Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuroscientists as Cartographers: Mapping the Crossroads of Gonadal Hormones, Memory and Age Using Animal Models

Cognitive function is multidimensional and complex, and research in multiple species indicates it is considerably impacted by age and gonadal hormone milieu. One domain of cognitive function particularly susceptible to age-related decrements is spatial memory. Gonadal hormones can alter spatial memory, and they are potent modulators of brain microstructure and function in many of the same brain areas affected by aging. In this paper, we review decades of animal and human literature to support a tertiary model representing interactions between gonadal hormones, spatial cognition and age given that: 1) gonadal hormones change with age, 2) age impacts spatial learning and memory, and 3) gonadal hormones impact spatial learning and memory. While much has been discovered regarding these individual tenets, the compass for future aging research points toward clarifying the interactions that exist between these three points, and understanding mediating variables. Indeed, identifying and aligning the various components of the complex interactions between these tenets, including evaluations using basic science, systems, and clinical perspectives, is the optimal approach to attempt to converge the many findings that may currently appear contradictory. In fact, as discoveries are being made it is becoming clear that the findings across studies that appear contradictory are not contradictory at all. Rather, there are mediating variables that are influencing outcome and affecting the extent, and even the direction, of the effects that gonadal hormones have on cognition during aging. These mediating variables are just starting to be understood. By aligning basic scientific discoveries with clinical interpretations, we can maximize the opportunities for discoveries and subsequent interventions to allow individuals to “optimize their aging” and find their own map to cognitive health as aging ensues.
Detection on four continents of dengue fever cases related to an ongoing outbreak in Luanda, Angola, March to May 2013.

In April 2013, ten cases of dengue fever in travellers returning from Luanda, Angola, to five countries on four continents, were reported to the globally distributed GeoSentinel Surveillance network. Dengue virus serotype 1 was identified in two cases. The findings indicate that a major dengue outbreak is currently ongoing in Luanda. This report illustrates how cases from an emerging arboviral epidemic focus can spread internationally and highlights the risk of dissemination of a vector-borne disease into receptive areas
The Imperfect Unbound : A Cognitive Linguistic Approach to Greek Aspect

In Ancient Greek narrative, the imperfect typically presents the state of affairs as ongoing in order to serve as a temporal framework for the occurrence of one or more other states of affairs. However, in narrative we also find a considerable number of imperfects (especially with verbs of motion and verbs of speech) which refer to completed states of affairs. In this paper, it is argued that Cognitive Grammar notions such as construal, temporal scope of view, profile and base can be helpful in describing aspectual contrasts. The imperfects at issue express the narrator’s construal of the state of affairs as unbounded, thereby emphasizing that the state of affairs is of continuing relevance in the subsequent narrative.
Taxonomy Learning Using Word Sense Induction

Taxonomies are an important resource for a variety of Natural Language Processing (NLP) applications. Despite this, the current state-of-the-art methods in taxonomy learning have disregarded word polysemy, in effect, developing taxonomies that conflate word senses. In this paper, we present an unsupervised method that builds a taxonomy of senses learned automatically from an unlabelled corpus. Our evaluation on two WordNet-derived taxonomies shows that the learned taxonomies capture a higher number of correct taxonomic relations compared to those produced by traditional distributional similarity approaches that merge senses by grouping the features of each word into a single vector.
Filtering for personal web information agents

Text filtering algorithms are a main component of a personalized Web information agent. Web information agents, such as WebMate [2] and Syskill & Webert [5], essentially combine text filtering and algorithms that generate the incoming stream of Web documents. However, these algorithms are subject to additional restrictions: negative feedback is considered an inconvenience to the user, the number of training samples is limited, and space is a consideration (thus, storing full text of all examples is discouraged). We examine two types of adaptive filtering that appear suited to our requirements. The first one is based on TFIDF and the second, which was used previously for a Web information agent [5], on a naive Bayes classifier (NBC). We present a new variant on NBC that does not require explicit negative feedback. In a study with TREC data, we find that, while all methods are capable of achieving good performance, they each incur a different penalty.
An examination of speech characteristics under conditions of affective reactivity and variable cognitive load as distinguishing feigned and genuine schizophrenia

iv INTRODUCTION . 1 Schizophrenia . 1 Malingering of Schizophrenia.3 Current methods of assessment of malingering of schizophrenia . 4 Currently utilized assessment tools . 8 Examining Behaviorally-Based Speech Characteristics Under Controlled Conditions of Variable Affective and Cognitive Load to Identify Feigning of Schizophrenia . 10 Communication Disturbances Index . 12 Communication disturbances under conditions of variable affective load . 14 Communication disturbances under conditions of variable cognitive load . 16 Flat affect and alogia as measured using the CANS procedure . 22 Flat affect and alogia under conditions of variable affective load . 22 Flat affect and alogia under conditions of variable cognitive load . 23 Study Design . 23 Hypotheses . 25 METHODS . 29 Participants . 29 Schizophrenia group . 29 Honest control group.30 Feigning group . 30 Speech Tasks . 32 Cognitive load speech task.32 Medium-load cognitive task . 33 High-load cognitive task . 33 Affective reactivity speech task . 34 Post-test Assessment . 34 Dependent Variables . 35 Speech variables.35 CDI . 35 CANS . 36 Cognitive task performance . 39 Analyses . 39 Data distribution.39 Demographic variables . 39 Primary analyses . 40 Feigning group post-task questionnaire . 40 iii Power Analysis . 41 RESULTS . 43 Data Distribution . 43 Demographic Variables . 43 Primary Analyses . 48 Affective reactivity speech task . 48 CDI . 49 Alogia . 51 Blunt Affect . 55 Formant variables.58 Cognitive load speech task.62 CDI . 62 Alogia . 65 Blunt Affect . 71 Formant variables.75 Cognitive task performance . 79 Feigning group post-task questionnaire . 81 DISCUSSION . 85 REFERENCES . 102 APPENDIX A SCHIZOPHRENIA SUMMARY EXCERPTED FROM THE NATIONAL INSTITUTE OF MENTAL HEALTH (2009) . 109 APPENDIX B NEUTRAL SPEECH TASK INSTRUCTIONS . 111 APPENDIX C INSTRUCTIONS FOR AFFECTIVE LOAD SPEECH TASK . 112 APPENDIX D POST-TASK QUESTIONNAIRE FOR THE FEIGNING GROUP . 113 APPENDIX E COPY OF THE LOUISIANA STATE UNIVERSITY INTERNAL REVIEW BOARD’S PROJECT APPROVAL FORM . 114 THE VITA . 123
Examination of aerobic and anaerobic contributions to Yo-Yo intermittent recovery level 1 test performance in female adolescent soccer players

Supervisory Committee Dr. Catherine Gaul, (School of Exercise Science, Physical and Health Education) Supervisor Dr. Lynneth Stuart-Hill, (School of Exercise Science, and Physical and Health Education) Departmental Member Dr. John Anderson, (Educational Psychology and Leadership) Outside Member The purpose of the study was to examine the physiological components related to the Yo-Yo intermittent recovery level 1 (YYIRL1) test in female adolescent soccer players. Eighteen female soccer players (age 16.3 ± .77 years) were tested for maximal oxygen uptake (VO2 max) and ventilatory threshold (VT) on a motorized treadmill. Anaerobic power and capacity were assessed by peak power (W) measured during a counter movement jump (CMJ) and performance on an anaerobic speed test (AST), respectively. As well, participants completed the Multistage 20m Shuttle run (Leger). YYIRL1 performance (meters) was significantly correlated to VO2 max (r = .59), VT (r = .42), Peak Power (r = .41), CMJ height (r = .41), AST (r = .52) and the Leger (r = .72, p < .05). Leger performance (m) was significantly correlated to VO2 max (r = .60) and AST (r = .47, p < .05). Multiple stepwise linear regression equations were run with YYIRL1 and Leger as the dependent variables. VO2 max was the only variable that contributed to prediction of YYIRL1 or Leger performance with R values of . 35 and . 36. The results of the study showed that YYIRL1 performance is related to both aerobic and anaerobic variables, although predominantly maximal aerobic power (VO2 max). It is recommended that the YYIRL1 be used when assessing female adolescent soccer players as the results provide evidence that the YYIRL1 is related to anaerobic variables iv associated with soccer match performance. As well, coaches can efficiently test their athletes in a shorter amount of time compared to the Leger.
Flexible and efficient architecture design for MIMO MMSE-IC linear turbo-equalization

The variety of wireless communication standards and their corresponding applications requires more and more flexible, yet efficient, implementations. The emerging flexibility need induces a new challenge when added to the ever increasing requirements in terms of high throughput and low complexity. This paper presents a design of an application-specific processor dedicated for a minimum mean square error interference cancellation (MMSE-IC) linear equalizer (LE) used in iterative multi-input multi-output (MIMO) turbo receiver. The explored design approach applies static scheduling of datapath control signals. The proposed architecture supports the requirements of flexibility for different MIMO system configurations concerning channel time selectivity and transmission diversity. In order to evaluate the efficiency of the adopted architecture model for this kind of applications and requirements, a fair comparison is conducted with a state-of-the-art application specific instruction-set processor (ASIP) implementation. The obtained results illustrate a significant performance improvement in terms of execution time and implementation area while using identical computational resources and supporting same flexibility parameters.
Intrusion Trace Classification using Inter-element Dependency Models with k-Truncated Generalized Suffix Tree 1

We present a scalable and accurate method for classifying program traces to detect system intrusion attempts. By employing inter-element dependency models to overcome the independence violation problem inherent in the Naive Bayes learners, our method yields intrusion detectors with better accuracy. For efficient counting of n-gram features without losing accuracy, we use a k-truncated generalized suffix tree (k-TGST) for storing n-gram features. The k-TGST storage mechanism enables to scale up the classifiers, which cannot be easily achieved by SVM (Support Vector Machine) based methods that require implausible computing power and resources for accuracy.
Fungal and Bacterial Communities in Indoor Dust Follow Different Environmental Determinants

People spend most of their time inside buildings and the indoor microbiome is a major part of our everyday environment. It affects humans’ wellbeing and therefore its composition is important for use in inferring human health impacts. It is still not well understood how environmental conditions affect indoor microbial communities. Existing studies have mostly focussed on the local (e.g., building units) or continental scale and rarely on the regional scale, e.g. a specific metropolitan area. Therefore, we wanted to identify key environmental determinants for the house dust microbiome from an existing collection of spatially (area of Munich, Germany) and temporally (301 days) distributed samples and to determine changes in the community as a function of time. To that end, dust samples that had been collected once from the living room floors of 286 individual households, were profiled for fungal and bacterial community variation and diversity using microbial fingerprinting techniques. The profiles were tested for their association with occupant behaviour, building characteristics, outdoor pollution, vegetation, and urbanization. Our results showed that more environmental and particularly outdoor factors (vegetation, urbanization, airborne particulate matter) affected the community composition of indoor fungi than of bacteria. The passage of time affected fungi and, surprisingly, also strongly affected bacteria. We inferred that fungal communities in indoor dust changed semi-annually, whereas bacterial communities paralleled outdoor plant phenological periods. These differences in temporal dynamics cannot be fully explained and should be further investigated in future studies on indoor microbiomes.
Bank Capitalization and Cost: Evidence of Scale Economies in Risk Management and Signaling

We amend the standard cost model to account for the role of financial capital in banking. The cost function is conditioned on the level of capital, but we model the demand for financial capital so that it can serve as a cushion against insolvency for potentially risk-averse managers and as a signal of risk for less informed outsiders. Scale economies are then computed without assuming that the bank chooses a level of capitalization that minimizes cost. We find evidence of substantial scale economies and that bank managers are risk averse and use the level of financial capital to signal the level of risk.
Spherical Laser Point Sampling with Application to 3D Scene Genetic Registration

Scene registration of 3D laser rangefinder scans is increasingly being required in applications, such as mobile robotics, that demand a timely response. For speeding up point matching methods, the large amount of range data should be reduced. This sampling, in turn, can have a significant impact on accuracy. In particular, genetic algorithms provide a robust optimization method that avoids local minima for scan matching, but their computational cost grows with the number of points. This paper proposes a new point sampling strategy that considers the spherical scanning process of most sensors to equalize the measure-direction density. This fast sampling method reduces the number of points without loss of relevant scene information. It is experimentally compared with other systematic approaches for the case of actual scene genetic registration.
Internalized transphobia: Exploring perceptions of social messages in transgender and gender-nonconforming adults

ABSTRACT Background: Transgender and gender nonconforming (TGNC) individuals encounter a variety of minority stressors that have yet to be fully articulated or explored within the research literature. The purpose of this study is to better understand internalized stigma—the experience of accepting and internalizing negative social messages and experiences about one's identity—an underexplored minority stressor for TGNC people. Method: We conducted in-depth interviews with 30 diverse TGNC participants using consensual qualitative research (CQR) methodology. Results: Following data saturation and analysis, six distinct themes emerged across participants: (1) TGNC identities are regarded negatively by society; (2) social messages are perceived as originating from the media and religious ideology; (3) TGNC individuals report emotional distress; (4) negative self-perceptions in response to social messages; (5) TGNC individuals report resilience processes in response to negative social messages; and (6) social messages are perceived generally to differentially impact TGNC people of color. Conclusion: Findings highlight the common experience of encountering social marginalization for TGNC individuals. Structural interventions that target pervasive sociocultural messages regarding TGNC identities are warranted.
Compressive sensing for in depth focusing in 3D automotive imaging radar

Today, there is a growing attention to automotive sensors monitoring systems, in order to make them an effective and valuable aid in situations of danger, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in poor weather conditions (such as fog, rain) and in presence of smoke. This limitation can be overcome by using radar sensors. In particular, imaging radar are gaining interest in the framework of Driver Assistance Systems (DAS). In this paper we propose a novel radar signal processing technique, based on Compressive Sensing (CS) theory, to perform the imaging of two or more targets on the same line of sight, greatly improving the performances of a radar DAS. After a brief description of the proposed methodology, case studies are presented in order to evaluate the performances of the technique.
PGH1, the Precursor for the Anti-Inflammatory Prostaglandins of the 1-series, Is a Potent Activator of the Pro-Inflammatory Receptor CRTH2/DP2

Prostaglandin H1 (PGH1) is the cyclo-oxygenase metabolite of dihomo-γ-linolenic acid (DGLA) and the precursor for the 1-series of prostaglandins which are often viewed as “anti-inflammatory”. Herein we present evidence that PGH1 is a potent activator of the pro-inflammatory PGD2 receptor CRTH2, an attractive therapeutic target to treat allergic diseases such as asthma and atopic dermatitis. Non-invasive, real time dynamic mass redistribution analysis of living human CRTH2 transfectants and Ca2+ flux studies reveal that PGH1 activates CRTH2 as PGH2, PGD2 or PGD1 do. The PGH1 precursor DGLA and the other PGH1 metabolites did not display such effect. PGH1 specifically internalizes CRTH2 in stable CRTH2 transfectants as assessed by antibody feeding assays. Physiological relevance of CRTH2 ligation by PGH1 is demonstrated in several primary human hematopoietic lineages, which endogenously express CRTH2: PGH1 mediates migration of and Ca2+ flux in Th2 lymphocytes, shape change of eosinophils, and their adhesion to human pulmonary microvascular endothelial cells under physiological flow conditions. All these effects are abrogated in the presence of the CRTH2 specific antagonist TM30089. Together, our results identify PGH1 as an important lipid intermediate and novel CRTH2 agonist which may trigger CRTH2 activation in vivo in the absence of functional prostaglandin D synthase.
Informative narrowcasting with consumer search

Improved consumer addressability in electronic markets allows vendors to send focused promotional messages to specific customers, facilitating a targeted advertising approach that we call "narrowcasting". We characterize a rational consumer's market participation decision and identify a narrowcasting firm's optimal targeting decision when buyers face nontrivial search costs. In the special case where consumer reservation utility is relatively low and search cost is relatively high, consumers will neither search nor purchase blindly without search, and the market breaks down. Our main contribution here is to show that narrowcasting can help a seller revitalize this market by replacing learning by consumers with learning and targeting by the seller.
SKYPEER: Efficient Subspace Skyline Computation over Distributed Data

Skyline query processing has received considerable attention in the recent past. Mainly, the skyline query is used to find a set of non dominated data points in a multidimensional dataset. While most previous work has assumed a centralized setting, in this paper we address the efficient computation of subspace skyline queries in large-scale peer-to-peer (P2P) networks, where the dataset is horizontally distributed across the peers. Relying on a super-peer architecture we propose a threshold based algorithm, called SKYPEER, which forwards the skyline query requests among peers, in such a way that the amount of transferred data is significantly reduced. For efficient subspace skyline processing, we extend the notion of domination by defining the extended skyline set, which contains all data elements that are necessary to answer a skyline query in any arbitrary subspace. We prove that our algorithm provides the exact answers and we present optimization techniques to reduce communication cost and execution time. Finally, we provide an extensive experimental evaluation showing that SKYPEER performs efficiently and provides a viable solution when a large degree of distribution is required.
Nodesat, an Arithmetical Tactic for the Coq Proof Assistant Nodesat, an Arithmetical Tactic for the Coq Proof Assistant

RRsumm Ce rapport ddcrit l'implantation de Nodesat, une proccdure de dd-cision arithmmtique pour le systtme d'aide la preuve Coq, qui est ddvelopp l'INRIA (Rocquencourt) et l''cole Normale Suprieure de Lyon. partir d'un systtme de comparaisons entre expressions arithmmtiques, l'algorithme construit un graphe orientt et valuu dans lequel il essaye de mettre en vidence des cycles de poids strictement positif, ce qui revient vriier le systtme initial. Lorsque la proccdure vriie ce systtme, un terme de preuve est construit partir de ce qui est en fait une trace des diiirentes tapes de l'algorithme. Il s'agit pour le systtme Coq d'une premiire tentative d''criture de proccdure de ddcision arithmmtique, un outil qui se rrvle indispensable dans le cadre du ddveloppement d'applications industrielles. Abstract This report describes the implementation of Nodesat, an arith-metical decision procedure for the Coq proof assistant, a system devel-opped at INRIA (Rocquencourt) and at the cole Normale Suprieure (Lyon). The algorithm builds a directed, valuated graph representing a system of comparisons between arithmetical expressions, and looks for a strictly positive cycle graph in order to check the validity of the system. If the procedure succeeds, a proof term is generated, which is basically a trace of the various steps of the algorithm. This attempt is a rst step towards implementation of an arithmetical decision procedure for Coq, a feature that turns out very useful for industrial applications.
Fathers' Autonomy Support and Social Competence of Sons and Daughters

Relations between paternal autonomy support and four aspects of adolescent social competence and responsibility at age 16 were examined using data from the NICHD Study of Early Child Care and Youth Development. With controls on maternal autonomy support, significant relations were observed between paternal autonomy support and three of the four aspects of social behavior examined for daughters (but not sons). For daughters, the influence of paternal autonomy support was moderated by family conflict for both resistance to peer pressure and responsible behavior. The temperament of daughters moderated the relation between paternal autonomy support and resistance to peer pressure, as well. Findings were interpreted with respect to the dynamics of parent–child relationships and increasing individuation during adolescence.
Digital Object Lifecycle in dLibra Digital Library Framework

In this article we describe support for a digital objects lifecycle, which we have created during our digital library re lat d works. Basing on our experiences from WBC digital library, we intend to sh ow how a properly constructed lifecycle can extend the functionality of digital libraries for both library readers and librarians responsible for main taining content gathered in a digital library.