Miracle-dz/UniFAR-FTUs huggingface dataset:
Beyond Culture Learning Theory

The meta-analytic study examined correlates of cultural competence as assessed by the Sociocultural Adaptation Scale. A total of 17 variables were analyzed from 66 independent studies (N = 10,672). In line with culture learning theory, situational factors such as length of residence (r = .16), cultural knowledge (r = .34), previous cross-cultural experience (r = .17), cultural distance (r = −.33), language proficiency (r = .35), and contact with host nationals (r = .29) were associated with better sociocultural adaptation. The meta-analysis was extended to personality variables, with small to medium effect sizes found for the “Big Five” traits of agreeableness (r = .16), conscientiousness (r = .22), openness/flexibility (r = .29), extraversion (r = .29), and neuroticism (r = −.32), and large effect sizes found for more narrowly defined, culture-relevant factors such as cultural empathy (r = .49) and cross-cultural self-efficacy (r = .45). The findings indicate that both personal and situational factors relate to cultural competence and that personality variables deserve greater attention in future studies of sociocultural adaptation.
High-content Functional Screen to Identify Proteins that Correct F508del-CFTR Function*S

Cystic Fibrosis is caused by mutations in CFTR, with a deletion of a phenylalanine at position 508 (F508del-CFTR) representing the most common mutation. The F508del-CFTR protein exhibits a trafficking defect and is retained in the endoplasmic reticulum. Here we describe the development of a high-content screen based on a functional assay to identify proteins that correct the F508del-CFTR defect. Using a HEK293 MSR GripTite cell line that stably expresses F508del-CFTR, we individually co-expressed ∼450 unique proteins fused to the Cl−-sensitive YFP(H148Q/I152L) mutant. We then tested correction of F508del-CFTR function by the CI−/l− exchange method following stimulation with forskolin/IBMX/genistein, using quantitative recordings in multiple individual cells with a high-content (high-throughput) Cellomics KSR imaging system. Using this approach, we identified several known and novel proteins that corrected F508del-CFTR function, including STAT1, Endothelin 1, HspA4, SAPK substrate protein 1, AP2M1, LGALS3/galectin-3, Trk-fused gene, Caveolin 2, PAP/REG3α, and others. The ability of these correctors to rescue F508del-CFTR trafficking was then validated by demonstrating their enhancement of maturation (appearance of band C) and by cell surface expression of F508del-CFTR bearing HA tag at the ectodomain using confocal microscopy and flow cytometry. These data demonstrate the utility of high-content analyses for identifying proteins that correct mutant CFTR and discover new proteins that stimulate this correction. This assay can also be utilized for RNAi screens to identify inhibitory proteins that block correction of F508del-CFTR, small molecule, and peptide screens.
Simulating Entrepreneurial Learning

Theorizing about entrepreneurial learning is examined in this article to determine key learning processes within this body of research. It explores how these processes might be simulated in a student-learning environment and highlights the role of emotional exposure, situated learning, action-orientation and discontinuity. An argument is made for experiential, work-based learning when seeking to simulate contexts similar to those in which entrepreneurs learn. A conceptual framework is introduced that highlights a course design based on the factors identified. In the analysis, formal course assessments are reviewed and narrative coding based on student reflections is evaluated. The article illustrates that it is possible to simulate aspects of entrepreneurial learning, such as emotional exposure and situated learning, but not others. It also demonstrates a range of learning benefits linked to experiential learning. In conclusion, the article explains why entrepreneurship education can play an important role in encouraging management learning.
Public Organizations and Mission Valence

Given the service- and community-oriented nature of organizational goals in the public sector, it is not surprising that public management scholars have highlighted the potential of the missions to be an asset of public organizations. To date, however, little empirical research has investigated ways in which these benefits can be cultivated. The present study of mission valence—based on a sample from a single organization—has formative and developmental value. The authors find that organizational goal clarity, public service motivation, and work impact can increase an organization’s mission valence. In addition, the findings validate the importance of mission valence by illustrating its effect on two important human resource outcomes, job satisfaction and absenteeism.
A New Line Integral Convolution Algorithm for Visualizing Time-Varying Flow Fields

New challenges on vector field visualization emerge as time dependent numerical simulations become ubiquitous in the field of computational fluid dynamics (CFD). To visualize data generated from these simulations, traditional techniques, such as displaying particle traces, can only reveal flow phenomena in preselected local regions and thus, are unable to track the evolution of global flow features over time. The paper presents an algorithm, called UFLIC (Unsteady Flow LIC), to visualize vector data in unsteady flow fields. Our algorithm extends a texture synthesis technique, called Line Integral Convolution (LIC), by devising a new convolution algorithm that uses a time-accurate value scattering scheme to model the texture advection. In addition, our algorithm maintains the coherence of the flow animation by successively updating the convolution results over time. Furthermore, we propose a parallel UFLIC algorithm that can achieve high load balancing for multiprocessor computers with shared memory architecture. We demonstrate the effectiveness of our new algorithm by presenting image snapshots from several CFD case studies.
Toward Practical Procedures for Predicting and Promoting Success in Virtual School Students

Abstract Two lines of research have emerged to study the causes and prevention of student failure in virtual (K–12) schools: studies of learner characteristics and studies of learning environment characteristics. To develop a useful model for predicting failure and promoting success in virtual school environments, a study was designed to measure the relation between a combination of student and environmental factors derived from previous research and successful course completion during one semester at a large (N = 4,100) virtual school. Study findings yielded a model that can discriminate between successful and unsuccessful online school students and is especially effective at identifying those likely to succeed.
Who is Framing the National Understanding of Educational Leadership Preparation and Practice?

In this article we examine the current national conversation on educational leadership preparation and practice and the implications of these conversations for educational leadership preparation. We focus specifically on the rhetoric and research concerning two issues identified as major contributors to our current leadership crisis : the shortage of qualified administrators and leadership preparation. Based upon our assessment of this literature, we then make the case for increased involvement in the national conversation by educational “insiders. ” We suggest in this manuscript that if we are to realize the goal of ensuring educational excellence and equity for all children, we must get involved. First, we must focus on preparing high-quality leaders through rigorous, standards-based, theoretically sound preparation programs. To do otherwise is to risk further increasing the number of mediocre candidates with administrative certificates, lacking the knowledge, skills, interest, motivation, and commitment to lead our nation's schools. Second, we must find ways to substantively engage in the national conversation on educational leadership preparation. Within that conversation, we must argue for quality in leadership preparation, we must share what is known about best practice in leadership preparation, we must urge collaboration among stakeholders, and we must insist that all decisions that are made concerning leadership preparation have at their core the interest of our nation's children.
Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding

Genomic-enabled prediction is becoming increasingly important in animal and plant breeding and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of markers concurrently. Methods exist that allow implementing these large-p with small-n regressions, and genome-enabled selection (GS) is being implemented in several plant and animal breeding programs. The list of available methods is long, and the relationships between them have not been fully addressed. In this article we provide an overview of available methods for implementing parametric WGR models, discuss selected topics that emerge in applications, and present a general discussion of lessons learned from simulation and empirical data analysis in the last decade.
Validation of the French Version of the Hierarchical Personality Inventory for Children (HiPIC) Influence of Gender and Age on Personality Traits in 8- to 12-Year-Olds

Abstract. The study was designed to investigate the psychometric properties of the French version and the cross-language replicability of the Hierarchical Personality Inventory for Children (HiPIC). The HiPIC is an instrument to assess the five dimensions of the five-factor model for children. Subjects were 552 children aged between 8 and 12 years, rated by one or both parents. At the domain level, reliability ranged from . 83 to . 93 and at the facet level, reliability ranged from . 69 to . 89. Differences between genders were congruent with those found in the Dutch sample. Girls scored higher on Benevolence and Conscientiousness. Age was negatively correlated with Extraversion and Imagination. For girls, we also observed a decrease of Emotional Stability. A series of exploratory factor analyses confirmed the overall five-factor structure for girls and boys. Targeted factor analyses and congruence coefficients revealed high cross-language replicability at the domain and at the facet levels. The results showe.
Structure of Ethnic Identity of Arab-Israeli Students

The main problems posed in this study were: What is the structure of the Arab-Israeli identity? What is the relation of ethnic identity to another self-referent scale? The Ethnic Identity and Self-esteem scales were administered in the summer of 1973–74 to 532 Arab-Israeli university students. Factor analysis of the items demonstrated that most of the common factor variance was appropriated by three factors, all of which were clearly recognized as already known constructs. Despite the peculiar situation of the Arab minority in Israel, two relatively orthogonal factors, an Arab identity and an Israeli identity, emerged while the other factor represented a self-esteem construct. These findings supported the conclusions of previous research on Jewish-American identity and raised questions about the notion that ethnic-majority identity forms a bipolar continuum. The ethnic identity is then discussed in relation to the broader concept of self-identity.
AAV Vector-Mediated Gene Delivery to Substantia Nigra Dopamine Neurons: Implications for Gene Therapy and Disease Models

Gene delivery using adeno-associated virus (AAV) vectors is a widely used method to transduce neurons in the brain, especially due to its safety, efficacy, and long-lasting expression. In addition, by varying AAV serotype, promotor, and titer, it is possible to affect the cell specificity of expression or the expression levels of the protein of interest. Dopamine neurons in the substantia nigra projecting to the striatum, comprising the nigrostriatal pathway, are involved in movement control and degenerate in Parkinson’s disease. AAV-based gene targeting to the projection area of these neurons in the striatum has been studied extensively to induce the production of neurotrophic factors for disease-modifying therapies for Parkinson’s disease. Much less emphasis has been put on AAV-based gene therapy targeting dopamine neurons in substantia nigra. We will review the literature related to targeting striatum and/or substantia nigra dopamine neurons using AAVs in order to express neuroprotective and neurorestorative molecules, as well as produce animal disease models of Parkinson’s disease. We discuss difficulties in targeting substantia nigra dopamine neurons and their vulnerability to stress in general. Therefore, choosing a proper control for experimental work is not trivial. Since the axons along the nigrostriatal tract are the first to degenerate in Parkinson’s disease, the location to deliver the therapy must be carefully considered. We also review studies using AAV-α-synuclein (α-syn) to target substantia nigra dopamine neurons to produce an α-syn overexpression disease model in rats. Though these studies are able to produce mild dopamine system degeneration in the striatum and substantia nigra and some behavioural effects, there are studies pointing to the toxicity of AAV-carrying green fluorescent protein (GFP), which is often used as a control. Therefore, we discuss the potential difficulties in overexpressing proteins in general in the substantia nigra.
Improving Learning Experiences Through Gamification: A Case Study

Gamified learning systems are becoming increasingly common within educational institutions, however there is a lack of understanding on the elements of gamification that influence, either positively or negatively, the learning experiences of students using these systems. This study examines an existing gamified learning tool implemented within an Australian university, and explores the aspects of this system that impact upon the student experience. It was found that positive influences included a combination of motivational and game-based elements such as presentation of content, self-efficacy of learning experiences, and feedback that positively influence students. Additionally, aspects of the system that negatively influenced learning experiences included issues such as interaction flaws and compatibility issues.
Knowledge Modeling for Adaptive Content Selection in Educational Hypermedia Systems

Adaptive content selection and sequencing is recognized as among the most interesting research questions in adaptive educational hypermedia systems. In this paper, we address the adaptive content selection problem in educational hypermedia systems proposing a concrete methodology for capturing expert’s knowledge on selection of learning content following the philosophy and principles of techniques derived from computational intelligence. The result is a generic decision model that mimics the way an expert decides on the selection problem.
Motivos de sucesso, afiliação e poder: um estudo de validação do constructo no Brasil

The achievement, affiliation and power motives: a study of the construct validation in Brazil. This short research note aims at showing the findings of a study that replicates in Brazil the instrument proposed by Rego (1998a, 2000; Rego & Carvalho, 2001, 2002) for measuring the motives of achievement, affiliation and power in Portugal. Data from a sample comprising 162 university students (50% from each gender) were collected. The findings suggest that the good psychometric properties obtained in Portugal are not replicated in Brazil. In any case, the results showed here have some merit, suggesting that the measurement instrument needs to (and can) be ameliorated with some changes in order to adapt it to a cultural context different from the Portuguese.
Sufficient Encryption with Codewords and Bin-strings of H.264/SVC

Multi-layered scalable bit-stream distribution requires protection for the rendering and transmission of its individual layers. This paper presents a sufficient encryption (SE) scheme for SVC layers which maintains the compression efficiency and the format compliancy of scalable bit-streams, without compromising the security. The purpose of SE is achieved by applying the partial encryption on carefully selected codewords and bin-strings of the CAVLC and CABAC of H.264/SVC respectively. The performance of the scheme is tested on various resolution sequences, which demonstrate the advantages of the scheme when compared to alternative techniques. These advantages include: minimal computational delay by encrypting partial data; no bit-rate escalation by keeping the compression ratio unchanged; and, format compliancy of the bit-stream at the decoder. A comparative security analysis of the scheme confirms that it is suitable for commercial, real-time applications. The minimal increase in processing requirements ensures that the scheme is highly suitable for video distribution to users who have subscribed to differing video qualities on end systems ranging from small handheld devices to those with high computational capability.
Rig-space physics

We present a method that brings the benefits of physics-based simulations to traditional animation pipelines. We formulate the equations of motions in the subspace of deformations defined by an animator's rig. Our framework fits seamlessly into the workflow typically employed by artists, as our output consists of animation curves that are identical in nature to the result of manual keyframing. Artists can therefore explore the full spectrum between handcrafted animation and unrestricted physical simulation. To enhance the artist's control, we provide a method that transforms stiffness values defined on rig parameters to a non-homogeneous distribution of material parameters for the underlying FEM model. In addition, we use automatically extracted high-level rig parameters to intuitively edit the results of our simulations, and also to speed up computation. To demonstrate the effectiveness of our method, we create compelling results by adding rich physical motions to coarse input animations. In the absence of artist input, we create realistic passive motion directly in rig space.
The Effectiveness of Idaho DUI and Misdemeanor/DUI Courts: Outcome Evaluation

As DUI Courts continue to expand through the United States, research needs to match the growth to inform administrators and the public on the effectiveness of these courts. The current study found that participation in a DUI or Misdemeanor/DUI Drug Court (23%) reduced recidivism compared to a comparison group (37%) with court filing records that resulted in a disposition of guilty. The current study measured multiple court sites and analyzed recidivism over a 4.5 year time frame, and through the use of a Cox Proportional Hazard model it was identified that those not in the DUI court group were 1.6 times more likely to recidivate. The authors discuss the limitations and results in their efforts to increase the research on this ever expanding criminal justice practice.
A Stochastic Gradient Method with Linear Convergence Rate for a Class of Non-smooth Non-strongly Convex Optimizations

In this paper, we show that a (stochastic) gradient decent method with multiple restarting, named Restarted (S)GD, can achieve a linear convergence rate for a class of non-smooth and non-strongly convex optimization problems where the epigraph of the objective function is a polyhedron. Its applications in machine learning include minimizing `1 constrained or regularized piecewise linear loss. To the best of our knowledge, this is the first result on the linear convergence rate of a stochastic gradient method for non-smooth and non-strongly convex optimization.
Relative Deprivation and Social Identity in Times of Dramatic Social Change: The Case of Nurses1

In the present study, an integration of relative deprivation theory and social identity theory is proposed to account for people’s reactions to dramatic changes affecting their daily lives. Data collected among nurses (n = 108) indicate that feelings of relative deprivation are influenced by different perceptions of organizational change. Path analysis shows that feelings of social relative deprivation derive from negative changes that are numerous, and that temporal relative deprivation is experienced as a result of negative changes that are rapid. In terms of the link between social identity and relative deprivation, 2 contrasting approaches were tested. Analyses support the view that in-group identification acts as a precursor, rather than as a consequence, of relative deprivation. Social change is a constant. Some changes are more dramatic than others in that they profoundly reshape the entire structure of a society or an organization. The overthrow of a government, the introduction of radical new laws, and the globalization of the economy are examples of social change that may have a profound impact on organizations and their employees. Moreover, technological advances have revolutionized the working environment for virtually all organizations. Social change, then, is defined as a permanent and rapid transformation of a given social organization and its internal dynamics (Parsons, 1964; Rocher, 1992; Rogers, 2003). Transformations of this magnitude and pace not only modify the history of an organization, they also threaten its equilibrium. Social change has become a reality for most modern societies. Changes are not only numerous, they are also occurring at a rapid pace (e.g., Chirot & Merton, 1986; Nolan & Lenski, 1998; Ponsioen, 1969; Sztompka, 1998; Zuck, 1997). Indeed, the ongoing “technological revolution” has had a profound impact on organizations and workers
MetaGenSense : A web application for analysis and visualization

The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive exploratory tools, like Krona for representation of taxonomic classification, can be achieved very 1* 2* 3 1