Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic Propagation on Contextonyms using SentiWordNet

Sentiment analysis and affect detection algorithms are generally based onto annotated data, structured into dictionaries, ontologies or word nets. The focus, so far, has been concentrated on manual annotation of the data, and then, in some situations, a semantic valence propagation is applied. The problem with this approach is that while it is able to build new affective labels through the propagation process, the precision of the decision decreases. Our approach disambiguates through the data, by offering a strong context using a contextonym model, for the usage of a certain term with a valence.
The short-term traffic flow prediction based on neural network

As we all know, to predict the short-term traffic flow accurately and efficiently is the premise and key of traffic management and control. Based on these existing study, this paper selected BP neural network model in which the traffic flow difference was taken as the input parameter, applied the thought of dynamic rolling prediction to design a new short-term traffic flow prediction method, and wrote the corresponding program. Then using the actual observation data of traffic flow presented the model structure, thought and calculation steps of this new method. The results show this method is feasibility, reliability, and of some practical value.
Red tide algae classification using SVM-SNP and semi-supervised FCM

In this paper, a novel approach for classifying algal images was presented, which is used in flow-cytometry-based real-time red tide monitoring system. Firstly, an ensemble of support vector machines (SVMs) was trained and the test samples were labeled by them based on the summation of negative probability (SNP). Secondly, those samples most likely mistakenly labeled were picked out and re-labeled by semi-supervised fuzzy c-means (FCM) clustering algorithm. Experiments show that this new method improves the accuracy of algal images classification for the same subject with SVMs of different kernels.
The 2175 Å Dust Feature in a Gamma-Ray Burst Afterglow at Redshift 2.45

We present optical and near-infrared photometry of the afterglow of the long gamma-ray burst (GRB) 070802 at redshift 2.45 obtained with the ESO/MPI 2.2 m telescope equipped with the multichannel imager GROND. Follow-up observations in g'r'i'z' and JHKS bands started at ~17 minutes and extended up to 28 hr postburst. We find an increase in the brightness of the afterglow at early times, which can be explained by the superposition of reverse and forward shock (FS) emission or the onset of the afterglow FS. In addition, we detect a strong broadband absorption feature in the i' band, which we interpret as extinction from the redshifted 2175 Å bump in the GRB host galaxy. This is one of the first and clearest detections of the 2175 Å feature at high redshift. It is strong evidence for a carbon-rich environment, indicating that Milky Way- or Large Magellanic Cloud-like dust was already formed in substantial amounts in a galaxy at z = 2.45.
Poster: preliminary analysis of Google+'s privacy

In this paper we provide a preliminary analysis of Google+ privacy. We identified that Google+ shares photo metadata with users who can access the photograph and discuss its potential impact on privacy. We also identified that Google+ encourages the provision of other names including maiden name, which may help criminals performing identity theft. We show that Facebook lists are a superset of Google+ circles, both functionally and logically, even though Google+ provides a better user interface. Finally we compare the use of encryption and depth of privacy control in Google+ versus in Facebook.
The Effect of Multicultural Family Support Service: Examining Integration with Immigrant Wives in South Korea

ABSTRACT Since 2009, Multicultural Family Support Service (MFSS) has provided service to immigrant wives designed to improve their integration, yet little research exists to support its effectiveness. Hence, this study is aimed to empirically estimate the net effect of MFSS, and its quantifying effect on immigrant wives' integration, using propensity score matching to reduce selection bias. Utilizing the 2012 National Survey on Multicultural Families, which examines the actual conditions of multicultural families, this study extracts immigrant wives (N = 12,324), including service users (n = 6,012) and non–service users (n = 6,312). The findings show that the extent of four dimensions of integration—citizenship, employment, Korean language proficiency, and life satisfaction—between service users and non–service users is not significantly different. This indicates that MFSS may be failing to improve immigrant wives' integration, and improvements are recommended. This study concludes that case management, cultural competence, and management reflecting regional differences are ways to improve integration.
Reexamining the Use of Tentative Language in Emails: The Effects of Gender Salience and Gender Typicality

Drawing on self-categorization theory, the current study examines the effects of gender salience and interlocutor gender typicality on men and women’s use of tentative language in emails. We conducted an experiment manipulating identity salience using gender-stereotypic conversation topics, and typicality using biographies of the fictitious female interlocutor. The results were consistent with self-categorization theory and previous research on gender-based language use: Men were more tentative when discussing a conversation topic in which their gender group was not considered experts. More important, interlocutor gender typicality influenced participants’ tentative language, such that when the interlocutor was a typical woman, men and women became more tentative discussing a conversation topic in which they were not considered experts. This study has implications for future research on the contextual factors that may influence the use of language in both intragroup and intergroup communication.
Robust dataglove mapping for recording human hand postures

We present a novel dataglove mapping technique based on parameterisable models that handle both the cross coupled sensors of the fingers and thumb, and the under-specified abduction sensors for the fingers. Our focus is on realistically reproducing the posture of the hand as a whole, rather than on accurate fingertip positions. The method proposed in this paper is a vision-free, object free, data glove mapping and calibration method that has been successfully used in robot manipulation tasks.
A randomized, controlled trial of sequential bilateral repetitive transcranial magnetic stimulation for treatment-resistant depression.

OBJECTIVE High-frequency left-side repetitive transcranial magnetic stimulation (rTMS) and low-frequency stimulation to the right prefrontal cortex have both been shown to have antidepressant effects, but doubts remain about the magnitude of previously demonstrated treatment effects. The authors evaluated sequentially combined high-frequency left-side rTMS and low-frequency rTMS to the right prefrontal cortex for treatment-resistant depression. METHOD The authors conducted a 6-week double-blind, randomized, sham-controlled trial in 50 patients with treatment-resistant depression. Three trains of low-frequency rTMS to the right prefrontal cortex of 140 seconds' duration at 1 Hz were applied daily, followed immediately by 15 trains of 5 seconds' duration of high-frequency left-side rTMS at 10 Hz. Sham stimulation was applied with the coil angled at 45 degrees from the scalp, resting on the side of one wing of the coil. The primary outcome variable was the score on the Montgomery-Asberg Depression Rating Scale. RESULTS There was a significantly greater response to active than sham stimulation at 2 weeks and across the full duration of the study. A significant proportion of the study group receiving active treatment met response (11 of 25 [44%]) or remission (nine of 25 [36%]) criteria by study end compared to the sham stimulation group (two of 25 [8%] and none of 25 respectively). CONCLUSIONS Sequentially applying both high-frequency left-side rTMS and low-frequency rTMS to the right prefrontal cortex, has substantial treatment efficacy in patients with treatment-resistant major depression. The treatment response accumulates to a clinically meaningful level over 4 to 6 weeks of active treatment.
Stereotype Threat Affects Financial Decision Making

The research presented in this article provides the first evidence that one’s decision making can be influenced by concerns about stereotypes and the devaluation of one’s identity. Many studies document gender differences in decision making, and often attribute these differences to innate and stable factors, such as biological and hormonal differences. In three studies, we found that stereotype threat affected decision making and led to gender differences in loss-aversion and risk-aversion behaviors. In Study 1, women subjected to stereotype threat in academic and business settings were more loss averse than both men and women who were not facing the threat of being viewed in light of negative stereotypes. We found no gender differences in loss-aversion behavior in the absence of stereotype threat. In Studies 2a and 2b, we found the same pattern of effects for risk-aversion behavior that we had observed for loss-aversion behavior. In addition, in Study 2b, ego depletion mediated the effects of stereotype threat on women’s decision making. These results suggest that individuals’ decision making can be influenced by stereotype concerns.
Automatic Detection of Arabicized Berber and Arabic Varieties

Automatic Language Identification (ALI) is the detection of the natural language of an input text by a machine. It is the first necessary step to do any language-dependent natural language processing task. Various methods have been successfully applied to a wide range of languages, and the state-of-the-art automatic language identifiers are mainly based on character n-gram models trained on huge corpora. However, there are many languages which are not yet automatically processed, for instance minority and informal languages. Many of these languages are only spoken and do not exist in a written format. Social media platforms and new technologies have facilitated the emergence of written format for these spoken languages based on pronunciation. The latter are not well represented on the Web, commonly referred to as under-resourced languages, and the current available ALI tools fail to properly recognize them. In this paper, we revisit the problem of ALI with the focus on Arabicized Berber and dialectal Arabic short texts. We introduce new resources and evaluate the existing methods. The results show that machine learning models combined with lexicons are well suited for detecting Arabicized Berber and different Arabic varieties and distinguishing between them, giving a macro-average F-score of 92.94%.
Social Preferences and Relational Contracting Performance: An Experimental Investigation

We examine how social preferences affect behavior and surplus in relational contracts. Experimental subjects participate in a contracting environment similar to Brown, Falk, and Fehr [Brown, M. , Falk, A. & Fehr, E. , “Relational Contracts and the Nature of Market Interactions, Econometrica, 72 (2004):747-780] and in social preference experiments adapted from Charness and Rabin [Charness, G. & Rabin, M. “Understanding Social Preferences with Simple Tests. ” The Quarterly Journal of Economics 117(2002): 817-869]. Subjects’ behavior during the Charness and Rabin experiment is a significant predictor of behavior and outcomes observed during the subsequent multi-period, finite-horizon, relational- contracting environment, which features market power, unenforceable performance, reputation formation and endogenous matching of trading partners. Compared to subjects who respond to the Charness-Rabin games in a fashion consistent with purely self-interested, competitive or reciprocal social preferences, buyers and sellers with alternative social preference structures engage in contracts with substantially higher quality and price, which leads to greater surplus for both parties. A key difference is that self-interested, competitive and reciprocal buyers respond to early-period shirking by extending subsequent offers that are less generous to the seller, while buyers with other social preferences extend subsequent offers that are more generous. Reciprocal and competitive sellers and, to a lesser extent, self-interested sellers, deliver sub-contractual levels of quality more often, which substantially lowers buyer and total welfare. We conclude that intentional or ‘cold’ measures of social preferences have considerable predictive power in dynamic, interactive (or ‘hot’) economic settings.
Guaranteed Cost Certification for Discrete-Time Linear Switched Systems With a Dwell Time

This technical note studies the guaranteed cost of a quadratic criterion associated with a linear discrete-time switched system for all the set of admissible switching laws. The admissible switching laws are here the ones exhibiting a dwell time. The approach provided here is to design an upper bound and a parametrized family of lower bounds of the guaranteed cost as close as possible in order to obtain a certification of the guaranteed cost. The upper bound is determined via a switched Lyapunov function and the lower bounds are obtained via the numerical computation of the cost induced by particular periodic switching laws. The features of the proposed approach are illustrated by a numerical example.
An evaluation of test statistics for detecting level change in BL(1,1,1,1) models

A study is carried out to investigate the sampling properties of the outlier test statistics of a procedure developed for detecting level change in BL(1,1,1,1) processes. It is done with respect to the sample size, the type of outlier and the size of the coefficients of the BL(1,1,1,1) process. The results show that, in general, the outlier detection procedure is capable of detecting level change, although the performance is affected if ω is large.
Real-Time Synthesis and Rendering of Ocean Water

We present a multi-band Fourier domain approach to synthesizing and rendering deep-water ocean waves entirely on the graphics processor. Our technique begins by using graphics hardware to generate and animate a Fourier domain spectrum of ocean water. We subsequently use the graphics hardware to apply an IFFT to transform the spectrum into a realistic height map of ocean water in the spatial domain. As a result, this technique can be used to efﬁciently synthesize and render height maps and normal maps which are spatially periodic. GPU-synthesized low frequency height maps are used to displace geometry while broad spectrum GPU-synthesized waveforms are used to generate a normal map for shading. The model also allows for compositing of other waveforms such as wakes or eddies caused by objects interacting with the water. The primary contributions of this work are the use of the GPU to perform all synthesis and rendering steps as well as the multi-band approach which enables efﬁcient simulation of the natural ﬁltering of high frequencies at different points on the water surface due to depth variation or the presence of plant matter.
Genome-wide linkage analysis for uric acid in families enriched for hypertension.

BACKGROUND Uric acid is heritable and associated with hypertension and insulin resistance. We sought to identify genomic regions influencing serum uric acid in families in which two or more siblings had hypertension. METHODS Uric acid levels and microsatellite markers were assayed in the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort (1075 whites and 1333 blacks) and the Hypertension Genetic Epidemiology Network (HyperGEN) cohort (1542 whites and 1627 blacks). Genome-wide linkage analyses of uric acid and bivariate linkage analyses of uric acid with an additional surrogate of insulin resistance were completed. Pathway analysis explored gene sets enriched at loci influencing uric acid. RESULTS In the GENOA white cohort, loci influencing uric acid were identified on chromosome 8 at 135 cM [multipoint logarithm of odds score (MLS) = 2.4], on chromosome 9 at 113 cM (MLS = 3.7) and on chromosome 16 at 93 cM (MLS = 2.3), but did not replicate in HyperGEN. At these loci, there was evidence of pleiotropy with other surrogates of insulin resistance and genes in the fructose and mannose metabolism pathway were enriched. In the HyperGEN-black cohort, there was some evidence of a locus for uric acid on chromosome 4 at 135 cM (MLS = 2.4) that had modest replication in GENOA (MLS = 1.2). CONCLUSIONS Several novel loci linked to uric acid were identified but none showed clear replication. Widespread diuretic use, a medication that raises uric acid levels, was an important study limitation. Bivariate linkage analyses and pathway analysis were consistent with genes regulating insulin resistance and fructose metabolism contributing to the heritability of uric acid.
Stem Cell Conditioned Culture Media Attenuated Albumin-Induced Epithelial– Mesenchymal Transition in Renal Tubular Cells

Background: Proteinuria-induced epithelial-mesenchymal transition (EMT) plays an important role in progressive renal tubulointerstitial fibrosis in chronic renal disease. Stem cell therapy has been used for different diseases. Stem cell conditioned culture media (SCM) exhibits similar beneficial effects as stem cell therapy. The present study tested the hypothesis that SCM inhibits albumin-induced EMT in cultured renal tubular cells. Methods: Rat renal tubular cells were treated with/without albumin (20 µmg/ml) plus SCM or control cell media (CCM). EMT markers and inflammatory factors were measured by Western blot and fluorescent images. Results: Albumin induced EMT as shown by significant decreases in levels of epithelial marker E-cadherin, increases in mesenchymal markers fibroblast-specific protein 1 and a-smooth muscle actin, and elevations in collagen I. SCM inhibited all these changes. Meanwhile, albumin induced NF-κB translocation from cytosol into nucleus and that SCM blocked the nuclear translocation of NF-κB. Albumin also increased the levels of pro-inflammatory factor monocyte chemoattractant protein-1 (MCP)-1 by nearly 30 fold compared with control. SCM almost abolished albumin-induced increase of MCP-1. Conclusion: These results suggest that SCM attenuated albumin-induced EMT in renal tubular cells via inhibiting activation of inflammatory factors, which may serve as a new therapeutic approach for chronic kidney diseases.
Module-based modeling of flow-type multistage manufacturing systems adopting dual-card Kanban system

A systematic procedure of module-based modeling is designed and proposed to develop a simulation of any flow-type multistage manufacturing system adopting especially the dual-card Kanban system. First, functional analysis is performed to present kanban flows exactly in the same fashion in a simulation model as they are actually appeared in the real manufacturing system. One Customer module, the required number of Workstation modules, and one Supplier module make a set to develop a designated simulation. In addition, a numerical example is shown to apply the proposed procedure.
The Foundations of Causal Inference : A Review ∗

This paper reviews recent advances in the foundations of causal inference and introduces a systematic methodology for defining, estimating and testing causal claims in experimental and observational studies. It is based on non-parametric structural equation models (SEM)– a natural generalization of those used by econometricians and social scientists in the 1950-60s, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring the effects of potential interventions (also called “causal effects” or “policy evaluation”), as well as direct and indirect effects (also known as “mediation”), in both linear and non-linear systems. Finally, the paper clarifies the role of propensity score matching in causal analysis, defines the relationships between the structural and potential-outcome frameworks, and develops symbiotic tools that use the strong features
A Game Model Based Co-evolutionary Algorithms for Multiobjective Optimization Problems

In this paper, we discuss multiobjective optimization problems solved by co-evolutionary algorithms. We present a game model based co-evolutionary algorithm (GMBCA) to solve this class of problems and its performance is analyzed in comparing its results with those obtained with four others algorithms. Finally, the GMBCA is applied to solve the nutrition decision making problem to map the Pareto-optimum front. The results in the problem show its effectiveness
Children's Risky Play from an Evolutionary Perspective: The Anti-Phobic Effects of Thrilling Experiences

This theoretical article views children's risky play from an evolutionary perspective, addressing specific evolutionary functions and especially the anti-phobic effects of risky play. According to the non-associative theory, a contemporary approach to the etiology of anxiety, children develop fears of certain stimuli (e.g., heights and strangers) that protect them from situations they are not mature enough to cope with, naturally through infancy. Risky play is a set of motivated behaviors that both provide the child with an exhilarating positive emotion and expose the child to the stimuli they previously have feared. As the child's coping skills improve, these situations and stimuli may be mastered and no longer be feared. Thus fear caused by maturational and age relevant natural inhibition is reduced as the child experiences a motivating thrilling activation, while learning to master age adequate challenges. It is concluded that risky play may have evolved due to this anti-phobic effect in normal child development, and it is suggested that we may observe an increased neuroticism or psychopathology in society if children are hindered from partaking in age adequate risky play.
Morphological and Genotypic Variations among the Species of the Subgenus Adlerius (Diptera: Psychodidae, Phlebotomus) in Iran

Background: Female sand flies of subgenus Adlerius are considered as probable vectors of visceral leishmaniasis in Iran. The objective of this study was to determine the morphological and genotypic variations in the populations of this subgenus in the country. Methods: Sand flies collected using sticky traps from 17 provinces during 2008–2010. The morphometric measurements were conducted with an Ocular Micrometer. Data was analyzed by SPSS. The Cytb gene was used to estimate population genetic diversity and identify the female specimens. UPGMA phenetic tree was used for DNA haplotypes of Cytb gene. Results: Six species of subgenus Adlerius identified from which one species, P. (Adlerius) kabulensis, is new record. The identification key is provided for males. Results revealed the molecular systematic in the species of subgenus Adlerius and determine the relationship of three females of P. comatus, P. balcanicus and P. halepensis. Conclusion: The positions of three females and the males in the UPGMA tree are correct and the similarities among them confirm our results. The branches of each species are not genetically distinct which justify the overlapping morphological characters among them. Molecular sequencing of Cytb-mtDNA haplotypes can be used for female identification for different species of subgenus Adlerius in Iran.