Miracle-dz/UniFAR-FTUs huggingface dataset:
Geographical accessibility to gambling venues and pathological gambling: an econometric analysis of pachinko parlours in Japan

Abstract The relationship between geographical accessibility to gambling venues and the prevalence of pathological gambling is still unknown. This study aimed to reveal this relationship in Japan as well as its variation by subpopulation. A cross-sectional study was conducted, based on an original web-based survey to understand the level of pathological gambling depending on accessibility to pachinko parlours. Pathological gamblers were measured using the Japanese version of the South Oaks Gambling Screen. Accessibility to gambling venues was defined as the number of pachinko parlours within a 1.5 km radius from home. Moreover, the study adopted the instrumental variable approach to solve the potential endogeneity problem. The results showed that the accessibility was not significantly associated with pathological gambling in general, but that the effects of accessibility varied by subpopulation. Accessibility was significantly and positively correlated with pathological gambling for men and people in low-income areas, but this was not so for women and people in high-income areas. The study’s findings show the importance of the neighbourhood environment and could help in implementing more effective interventions for pathological gamblers.
A VTS-based feature compensation approach to noisy speech recognition using mixture models of distortion

Recently, we proposed an approach to irrelevant variability normalization (IVN) based joint training of a reference Gaussian mixture model (GMM) for feature compensation and hidden Markov models (HMMs) for acoustic modeling by using a vector Taylor series (VTS) based feature compensation technique, where single-component densities are used to model additive noise and convolutional distortion respectively. In this paper, mixtures of densities are used to enhance the distortion model. New formulations for maximum likelihood (ML) estimation of distortion model parameters, and minimum mean squared error (MMSE) estimation of clean speech are derived and presented. A comparative study is conducted under three “training-testing” conditions on Aurora3 database. Experimental results confirm that the proposed mixture models of distortion can achieve significant performance gain compared with the traditional distortion modeling.
FlowTwist: efficient context-sensitive inside-out taint analysis for large codebases

Over the past years, widely used platforms such as the Java Class Library have been under constant attack through vulnerabilities that involve a combination of two taint-analysis problems: an integrity problem allowing attackers to trigger sensitive operations within the platform, and a confidentiality problem allowing the attacker to retrieve sensitive information or pointers from the results of those operations. While existing static taint analyses are good at solving either of those problems, we show that they scale prohibitively badly when being applied to situations that require the exploitation of both an integrity and confidentiality problem in combination. The main problem is the huge attack surface of libraries such as the Java Class Library, which exposes thousands of methods potentially controllable by an attacker. In this work we thus present FlowTwist, a novel taint-analysis approach that works inside-out, i.e., tracks data flows from potentially vulnerable calls to the outer level of the API which the attacker might control. This inside-out analysis requires a careful, context-sensitive coordination of both a backward and a forward taint analysis. In this work, we expose a design of the analysis approach based on the IFDS algorithm, and explain several extensions to IFDS that enable not only this coordination but also a helpful reporting of error situations to security analysts. Experiments with the Java Class Library show that, while a simple forward taint-analysis approach does not scale even with much machine power, FlowTwist's algorithm is able to fully analyze the library within 10 minutes.
Developing a System for Recognizing the Emotional States Using Physiological Devices

Recognizing emotional states is becoming a majorpart of a user's context for wearable computing applications. The system should be able to acquire a user's emotional states by using physiological sensors. We want to develop a personal emotional states recognition system that is practical, reliable, and can be used for health-care related applications. We propose to use the eHealth platform [1] which is a ready-made, light weight, small and easy to use device for recognizing a few emotional states like 'Sad', Dislike', 'Joy', 'Stress', 'Normal', 'No-Idea', 'Positive' and Negative' using decision tree (J48)and IBK classifiers. In this paper, we present an approach tobuild a system that exhibits this property and provides evidence based on data for 8 emotional states collected from 24 different subjects. Our results indicate that the system has an accuracy rate of approximately 97%. In our work, we used three physiological sensors (i.e. 'BloodVolume Pulse', 'Galvanic Skin Response' and 'SkinTemperature') in order to recognize emotional states (i.e.stress, joy/happy, sad, normal/neutral, dislike, no-idea, positive and negative).
Intentions in Equilibrium

Intentions have been widely studied in AI, both in the context of decision-making within individual agents and in multi-agent systems. Work on intentions in multi-agent systems has focused on joint intention models, which characterise the mental state of agents with a shared goal engaged in teamwork. In the absence of shared goals, however, intentions play another crucial role in multi-agent activity: they provide a basis around which agents can mutually coordinate activities. Models based on shared goals do not attempt to account for or explain this role of intentions. In this paper, we present a formal model of multi-agent systems in which belief-desire-intention agents choose their intentions taking into account the intentions of others. To understand rational mental states in such a setting, we formally define and investigate notions of multi-agent intention equilibrium, which are related to equilibrium concepts in game theory.
BIAS: Bioinformatics Integrated Application Software

MOTIVATION We introduce a development platform especially tailored to Bioinformatics research and software development. BIAS (Bioinformatics Integrated Application Software) provides the tools necessary for carrying out integrative Bioinformatics research requiring multiple datasets and analysis tools. It follows an object-relational strategy for providing persistent objects, allows third-party tools to be easily incorporated within the system and supports standards and data-exchange protocols common to Bioinformatics. AVAILABILITY BIAS is an OpenSource project and is freely available to all interested users at http://www.mcb.mcgill.ca/~bias/. This website also contains a paper containing a more detailed description of BIAS and a sample implementation of a Bayesian network approach for the simultaneous prediction of gene regulation events and of mRNA expression from combinations of gene regulation events. CONTACT hallett@mcb.mcgill.ca.
Reactive Nitrogen Species-Induced Cell Death Requires Fas-Dependent Activation of c-Jun N-Terminal Kinase

ABSTRACT Nitrogen dioxide is a highly toxic reactive nitrogen species (RNS) recently discovered as an inflammatory oxidant with great potential to damage tissues. We demonstrate here that cell death by RNS was caused by c-Jun N-terminal kinase (JNK). Activation of JNK by RNS was density dependent and caused mitochondrial depolarization and nuclear condensation. JNK activation by RNS was abolished in cells lacking functional Fas or following expression of a truncated version of Fas lacking the intracellular death domain. In contrast, RNS induced JNK potently in cells expressing a truncated version of tumor necrosis factor receptor 1 or cells lacking tumor necrosis factor receptor 1 (TNF-R1), illustrating a dependence of Fas but not TNF-R1 in RNS-induced signaling to JNK. Furthermore, Fas was oxidized, redistributed, and colocalized with Fas-associated death domain (FADD) in RNS-exposed cells, illustrating that RNS directly targeted Fas. JNK activation and cell death by RNS occurred in a Fas ligand- and caspase-independent manner. While the activation of JNK by RNS or FasL required FADD, the cysteine-rich domain 1 containing preligand assembly domain required for FasL signaling was not involved in JNK activation by RNS. These findings illustrate that RNS cause cell death in a Fas- and JNK-dependent manner and that this occurs through a pathway distinct from FasL. Thus, avenues aimed at preventing the interaction of RNS with Fas may attenuate tissue damage characteristic of chronic inflammatory diseases that are accompanied by high levels of RNS.
Improving Cloze Test Performance of Language Learners Using Web N-Grams

We study the effectiveness of search engines for common usage, a new category of search engines that exploitn-gram frequencies on the web to measure the commonness of a formulation, and that allow their users to submit wildcard queries about formulation uncertainties often encountered in the process of writing. These search engines help to resolve questions on common prepositions following verbs, common synonyms in given contexts, and word order difficulties, to name only a few. Until now, however, it has never been shown that search engines for common usage have a positive impact on writing performance. Our contribution is a large-scale user study with 121 participants using the Netspeak search engine to shed light on this issue for the first time. Via carefully designed cloze tests we show that second language learners who have access to a search engine for common usage significantly and effectively improve their test performance as opposed to not using them.
S6K1 in the Central Nervous System Regulates Energy Expenditure via MC4R/CRH Pathways in Response to Deprivation of an Essential Amino Acid

It is well established that the central nervous system (CNS), especially the hypothalamus, plays an important role in regulating energy homeostasis and lipid metabolism. We have previously shown that hypothalamic corticotropin-releasing hormone (CRH) is critical for stimulating fat loss in response to dietary leucine deprivation. The molecular mechanisms underlying the CNS regulation of leucine deprivation–stimulated fat loss are, however, still largely unknown. Here, we used intracerebroventricular injection of adenoviral vectors to identify a novel role for hypothalamic p70 S6 kinase 1 (S6K1), a major downstream effector of the kinase mammalian target of rapamycin, in leucine deprivation stimulation of energy expenditure. Furthermore, we show that the effect of hypothalamic S6K1 is mediated by modulation of Crh expression in a melanocortin-4 receptor–dependent manner. Taken together, our studies provide a new perspective for understanding the regulation of energy expenditure by the CNS and the importance of cross-talk between nutritional control and regulation of endocrine signals.
Robust integrated lateral guidance and control of UAVs

In this paper, a novel guidance scheme is presented for UAVs using the Integrated Guidance and Control (IGC) framework. The proposed guidance scheme is derived using H∞ Loop Shaping Design Procedure (LSDP). To recover from an initial cross track error, the proposed guidance algorithm produces such aileron commands that ensure the roll maneuvers without saturating the roll angle. The shaping of the open loop plant is carried out using the pre and post weights and then the robust stabilization is done by using the normalized left coprime factor uncertainty. The performance and robustness of the system are verified by introducing parametric uncertainties in to the system model. The results of the proposed scheme are verified by implementing it on a complete 6-DOF nonlinear model in the presence of wind disturbance. The simulation results indicate the effectiveness and robustness of the proposed guidance algorithm.
Approche communicationnelle des compétences managériales en secteur santé : les cadres de santé du CHU de Grenoble face aux injonctions et aux dispositifs communicationnels issus de la notion de « nouveau management public »

Dans ce travail, il s’agit de developper les premiers axes problematiques d’une reflexion longue sur les mutations communicationnelles des competences manageriales des cadres de sante. Il s’agit, en outre, d’adopter une vision theorique critique concernant les enjeux pratiques, theoriques et ideologiques des formes de communications actuelles dans les organisations publiques. Nous abordons notamment la question de la gestionnarisation du service publique, induite par un contexte favorable a son developpement, issue, selon nous, du « nouvel esprit du capitalisme » (Boltanski, Chiapello, 1999), d’un point de vue communicationnel, relativement a notre ancrage theorique en Sciences de l’Information et de la Communication.
Sentiment Analysis: Towards a Tool for Analysing Real-Time Students Feedback

Students' real-time feedback has numerous advantages in education, however, analysing feedback while teaching is both stressful and time consuming. To address this problem, we propose to analyse feedback automatically using sentiment analysis. Sentiment analysis is domain dependent and although it has been applied to the educational domain before, it has not been previously used for real-time feedback. To find the best model for automatic analysis we look at four aspects: preprocessing, features, machine learning techniques and the use of the neutral class. We found that the highest result for the four aspects is Support Vector Machines (SVM) with the highest level of preprocessing, unigrams and no neutral class, which gave a 95 percent accuracy.
Evaluation of supervisory vs. peer-peer interaction with human-robot teams

We submit that the most interesting and fruitful human-robot interaction (HRI) may be possible when the robot is able to interact with the human as a true team member, rather than a tool. However, the benefits of shared control can all too easily be overshadowed by challenges inherent to blending human and robot initiative. The most important requirements for peer-peer interaction are system trust and ability to predict system behavior. The human must be able to understand the reason for and effects of robot initiative. These requirements can only be met through careful application of human factors principles and usability testing to determine how users interact with the system. This paper discusses the recent human participant usability testing, which took our current implementation to task using a search and rescue scenario within a complex, real-world environment. The purpose of testing was to examine how human operators work with the robotic system at each level of autonomy, and how interaction with the robot should be structured to enable situation awareness and task completion. Analyses revealed that our architecture equally supported situation awareness and target detection by novices and experts, although experienced users were more likely to have more performance expectations of the interface. Results also had implications regarding the ability of participants to effectively utilize the collaborative workspace and, most importantly, their ability to understand and willingness to accept robot initiative.
Sea Duck Joint Venture Annual Project Summary for Endorsed Projects

We obtained blood samples from females trapped at the nest during 2001 – 2003, and feather samples from 113 nests from Aropuk Lake across three years (2002 – 2004). We screened 70 microsatellite loci and typed 29 individuals from Aropuk Lake at 12 variable loci, to create a baseline dataset (data not shown). Following informal exploration of data from these loci, we selected 8 (Table 1) for further consideration, based on published guidelines for choosing markers for genetic tagging studies (Paetkau 2000, 2003). These 8 loci were initially selected because they demonstrated the highest mean expected heterozygosity (HE), high resolution, with few or no 1 base-pair (bp) insertions, no initial indication of null alleles or allelic dropout, and relatively high variability (Talbot et al. 2004).
The “Artificial Artery” as In Vitro Perfusion Model

Metabolic stimuli, pressure, and fluid shear stress (FSS) are major mediators of vascular plasticity. The exposure of the vessel wall to increased laminar FSS is the main trigger of arteriogenesis, the remodelling of pre-existent arterio-arteriolar anastomoses to functional conductance arteries. In this study, we have used an in vitro bioreactor to investigate cell-specific interactions, molecular mechanisms as well as time-dependent effects under laminar FSS conditions. This bioreactor termed “artificial artery” can be used for screening potential arterio-protective substances, pro-arteriogenic factors, and for investigating biomarkers of cardiovascular diseases such as cardiac diseases. The bioreactor is built up out of 14 hollow fiber membranes colonized with endothelial cells (HUVECs) on the inside and smooth muscle cells (HUASMCs) on the outside. By means of Hoechst 33342 staining as well as immunocytochemistry of ß-catenin and α-smooth-muscle-actin, a microporous polypropylene membrane was characterized as being the appropriate polymer for co-colonization. Defined arterial flow conditions (0.1 N/m2 and 3 N/m2), metabolic exchange, and cross-talk of HUVECs and HUASMCs through hollow fibers mimic physiological in vivo conditions of the vasculature. Analysing mono- and co-culture secretomes by MALDI-TOF-TOF mass spectrometry, we could show that HUVECs secreted Up4A upon 3 N/m2. A constant cellular secretion of randomly chosen peptides verified viability of the “artificial artery” for a cultivation period up to five days. qRT-PCR analyses revealed an up-regulation of KLF2 and TIMP1 as mechano-regulated genes and demonstrated arterio-protective, homeostatic FSS conditions by a down-regulation of EDN1. Expression analyses of VWF and EDN1 furthermore confirmed that RNA of both cell types could separately be isolated without cross-contamination. CCND1 mRNA expression in HUVECs did not change upon FSS indicating a quiescent endothelial phenotype. Taken together, the “artificial artery” provides a solid in vitro model to test pharmacological active compounds for their impact on arterio-damaging or arterio-protective properties on vascular response.
Organizational Models for Non-Core Processes Management: A Classification Framework

This study investigates the impact of different organizational models for the management of non-core processes in the facility management (FM) industry and seeks to suggest which is the best in terms of strategic and operative advantages and disadvantages. A literature analysis of the empirical evidence as to business process outsourcing and, in particular, as to the practices of the FM business sector has been carried out. The analysis has allowed us to identify a total of 11 organizational models that are a consequence of five different strategic approaches. A comprehensive classification framework of the strategies and organizational models on the basis of two dimensions is proposed: the organizational role of a non-core processes manager (called a ‘facility manager’) and the typology of non-core process/service providers. The framework enables the identification and the explanation of the main advantages and disadvantages of each strategy and to highlight how a company should coherently choose an organizational model on the basis of (a) the specialization/complexity of the non-core processes, (b) the focus on core processes, (c) its inclination towards know-how outsourcing, and (d) the desired level of autonomy in the management of non-core processes.
Robust Mixed-Size Placement by Recursive Legalized Bipartitioning ⁄

Anovelandverysimplecorrect-by-constructiontop-downmethodologyformixed-sizeplacement is presented. The PolarBear algorithm combines recursive cutsize-driven partitioning withfastandscalablelegalizationofeveryplacementsubproblemgeneratedbyeverypartitioning. Thefeedbackprovidedbythelegalizeratallstagesofpartitioningimprovesflnalplacement qualitysigniflcantlyonstandardIBMbenchmarksanddramaticallyonlow-white-spaceadaptationsofthem. ComparedtoFengShui2.6andCapo9.0, PolarBearistheonlytoolthatcan consistently flnd high-quality placements for benchmarks with less than 5% white space. With whitespaceat12%, PolarBearbeatsCapo9.0by6%inaveragetotalwirelengthwhileFeng Shui2.6frequentlyfailstoflndlegalplacementsaltogether. With20%whitespace, PolarBear still beats Capo 9.0 by 10% and FengShui 2.6 by 2% in average total wirelength, using very similar runtime.
Asymptotically Near-Optimal Planning With Probabilistic Roadmap Spanners

Asymptotically optimal motion planners guarantee that solutions approach optimal as more iterations are performed. A recently proposed roadmap-based method, i.e., the <formula formulatype="inline"><tex Notation="TeX">$\hbox{\tt PRM}^{*}$ </tex></formula> approach, provides this desirable property and minimizes the computational cost of generating the roadmap. Even for this method, however, the roadmap can be slow to construct and quickly grows too large for storage or fast online query resolution, especially for relatively high-dimensional instances. In graph theory, there are algorithms that produce sparse subgraphs, which are known as graph spanners, that guarantee near-optimal paths. This paper proposes different alternatives for interleaving graph spanners with the asymptotically optimal <formula formulatype="inline"><tex Notation="TeX">$\hbox{\tt PRM}^{*}$</tex></formula> algorithm. The first alternative follows a sequential approach, where a graph spanner algorithm is applied to the output roadmap of <formula formulatype="inline"> <tex Notation="TeX">$\hbox{\tt PRM}^{*}$</tex></formula>. The second one is an incremental method, where certain edges are not considered during the construction of the roadmap as they are not necessary for a roadmap spanner. The result in both cases is an asymptotically near-optimal motion planning solution. Theoretical analysis and experiments performed on typical, geometric motion planning instances show that large reductions in construction time, roadmap density, and online query resolution time can be achieved with a small sacrifice of path quality through roadmap spanners.
Nonlinear system identification by means of mixtures of linear-in-the-parameters nonlinear filters

In this paper, we deal with the unconstrained linear combination of the outputs of linear-in-the-parameters (LIP) nonlinear filters. We first analyze its steady-state performance using the Wiener theory of the optimal filter. Then, the implementation of the mixture of a linear and an even mirror Fourier nonlinear filter is considered. A simple adaptation algorithm for the filters in the mixture scheme that does not require the preliminary choice of the step sizes, as in the case of usual adaptation algorithms, is proposed. The presented approach is useful for the identification of time-varying nonlinear systems, exploiting the orthogonality of the basis functions of the constituent filters in presence of a white uniform input signal in [-1, +1]. Simulations results are reported showing the good performance obtained in these cases.