266 research outputs found

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    Investigation of the treatment of epilepsy with cannabinoids

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    Cannabis has been consumed by humans for millennia, and is currently used in Canada for the treatment of a variety of medical conditions including anxiety, PTSD, and chronic pain. The medical community is hesitant to accept the use of Cannabis and cannabinoids to treat epilepsy due to inadequate information on mechanism of action and long-term effects. Cannabidiol (CBD) is approved to treat pediatric patients with severe epilepsies such as Dravet Syndrome and Lennox-Gastaut Syndrome in the US and some European countries, but there are many individuals with less severe epilepsies whose quality of life is affected by negative side-effects from current anti-epileptic drugs. This research aims to globally evaluate which of the 6 most prevalent cannabinoids show seizure reduction and to investigate the mechanism of action of cannabinoids in an epilepsy model. Using a chemical model of epilepsy, zebrafish larvae were treated with phytocannabinoids, and their seizures measured through an optimized behaviour tracking method. Unique to this study, cannabinoid uptake was measured in larvae with a novel HPLC method developed in this project. This accomplishment is superior to previous attempts to quantify cannabinoid uptake by measuring losses in the water used to deliver cannabinoid to fish, which assumes that all losses are due to uptake and metabolism by the study organisms. CBD induced seizure reduction is partially mediated by the Gprotein coupled receptor GPR55 and potentially through CB1R. Treatment with cannabinol (CBN) and cannabichromene (CBC) decreased seizure intensity at lower concentrations than CBD. Δ9-tetrahydrocannabinol (Δ9-THC), Δ8-tetrahydrocannabinol (Δ8-THC), and cannabigerol (CBG) only showed antiepileptic effects at a high concentration, but when concentrationd in combination with CBD reduced seizures more than either treatment alone. RT-qPCR showed changes in expression of endocannabinoid system (napepld, gde1, faah, ptgs1, ptgs2a) and neural (fosab, pyya) genes in response to phytocannabinoid treatment. The data reported in this thesis supports the hypothesis that phytocannabinoids are promising anti-epileptics and could be used in combination therapies for more effective seizure relief

    Brain imaging biomarkers in Multiple Sclerosis

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    Background: Iron rim lesions (IRLs), white matter lesions (WMLs) accumulation and linear brain atrophy measurements have been suggested to be important imaging biomarkers in multiple sclerosis (MS). The extent to which these markers are related to MS diagnosis and predict disease prognosis remains unclear. Furthermore, research Magnetic Resonance Imaging (MRI) findings need validation in clinical settings before they can be incorporated into clinical practice. Methods: I conducted two reviews one was a mapping review on IRLs and the other was a meta-analysis on WMLs in MS. I then tested the diagnostic and prognostic usefulness of the IRL in two studies: (1) a large, cross-sectional, multi-centre study of patients with MS and mimicking disorders using 3T MRI, (2) a retrospective single-centre study of patients with first presentation of a clinically isolated syndrome (CIS) or at the early stage of the disease using 7T MRI. I also explored the utility of routine, non-standardised MRI scans measuring WMLs number, volume and linear measures of atrophy at the early stage of the disease and examined their role in predicting long-term disability. Results: The IRLs achieved high specificity (up to 99%) in diagnosing MS compared to MS-mimics but low sensitivity of 24%. All patients with IRLs showing a central vein sign (CVS) had MS or CIS, giving a diagnostic specificity of 100% but equally low sensitivity of 21%. Moreover, the presence of IRLs was also a predictor of long-term disability, especially in patients with ≥4 IRLs. IRLs had a greater impact on disability compared to the WMLs number and volume. Linear brain atrophy of Inter-Caudate Distance (ICD) and Third Ventricle Width (TVW) had a significant impact in predicting disability after 10 years. Conclusions: The perilesional IRLs may reduce diagnostic uncertainty in MS by being a highly specific imaging diagnostic biomarker, especially when used in conjunction with the CVS. Also, the presence and number of IRLs hold prognostic value for long-term physical disability in MS. Simple and reliable assessment of brain atrophy remains challenging in clinical practice

    Ancestral Sequence Reconstructions of Stator Proteins of the Bacterial Flagellar Motor

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    The bacterial flagellar motor (BFM) is a bidirectional nanomachine that confers motility to several bacteria. The BFM is powered by ion transfer across the cell membrane through its stator. The stator consists of two membrane proteins: MotA and MotB in proton (H+)-powered motors or PomA and PomB in sodium (Na+)-powered motors. Over the years, several parts of the BFM have been resolved using numerous mutagenesis studies and different microscopic techniques. However, the entire structure of the BFM, its ion selection mechanism, the functional roles of each structural residue, and how its complexity evolves and adapts over time are not completely known. In this thesis, we used ancestral sequence reconstruction (ASR) to study the evolutionary history and roles of the key structural residues of the stator complex of the BFM. First, we reconstructed and synthesised thirteen combined transmembrane (TM) and plug domains of ancestral MotBs (MotB-ASRs) to test previously hypothesised critical motifs for the ion-selectivity of BFM. The results showed that all resurrected MotB-ASRs were functional and restored motility with the contemporary E. coli MotA in a stator-deleted strain. In addition, all MotB-ASRs exhibited Na+-independent motility in different ionic conditions, suggesting that the synthesised MotB-ASRs were more likely to be proton-powered. Secondly, we reconstructed and synthesised ten complete ancient MotAs (MotA-ASRs) to study the role of the key structural residues of MotA in BFM function. We identified that four of the ten MotA-ASRs were functional and restored motility in combination with contemporary E. coli MotB and several previously synthesised MotB-ASRs. The functional MotA-ASRs also showed Na+-independent motility in different ionic conditions, like our MotB-ASRs. Additionally, the resurrected MotA-ASRs provided evidence of several variable regions of MotA and revealed 30 conserved residues that were essential for flagellar function. Lastly, we screened two novel motility inhibitors, HM2-16F and BB2-50F, and characterised their anti-motility activity on multiple strains and stator types. We also optimised and developed new high-resolution assays for the phenotypic study of stator function to verify the targets of the motility inhibitors. Our results confirmed that these compounds inhibited bacterial swimming but did not target the stator. In summary, this thesis shows the use of ASR as a tool to study the stator proteins of the BFM

    Internet and Biometric Web Based Business Management Decision Support

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    Internet and Biometric Web Based Business Management Decision Support MICROBE MOOC material prepared under IO1/A5 Development of the MICROBE personalized MOOCs content and teaching materials Prepared by: A. Kaklauskas, A. Banaitis, I. Ubarte Vilnius Gediminas Technical University, Lithuania Project No: 2020-1-LT01-KA203-07810

    High throughput screening system for 3D engineered cardiac tissue

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    Three dimensional engineered cardiac tissues (3D ECTs) have become a promising tool for in vitro screening to assess drug cardiotoxicity, a leading cause of failure in pharmaceutical development. A current bottleneck is the relatively low throughput of such assays, which infer spontaneous contractile forces exerted by millimeter-scale ECTs through precise optical measurement of deflection of the polymer scaffolds that support them. The required resolution and speed restrain the field of view to at most a few ECTs at a time using conventional imaging. To balance the inherent tradeoff among imaging resolution, field of view and speed, an innovative mosaic imaging system was designed, built, and validated to sense contractile force of 3D ECTs seeded on a 96-well plate. Results have shown real-time, parallel contractile force monitoring for up to 3 weeks. Pilot drug testing was conducted using isoproterenol. A parallel molding process was also developed to fabricate the compliant ECT scaffolds in a 96-wellplate, significantly reducing cost and labor associated with the current one-by-one molding process. Work in progress involves development of parallel electrical pacing and fluorescent imaging, allowing electrophysiological characterization of ECTs in conjunction with the contractile characterization in the 96-well plate format. Future work will focus on optimization of the ECT seeding process for the 96-wellplate. The dissertation provides a scale-up prototype for the entire workflow of cardiotoxicity testing with ECTs including scaffold molding, tissue seeding and functional assay. Outcome of this dissertation is partially or fully licensable with confirmed interests from industrial and government sources. The engineering work encompassed in this dissertation could contribute to the high throughput translational use of other types of engineered tissues

    Metallurgical Process Simulation and Optimization

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    Metallurgy involves the art and science of extracting metals from their ores and modifying the metals for use. With thousands of years of development, many interdisciplinary technologies have been introduced into this traditional and large-scale industry. In modern metallurgical practices, modelling and simulation are widely used to provide solutions in the areas of design, control, optimization, and visualization, and are becoming increasingly significant in the progress of digital transformation and intelligent metallurgy. This Special Issue (SI), entitled “Metallurgical Process Simulation and Optimization”, has been organized as a platform to present the recent advances in the field of modelling and optimization of metallurgical processes, which covers the processes of electric/oxygen steel-making, secondary metallurgy, (continuous) casting, and processing. Eighteen articles have been included that concern various aspects of the topic

    Naval Postgraduate School Academic Catalog - February 2023

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    CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship

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    This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship
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