Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of network setting and gender in online content popularity

ABSTRACT In this study, we explore the role of specific network structures that enhance social capital and assess the extent to which gender, social ties, and communication interaction relate to content popularity within online social networks (OSNs). Our results are based on an extensive OSN data set, containing over 100,000 members, connected by over 1.7 million links. The findings indicate that content popularity inference is more accurate when considering activity interaction among users and that network structures known as advantageous for amassing social capital in the offline environment are relevant online as well. We conclude by discussing how gender mediates the correlation between some network measures and the growth of users’ content popularity and provide a potential explanation for the emergence of gender differences.
Recognizing composite sketches with digital face images via SSD dictionary

Sketch recognition has important law enforcement applications in detecting and apprehending suspects. Compared to hand drawn sketches, software generated composite sketches are faster to create and require lesser skill sets as well as bring consistency in sketch generation. While sketch generation is one side of the problem, recognizing composite sketches with digital images is another side. This paper presents an algorithm to address the second problem, i.e. matching composite sketches with digital images. The proposed algorithm utilizes a SSD based dictionary generated via 50,000 images from the CMU Multi-PIE database. The gallery-probe feature vectors created using SSD dictionary are matched using GentleBoostKO classifier. The results on extended PRIP composite sketch database show the effectiveness of the proposed algorithm.
Molecular basis of the attenuated phenotype of human APOBEC3B DNA mutator enzyme

The human APOBEC3A and APOBEC3B genes (A3A and A3B) encode DNA mutator enzymes that deaminate cytidine and 5-methylcytidine residues in single-stranded DNA (ssDNA). They are important sources of mutations in many cancer genomes which show a preponderance of CG->TA transitions. Although both enzymes can hypermutate chromosomal DNA in an experimental setting, only A3A can induce double strand DNA breaks, even though the catalytic domains of A3B and A3A differ by only 9% at the protein level. Accordingly we sought the molecular basis underlying A3B attenuation through the generation of A3A-A3B chimeras and mutants. It transpires that the N-terminal domain facilitates A3B activity while a handful of substitutions in the catalytic C-terminal domain impacting ssDNA binding serve to attenuate A3B compared to A3A. Interestingly, functional attenuation is also observed for the rhesus monkey rhA3B enzyme compared to rhA3A indicating that this genotoxic dichotomy has been selected for and maintained for some 38 million years. Expression of all human ssDNA cytidine deaminase genes is absent in mature sperm indicating they contribute to somatic mutation and cancer but not human diversity.
EHE-LEACH: Enhanced heterogeneous LEACH protocol for lifetime enhancement of wireless SNs

Wireless Sensor Network (WSNs) are collection of small Sensor Nodes (SNs) which are capable of performing multiple tasks such as data aggregation, processing and communication either to other SNs or to the Base Station (BS). As SNs are battery operated, so efficient utilization of energy during various operations in WSNs is one of the major issues which requires special attention. It has been observed in literature that Hierarchical clustering and the node heterogeneity are the two parameters by which the lifetime of WSNs can be enhanced. Keeping in view of the above, in this paper, we propose an Enhanced Heterogeneous LEACH (EHE-LEACH) Protocol for Lifetime Enhancement of SNs. A fixed distance based threshold is used for the bifurcation of direct communication and cluster based communication in the proposed scheme. SNs near to the BS communicate directly and those which are far away from the BS use cluster based communication. To evaluate the performance of the proposed scheme two key parameters known as: Half Nodes Alive (HNA) and Last Node Alive (LNA) are selected. By selecting the distance based threshold with the ratio of 1:9 between direct communication and cluster based communication it has been observed that EHE-LEACH has better network lifetime with respect to various parameters in comparison to the other well known proposals such as LEACH and SEP.
The New Institutional Economics: Taking Stock, Looking Ahead

This paper examines the progressive development of the new institutional economics over the past quarter century. It begins by distinguishing four levels of social analysis, with special emphasis on the institutional environment and the institutions of governance. It then turns to some of the good ideas out of which the NIE works: the description of human actors, feasibility, firms as governance structures, and operationalization. Applications, including privatization, are briefly discussed. Its empirical successes, public policy applications, and other accomplishments notwithstanding, there is a vast amount of unfinished business.
Towards a Gravity-Based Trust Model for Social Networking Systems

Web-based social networks are emerging as the top applications on the Internet. With this immense popularity, many of the shortcomings of the current social network deployments are also coming to light. One of the glaring problems with existing web-based social networks is trust management. In this paper, we focus on trust modeling in social networks. Another allied issue that is not considered here is using trust in managing the activities within the social network. We introduce a gravity-based model for estimating trust. We present the complete model along with the trust computation algorithms. We present initial results from a simulation study that investigates the feasibility of the proposed scheme.
Employability skills for entry-level human resources management positions: Perceptions of students and employers

This paper offers (a) a multidimensional Employability Skill Scale development method, and (b) one 30-item, seven-dimensional, and another 26-item six-dimensional employability skill requirement scale for use with entry-level human resources management positions, as perceived by employers and students, respectively, in Bangladesh. The study is based on samples of 174 and 446 survey responses collected from corporate managers and university students, respectively. There were significant variations in opinions between employers and students on employability skill requirements in entry-level human resources management positions. Employers prioritized skills such as subject knowledge, applying knowledge, listening effectively, breadth of knowledge, working safely, and self-management. On the other hand, students preferred skills such as team leading ability, complex problem-solving ability, judgment ability, proactivity, negotiation ability, strength of reference, type of university, and image of the university.
Evolutionary and plastic responses to climate change in terrestrial plant populations

As climate change progresses, we are observing widespread changes in phenotypes in many plant populations. Whether these phenotypic changes are directly caused by climate change, and whether they result from phenotypic plasticity or evolution, are active areas of investigation. Here, we review terrestrial plant studies addressing these questions. Plastic and evolutionary responses to climate change are clearly occurring. Of the 38 studies that met our criteria for inclusion, all found plastic or evolutionary responses, with 26 studies showing both. These responses, however, may be insufficient to keep pace with climate change, as indicated by eight of 12 studies that examined this directly. There is also mixed evidence for whether evolutionary responses are adaptive, and whether they are directly caused by contemporary climatic changes. We discuss factors that will likely influence the extent of plastic and evolutionary responses, including patterns of environmental changes, species’ life history characteristics including generation time and breeding system, and degree and direction of gene flow. Future studies with standardized methodologies, especially those that use direct approaches assessing responses to climate change over time, and sharing of data through public databases, will facilitate better predictions of the capacity for plant populations to respond to rapid climate change.
Data Epistemologies / Surveillance and Uncertainty

Data Epistemologies studies the changing ways in which ‘knowledge’ is defined, promised, problematised, legitimated vis-á-vis the advent of digital, ‘big’ data surveillance technologies in early twenty-first century America. As part of the period’s fascination with ‘new’ media and ‘big’ data, such technologies intersect ambitious claims to better knowledge with a problematisation of uncertainty. This entanglement, I argue, results in contextual reconfigurations of what ‘counts’ as knowledge and who (or what) is granted authority to produce it – whether it involves proving that indiscriminate domestic surveillance prevents terrorist attacks, to arguing that machinic sensors can know us better than we can ever know ourselves. The present work focuses on two empirical cases. The first is the ‘Snowden Affair’ (2013-Present): the public controversy unleashed through the leakage of vast quantities of secret material on the electronic surveillance practices of the U.S. government. The second is the ‘Quantified Self ’ (2007-Present), a name which describes both an international community of experimenters and the wider industry built up around the use of datadriven surveillance technology for self-tracking every possible aspect of the individual ‘self ’. By triangulating media coverage, connoisseur communities, advertising discourse and leaked material, I examine how surveillance technologies were presented for public debate and speculation. This dissertation is thus a critical diagnosis of the contemporary faith in ‘raw’ data, sensing machines and algorithmic decision-making, and of their public promotion as the next great leap towards objective knowledge. Surveillance is not only a means of totalitarian control or a technology for objective knowledge, but a collective fantasy that seeks to mobilise public support for new epistemic systems. Surveillance, as part of a broader enthusiasm for ‘data-driven’ societies, extends the old modern project whereby the human subject – its habits, its affects, its actions – become the ingredient, the raw material, the object, the target, for the production of truths and judgments about them by things other than themselves. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Communication First Advisor Carolyn Marvin
Algorithms for Vertex Partitioning Problems on Partial k-Trees

In this paper, we consider a large class of vertex partitioning problems and apply to them the theory of algorithm design for problems restricted to partial k-trees. We carefully describe the details of algorithms and analyze their complexity in an attempt to make the algorithms feasible as solutions for practical applications. We give a precise characterization of vertex partitioning problems, which include domination, coloring and packing problems, and their variants. Several new graph parameters are introduced as generalizations of classical parameters. This characterization provides a basis for a taxonomy of a large class of problems, facilitating their common algorithmic treatment and allowing their uniform complexity classification. We present a design methodology of practical solution algorithms for generally $\NP$-hard problems when restricted to partial k-trees (graphs with treewidth bounded by k). This "practicality" accounts for dependency on the parameter k of the computational complexity of the resulting algorithms. By adapting the algorithm design methodology on partial k-trees to vertex partitioning problems, we obtain the first algorithms for these problems with reasonable time complexity as a function of treewidth. As an application of the methodology, we give the first polynomial-time algorithm on partial k-trees for computation of the Grundy number.
Inferior frontal white matter asymmetry correlates with executive control of attention

White matter (WM) asymmetries of the human brain have been well documented using diffusion tensor imaging (DTI). However, the relationship between WM asymmetry pattern and cognitive performance is poorly understood. By means of tract‐based spatial statistics (TBSS) and voxel‐based analyses of whole brain, this study examined the WM asymmetries and the correlations between WM integrity/asymmetries and three distinct components of attention, namely alerting, orienting, and executive control (EC), which were assessed by attention network test (ANT). We revealed a number of WM anisotropy asymmetries, including leftward asymmetry of cingulum, corticospinal tract and cerebral peduncle, rightward asymmetry of internal capsule, superior longitudinal fasciculus and posterior corona radiata, as well as heterogeneous asymmetries in anterior corpus callosum and anterior corona radiata (ACR). Moreover, specific correlation was found between asymmetric pattern of inferior frontal ACR and EC performance. Additionally, this study also proposed that there were no significant relationships of WM anisotropy asymmetries to alerting and orienting functions. Further clusters of interest analyses and probabilistic fiber tracking validated our findings. In conclusion, there are a number of differences in WM integrity between human brain hemispheres. Specially, the anisotropy asymmetry in inferior frontal ACR plays a crucial role in EC function. Our finding is supportive of the functional studies of inferior frontal regions and in keeping with the theory of the brain lateralization on human ventral attention system. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.
Comparing Pre-Post Change Across Groups: Guidelines for Choosing between Difference Scores, ANCOVA, and Residual Change Scores

Psychological researchers often investigate differences between groups in the amount of change from pre-test to post-test. For example, researchers treating a group of depressed students may wish to compare the amount of improvement from pre-intervention to post-intervention for males and females, or the researchers may randomly assign participants to groups and compare their improvement across two treatments. In the first case, there are likely to be pre-test differences between the groups, whereas in the second case no pre-test group differences are expected. Three of the most popular methods for comparing independent groups with regard to the amount of change are difference scores, ANCOVA, and residualized change scores. Although the choice between these methods is sometimes clear, in most instances this is not the case. In this research, a simulation study was used to determine the effect of many common issues on the bias, Type I error rates, and power of the difference score, ANCOVA, and residual change score. These issues included: sample size, reliability of the measure, floor/ceiling effects, effect size, and baseline group differences. Results from the study are used to provide specific recommendations with regards to applying each of these three methods.
The Relationship of Student Learning Styles and Achievement in History Subject

Learning styles are essential elements for students’ as learning styles have its strong influence on the achievement of a subject.The objective of the study is to investigate the relationship between learning styles and student’s achievement in History subject.This study identifies six different Grasha learning styles by gender and relationship to student achievement in History subject.Suitability of students learning styles in the History subjects will be more effective and provide a positive impact on students’ academic if the teaching process and learning tailored to students' learning styles.A total of 200 students were selected as respondents from two schools in the district of Kulim, Kedah. A set of questionnaire instrument was used to measure students' learning style preferences.Overall; the tendencies of students to use learning styles are at a higher level unless avoidance learning styles. The T-test showed no difference between learning styles based on gender. Pearson correlation analysis showed no significant relationship between learning styles and achievement of student in History subject.A study implication towards teachers is the need of diversification of skills and teaching methods in the classroom. This, in turn, will foster interest and improve learning habit among students.As a result, students can achieve better in History subject.
CaSCADE: Compressed Carrier and DOA Estimation

Spectrum sensing and direction of arrival (DOA) estimation have both been thoroughly investigated. Estimating the support of a set of signals and their DOAs is crucial to many signal processing applications, such as cognitive radio (CR). A challenging scenario, faced by CRs, is that of multiband signals, composed of several narrowband transmissions spread over a wide spectrum each with unknown carrier frequency and DOA. The Nyquist rate of such signals is high and constitutes a bottleneck for both analog and digital processing. To alleviate the sampling rate issue, several sub-Nyquist sampling methods, such as multicoset or the modulated wideband converter (MWC), have been proposed in the context of spectrum sensing. In this paper, we first suggest an alternative sub-Nyquist sampling and signal reconstruction method to the MWC, based on a uniform linear array (ULA). We then extend our approach to joint spectrum sensing and DOA estimation and propose the CompreSsed CArrier and DOA Estimation (CaSCADE) system, composed of an L-shaped array with two ULAs. In both cases, we derive conditions for perfect recovery of the signal parameters and the signal itself and provide two reconstruction algorithms. The first is based on the ESPRIT method and the second on compressed sensing techniques. Both our joint carriers and DOA recovery algorithms overcome the well-known pairing issue between the two parameters. Simulations demonstrate joint carrier and DOA recovery from CaSCADE sub-Nyquist samples. In addition, we show that our alternative spectrum sensing system outperforms the MWC in terms of recovery error and design complexity.
When daddy comes to school: father–school involvement and children’s academic and social–emotional skills

ABSTRACT The present study used a large sample of mostly non-resident fathers (74%) to determine whether father–school involvement (e.g. attending parent–teacher conferences) predicted better academic and social emotional skills after controlling for the influence of mother–school involvement, the quality of children’s home learning environment, and demographics. A total of 3570 children participated in the study (47% European American, 35% African-American, and 18% Hispanic). Although mothers in this study engaged in more frequent involvement in their children’s schools, father–school involvement was positively associated with children’s reading, math, and teacher-rated approaches to learning scores in elementary school. Furthermore, father–school involvement predicted better reading and math scores after controlling for the influence of mother–school involvement, the quality of children’s home learning environment, and demographics.
Physical Activity of Parents of Children with Autism Spectrum Disorder

Abstract A preliminary study was conducted to investigate the physical activity status of parents of children with autism spectrum disorder (ASD) and related demographic characteristics. Thirty-four parents completed the IPAQ-S and demographic survey. Mean metabolic equivalent-minutes per week (MET-min/week) across participants was 3371. Significant correlations were found between parent’s age and moderate (τ = .287, p = .034) and vigorous (τ = .318, p = .020) physical activity minutes as well as vigorous (τ = .308, p = .021) and total (τ = .366, p = .005) MET-min/week. Similarly, significant correlations were found between child’s age and walking minutes (τ = .412, p = .002), walking MET-min/week (τ = .380, p = .005) and total MET-min/week (τ = .342, p = .010). This study provides current evidence about the physical activity participation of parents of children with ASD, and demonstrates a need for further research exploring barriers and facilitators towards physical activity for this population.
Factors to Curb Tax Evasion: Evidences from the TAXSIM Agent-Based Simulation Model

Agent based models are proposed as an adequate tool for analysing tax payer decisions and, thereby, the consequences of such decisions as they manifest themselves at the macro level. TAXSIM models the conduct of agents of three types, i.e. employers, employees and the government, in an economy of a single sector. Using this model, we examine the conduct of each individual agent and the impact of their decisions on the size of tax evasion and aggregated tax revenues. The main objective is the analysis of the relations between the government and tax payers, as well as the identification of how this relationship affects tax evasion. In this paper, the operation of several factors affecting the incidence of non-registered employment is studied with the help of an improved version of the TAXSIM agent-based simulation model. We analyse the effects of unemployment experience, the quality of government services and the audit strategy of the tax authority on totally hidden, mixed (hidden and legal) and totally legal payments. We start by a brief overview of the TAXSIM model and introduce the novel components in detail. This is followed by a thorough analysis of a vast series of computational experiments, analysing the behavior of the base model, as well as the effect of the newly introduced components (i.e., unemployment experience, adaptive audit strategy, etc.) and their various parameters. Our computational results suggest that the government can use effective tools to improve tax morale and curb tax evasion. Beyond improving the frequency and precision of tax audits the implementation of an adaptive tax audit strategy, the reduction of the exposure to unemployment or, on the motivation side, the improvement of the quality of government services can also be effective.
DETERMINANTS AND CHARACTERISTICS OF UNMARRIED COHABITATION AND ITS IMPACTS ON MARRIAGE: WESTERN EXPERIENCES

Hidup bersama tanpa nikah merupakan fenomena yang tidak asing di Barat. Ada beberapa aspek menarik yang dapat dipelajari dari fenomena itu. Hasil-hasil penelitian menunjukkan latar belakang, karakteristikdan pola hubungan sosial yang spesifik pada individu yang memilih hidup bersama tanpa nikah. Hal lain yang menarik dari fenomena itu adalah efeknya terhadap perkawinan. Anggapan bahwa melakukan kumpul kebo sebelum nikah akan menurunkan risiko terjadinya perceraian, ternyata tidak terbukti. Tidak terbuktinya hipotesis bahwa kumpul kebo merupakan persiapan pernikahan memunculkan anggapan bahwa pola hubungan itu sebagai alternatif pernikahan atau upaya untuk tidak terikat. Ketiga anggapan itupun belum jelas terbukti dalam tulisan ini. Sementara itu ada anggapan yang kuat bahwa hakekat pernikahan tidak berubah dengan makin banyaknya pasangan yang memilih hidup tanpa nikah