Miracle-dz/UniFAR-FTUs huggingface dataset:
IT AND SOCIAL INEQUALITY IN THE NETHERLANDS

In the Netherlands, access to IT is unevenly distributed among population groups. As in other countries, males, young people, the higher educated and higher income groups take the lead. This pattern also applies for the possession of a PC and for Internet access at home, as well as for the frequency and diversity of use and for digital skills. These differences coincide with old inequalities. However, the rise of IT also leads to new inequalities. Early adopters of a PC have gained an early advantage, and they have a lasting lead compared to laggards. Early adopters more often have Internet access at home, they have more digital skills, and they use the PC more often. These differences cut across existing social inequalities. This lead by early adopters also applies to differences between early and later adopters with regard to e-commerce and establishing new social contacts via the Web.
Causes of Software/Information Technology Project Failures In Nigerian Software Development Organizations

Managing the software development process has become one of the major areas for research especially in today’s information driven economy. A literature search shows that most software development projects are considered as partial failures due to technical and nontechnical factors. There is however dearth of information on studies of the state of software development in Nigeria which forms the focus of this paper. Using descriptive research methods, an introspective assessment of 20 randomly selected software development organizations in Nigeria was performed. The findings show that most software development organizations do not adopt structured software development methodologies. Other factors contributing to failures/chaos in software development in Nigeria are also reported.
Multi-stage attack detection and signature generation with ICS honeypots

New attack surfaces are emerging with the rise of Industrial Control System (ICS) devices exposed on the Internet. ICS devices must be protected in a holistic and efficient manner; especially when these are supporting critical infrastructure. Taking this issue into account, cyber-security research is recently being focused on providing early detection and warning mechanisms for ICSs. In this paper we present a novel honeypot capable of detecting multi-stage attacks targeting ICS networks. Upon detecting a multi-stage attack, our honeypot can generate signatures so that misuse Intrusion Detection Systems (IDSs) can subsequently thwart attacks of the same type. Our experimental results indicate that our honeypot and the signatures it generates provide good detection accuracy and that the Bro IDS can successfully use the signatures to prevent future attacks.
Separators and Structure Prediction inSparse Orthogonal

In the factorization A = QR of a matrix A, the orthogonal matrix Q can be represented either explicitly (as a matrix) or implicitly (as a matrix H of Householder vectors). We derive both upper and lower bounds on the number of nonzeros in H and the number of nonzeros in Q, in the case where the graph of A T A has \good" separators and A need not be square. We also derive an upper bound on the number of nonzeros in the null-basis part of Q in the case where A is the edge-vertex incidence matrix of a planar graph. The signiicance of these results is that they both illuminate and amplify a folk theorem of sparse QR factorization, which holds that the matrix H of Householder vectors represents the orthogonal factor of A much more compactly than Q itself. To facilitate discussion of this and related issues, we review several related results which have appeared previously.
Clustering of Genetically Defined Allele Classes in the Caenorhabditis elegans DAF-2 Insulin/IGF-1 Receptor

The DAF-2 insulin/IGF-1 receptor regulates development, metabolism, and aging in the nematode Caenorhabditis elegans. However, complex differences among daf-2 alleles complicate analysis of this gene. We have employed epistasis analysis, transcript profile analysis, mutant sequence analysis, and homology modeling of mutant receptors to understand this complexity. We define an allelic series of nonconditional daf-2 mutants, including nonsense and deletion alleles, and a putative null allele, m65. The most severe daf-2 alleles show incomplete suppression by daf-18(0) and daf-16(0) and have a range of effects on early development. Among weaker daf-2 alleles there exist distinct mutant classes that differ in epistatic interactions with mutations in other genes. Mutant sequence analysis (including 11 newly sequenced alleles) reveals that class 1 mutant lesions lie only in certain extracellular regions of the receptor, while class 2 (pleiotropic) and nonconditional missense mutants have lesions only in the ligand-binding pocket of the receptor ectodomain or the tyrosine kinase domain. Effects of equivalent mutations on the human insulin receptor suggest an altered balance of intracellular signaling in class 2 alleles. These studies consolidate and extend our understanding of the complex genetics of daf-2 and its underlying molecular biology.
Testing Associations of Plant Functional Diversity with Carbon and Nitrogen Storage along a Restoration Gradient of Sandy Grassland

The trait-based approach shows that ecosystem function is strongly affected by plant functional diversity as reflected by the traits of the most abundant species (community-weighted mean, CWM) and functional dispersion (FDis). Effects of CWM and FDis individually support the biomass ratio hypothesis and the niche complementarity hypothesis. However, there is little empirical evidence on the relative roles of CWM traits and FDis in explaining the carbon (C) and nitrogen (N) storage in grassland ecosystems. We measured plant functional traits in the 34 most abundant species across 24 sites along a restoration gradient of sandy grassland (mobile dune, semi-fixed dune, fixed dune, and grassland) in Horqin Sand Land, northern China. Thereafter, we calculated the CWM traits, the functional divergence of each single trait (FDvar) and the trait dispersion of multiple traits (FDis). We also measured the C and N storage in plant, litter, root, and soil. Using a stepwise multiple regression analysis, we further assessed which of the functional diversity components best explained C and N storage in the sandy grassland restoration. We found consistent links between C or N storage and leaf traits related to plant resource use strategy. However, the CWM of plant height was retained as an important predictor of C and N storage in plant, litter, soil, and total ecosystem in the final multiple models. CWMs of specific leaf area and plant height best predicted soil C and N storage and total ecosystem N storage. FDis was one of good predictors of litter C and N storage as well as total ecosystem C storage. These results suggest that ecosystem C and N pools in the sandy grassland restoration are primarily associated with the traits of the most abundant species in communities, thereby supporting the biomass ratio hypothesis. The positive associations of FDis with C storage in litter and total ecosystem provide evidence to support the niche complementarity hypothesis. Both functional traits of dominant species and traits’ dispersion in plant communities could contribute to explaining total ecosystem C storage. Thus, single- and multi-trait indices of functional composition play a crucial role in predicting C storage in sandy grasslands.
Receiver Operating Characteristic (ROC) Area Under the Curve (AUC): A Diagnostic Measure for Evaluating the Accuracy of Predictors of Education Outcomes

Abstract Early Warning Systems (EWS) and Early Warning Indictors (EWI) have recently emerged as an attractive domain for states and school districts interested in predicting student outcomes using data that schools already collect with the intention to better time and tailor interventions. However, current diagnostic measures used across the domain do not consider the dual issues of sensitivity and specificity of predictors, key components for considering accuracy. We apply signal detection theory using Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) analysis adapted from the engineering and medical domains, and using the pROC package in R. Using nationally generalizable data from the Education Longitudinal Study of 2002 (ELS:2002) we provide examples of applying ROC accuracy analysis to a variety of predictors of student outcomes, such as dropping out of high school, college enrollment, and postsecondary STEM degrees and careers.
Conflict Management in Occupational Therapy Education: Process Drama as a Teaching Strategy

The stressful and demanding environment of a healthcare facility can lead to interpersonal conflict. As a result of working in these environments, occupational therapy students may experience such conflict during Level II fieldwork. Research has shown that effective conflict management is an important component of success on Level II fieldwork; however, occupational therapy students often self-report a lack of confidence, comfort, and competence with managing conflict. Forty Master of Occupational Therapy students took part in a 2-day conflict management workshop. The workshop consisted of didactic training of conflict management concepts; large group process drama activities that introduced relevant role-play concepts; and small groups process drama activities that applied role-play concepts specific to fieldwork conflict scenarios. Evaluation was conducted through preand post-surveys before and after the training. Preand post-surveys both gauged students’ self-perceptions of confidence, competence, and comfort around conflict management. The mean average of students’ self-perceptions of comfort, confidence, and competence with regard to conflict management improved after participation in the workshop. An independent samples t-test was completed for each self-perception question (confidence, comfort, and competence). There was significant difference in the scores for two questions: confidence pre-survey (M=2.95) and confidence post-survey (M=3.31); t(78)=3.46, p
Exploring obstacles faced by gifted minority students through Bronfenbrenner’s bioecological systems theory

ABSTRACT For the past several decades, issues such as underrepresentation of racial/ethnic minority students in gifted programming, as well as the widening of the existing achievement gap between specific minority and majority groups have persisted. The majority of gifted education researchers studying underrepresentation in gifted programming focus on consequences resulting from a single setting in which the student interacts (e.g. home, school). Consequently, less attention is given to the nested network of interactions between multiple settings that play a role in underrepresentation. It is our goal to examine the existing frameworks that have been used to understand the obstacles faced by students who are underrepresented in their school’s gifted programs. By providing examples of proximal processes and the Process–Person–Context–Time (PPCT) model, we show how Bronfenbrenner’s bioecological systems theory provides the most suitable framework for exploring (1) identification issues for underrepresented minority students with gifted capabilities who have not been formally identified for gifted programming and (2) challenges faced by underrepresented minority students who have participated in a gifted program after having been formally identified as gifted. Research and educational implications are discussed.
Statistical Mechanics Algorithm for Response to Targets (SMART)

It is proposed to apply modern methods of nonlinear nonequilibrium statistical mechanics to develop software algorithms that will optimally respond to targets within short response times with minimal computer resources. This Statistical Mechanics Algorithm for Response to Targets (SMART) can be developed with a view towards its future implementation into a hardwired Statistical Algorithm Multiprocessor (SAM) to enhance the efficiency and speed of response to targets (SMART_SAM).
The Variability of Compound Stress in English : Towards an Exemplar-Based Alternative to the Compound Stress Rule

Recent research has shown that the Compound Stress Rule cannot adequately handle the variable stress behaviour of noun-noun constructs in English (e.g. Plag, 2006, Plag et al., 2006a, 2006b). In this paper we present an analysis of compound stress assignment in exemplarbases models, using data from two corpora, CELEX (Baayen et al., 1995) and the Boston University Radio Speech Corpus (Ostendorf et al., 1996). The data were coded according to a number of semantic and structural criteria taken from the literature on compound stress. Two different algorithms are tested, TiMBL 5.1 (Daelemans et al., 2004) and AM::Parallel (Skousen et al., 2004), and it turns out that both analogical algorithms are superior to previous, categorical approaches.
Global Economy and Labor Force Migration: The Case of Iranian Workers in Japan

A large number of Iranian youth left Iran for Japan hoping to fi nd high-paying jobs at the outset, and for the duration, of the bubble economy. When the bubble burst and unemployment began to increase in Japan, most of these workers returned to Iran, while some migrated to Canada, Australia, Thailand, Singapore and other Asian countries. This article assesses Iranian immigration via analysis of a database of Japanese government statistics, created for this research. This quantitative analysis is combined with the results of 60 in-depth interviews of Iranian workers in which the hidden aspects of global migration emerge. The quality of workers’ lives is shown to be of great concern, with visa status proving the greatest barrier to the safeguarding of health and safety.
An Exploration of English Language Teaching Pedagogy in Secondary Yemeni Education: A Case Study

The teaching of English at the Yemeni public schools has been criticized as ineffective due to the poor level of the language competency of most school leavers though they spend six years studying English whose curriculum, according to Bose (2002), is largely based on the Communicative Language Teaching (CLT). In this respect, this paper mainly attempted to: 1) investigate Yemeni English teachers’ classroom teaching practices in secondary schools, (2) Explore the Yemeni teachers’ awareness of CLT, and 3) explore the constraints teachers face while implementing the CLT. The results of the study indicate that the Grammar Translation Method (GTM) is the predominant pedagogy practiced by the EFL teachers participated in this study. The use of the mother-tongue, both by teachers and students were noticed to be the prevailing. The meanings of words are given in Arabic and the teachers do not focus on developing students’ fluency rather they focus on grammar. The results also show that the participants do not have a clear cut idea regarding the principles and concepts of CLT and are not clear about what they do in the classroom. The constraints faced by the participants while implementing CLT are also investigated and presented in the paper.
"We are the employment team": Socialisation in European Parliament committees and possible effects on policy-making

EP committees have become a key element in the EU policy-making process and can be seen as a vital contribution to the shaping of legislation: Westlake (1994, p. 191) effectively described them as the “legislative backbone” of the EP. Although committees play such an important role within the EP until the mid 1990s they rarely were at the focus of academic attention. More recently some studies have tried to shed some light on these fora in order to explain how they contribute to the functioning of the EP as a whole (Mamadouh and Raunio 2003; McElroy 2001; Whitaker 2005; Hix and Noury and Roland 2005). What however can be seen as a lacuna in EP committee research is the examination of the question of how Members of the European Parliament (MEPs) are socialized into EP committees and whether this process has an impact on the decision-making process within the EP, for example has an effect on consensus formation in any way.
Changes of the Bacterial Abundance and Communities in Shallow Ice Cores from Dunde and Muztagata Glaciers, Western China

In this study, six bacterial community structures were analyzed from the Dunde ice core (9.5-m-long) using 16S rRNA gene cloning library technology. Compared to the Muztagata mountain ice core (37-m-long), the Dunde ice core has different dominant community structures, with five genus-related groups Blastococcus sp. /Propionibacterium, Cryobacterium-related. , Flavobacterium sp. , Pedobacter sp. , and Polaromas sp. that are frequently found in the six tested ice layers from 1990 to 2000. Live and total microbial density patterns were examined and related to the dynamics of physical-chemical parameters, mineral particle concentrations, and stable isotopic ratios in the precipitations collected from both Muztagata and Dunde ice cores. The Muztagata ice core revealed seasonal response patterns for both live and total cell density, with high cell density occurring in the warming spring and summer months indicated by the proxy value of the stable isotopic ratios. Seasonal analysis of live cell density for the Dunde ice core was not successful due to the limitations of sampling resolution. Both ice cores showed that the cell density peaks were frequently associated with high concentrations of particles. A comparison of microbial communities in the Dunde and Muztagata glaciers showed that similar taxonomic members exist in the related ice cores, but the composition of the prevalent genus-related groups is largely different between the two geographically different glaciers. This indicates that the micro-biogeography associated with geographic differences was mainly influenced by a few dominant taxonomic groups.
Numerical simulation of deformation/motion of a drop suspended in viscous liquids under influence of steady electric fields

The deformation/motion of a droplet suspended in a viscous liquid under the influence of an applied external electric field is investigated through numerical simulations in an axisymmetric system. The two-phase flow field of the drop suspension system is simulated using a front tracking/finite volume method by solving the full Navier–Stokes equations. Three different electric field models are applied in order to take into account the effects of the electric field, electric charge, and electrical properties of liquids. Drops without net charges but finite electrical conductivity are simulated using a leaky dielectric model. Perfect dielectric model is used for the drops of electrically isolating fluid. To take into account the presence of net charges on drop surface, we proposed a simplified constant surface charge model. In addition, the simulation code using the leaky dielectric model and perfect dielectric model is validated systematically against the results of theoretical analysis, the available exper.
The second trimester Doppler ultrasound examination is the best predictor of late pregnancy outcome in systemic lupus erythematosus and/or the antiphospholipid syndrome.

OBJECTIVE To examine the predictive value of clinical examination, laboratory tests and Doppler ultrasound examination in systemic lupus erythematosus (SLE) and/or antiphospholipid syndrome (APS) pregnancies. METHODS A prospective study of 116 pregnancies followed in a single tertiary referral centre. Outcomes analysed were fetal/neonatal death and adverse pregnancy outcome. Univariate analysis was performed for: (i) medical and obstetric history; (ii) medical and obstetric clinical examination; (iii) biological data; (iv) Doppler ultrasound examination. Variables significantly associated with the outcomes in the univariate analysis were entered into a logistic regression model. RESULTS Sixteen out of 116 pregnancies ended in 12 fetal deaths and 4 embryonic losses. Hence, data for 100 pregnancies were analysed. Seven fetal deaths and one neonatal death occurred, associated with abnormal end-diastolic umbilical artery Doppler flow at the second trimester (P < 0.006), a history of thrombophlebitis (P < 0.001) or notched uterine artery and growth restriction at the second trimester (P < 0.002). Multivariate analysis retained abnormal end-diastolic umbilical artery Doppler flow (P = 0.047) and history of thrombophlebitis (P = 0.018) as significant predictors. Thirty-one adverse pregnancy outcomes occurred, associated with notched uterine artery (P < 0.00003), abnormal end-diastolic umbilical artery Doppler flow (P < 0.0006) and fetal growth restriction at the second trimester (P < 0.008), growth restriction (P < 0.00001) and notched uterine artery at the third trimester (P < 0.0008), use of heparin (P < 0.05) and history of thrombophlebitis (P < 0.04). Notched uterine artery at the second trimester remained the only predictor in multivariate analysis (P = 0.001). CONCLUSIONS Results of the second trimester Doppler ultrasound examination are the best predictors for late pregnancy outcome in SLE and/or APS.
Semi-supervised Multi-label Learning by Solving a Sylvester Equation

Multi-label learning refers to the problems where an instance can be assigned to more than one category. In this paper, we present a novel Semi-supervised algorithm for Multi-label learning by solving a Sylvester Equation (SMSE). Two graphs are first constructed on instance level and category level respectively. For instance level, a graph is defined based on both labeled and unlabeled instances, where each node represents one instance and each edge weight reflects the similarity between corresponding pairwise instances. Similarly, for category level, a graph is also built based on all the categories, where each node represents one category and each edge weight reflects the similarity between corresponding pairwise categories. A regularization framework combining two regularization terms for the two graphs is suggested. The regularization term for instance graph measures the smoothness of the labels of instances, and the regularization term for category graph measures the smoothness of the labels of categories. We show that the labels of unlabeled data finally can be obtained by solving a Sylvester Equation. Experiments on RCV1 data set show that SMSE can make full use of the unlabeled data information as well as the correlations among categories and achieve good performance. In addition, we give a SMSE’s extended application on collaborative filtering.
Importance of coherence for electron transport in terahertz quantum cascade lasers

A density matrix approach is used in combination with a tight-binding model to describe electron transport in terahertz quantum cascade lasers and is incorporated into a Monte Carlo simulation. Scattering events, including LO-phonon, electron-electron, and ionized impurity scattering, are treated semiclassically but contribute to dephasing scattering. In addition, a phenomenological “pure dephasing rate” was introduced to take into account dephasing caused by interface roughness scattering. This model was used to investigate the influence of dephasing on electron transport through a barrier. Additionally, current densities, populations and electron temperatures were calculated for a simple three-level structure and a five-level structure that achieved lasing at 3.2THz, and the results were compared to a semiclassical simulation. We find that the inclusion of coherent transport and dephasing in the calculations is essential when transport is dominated by transitions between weakly coupled states.