Miracle-dz/UniFAR-FTUs huggingface dataset:
THREE-DIMENSIONAL SCATTERING OF PLANE HARMONIC SH , SV , AND P WAVES IN MULTILAYERED ALLUVIAL VALLEYS

In this paper, three-dimensional amplification of plane harmonic SH, SV, and P waves in multilayered alluvial valleys is investigated by using a boundary element method in frequency domain. It is shown that in order to achieve real responses, the problem must be analyzed and modeled three-dimensionally. Also, for exact evaluation of surface ground motions in alluvial valleys all key parameters such as layering, material and geometrical characteristics of each layer, stimulation frequency, wave type, plus angle and azimuth of incidence must be taken into account altogether. The accuracy and efficiency of the proposed formulations for the computation of the surface displacement field amplification is verified by solving a number of problems.
Selecting new BGP Feeders to Address the Incompleteness of the Internet AS-level Graph

In the last decade many studies have used the Internet AS-level topology to perform several analyses, from the discovery of its graph properties to its impact on the effectiveness of worm-containment strategies. Yet, the completeness of the BGP data used to reveal the Internet AS-level topology is questionable. In this work we analyze BGP data currently gathered by RouteViews and RIS route collectors, investigating the reasons of its incompleteness. This analysis lead us to define an ad-hoc metric, named p2c-distance, able to identify which ASes hide part of their connectivity from the route collectors due to BGP export policies and how much the information is filtered due to the best route selection applied by each BGP border router crossed before reaching a route collector. This metric allow us to create the basis of an innovative methodology able to select the minimum set of Autonomous Systems from which the route collectors should receive information in order to maximize the coverage of the core of the Internet. The large number of elements found Copyright c © 2012 by the paper’s authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors. Published at http://ceur-ws.org to be required confirms the incompleteness of the current dataset.
Realistic 3 D Reconstruction method from the set of 2 D image sequences

The 3D model reconstruction from hand-held camera photographs allows new useful Computer Graphics and Computer Vision applications. In this paper a complete system to build realistic 3D visual model from images is presented. The system can deal with uncalibrated image sequences acquired with a hand-held camera. Based on Kanade–Lucas–Tomasi (KLT) method features in the image are detected and tracked. Then features are matched between image pairs using approximate nearest neighbors (ANN) algorithm. After matching features for an image pair, a fundamental matrix for the pairs is estimated using Random sample consensus (RANSAC) method, and finally we run a structure from motion (SfM) procedure to recover camera parameters. From experiment results, which was held on hundred of photos, we found that our proposed world realistic 3D reconstruction method provides good performance with less probability of false matching.
Anderson Localization for Lattice Fermions in the Hartree Aproximation at Positive Temperature ∗

The present work focuses on the effects of disorder on an environment. More particularly, we obtain a proof of Anderson localization in a context to be described below. Anderson was awarded a Nobel prize in physics in 1977, for more details we refer to [13] and the references therein. His seminal paper [4] remains the inspiring source of several mathematically rigorous results and open questions in mathematical physics within the common theme of Anderson Localization which [13] succinctly describes as “ The suppression of electron transport due to disorder” . The first proof of Anderson Localization in one dimension goes back to Goldsheid, Molchanov and Pastur [10]. The first rigorous result in the Anderson model (which we describe more precisely in the next section) was provided by Kunz and Souillard in [11], where they proved complete localization in dimension d = 1. In 1983 Fröhlich and Spencer [8] used multi-scale analysis to prove a result which implies absence of absolutely continuous (ac) spectrum in arbitrary dimension. In 1993, Aizemman and Molchanov [1] introduced the fractional moment method (FMM ) whose application resulted in a somewhat elementary proof of localization at large disorder and extreme energies. The FMM, when applicable, simplifies the task of establishing localization as it typically leads to proofs which are technically less intricate when compared to the multi-scale analysis. As a consequence, the FMM inspired many of the subsequent developments in the field, including the present work.
Mutations in Efflux Pump Rv1258c (Tap) Cause Resistance to Pyrazinamide, Isoniazid, and Streptomycin in M. tuberculosis

Although drug resistance in Mycobacterium tuberculosis is mainly caused by mutations in drug activating enzymes or drug targets, there is increasing interest in the possible role of efflux in causing drug resistance. Previously, efflux genes have been shown to be upregulated upon drug exposure or implicated in drug resistance in overexpression studies, but the role of mutations in efflux pumps identified in clinical isolates in causing drug resistance is unknown. Here we investigated the role of mutations in efflux pump Rv1258c (Tap) from clinical isolates in causing drug resistance in M. tuberculosis. We constructed point mutations V219A and S292L in Rv1258c in the chromosome of M. tuberculosis and the point mutations were confirmed by DNA sequencing. The susceptibility of the constructed M. tuberculosis Rv1258c mutants to different tuberculosis drugs was assessed using conventional drug susceptibility testing in 7H11 agar in the presence and absence of efflux pump inhibitor piperine. A C14-labeled PZA uptake experiment was performed to demonstrate higher efflux activity in the M. tuberculosis Rv1258c mutants. Interestingly, the V219A and S292L point mutations caused clinically relevant drug resistance to pyrazinamide (PZA), isoniazid (INH), and streptomycin (SM), but not to other drugs in M. tuberculosis. While V219A point mutation conferred low-level drug resistance, the S292L mutation caused a higher level of resistance. Efflux inhibitor piperine inhibited INH and PZA resistance in the S292L mutant but not in the V219A mutant. The S292L mutant had higher efflux activity for pyrazinoic acid (the active form of PZA) than the parent strain. We conclude that point mutations in the efflux pump Rv1258c in clinical isolates can confer clinically relevant drug resistance, including PZA resistance, and could explain some previously unaccounted drug resistance in clinical strains. Future studies need to take efflux mutations into consideration for improved detection of drug resistance in M. tuberculosis and address their role in affecting treatment outcome in vivo.
Chapter 1 Cooperative Exploration , Localization , and Visual Map Construction

We examine the problem of learning a visual map of the environment based on discrete landmarks. While making this map we seek to maintain an accurate pose estimate for the mapping robots. Our approach is based on using a team of at least two (heterogeneous) mobile robots in a simple collaborative scheme. In many mapping contexts, a robot moves about the environment collecting data (images, in particular) which are later used to assemble a map; we view the map construction as both a knowledge acquisition and a training process. Without reference to the environment, as a robot collects training images, its position estimate accumulates errors, thus corrupting its estimate of the positions from which observations are taken. We address this problem by deploying a second robot to observe the first one as it explores, thereby establishing a virtual tether, and enabling an accurate estimate of the robot’s position while it constructs the map. We refer to this process as cooperative localization. The images collected during this process are assembled into a representation that allows vision-based position estimation from a single image at a later time. In addition to developing a formalism and concept, we validate our approach experimentally and present quantitative results demonstrating the performance of the method in over 90 trials.
An IoT-based solution for Post-Prognostics Decision in Cloud computing environment

Maintenance is one of the main factors of production process. The aim of maintenance strategy is not just to repair and maintain equipment in a good condition, but to implement efficient maintenance solutions to ensure the good function while minimizing the cost and time of maintenance. Maintenance strategies start by collecting information from sensors, analyze this information to predict the malfunction or failure in the system. As a result, with this information, we try to find the optimal solution for maintenance. Prognostics Health Manager (PHM) offers significant benefits for maintenance. It predicts the future behavior of a system as well as its remaining useful life. However when factory have a large number of asset with mobile and stationary equipment in different geographically sites. Making decision and collecting information become difficult to be done. In this study we interested in stationary equipment geographically distributed; and we propose a decision post-prognostics framework to help engineers to take the optimal decision for maintenance operation in order to minimize cost and time. In order to enhance the postprognostics decision, we propose a framework based on Iot technology for real-time sensing to collect information from equipment and Cloud computing paradigm for resources management and information processing.
Design of an Efficient Full Adder for Low power Applications

Adders are the key building blocks of the ALU circuit. Arithmetic and logical unit plays a very important role in any of the systems. Any changes to adder circuit directly affect on the processor. By using proposed system it gives low power dissipation, more accuracy and at the same time it gives the fast of operation because we are reducing the transistors. The proposed system gives high speed with low area consumption. So compare to existed method the proposed method gives the better performance in terms of power delay and area. Instead of utilizing the more transistors here, we are using less transistors for the same work then we get the less area and at the same time concentrating on power dissipation and performance.
SLOW INTELLIGENCE SYSTEM BASED SOFTWARE TESTING

Testing of software is highly important than developing it, because doing activities without software is better than with erroneous software. Modern software world has plenty of software testing tools which can find errors only. Rectification is very difficult because it requires high level of human cleverness and computerization. Slow Intelligence System can provide intellect as well as mechanization in the area of error correction with the help of different phases such as enumeration, propagation, adaptation, elimination and concentration. This paper is mainly designed to make comfortable for both software developer and testers. So we include a unique concept called Slow Intelligence System which is used to find maximum possibilities of bug during development stage. It is implemented after the process of test cases. So it leads to detect exact possible errors in the software. So the developers can easily rectify their development consequences.
Modification de la virémie du VHC après transplantation rénale

Au cours de la dernière décennie, le dépistage systématique du virus de l’hépatite C (VHC) dans les produits dérivés du sang et l’utilisation de l’érythropoïtéine recombinante pour le traitement de l’anémie chez les insuffisants rénaux terminaux ont permis de considérablement diminuer l’incidence de l’infection par le VHC chez les hémodialysés chroniques et chez les transplantés rénaux. Bien que les cas de transmission nosocomiale du VHC soient rares, la prévalence de l’infection par le VHC reste toujours élevée dans ces deux populations. L’infection chronique par le VHC constitue la cause la plus fréquente des maladies hépatiques après transplantation rénale [1, 2]. Les principaux facteurs de risques d’infection par le VHC chez le transplanté rénal sont la durée de dialyse et le mode de dialyse. Le risque est plus élevé en hémodialyse qu’en dialyse péritonéale et en hémodialyse en centre qu’en hémodialyse à domicile. Le nombre de culots globulaires reçus, les antécédents de greffe rénale, la présence d’une toxicomanie ou d’une infection par le virus de l’hépatite B (VHB) sont d’autres facteurs associés à l’infection par le VHC [1, 2].
LSTM-RNN MULTI-LEVEL ALIGNER DECODERENCODER Aligner LSTM-RNN LSTM-RNN LSTM-RNN go forward two segments to the end of the hall E World State Action Sequence Instruction

We propose a neural sequence-to-sequence model for direction following, a task that is essential to realizing effective autonomous agents. Our alignment-based encoder-decoder model with long short-term memory recurrent neural networks (LSTM-RNN) translates natural language instructions to action sequences based upon a representation of the observable world state. We introduce a multi-level aligner that empowers our model to focus on sentence “regions” salient to the current world state by using multiple abstractions of the input sentence. In contrast to existing methods, our model uses no specialized linguistic resources (e.g., parsers) or taskspecific annotations (e.g., seed lexicons). It is therefore generalizable, yet still achieves the best results reported to-date on a benchmark single-sentence dataset and competitive results for the limited-training multi-sentence setting. We analyze our model through a series of ablations that elucidate the contributions of the primary components of our model.
Aberrant Expression of Perilipins and 11-β-HSD-1 as Molecular Signatures of Metabolic Syndrome X in South East Asians

Metabolics syndrome is common in SE Asian. An hypothesis that aberrant expression of perilipins and 11-βhydroxysteroid dehydrogenase-1 (11-β-HSD-1) enzyme plays a significant role in the development of metabolic syndrome X in Indians is proposed. Thus, methods designed to target perilipins and 11-β-HSD-1 may form a novel approach in the prevention and management of metabolic syndrome X. ©
Sensitivity Analysis in Correlated Bivariate Continuous and Binary Responses

Factorization models for correlated binary and continuous responses are proposed. Full likelihoodbased approach that yields maximum likelihood estimates of the model parameters is used. A common way to investigate if perturbations of model components influence key results of the analysis is to compare the results derived from the original and perturbed models using an influence graph. So small perturbation influence of the correlation parameters of the models on likelihood displacement and a general index of sensitivity (ISNI) are also studied. The model is illustrated using data from arthritis and body mass index data. The effect of systolic blood pressure, gender and age on arthritis and body mass index are investigated.
A GPU Based Approach for As-Planned versus As-Built Comparison in the Scope of Automated BIM Based Construction Progress Monitoring

The delay of construction projects and the resulting cost increase is a common issue in civil engineering projects. These difficulties are often related to poor site supervision and project performance management [66]. The advances in computer science and 3D geometry scanning allow the construction of a dense point cloud which can be used to automatically identify the presence and absence of objects on the construction site. The automation of construction site progress monitoring is still subject to research and includes time-consuming computations. These problems include the alignment of two data sets in a common coordinate system and object recognition which both offer great acceleration potential through parallel data processing [8]. The automatic progress detection pipeline is analysed and an approach for the application of graphics processing units (GPU) to accelerate the processes of rigid point cloud alignment and building component classification is proposed. Implementations based on NVIDIA Cuda originally proposed by Tamaki et al. [58] for point cloud alignment and a new method for progress detection implemented with Microsoft’s C++ AMP are compared with current automated progress tracking procedures. The evaluations are performed using data provided by Braun et al. [13] which was acquired on two different construction sites in Munich.
When Stories Wander : Ideas on the Co-Production of Social Movements ’ Narratives in Transnational Space

Burma/Myanmar has faced change in recent years. Since the elections of 2010, sanctions have been lifted and foreign direct investment has risen significantly. These developments, however, have not always been welcome. Local people from Dawei, for example, have expressed their dissatisfaction over land seizure, lack of compensation and participation in the decision-making processes over the development of a large Special Economic Zone (SEZ). The local grassroots movements can rely in their struggles on a network that is not restricted to Myanmar, but reaches out to exile groups, INGOs and academia in Thailand and beyond. To successfully communicate their stories, these groups rely on transculturally competent individuals re-presenting their stories within and across various (transnational) spaces. The conceptions of space I apply in this context rely heavily on Harvey and Lefebvre. But while these scholars focus more on the production of space(s), I intend to undertake an examination of the utilization of space(s). Hence, the main questions of this ongoing research project are: 1. how do transnational spaces affect the production and representation of social movement narratives? 2. What narratives are re-presented when, where, how and why by transculturally competent individuals from Dawei’s social movement network? 3. What difficulties do these transculturally competent individuals face in translating/re-presenting these narratives? 4. Ultimately, how empowering are these narratives for Dawei’s activist network? The paper itself will not elaborate on any findings (as it is too early in the research process, yet), but on the theoretical framework and its implication for fieldwork offering a hopefully exciting new perspective on the re-production of narratives in transnational spaces like the borderland of Myanmar and Thailand.
Affect and Vulnerability for Psychostimulant Relapse

Psychostimulant dependence (including cocaine, amphetamine, and methamphetamine) is a chronic relapsing disorder with significant personal, health, and financial burdens. Attempts at abstinence produce a severe and protracted withdrawal syndrome characterized by stress hypersensitivity that can facilitate drug craving, anxiety, and dysphoria. These negative withdrawal symptoms can induce relapse, maintaining the addiction cycle. The hippocampus mediates cognitive, emotional, and endocrine responses to stressors. The ventral hippocampus is in a pivotal position to regulate the mesoaccumbal dopamine reward system, and interacts with serotonergic and glucocorticoid systems that mediate anxiety and stress responsiveness. Psychostimulant actions on the hippocampus induce long-term changes to these systems and impact the process of adult neurogenesis in the hippocampus, which may facilitate drug dependence by altering drug-cue learning and emotional regulation. Multiple studies indicate that psychostimulant-induced hippocampal neuroadaptations heighten hippocampal-mesoaccumbal activity to amplify drugand drug-cue responses while persistent dysregulation of hippocampal emotional systems potentiate negative affect. Understanding how psychostimulants modulate the hippocampus to alter hippocampal-mesoaccumbal activity—and how hippocampal neurogenesis influences drug-related memories and reward—is important for identifying novel treatment strategies that can ameliorate negative affect and relapse vulnerability in psychostimulant addiction.
Computer Network Reliability Dynamics Modeling : An Automatic Service Stabilization

Dependence on computer networks is now a reality. The networks are continuously becoming larger, heterogeneous and more complex in size and functionality. Any computer network service relies on several component interactions. This might involve mutually communicating hardware and software. The main task is to guarantee network service in the presence of network faults. In this work we present a design of a model to identify, predict, evaluate and neutralize faults on a computer network. The approach incorporates the capability of Dynamic Bayesian Networks to diagnose, predict and forecast faults and evaluate the magnitude of the network service degradation. The model is complex enough to diagnose and yet simple enough to avoid time and space complexity on the network. Fault thresholds to satisfy probability of error occurrence are established. We present model simulated results to demonstrate the applicability of proposed model.
ABO sensitization and desensitization in renal transplantation

If not adequately removed, the presence of such antibodies is likely to result in severe antibody mediated rejection (AMR) and early graft loss. Antibody mediated rejection or "humoral" rejection was recognized early in the history of transplantation as hyperacute rejection caused by the presence of preformed antibodies ("humors") to donor blood group ABO or HLA antigens. Introduction of pretransplant crossmatch techniques and the use of ABO compatible donors essentially eliminated hyperacute rejection.
AUTONOMOUS TARGETED FLIGHT OF A ROTARY-WING MICRO AERIAL VEHICLE IN INDOOR , GPS-DENIED ENVIRONMENTS

This work focuses on targeted flight of RotaryWing Micro Aerial Vehicles (RW MAV) in indoor environments. In such missions, Global Positioning System (GPS) signals may be unavailable and a map of the environment is unknown prior to the flight. Thus, the MAV should be able to estimate its position, build a map of the environment, and plan an obstacle-free flight path towards the target, while taking into consideration its maneuverability limitations. This paper presents a modular system that comprises required components for these tasks. The proposed methodology relies on using a single laser range scanner. We present the components of the proposed system and algorithms, including a high level module for mission planning and decision making. The system was checked in different simulated environments under the realistic level of disturbances and system noise. The obtained results illustrate the effectiveness of the system for GPS-denied navigation of RW MAVs.
Ycga Therapy in Practice Using Integrative Yoga Therapeutics in the Treatment of Comorbid Anxiety and Depression

This article describes the symptoms, causes, and treatments for anxiety, depression, and comorbid anxiety and depression. It provides strategies for addressing the hyper-arousal or hypo-arousal of the nervous system that is commonly associated with anxiety and depression. It explores research and theory on Yoga's potential for addressing comorbid anxiety and depression, and also discusses the specific approach of the Center for Integrative Yoga Therapeutics, a Yoga therapy center in Boston that specializes in the treatment of Yoga therapy for anxiety, depression, chronic pain disorders, and physical issues such as spinal anomalies or injuries. The described Yoga therapy approach includes a combination of prânâyâma (breathing practices) and Restorative Yoga, a practice of prone or supine postures that is designed to facilitate the relaxation response. K e y w o r d s ; Yoga, depression, anxiety, prânâyâma, psychotherapy, Restorative Yoga