Miracle-dz/UniFAR-FTUs huggingface dataset:
Australian Immigration Policy in Practice: a case study of skill recognition and qualification transferability amongst Irish 457 visa holders

ABSTRACT Immigration quotas in Australia are guided primarily by economic policy—the needs of the nation are quite rightly the principal concern of policymakers. Using data from a mixed-methods study, this article engages in a dialogue between labour geography and population and migration studies through an examination of the lived experiences of migrating workers and their families. The paper examines a number of cases where policy and practice have detrimentally affected the migration experience of Irish migrants who came to Australia under the Temporary Work (Skilled) (subclass 457) visa. The case study focuses on interviews with secondary 457 visa applicants, namely the wives of former 457 workers. These interviews highlight the problems faced by newcomers to Australia who arrive under this visa. The experiences relayed by these women demonstrate how ill-considered policy relating to qualification transferability makes entering the workplace and, therefore, transition to life in Australia more difficult than it needs to be. While the cases that underpin this paper ended in migration failure (the families involved returned to Ireland), the core issues of qualification transferability and skill comparison were replicated in the wider study dataset (of 1022 survey responses and 80 qualitative interviews). While acknowledging that citizens generally have more freedom and more civil rights than non-citizens, the findings of this study indicate that further review of Australia’s 457 visa is needed, particularly with respect to the limitations placed on the agency of migrant workers. Greater awareness amongst prospective migrants as to the purpose and limits of the 457 visa is also necessary, in order to avoid misinterpretation and the extreme personal repercussions outlined in this paper.
A View-Dependent Stereoscopic System Using Tiled Projection

In this paper, we present a novel system which allows its users to see a stereoscopic virtual object. Unlike most existing stereoscopic systems that display the same imagery when watched from different directions, the user's head is tracked in real-time so that the real-time images can be rendered according to the viewing position, which enables the dynamic images to be displayed on the screen and the users can see different parts of a virtual object when wearing a pair of polarized glasses. This creates a more vivid illusion that a real object is set at the physical scene. The key technologies of the proposed system such as depth-image-based head tracking, geometric calibration and view-dependent real-time stereoscopic image rendering are studied and the experimental results proves the performance of the proposed system.
Improvements in the Quantitative Assessment of Cerebral Blood Volume and Flow with the Removal of Vessel Voxels from MR Perfusion Images

Objective. To improve the quantitative assessment of cerebral blood volume (CBV) and flow (CBF) in the brain voxels from MR perfusion images. Materials and Methods. Normal brain parenchyma was automatically segmented with the time-to-peak criteria after cerebrospinal fluid removal and preliminary vessel voxel removal. Two scaling factors were calculated by comparing the relative CBV and CBF of the segmented normal brain parenchyma with the absolute values in the literature. Using the scaling factors, the relative values were converted to the absolute CBV and CBF. Voxels with either CBV > 8 mL/100 g or CBF > 100 mL/100 g/min were characterized as vessel voxels and were excluded from the quantitative measurements. Results. The segmented brain parenchyma with normal perfusion was consistent with the angiographic findings for each patient. We confirmed the necessity of dual thresholds including CBF and CBV for proper removal of vessel voxels. The scaling factors were 0.208 ± 0.041 for CBV, and 0.168 ± 0.037, 0.172 ± 0.037 for CBF calculated using standard and circulant singular value decomposition techniques, respectively. Conclusion. The automatic scaling and vessel removal techniques provide an alternative method for obtaining improved quantitative assessment of CBV and CBF in patients with thromboembolic cerebral arterial disease.
An efficient approach based on ontology to optimize the organizational knowledge base management for advanced queries service

Today, enterprises consider their produced and existing knowledge a principal capital and seek to collect and maintain this knowledge. Unfortunately, the bulk of the enterprises' implicit knowledge has been gradually faded or neglected, due to lack of necessary attention and suitable saving. In this paper we attempt to present an efficient methodology based on ontology which displays the role of this system in the improvement of the existing know-how in the enterprise. By applying ontology in an enterprise, we seek to determine the relationships between the responsibilities and the activities of that organization with the organizational knowledge and the tools proportionate with it. This paper presents a method for designing and creating enterprise ontology as well as organizational knowledge base for explaining the concepts and relationships between the existing organizational information. The present design is a factor upon which the devices gain the capability of understanding the information structure of the enterprise. As a result, queries based on concepts have become possible.
Inferring Individual Influence in Social Network

We study the integration of individuals attributes to infer their influence ability in social network in this paper. The influence between individuals is usually asymmetric and can propagate via edges gradually. We suggest an Influence Factor Graph(IFG) which can integrate different node and edge features into a uniform inferring model. And for each node the model can compute personalized influence ability value. Experiment results in Zarchary and Wikipedia co-editing social networks show that, the model can depict influence reasonably and reveal some interesting social influence rules.
Eigenvector Selection for Eigenvector Spatial Filtering

Eigenvector spatial filtering (ESF) furnishes a methodology that accounts for spatial dependency in georeferenced data (Griffith 2003), which, to date, has been the domain of spatial autoregressive (SAR) models. Its fundamental idea exploits the decomposition of a spatial variable into the following three components: trend, spatially structured random component (i.e., spatial stochastic signal), and random noise. Its aim is to separate spatially structured random components from both trend and random noise, and, consequently, furnishes a sounder statistical inferential basis and useful visualization. In other words, ESF uses a set of synthetic proxy variables, which are extracted as eigenvectors from a spatial connectivity matrix that ties geographic objects together in space, and then adds these vectors as control variables to a model specification. These control variables identify and isolate the stochastic spatial dependencies among the georeferenced observations, thus allowing model building to proceed as if the observations are independent. Because ESF model specification is flexible, it can be utilized to describe variables following various types of distributions, including the Gaussian, Poisson, and binomial. Different ESF specifications have been compared with other specifications, such as the SAR (Getis and Griffith 2002, Tiefelsdorf and Griffith 2007, Thayn and Siminas 2012), auto-Poisson (Griffith 2002), and auto-logistic (Griffith 2004) ones. Although ESF has become more popular in addressing spatial autocorrelation (SA) latent in georeferenced data (e.g., Hughes and Haran 2012), it faces two major computational challenges. Both the extraction of eigenvectors from an n-by-n modified geographic weights matrix, and the selection of a subset from the resulting set of n eigenvectors to construct a spatial filter, become increasingly challenging as n increases. In this paper, the selection of eigenvectors to construct ESF-based estimators in linear regression is investigated in terms of this latter computational issue.
Neural control for a field of concentrator heliostats

Today the world is facing a huge problem because of energy scarcity. Many alternative options are being developed. Solar energy has been proved to be a very promising alternative, but manychallenges are to be solved to do the advancements in this sector. Towardsthis, we develop an approach by doing the neural control for a field ofconcentrator heliostats. We have done use ofadvanced techniques like Extended Kalman Filter (EKF), Particles Swarm Optimization (PSO), Recursive High Order Neural Networks (RHONN) andSliding Modes Control to achieve the goal. PSO is used to initialize the parameters for the EKF. The performances of the above techniques are illustrated through simulation.
TV Commercial Detection Based on Shot Change and Text Extraction

A new algorithm is proposed for TV commercial detection from color video in this paper. High shot change frequency and "still" shots of the trademark information, which are two basic characteristics of TV commercial, are exploited to distinguish commercials from general programs. Our commercial retrieval system based on shot change and text detection is realized through a slide window. First, histogram difference is computed on consecutive images and then the four common shot transitions including cut, dissolve, fade in/out and wipe are detected. Our text detection algorithm based on maximum gradient difference, allows fast filtering of scan lines without text. A commercial is determined either if its shot change frequency is satisfied or if its trademark information is detected. Performance evaluation shows that our algorithm performs well with relatively high detection accuracy for different kinds of programs when we involved the text detection, which is an important contribution of this paper.
Epstein-Barr virus (EBV)-associated lymphoproliferative disease in the SCID mouse model: implications for the pathogenesis of EBV-positive lymphomas in man

When human peripheral blood lymphocytes (PBLs) from Epstein-Barr virus (EBV)-seropositive donors are injected intraperitoneally into SCID mice, EBV+ B cell tumors develop within weeks. A preliminary report (Mosier, D. E., R. J. Gulizia, S. M. Baird, D. D. Richman, D. B. Wilson, R. I. Fox, and T. J. Kipps, 1989. Blood. 74(Suppl. 1):52a) has suggested that such tumors resemble the EBV-positive malignancy, Burkitt's lymphoma. The present work shows that generally the human (hu) PBL-SCID tumors are distinct from Burkitt's lymphoma and instead resemble lymphoblastoid cell lines (LCLs) generated by EBV-infection of normal B cells in vitro in terms of: (a) their cell surface phenotype, with expression of B cell activation antigens and adhesion molecules, (b) normal karyotype, and (c) viral phenotype, with expression of all the transformation-associated EBV latent proteins and, in a minority of cells, productive cycle antigens. Indeed, in vitro-transformed LCLs also grow when inoculated into SCID mice, the frequency of tumor outgrowth correlating with the in vitro growth phenotype of the LCL which is itself determined by the identity of the transforming virus (i.e., type 1 or type 2 EBV). Histologically the PBL-derived hu-SCID tumors resemble the EBV+ large cell lymphomas that develop in immuno- suppressed patients and, like the human tumors, often present at multiple sites as individual monoclonal or oligoclonal foci. The remarkable efficiency of tumor development in the hu-SCID model suggests that lymphomagenesis involves direct outgrowth of EBV- transformed B cells without requirement for secondary genetic changes, and that selection on the basis of cell growth rate alone is sufficient to explain the monoclonal/oligoclonal nature of tumor foci. EBV+ large cell lymphoma of the immunosuppressed may arise in a similar way.
Telco User Activity Level Prediction with Massive Mobile Broadband Data

Telecommunication (telco) operators aim to provide users with optimized services and bandwidth in a timely manner. The goal is to increase user experience while retaining profit. To do this, knowing the changing behavior patterns of users through their activity levels in advance can be a great help for operators to adjust their management strategies and reduce operational risk. To achieve this goal, the operators can make use of knowledge discovered from telco’s historical mobile broadband (MBB) records to predict mobile access activity level at an early stage. In this article, we report our research in a real-world telco setting involving more than one million telco users. Our novel contribution includes representing users as documents containing a collection of changing spatiotemporal “words” that express user behavior. By extracting users’ space-time access records in MBB data, we use latent Dirichlet allocation (LDA) to learn user-specific compact topic features for user activity level prediction. We propose a scalable online expectation-maximization (OEM) algorithm that can scale LDA to massive MBB data, which is significantly faster than several state-of-the-art online LDA algorithms. Using these real-world MBB data, we confirm high performance in user activity level prediction. In addition, we show that the inferred topics indicate that future activity level anomalies correlate highly with early skewed bandwidth supply and demand relations. Thus, our prediction system can also guide the telco operators to balance the telecommunication network in terms of supply-demand relations, saving deployment costs and energy of cell towers in the future.
Self-Compassion: A Potential Buffer in an Evaluative Dance Environment

Common characteristics of the dance environment, including mirrored settings, tight-fitted clothing, and evaluation by others create an atmosphere that can negatively influence a ballet dancer’s body image and act as a barrier to participation (Radell, Adame, Cole, & Blumenkehl, 2011; Tiggemann & Slater, 2001). Thus, it is important to identify resources that can buffer against negative self-perceptions in an evaluative dance environment. The purpose of this study was to explore self-compassion in relation to self-evaluative thoughts and behaviours in an evaluative ballet environment. Participants ( N = 57 women undergraduate students; M age = 20.59 years, SD = 3.81) completed an online questionnaire containing measures of self-compassion, social physique anxiety (trait and state versions), fear of negative evaluation (trait and state versions), as well as reactions, thoughts, and emotions to a hypothetical first day of beginner ballet class scenario consistent with the common characteristics of the dance environment. Self-compassion was negatively related to trait and state social physique anxiety, trait and state fear of negative evaluation, total negative affect, personalizing thoughts, and catastrophizing thoughts, as well as positively associated with behavioural equanimity and thoughts of equanimity. Finding self-compassion to be associated with lower neegative self-perceptions within the context of an evaluative beginner ballet class replicates past correlational research and advances the literature by contextualizing self-compassion to a specific evaluative environment.
Overcoming Weaknesses of Current Personalization Techniques by Semantic Web Technologies ⋆

Nowadays, users are exposed to an overwhelming amount of inf ormation in several application domains. Recommender systems fi ght such an overload by selecting the products which are more appealing to each us er, according to his personal preferences or needs. Current personalizatio n techniques are based on more or less sophisticated syntactic methods which miss a lot of knowledge during the elaboration of the recommendations. In this pape r, w propose an approach that effectively overcomes the drawbacks of the exis ting personalization techniques by resorting to reasoning mechanisms inspired i n Semantic Web technologies. Such a reasoning provides recommender system wit h extra knowledge about the user’s preferences, thus favoring more accurate p ersonalization processes.
Assessment of Inhibitors of Pathogenic Crimean-Congo Hemorrhagic Fever Virus Strains Using Virus-Like Particles

Crimean-Congo hemorrhagic fever (CCHF) is an often lethal, acute inflammatory illness that affects a large geographic area. The disease is caused by infection with CCHF virus (CCHFV), a nairovirus from the Bunyaviridae family. Basic research on CCHFV has been severely hampered by biosafety requirements and lack of available strains and molecular tools. We report the development of a CCHF transcription- and entry-competent virus-like particle (tecVLP) system that can be used to study cell entry and viral transcription/replication over a broad dynamic range (~4 orders of magnitude). The tecVLPs are morphologically similar to authentic CCHFV. Incubation of immortalized and primary human cells with tecVLPs results in a strong reporter signal that is sensitive to treatment with neutralizing monoclonal antibodies and by small molecule inhibitors of CCHFV. We used glycoproteins and minigenomes from divergent CCHFV strains to generate tecVLPs, and in doing so, we identified a monoclonal antibody that can prevent cell entry of tecVLPs containing glycoproteins from 3 pathogenic CCHFV strains. In addition, our data suggest that different glycoprotein moieties confer different cellular entry efficiencies, and that glycoproteins from the commonly used strain IbAr10200 have up to 100-fold lower ability to enter primary human cells compared to glycoproteins from pathogenic CCHFV strains.
Comparative Morphology of Dendritic Arbors in Populations of Purkinje Cells in Mouse Sulcus and Apex

Foliation divides the mammalian cerebellum into structurally distinct subdivisions, including the concave sulcus and the convex apex. Purkinje cell (PC) dendritic morphology varies between subdivisions and changes significantly ontogenetically. Since dendritic morphology both enables and limits sensory-motor circuit function, it is important to understand how neuronal architectures differ between brain regions. This study employed quantitative confocal microcopy to reconstruct dendritic arbors of cerebellar PCs expressing green fluorescent protein and compared arbor morphology between PCs of sulcus and apex in young and old mice. Arbors were digitized from high z-resolution (0.25 µm) image stacks using an adaptation of Neurolucida's (MBF Bioscience) continuous contour tracing tool, designed for drawing neuronal somata. Reconstructed morphologies reveal that dendritic arbors of sulcus and apex exhibit profound differences. In sulcus, 72% of the young PC population possesses two primary dendrites, whereas in apex, only 28% do. Spatial constraints in the young sulcus cause significantly more dendritic arbor overlap than in young apex, a distinction that disappears in adulthood. However, adult sulcus PC arbors develop a greater number of branch crossings. These results suggest developmental neuronal plasticity that enables cerebellar PCs to attain correct functional adult architecture under different spatial constraints.
The study of gamification application architecture for programming language course

Students sometimes find it hard to learn new programming languages. They often confront unfamiliar programming terms and are required to visualize the processes that happen in the computer memory. Weak students find this a burden and end up memorizing the processes without understanding them and their working. This situation invariably leads students to get low grades in their programming subjects. Some researchers suggested that an enjoyable approach must be adopted in learning difficult subjects. Studies have shown that applying gamification elements in websites engages users. "Gamification" refers to the use of game elements in a non-game context to increase engagement between humans and computers. This research try to solve the problem by apply gamification elements in programming language course as a new architecture of Gamification application to increase the effectiveness of learning and enhance the understanding of students'.
Religious voters and the religious-secular cleavage since 1990

ABSTRACT Most studies of electoral behaviour in New Zealand do not pay much attention to the religious-secular cleavage. While a few studies noted a religious-secular cleavage prior to the adoption of proportional representation, most have assumed that such a divide since 1996 has been confined to the margins of electoral politics, with religious voters supporting smaller third parties over National. This article re-evaluates this conclusion using data from the New Zealand Election Study since 1990. The analyses show that, rather than supporting small third parties more clearly representing issues of concern to them, religious voters have voted largely for National in most elections as part of a religious-secular cleavage between National and Labour. Fluctuation in support for National among religious voters is tied to National’s electoral fortunes: religious voters have been more likely to support National when the party has been likely to form the next government, but more likely to cast votes for third parties when National’s prospects have been poor.
Genomic Signatures of Speciation in Sympatric and Allopatric Hawaiian Picture-Winged Drosophila

The Hawaiian archipelago provides a natural arena for understanding adaptive radiation and speciation. The Hawaiian Drosophila are one of the most diverse endemic groups in Hawaiì with up to 1,000 species. We sequenced and analyzed entire genomes of recently diverged species of Hawaiian picture-winged Drosophila, Drosophila silvestris and Drosophila heteroneura from Hawaiì Island, in comparison with Drosophila planitibia, their sister species from Maui, a neighboring island where a common ancestor of all three had likely occurred. Genome-wide single nucleotide polymorphism patterns suggest the more recent origin of D. silvestris and D. heteroneura, as well as a pervasive influence of positive selection on divergence of the three species, with the signatures of positive selection more prominent in sympatry than allopatry. Positively selected genes were significantly enriched for functional terms related to sensory detection and mating, suggesting that sexual selection played an important role in speciation of these species. In particular, sequence variation in Olfactory receptor and Gustatory receptor genes seems to play a major role in adaptive radiation in Hawaiian pictured-winged Drosophila.
Interpretation of Care Guidelines for Obese Women in Labor: Intergroup Language and Social Identity

The hospital-based care of pregnant women who are obese is complex. Current guidelines recommend early epidural analgesia, but there is disagreement about the guidelines and their implementation by anesthesiologists. In this study, we conducted semistructured interviews with 42 specialist anesthesiologists about their experiences implementing the “early epidural” recommendation. We examined the impact of intergroup identity and system factors on the language used by anesthesiologists to express their experiences, framing the work by social identity and communication accommodation theory. Leximancer text mining was used to elicit the dominant theme “epidural” in the interviews, and discourse analysis aided in exploring selected extracts. Findings indicated that anesthesiologists expressed their role primarily as technical experts, along with the core value of accommodating patients’ wishes. Furthermore, the extent to which they were prepared to accommodate the perspective of other health professionals was a key indicator of the intergroup climate.