Abstract

As the roll-out of antiretroviral therapy continues to drive downwards morbidity and mortality in people living with HIV/AIDS (PLWHAs), organ toxicities (especially the liver) are frequently becoming a major concern for researchers, scientists and healthcare planners. This study was conducted to investigate the possible protective effect of Hypoxis hemerocallidea (AP) against highly active antiretroviral therapy (HAART)-induced hepatotoxicity. A total of 63 pathogen-free adult male Sprague-Dawley rats were divided into 9 groups and treated according to protocols. While no mortality was reported, animals treated with adjuvant HAART and AP recorded least% body weight gain. Significant derangements in serum lipid profiles were exacerbated by treatment of with AP as LDL (increased p < 0.03), triglycerides (increased p < 0.03) with no change in total cholesterol levels. Adjuvant AP with HAART caused reduction in LDL (p < 0.05 and 0.03), increased HDL (p < 0.05) and TG (p < 0.05 and 0.001 for AP100 and AP200 doses respectively). Markers of liver injury assayed showed significant increase (p < 0.003, 0.001) in AST in AP alone as well as HAART+ vitamins C and E groups respectively. Adjuvant HAART and AP and vitamins C and E also caused significant declines in ALT and ALP levels. Serum GGT was not markedly altered. Disturbances in histopathology ranged from severe hepatocellular distortions, necrosis and massive fibrosis following co-treatment of HAART with vitamins C and E as well as HAART alone. These results warrant caution on the adjuvant use of AP with HAART by PLWHAs as implications for hepatocellular injuries are suspect with untoward cardiometabolic changes.

Abstract

Since the introduction of mental disorders as networks of causally interacting symptoms, this novel framework has received considerable attention. The past years have resulted in over 40 scientific publications and numerous conference symposia and workshops. Now is an excellent moment to take stock of the network approach: What are its most fundamental challenges, and what are potential ways forward in addressing them? After a brief conceptual introduction, we first discuss challenges to network theory: (1) What is the validity of the network approach beyond some commonly investigated disorders such as major depression? (2) How do we best define psychopathological networks and their constituent elements? And (3) how can we gain a better understanding of the causal nature and real-life underpinnings of associations among symptoms? Next, after a short technical introduction to network modeling, we discuss challenges to network methodology: (4) heterogeneity of samples studied with network analytic models, and (5) a lurking replicability crisis in this strongly data-driven and exploratory field. Addressing these challenges may propel the network approach from its adolescence into adulthood and promises advances in understanding psychopathology both at the nomothetic and idiographic level. Keywords: clinical psychology; dynamic systems; mental disorders; networks; personalized medicine; psychiatry; reproducibility Document type: Part of book or chapter of book

Abstract

Cost-benefit analysis (CBA) is the root of Health Economics and is based on the welfare theory. CBA is the broadest economic evaluation (EE) method that assesses all benefits and costs in monetary units; the production of welfare is expressed in terms of net benefit (the difference between benefits and costs). The main goal in the welfarist approach is to maximize welfare according to individuals’ preferences. The application of CBA principles faces multiple obstacles, mainly because valuing health in terms of monetary units is challenging and raises ethical and methodological constraints. In the health sector, CBA has received relevant criticism, leading to the emergence and adoption of other methods of EE, such as cost-effectiveness analysis (CEA) and cost-utility analysis (CUA). However, attempts to apply welfarist principles to CEA were far of being accepted, and consensus among health economists in this regard still does not exist. The extra-welfarist approach encompassing CEA and CUA has progressed toward maximizing health outcomes and focusing on equity and fairness issues. The most common technique used in CBA to elicit preferences is the contingent valuation (willingness to pay). Despite the challenging task of valuing mental health outcomes, some studies demonstrate the feasibility of this technique in people with mental disorders, though some level of inconsistency and inaccuracy in respondents’ answers was reported. Despite methodological limitations among all EE methods applied to health, there is a growing interest in CBA and, more specifically, in discrete choice experiment, especially for health services and public health policies, and in exploring patients’ treatment preferences. The Mental Health field adds challenges to CBA regarding the complexity of defining and measuring outcomes representing mental health maximization. Document type: Book

Abstract

Traffic engineering encompasses a set of techniques that can be used to control the flow of traffic in data networks. We discuss several of those techniques that have been developed during the last few years. Some techniques are focused on pure IP networks while others have been designed with emerging technologies for scalable Quality of Service (QoS) such as Differentiated Services and MPLS in mind. We first discuss traffic engineering techniques inside a single domain. We show that by using a non-linear programming formulation of the traffic engineering problem it is possible to meet the requirements of demanding customer traffic, while optimising the use of network resources, through the means of an automated provisioning system. We also extend the functionality of the traffic engineering system through policies. In the following, we discuss the techniques that can be used to control the flow of packets between domains. First, we briefly describe interdomain routing and the Border Gateway Protocol (BGP). Second, we summarise the characteristics of interdomain traffic based on measurements with two different Internet Service Providers. We show by simulations the limitations of several BGP-based traffic engineering techniques that are currently used on the Internet. Then, we discuss the utilisation of BGP to exchange QoS information between domains by using the QOS_NLRI attribute to allow BGP to select more optimum paths. Finally, we consider the multi-homing problem and analyse the current proposed IPv6 multi-homing solutions are analysed along with their impact on communication quality.

Abstract

mong the several findings deriving from the application of complex network formalism to the investigation of natural phenomena, the fact that linguistic constructions follow power laws presents special interest for its potential implications for psychology and brain science. By corresponding to one of the most essentially human manifestations, such language-related properties suggest that similar dynamics may also be inherent to the brain areas related to language and associative memory, and perhaps even consciousness. The present work reports a preliminary experimental investigation aimed at characterizing and modeling the flow of sequentially induced associations between words from the English language in terms of complex networks. The data is produced through a psychophysical experiment where a word is presented to the subject, who is requested to associate another word. Complex network and graph theory formalism and measurements are applied in order to characterize the experimental data. Several interesting results are identified, including the characterization of attraction basins, association asymmetries, context biasing, as well as a possible power-law underlying word associations, which could be explained by the appearance of strange loops along the hierarchical structure underlying word categories. Comment: 5 pages, 6 figures, 3 table Document type: Preprint

Abstract

High-precision and lane selective position estimation is of fundamental importance for prospective advanced driver assistance systems (ADAS) and automated driving functions, as well as for traffic information and management processes in intelligent transportation systems (ITS). User and vehicle positioning is usually based on Global Navigation Satellite System (GNSS), which, as stand-alone positioning, does not meet the necessary requirements in terms of accuracy. Furthermore, the rise of connected driving offers various possibilities to enhance GNSS positioning by applying cooperative positioning (CP) methods. Utilizing only low-cost sensors, especially in urban environments, GNSS CP faces several demanding challenges. Therefore, this contribution presents an empirical study on how Vehicle-to-Everything (V2X) technologies can aid GNSS position estimation in urban environments, with the focus being solely on positioning performance instead of multi-sensor data fusion. The performance of CP utilizing common positioning approaches as well as CP integration in state-of-the-art Vehicular Ad-hoc Networks (VANET) is displayed and discussed. Additionally, a measurement campaign, providing a representational foundation for validating multiple CP methods using only consumer level and low-cost GNSS receivers, as well as commercially available IEEE 802.11p V2X communication modules in a typical urban environment is presented. Evaluating the algorithm&rsquo s performance, it is shown that CP approaches are less accurate compared to single positioning in the given environment. In order to investigate error influences, a skyview modelling seeking to identify non-line-of-sight (NLoS) effects using a 3D building model was performed. We found the position estimates to be less accurate in areas which are affected by NLoS effects such as multipath reception. Due to covariance propagation, the accuracy of CP approaches is decreased, calling for strategies for multipath detection and mitigation. In summary, this contribution will provide insights on integration, implementation strategies and accuracy performances, as well as drawbacks for local area, low-cost GNSS CP in urban environments. Document type: Article

Abstract

Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in current versions of crowdsourced mapping databases including OpenStreetMap. CAP4Access European project aimed to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset (“ground truth dataset”). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions. Document type: Article

Abstract

Presently, in the event of a failure in Automated Driving Systems, control architectures rely on hardware redundancies over software solutions to assure reliability or wait for human interaction in takeover requests to achieve a minimal risk condition. As user confidence and final acceptance of this novel technology are strongly related to enabling safe states, automated fall-back strategies must be assured as a response to failures while the system is performing a dynamic driving task. In this work, a fail-operational control architecture approach and dead-reckoning strategy in case of positioning failures are developed and presented. A fail-operational system is capable of detecting failures in the last available positioning source, warning the decision stage to set up a fall-back strategy and planning a new trajectory in real time. The surrounding objects and road borders are considered during the vehicle motion control after failure, to avoid collisions and lane-keeping purposes. A case study based on a realistic urban scenario is simulated for testing and system verification. It shows that the proposed approach always bears in mind both the passenger&rsquo s safety and comfort during the fall-back maneuvering execution. Document type: Article

Abstract

This research introduces an inverse transient-based optimization approach to automatically detect potential faults, such as leaks, partial blockages, and distributed deteriorations, within pipelines or a water distribution network (WDN). The optimization approach is named the Pipeline Examination Ordinal Symbiotic Organism Search (PEOS). A modified steady hydraulic model considering the effects of pipe aging within a system is used to determine the steady nodal heads and piping flow rates. After applying a transient excitation, the transient behaviors in the system are analyzed using the method of characteristics (MOC). A preliminary screening mechanism is adopted to sift the initial organisms (solutions) to perform better to reduce most of the unnecessary calculations caused by incorrect solutions within the PEOS framework. Further, a symbiotic organism search (SOS) imitates symbiotic relationship strategies to move organisms toward the current optimal organism and eliminate the worst ones. Two experiments on leak and blockage detection in a single pipeline that have been presented in the literature were used to verify the applicability of the proposed approach. Two hypothetical WDNs, including a small-scale and large-scale system, were considered to validate the efficiency, accuracy, and robustness of the proposed approach. The simulation results indicated that the proposed approach obtained more reliable and efficient optimal results than other algorithms did. We believe the proposed fault detection approach is a promising technique in detecting faults in field applications. Document type: Article