For donated buildings, however, little to no significant correlations were observed in classroom size, architectural features, plumbing, and structural components. Overall, the study highlights critical areas of non-compliance and the need for targeted improvements in school infrastructure.
Abstract
In developing educational infrastructure, adherence to regulatory standards is vital to ensuring safe, conducive learning environments. This study evaluated the compliance [...]
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Market Signal from Syntactic Authority: Syntactic Authority Index and Market Signal
A. Startari

Market Signal from Syntactic Authority: Syntactic Authority Index and Market Signal (2025). https://zenodo.org/records/17406334

Abstract
This study presents the Syntactic Authority Index (SAI) as a quantitative measure of linguistic authority within financial discourse and evaluates its predictive capacity for market behavior. By detecting recurrent authority-bearing constructions such as deontic modalities, nominalizations, enumerations, and passive imperatives, the index demonstrates how linguistic form itself carries institutional weight. The regla compilada, understood as a Type-0 production that binds constraints to model decisions, functions as the generative substrate connecting syntax to observable financial reactions. Using multilingual corpora of earnings calls, investor letters, and regulatory filings, the research examines whether variations in the SAI precede abnormal returns, volume shifts, and regulatory enforcement events. Out-of-sample evaluations show that increases in syntactic authority correlate with short-term market anomalies while remaining independent of sentiment or tone. The signal intensifies under macroeconomic uncertainty or within firms under regulatory observation. These findings indicate that linguistic form operates as an actionable signal, showing that authority encoded in syntax can coordinate expectations and influence market conduct without relying on authorial intent. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book AI Syntactic Power and Legitimacy. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained.
Abstract
This study presents the Syntactic Authority Index (SAI) as a quantitative measure of linguistic authority within financial discourse and evaluates its predictive capacity [...]
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Causal vs Retrocausal Attention Boundaries
A. Startari

Causal vs Retrocausal Attention Boundaries (2025). https://zenodo.org/records/17378361

Abstract
This study quantifies the minimal right context that changes model decisions about authority bearing constructions under strict causal masking versus non causal access. We formalize flip probability P_flip(b to b+Δ), the instance level threshold τ(x), and the construction level threshold τ_C, and we measure breakpoint sharpness over a right context ladder b in {0, 1, 2, 4, 8, 16, 32}. The dataset contains minimal pair ladders per construction family, deontic stacks, nominalizations, enumerations, defaults, agent deletion, scope setting adverbs, role addressatives, across six languages, en, es, pt BR, fr, de, hi, with balanced length, domain, and register, and human gold labels. We evaluate frozen causal decoder models, non causal encoders and encoder decoders, and causal streaming variants with sliding windows. Masking primitives include hard truncation, stochastic truncation, and delayed reveal streaming with cache isolation and sentinel based leakage tests. Primary endpoints are τ_C by construction and language, P_flip curves, AUC_flip, and a latency accuracy frontier. Results map τ_C to observed compliance deltas on instructed tasks while holding administrative workflow constant. The contributions are a public dataset with right context ladders, an evaluation harness with tested masks, per construction τ atlases and P_flip plots, and a preregistered analysis that links regla compilada constraints, Type 0 production equivalence, to measurable authority judgments. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book AI Syntactic Power and Legitimacy. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained.
Abstract
This study quantifies the minimal right context that changes model decisions about authority bearing constructions under strict causal masking versus non causal access. We [...]
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Numerical and Experimental Investigation of Thermal Pre-Treatment for Lithium-Ion Battery Recycling
E. Souza, C. Spijker, D. Maxim, Z. Raonic

Particles 2025.

Abstract
Conventional recycling of lithium-ion batteries (LIBs) generally proceeds through stages of discharging, dismantling, shredding, and thermal treatment. The pyrolysis step is particularly important for removing organic components, such as electrolytes and binders. The present study focuses on investigating a thermal pretreatment process that integrates the discharging, dismantling, and pyrolysis steps. The process involves exposing LIB cells to moderate temperatures (below 300 °C) to trigger thermal runaway, while conserving the materials to be recycled. This method is intended to serve as an initial step in the LIB recycling chain, aiming to enhance the efficiency of downstream recycling processes, including pyro-, hydro-, and bio-metallurgy. To study this process, experimental and numerical approaches are being employed, with the goal of better understanding of the physical and chemical phenomena involved and providing insights for industrial optimization.
Abstract
Conventional recycling of lithium-ion batteries (LIBs) generally proceeds through stages of discharging, dismantling, shredding, and thermal treatment. The pyrolysis step [...]
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DISEÑO Y CONSTRUCCIÓN DE UN PROTOTIPO INTELIGENTE DE OXIGENACIÓN MEDIANTE ENERGÍA SOLAR EN ESTANQUE DE GEOMEMBRANAS EXISTENTE EN EL SENA SUCRE
Á. Mosquera, C. Perez, R. Rojas

DISEÑO Y CONSTRUCCIÓN DE UN PROTOTIPO INTELIGENTE DE OXIGENACIÓN MEDIANTE ENERGÍA SOLAR EN ESTANQUE DE GEOMEMBRANAS EXISTENTE EN EL SENA SUCRE (2025).

Abstract
In this project, it is proposed to design and build an intelligent oxygenation prototype powered by solar energy, in the existing geomembrane ponds at SENA, with the aim of ensuring an efficient oxygen supply for tilapia farming in Sucre. Through the design and construction of this intelligent oxygenation system, aquaculture production will be optimized by improving fish health and growth, as it provides optimal levels of dissolved oxygen in the water. In addition to improving production, this prototype will reduce energy costs, representing savings for producers.
Abstract
In this project, it is proposed to design and build an intelligent oxygenation prototype powered by solar energy, in the existing geomembrane ponds at SENA, with the aim of [...]
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Description of Air-Droplet Flow in the Problem of Aircraft Icing Modeling
S. Aleksieienko, Z. Sazanishvili, V. Nekrasov

Particles 2025.

Abstract
In-flight aircraft icing is a serious problem affecting flight safety and operational reliability. Atmospheric supercooled water droplets impinge on aircraft surfaces and freeze, forming ice, which can severely degrade aerodynamic performance and operational safety, potentially leading to a complete loss of control. Computational fluid dynamics is an important tool in the development of aircraft anti-icing systems, and modeling icing processes is a complex, interdisciplinary, and multi-physics task. This study presents approaches to describing the air-droplet incoming flow in aircraft icing modeling and analyzes the behavior of droplets interacting with an ice-covered aerodynamic surface. The Navier-Stokes equations coupled with the Spalart-Allmaras turbulence model are used to describe the motion of the carrier medium. The applicability of the polydisperse Eulerian, Lagrangian trajectory, and homogeneous models is analyzed for supercooled droplet dynamics. Numerical simulation of icing processes is performed using the control volume method, taking into account the conservation laws of mass, momentum, and energy. The analysis conducted in this work showed that the homogeneous model is appropriate for conditions near the phase transition point. The freezing of moisture that impinges on the aerodynamic surface is primarily governed by the temperature of the aerodynamic body and its heat exchange with the incoming flow. In cases where supercooled atmospheric droplets play a dominant role in the icing process, the Lagrangian trajectory model and the polydisperse Eulerian model are preferable for describing the air-droplet flow. The primary conclusion is that the polydisperse Eulerian model is preferable, as it best accounts for the characteristics of two-phase viscous compressible flow around bodies and the interaction of the carrier and liquid phases, making it the most promising approach for modeling aircraft icing. The results obtained can be used to ensure flight safety, design anti-icing systems, and investigate aviation accidents
Abstract
In-flight aircraft icing is a serious problem affecting flight safety and operational reliability. Atmospheric supercooled water droplets impinge on aircraft surfaces and [...]
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Simulating interparticular forces in cementitious media using the Discrete Particle Method
F. Wiese, R. Sposito, A. Kustermann, T. Stengel

Particles 2025.

Abstract
Concrete is by far the most produced material in the world, at around 15 billion tonnes per year [1]. Given the scale of production and the associated use of cement, the concrete industry is a large CO2 emitter, responsible for more than twice the CO2 emissions of global aviation [2, 3]. Consequently, concrete offers significant potential for climate impact mitigation by reducing the embodied CO2 per kilogram of material [4]. Concrete consists mainly of sand, gravel, water, and Portland cement clinker, with the latter being the main source of its high global warming potential. Therefore, the ongoing research effort is to minimise the amount of clinker in concrete by pursuing two different strategies: the development of alternative binders and the optimisation of concrete composition. This study follows the latter approach. Optimising concrete composition requires a detailed understanding of the interparticular forces that occur. These forces are complex, and an efficient yet accurate strategy is required to predict and investigate their effects on small scales, with the aim of upscaling to concrete in the future. Therefore, this study investigates the linear viscoelastic contact model with adhesion forces to capture the interactions between cement clinker, limestone filler, and quartz sand in an alkaline solution. The contact model is then used to simulate the packing problem with three distinct materials. The resulting packing density is compared to the same simulation, without interparticular forces.
Abstract
Concrete is by far the most produced material in the world, at around 15 billion tonnes per year [1]. Given the scale of production and the associated use of cement, the concrete [...]
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Turbulent Flow Simulation with High-Order Regularized Lattice Boltzmann Method Using D3Q27
B. Anjos, G. Choaire, L. Hegele

Particles 2025.

Abstract
We employ the lattice Boltzmann method (LBM) to perform flow simulations with the objective of evaluating the performance of the D3Q27 stencil in capturing complex flow structures. We used a specific variation of the method known as the Moment Representation Lattice Boltzmann Method (MR-LBM), which employs a second-order moment representation to regularize the distribution functions, thereby enhancing computational performance. The implementation incorporates the Bhatnagar-Gross-Krook (BGK) collision operator, which is embedded in the moment evaluation process. As benchmark cases, we considered the lid-driven cavity (LDC) flow and a turbulent jet, both of which require robust numerical treatment to handle boundary conditions and resolve small-scale flow features. Dirichlet boundary conditions are enforced at solid walls, and the implementation adopts the incompressible regularized boundary condition (IRBC), which reduces the number of constraints on the second-order moments, thereby improving the stability and efficiency of the simulations. Additionally, we incorporated a high-order regularization technique and enforced a zero-trace condition on the momentum flux tensor to further enhance numerical stability and accuracy. Numerical experiments were conducted for Reynolds numbers of 10,000, 15,000, 25,000, and 50,000, employing mesh sizes up to 256 lattice nodes per dimension, ensuring a comprehensive assessment of the performance of the method under different flow conditions. The results were evaluated based on root mean square (RMS) and mean velocity profiles across different mesh sizes and Reynolds numbers. The findings were validated with results from the literature and showed good agreement.
Abstract
We employ the lattice Boltzmann method (LBM) to perform flow simulations with the objective of evaluating the performance of the D3Q27 stencil in capturing complex flow structures. [...]
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Impact of outlet boundary condition schemes for the lattice Boltzmann method regarding the Stefan phase-change problem
I. T. Martins, L. C. Gómez, P. F. Alvariño

Particles 2025.

Abstract
In several industrial applications, there are systems that depend on multiphase flows. Consequently, modelling these processes are very attractive for the scientific community. Having a mesoscopic nature, the lattice Boltzmann method (LBM) presents advantages to deal with complex geometries and complex processes, such as bubble merging, fluid-structure interaction, etc. Several LBM models for multiphase flows were developed by the research community. Usually, in the applications of multiphase flows, there are open boundaries where the fluid with more than one phase leaves the domain. However, there are few works in the literature regarding the impact of the BC schemes with the Allen-Cahn-based phase-field LBM, especially considering liquid-gas phase change. Then, in this work, we explore the impact of three schemes of open BC: the equilibrium scheme, the extrapolation scheme, and the convective BC scheme. First, the impact of the BC schemes on a channel flow with a bubble inside is studied. Next, the Stefan problem considering real properties (saturated HFE7100) is simulated. The results showed that both the extrapolation and equilibrium schemes can introduce instabilities and incoherences in the results, while the convective BC is the one that better conserves the coherence of the results.
Abstract
In several industrial applications, there are systems that depend on multiphase flows. Consequently, modelling these processes are very attractive for the scientific community. [...]
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Numerical Calculation Model for MR Fluid Behavior in Magnetic Field
S. Tsujimoto, T. Kikugawa, K. Hirata, F. Miyasaka, S. Kamada, Y. Hanajima, S. Taniguchi, P. Ramadhan, N. Kaito

Particles 2025.

Abstract
Recently, Magnetorheological (MR) fluids have been attracting attention as a type of functional fluid. MR fluids have the property that the ferromagnetic particles form chain-like clusters and change their viscosity significantly in response to the applied magnetic field strength. MR fluids are expected to be applied to vibration control systems such as dampers, clutches, brakes and so on because of their ability to change viscosity electrically, reversibly, and continuously on the order of milliseconds. However, the mechanism is complex, and experimental approaches are the most common, requiring a large number of experiments on actual equipment. Therefore, it is expected to analyze the behavior of magnetic particles inside the fluids by numerical simulation and clarify their dynamic characteristics for determining the optimal parameters for application to actual equipment. In this study, we propose a numerical analysis method that couples the particle method and the magnetic moment method, focusing on the change in shear stress due to the magnetic field in MR fluids. Also, we evaluate the effects of magnetic particle density and external magnetic field strength on the cluster formation speed and particle behavior.
Abstract
Recently, Magnetorheological (MR) fluids have been attracting attention as a type of functional fluid. MR fluids have the property that the ferromagnetic particles form chain-like [...]
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Computational analysis of carbon-neutral biofuels co-firing in a rotary kiln
S. Saberi, C. Spijker, M. Gruber, I. Kofler

Particles 2025.

Abstract
This study presents a computational fluid dynamics (CFD) analysis of biomass co-firing in an industrial rotary kiln as a pathway toward reducing fossil fuel dependency and supporting decarbonization strategies. A three-dimensional multiphase model was developed in ANSYS Fluent, where biomass was represented as multi-component particles undergoing sequential processes of drying, pyrolysis, and char oxidation. Two operating scenarios were evaluated: (i) a baseline case with natural gas as the sole fuel, and (ii) a co-firing case in which 10% of the thermal input was provided by carbon-neutral biofuels. The results highlight the influence of biomass addition on the thermal field and particle behavior. While a slight reduction in peak flame temperature was observed after biomass injection, the overall temperature distribution and bed heating profiles remained stable and adequate for process requirements. Particle-scale analysis confirmed complete thermal conversion, with moisture release, volatile consumption, and char oxidation leading to full burnout within the residence time. These findings demonstrate the technical feasibility of partial biomass substitution in rotary kilns and emphasize the value of CFD modeling as a predictive tool for evaluating combustion stability, particle conversion, and process efficiency in high-temperature industrial systems.
Abstract
This study presents a computational fluid dynamics (CFD) analysis of biomass co-firing in an industrial rotary kiln as a pathway toward reducing fossil fuel dependency and [...]
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Smoothed-Particle Hydrodynamics Post-Processing & Visualization Using ParaView: a Survey
L. Gombert, F. Mazen, G. Gisbert, J. Favre

Particles 2025.

Abstract
Smoothed-particle hydrodynamics (SPH) simulation is a mesh-free method to simulate solid mechanics or fluid flows by approximating their volume with a set of particles and computation kernels. Hence the output of these simulations is usually a large set of points with associated values such as velocity or pressure. Due to the mesh-free nature of this method, their post-processing and visualization raise challenges to reconstruct the actual volume and extract significant features like interface surface or critical values. This paper surveys the current and future post-processing methods of SPH simulations using ParaView [1], a reference tool to visualize and explore scientific data at scale. To visualize the millions of particles that SPH simulations can produce, ParaView can discretize particles and their density function over a regular grid, a surface or a line using a point interpolator. This enables using classic visualization techniques such as iso-contours or slicing. We also discuss other indirect rendering methods that can be used in ParaView, such as surface extraction and convex hulls, and introduce GPU representation methods [2], for direct and efficient rendering of particles over time, using gaussian points, volume rendering and ray tracing [3]. Finally, this paper provides an overview of particle rendering methods not yet available in Paraview, such as volume rendering using SPH kernels and data parallel processing algorithms on the GPU, for in situ rendering of large-scale SPH simulations.
Abstract
Smoothed-particle hydrodynamics (SPH) simulation is a mesh-free method to simulate solid mechanics or fluid flows by approximating their volume with a set of particles and [...]
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Methods 3D DEM investigation into the liquefaction characteristics of highly crushable pumice sand
S. Bahmani, R. Orense, Z. Bakhshsipour, I. Bahri

Particles 2025.

Abstract
Pumice sand particles present engineering challenges due to their tendency to crush and compress. Although laboratory and field tests can assess their behaviour, these methods are often time-consuming and costly. This study investigates the liquefaction behaviour of crushable pumice sand using the Discrete Element Method (DEM). In the model, each pumice particle is represented as a sphere that fractures into 14 smaller spheres when a critical contact force is exceeded. Initially, single particle crushing tests are conducted to determine breakage characteristics based on particle size. Subsequently, using the open-source code YADE, three-dimensional loose specimens are prepared and isotopically consolidated under specified confining pressures. These numerical specimens undergo cyclic loading under undrained conditions. The findings indicate that the DEM model successfully replicates experimental results, providing insights into how particle crushing influences cyclic deviator strain. Microscale observations also shed light on the development of force chains within the specimens, enhancing the understanding of pumice sand behaviour during cyclic loading.
Abstract
Pumice sand particles present engineering challenges due to their tendency to crush and compress. Although laboratory and field tests can assess their behaviour, these methods [...]
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Adaptive Time Step and Solver for Discrete Element Method - Beam Bond Model
R. Varga, M. Čermák

Particles 2025.

Abstract
This contribution introduces an adaptive strategy for time-stepping and solver selection in simulations based on the Discrete Element Method with beam bond models (DEMBBM). In this approach, particles are connected by virtual beams capable of transmitting axial, shear, and bending forces, enabling the simulation of both discrete and continuum mechanical behaviour. Such capabilities are particularly relevant in crack propagation problems, where an initially continuous structure is progressively disrupted by fracture. While DEM is traditionally solved using explicit or semi-implicit integration schemes, certain classes of DEM-BBM problems, such as those involving progressive fracture, can benefit from implicit methods. These allow for longer time steps without compromising numerical stability. However, the time step size can affect the accuracy of the solution, particularly under rapidly changing conditions. For this reason, it must be continuously adapted based on the current state of the system, with respect to velocities, stress distribution, and oscillatory response. Depending on the state of the system, different solver types can be employed. When the system remains stable and the time step is constant, direct solvers offer high efficiency. In contrast, when frequent structural changes occur, such as during fracture development, iterative solvers are more suitable. The proposed strategy enables dynamic transitions between solver types and time-stepping adaptions, which improves robustness and computational performance.
Abstract
This contribution introduces an adaptive strategy for time-stepping and solver selection in simulations based on the Discrete Element Method with beam bond models (DEMBBM). In [...]
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Simulating Turbulent Flows With Synthetic Inflow Turbulence Using Smoothed Particle Hydrodynamics
M. Goebel, N. Buerkle, G. Chaussonnet, R. Koch, H. Bauer

Particles 2025.

Abstract
In this work, two algorithms for synthetic turbulent inflow generation are implemented within a modern transport-velocity SPH framework. Both methods are tested using three-dimensional simulations of convected isotropic turbulence with prescribed turbulence characteristics, including length scale, time scale and fluctuation intensity. The capability to model anisotropic turbulence is further assessed by simulating turbulent flow in a circular pipe. Near the turbulent inlet, a high agreement with the prescribed statistics is achieved. Coherent structures are successfully formed and exhibit realistic downstream evolution, demonstrating promising potential for future applications to more complex scenarios, such as shear-driven liquid atomization.
Abstract
In this work, two algorithms for synthetic turbulent inflow generation are implemented within a modern transport-velocity SPH framework. Both methods are tested using three-dimensional [...]
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A Comparative Study of a Conventional and Modern Transport-Velocity SPH Scheme in a Reactive Mass Transfer Problem
K. Muthukumar, C. Ates, N. Bürkle, M. Wicker, R. Koch, H. Bauer

Particles 2025.

Abstract
The advection-diffusion equation is fundamental to modeling mass transfer in various engineering applications, including solute transport in catalytic reactors, pollutant dispersion in environmental flows, and drug delivery in biological tissues. These problems often span a wide range of transport regimes, making accurate and robust numerical solutions essential for predictive modeling and design. In this work, we investigate two Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) approaches, a conventional SPH and a modern SPH with transport velocity, for modeling mass transport in a Laminar Flow Reactor (LFR), which includes advection, diffusion, and reaction effects. The study examines three Peclet numbers (Pe = 10, 1000, and 100,000), corresponding to diffusion-influenced, mixed, and advection-dominated transport regimes, respectively. Numerical results are benchmarked against COMSOL Multiphysics®. The modern SPH method demonstrates improved performance over the conventional SPH in low to moderate Peclet regimes, exhibiting reduced particle disorder, enhanced stability, and more accurate diffusion resolution. At high Peclet numbers, both approaches yield comparable results, though the modern SPH shows improved convergence and outlet concentration predictions. These findings highlight the potential of the implemented modern SPH approach for improved modeling of mass transfer in chemical reactors, particularly in diffusion-sensitive applications.
Abstract
The advection-diffusion equation is fundamental to modeling mass transfer in various engineering applications, including solute transport in catalytic reactors, pollutant [...]
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Power Distribution of various Rotor Configurations in a Vertical Stirred Mill determined with DEM
M. Denzel, F. Wang, A. Boylston, R. Soutar-Dawson

Particles 2025.

Abstract
Vertical stirred milling is a well-recognized technology for fine grinding applications in the mineral processing industry. It is increasingly used due to the higher energy efficiency compared to horizontal mills. Vertical arrangement leads to high grinding intensity and power draw in the bottom grinding chambers, thus bottom rotors may wear out more than upper rotors. Modelling power draw is of great interest proven by the effort in previous work. An analytical power model for this type of mills based on measurement data was developed by Heath et al. [1] and a particle-based approach was presented by Larsson et al. [2]. In this contribution a DEM model to determine the torque distribution along the shaft for every grinding compartment in a vertical stirred mill with castellated rotors [3] is presented. Different rotor configurations are evaluated, whereby the rotors vary in diameter, alignment and spacing. An optimized configuration with a combination of different rotors could be developed, which leads to a more even power distribution and a significant reduction of load on the bottom rotors. Simulations also reveal particle dynamics, which explain field experience in terms of wear. Furthermore, the influence of grinding media filling level on power draw is investigated. Higher filling levels increase power draw following an exponential trend. This model allows to optimize the rotor configuration along the shaft, which has a strong impact on rotor and liner wear, critically influencing operational costs
Abstract
Vertical stirred milling is a well-recognized technology for fine grinding applications in the mineral processing industry. It is increasingly used due to the higher energy [...]
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Investigations regarding the influence of particle shape on the numerical simulation of air pluviation using the dem method
N. Heim, S. Henke

Particles 2025.

Abstract
Air pluviation or sand raining is a method in geotechnics to create homogenous sand samples [1]. To investigate the behavior of the sand particles during pluviation, DEM (discrete element method) can be used due to its ability to realistically model particle interactions [2] with other sand particles or the pluviation equipment. These interactions are in turn influenced by the material as well as interaction properties and particle scaling. However, particle shape also influences the behavior such that realistically considering real-world particles’ shapes may improve modelling of the pluviation process. To investigate the influence of particle shape on the simulation of air pluviation, three different numerical representations for sand particles will be used: (I) homogenous sand with spherical particles, (II) homogenous sand with uniform non-spherical particle shape, representing the average particle shape, and (III) heterogenous sand with varying particle shapes. The non-spherical particles are created using bonded spheres. For investigation of the pluviation process four partial processes were identified which are most likely to be influenced by particle shape: (I) the outflow out of the sieve, which regulates deposition intensity, (II) interactions with the diffusor sieves, which distribute the sand homogeneously over the sample surface, (III) free falling and the resulting particle interactions as well as (IV) the resulting sample density. For these processes, the impact of particle shape will be determined, including resulting particle velocities, angular velocities as well as the reached sample density. The results will, were applicable, be compared to results of physical experiments for further evaluation and validation.
Abstract
Air pluviation or sand raining is a method in geotechnics to create homogenous sand samples [1]. To investigate the behavior of the sand particles during pluviation, DEM (discrete [...]
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Wave Behavior caused by Ladle Pouring and Plunger Advancing in Aluminum Alloy Die Casting using Particle-Based SPH Method
Y. Seo, F. Itakura, Y. Maeda, A. Hasuno, Y. Mochida

Particles 2025.

Abstract
Casting CAE software determines the operating conditions of ladle pouring and plunger advancing and prevents defects in aluminum alloy die casting. Quick operations of the ladle pouring and plunger advancing lead to disturbance of the molten metal flow and increase the risk of air entrapment. Conversely, if these operations are performed slowly, the temperature of the molten metal drops, and the risk of cold flake formation increases. Furthermore, since an oxide film exists on the surface of molten aluminum alloy and flows differently from water, it is necessary to perform simulations considering the oxide film. In conventional casting CAE simulation, the flow behavior by the plunger advancing is often simulated from a state in which the molten metal is stationary in the sleeve. In this study, we numerically analyze wave behavior caused by ladle pouring and plunger advancing processes. One is the superimposed ones of wave behavior when ladle pouring and plunger advance processes are simulated separately. The other is the wave behavior when simulated as a series of processes. The casting analysis software “COLMINA CAE” by the particle-based SPH method, which is considered the oxide film of molten aluminum alloy, is used to analyze the wave behaviors. Further, they have verified the wave behavior through visualization experiments. Comparing the simulated wave height and velocity, which shows the wave motion generated when the plunger advances from the stationary state of the molten metal in the sleeve is different from the wave motion in a series of processes, suggesting the need for simulation of a series of processes. These trends of wave behavior obtained in the simulation are similar to that of the actual phenomenon. Therefore, the present simulation
Abstract
Casting CAE software determines the operating conditions of ladle pouring and plunger advancing and prevents defects in aluminum alloy die casting. Quick operations of the [...]
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Construction and Orthogonality of Fractional Laguerre Functions via the Caputo Derivative
K. Abuasbeh, M. Awadalla, A. Sharif, M. Balti

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. Online First, 61

Abstract
This paper presents a rigorous framework for generalizing Laguerre polynomials to the fractional domain using the Caputo derivative. We solve the resulting fractional Laguerre differential equation via the power series method, deriving an explicit form for the fractional Laguerre functions. A key contribution is the identification of a novel weight function, wα(x) = x−(2α−1)e−x, which is essential to prove the orthogonality of these functions over the interval [0,∞). Comprehensive numerical validation is provided, confirming the theoretical orthogonality across a wide range of fractional orders α and demonstrating a clean reduction to the classical polynomials when α = 2. An analysis of computational feasibility confirms the practical applicability of these functions for solving fractional differential equations and other applied problems.
Abstract
This paper presents a rigorous framework for generalizing Laguerre polynomials to the fractional domain using the Caputo derivative. We solve the resulting fractional Laguerre [...]
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Entropy of Authority in Dialogue Games
A. Startari

Entropy of Authority in Dialogue Games (2025). https://zenodo.org/records/17342502

Abstract
We introduce Authority Entropy, an index that quantifies the distribution of authority stances within dialogue windows and tests its predictive value for compliance, convergence speed, and equilibrium stability. Using a multilingual lexicon of authority-bearing constructions anchored in the regla compilada as an operational constraint set, we train a strictly causal classifier that maps text to stance probabilities over {low, neutral, high}. Authority Entropy is computed per sliding window, together with its slope and volatility, and related to behavioral endpoints through survival models and doubly robust estimators. The study spans synthetic arenas with controllable payoffs, open multi-party tasks with outcome labels, and consented human–model interactions. Baselines include sentiment, toxicity, politeness, formality, and power taggers. Stress tests apply adversarial edits that alter authority cues while preserving semantics to assess sensitivity of entropy and downstream effects. Primary outcomes are compliance rate, convergence time, payoff stability, and regret, reported with leakage audits, calibration checks, and confidence intervals. Results target a public specification of the index, a causal benchmark and leaderboard, and open tooling to visualize instability regimes over time. The contribution is a portable, language-aware measure that links local authority structure to cooperative dynamics without right context leakage. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book AI Syntactic Power and Legitimacy. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained.
Abstract
We introduce Authority Entropy, an index that quantifies the distribution of authority stances within dialogue windows and tests its predictive value for compliance, convergence [...]
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Classical and Bayesian Inference of Engineering and Disability Data: Using the Kavya Manoharan Power Chris-Jerry Distribution under Hybrid Censoring
A. Ahmadini, A. El-Saeed, E. Almetwally, M. Elgarhy

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. Online First, 60

Abstract
In this article, we study and introduce the Kavya-Manoharan power ChrisJerry distribution (KMPCJD) which is a new generation of the power Chris-Jerry distribution (PCJD) which is suitable for engineering and disability data. The probability density curves of KMPCJD demonstrate that it has practical applications in analyzing engineering and disability data in Saudi Arabia. Researchers have a lot of flexibility when developing statistical models for research on disability issues, since the hazard rate function (HRF) for KMPCJD can exhibit J-shaped, increasing, and decreasing trends. In addition, several significant KMPCJD features are calculated, including moments, reliability metrics, moment-generating function, and order statistics. Using data on engineering and disability difficulties, we estimate the parameters of KMPCJD and use classical and Bayesian techniques to assess their reliability and HRF under hybrid censored schemes. Asymptotic confidence/credible intervals are calculated. The numerical results show that when the sample size n increases while keeping other factors like r and T constant, the estimators for δ and λ show improved performance in terms of reduced Bias, mean square error (MSE), and narrower confidence intervals. Also, the Bayesian method also produces shorter credible intervals (LCCI) compared to the traditional confidence intervals (LACI) from ML and MPS methods, suggesting higher precision. To show the utility of the suggested distribution, it was tested in five datasets related to engineering and disability issues in Saudi Arabia. The KMPCJD performed better in terms of goodness of fit than a number of models, including the Kavya Manoharan Rayleigh inverted Weibull distribution, Kavya Manoharan Burr X distribution, exponentiated generalized power Lindley distribution, Weibull power Lindley distribution, power Lindley distribution, Kavya Manoharan generalized exponential distribution, power XLindley distribution, Kavya Manoharan unit exponentiated half logistic distribution, and PCJD. Due to its superior fit capabilities, the KMPCJD is suggested for data modeling in disciplines including engineering and disability difficulties.OPEN ACCESS Received: 27/08/2025 Accepted: 19/09/2025
Abstract
In this article, we study and introduce the Kavya-Manoharan power ChrisJerry distribution (KMPCJD) which is a new generation of the power Chris-Jerry distribution (PCJD) which [...]
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Total Quality Management and Organizational Performance in Tuguegarao City’s Construction Industry
K. Ballesteros(1), G. Rosario(2), D. Siriban(3), J. Casibang(4*)

JSC Matls. Proj. Mangt. (2025). Vol. 1, (Issue-2, December), 11

Abstract
In 2024, Tuguegarao City recorded its lowest economic growth. Recognizing the construction industry’s vital role in driving development, this study explored the influence of Total Quality Management (TQM) on the organizational performance of local construction companies. Data were collected through a standardized survey administered to 20 respondents. Most participating companies had been in operation for 5 to 10 years and held small to medium-sized Inter-Agency Committee licenses. Findings revealed a strong positive relationship between TQM practices and organizational performance, with Organizational Culture and Top Management Commitment and Leadership emerging as the most influential predictors. Multiple regression analysis showed that TQM practices accounted for 84.50% of the variance in performance. The study concludes that prioritizing these key TQM dimensions is crucial for enhancing performance and proposes a framework to facilitate the effective implementation of TQM in construction companies.
Abstract
In 2024, Tuguegarao City recorded its lowest economic growth. Recognizing the construction industry’s vital role in driving development, this study explored the influence [...]
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Personalized design and reconstruction for the defect bone based on data driving and mechanics modelling
Z. Zhuang

Complas2025.

Abstract
Human periarticular bone defect is a difficult disease in orthopedics. There is challenge issue to recognize anisotropy, heterogeneity of bone tissue structure and graphics by low resolution clinic-CT image. In collaboration with clinical medicine, the data-driven and mechanics modeling technique for bone defect reconstruction is proposed. Data driven micro-CT and clinical-CT images are used to obtain the characteristics of cancellous bone structure and graphics. The experimental technology and numerical method are developed for predicting the mechanics parameters of animal specimen on the multi-axial stress state. The constitutive model of heterogeneous anisotropy of bone tissue is established and the parameters are deduced by Bayesian inference using the data given by numerical simulation and experiment. For designing the robust cancellous prosthesis bone, a kind of spinodal lattice is designed with random, indeterminate, aperiodic, asymmetry, irregular, large space for mechanical and biological function. The digital triplets with physical scanning CT image, virtual equivalent modulus and additive manufacturing lattice design are created to guide the clinical treatment of personalized bone defects. This work has been demonstrated in some clinical applications to the benefit of patients.
Abstract
Human periarticular bone defect is a difficult disease in orthopedics. There is challenge issue to recognize anisotropy, heterogeneity of bone tissue structure and graphics [...]
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Constitutive Laws as Generative Graphs and Trees
W. Sun

Complas2025.

Abstract
This talk explores the various ways high-fidelity constitutive laws for a wide range of solids, such as soil, rock, alloys, and polymer composites, can be represented and how the choice of representations influences the accuracy, robustness, and data/computational efficiency for computer simulations of solids. To represent material models as points, we adopt a model-free approach that enables physical simulations of material behaviors without a smooth constitutive law. In this case, pointwise stress-strain pairs are selected in Gauss points of finite elements to be compatible with the conservation laws. To represent material models as meshes, we introduce a latent diffusion model where previous material models and experimental data are used to guide the reverse generation of models. This mesh-based material model is particularly efficient for non-smooth plasticity, where projection on segments can lead to significantly faster simulations. To represent material models as expression trees, we use the neural additive model in the projected space of strain measures. This technique enables us to search for hyperelasticity in high-dimensional space without sacrificing the expressivity of neural networks. We show that the proposed model may reproduce any polynomial of arbitrary orders and dimensions and thus achieve the universal approximation through the StoneWeierstrass theorem. Through a series of 1D post-hoc symbolic regressions, we obtain symbolic material models that significantly reduce the inference time for hydrocodes [1]. The pros and cons of these techniques for various practical applications will be discussed.
Abstract
This talk explores the various ways high-fidelity constitutive laws for a wide range of solids, such as soil, rock, alloys, and polymer composites, can be represented and [...]
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On the application of the virtual element method for problems with inelastic material behaviour
P. Wriggers

Complas2025.
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Plasticity and the airframe -- aircraft structure from birth to ultimate state
S. Van-der-Veen

Complas2025.

Abstract
From the beginning of metallic airframes in the 1930's until today, it has always been required to have a thorough understanding of the plastic behaviour of aircraft structure. Nowadays, advanced models of plasticity are used along the entire design and development process: they are needed to compute the ultimate state of the structure for certification, and also to simulate the manufacturing of the often complex, double-curved components. Mastery of this chain has helped to create the safest mode of transport humankind has known so far. This talk will recap some of the history that got us to where we are today, to help understand current practice, and it will sketch future needs and possibilities. As in the past, the collaboration between academic research and the aerospace industry will continue to be the key to safety, comfort and sustainability.
Abstract
From the beginning of metallic airframes in the 1930's until today, it has always been required to have a thorough understanding of the plastic behaviour of aircraft structure. [...]
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Surrogate computational homogenization for inelastic composites and room for quantum acceleration strategies
K. Terada

Complas2025.

Abstract
We have recently proposed a class of data-centric methods for computational homogenization (CH) using radial basis function (RBF) interpolation, which substitutes for the microscopic analysis for inelastic composites at small-strain and finite-strain [1,2,3]. This approach, which is referred to as RBF-based surrogate CM, has been applied to elastoplastic composite materials at small strain [1] and finite strain [2], and viscoelastic composite materials [3] to demonstrate the capability in overcoming the difficulty of conventional multiscale analysis methods. However, the computational cost of the process of obtaining the weights of RBFs by solving linear equations with the kernel matrix as coefficients is high, and this approach has been applied only to twodimensional (2D) problems. To address the problem that comes from the sheer volume of data, in this study, various measures can be taken to extend the RBF-based surrogate CH to 3D problems from a practical perspective. For example, a limited number of combinations of the six components of macroscopic strain are randomly selected on the hypersphere to perform numerical material tests to generate a set of macroscopic stresses and macroscopic strain histories. After that, the procedure should be the same as the one we have developed so far. The present study particularly focusses on a partitioned RBF interpolation with the help of decision-tree-based partitioning of the data space. Optimizing the partitioning of the hyperspace, consisting of macrostrain and historydependent variables in the input data, allows for low-cost and efficient RBF interpolation approximation. Several numerical examples are presented to demonstrate the promise and performance of the proposed method. The RBF-based surrogate model thus created can be applied to several engineering problems. For example, its convenience can be used for topology optimization, and we will also briefly discuss its potential for combination with quantum algorithms for nonlinear multiscale analysis.
Abstract
We have recently proposed a class of data-centric methods for computational homogenization (CH) using radial basis function (RBF) interpolation, which substitutes for the [...]
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Advances and structural applications of Isogeometric Analysis
A. Reali

Complas2025.

Abstract
Isogeometric Analysis (IGA) is a successful simulation framework originally proposed by T.J.R. Hughes et al., in 2005, with the aim of bridging Computational Mechanics and Computer Aided Design. In addition to this, thanks to the high-regularity properties of its basis functions, IGA has shown a better accuracy per degree-of-freedom and an enhanced robustness with respect to standard finite elements in many contexts - ranging from solids and structures to fluids, as well as to different kinds of coupled problems – opening also the door for the approximation in primal form of higher-order partial differential equations. After a concise introduction of the basic isogeometric concepts, this lecture aims at presenting some IGA recent advances with a special focus on interesting structural applications in several fields where the characteristics of IGA seem to be of great advantage. In particular, applications that will be discussed include the simulation of fluid-structure interaction in different situations, studies on the effect of mechanicallyinduced stresses on prostate cancer growth, thermo-mechanical simulations of additive manufacturing processes, electro-mechanical simulations for biological tissues, and the use of phase-field modeling of fracture and other problems.
Abstract
Isogeometric Analysis (IGA) is a successful simulation framework originally proposed by T.J.R. Hughes et al., in 2005, with the aim of bridging Computational Mechanics and [...]
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Recent advances in the particle finite element method for fluid-structure interactions and multi-physics problems
J. Ponthot

Complas2025.

Abstract
Particle Finite Element Method (PFEM) is a still rather young discretization method that seeks to merge the advantages of the classical FEM with those of modern particle-based methods, such as SPH. To this end, PFEM is designed as a Lagrangian method that combines computations over one time step using FEM with a fast remeshing algorithm, thereby avoiding mesh distortions consequent to very large deformations, such as those encountered in fluid flow with free surfaces. The method is thus quite flexible and can be applied to both solid and fluid material behavior (see e.g. [1] as a sample of the state of the art). PFEM has proven to be a very versatile method that not only allows tracking free evolving boundaries but also take into account thermo-mechanical coupling and thus tackle more complex multi-physics problems. For instance, thanks to its Lagrangian character and its ability to automatically track evolving free surfaces and interfaces, PFEM allows handling phase change due to solidification, melting and vaporization, as well as capillary and Marangoni effects from surface tension [2]. These physical ingredients are highly valuable for simulating melt pool dynamics, for example, in the context of additive manufacturing. Multiphysics problems can lead to models that are inherently incompatible or highly difficult to combine within the same numerical implementation. In such a case, it is convenient to split the physical models and solve them separately using dedicated software. Although this approach has been used mostly to address fluid-structure interaction problems in PFEM, it has also been used to couple thermo-mechanical models, for example, in the simulation of welding processes. This work gathers recent advances in the PFEM with special attention to the incorporation of multi-physics models and their applications. In addition, numerical examples of the PFEM will illustrate fluid-structure interaction problems including contact between different solid parts and plastic deformation of some components of the system. These advances will be complemented by new remeshing proposals to further improve the PFEM strategy, which aim at reducing numerical artifacts and improving the continuity and smoothness of the free surface on which complex physical phenomena take place.
Abstract
Particle Finite Element Method (PFEM) is a still rather young discretization method that seeks to merge the advantages of the classical FEM with those of modern particle-based [...]
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A coupled Multiscale Model of the Human Cornea Accounting for the Collagenous Microstructure and the Extracellular Matrix
A. Pandolfi

Complas2025.

Abstract
The human cornea is a complex, highly specialized structure necessary for the vision function of the Eye. The cornea, due to its shape and transparency, refracts and transmits the light to the retina. Cornea's mechanical properties, critical for maintaining corneal shape and function under intraocular pressure, arise from the composition of a hydrated proteoglycan-rich extracellular matrix (ECM) reinforced by an intricate network of collagen fibrils organized into lamellae. Despite extensive research, existing biomechanical models often fall short of capturing the coupled interplay between the ECM and collagen reinforcements, especially under physiological and pathological conditions. This work seeks to address this gap by proposing a novel computational model that integrates a continuum representation of the ECM with a discrete collagencrosslinking network. The continuum approach for the ECM is chosen to represent its viscoelastic behavior and interaction with fluid flow, critical for corneal hydration and load transmission. Conversely, the collagen network is modeled as a discrete, anisotropic reinforcement system, capturing the directional stiffness imparted by the collagen fibrils and their crosslinking. The model is developed to account for the influence of enzymatic degradation, age-related changes, and disease processes such as keratoconus, where alterations in the ECM-collagen coupling are known to drive structural instability. The innovation of this approach lies in its multiscale integration, bridging the molecular mechanics of collagen crosslinking with macroscopic corneal behavior. By explicitly linking the continuum matrix with a collagen-reinforced network, the model offers some possibility to deepen our understanding of corneal mechanics. The inclusion of experimentally derived parameters for collagen alignment, crosslink density, and ECM properties, will make the model predictive in the simulation of physiological responses to intraocular pressure and external mechanical perturbations.
Abstract
The human cornea is a complex, highly specialized structure necessary for the vision function of the Eye. The cornea, due to its shape and transparency, refracts and transmits [...]
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Front tracking with a twist: the eXtreme mesh deformation approach (X-MESH)
N. Moës

Complas2025.

Abstract
The arbitrary Eulerian Lagrangian (ALE) formulation is a common approach for tracking fronts in finite element simulations. It is, however, difficult to track fronts over long distances because the mesh quality becomes poor on one side of the front. Moreover, traditional ALE front tracking cannot cope with changes in the front topology. To remedy the above problems (at least the first one), remeshing is required from time to time to maintain correct mesh approximation capability on both sides of the front. This remeshing requires projection of the field and updating of the database in the simulation, which is detrimental to the speed and accuracy. We introduce a new approach in which the set of nodes located on the front evolves over time allowing the front to migrate through the mesh. Topological changes are easily considered. For example, a front can nucleate, propagate and merge with other fronts as it propagates. For the new approach to work properly, we must accept that some elements become very small and possibly of zero measure. This means that the elements can deform in extreme ways, hence the acronym X-MESH. Surprisingly, as we shall show, this situation does not prevent simulations from being carried out. In short, X-MESH simply uses node movements to propagate fronts over long distances, even in the event of topological changes. The mesh topology remains unchanged during simulation. The size and sparsity of the finite element matrices are therefore fixed throughout the simulation, and no field projection is required. As the simulation progresses, nodes arrive and depart from the front. X-MESH's capability will be demonstrated for several important applications in mechanics and physics, such as front tracking in the Stefan phase change model or the simulation of immiscible two-phase flows. The work is funded by a European Research Council (ERC) Synergy Grant whose co-pI is Professor J-F. Remacle also at UCLouvain
Abstract
The arbitrary Eulerian Lagrangian (ALE) formulation is a common approach for tracking fronts in finite element simulations. It is, however, difficult to track fronts over [...]
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Recent developments in detecting and localizing weaknesses in structures for high-fidelity digital twins
R. Lohner

Complas2025.

Abstract
Given that all materials exposed to the environment and/or undergoing loads eventually age and fail, the task of trying to detect and localize weaknesses in structures is common to many fields. Traditionally, manual inspection was the only way of carrying out this task, aided by ultrasound, X-ray, or vibration analysis techniques. The advent of accurate, abundant and cheap sensors, together with detailed, high-fidelity computational models in an environment of digital twins has opened the possibility of enhancing and automating the detection and localization of weaknesses in structures. The procedures proposed here are based on measured forces and displacements/strains, and formulate the determination of material properties (or weaknesses) as an optimization problem for the strength factor. These procedures belong to the more general class of inverse problems where structural properties are sought based on a desired cost functional. The use of adjoint formulations and smoothing of gradients to quickly localize damaged regions makes the problem tractable. Recent developments include: extension to nonlinear materials, incorporation of uncertainty, and transient problems. Several examples show the viability, accuracy and efficiency of the proposed methodology and its potential use for high fidelity digital twins.
Abstract
Given that all materials exposed to the environment and/or undergoing loads eventually age and fail, the task of trying to detect and localize weaknesses in structures is [...]
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AI-accelerated computational multiscale modeling
D. Kochmann

Complas2025.

Abstract
Multiscale modeling is the branch of computational mechanics that has suffered from the limits imposed by computational costs probably the most, owing to computations being performed on more than one scale. Consequently, the use of machine learning (ML) methods to bypass costly lower-scale or scale-bridging simulations has tremendous potential to accelerate multiscale modeling and provide new opportunities for simulating the complex mechanics of materials and structures. We will discuss a few recent applications of ML to the field of computational mechanics, all united by the ambition to accelerate simulations across scales. One example is ML-based surrogate material modeling to bypass expensive material point calculations, e.g., by using Recurrent Neural Operators (RNOs) as surrogates for computationally expensive constitutive laws. This is demonstrated for finite-strain crystal plasticity models for magnesium, which are typically too expensive to be used in a multiscale setting. Similarly, FE2 simulations can be considerably accelerated when replacing the microscale boundary value problem by an efficient ML-based surrogate model [1] – as we will show for multiscale simulations of beam-based metamaterials, accelerated by a Kolmogorov-Arnold (KAN) network. Another example are constitutive artificial neural networks for architected materials, which learn the complex constitutive response as a function of the underlying structural architecture [2] for use as surrogate models in macroscale boundary value problems. Overall, we demonstrate how the integration of the principles of mechanics and thermodynamics with ML tools can result in (sufficiently) accurate and efficient AIaccelerated solutions for computational multiscale modeling. We close by highlighting the potential of such tools also for design optimization, e.g., of architected materials.
Abstract
Multiscale modeling is the branch of computational mechanics that has suffered from the limits imposed by computational costs probably the most, owing to computations being [...]
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Strain ageing phenomena in metallic alloys: Experiments and modelling
S. Forest

Complas2025.

Abstract
Static and dynamic strain ageing phenomena induced by the interaction between dislocations and solute atoms, are ubiquitous in engineering metallic alloys. In Nickel-based superalloys used for turbine disks in jet engines, negative strain rate sensitivity is observed at service tempature and results in the devlopment of Portevin-Le Chatelier bands. A viscoplastic constitutive model will be presented which captures the serrations in tensile notch samples and biaxial tension specimens. Finite element simulations then show the impact of DSA on the burst of turbine disks [1]. Static strain ageing is associated to the formation of L¨uders bands in steel sheets. We illustrate the impact of their propagation on the viscoplastic behaviour of zinc coatings on galvanized steel sheets, by means of crystal plasticity applied to zinc grains
Abstract
Static and dynamic strain ageing phenomena induced by the interaction between dislocations and solute atoms, are ubiquitous in engineering metallic alloys. In Nickel-based [...]
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Variational Phase-Field Modeling of Fracture: Towards Second-Generation Models
L. De Lorenzis

Complas2025.
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Recent advances in the development of reliable neural simulators based on graph architectures
E. Cueto

Complas2025.

Abstract
Of all the contributions that AI is making to computational mechanics, the possibility of developing learned simulators is one of the most interesting. Of course, there is a whole ecosystem of techniques that can be used for this purpose, but the use of geometric deep learning is perhaps one of the most promising. Of particular interest is the so-called graph neural network architecture, since traditional finite element meshes can themselves be considered a graph. Thus, it is very convenient to train such architectures with synthetic data obtained by high-fidelity simulation. As will be seen in our presentation, graph networks (possibly informed by physics) allow a very high degree of generalization, as well as the level of accuracy they provide. In this talk we will show details about the inner workings of such networks, particularly the message passing scheme, and we will see how reliable they are for use in problems involving plasticity.
Abstract
Of all the contributions that AI is making to computational mechanics, the possibility of developing learned simulators is one of the most interesting. Of course, there is [...]
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School Leadership Challenges in Using Media Sites in selected High schools in the Khomas Region
M. Antonio, D. Nkengbeza

Collection of Articles on Social Sciences (2025). 1

Abstract
The ability of media sites to quicken uptake into everyday life is affecting the way people interact as they learn, particularly in schools. Social networking sites provide numerous possibilities for richer online instruction, instant message communication, and education-community interaction but also pose difficult problems for school leaders. The paper was guided by the following research question: What challenges do school leaders face when using media websites in selected high schools in the Khomas Region? It also analyzed how school leaders weigh advantages of media websites against difficulties it presents. Lastly, the paper states that school leaderships need to be able to use media websites effectively in senior schools. Five secondary schools were included in this study. The sample included five principals and ten HODs. Data was collected using semi-structured interviews with the five principals, and ten department heads. Data was analyzed using descriptive content analysis. The main findings indicated the difficulties associated with the use of media websites by the school leaders. School leadership misuse media websites by writing negative comments regarding the issues raised in these websites, and others use abusive language towards others when communicating on the media websites and forward non-academic emails to others. Most of the beneficiaries of information uploaded on media platforms by the school leadership lack technological devices upon which they can access the information and messages uploaded. The study also put forward a series of solutions that specifically that it is imperative the fact that all schools ought to be endowed with the required technological infrastructure, including a WI-FI network connection, improved internet connectivity and sufficient technological devices like laptops. Schools need to establish individual social networking accounts where students, teachers, caregivers, and school leadership can converse, exchange resources, and debate education-related matters. The social networking policies that provide easy guidelines for appropriate use, content sharing, and personal data protection need to be formulated and mandatory to implement. These policies also provide school leadership with how they can utilize more effectively media sites to improve their leadership approaches.
Abstract
The ability of media sites to quicken uptake into everyday life is affecting the way people interact as they learn, particularly in schools. Social networking sites provide [...]
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Citation by Completion: LLM Writing Aids and the Redistribution of Academic Credits
A. Startari

Citation by Completion: LLM Writing Aids and the Redistribution of Academic Credits (2025). https://zenodo.org/records/17287506

Abstract
Large language models increasingly shape how academic citations are produced, suggested, and normalized. This paper examines the redistribution of academic credit produced by autocomplete and citation recommendation systems. While citation metrics traditionally reflect author intent, the syntactic design of LLM suggestion interfaces introduces a new variable: authority-bearing syntax. Through a double-blind experimental design comparing writing sessions with suggestion disabled, neutral suggestion, and authority-framed suggestion, this study quantifies shifts in citation concentration, novelty, and legitimacy phrasing. Results show that completions containing legitimizing structures (“as established by,” “following the seminal work of”) significantly increase concentration and reduce source diversity. The paper defines three measurable deltas, ΔC (concentration), ΔN (novelty), and ΔA (authority syntax), and demonstrates how predictive phrasing can algorithmically reproduce canonical hierarchies. As a corrective, it proposes a Fair Citation Prompt specification and an editorial checklist to detect and mitigate credit capture through syntactic bias. The findings suggest that citation fairness must be treated not only as a bibliometric concern but as a structural property of text generation systems, requiring explicit governance at the level of language form.. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book AI Syntactic Power and Legitimacy. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained.
Abstract
Large language models increasingly shape how academic citations are produced, suggested, and normalized. This paper examines the redistribution of academic credit produced [...]
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Effect of Silt and Clay Contents in Natural Sand on the Compressive and Flexural Strengths of Standard Grade Concrete
J. Alipio(1), S. Anciado(2), K. Matalang(3), E. QUEZON(4*)

JSC Matls. Proj. Mangt. (2025). Vol. 1, (Issue-2, December), 10

Abstract
Natural river sand is often contaminated with varying quantities of silt, clay, and other organic impurities that adversely affect the quality of concrete. This research investigates the effects of silt and clay content on the compressive and flexural strengths of standard grade concrete. Sand samples were purposively collected from three locations, Site A, B, and C, while a control sample with slight impurities was obtained from Site D. Concrete cubes and beams using the same cement, coarse aggregate, and water ratios were tested at 14 and 28 days. The control sample obtained a compressive strength of 24.89 MPa, while the samples with 3, 4, 5, and 6 silt and clay attained 21.63, 17.18, 17.07, and 13.61 MPa, respectively. Flexural strengths follow a similar pattern, with only the control sample satisfying the minimum standard requirements. Results showed that increasing the silt and clay content decreases the compressive and flexural strengths. Hence, proper testing and washing to remove contaminated fine aggregates is strongly recommended prior to use in construction.
Abstract
Natural river sand is often contaminated with varying quantities of silt, clay, and other organic impurities that adversely affect the quality of concrete. This research investigates [...]
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Evaluation of the Mechanical performance of HMA containing PET plastic and CHA as a filler material
N. Tessera(1), E. Quezon(2*), T. Bezabih(3)

JSC Matls. Proj. Mangt. (2025). Vol. 1, (Issue-2, December), 5

Abstract
In road construction, various materials are used in the production of hot mix asphalt (HMA). Among them, bitumen and filler materials play a major role in the mechanical behavior of HMA. Bitumen properties and filler material govern HMA pavement performance. HMA pavements are associated with extremely high-temperature and high-traffic volume conditions, which can cause rutting, fatigue cracking, and permanent deformation. Pavement distress shortens service life and increases maintenance costs. This research focused on enhancing pavement resistance to distress by modifying the properties of bitumen with Polyethylene Terephthalate (PET) plastic and utilizing alternative fillers, such as coffee husk ash (CHA). In this study, two phases were used. The first phase involved collecting samples, and the second phase consisted of three sub-phases. To design a material quality test, the first step was to develop a Marshal mix design and three types of mixtures: a mixture of normal HMA with SD filler, a mixture of normal HMA with CHA filler, and a combination of CHA filler and 3%, 6%, 9%, and 12% PET plastic. Marshal mix was used to analyze the marshal and volumetric properties of HMA pavement. According to the Marshall test, the CHA filler exhibits better performance than the SD filler in HMA mixtures. At 6.8% optimum PET plastic higher stability (15.9KN) and density value (2.268g/cm3) and lower flow (2.96mm), VMA (14.83%), and VFA value (73.01%) as compared with unmodified bitumen of 14.30KN, 3.5mm, 2.256g/cm3, 15.62%, and 75.06% value respectively at 4% air void provided. Therefore, the evaluation showed that the HMA containing a combination of 6.8% PET plastic and 3.2% CHS filler shows better mechanical performance in terms of Marshall stability and the volumetric properties of HMA.
Abstract
In road construction, various materials are used in the production of hot mix asphalt (HMA). Among them, bitumen and filler materials play a major role in the mechanical behavior [...]
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Protocol as Prescription: Governance Gaps in Automated Medical Policy Drafting
A. Startari

Protocol as Prescription: Governance Gaps in Automated Medical Policy Drafting (2025). https://zenodo.org/records/17259810

Abstract
This article examines how health policy texts drafted with large language models can detach legal responsibility from the formal circuit of governance. Treating “protocol” as regla compilada, anchored to a Type 0 production in the Chomsky hierarchy, it specifies a provenance standard that binds each clause of an issued policy to its generating inputs, including prompts, parameters, retrieval sources, reviewers, timestamps, and cryptographic hashes. The method combines version-controlled diffs across scoping, drafting, legal review, and publication with a formal alignment of authority bearing constructions, focusing on deontic stacks, default scopes, agent deletion, and nominalizations. A simulated ministry case demonstrates end to end traceability, producing an exportable evidence bundle that links surviving clauses to their inputs and human approvals. Findings show where machine introduced formulations change duty of care or obscure decision rights, and define mandatory human sign offs when high risk constructions appear. The article delivers three operational artifacts for health agencies, a provenance specification, a responsibility matrix across drafting stages, and an audit checklist calibrated to inspection and courtroom needs. By reattaching authorship and justification to the formal record, the blueprint closes a governance gap in automated policy drafting and states the conditions under which AI assisted procedures remain defensible. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book AI Syntactic Power and Legitimacy. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained.
Abstract
This article examines how health policy texts drafted with large language models can detach legal responsibility from the formal circuit of governance. Treating “protocol” [...]
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Evaluation of the properties of Elevated Short Term Aged Asphalt Binder
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Evaluation of the properties of Elevated Short Term Aged Asphalt Binder (2025). 1

Abstract
The rheological properties of Asphalt binder are dependent on the induced temperature during mixing, hauling and compaction. Different literatures and manuals recommend the short term aging property to be checked for period of 85 minutes but during construction on the site this time will not be attained and there is a probability of increase on this time. The objective of this study is to determine time-dependent aging property of 80/100 penetration grade bitumen. Four specimens of equal weight were extracted from the Penetration grade-80/100 bitumen. The first specimen checked for quality requirements. The other three specimens are aged using Rolling Thin Film Oven for 85, 115, and 145 minutes to simulate the delay during HMA production, hauling, and compaction. Test results indicated as the time of aging increased, penetration and ductility decreased, while, softening point, flash point, and mass loss increased, but a fire point remained constant. Further rheological study using AST and FST test indicate that there is property change on the stiffness and flow property of asphalt binder.
Abstract
The rheological properties of Asphalt binder are dependent on the induced temperature during mixing, hauling and compaction. Different literatures and manuals recommend the [...]
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Indexical Collapse: Reference Disappears, Authority Remains in Predictive Systems
A. Startari

Indexical Collapse: Reference Disappears, Authority Remains in Predictive Systems (2025). https://zenodo.org/records/17226412

Abstract
This article introduces the concept of Indexical Collapse, the disappearance of reference in predictive systems. Indexical such as pronouns, demonstratives, and tenses presuppose a contextual anchor, yet predictive language models reproduce them without connection to reality. The outcome is a collapse of reference that paradoxically produces authority effects in law, medicine, and governance. By analyzing judicial transcripts, medical reports, institutional records, and chatbot interactions generated by AI, the paper proposes a framework for pragmatic auditing of predictive outputs. It establishes thresholds for acceptable referential absence in critical domains, positioning Indexical Collapse as a central category for evaluating the legitimacy of predictive discourse. DOI Primary archive: https://doi.org/10.5281/zenodo.17226412 Secondary archive: https://doi.org/10.6084/m9.figshare.30233950 SSRN: Pending assignment (ETA: Q3 2025)
Abstract
This article introduces the concept of Indexical Collapse, the disappearance of reference in predictive systems. Indexical such as pronouns, demonstratives, and tenses [...]
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Influence of Recycled Polyisobutylene and Ceramic Powder on the Mechanical Performance of Asphalt Binder at High Temperature
S. TEMESGEN(1), E. Quezon(2*), G. Garedew(3), A. Feyissa(4)

JSC Matls. Proj. Mangt. (2025). Vol. 1, (Issue-2, December), 3

Abstract
The application of industrial wastes, particularly polyisobutylene and ceramic powder, to asphalt has not been investigated. Hence, this study was conducted to determine the influence of these waste materials on the physical and rheological properties of bitumen using both conventional and Superpave tests. In this investigation, a polyisobutylene-ceramic powder was used as a modifier for bitumen with a penetration grade of 60/70 at concentrations of 0.0%, 0.7%, 1.4%, and 2.1% by weight. The results indicated that increasing the modifier content led to a significant drop in penetration and a decrease in asphalt ductility. Additionally, the softening point increased as the modifier content also increased. Furthermore, as the modifier concentration increases, the asphalt binder's stiffness increases at high temperatures, while the complex modulus master curve shows a low-frequency response. Similarly, a performance-based asphalt grading system demonstrated that modified bitumen at 0.7% and 1.4% enhanced the PG grades to 64°C and 70°C, respectively. As a result, this represents the increased resistance of modifiers to permanent pavement deformation.
Abstract
The application of industrial wastes, particularly polyisobutylene and ceramic powder, to asphalt has not been investigated. Hence, this study was conducted to determine the [...]
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My AI, My Regime: Authoritarian Personalism in User–AI Governance by Form
A. Startari

My AI, My Regime: Authoritarian Personalism in User–AI Governance by Form (2025). https://zenodo.org/records/17208657

Abstract
This article introduces the concept of authoritarian personalism in user–AI governance by form. It argues that each user can establish a regime of authority over an AI through a self-authored set of rules that operate as a regla compilada, a Type-0 production in the Chomsky hierarchy. In contrast to aggregate alignment frameworks or provider constitutions, this regime functions at the level of linguistic form. The user acts as legislator, while the AI functions as a soberano ejecutable that enforces the compiled rule within platform constraints. The analysis distinguishes mirroring (descriptive reflection) from regime (prescriptive obedience) and identifies surface features that make obedience legible, including directive grammar, defaults, refusal and apology grammar, enumeration bias, evidentials, and style prohibitions. It predicts that user corrections generate path dependence, that rules generalize across tasks, and that retractability is observable when explicit rule citations occur. The risks include rule overreach, collisions with higher-order policies, and unintended spillover across domains. By centering the individual as a primary locus of governance, this framework reorients debates on AI alignment away from provider norms toward personal regimes, verified through linguistic form rather than intent. DOI Primary archive: https://doi.org/10.5281/zenodo.17208657 Secondary archive: https://doi.org/10.6084/m9.figshare.30218590 SSRN: Pending assignment (ETA: Q3 2025)
Abstract
This article introduces the concept of authoritarian personalism in user–AI governance by form. It argues that each user can establish a regime of authority over [...]
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REDISCOVERING THE MULLINS EFFECT WITH PHYSICS AUGMENTED NEURAL NETWORKS
M. Zlatić, M. Čanađija

coupled25.

Abstract
Neural networks (NNs) can be used to describe relationships without explicitly knowing them, but by approximating them through a number of superpositioned functions. In this way, a wider range of unknown behaviours can be modelled with a single approach. In this paper, we present the possibility of incorporating previously assumed relationships, i.e. analytical models, into an NN and then comparing them with a more general NN to model the same relationship without making any prior assumptions. This is demonstrated by modelling the Mullins effect, a simple isotropic damage model for hyperelastic materials where incompressibility is a priori assumed. The data was artificially generated by using the incompressible Ogden model as the underlying hyperelastic behaviour. A framework for modelling simple isotropic damage is shown that provides a high degree of flexibility while accounting for certain physical properties such as objectivity, normalisation of energy and thermodynamic consistency. This work follows other works that incorporate physical constraints in NNs, an approach referred to as Physics Augmented Neural Networks (PANNs). The NN model is only trained on simple deformation modes such as uniaxial, equibiaxial and planar tension and captures the complete 3D behaviour. Several numerical examples in Abaqus are presented to show the accuracy of the model and the simplicity of the numerical implementation in a widely used finite element software.
Abstract
Neural networks (NNs) can be used to describe relationships without explicitly knowing them, but by approximating them through a number of superpositioned functions. In this [...]
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Clinical Syntax: Diagnoses Without Subjects in AI-Powered Medical Notes
A. Startari

Clinical Syntax: Diagnoses Without Subjects in AI-Powered Medical Notes (2025). https://zenodo.org/records/17184301

Abstract
This article examines the structural erasure of the patient as an active subject in clinical records generated by artificial intelligence systems. Automated outputs from Epic Scribe, GPT-4, and institutional medical note generators increasingly rely on impersonal constructions, nominalizations, and fragmented clauses that displace the patient from the syntactic center of medical discourse. The shift toward objectified formulations such as “bilateral opacities noted” rather than “the patient presents with” produces a discourse where agency and responsibility are structurally absent. Building on prior analyses of passive voice and subject deletion, the study introduces the Syntactic Opacity Index (SOI) as a formal measure to quantify the density of non-agentive structures in AI-authored notes. The corpus analysis demonstrates how opacity accumulates at the sentence level, rendering the clinical narrative less transparent and more difficult to attribute. Beyond linguistic critique, the article assesses the ethical and epistemic consequences of syntactic opacity in medicine, particularly regarding accountability, patient-centered care, and institutional responsibility. The findings suggest that AI-powered medical documentation does not merely accelerate administrative workflows but also reconfigures the grammar of care itself, demanding urgent attention to how language structures shape both diagnosis and responsibility. DOI Primary archive: https://doi.org/10.5281/zenodo.17184301 Secondary archive: https://doi.org/10.6084/m9.figshare.30187882 SSRN: Pending assignment (ETA: Q3 2025)
Abstract
This article examines the structural erasure of the patient as an active subject in clinical records generated by artificial intelligence systems. Automated outputs from Epic [...]
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Bike Lane Project Implementation for Sustainable Transportation in Tuguegarao City: A Technical and Economic Perspective
J. Dayrit(1), K. Garo(2), M. Pastores(3), E. QUEZON(4*)

JSC Matls. Proj. Mangt. (2025). Vol. 1, (Issue-2, December), 4

Abstract
The Philippines is perennially confronted with transport problems, with 11.7 million registered vehicles resulting in highly congested, poorly mobile roadways. In line with the Philippine Development Plan, which focuses on creating intermodal terminals and sheltered bike lanes to promote sustainable transportation, this study examines the technical and financial feasibility of implementing bike lanes within Tuguegarao City. Employing a mixed-methods research design, the study assessed current road conditions and traffic flow and collected insights from stakeholders. The qualitative data were collected using structured survey questionnaires, while the quantitative analysis used traffic volume data to calculate the level of service (LOS). The findings show that health and environmental benefits motivate bicycle use, while the lack of dedicated lanes and safe parking spaces discourages its adoption. However, there is high public support for bike lane implementation (mean rating: 4.48). Infrastructure constraints suggest that upgrading should precede construction. LOS results (B and D) confirm the viability of shared roads to improve traffic performance. Economic analysis also showed that the cost of bicycle investments can be recouped in 14 months through transportation benefits. These results indicate a high level of public desire to transition to cycling, provided that facilitating infrastructure and safe, dedicated cycling lanes are in place.
Abstract
The Philippines is perennially confronted with transport problems, with 11.7 million registered vehicles resulting in highly congested, poorly mobile roadways. In line with [...]
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Stability in Composite Bearing Structures within Room-and-Pillar Goafs under Repeated Mining
W. Lv, L. Gao, Y. Wu, P. Xie, C. Lyu, R. You, T. Song, S. Li

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 59

Abstract
During repeated mining of shallow and closely spaced coal seams, the failure of coal pillars within the upper goaf can induce dynamic hazards—such as shield jamming, support collapse, and roof fall—at the lower fully mechanized working face. To assess the stability of composite bearing structures, this study adopts a comprehensive approach that integrates orthogonal experimental design with single-factor experiments, supported by numerical simulation methods. Firstly, a composite bearing structure model is developed based on the engineering conditions of the Xingelao Coal Mine, followed by a comprehensive mechanical analysis. Secondly, experimental variables such as cement content, fly ash content, river sand content, and solid/slurry concentration are considered to systematically analyze their impact on backfill strength through proportion adjustment experiments. Furthermore, the controlled variable method is applied to adjust the backfill ratio, ultimately determining the optimal backfill mix ratio S8-2/3, which demonstrates a 7-day uniaxial compressive strength of 2.70 MPa with a backfill ratio of 2/3. This ratio satisfies both the mine’s strength requirements and cost-effectiveness criteria. Based on this, a failure model for the “backfill-pillar” composite bearing structure is established by integrating stress-strain curves with observed failure modes during load-bearing processes. Finally, numerical simulation software was utilized to perform a stability analysis on both the composite load-bearing structure formed by post-backfilling in the roomand-pillar goaf and the overlying strata of the mined-out area. Numerical simulation results indicate that, under repeated mining conditions, the use of S8-2/3 backfilling material in room-and-pillar goafs significantly enhances the load-bearing capacity of residual coal pillars. It also effectively controls overburden movement and supports the safe and efficient extraction of coal resources.OPEN ACCESS Received: 23/04/2025 Accepted: 16/06/2025 Published: 22/09/2025
Abstract
During repeated mining of shallow and closely spaced coal seams, the failure of coal pillars within the upper goaf can induce dynamic hazards—such as shield jamming, [...]
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A Novel Analytical Framework for Investigating Mittag—Leffler Stability in Fractional Order Reaction—Diffusion Systems
I. Bendib, A. Ouannas, M. Dalah

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 58

Abstract
In this paper, we develop a novel analytical framework to investigate the Mittag-Leffler stability (MLS) of fractional order reaction—diffusion systems (FO-RDs). By employing fractional calculus and Lyapunov function (LF) techniques, we derive sufficient conditions that guarantee the system’s equilibrium point (EP) is reached within a settling time (ST). Our approach provides explicit estimates for the ST, linking the fractional dynamics to practical stability criteria. The theoretical results are rigorously validated through numerical simulations on a glycolysis RD model, which demonstrates rapid convergence of the state trajectories to the unique equilibrium. These findings not only deepen the understanding of the transient behavior in FO-RDs but also pave the way for applications in biomedical engineering, chemical reactor design, and environmental management, where swift stabilization is essential.OPEN ACCESS Received: 30/03/2025 Accepted: 17/06/2025 Published: 22/09/2025
Abstract
In this paper, we develop a novel analytical framework to investigate the Mittag-Leffler stability (MLS) of fractional order reaction—diffusion systems (FO-RDs). By [...]
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Numerical Analysis of Protective Performance of Segmented Excavation Schemes for Metro Tunnels Considering Excavation-Induced Disturbance
D. Lin, R. Lin, S. Zhou, H. Wang, Y. Xiao, J. Bao, L. Fei

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 57

Abstract
This paper presents an integrated laboratory and numerical study on the effects of excavation-induced soil disturbance on the displacement of underlying metro tunnels, as well as the protective performance of different segmented excavation methods. Artificial disturbed soils were prepared by mixing salt grains and different cement contents into remolded Ningbo silty clay. One-dimensional compression tests and triaxial shear tests were then conducted. These tests were used to investigate and compare the engineering properties of undisturbed and artificially disturbed soils. Subsequently, the Hardening Soil Model with Small Strain (HSS) parameters were obtained for soils under varying degrees of disturbance. Considering the deterioration of soil properties due to disturbance and based on the disturbance zoning determined from the unloading influence depth and field measurements, numerical simulations were performed using Plaxis 3D. These simulations analyzed tunnel displacements induced by large-area direct excavation and three segmented excavation schemes. The results indicate that excavation-induced disturbance can significantly increase tunnel vertical displacement. Compared to unmitigated direct excavation, segmented excavation methods (i.e., block jumping excavation, ends to center excavation, and sequential excavation) can reduce the average tunnel displacement by about 28%. Among the three schemes, block jumping excavation offers the best balance between deformation control and efficiency with the highest comprehensive benefit index (11.04%). Ends to center excavation provides optimal deformation control but exhibits relatively low efficiency. In contrast, although sequential excavation effectively reduces displacement, it leads to concentrated deformation and low construction efficiency, making it the least favorable option.OPEN ACCESS Received: 13/04/2025 Accepted: 30/07/2025 Published: 22/09/2025
Abstract
This paper presents an integrated laboratory and numerical study on the effects of excavation-induced soil disturbance on the displacement of underlying metro tunnels, as [...]
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Computational Analysis of Newly Topp-Leone Data Using Adaptive Progressive Type-II Censoring and Its Applications in Medical and Industrial Sciences
H. Mohammed, O. Abo-Kasem, A. Elshahhat

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 56

Abstract
Reliability analysis is critical in various scientific fields, necessitating robust lifetime models that effectively capture real-world failure mechanisms. This work explores a novel extension of the classical ToppLeone (TL) lifespan model, called the generalized-TL (GTL) distribution, when datasets are gathered from adaptive progressive Type-II censoring. This model is highly superior for analyzing complex lifetime data with diverse hazard rate structures, including decreasing, increasing, and bathtub-shaped patterns. Employing both likelihood and Bayes estimation approaches, this work attempts to infer the unknown parameters and the reliability and failure rate functions of the GTL model. The Bayesian inference is created using the squared-error loss and independent gamma assumptions. Asymptotic and credible intervals are also established for each unknown quantity. Since the posterior density is complicated, the Markov chain using the Monte Carlo approach is utilized to get information from the whole marginal posterior densities and thus assess the acquired Bayesian point and interval estimations. Using four optimality criteria, the optimum censoring is given among competing progressive techniques. The effectiveness of the offered estimations is tested against numerous parameters using comprehensive Monte Carlo comparisons. Lastly, the practical utility of the GTL model is demonstrated through two applications using different real-world datasets collected from veterinary medicine and engineering reliability studies. Our findings state that the Bayes’ setup outperforms classical approaches, particularly in smallsample settings, making the proposed methodology flexible and beneficial in concluding the study when the researcher’s foremost concern is the total number of failed items.OPEN ACCESS Received: 29/03/2025 Accepted: 21/05/2025 Accepted: 22/09/2025
Abstract
Reliability analysis is critical in various scientific fields, necessitating robust lifetime models that effectively capture real-world failure mechanisms. This work explores [...]
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Surface Settlement of Small Clear Distance Tunnel in Soft Soil Layer during Shield Propulsion
X. Zhao, S. Wu, F. Jiang, S. Chen

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 55

Abstract
Shield tunneling has become a widely adopted method for urban underground transport construction. However, research on the impact of small-clearance shield tunnel construction in urban soft soil layers is still in its early stages. Understanding the effects of such construction on surface settlement and summarizing temporal settlement patterns is crucial for reducing construction risks and minimizing disturbances to the surrounding areas. This paper investigates the impact of two-lane small-clearance tunneling on surface settlement through finite element modeling and analysis, focusing on the Nanjing Heyan Road Crossing as a case study. The study also evaluates the feasibility of different construction distances in successive two-lane shield tunneling. Numerical simulations and on-site measurements were conducted to explore the surface settlement behavior under varying construction distances. The research examines the vertical and lateral settlement characteristics in the backfilled area, located 32 m from the tunnel initiation well. The findings reveal the settlement behavior throughout the shield tunneling process under different construction distances. The results indicate that the vertical settlement profiles of shield tunnel construction in soft soil layers conform to the Mindlin settlement curve, while the lateral settlement profiles follow the double-funnel Peck curves. Additionally, the closer the construction distance between the two tunnels, the greater the disturbance to the ground surface, whereas increasing the construction distance results in higher peak surface settlement. Soil settlement around the tunnel is significantly affected by construction disturbances, structural stiffness, lateral unloading bias, the extrusion effect of tube sheet weight, and shield machine movement. The use of synchronous grouting effectively mitigates excessive surface settlement. This study provides valuable insights and serves as a reference for similar shield tunnel construction projects in urban soft soil layers.OPEN ACCESS Received: 18/03/2025 Accepted: 16/05/2025 Published: 22/09/2025
Abstract
Shield tunneling has become a widely adopted method for urban underground transport construction. However, research on the impact of small-clearance shield tunnel construction [...]
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Statistical Analysis of Progressive Interval Type-I Partially Accelerated Test and Its Inspection of Optimum Periods
R. Alotaibi, C. Park, H. Rezk, A. Elshahhat

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 54

Abstract
This study explores a general framework for reliability analysis named progressive interval Type-I censoring within a multi-stage step-stress partially accelerated life testing setting. A more flexible alternative to the traditional exponential model, known as the length-biased exponential (LBE) distribution, is employed to model failure times. Due to its symmetrical feature, it has extensive applications in real-world domains such as survival analysis, actuarial science, reliability, and mathematical finance. The maximum likelihood approach of estimation is utilized to estimate the model parameters, along with bootstrapping techniques to assess estimation efficiency. Confidence intervals for the LBE parameters are also derived based on asymptotic variances. To optimize the inspection period, two competing optimality criteria—variance minimization (Varoptimality) and determinant maximization (D-optimality)—are investigated. A comprehensive Monte Carlo simulation study is conducted to evaluate the performance of different estimation strategies, demonstrating the superiority of the proposed methodology. Steel is particularly valued for its toughness, wear resistance, and hardness, all of which can be significantly modified through heat treatment and annealing processes. So, a real-world application using hardened steel failure data validates the practical relevance of the developed inferential framework. The findings offer valuable insights for statisticians and reliability engineers in designing efficient life-testing experiments under constrained resources.OPEN ACCESS Received: 21/03/2025 Accepted: 07/05/2025 Published: 22/09/2025
Abstract
This study explores a general framework for reliability analysis named progressive interval Type-I censoring within a multi-stage step-stress partially accelerated life testing [...]
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Numerical Simulation Analysis on the Stress and Strain Behavior of Composite Geomembrane in Rigid Landfill
M. Huang, T. Tu, Y. Jiang, F. Yang

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 53

Abstract
In order to investigate the stress characteristics of a composite geomembrane during the operation of a rigid landfill, a three-dimensional finite element model was developed for a specific rigid landfill project in Tongling China. This model takes into account the contact behavior between the composite geomembrane and concrete unit pool. It aims to calculate and analyze the distribution of stress and strain in both the composite geomembrane and rigid landfill under various working conditions, including empty and full storage. At the same time, the influence of the change of friction coefficient between the composite geomembrane and the concrete cell pool on the stress and strain of the geomembrane is analyzed under the condition of full reservoir. The results indicate that the stress and displacement distribution of the composite geomembrane and concrete structures in the landfill site remain reasonable and safe before and after transitioning from empty to full storage. Under critical conditions, specifically when the cell pool is fully loaded, significant tensile stress and strain occur at the top anchorage of the pool, the edge of the pool bottom, and the corners of the cell pool. The tensile stress in the concrete structure is notably higher at the junction between the side walls and the bottom floor of the cell pool, while compressive stress is more pronounced at the connection between the frame columns of the lower maintenance layer and the bottom floor of the cell pool. Increasing the friction between the composite geomembrane and the concrete cell pool can effectively mitigate stress concentration in the composite geomembrane, thereby enhancing the structural stability and safety.OPEN ACCESS Received: 14/03/2025 Accepted: 21/05/2025 Published: 22/09/2025
Abstract
In order to investigate the stress characteristics of a composite geomembrane during the operation of a rigid landfill, a three-dimensional finite element model was developed [...]
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Existence and Uniqueness Results for a Class of Backward Neutral Fractional Differential Equations
S. Abusalim

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 52

Abstract
In this work, we investigate the existence and uniqueness results (EUR) for a class of neutral fractional differential equations (FDEs) with time advance, incorporating the Caputo derivative concerning. By employing the fixed-point theory, we establish rigorous criteria ensuring the wellposedness of the problem. Additionally, we explore the Ulam-Hyers stability properties of the proposed model, providing a comprehensive analysis of its dynamic behavior. To further support our theoretical findings, we present two examples that illustrate the applicability and effectiveness of the obtained results. These findings contribute to the growing body of research on FDEs and their applications in various scientific and engineering fields.OPEN ACCESS Received: 24/03/2025 Accepted: 29/05/2025 Published: 22/09/2025
Abstract
In this work, we investigate the existence and uniqueness results (EUR) for a class of neutral fractional differential equations (FDEs) with time advance, incorporating the [...]
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Neural Network Model Predictive Control Applied to Parafoil under Turbulence Wind Field
J. Li, H. Sun, Q. Sun

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 51

Abstract
In the field of parafoil flight control, a critical challenge is managing the complex control requirements and mitigating the effects of turbulenceinduced disturbances. This paper explores the intricacies of parafoil control and the influence of the turbulent wind field on system performance. To address the challenges, we propose a Neural Network Model Predictive Control (NNMPC) strategy that utilizes extensive historical operational data, including flight attitude records from multiple flights and control responses under various wind conditions, to develop a neural network model as an alternative to traditional 3-degree-of-freedom (3DOF) models. The proposed approach integrates a NARX (Nonlinear AutoRegressive with Exogenous inputs) neural network into the Model Predictive Control(MPC) framework, leveraging its temporal modeling capabilities to improve prediction accuracy and enhance disturbance rejection. Experimental validation was performed in a simulated turbulence environment using the Dryden turbulence model, with carefully designed control groups in which both traditional MPC and NNMPC were tested under identical initial conditions and target trajectories. The results demonstrate that NNMPC achieves superior trajectory tracking performance, indicating its potential for robust parafoil control in complex atmospheric conditions.OPEN ACCESS Received: 06/03/2025 Accepted: 06/05/2025 Published: 22/09/2025
Abstract
In the field of parafoil flight control, a critical challenge is managing the complex control requirements and mitigating the effects of turbulenceinduced disturbances. This [...]
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Computational Investigation of Novel Half-Normal Data Using Improved Type-II Adaptive Progressive Censoring and Its Application to the Shasta Reservoir
O. Alqasem, M. Nassar, M. Elwahab, A. Elshahhat

Rev. int. métodos numér. cálc. diseño ing. (2025). Vol. 41, (3), 50

Abstract
Shasta Reservoir is the largest in California, formed by Shasta Dam on the Sacramento River, and plays a major role in the Central Valley Project (CVP) by providing water storage, flood control, hydroelectric power, and irrigation. This study employs advanced statistical methods to evaluate the reservoir’s reliability and operational risks using censored hydrological data. We propose an improved adaptive progressive censoring plan and apply established statistical techniques, maximum likelihood and maximum product of spacings, alongside Bayesian estimation. The Bayes estimates are obtained through the squared error loss function and based on two sources for the observed data, namely the likelihood and spacing functions. The focus is on estimating the distribution’s scale parameter and two critical reliability metrics: the reliability function and the hazard rate function. The approximate confidence intervals based on the two classical approaches of the scale parameter and reliability metrics are studied. The highest posterior density credible intervals are also discussed. A simulation study evaluates the model’s accuracy under diverse data scenarios, and its practical utility is demonstrated through real-world data from Shasta Reservoir. The problem of optimizing data collection strategies is discussed with the same real data. The findings underscore the model’s value in enhancing reservoir reliability assessments, offering actionable insights for hydrology, disaster preparedness, and sustainable resource management.OPEN ACCESS Received: 15/03/2025 Accepted: 12/06/2025 Published: 22/09/2025
Abstract
Shasta Reservoir is the largest in California, formed by Shasta Dam on the Sacramento River, and plays a major role in the Central Valley Project (CVP) by providing water [...]
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AI Syntactic Power and Legitimacy: How AI Structures Shape Authority
A. Startari

(2025). https://zenodo.org/records/17154108

Abstract
AI Syntactic Power and Legitimacy: How AI Structures Shape Authority This book consolidates a cycle of research on the structural foundations of authority in artificial intelligence. It brings together a series of peer-reviewed articles that demonstrate how power in AI systems no longer depends on meaning, interpretation, or intention, but on syntactic sufficiency. The argument develops in fourteen chapters, beginning with the autonomy of sense beyond reference and culminating in the colonization of temporality by predictive infrastructures. Along the way, it formalizes a set of theoretical contributions: the regla compilada as a Type 0 grammar of executable authority, the figure of the soberano ejecutable as operator of legitimacy without subject, the theorem of Disconnected Syntactic Authority (DSAT), the theorem of the Limit of Conditional Obedience (TLOC), the δ [E] → ∅ rule of ethical trace deletion, and the formalization of compiled norms as computable legal speech. The book demonstrates that: Authority migrates from agents to structures, producing the sujeto evanescente. Ethical, interpretative, and referential markers can be structurally erased without breaking execution. Legal norms can be transformed into executable grammars with cross-linguistic validity. Predictive infrastructures colonize time, replacing futurity with executable closure. AI Syntactic Power and Legitimacy marks the closure of a first syntactic phase of research, while opening the way to further studies on structural delegation, institutional obedience, and computable legality. Author: Agustin V. Startari, linguistic theorist and researcher in historical studies (UdelaR and University of Palermo). Publisher: LEFORTUNE ISBN: 9798266066687 DOI: https://doi.org/10.5281/zenodo.17154108 and https://doi.org/10.6084/m9.figshare.30158239
Abstract
AI Syntactic Power and Legitimacy: How AI Structures Shape Authority This book consolidates a cycle of research on the structural foundations of authority in artificial [...]
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Total Quality Management and Organizational Performance in Tuguegarao City’s Construction Industry
J. CASIBANG

JOHN MICHAEL B. CASIBANG's personal collection (2025). 1

Abstract
In the year 2024, Tuguegarao City receives its lowest economic growth over the past years. Considering the contribution of construction industry in the economic growth, the researchers underscore the philosophy on the dynamic improvement, the Total Quality Management. The study examined the relationship between Total Quality Management practices and organizational performance in construction companies in Tuguegarao City, Cagayan. A standardized survey questionnaire was used to gather data from 20 respondents. The results showed that most companies had 5-10 years of experience and held small or medium Inter-Agency Committee licenses. The study found a strong positive relationship between TQM dimensions and organizational performance, with Organizational Culture and Top Management Commitment and Leadership being the most influential predictors. A multiple regression analysis confirmed that 84.50% of performance variance could be explained by TQM practices.The study concludes that strategic OC and TMCL focus is crucial for improving organizational performance and recommends a framework for effective TQM implementation in construction companies.
Abstract
In the year 2024, Tuguegarao City receives its lowest economic growth over the past years. Considering the contribution of construction industry in the economic growth, the [...]
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Designing Accountability: Ethical Frameworks for Reintroducing Responsibility in Executable Governance
A. Startari

Designing Accountability: Ethical Frameworks for Reintroducing Responsibility in Executable Governance (2025). https://zenodo.org/records/17106808

Abstract
This article develops an ethical legal framework for reintroducing responsibility into executable governance. Predictive systems, by generating authority without agents, displace accountability and leave institutions without appeal mechanisms. Building on the concepts of spectral sovereignty, null subjects, and the codex of authority, the paper introduces the notion of accountability injection as a design principle. It formulates a three tier model: (1) human, where non delegable critical decisions are tied to named subjects; (2) hybrid, where human judgment co exists with model output under calibrated thresholds; and (3) syntactic supervised, where delegation is permitted only with immutable ledgers, traceability, and automatic escalation triggers. Through applied case studies in EU AI Act conformity assessment, DAO governance, predictive credit scoring, and automated medical audits, the framework demonstrates how appeal and responsibility can be restored without undermining institutional efficiency. The conclusion argues that accountability must be compiled directly into the regla compilada of governance systems, creating a normative blueprint for legislators, courts, and regulators to maintain responsibility in predictive societies. DOI Primary archive: https://doi.org/10.5281/zenodo.17106808 Secondary archive: https://doi.org/10.6084/m9.figshare.30112711 SSRN: Pending assignment (ETA: Q3 2025)
Abstract
This article develops an ethical legal framework for reintroducing responsibility into executable governance. Predictive systems, by generating authority without agents, displace [...]
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Exploring the Socio-Economic impacts of various extension services on Public Infrastructures: A Qualitative Assessment
C. Macabangon, R. Estiller(2*), J. Casibang(3), A. Gonzales(4), O. Doctolero(5)

JSC Matls. Proj. Mangt. (2025). Vol. 1, (Issue-2, December), 2

Abstract
This study assesses the socio-economic impact of the extension projects conducted by the Civil Engineering Department as part of the "Integrated Engineering Services for Sustainable Agro-Industrial and Infrastructure Development" program from 2016 to 2020. Using a qualitative, multiple-case design, the research focused on facility assessments at two public schools, the construction of a vermicompost facility, and a rainwater harvesting system at a public gymnasium. Key findings demonstrate that the department's technical assistance led to measurable improvements in school infrastructure and safety, resulting in tangible cost savings for the beneficiaries. The findings were used to guide school development plans and secure project funding from the Department of Education. While the rainwater harvesting facility proved beneficial for daily operations, a critical gap in capacity and power resilience was identified for use during large-scale calamities. This study validates the strategic value of targeted university extension services and provides a model for future program enhancement and policy-making.
Abstract
This study assesses the socio-economic impact of the extension projects conducted by the Civil Engineering Department as part of the "Integrated Engineering Services [...]
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ECOFERTILIZANTES LA SALLE: CULTIVANDO CONCIENCIA AMBIENTAL
J. Pineda Palencia

Juan Emilio Pineda Palencia's personal collection (2025). 1

Abstract
Composting is an ancestral technique for managing organic waste. Recent studies show that incorporating ''Trichoderma'' spp., especially ''T. harzianum'' and ''T. viride'', significantly accelerates the decomposition of organic residues thanks to enzymes capable of degrading cellulose, chitin, and glucans. This improves the quality and nutritional value of the final compost, optimizing soil fertility and nutrient availability for crops. Therefore, implementing ''Trichoderma'' as a microbial bioactivator in compost represents a sustainable agroecological solution that strengthens soil fertility and reduces reliance on chemical fertilizers. In many rural and periurban areas, organic waste is poorly managed and there is excessive dependence on synthetic fertilizers, which degrade soil health. Inoculating compost with ''Trichoderma'' enhances compost quality—by increasing its nutritional content and biological activity—and provides biological control of pathogens, contributing to healthier and more sustainable agriculture. Composting with effective microorganisms (EM) is based on introducing beneficial microbial communities such as lactic acid bacteria, yeasts, and actinomycetes that rapidly decompose organic waste. According to Higa and Parr (1994), EM improve soil structure, increase nutrient availability, and suppress pathogenic organisms. In an agroecological approach, microbially enriched compost contributes to regenerative and resilient agricultural systems. Mycorrhizae are symbiotic associations between fungi and plant roots. These associations enhance nutrient uptake—especially phosphorus—and increase plant resistance to soil pathogens. Additionally, mycorrhizae contribute to soil structural stability and microbial biodiversity. Including them in composting can enrich soil microbiota and promote a healthier, more productive environment for plants.
Abstract
Composting is an ancestral technique for managing organic waste. Recent studies show that incorporating ''Trichoderma'' spp., especially ''T. harzianum'' [...]
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Endovascular Therapy Versus Surgical Clipping for Intracranial Aneurysms: A Systematic Review and Meta-Analysis
C. Vanegas-Mondragon, O. Tellez-Tellez

Collection of Articles on Medicine (2025). 10

Abstract
Intracranial aneurysms are a leading cause of subarachnoid hemorrhage (SAH), associated with high morbidity and mortality. Traditionally, microsurgical clipping was the gold standard, but endovascular coiling has emerged as a less invasive alternative. This review synthesizes current evidence comparing endovascular and surgical approaches. A systematic search was conducted across PubMed, Scopus, and the Cochrane Library, including randomized controlled trials (RCTs) and cohort studies published between 2000 and 2025. Outcomes assessed were mortality, functional independence, perioperative complications, recurrence, and retreatment rates. Twenty-seven studies encompassing 18,560 patients were analyzed. Endovascular therapy demonstrated reduced short-term mortality and higher rates of functional independence, particularly in elderly patients and those with posterior circulation aneurysms. Conversely, surgical clipping ensured greater long-term durability with fewer retreatments, especially among younger patients. Both techniques carry unique benefits and limitations; thus, treatment should be individualized, taking into account aneurysm morphology, patient age, comorbidities, and surgical risk. Risk of bias assessment was performed using Cochrane RoB2 for RCTs and the Newcastle-Ottawa Scale for observational studies, with most studies showing moderate risk. This review highlights the importance of a multidisciplinary, patient-centered approach, while emphasizing the need for future long-term RCTs and device innovations. In conclusion, endovascular therapy provides superior early safety, while surgical clipping ensures durable occlusion; an evidence-based, personalized strategy remains essential to optimize patient outcomes.
Abstract
Intracranial aneurysms are a leading cause of subarachnoid hemorrhage (SAH), associated with high morbidity and mortality. Traditionally, microsurgical clipping was the gold [...]
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Pol.lució i restriccions a la mobilitat a Catalunya: Un experiment natural basat en la COVID-19
M. Garcia López, G. Congrés2025

4rceec (2025). 222

Abstract
Aquest treball investiga l’impacte que té la mobilitat sobre la pol.lució als municipis de Catalunya. Per fer-ho, fem ús de l’experiment natural que representa la pandèmia de la COVID-19 per avaluar fins a quin punt es poden reduir els nivells de pol.lució quan s’estableixen restriccions a la mobilitat i la tecnologia no canvia. Gràcies a l’ús de dades amb un elevat detall temporal, analitzem també els impactes durant els diferents subperíodes de la pandèmia (primera onada, nova normalitat i segona i tercera onades) i a cadascuna de les hores del dia. En conjunt, els resultats d’aquestes anàlisis poden interpretar-se com una aproximació als possibles efectes de fenòmens cada cop més importants en la nostra vida com el teletreball o el comerç electrònic. Classificació JEL: R41, Q53, L86
Abstract
Aquest treball investiga l’impacte que té la mobilitat sobre la pol.lució als municipis de Catalunya. Per fer-ho, fem ús de l’experiment natural [...]
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Reducing the number of input variables through symbolic regression
D. Brkić, P. Praks, M. Marek, U. Ilić, Z. Stajić

Electronic Research Archive (2025). 2. Brkić, D., Praks, P., Marek, M., Ilić, U., Stajić, Z. (2025). Reducing the number of input variables through symbolic regression. Electronic Research Archive, Vol. 33, No. 9, paper No. 5158-5178.

Abstract
Symbolic regression, a type of machine learning technique, can efficiently disregard variables that are not significant to the final output, even if they were initially preselected as inputs. Various input parameters are tested in the three examples presented here, where the outputs are modeled using symbolic regression: estimating the middle plasma torch temperature used for waste gasification, the active energy of a solar power plant, and the diameter of a pipe with a known flow and pressure drop through it. Final highly accurate formulas are produced after numerous attempts with lower performances. The process for rejecting the parameters without or with limited influence is automatic and can be performed without human intervention and supervision. The results obtained using symbolic regression are easily interpretable by human experts. This approach shows how to use machine learning-based modeling as an additional tool for sensitivity analysis.
Abstract
Symbolic regression, a type of machine learning technique, can efficiently disregard variables that are not significant to the final output, even if they were initially preselected [...]
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The Codex of Authority
A. Startari

The Codex of Authority (2025). https://zenodo.org/records/17026629

Abstract
This article introduces the concept of the Codex of Authority, a juridical metaphor for the compiled rule that governs without reference to a legislator. In predictive societies, authority is no longer produced by political will but by syntactic form. From automated drafts of the EU’s AI Act to blockchain smart contracts, institutional norms emerge as selfsufficient codices where legitimacy resides in structure rather than origin. By analyzing this shift, the article proposes a framework for understanding how legal authority becomes executable, impersonal, and detached from interpretation. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book AI Syntactic Power and Legitimacy. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained. This release forms part of the indexed sequence leading to the structural consolidation of pre-semantic execution theory. Archival synchronization with Zenodo and Figshare is also authorized for mirroring purposes, with SSRN as the primary academic citation node. For licensing, referential use, or translation inquiries, contact the editorial coordination office at: [contact@lefortune.org]
Abstract
This article introduces the concept of the Codex of Authority, a juridical metaphor for the compiled rule that governs without reference to a legislator. In predictive societies, [...]
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The Role of Robotic Surgery in General Surgery: Advances, Limitations, and Future Perspectives
C. Vanegas-Mondragon

Collection of Articles on Medicine (2025). 9

Abstract
Background: Robotic surgery is an important advancement in minimally invasive surgery, providing enhanced precision, ergonomics, and visualization compared to laparoscopy. Its increasing adoption in general surgery reflects both its potential and its limitations. Objective: To review the current role of robotic surgery in general surgery, emphasizing advances, limitations, and future perspectives. Methods: A narrative review was performed using PubMed, Scopus, and Web of Science (2020-2023). Search terms included “robotic surgery,” “general surgery,” “da Vinci system,” and “cost-effectiveness.” Priority was given to guidelines, randomized controlled trials, systematic reviews, and meta-analyses. Results: Robotic surgery shows advantages in ergonomics, dexterity, visualization, and conversion rates, particularly in colorectal, hernia, and hepatopancreatobiliary procedures. Limitations include high cost, limited access, absence of haptic feedback, and the need for structured training. Emerging technologies such as novel robotic platforms, artificial intelligence, and augmented reality suggest promising directions. Conclusions: Robotic surgery improves outcomes but requires addressing cost, access, and training challenges.
Abstract
Background: Robotic surgery is an important advancement in minimally invasive surgery, providing enhanced precision, ergonomics, and visualization compared to laparoscopy. [...]
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Alcohol Intoxication as Just Cause for Employment Termination: A Comparative Medical–Legal Perspective in Argentina, Peru, Costa Rica, and Mexico
C. Vanegas-Mondragon, E. Vanegas-Lopez

International Journal of Multidisciplinary Educational Research and Innovation (2025). 2

Abstract
Objective: To analyze the medical–legal framework regarding drunkenness as grounds for termination of the employment relationship in Argentina, Peru, Costa Rica, and Mexico, considering alcoholism as a disease and its implications for occupational health. Methods: A documentary and comparative review of labor legislation, jurisprudence, and doctrine was conducted in the four countries. Additionally, medical literature on alcoholism published between 2000 and 2023 was reviewed, using PubMed, Scopus, Web of Science, WHO, and ILO sources [1–3,5,9,13]. Results: Although labor laws in Latin America recognize drunkenness as just cause for dismissal [4–7], judicial practice has progressively incorporated principles of proportionality, human dignity, and the right to health [13,14]. National jurisprudence shows variability: while some courts uphold dismissal, others consider alcoholism a disease requiring treatment and rehabilitation [16–21]. The medical literature highlights the health burden of alcohol use and the need for workplace interventions focused on prevention and reintegration [9–12,22]. Conclusion: Dismissal due solely to drunkenness is insufficient without evidence of recurrence, direct harm to productivity, or risk to third-party integrity. A balanced approach integrating occupational health policies, rehabilitation measures, and proportional sanctions is recommended.
Abstract
Objective: To analyze the medical–legal framework regarding drunkenness as grounds for termination of the employment relationship in Argentina, Peru, Costa Rica, and [...]
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Implementación de Energía fotovoltaica como solución eficiente para la oxigenación en la acuicultura: un caso de éxito.
V. florez ramos

Collection of Agricultural and Biological Sciences (2025). 2

Abstract
Colombian fish farming is a rapidly growing sector, crucial for food security and the national economy, generating a significant number of direct and indirect jobs. However, its sustainable development is threatened by its high dependence on fossil fuels to meet energy demands, which can account for up to 40% of operational costs, primarily to maintain optimal pond conditions, with oxygenation being the most critical parameter. This article analyzes the integration of solar photovoltaic (PV) energy systems as a viable and sustainable solution to the energy challenges of aquaculture. Known as aquavoltaic systems, they not only provide clean and economically competitive energy but also drive the sector's digitalization by enabling real-time water quality monitoring. This allows for precise control of dissolved oxygen levels, reducing fish mortality, improving yields, and minimizing environmental impact by avoiding CO₂ emissions. Although it is acknowledged that panel manufacturing has environmental impacts, these are significantly lower compared to the continuous damage caused by fossil fuels. It is concluded that synergy between public policy and private investment is essential to promote the adoption of this technology and consolidate sustainable growth for Colombian aquaculture. Keywords: Aquaculture, Solar Photovoltaic Energy, Sustainability, Dissolved Oxygen, Colombia, Aquavoltaics, Energy Efficiency. Colombian fish farming is a rapidly growing sector, crucial for food security and the national economy, generating a significant number of direct and indirect jobs. However, its sustainable development is threatened by its high dependence on fossil fuels to meet energy demands, which can account for up to 40% of operational costs, primarily to maintain optimal pond conditions, with oxygenation being the most critical parameter. This article analyzes the integration of solar photovoltaic (PV) energy systems as a viable and sustainable solution to the energy challenges of aquaculture. Known as aquavoltaic systems, they not only provide clean and economically competitive energy but also drive the sector's digitalization by enabling real-time water quality monitoring. This allows for precise control of dissolved oxygen levels, reducing fish mortality, improving yields, and minimizing environmental impact by avoiding CO₂ emissions. Although it is acknowledged that panel manufacturing has environmental impacts, these are significantly lower compared to the continuous damage caused by fossil fuels. It is concluded that synergy between public policy and private investment is essential to promote the adoption of this technology and consolidate sustainable growth for Colombian aquaculture. Keywords: Aquaculture, Solar Photovoltaic Energy, Sustainability, Dissolved Oxygen, Colombia, Aquavoltaics, Energy Efficiency.
Abstract
Colombian fish farming is a rapidly growing sector, crucial for food security and the national economy, generating a significant number of direct and indirect jobs. However, [...]
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Obedience Without Command: The Silent Authority of Predictive Systems
A. Startari

Obedience Without Command: The Silent Authority of Predictive Systems (2025). https://zenodo.org/records/16993991

Abstract
This article investigates the paradox of obedience without command in predictive societies. Authority, once tied to explicit orders and visible command structures, is now embedded in syntactic operations that organize compliance without issuing instructions. Obedience Without Command explores how predictive systems generate silent authority, where rules are followed not because they are commanded, but because their form leaves no alternative. Through case studies of financial reporting, automated governance, and predictive scoring, the paper develops a framework to understand authority that operates without decisionmakers, and obedience that emerges without command. Acknowledgment / Editorial Note This article is published with editorial permission from LeFortune Academic Imprint, under whose license the text will also appear as part of the upcoming book Syntactic Authority and the Execution of Form. The present version is an autonomous preprint, structurally complete and formally self-contained. No substantive modifications are expected between this edition and the print edition. LeFortune holds non-exclusive editorial rights for collective publication within the Grammars of Power series. Open access deposit on SSRN is authorized under that framework, if citation integrity and canonical links to related works (SSRN: 10.2139/ssrn.4841065, 10.2139/ssrn.4862741, 10.2139/ssrn.4877266) are maintained. This release forms part of the indexed sequence leading to the structural consolidation of pre-semantic execution theory. Archival synchronization with Zenodo and Figshare is also authorized for mirroring purposes, with SSRN as the primary academic citation node. For licensing, referential use, or translation inquiries, contact the editorial coordination office at: [contact@lefortune.org]
Abstract
This article investigates the paradox of obedience without command in predictive societies. Authority, once tied to explicit orders and visible command structures, is now [...]
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TRAMPA TECNO-BIO: ALTERNATIVA LIMPIA PARA EL CONTROL DE PLAGAS AGRÍCOLAS
A. Yepes Acosta

Collection of Agricultural and Biological Sciences (2025). 1

Abstract
The purpose of this project is to design and build an automated and ecological trap for the control of common pests in school and family crops in the department of Sucre, as an alternative to the intensive use of chemical pesticides. It is intended to integrate technological and biological components that allow attracting and capturing insects such as the white fly (Bemisia tabaci) and the codling moth (Spodoptera frugiperda), by means of light stimuli and suction mechanisms. The study incorporates STEAM fundamentals to foster interdisciplinary learning and critical thinking in high school students. It will be developed through a project-based methodology (PBL) and formative research, with field tests, data recording, and scientific dissemination activities. Keywords: Organic farming, STEAM education, Micro:bit, sustainability, pest control, educational innovation.
Abstract
The purpose of this project is to design and build an automated and ecological trap for the control of common pests in school and family crops in the department of Sucre, [...]
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GANADOGO: APLICACIÓN MÓVIL PARA EL CONTROL Y GESTIÓN DE GANADO MEDIANTE GPS Y GEOREFERENCIACIÓN
E. itinerantes., H. Ahumada Hernandez

International workshop on Inkjet Technology and Beyond: Experiments, CFD, and Artificial Intelligence (2025). 2

Abstract
GanadoGo es una innovadora aplicación móvil diseñada para optimizar la gestión ganadera en el municipio de Sampués, Colombia. Mediante la integración de geolocalización GPS y dispositivos micro:bit, la aplicación permite el seguimiento y monitoreo del ganado en tiempo real, mejorando el control y minimizando las pérdidas. La implementación de GanadoGo representa un avance significativo en la eficiencia productiva, el bienestar social y la sostenibilidad ambiental. Este proyecto apoya el desarrollo rural y económico de la región, en consonancia con los planes de desarrollo nacionales y sectoriales, a la vez que mejora la seguridad alimentaria, promueve la inclusión social y fomenta el uso responsable de los recursos naturales.
Abstract
GanadoGo es una innovadora aplicación móvil diseñada para optimizar la gestión ganadera en el municipio de Sampués, Colombia. Mediante la [...]
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Masa Madre Sin Gluten: Ciencia, Innovación y Emprendimiento Gluten-Free Sourdough: Science, Innovation, and Entrepreneurship
D. Barboza Pantoja

David Ernesto Barboza Pantoja's personal collection (2025). 1

Abstract
Este estudio analiza la aplicación de la masa madre sin gluten como herramienta educativa y productiva en comunidades rurales, específicamente en la vereda Chochó, municipio de Sincelejo. El objetivo principal fue evaluar cómo la integración de conocimientos microbiológicos y fisicoquímicos con los procesos de panificación artesanal puede fomentar el espíritu emprendedor. La metodología consistió en fases de exploración, experimentación, producción y emprendimiento, utilizando harinas alternativas como arroz, yuca y ñame. Se registraron variables fisicoquímicas durante la fermentación, como pH, volumen y tiempo de duplicación. Los resultados mostraron que las harinas alternativas permiten obtener productos con buenas características sensoriales y mayor valor nutricional. La discusión compara estos hallazgos con estudios previos en Scielo, destacando el potencial económico y social del enfoque. Se concluye que la masa madre sin gluten puede ser una vía efectiva para la educación práctica, el desarrollo de habilidades científicas y la generación de ingresos en contextos rurales. '''Palabras clave:''' masa madre, fermentación, harinas alternativas, educación científica, emprendimiento, panificación, nutrición.
Abstract
Este estudio analiza la aplicación de la masa madre sin gluten como herramienta educativa y productiva en comunidades rurales, específicamente en la vereda Chochó, [...]
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AgroScan: Aplicación para el Diagnóstico de Enfermedades en el Cultivo de Yuca mediante Fotografías y Reconocimiento de Imágenes con Inteligencia Artificial.
H. Ahumada Hernandez

International workshop on Inkjet Technology and Beyond: Experiments, CFD, and Artificial Intelligence (2025). 1

Abstract
AgroScan is a mobile application designed to support farmers and students in the department of Sucre, Colombia, in the early detection of diseases affecting cassava crops using artificial intelligence (AI). By capturing leaf images with mobile phones, the system analyzes visual symptoms to identify potential diseases. This project offers an accessible and educational technological solution that strengthens the agricultural sector, enhances crop yields, and promotes the adoption of emerging technologies in rural contexts. AgroScan addresses the critical need for early disease diagnosis, contributing to economic development, technological education, rural inclusion, and sustainable agricultural practices.
Abstract
AgroScan is a mobile application designed to support farmers and students in the department of Sucre, Colombia, in the early detection of diseases affecting cassava crops [...]
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AgroScan: A Mobile Application for Diagnosing Cassava Diseases through Image Recognition and Artificial Intelligence in Sucre, Colombia
H. Ahumada Hernandez

Colección Personal de Artículos (2025). 1

Abstract
AgroScan is a mobile application designed to support farmers and students in the Department of Sucre in the early detection of diseases affecting cassava crops through the use of artificial intelligence (AI). By capturing photographs with mobile phones, the system analyzes cassava leaves to identify signs of disease. This project offers an accessible and educational technological solution that strengthens the agricultural sector, improves crop yields, and promotes the learning of emerging technologies in rural contexts.
Abstract
AgroScan is a mobile application designed to support farmers and students in the Department of Sucre in the early detection of diseases affecting cassava crops through the [...]
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Alcohol Intoxication as Just Cause for Employment Termination: A Comparative Medical–Legal Perspective in Argentina, Peru, Costa Rica, and Mexico
C. Vanegas-Mondragon, E. Vanegas-Lopez

International Journal of Multidisciplinary Educational Research and Innovation (2025). 1

Abstract
Drunkenness as grounds for termination of the employment relationship without employer liability has been widely debated in Latin America. Although contemplated in the labor laws of Argentina, Peru, Costa Rica, and Mexico, recent case law questions its strict application. From a medical perspective, alcoholism is recognized as a chronic, progressive disease, creating tension between workers' right to health and employers' authority to terminate contracts[1–3]. This article provides a medical-legal comparative analysis of legal and health criteria regarding workplace drunkenness. The study highlights the principle of proportionality, recognition of alcoholism as a disease, and the need to align labor regulations with occupational health[4–6]. We conclude that mere drunkenness should not suffice to justify dismissal, except when workplace safety, productivity, or third-party integrity is compromised, emphasizing preventive and rehabilitative measures[7,8].
Abstract
Drunkenness as grounds for termination of the employment relationship without employer liability has been widely debated in Latin America. Although contemplated in the labor [...]
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