Miracle-dz/UniFAR-FTUs huggingface dataset:
Alcohol-Seeking Behavior

Both the hormones of the hypothalamic-pituitary-adrenal (HPA) axis and the endogenous opioid system are activated in response to stress as well as after alcohol consumption, supporting the hypothesis that stress can influence both alcohol consumption and craving for alcohol. Activation of the HPA axis by stress or alcohol results in the production of glucocorticoid hormones, such as cortisol. Those hormones, in turn, are important for the release of the brain chemical dopamine in certain brain areas that are associated with the rewarding and reinforcing effects of alcohol and other drugs. Alcohol-induced release of certain endogenous opioids similarly results in dopamine release in those brain regions. Through this mechanism, both the HPA axis and the endogenous opioid system may influence alcohol consumption. Consequently, genetically determined differences in the activities of the HPA axis and endogenous opioid system may help determine a person’s alcohol consumption level and vulnerability to alcoholism.
Effect of Emotion on Item Memory and Source Memory

The effect of emotion on memory has increasingly received attention from cognitive psychologists over the past several decades.This article is a summary of the research that I conducted for my dissertation under the supervision of Professor Xiaolan Fu in the Institute of Psychology,Chinese Academy of Sciences.My research was concerned with the effect of emotion on item memory and source memory for Chinese words.When emotion was elicited by emotional words during encoding,the main findings were:1) Negative emotion enhanced free recall,whereas there was only a trend that positive emotion enhanced free recall.2) Negative emotion reduced general recognition,whereas positive emotion had no effect on general recognition.Additionally,neither positive nor negative emotion affected recollection.However,negative emotion reduced familiarity,and positive emotion had no effect on familiarity.3) Neither positive nor negative emotion affected source memory(i.e.,memory for font colors of words). When emotion was elicited by emotional video clips after encoding,the main findings were:1) For females,negative emotion enhanced consolidation of item memory.However,for males,neither negative emotion nor positive emotion had an effect on item memory.2) Neither negative nor positive emotion had an effect on source memory.The above findings have theoretical significance for the establishment of the relationship between emotion and memory consolidation,and have practical implications for improving students' memory consolidation in educational settings.
Without conscious effort: The ability of nontonal language speakers to discriminate lexical and nonlexical tones

Abstract. Tonal language speakers perform well in discriminating lexical tones in their own language. However, it is unknown whether their proficiency extends to the nonlinguistic context. This study compared the accuracy of performance of Cantonese and English speakers on tonal discrimination tasks. The findings demonstrated that the Cantonese speakers performed better than the English speakers in discriminating lexical tones in the linguistic context, even when the stimuli could not be consciously perceived. Nevertheless, there was no significant performance difference between Cantonese and English speakers in discriminating nonlexical tones in the nonlinguistic context. The results demonstrate the excellence of the linguistic component to tolerate noise. Moreover, the contrastive findings obtained in this study suggest that the transferability of the experience with lexical tones to nonlinguistic activities can be highly contextualized.
Advanced Techniques for Mobile Localization and Tracking

There is an exponential growth of smartphone usage and computational capability in the past several years. The widespread usage of smartphones provides a unique opportunity for large-scale monitoring of urban and suburban environments. For example, aggregated and anonymous localization and tracking of smartphones of a subset of people in a particular area enable several applications such as monitoring street traffic flow and crowd movement. With the increasing computational and sensing capability of smartphones, it is now possible to build compute-intensive applications such as high-accuracy localization of a smartphone by video analysis, which can be more accurate and offers and attractive complement to the GPS. How- ever, there are many challenges for building these applications effectively, such as low-level and domain-specific computation methods, accuracy, resource cost, and efficient system and network architecture. In this dissertation, we address some of these fundamental challenges and develop three systems in the context of localization and tracking. First, we present a system for tracking unmodified smartphones using Wi-Fi. In this system, we use hidden-Markov-model along with map topology and signal strength characteristics to achieve high accuracy localization and tracking in challenging conditions such as sparse packet reception, signal strength variation, and a variable number of received packets. Furthermore, we use low-level Wi-Fi protocol features involving association process and management frames to obtain additional packets from a passing smartphone for improved tracking accuracy. Second, we present an online GPS tracking system that transmits the GPS locations to a central server over a cellular uplink with controllable location error, data usage budget, and reporting delay. We also show the first fundamental three-way trade-off between error, budget, and delay in such a system. Finally, we present a system for sub-meter localization of smartphones using video analysis. In this system, we use the 3D reconstruction of the environment and efficient image feature matching to obtain sub-meter accurate localization in both indoor and outdoor environments. Here, we optimize various stages of the localization pipeline such as compression of the 3D reconstruction and features, and interleaved matching and tracking to achieve near real-time operation.
Grünes Licht für pädagogische Konstruktionsgrammatik – Denn: Linguistik ist nicht (mehr) nur Chomsky

This article argues in favour of a constructionist approach to foreign language teaching. It provides a survey of the basic principles of the linguistic theories that have become known under such labels as cognitive linguistics, usage-based approach or construction grammar that envisage language as a network of constructions (learned form-meaning-pairings). Particular emphasis is placed upon collostructional analysis. Finally, the paper sets out to show why the model of language underlying these approaches can be fruitfully applied to foreign language teaching
Recurrent Neural Network and Rapidly-exploring Random Tree Path Planning Adaptable to Environmental Change

We propose a robot path planning method adaptable to environmental change combining RRT and LSTM network. In this method, assuming multiple environments, a large amount of routes are generated by the RRT method and learning is performed using the LSTM network. We also try to adapt to environmental changes by using CAE during learning. By the proposed method, we perform the difficulty of a general random base method, that is, “generate reproducible route” at high speed. In addition, it is possible to generate routes adapted to small environmental changes.
Prosody in Automatic Speaker Recognition: Applications in Biometrics and Voice Imitation

Over the last years, automatic speaker recognition (ASR) has undergone an increasing use in applications such as access control, forensics and system customisation, among others, relying traditionally on short-term features related to the spectrum of the voice. However, since human speaker recognition uses other sources of information like prosody, there is reason to believe that they can play an important role in the ASR task, adding complementary knowledge and improving accuracy. Furthermore, humans are able to identify others from voice even when their voices are disguised, so that the question arises as to how vulnerable ASR systems are against voice disguises such as human imitation or artificial conversion, which are potential threats to security systems that rely on ASR. This book provides a detailed analysis of the use of prosody in a multimodal biometric environment and the robustness of ASR systems against voice imitations and synthetic converted voices. These analyses should help shed some light on the exciting field of biometrics and voice imitation, and should be especially useful to researchers having none or some expertise in Linguistics and Signal Processing fields.
Analysis Web Mining Technology to Predict the User Behavior in Multi-Media

The fast growth of the Internet, we have entered a period of information explosion, there is a considerable measure of repetitive data in the Network. How to extract a useful part of this information from the massive information resources, dissecting the huge measure of data lastly get the potential information we need to extracted. Web mining innovation appeared and spared out the human from the data sea. This paper will break down the acknowledgment of Web content mining and Web structure mining, their essential algorithms standards, and their application areas.
A Machine Learning Approach to Reveal the NeuroPhenotypes of Autisms

Although much research has been undertaken, the spatial patterns, developmental course, and sexual dimorphism of brain structure associated with autism remains enigmatic. One of the difficulties in investigating differences between the sexes in autism is the small sample sizes of available imaging datasets with mixed sex. Thus, the majority of the investigations have involved male samples, with females somewhat overlooked. This paper deploys machine learning on partial least squares feature extraction to reveal differences in regional brain structure between individuals with autism and typically developing participants. A four-class classification problem (sex and condition) is specified, with theoretical restrictions based on the evaluation of a novel upper bound in the resubstitution estimate. These conditions were imposed on the classifier complexity and feature space dimension to assure generalizable results from the training set to test samples. Accuracies above 80% on gray and white matter tissues estimated from voxel-based morphometry (VBM) features are obtained in a sample of equal-sized high-functioning male and female adults with and without autism ( N = 120 , n = 30 /group). The proposed learning machine revealed how autism is modulated by biological sex using a low-dimensional feature space extracted from VBM. In addition, a spatial overlap analysis on reference maps partially corroborated predictions of the "extreme male brain" theory of autism, in sexual dimorphic areas.
Kinetic studies on the reaction of p-Toluenesulfonyl chloride with α-Hydroxy acids in the presence of pyridine in acetonitrile

The kinetic studies on the reaction of p-Toluenesulfonyl Chloride (TsCl) with α-Hydroxy acids in the presence of Pyridine under equimolar and pseudo first order conditions in Acetonitrile at 20, 30 and 40 ̊C have been studied by conductometric method. The rate constants were obtained by the least square method. Kinetic data shows that the reaction follows second order kinetics and first order with respect to each of the reactants. The attacking nucleophile is found to be a hydrogen bonded ion pair. Thermodynamic parameters have been evaluated by using kinetic data. The entropy of activation is negative as expected for bimolecular reactions. Kinetic data and product analysis indicate that the reaction proceeds through direct nucleophilic attack on the sulfur center.
Understanding the post-colonial India’s culture: A juxtaposition of modern and traditional values

This conceptual paper aims to understand post-colonial India’s culture, specifically the changes brought about due to economic liberalisation in the 1990s. Although traditionally India was classified as a collectivist society, contemporary Indian researchers proposed that current India is a mix of collectivism and individualism. Indians tend be collectivists in matter relating to the family and individualists in matters relating to work. While the caste system was abolished several decades back, hierarchical relationships continue to exist and translate into paternalism in the workplace. Paternalism refers to father-like behaviour of the superiors towards their subordinates. However, this perhaps was not a detrimental attitude as subordinates considered the workplace as family; willingly accepted authority; were loyal and deferential; and would go out of their way to help the superior in their personal life. Thus, post-colonial Indian culture is a complex and contradictory mix of modern and traditional values which often come into conflict and yet complement each other in a way that perhaps provides Indians with a unique competitive edge.
Of bad hombres and nasty women; the quality of the live closed captioning in the 2016 US final presidential debate

ABSTRACT After decades of dedicating good efforts to increase the amount of television programing accessible to the hearing impaired, awareness about the need to deliver better closed captions has grown in the last years. As a result, the focus has been moved from the quantity to the quality of the accessibility services provided. In an attempt to explore the subtitles currently delivered on television, this paper presents the main findings of a study aimed at analyzing the quality of the live closed captions provided during one of the most relevant political events of 2016: the final presidential debate in the United States. A corpus of more than 9,400 captions was analyzed according to the quality criteria defined by the Federal Communications Commission. The results obtained shed light on the completeness, placement, synchronicity and accuracy of the captions, but they also elicit interesting questions in terms of reception.
Robot vision localization system based on image content matching

In order to take advantage of global navigation map for robot self-localization and solve kidnap problem, a robot vision localization system is presented based on graphic content matching. It can make good use of the different objects and their layout in different rooms or corridors to fix robot position, which cannot be disturbed by similar objects. This vision localization system is composed of frames overlap region extraction and overlap region re-building through sub-blocks matching, and the interference caused by points on the wall and mismatching sub-blocks can be deleted. The image distortion can be adjusted to the same before matching. In the experiment, this graphic matching method can match the real-time robot vision with keyframes global map effectively, and find out the most similar keyframe for each vision image and fix robot position exactly. More than 95% robot vision can be matched and position RMSE<0.5 m. Robot can also localize itself effectively when it is kidnapped.
An efficient detection of local features in depth maps

In this paper, we propose an algorithm for the detection of local features in depth maps. The local features can be utilized for determination of special points for Iterative Closest Point (ICP) algorithms. The proposed algorithm employs a novel approach based a cascade mechanism, which can be applied for several 3D keypoint detection algorithms. Computer simulation and experimental results obtained with the proposed algorithm in real-life scenes are presented and compared with those obtained with state-of-the-art algorithms in terms of detection efficiency, accuracy, and speed of processing. The results show an improvement in the accuracy of 3D object reconstruction using the proposed algorithm followed by ICP algorithms.
Santa Clara, California

An Australian-based software house was recognized for its world-class innovation when it received a Jolt Productivity Award at this year's SD West conference in Silicon Valley. SPARX Systems won the award in the “Design tools and Modeling” software category for their Enterprise Architect UML 2 modeling software. Over the last 18 months, Enterprise Architect has rapidly moved from cult status to mainstream usage. With extensions for project managers, testers, developers, business analysts, support staff, report writers and more, Enterprise Architect has won converts from all industry segments.
Apport d'une conception centrée utilisateur adaptée selon les besoins des personnes en situation de handicap

Les personnes en situation de handicap moteur des membres superieurs ont besoin de systeme de suppleance pour leur autonomie. Cependant 1/3 de ces aides de compensation sont abandonnees car pas encore suffisamment centrees sur les besoins et les aptitudes de l'utilisateur. La problematique centrale de cette these concerne la mise en œuvre d'une methode de conception centree utilisateur, adaptee en fonction de la population d'etudes (personnes en situation de handicap ayant des troubles neuro-moteurs langagiers) pour la conception de trois aides de compensation. La premiere concerne la commande d'un bras robotique de prehension JACO pour laquelle la conception centree utilisateur classique a ete appliquee. Celle-ci est adaptee pour les personnes pouvant s'exprimer oralement mais qu'en est-il lorsque ces personnes ne peuvent participer directement ou bien ont besoin de leurs aidants pour exprimer leurs besoins ou repondre aux questionnaires? Une alternative est de recueillir les besoins par l'intermediaire d'experts. Nous montrerons comment la methode de conception centree utilisateur a ete adaptee pour la conception du systeme HandiMathKey pour la saisie de formules Mathematiques. Notre derniere adaptation est d'utiliser l'ecosysteme de la personne comme mediateur pour communiquer et un profil utilisateur. Cette methode a permis de concevoir l'interface de communication integree et de controle d'environnement nommee CECI. Nous decrirons egalement comment la plateforme SoKeyTo permet le prototypage des aides de compensation. Pour chacune des aides de compensation, nous rapporterons les evaluations realisees et nous discuterons la maniere dont la methode de conception a ete adaptee.
ROMOP: a light-weight R package for interfacing with OMOP-formatted electronic health record data

Abstract Objectives Electronic health record (EHR) data are increasingly used for biomedical discoveries. The nature of the data, however, requires expertise in both data science and EHR structure. The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) standardizes the language and structure of EHR data to promote interoperability of EHR data for research. While the OMOP CDM is valuable and more attuned to research purposes, it still requires extensive domain knowledge to utilize effectively, potentially limiting more widespread adoption of EHR data for research and quality improvement. Materials and methods We have created ROMOP: an R package for direct interfacing with EHR data in the OMOP CDM format. Results ROMOP streamlines typical EHR-related data processes. Its functions include exploration of data types, extraction and summarization of patient clinical and demographic data, and patient searches using any CDM vocabulary concept. Conclusion ROMOP is freely available under the Massachusetts Institute of Technology (MIT) license and can be obtained from GitHub (http://github.com/BenGlicksberg/ROMOP). We detail instructions for setup and use in the Supplementary Materials. Additionally, we provide a public sandbox server containing synthesized clinical data for users to explore OMOP data and ROMOP (http://romop.ucsf.edu).
The Development of A Project-Based Portfolio Assessment Instrument on The Material of Word Processing Application Program

The development of word processing assessment instrument on ICT in SMP is not in accordance with the rules of assessment instrument development yet, so that the quality is not guaranteed. This study aims to develop an instrument of project-based portfolio assessment on qualified (valid and reliable) word processing application material. The assessment instrument was tested on 31 students of grade VIII of SMP Negeri 1 Jekulo Kabupaten Kudus. This development of assessment instrument used Djemari Mardapi’s development model. The methods used for data collection were interviews, validation sheet, assessment rubric and questionnaire. The data were analyzed through validity test of experts and inter rater reliability test with Ebel formula. The results showed that the development procedure of assessment instrument was able to produce a valid and reliable portfolio assessment instrument, product, presentation and assessment of the knowledge aspect. The results of validity test on the content, language, and presentation of the assessment instrument obtained an average percentage score of 83% (content), 81% (language) and 83% (presentation). The reliability test using Ebel formula showed that portfolio assessment instrument obtained r11 value of 0.81 (process), 0.80 (proposal), 0.94 (invitation), 0.89 (decoration), 0.95 (presentation) and coefficient value of Cronbach Alpha 0.759 on knowledge instrument. The result of this instrument assessment development was practical and had a positive response of 85%. Therefore, it can be implemented in other schools because its quality has been tested as a good instrument (valid and reliable). Through this assessment, teachers can use it as a guide to assess the student applicative capability on ICT word processing materials.
Augmented Reality Uses in Interior Design

Increasingly, interior design retailers rely on online stores to reach their customers as more and more people are connected to the internet. One of the issue in online shopping is that customers cannot visualize how new furniture pieces would blend in their home, but that is not the case anymore as Augmented Reality (AR) becomes more mainstream. This paper analyses several AR applications used in the interior design and highlights their pros and cons. Based on this analysis, we propose an AR application that solves most of the current issues of the interior spaces design.
First steps towards the development of an academic system to follow the trajectories of primary and secondary uruguayan students

1 Universidad de la República (UDELAR), Montevideo, Uruguay 2 Universidade Federal de Santa Catarina (UFSC), Araranguá, Brasil 3 Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brasil 4 Escuela Superior Politécnica del Litoral (ESPOL), Guayaquil, Ecuador 5 Administración Nacional de Educación Pública (ANEP), Montevideo, Uruguay virginia.rodes@cse.edu. uy, cristian.cechinel@ufsc.br, hlsantos@inf.ufrgs. br, xavier@cti.espol. edu.ec, gettlinal@anep.edu. uy
Détection automatique de phrases en domaine de spécialité en français (Sentence boundary detection for specialized domains in French )

La détection de frontières de phrase est généralement considéré comme un problème résolu. Cependant, les outils performant sur des textes en domaine général, ne le sont pas forcement sur des domaines spécialisés, ce qui peut engendrer des dégradations de performance des outils intervenant en aval dans une chaîne de traitement automatique s’appuyant sur des textes découpés en phrases. Dans cet article, nous évaluons 5 outils de segmentation en phrase sur 3 corpus issus de différent domaines. Nous ré-entrainerons l’un de ces outils sur un corpus de spécialité pour étudier l’adaptation en domaine. Notamment, nous utilisons un nouveau corpus biomédical annoté spécifiquement pour cette tâche. La detection de frontières de phrase à l’aide d’un modèle OpenNLP entraîné sur un corpus clinique offre une F-mesure de . 73, contre . 66 pour la version standard de l’outil.