Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting k-Balanced Trusted Cliques in Signed Social Networks

k-Clique detection enables computer scientists and sociologists to analyze social networks' latent structure and thus understand their structural and functional properties. However, the existing k-clique-detection approaches are not applicable to signed social networks directly because of positive and negative links. The authors' approach to detecting k-balanced trusted cliques in such networks bases the detection algorithm on formal context analysis. It constructs formal contexts using the modified adjacency matrix after converting a signed social network into an unweighted one. Experimental results demonstrate that their algorithm can efficiently identify the trusted cliques.
National's Advanced Graphics Chip Set for High-Performance Graphics

To reinforce the growth of computer graphics, hardware architectures must be developed to support the rapid growth in display resolution that will occur in the next few years. The architectures must allow a high degree of application independence without requiring significant changes in the overhead software interface. The hardware architecture must be expandable, again avoiding significant software changes. Finally, the architecture must be implemented in VLSI for reasons of cost and speed. This article will describe a graphics hardware architecture that meets these criteria.
How Are Iraq/Afghanistan-Era Veterans Faring in the Labor Market?

This study examines labor market status of Veterans of the Iraq/Afghanistan-era and previous eras, and variations by age and by health status, using the Current Population Survey (CPS) March supplement from 2006 to 2011. Although this observational study does not demonstrate a causal effect of military service on labor market outcomes, the authors find that Iraq/Afghanistan-era service among the youngest Veterans (ages 18–24) was associated with higher earnings and greater odds of being enrolled in school, but also higher odds of unemployment. Military service in previous eras by older Veterans, particularly those in fair or poor health, was associated with higher odds of unemployment and lower earnings than their nonveteran counterparts. Future research should examine the reasons for the higher unemployment rates of the youngest Veterans and should examine whether receipt of services such as health care services, disability benefits, and military reintegration programs are associated with improved labor market outcomes.
Comprehensive Evaluation of the Association of APOE Genetic Variation with Plasma Lipoprotein Traits in U.S. Whites and African Blacks

Although common APOE genetic variation has a major influence on plasma LDL-cholesterol, its role in affecting HDL-cholesterol and triglycerides is not well established. Recent genome-wide association studies suggest that APOE also affects plasma variation in HDL-cholesterol and triglycerides. It is thus important to resequence the APOE gene to identify both common and uncommon variants that affect plasma lipid profile. Here, we have sequenced the APOE gene in 190 subjects with extreme HDL-cholesterol levels selected from two well-defined epidemiological samples of U.S. non-Hispanic Whites (NHWs) and African Blacks followed by genotyping of identified variants in the entire datasets (623 NHWs, 788 African Blacks) and association analyses with major lipid traits. We identified a total of 40 sequence variants, of which 10 are novel. A total of 32 variants, including common tagSNPs (≥5% frequency) and all uncommon variants (<5% frequency) were successfully genotyped and considered for genotype-phenotype associations. Other than the established associations of APOE*2 and APOE*4 with LDL-cholesterol, we have identified additional independent associations with LDL-cholesterol. We have also identified multiple associations of uncommon and common APOE variants with HDL-cholesterol and triglycerides. Our comprehensive sequencing and genotype-phenotype analyses indicate that APOE genetic variation impacts HDL-cholesterol and triglycerides in addition to affecting LDL-cholesterol.
Using scouts to predict swarm success rate

The scenario addressed here is that of a swarm of agents (simulated robots) that needs to travel from an initial location to a goal location, while avoiding obstacles. Before deploying the entire swarm, it would be advantageous to have a certain level of confidence that a desired percentage of the swarm will be likely to succeed in getting to the goal. The approach taken in this paper is to use a small group of expendable robot ldquoscoutsrdquo to predict the success probability for the swarm. Two approaches to solving this problem are presented and compared - the standard Bernoulli trials formula, and a new Bayesian formula. Extensive experimental results are summarized that measure and compare the mean-squared error of the predictions with respect to ground truth, under a wide variety of circumstances. Experimental conclusions include the utility of a uniform prior for the Bayesian formula in knowledge-lean situations, and the accuracy and robustness of the Bayesian approach. The paper also reports an intriguing result, namely, that both formulas usually predict better in the presence of inter-agent forces than when their independence assumptions hold.
Integrating Culture and Language Learning in Institution-wide Language Programmes

This paper argues for integrated culture and language study in institution-wide language programmes (IWLPs) at UK universities. Building on the assumption that all foreign language learning at university level should to be based on the principles of LSP (languages for specific purposes) teaching, the paper suggests that culture learning should be an integral component of language modules for non-specialist learners, who are increasingly likely to need culture skills in the university and the workplace. The culture focus, it is argued, will not only support linguistic competence and learner autonomy, but will also give coherence to and raise the profile of institution-wide language schemes. In combining culture and language learning, a skills-oriented and learner-centred approach is suggested. The paper goes on to discuss the targets, skills and materials of culture-integrated language learning and suggests a framework for adapting existing curricula and materials to independent culture and language study. Particular emphasis is given to the use of information technology and the Internet in supporting autonomous culture and language learners.
Automatic Sound Classification of Radio Broadcast News

Automatic extraction of the index of broadcast streams from radio and television has become a challenging research topic over the last years. The automatic classification of audio types, such as speech, music, noises/atypical events etc, has found numerous applications. In this paper we study the evaluation of different machine learning algorithms, which have successfully been used in other classification tasks, on the task of classification of audio broadcast news. The audio classification scheme consists of pre-processing, audio parameterization with established audio features, and classification to acoustic events. The experimental evaluation was carried out using the Voice of America broadcast recordings database for the Greek language. The experimental results indicated that the best performance, approximately 92% of accuracy, was achieved by the classification scheme using the boosting technique with decision trees.
Comparing maximum a posteriori vector quantization and Gaussian mixture models in speaker verification

Gaussian mixture model - universal background model (GMM-UBM) is a standard reference classifier in speaker verification. We have recently proposed a simplified model using vector quantization (VQ-UBM). In this study, we extensively compare these two classifiers on NIST 2005, 2006 and 2008 SRE corpora, while having a standard discriminative classifier (GLDS-SVM) as a reference point. We focus on parameter setting for N-top scoring, model order, and performance for different amounts of training data. The most interesting result, against a general belief, is that GMM-UBM yields better results for short segments whereas VQ-UBM is good for long utterances. The results also suggest that maximum likelihood training of the UBM is sub-optimal, and hence, alternative ways to train the UBM should be considered.
South Asian remittances: implications for development

Remittances are increasingly identified as golden eggs that contribute crucially to the foreign exchange earnings of many developing countries across the world. While their global value may be around US$150–200 billion, remittances to South Asia alone total perhaps US$40–50 billion. This paper seeks to document the flow of remittances into this region in an attempt to reveal the complexity of the procedures associated with the informal international transfer of funds. It argues that, if remittances are to serve development goals, they must be distinguished from other international transfers (some of which are associated with subversive and even criminal activities), and should not be subjected to heavy-handed forms of regulation and control that risk destroying the fragile links between foreign migrants working abroad and the households and local communities to whom they seek to send remittances for survival and development purposes.
Joint Parsing and Translation

Tree-based translation models, which exploit the linguistic syntax of source language, usually separate decoding into two steps: parsing and translation. Although this separation makes tree-based decoding simple and efficient, its translation performance is usually limited by the number of parse trees offered by parser. Alternatively, we propose to parse and translate jointly by casting tree-based translation as parsing. Given a source-language sentence, our joint decoder produces a parse tree on the source side and a translation on the target side simultaneously. By combining translation and parsing models in a discriminative framework, our approach significantly outperforms a forest-based tree-to-string system by 1.1 absolute BLEU points on the NIST 2005 Chinese-English test set. As a parser, our joint decoder achieves an F1 score of 80.6% on the Penn Chinese Treebank.
Weighted Spectral Cluster Ensemble

Clustering explores meaningful patterns in the non-labeled data sets. Cluster Ensemble Selection (CES) is a new approach, which can combine individual clustering results for increasing the performance of the final results. Although CES can achieve better final results in comparison with individual clustering algorithms and cluster ensemble methods, its performance can be dramatically affected by its consensus diversity metric and thresholding procedure. There are two problems in CES: 1) most of the diversity metrics is based on heuristic Shannon's entropy and 2) estimating threshold values are really hard in practice. The main goal of this paper is proposing a robust approach for solving the above mentioned problems. Accordingly, this paper develops a novel framework for clustering problems, which is called Weighted Spectral Cluster Ensemble (WSCE), by exploiting some concepts from community detection arena and graph based clustering. Under this framework, a new version of spectral clustering, which is called Two Kernels Spectral Clustering, is used for generating graphs based individual clustering results. Further, by using modularity, which is a famous metric in the community detection, on the transformed graph representation of individual clustering results, our approach provides an effective diversity estimation for individual clustering results. Moreover, this paper introduces a new approach for combining the evaluated individual clustering results without the procedure of thresholding. Experimental study on varied data sets demonstrates that the prosed approach achieves superior performance to state-of-the-art methods.
Detecting daily commuting distance from GPS trajectory

Most people have certain acceptance of daily travel distance, which determines where they choose to live, to work, and to go for leisure. Such information is an important input for facility location-allocation, urban planning and transport management. Therefore, daily commuting distance has been adopted as an indicator to measure the distance acceptance, the rationality of land use structure, and livability of a city. At the same time, daily commuting distance also can reveal many personal characteristics. However, such information traditionally is obtained by questionnaire which is both labor-intensive and time-consuming. And most importantly, the sampling could not be very comprehensive. With the popularization of mobile phones, it has become possible to obtain individual movement trajectories to understand personal travel behavior. Related studies have shown that, human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics (Barabási, 2005). This study uses GPS trajectories generated by smart phone to detect daily travel pattern, especially the daily commuting distance.
Pado: A Data Processing Engine for Harnessing Transient Resources in Datacenters

Datacenters are under-utilized, primarily due to unused resources on over-provisioned nodes of latency-critical jobs. Such idle resources can be used to run batch data analytic jobs to increase datacenter utilization, but these transient resources must be evicted whenever latency-critical jobs require them again. Resource evictions often lead to cascading recomputations, which is usually handled by checkpointing intermediate results on stable storages of eviction-free reserved resources. However, checkpointing has major shortcomings in its substantial overhead of transferring data back and forth. In this work, we step away from such approaches and focus on observing the job structure and the relationships between computations of the job. We carefully mark the computations that are most likely to cause a large number of recomputations upon evictions, to run them reliably using reserved resources. This lets us retain corresponding intermediate results effortlessly without any additional checkpointing. We design Pado, a general data processing engine, which carries out our idea with several optimizations that minimize the number of additional reserved nodes. Evaluation results show that Pado outperforms Spark 2.0. 0 by up to 5.1×, and checkpoint-enabled Spark by up to 3.8×.
The rhetoric of Islamic activism: A DICTION study

Given the paucity of understanding in the West regarding Middle Eastern discourse, this study provides a careful description of Islamic activist rhetoric. Using DICTION, a program that calculates some 40 different stylistic variables and 5 master variables, we compared the rhetoric of Western politicians, protestors, preachers, and pundits to that of Islamic activists. Relative to the West, the Islamic sample was relatively hopeful and communal, extremely doctrinaire, and often had a transcendental tone. Analysis within the Islamic sample showed it to be more flexible and variegated than might have been expected. Intriguingly, the rhetoric of violent Islamists was more optimistic than that of their nonviolent brethren. The violent groups were more likely to embrace charismatic authority and to substitute ideology for practicality. In short, our findings confirm some popular expectations of Muslim discourse but also call into question a number of received truths, all of which suggests that much more needs to be learned about the voices of Islam.
The relationship between alcohol consumption, perceived stress, and CRHR1 genotype on the hypothalamic–pituitary–adrenal axis in rural African Americans

Objective: Rurally situated African Americans suffer from stress and drug-related health disparities. Unfortunately, research on potential mechanisms that underlie this public health problem have received limited focus in the scientific literature. This study investigated the effects of perceived stress, alcohol consumption, and genotype on the hypothalamic–pituitary–adrenal (HPA) Axis. Methods: A rural sample of African American emerging adults (n = 84) completed a battery of assessments and provided six samples of salivary cortisol at wakeup, 30 min post wakeup, 90 min post wakeup, 3:00 PM, 3:30 PM, and 4:30 PM. Results: Participants with a TT genotype of the CRHR1 (rs4792887) gene tended to produce the most basal cortisol throughout the day while participants with a CC genotype produced the least amount. Increased levels of perceived stress or alcohol consumption were associated with a blunted cortisol awakening response (CAR). Moreover, the CAR was obliterated for participants who reported both higher stress and alcohol consumption. Conclusion: Perceived stress and alcohol consumption had a deleterious effect on the HPA-Axis. Furthermore, genotype predicted level of cortisol production throughout the day. These findings support the need to further investigate the relationship between stress dysregulation, drug-use vulnerability, and associated health disparities that affect this community.
Measuring Market Power in the Ready-to-Eat Cereal Industry

The ready-to-eat cereal industry is characterized by high concentration, high price-cost margins, large advertising-to-sales ratios, and numerous introductions of new products. Previous researchers have concluded that the ready-to-eat cereal industry is a classic example of an industry with nearly collusive pricing behavior and intense non-price competition. This paper empirically examines this conclusion. In particular, I estimate price-cost margins, but more importantly I am able empirically to separate these margins into three sources: (1) that which is due to product differentiation; (2) that which is due to multi-product firm pricing; and (3) that due to potential price collusion. The results suggest that given the demand for different brands of cereal, the first two effects explain most of the observed price-cost markups. I conclude that prices in the industry are consistent with non-collusive pricing behavior, despite the high price- cost margins. Leading firms are able to maintain a portfolio of differentiated products and influence the perceived product quality. It is these two factors that lead to high price-cost margins.
Making sense of disengagement in the primary classroom: a study of pupil, teacher and parent perceptions

This paper is based upon the findings of an interpretative, school‐based study of pupil, teacher and parent perceptions of disengagement within the primary classroom. It examines how pupil and parent perceptions support or challenge professional discourses about pupil behaviour, raising questions about the nature of disengagement and the intervention strategies used to manage it. The central finding of the study is that pupil, teacher and parent perceptions show a striking lack of intersubjectivity. Though there are some commonalities of perception between participants, most of these commonalities are shared by pupils and parents, rather than pupils and teachers. It is argued that the underlying lack of shared meaning between teachers and pupils skews classroom interaction and obfuscates teacher intervention, accounting for the poor relationships, and the breakdown of teaching and learning, in the classrooms observed. The explanatory concept of pupil and teacher ‘survival strategies’ is used to explore this negative dynamic.
On consciousness in syntactic learning and judgment: A reply to Reber, Allen, and Regan

In this article we examine Reber, Allen, and Regan's (1985) commentary on our analysis of consciousness and abstraction in a case of syntactical learning and judgment (Dulany, Carlson, & Dewey, 1984). We reject their methodological criticism; it is not recall, but assessment at the moment of judgment, that maximizes the validity of reports of rules in consciousness at many moments of judgment. Furthermore, as our computer simulations show, if subjects' reports were merely guessed justifications of unconsciously controlled judgments, the obtained relation of rules to judgments is an event so deviant as to be expected about once in 10 billion occasions. In addition, we discuss a number of broader issues raised by our analysis and their response: judgment after early learning and after automatization, correlated grammars and consciousness, the scope and mental abstractness of rules, conscious and unconscious control, and intuition. Although Reber et al. raise questions that should be examined, we find no reason to revise the interpretation of our experiment. In their commentary, Reber, Allen, and Regan (1985) raise two related methodological issues and greatly broaden the theoretical issue. We welcome the opportunity to reply, rebutting their methodological criticism and placing our analysis in its broader theoretical context. These are methodological issues that anyone investigating consciousness should face, and the broader question of the role of consciousness in the mind should be a central concern of current psychology (Hilgard, 1980; Mandler, 1975; Miller, 1980; Norman 1980). On Methodology
Outbound Load Balancing in BGP Using Online Simulation

In this paper, we investigate a specific interdomain traffic engineering problem: the outbound load balancing in a multi-homed Autonomous System (AS). We present an optimization-based approach for this problemwithout modifying BGP protocol in any way. In this approach, the load balancing problem is generalized as a black-box optimization problem. The Online Simulation system [1], specifically designed for this class of problems, can be applied to adaptively adjust BGP configuration to achieve load balancing. This approach is also very flexible in that other optimization objectives can be used to achieve different TE objectives easily. The simulation results show that the proposed scheme substantially improves the load balancing or packet drop probability at the outbound links of a multi-homed AS.
Changes in Enteric Neurons of Small Intestine in a Rat Model of Irritable Bowel Syndrome with Diarrhea

Background/Aims Physical and/or emotional stresses are important factors in the exacerbation of symptoms in irritable bowel syndrome (IBS). Several lines of evidence support that a major impact of stress on the gastrointestinal tract occurs via the enteric nervous system. We aimed to evaluate histological changes in the submucosal plexus (SMP) and myenteric plexus (MP) of the distal ileum in concert with the intestinal motor function in a rat model of IBS with diarrhea. Methods The rat model was induced by heterotypic chronic and acute stress (CAS). The intestinal transit was measured by administering powdered carbon by gastric gavage. Double immunohistochemical fluorescence staining with whole-mount preparations of SMP and MP of enteric nervous system was used to assess changes in expression of choline acetyltransferase, vasoactive intestinal peptide, or nitric oxide synthase in relation to the pan neuronal marker, anti-Hu. Results The intestinal transit ratio increased significantly from control values of 50.8% to 60.6% in the CAS group. The numbers of enteric ganglia and neurons in the SMP were increased in the CAS group. The proportions of choline acetyltransferase- and vasoactive intestinal peptide-immunoreactive neurons in the SMP were increased (82.1 ± 4.3% vs. 76.0 ± 5.0%, P = 0.021; 40.5 ± 5.9% vs 28.9 ± 3.7%, P = 0.001), while nitric oxide synthase-immunoreactive neurons in the MP were decreased compared with controls (23.3 ± 4.5% vs 32.4 ± 4.5%, P = 0.002). Conclusions These morphological changes in enteric neurons to CAS might contribute to the dysfunction in motility and secretion in IBS with diarrhea.