Miracle-dz/UniFAR-FTUs huggingface dataset:
Weighted SCAN for modeling cooperative group role dynamics

Social agents have the ability of communicating and forming groups with each other. Group members in games typically share the same role. In dynamic environments with the presence of obstacles and barriers separating members from each other presents a situation where a member separated from the rest of the group, while still a member of that group, should not have the same role or updates of the rest of the group due to the physical distance presented by the obstacles. This study introduces a weighted version of the SCAN and hierarchical SCAN graph clustering algorithms which are essentially based on neighbors. The autonomous agent players in spatial strategy game scenarios tested with the weighted SCAN have demonstrated an improved realistic behaviour in the social test settings.
Fast 2D Convolutions and Cross-Correlations Using Scalable Architectures

The manuscript describes fast and scalable architectures and associated algorithms for computing convolutions and cross-correlations. The basic idea is to map 2D convolutions and cross-correlations to a collection of 1D convolutions and cross-correlations in the transform domain. This is accomplished through the use of the discrete periodic radon transform for general kernels and the use of singular value decomposition -LU decompositions for low-rank kernels. The approach uses scalable architectures that can be fitted into modern FPGA and Zynq-SOC devices. Based on different types of available resources, for <inline-formula> <tex-math notation="LaTeX">$P\times P$ </tex-math></inline-formula> blocks, 2D convolutions and cross-correlations can be computed in just <inline-formula> <tex-math notation="LaTeX">$O(P)$ </tex-math></inline-formula> clock cycles up to <inline-formula> <tex-math notation="LaTeX">$O(P^{2})$ </tex-math></inline-formula> clock cycles. Thus, there is a trade-off between performance and required numbers and types of resources. We provide implementations of the proposed architectures using modern programmable devices (Virtex-7 and Zynq-SOC). Based on the amounts and types of required resources, we show that the proposed approaches significantly outperform current methods.
A Contingency Theory of Socialization

September 1976, volume 21 A model of individual socialization into organizations is presented and tested. The model (a) identifies three distinct stages of socialization, (b) specifies the activities engaged in by an individual at each stage, and (c) specifies the personal and organizational contingencies that control an individual's movement through the stages. Interview and questionnaire data collected from 118 hospital employees -nurses, nurse's aides, radiology technologists, tradesmen, and accounting clerks -were used to develop, refine, and test the model. The model basically was supported by the data. Four variables are identified as possible outcomes of the socialization process: general satisfaction, mutual influence, internal work motivation, and job involvement. Two of these variables general satisfaction and mutual influence are empirically linked with important aspects of the socialization process, and are shown to increase steadily as individuals progress through socialization. The differences between the socialization experiences of professional, paraprofessional, and nonprofessional workers are identified and explained, and implications for the conduct of socialization programs are drawn.1
Psychological Effects of a 1-Month Meditation Retreat on Experienced Meditators: The Role of Non-attachment

Background: There are few studies devoted to assessing the impact of meditation-intensive retreats on the well-being, positive psychology, and personality of experienced meditators. We aimed to assess whether a 1-month Vipassana retreat: (a) would increase mindfulness and well-being; (b) would increase prosocial personality traits; and (c) whether psychological changes would be mediated and/or moderated by non-attachment. Method: A controlled, non-randomized, pre-post-intervention trial was used. The intervention group was a convenience sample (n = 19) of experienced meditators who participated in a 1-month Vipassana meditation retreat. The control group (n = 19) comprised matched experienced meditators who did not take part in the retreat. During the retreat, the mean duration of daily practice was 8–9 h, the diet was vegetarian and silence was compulsory. The Experiences Questionnaire (EQ), Non-attachment Scale (NAS), Positive and Negative Affect Schedule (PANAS), Satisfaction With Life Scale (SWLS), Temperament Character Inventory Revised (TCI-R-67), Five Facets Mindfulness Questionnaire (FFMQ), Self-Other Four Immeasurables (SOFI) and the MINDSENS Composite Index were administered. ANCOVAs and linear regression models were used to assess pre-post changes and mediation/moderation effects. Results: Compared to controls, retreatants showed increases in non-attachment, observing, MINDSENS, positive-affect, balance-affect, and cooperativeness; and decreases in describing, negative-others, reward-dependence and self-directedness. Non-attachment had a mediating role in decentring, acting aware, non-reactivity, negative-affect, balance-affect and self-directedness; and a moderating role in describing and positive others, with both mediating and moderating effects on satisfaction with life. Conclusions: A 1-month Vipassana meditation retreat seems to yield improvements in mindfulness, well-being, and personality, even in experienced meditators. Non-attachment might facilitate psychological improvements of meditation, making it possible to overcome possible ceiling effects ascribed to non-intensive practices.
A Regularized Correlation Criterion for Efficient Gene Subset Selection

Motivation: The correlation between a gene and class labels reflects the predictive power of a gene, and has been commonly used in gene selection for gene expression data analysis. But this correlation criterion evaluates genes on an individual basis. It is generally acknowledged that a collection of individually predictive genes may not necessarily produce satisfactory classification performance due to the sereve redundancy underlying the gene collection. Results: In this study, a new set-based correlation criterion is developed for sequential forward gene selection, with the goal of alleviating redundancy and improving classification performance. Given a gene subset selected at previous selection steps, the new approach evaluates the significance of a candidate gene to be added by first isolating the part of information that is complementary to the gene subset, and then evaluating the gene based on the correlation between class label and the isolated complementary component. The isolation of complementary component is done through orthogonal decomposition. Instead of orthogonalizing a candidate gene with each of the genes in the subset, the new approach orthogonalizes the candidate gene to the class label prediction built upon the gene subset. The merit of this approach is that it retains the redundancy handling capacity of orthogonal decomposition but demands less computation than conventional orthogonal decomposition. In addition, it is noted that overfitting could easily occur in gene selection due to the small sample size and very high dimensionality of gene expression data. In this study, regularization technique is introduced to gene selection and a regularized correlation criterion is derived. Experimental studies on 6 problems show that regularization is very necessary in gene selection for small-sized expression data, and the gene subsets selected by the regularized correlation criterion produces improved classification performance. Contact: ekzmao@ntu.edu. sg
Humanoid Robot's Autonomous Acquisition of Proto-Symbols through Motion Segmentation

Mimesis is the theory that human intelligence originated in the interactive communication of motion recognition and generation through imitation. A mimesis model has been proposed using hidden Markov models (HMMs), which represent proto symbols. In our previous system, the user had to manually divided a sequence of motion into segments in order to embed each segment as an HMM. Automatic segmentation is essential for a system to autonomously learn and develop through imitation. In this paper, we propose an automatic motion segmentation method utilizing correlation among movements for a short time period. In addition, we show that it is possible to acquire proto symbols by providing the automatically segmented motion patterns with the mimesis system
The Duffy binding protein as a key target for a Plasmodium vivax vaccine: lessons from the Brazilian Amazon

Plasmodium vivax infects human erythrocytes through a major pathway that requires interaction between an apical parasite protein, the Duffy binding protein (PvDBP) and its receptor on reticulocytes, the Duffy antigen/receptor for chemokines (DARC). The importance of the interaction between PvDBP (region II, DBPII) and DARC to P. vivax infection has motivated our malaria research group at Oswaldo Cruz Foundation (state of Minas Gerais, Brazil) to conduct a number of immunoepidemiological studies to characterise the naturally acquired immunity to PvDBP in populations living in the Amazon rainforest. In this review, we provide an update on the immunology and molecular epidemiology of PvDBP in the Brazilian Amazon - an area of markedly unstable malaria transmission - and compare it with data from other parts of Latin America, as well as Asia and Oceania.
Transcription Factor IIA Derepresses TATA-binding Protein (TBP)-associated Factor Inhibition of TBP-DNA Binding*

The interaction of the general transcription factor (TF) IIA with TFIID is required for transcription activationin vitro. TFIID consists of the TATA-binding protein (TBP) and TBP associated factors (TAFIIs). TFIIA binds directly to TBP and stabilizes its interaction with TATA-containing DNA. In this work, we present evidence that TAFIIs inhibit TBP-DNA and TBP-TFIIA binding, and that TFIIA stimulates transcription, in part, by overcoming this TAFII-mediated inhibition of TBP-DNA binding. TFIIA mutants modestly compromised for interaction with TBP were found to be significantly more defective in forming complexes with TFIID. Subtle changes in the stability or conformation of the TFIIA-TBP complex resulted in a failure of TFIIA to overcome TAFII-mediated inhibition of TBP-DNA binding and transcription function. Inhibition of TBP-DNA binding by TAFIIs could be partially relieved by limited proteolysis of TFIID. Proteolysis significantly stimulated TFIIA-TFIID-TATA binding in both electrophoresis mobility shift assay and DNase I footprinting but had little effect on complexes formed with TBP. Recombinant TAFII250 inhibits TBP-DNA binding, whereas preincubation of TFIIA with TBP prevents this inhibition. Thus, TFIIA competes with TAFII250 for access to TBP and alters the TATA binding properties of the resulting complex. Transcriptional activation by Zta was enhanced by temperature shift inactivation of TAFII250 in the ts13 cell line, suggesting that TAFII250 has transcriptional inhibitory activity in vivo. Together, these results suggest that TAFIIs may regulate transcription initiation by inhibiting TBP-TFIIA and TBP-DNA complex formation.
Modular multilevel inverter with maximum power point tracking for grid connected photovoltaic application

A single-phase modular multilevel inverter based photovoltaic system for grid connection is proposed. This photovoltaic system utilizes two conversion stages; a boost converter for tracking the maximum power point and a modular multilevel inverter used as an interfacing unit. The maximum power point tracking is achieved with a fuzzy logic controller, and the modular multilevel inverter regulates the dc link voltage and synchronizes the grid voltage and current in order to achieve unity power factor operation. The proposed system provides high dynamic performance and power quality injected into the grid. The validity of the proposed system is confirmed by simulations.
Heterotopic oceans in Southern Chile: heritage, fisheries, and marine conservation

ABSTRACT This article explores the ways in which hierarchical social relations contribute to the social configuration of space in the seas around the archipelago of Chiloé, in southern Chile. Heritage projects, fisheries production regimes, and efforts to install marine conservation areas through scientific research, increased popular awareness, and legal means, all contribute to the growing number of overlapping oceanic spatial projects. Each project is examined for the ways in which racialized, ethnicized, and class social orders are exercised, and for how these processes work together to deepen spatialized social hierarchy and social order. The analysis illuminates the commonalities and resonances between different kinds of quotidian oceanic spatial projects, and provides an excellent example of the ways in which coastal and territorial seas are being socially reorganized in the contemporary world.
The N-terminus of Prp1 (Prp6/U5-102 K) is essential for spliceosome activation in vivo

The spliceosomal protein Prp1 (Prp6/U5-102 K) is necessary for the integrity of pre-catalytic spliceosomal complexes. We have identified a novel regulatory function for Prp1. Expression of mutations in the N-terminus of Prp1 leads to the accumulation of pre-catalytic spliceosomal complexes containing the five snRNAs U1, U2, U5 and U4/U6 and pre-mRNAs. The mutations in the N-terminus, which prevent splicing to occur, include in vitro and in vivo identified phosphorylation sites of Prp4 kinase. These sites are highly conserved in the human ortholog U5-102 K. The results presented here demonstrate that structural integrity of the N-terminus is required to mediate a splicing event, but is not necessary for the assembly of spliceosomes.
A modal representation of RCC62

The major problem in developing a useful formalism for reasoning about spatial information is the trade off between expressive power and computational tractability. Based on Bennett's modal representation of convex-hull and the RCC62 model which describes the topological relation between simple concave regions, the modal representation of RCC62 is presented in this paper, which has a theoretical advantage over 1st-order representations.
Dyslexia without agraphia. Prognostic considerations.

"PURE word-blindness" has long been a subject attractive to writers devoted to neurologically based language disorders. Authors principally concern themselves with clinical descriptions and speculations relevant to possible pathophysiological mechanisms. The literature leaves uncertainty regarding the natural history or prognosis of dyslexia. This observation might be broadly applied to the field of aphasia in its entirety. The paucity of works and controlled studies dealing directly with recovery from aphasic language disorders may simply reflect silent discouragement accrued from long experience in this field. Neurologists generally agree that variable but unpredictable potential for improvement exists, but documentation is scanty.1-5 Relatively "pure" cases of word-blindness are infrequently recognized. Inasmuch as I have had the opportunity of following two cases of agnosic dyslexia for two and four years respectively, an attempt was made to demonstrate any change occurring in these interesting patients. Early and current performances with interval history have been
Simultaneous Computation of Dynamical and Equilibrium Information Using a Weighted Ensemble of Trajectories

Equilibrium formally can be represented as an ensemble of uncoupled systems undergoing unbiased dynamics in which detailed balance is maintained. Many nonequilibrium processes can be described by suitable subsets of the equilibrium ensemble. Here, we employ the “weighted ensemble” (WE) simulation protocol [Huber and Kim, Biophys. J.1996, 70, 97–110] to generate equilibrium trajectory ensembles and extract nonequilibrium subsets for computing kinetic quantities. States do not need to be chosen in advance. The procedure formally allows estimation of kinetic rates between arbitrary states chosen after the simulation, along with their equilibrium populations. We also describe a related history-dependent matrix procedure for estimating equilibrium and nonequilibrium observables when phase space has been divided into arbitrary non-Markovian regions, whether in WE or ordinary simulation. In this proof-of-principle study, these methods are successfully applied and validated on two molecular systems: explicitly solvated methane association and the implicitly solvated Ala4 peptide. We comment on challenges remaining in WE calculations.
Recurrence of Light Chain Nephropathy in a Renal Allograft

Myeloma and monoclonal gammopathies can affect the kidney in many ways with cast nephropathy and light chain deposition disease being the most commonly recognised histological entities. Renal transplantation in these patients remains controversial both because of the risk of recurrent disease affecting the graft and also because of concerns around the possibility of disease relapse within the patient. We suggest that the histological pattern of disease within the native kidneys is crucial in the overall assessment of these patients for renal transplantation. Those patients in whom renal deposition of light chains is associated with a proliferative glomerulonephritis have a considerably worse graft survival than those presenting with cast nephropathy.
Imaging low-risk prostate cancer

Purpose of review Prostate-specific antigen screening has led to a downstaging of prostate cancer that has resulted in overdiagnosis and overtreatment of the disease. The review discusses the potential role of imaging in identifying low-risk prostate cancer and enabling more appropriate management of the disease. Recent findings Clinical nomograms have been designed and validated for prediction of the probability of insignificant prostate cancer. The models integrate clinical and biopsy findings. Recently, nomogram models have been designed that incorporate MRI and magnetic resonance spectroscopic imaging data with clinical and biopsy data for prediction of insignificant prostate cancer; these models performed better than the clinical models. Summary Clinical nomograms for the prediction of insignificant disease provide more information than any diagnostic test alone; furthermore, nomograms that incorporate MRI or MRI/magnetic resonance spectroscopic imaging findings with clinical and biopsy data have been shown to improve the prediction of insignificant cancer. A greater level of certainty, however, is still needed to help segregate low-risk patients from intermediate and high-risk patients. Therefore, more research is needed on imaging of low-risk prostate cancer so that data-driven, evidence-based practice guidelines in oncology combining anatomical, metabolic and laboratory data can be designed.
' s personal copy Web services composition : A decade ’ s overview

Service-oriented computing (SOC) represents a paradigm for building distributed computing applications over the Internet. In the past decade, Web services composition has been an active area of research and development endeavors for application integration and interoperation. Although Web services composition has been heavily investigated, several issues related to dependability, ubiquity, personalization, among others, still need to be addressed, especially giving the recent rise of several new computing paradigms such as Cloud computing, social computing, and Web of Things. This article overviews the life cycle of Web services composition and surveys the main standards, research prototypes, and platforms. These standards, research prototypes, and platforms are assessed using a set of assessment criteria identified in the article. The paper also outlines several research opportunities and challenges for Web services composition. 2014 Elsevier Inc. All rights reserved.
Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70 × 70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.
Security evaluation of different AES implementations against practical setup time violation attacks in FPGAs

Security evaluation of various AES implementation against practical power attacks has been reported in literature. However, to the authors' knowledge, very few of the fault attacks reported on AES have been practically realized. Since sbox is a crucial element in AES, in this article, we evaluate the security of some unprotected AES implementations differing in sbox construction, targeted for FPGA. Here the faults have been generated practically by underpowering the targeted circuit. Then we correlate our results with the underlying architecture, along a methodology already suggested in other articles, albeit theoretically. We also carry out an extensive characterization of the faults, in terms of temporal localization. On the basis of our results, we reach the conclusion that the two cheaper implementations in terms of silicon area are also the more vulnerable against DFA when implemented without counter-measures.
Building a personalized tourist attraction recommender system using crowdsourcing

We demonstrate how crowdsourcing can be used to automatically build a personalized tourist attraction recommender system, which tailors recommendations to specific individuals, so different people who use the system each get their own list of recommendations, appropriate to their own traits. Recommender systems crucially depend on the availability of reliable and large scale data that allows predicting how a new individual is likely to rate items from the catalog of possible items to recommend. We show how to automate the process of generating this data using crowdsourcing, so that such a system can be built even when such a dataset is not initially available. We first find possible tourist attractions to recommend by scraping such information from Wikipedia. Next, we use crowdsourced workers to filter the data, then provide their opinions regarding these items. Finally, we use machine learning methods to predict how new individuals are likely to rate each attraction, and recommend the items with the highest predicted ratings.