Abstract

Structural brain networks may be reconstructed from diffusion MRI tractography data and have great potential to further our understanding of the topological organisation of brain structure in health and disease. Network reconstruction is complex and involves a series of processesing methods including anatomical parcellation, registration, fiber orientation estimation and whole-brain fiber tractography. Methodological choices at each stage can affect the anatomical accuracy and graph theoretical properties of the reconstructed networks, meaning applying different combinations in a network reconstruction pipeline may produce substantially different networks. Furthermore, the choice of which connections are considered important is unclear. In this study, we assessed the similarity between structural networks obtained using two independent state-of-the-art reconstruction pipelines. We aimed to quantify network similarity and identify the core connections emerging most robustly in both pipelines. Similarity of network connections was compared between pipelines employing different atlases by merging parcels to a common and equivalent node scale. We found a high agreement between the networks across a range of fiber density thresholds. In addition, we identified a robust core of highly connected regions coinciding with a peak in similarity across network density thresholds, and replicated these results with atlases at different node scales. The binary network properties of these core connections were similar between pipelines but showed some differences in atlases across node scales. This study demonstrates the utility of applying multiple structural network reconstrution pipelines to diffusion data in order to identify the most important connections for further study. Document type: Article

Abstract

This paper presents the results of a research study exploring consumer behaviour and uses of photography among first-year students of the Degrees in Journalism, Audiovisual Communication, and Advertising and Public Relations in four Spanish universities (University of Malaga, University of Santiago de Compostela, University of the Basque Country and Universitat Jaume I in Castellón). As it is well known, the emergence of digital technologies has caused far-reaching transformations in the field of photography. These changes have affected production, distribution and circulation processes. However, digital technology has particularly changed the concept of photography itself as a means of expression and communication, above all among young people. Changes in how photography is perceived nowadays, brought about by the onset of digitalization, in turn raises a series of questions that merit reflection. To this end, a survey was designed and administered to a total of 467 communication sciences students in Spain. The results of this research reveal, on the one hand, how these communication students relate to the use of photography today; on the other hand, and more importantly, the results throw some light on how to approach the teaching of digital photography in a higher education context.

Abstract

Root system analysis is a complex task, often performed using fully automated image analysis pipelines. However, these pipelines are usually evaluated with a limited number of ground-truth root images, most likely of limited size and complexity. We have used a root model, ArchiSimple to create a large and diverse library of ground-truth root system images (10.000). This library was used to evaluate the accuracy and usefulness of several image descriptors classicaly used in root image analysis pipelines. Our analysis highlighted that the accuracy of the different metrics is strongly linked to the type of root system analyzed (e.g. dicot or monocot) as well as their size and complexity. Metrics that have been shown to be accurate for small dicot root systems might fail for large dicots root systems or small monocot root systems. Our study also demonstrated that the usefulness of the different metrics when trying to discriminate genotypes or experimental conditions may vary. Overall, our analysis is a call to caution when automatically analyzing root images. If a thorough calibration is not performed on the dataset of interest, unexpected errors might arise, especially for large and complex root images. To facilitate such calibration, both the image library and the different codes used in the study have been made available to the community. Document type: Preprint

Abstract

n underwater imaging system was investigated for automotive use in highly scattered underwater environments. The purpose of the system is the driver&rsquo s information about hidden obstacles, such as stones, driftwood, open sewer hatches. A comparison of various underwater vision methods was presented by the way they are implemented, the range reached, and the cost of implementation. It has been experimentally shown that a conventional active system can provide a maximum visibility range of up to three light attenuation lengths. In most practical cases of turbid waters during floods, this corresponds to distances of about 1 meter. From the presented analysis it follows that advanced extended range imaging methods allow increasing of the visibility range up to 2 meters. Document type: Article

Abstract

Sound and durable concrete mixtures are essential in environments where microbial induced corrosion (MIC) is a concern. In this study three concrete mixtures prepared with different binders (ordinary portland cement (OPC), calcium aluminate cement (CAC) and alkali-activated cement (AAC) were petrographically examined after exposure to laboratory-controlled MIC conditions. Analytical techniques included reflected light microscopy, polarized and fluorescent transmitted light microscopy (FLM) and scanning electron microscopy equipped with an energy-dispersive X-ray spectrometer (SEM/EDX). SEM/EDX analyses obtained from the same areas provided information on chemical and mineralogical alteration, while quantitative image analysis with FLM affords an opportunity to quantify the variation in capillary porosity of the paste within alteration zonation. The microscopic observations indicate that the change in normalized capillary porosity coincide broadly with different alteration zones, which are in turn dependent on the type of binder. The OPC concrete shows the greatest deterioration where the paste is largely replaced by gypsum and high capillary porosity is lined to leaching of a calcium. The formation of ettringite densifies the paste and lowers the capillary porosity inboard of the gypsum zone in the OPC concrete. The CAC and AAC mixtures show better resistance to leaching than the OPC mixture, which explains their superior resistance to MIC. These findings are consistent with independent macroscopic observations that indicate the OPC mixture deteriorated more rapidly and severely than the CAC and AAC mixtures.

Abstract

Manufacturing quality in composite laminates is one of the key aspects to have in consideration when producing aerostructures. For composite structures quality evaluation, an iterative process of qualification of the first items manufactured is often followed. Thus, the manufacturing process parameters can be tuned until achieving an incremented maturity level that ensures the structure mechanical properties present values within the defined quality standards.

Volume fraction of voids (pores), resin and fibre is part of the set of properties that must be verified, especially in novel and/or low cost manufacturing processess that can affect the structural behaviour. The ability to obtain results depending on the technique used for testing becomes very important at this point.

This study proposes a comparative analysis of the measurement of voids, fibre and resin percentage on carbon fibre reinforced polymers by automated image analysis technique and acid digestion method, varying parameters of the test procedure with the purpose of evaluating their influence in the correct determination of volume fractions. The use of different methods and parameters allows to analyze comparatively the different results obtained and shows advantages and disadvantages of both methods as well as provides valuable information on the best practices for correct test execution following each procedure.

Abstract

Coke moisture content plays a crucial role as a quality indicator in ironmaking. Fast and accurate measurement of coke moisture content can effectively ensure operational stability, thereby guaranteeing the quality of pig iron. Coke with different moisture levels exhibits variations in light reflection, refraction, and powder adhesion characteristics. Drawing from this premise, we employed an image analysis approach to analyse the colour and texture features of coke images with varying moisture content. The results indicated that certain specific image features are highly sensitive to changes in coke moisture content. This study also conducted testing and comparison of performances of three common machine learning models in predicting coke moisture content based on image analysis. The Support Vector Machine (SVM) predictive model for coke moisture content based on image analysis showed optimal performance. This demonstrated a close connection between coke image features and moisture content.