Miracle-dz/UniFAR-FTUs huggingface dataset:
MOTIVATIONAL BELIEFS , SELF-REGULATED LEARNING AND MATHEMATICAL PROBLEM SOLVING

Learning is influenced by multiple components of interrelated belief and self-directed strategies. In this study we focus on motivational beliefs (MB) and self-regulated learning (SRL) in the context of mathematical problem solving (MPS). The aim was to search for relationship between 5 and 6 Graders’ MB (self-efficacy, task value beliefs and goal orientation) and SRL (use of cognitive, metacognitive and volitional strategies) and between MB and performance in MPS. Analysis of the data from 219 students, using a self-report questionnaire and a paper and pencil test, showed a significant relation between all dimensions of MB and SRL and between self-efficacy, intrinsic goal orientation and performance in MPS. The results draw attention on SRL strategies to guide instruction and scaffolding that enhances MB during MPS.
Neurosteroidogenesis Is Required for the Physiological Response to Stress: Role of Neurosteroid-Sensitive GABAA Receptors

The hypothalamic-pituitary-adrenal (HPA) axis, which mediates the body's response to stress, is largely under GABAergic control. Here we demonstrate that corticotropin-releasing hormone (CRH) neurons are modulated by the stress-derived neurosteroid, tetrahydrodeoxycorticosterone (THDOC), acting on δ subunit-containing GABAA receptors (GABAARs). Under normal conditions, THDOC potentiates the inhibitory effects of GABA on CRH neurons, decreasing the activity of the HPA axis. Counterintuitively, following stress, THDOC activates the HPA axis due to dephosphorylation of KCC2 residue Ser940, resulting in a collapse of the chloride gradient and excitatory GABAergic transmission. The effects of THDOC on CRH neurons are mediated by actions on GABAAR δ subunit-containing receptors since these effects are abolished in Gabrd−/− mice under both control and stress conditions. Interestingly, blocking neurosteroidogenesis with finasteride is sufficient to block the stress-induced elevations in corticosterone and prevent stress-induced anxiety-like behaviors in mice. These data demonstrate that positive feedback of neurosteroids onto CRH neurons is required to mount the physiological response to stress. Further, GABAAR δ subunit-containing receptors and phosphorylation of KCC2 residue Ser940 may be novel targets for control of the stress response, which has therapeutic potential for numerous disorders associated with hyperexcitability of the HPA axis, including Cushing's syndrome, epilepsy, and major depression.
In their own words? A terminological analysis of e-mail to a cancer information service

OBJECTIVE To better understand the terms used by consumers to describe their health information needs and determine if this "consumer terminology"differs from those used by health care professionals. METHODS Features and findings identified in 139 e-mail messages to the University of Pittsburgh Cancer Institute's Cancer Information and Referral Service were coded and matched against the 2001 Unified Medical Language System Metathesaurus. RESULTS 504 unique terms were identified. 185 (36%) were exact matches to concepts in the 2001 UMLS Metathesaurus (MTH). 179 (35%) were partial string matches; 119 (24%) were known synonyms for MTH concepts; and 2 (<1%) were lexical variants. Only 19,or 4% of the total terms, were not found to be present in the 2001 MT1H. CONCLUSION 96% of the clinical findings and features mentioned in e-mail by correspondents who did not self-identify as healthcare professionals were described using terms from controlled healthcare terminologies. The notion of a paradigmatic "consumer" who uses a particular vocabulary specific to her "consumer" status may be ill-founded.
Harmonic diffeomorphisms, minimizing harmonic maps and rotational symmetry

We study harmonic diffeomorphisms between BnB{a1, . , ak} and a Riemannian manifold u. For n = 2 and k = 0, we prove that such diffeomorphisms are minimizing harmonic maps, we generalize this result by replacing B2 by any Riemannian surface. For n 3 we give a sufficient condition for such diffeomorphisms to be a minimizing harmonic map. We apply it in the case where W is a hypersurface of revolution in Rn+'. This allows us
Ethnic Diversity and Public Policy: A Comparative Inquiry

Preface - Notes on the Contributors - Ethnic Diversity and Public Policy: An Overview C.Young - Decentralization and the Accommodation of Ethnic Diversity Y.Ghai - Electoral Systems K.M. de Silva - The Accommodation of Ethnic Diversity: The Role of Education J.Gundara & C.Jones - Indigenous Peoples: Emerging International Actors R.Stavenhagen - Public Policies towards Immigrant Minorities in Western Europe S.Collinson - Preferential Policies for Disadvantaged Ethnic Groups: Employment and Education L.D. Jenkins - Index
Glory and Agony: Isaac's Sacrifice and National Narrative

Glory and Agony is the first history of the shifting attitudes toward national sacrifice in Hebrew culture over the last century. Its point of departure is Zionism's obsessive preoccupation with its haunting "primal scene" of sacrifice, the near-sacrifice of Isaac, as evidenced in wide-ranging sources from the domains of literature, art, psychology, philosophy, and politics. By placing these sources in conversation with twentieth-century thinking on human sacrifice, violence, and martyrdom, this study draws a complex picture that provides multiple, sometimes contradictory insights into the genesis and gender of national sacrifice. Extending back over two millennia, this study unearths retellings of biblical and classical narratives of sacrifice, both enacted and aborted, voluntary and violent, male and female-Isaac, Ishmael, Jephthah's daughter, Iphigenia, Jesus. Glory and Agony traces the birth of national sacrifice out of the ruins of religious martyrdom, exposing the sacred underside of Western secularism in Israel as elsewhere.
A Novel Semi-Fragile Watermarking Scheme with Iterative Restoration

In this paper, a novel semi-fragile watermarking scheme utilizing Iterative Restoration techniques is proposed. The scheme embeds a restricted set of restoration data in the transform domain of a cover image, which equates to a highly compressed copy of that image. If tampering occurs, the image is authenticated by comparing the extracted watermark data to encrypted data from a key file to detect changes. The restricted restoration data extracted from the image is then passed through traditional image restoration techniques such as Lucy-Richardson Iterative restoration and Blind Deconvolution, in an attempt to improve the restoration data before inserting back into tampered regions, to give an initial reconstruction of the manipulated locations. The technique can maintain a high watermarked image and restored region image quality of above 34 dB PSNR, as well as survive up to 30% JPEG Compression and other nongeometric attacks such as Gaussian noise, copy and paste, and region removal. The Average Detection Rate (ADR) is high, and Lucy-Richardson Iteration demonstrates up to a 25% improvement of subjective restoration quality compared to previous techniques such as LSB restoration schemes which use direct restoration techniques.
Quantum information processing using quantum dot spins and cavity QED

The electronic spin degrees of freedom in semiconductors typically have decoherence times that are several orders of magnitude longer than other relevant time scales. A solid-state quantum computer based on localized electron spins as qubits is therefore of potential interest. Here, a scheme that realizes controlled interactions between two distant quantum dot spins is proposed. The effective long-range interaction is mediated by the vacuum field of a high finesse microcavity. By using conduction-band-hole Raman transitions induced by classical laser fields and the cavity-mode, parallel controlled-not operations, and arbitrary single qubit rotations can be realized.
PERSONALITY BASED PSYCHOLOGICAL ANTECEDENTS OF CONSUMERS' TRUST IN E-COMMERCE

trust is one of the main determinants of the success of e%retailers and much research has dealt with website features triggering consumer trust to them. Another stream of research focuses on the psychological antecedents to online trust; i.e., what ''happens'' in the consumer's mind before or while a person decides to trust an e%retailer? So far, each effort has focused on only a few selected aspects of this trust formation process. Only few studies have attempted to identify major personality based psychological antecedents of trust. Our work identified the relative importance of the personality based psychological antecedents of trust in technology adoption and e%re tailing. We develop a model that incorporates the Big Five personality traits (Extraversion, Neuroticism, Agreeableness, Conscientiousness and Openness to experience), the most widely accepted framework for personality research in psychology, as well as determinants of trust in our model. We empirically test our model using a survey%based approach sampling 140 university students . Possible limitations of research are also discussed.
Parallel scan-path visualization

Eye tracking analysis is the state of the art technique to study questions of usability and cognition of graphical user interfaces. This paper presents a new technique for the visualization of eye tracking data, the Parallel Scan-Path Visualization. A key feature is the visualization of eye movements of many subjects on a single screen in a parallel layout. The visualization presents various properties of scan-paths, such as fixations, gaze durations and eye shift frequencies at one glance. The paper concludes with an example of use of the Parallel Scan-Path Visualization technique.
Assembly of the draft genome of buckwheat and its applications in identifying agronomically useful genes

Buckwheat (Fagopyrum esculentum Moench; 2n = 2x = 16) is a nutritionally dense annual crop widely grown in temperate zones. To accelerate molecular breeding programmes of this important crop, we generated a draft assembly of the buckwheat genome using short reads obtained by next-generation sequencing (NGS), and constructed the Buckwheat Genome DataBase. After assembling short reads, we determined 387,594 scaffolds as the draft genome sequence (FES_r1.0). The total length of FES_r1. 0 was 1,177,687,305 bp, and the N50 of the scaffolds was 25,109 bp. Gene prediction analysis revealed 286,768 coding sequences (CDSs; FES_r1.0_cds) including those related to transposable elements. The total length of FES_r1. 0_cds was 212,917,911 bp, and the N50 was 1,101 bp. Of these, the functions of 35,816 CDSs excluding those for transposable elements were annotated by BLAST analysis. To demonstrate the utility of the database, we conducted several test analyses using BLAST and keyword searches. Furthermore, we used the draft genome as a reference sequence for NGS-based markers, and successfully identified novel candidate genes controlling heteromorphic self-incompatibility of buckwheat. The database and draft genome sequence provide a valuable resource that can be used in efforts to develop buckwheat cultivars with superior agronomic traits.
Self-Reported Knee Symptoms Assessed by KOOS Questionnaire in Downhill Runners (Skyrunners)

Background The knee is the weight-bearing joint most commonly associated with sports injuries, and therefore is most at risk of developing degenerative changes, including osteoarthritis. Skyrunners can be considered to be at risk of developing symptoms of post-traumatic osteoarthritis due to downhill running. Aim The aim of this study was to analyze the health of the knee joints of a large group of these athletes via a specific self-report questionnaire. Methods This study was carried out by asking the participants of seven official Skyraces (22.4±3.1 km length; 1596±393 m elevation) to fill out a questionnaire. Information regarding age, sex, downhill elevation (m) during training and competitions over the last month, and history of previous knee injury was also collected before the participants filled out the Knee injury and Osteoarthritis Outcome Score (KOOS), which is a reliable and validated instrument designed to assess patients’ opinions about their knees and associated problems that can result in post-traumatic osteoarthritis. Athletes were divided into six age groups (from 17 to 70 years) and 12 groups based on the downhill gradient they had covered over the last month (from 1,000 to 40,000 m). Results Six hundred twenty-one questionnaires were collected from 45% of the participants in the seven races. Multivariate analysis revealed that self-reported KOOS scores were unrelated to age, sex and monthly downhill gradient. Only 74 (12%) of the participants reported previous knee injuries. Significant differences in the five subscales of the KOOS were found between skyrunners with and without previous knee injuries (P<0.01). Conclusions In the studied population, regular training for downhill running and participation in Skyraces could not be considered risk factors for subjective knee symptoms. Skyrunners with self-reported histories of knee injuries scored worse on all five subscales of the KOOS.
Predicting Hospital Length of Stay (PHLOS): A Multi-tiered Data Mining Approach

A model to predict the Length of Stay (LOS) for hospitalized patients can be an effective tool for healthcare providers. Such a model will enable early interventions to prevent complications and prolonged LOS and also enable more efficient utilization of manpower and facilities in hospitals. In this paper, we propose an approach for Predicting Hospital Length of Stay (PHLOS) using a multi-tiered data mining approach. In this paper we propose a methodology that employs clustering to create the training sets to train different classification algorithms. We compared the performance of different classifiers along several different performance measures and consistently found that using clustering as a precursor to form the training set gives better prediction results as compared to non-clustering based training sets. We have also found the accuracies to be consistently higher than some reported in the current literature for predicting individual patient LOS. The classification techniques used in this study are interpretable, enabling us to examine the details of the classification rules learned from the data. As a result, this study provides insight into the underlying factors that influence hospital length of stay. We also examine our results with domain expert insights.
Decal-Maps: Real-Time Layering of Decals on Surfaces for Multivariate Visualization

We introduce the use of decals for multivariate visualization design. Decals are visual representations that are used for communication; for example, a pattern, a text, a glyph, or a symbol, transferred from a 2D-image to a surface upon contact. By creating what we define as decal-maps, we can design a set of images or patterns that represent one or more data attributes. We place decals on the surface considering the data pertaining to the locations we choose. We propose a (texture mapping) local parametrization that allows placing decals on arbitrary surfaces interactively, even when dealing with a high number of decals. Moreover, we extend the concept of layering to allow the co-visualization of an increased number of attributes on arbitrary surfaces. By combining decal-maps, color-maps and a layered visualization, we aim to facilitate and encourage the creative process of designing multivariate visualizations. Finally, we demonstrate the general applicability of our technique by providing examples of its use in a variety of contexts.
CXCL1 Contributes to β-Amyloid-Induced Transendothelial Migration of Monocytes in Alzheimer’s Disease

Background Bone marrow-derived microglia that originates in part from hematopoietic cells, and more particularly from monocytes preferentially attach to amyloid deposition in brains of Alzheimer’s disease (AD). However, the mechanism of monocytes recruited into the amyloid plaques with an accelerated process in AD is unclear. Methodology/Principal Findings Here we reported that monocytes from AD patients express significantly higher chemokine (C-X-C motif) ligand 1 (CXCL1) compared to age-matched controls. AD patient’s monocytes or CXCL1-overexpressing THP-1 cells had enhanced ability of β-amyloid (Aβ)-induced transendothelial migration and Aβ-induced transendothelial migration for AD patient’s monocytes or CXCL1-overexpressing THP-1 cells was almost abrogated by anti-CXCL1 antibody. Furthermore, monocytes derived from a transgenic mouse model of AD also expressed significantly higher CXCL1. CD11b+CD45hi population of cells that were recruited from the peripheral blood were markedly bolcked in APP mouse brain by anti-CXCL1 antibody. Accordingly, in response to Aβ, human brain microvascular endothelial cells (HBMEC) significantly up-regulated CXC chemokine receptor 2 (CXCR2) expression, which was the only identified receptor for CXCL1. In addition, a high level expression of CXCR2 in HBMEC significantly promoted the CXCL1-overexpressing THP-1 cells transendothelial migration, which could be was abrogated by anti-CXCR2 antibody. Further examination of possible mechanisms found that CXCL1-overexpressing THP-1 cells induced transendothelial electrical resistance decrease, horseradish peroxidase flux increase, ZO-1 discontinuous and occludin re-distribution from insoluble to soluble fraction through interacting with CXCR2. ROCK inhibitor, Y27632, could block CXCL1-overexpressing THP-1 cells transendothelial migration, whereas other inhibitors had no effects. Conclusions/Significance The present data indicate that monocytes derived from AD patients overexpressing CXCL1, which is a determinant for Aβ-induced transendothelial migration. CXCL1 expressed by monocytes and CXCR2 on HBMEC is involved in monocytes migrating from blood to brain in AD patients.
Improving Packing Algorithms for Server Consolidation

The Computer Measurement Group, commonly called CMG, is a not for profit, worldwide organization of data processing professionals committed to the measurement and management of computer systems. CMG members are primarily concerned with performance evaluation of existing systems to maximize performance (eg. response time, throughput, etc.) and with capacity management where planned enhancements to existing systems or the design of new systems are evaluated to find the necessary resources required to provide adequate performance at a reasonable cost.
Anticorrelation: A Diversity Promoting Mechanisms in Ensemble Learning

Anti–correlationhas been used in training neural network ensembles. Negative correlation learning (NCL) is the state of the art anti–correlation measure. We present an alternative anti–correlation measure, RTQRT–NCL, which shows significant improvements on our test examples for both artificial neural networks(ANN) andgenetic programming (GP) learning machines. We analyze the behavior of the negative correlation measure and derive a theoretical explanation of the improved performance of RTQRT–NCL in larger ensembles.
Econometric Identification of the Cost of Maintaining a Child

The paper estimates the cost of maintaining a child, of different ages, the cost of being a single and the cost of additional adults present in a family with the aim of making the income levels of different households comparable. The study investigates the issue of econometric identification of equivalence scales within a demand system modified to include demographic characteristics consistently with economic theory. It shows that a robust estimation of equivalence scales must take into formal consideration the problem of econometric identification. The estimation also proposes an encompassing demographic specification which permits isolation of the costs due to differences in needs and differences in household life-styles and scale economies.
Faster algorithms for some geometric graph problems in higher dimensions

We show how to apply the well-separated pair decomposition of a point-set P in ? X+ to significantly improve known time bounds on several geometric graph problems. We first present an algorithm to find an approximate Euclidean minimum spanning tree of P whose weight is at most 1 + e times the exact minimum. We achieve a time complexity of O(nlogn + (cd/2 log ‘)n), improving the best known bound of O(cmdn16gn). We then show how to construct a graph with O(cmd+rn) edges in which the shortest path between any pair of points is within 1 + c of the Euclidean distance. Our time complexity is O(nlogn+(c-d log $)n), a significant improvement over the best previous algorithm that produces a graph of this size. Finally, we show how to compute the exact Euclidean minimum spanning tree in time o(Td(n, n) lOgn), where Td(m, n) iS the time to find the bichromatic closest pair between m red points and n blue points. The previous bound was O(Td(n, n)logd n). As with the previous algorithm, our complexity reduces to O(Td(n,n)) if ? d(n,n) = i-@ 1+a) for some (Y > 0.
Difference analysis in IEEE 802.11 DCF

In this paper, a simple and accurate estimation on performance of the original IEEE 802.11 distributed coordination function (DCF) is presented. The performances obtained from the Bianchi's analytical model of the IEEE 802.11 DCF are compensated by means of (1) the number of consecutive successful transmissions and (2) the deferred slot time. The compensated performances including throughput, packet loss rate, and the average number of transmissions approximate to the simulation results with a high degree of accuracy under a number of conditions even when the minimum contention window is small. The analytical and simulation results show us the possibility of performance improvement by the sender priority.
Trusted computing technology analyzing in NGSCB

This paper mainly analyzes the Microsoft's implementations of Trusted Computing in its Next-Generation Secure Computing Base (NGSCB), and investigates that why NGSCB can build a secure and trusted system, and shows how it is built. In addition, Windows secure ability on withstanding attacks is also presented, and some defects that brought reproach upon NGSCB are proposed. Finally, some related works are listed, compared with the NGSCB.
Adaptive wavelet regularity scalable image coding

An adaptive regularity scalable wavelet image coding algorithm is proposed in this paper. The bitstream is generated in the order of regularity such that visually more important components of a decoded image can be obtained first, followed by the higher regularity components as more bits are received and decoded. The scalability is achieved by selecting different extents of wavelet coefficients at various regularity levels. These regularity levels are determined adaptively. Regularity of the image is estimated from the interscale ratios of the separable wavelet transform magnitude sums. Compared to the wavelet image coder generating resolution scalable bitstreams, significant improvement in visual quality and PSNR can be achieved.
Democratising Organisational Knowledge: The Potential of the Corporate Wiki

Attempts to impose knowledge management often ignore the vast organisational resource of workrelated tacit knowledge possessed by knowledge workers. Our research reveals that activities supported by social technologies such as Wikis, may provide a more appropriate capability for tacit knowledge management where a network centric focus is adopted. A corporate Wiki has the potential to engage the collective responsibilities of knowledge workers to transfer their collective experience and skills into a dynamic shared knowledge repository. However, the traditional organisational culture can be reluctant to allow this power shift which surrenders the monopolistic control of the few over the creation and management of organisational knowledge. In order to frame the theoretical perspectives of these new processes of creation, accumulation and maintenance of tacit knowledge in organisations, this paper uses Activity Theory to analyse the Wiki as a tool that mediates employee-based knowledge management activities leading to the democratisation of organisational knowledge.