Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributive Leadership Functions, Readiness for Change, and Teachers’ Affective Commitment to Change: A Partial Least Squares Analysis

Although the literature abounds with factors that contribute to organizational commitment and commitment to change, it is still unclear what factors influence teachers’ affective commitment to change. This study attempts to examine the relationships between two perceived distributive leadership functions, namely, leadership team cooperation and participative decision-making, and teachers’ affective commitment to change with the mediating effects of intentional, emotional, and cognitive readiness for change. Data consisted of 229 Malaysian teachers selected randomly from 24 secondary schools in Penang, Perak, and Johor. Data were analyzed using partial least squares structural equation modeling approach. Findings revealed either leadership team cooperation or participative decision-making has no significant direct relationship with teachers’ affective commitment to change. However, significant but weak mediating effects were found between participative decision-making and teachers’ affective commitment to change with the mediators of intentional, emotional, and cognitive readiness for change. Limitations, implications, and suggestions for future studies are presented.
Specified Species in Gingival Crevicular Fluid Predict Bacterial Diversity

Background Analysis of gingival crevicular fluid (GCF) samples may give information of unattached (planktonic) subgingival bacteria. Our study represents the first one targeting the identity of bacteria in GCF. Methodology/Principal Findings We determined bacterial species diversity in GCF samples of a group of periodontitis patients and delineated contributing bacterial and host-associated factors. Subgingival paper point (PP) samples from the same sites were taken for comparison. After DNA extraction, 16S rRNA genes were PCR amplified and DNA-DNA hybridization was performed using a microarray for over 300 bacterial species or groups. Altogether 133 species from 41 genera and 8 phyla were detected with 9 to 62 and 18 to 64 species in GCF and PP samples, respectively, per patient. Projection to latent structures by means of partial least squares (PLS) was applied to the multivariate data analysis. PLS regression analysis showed that species of genera including Campylobacter, Selenomonas, Porphyromonas, Catonella, Tannerella, Dialister, Peptostreptococcus, Streptococcus and Eubacterium had significant positive correlations and the number of teeth with low-grade attachment loss a significant negative correlation to species diversity in GCF samples. OPLS/O2PLS discriminant analysis revealed significant positive correlations to GCF sample group membership for species of genera Campylobacter, Leptotrichia, Prevotella, Dialister, Tannerella, Haemophilus, Fusobacterium, Eubacterium, and Actinomyces. Conclusions/Significance Among a variety of detected species those traditionally classified as Gram-negative anaerobes growing in mature subgingival biofilms were the main predictors for species diversity in GCF samples as well as responsible for distinguishing GCF samples from PP samples. GCF bacteria may provide new prospects for studying dynamic properties of subgingival biofilms.
Synthesis , part of a Special Feature on The Governance of Adaptation Social Justice and Adaptation in the UK

Adaptation strategies and policies are normally based on climate impact assessments that fail to take account of the social nature and distribution of vulnerability to climate change. This is largely a product of the dominant assessment techniques that are used to inform such strategies and the limits of existing evidence. In this paper I contribute to filling gaps in the current adaptation literature by exploring the social nature of vulnerability and the potential for socially just adaptation. It does so by reviewing studies from the UK, in particular those under the Joseph Rowntree Foundation’s Climate Change and Social Justice programme. It finds that vulnerability to high temperatures and fluvial and coastal flooding, in terms of sensitivity, exposure, and the capacity to anticipate, respond, and recover, is concentrated in certain disadvantaged and socially marginalized groups, including those on low incomes. It also finds that both autonomous and planned adaptation may fail to protect the most vulnerable individuals and groups, and may even reinforce existing patterns of vulnerability in some cases, i.e., mal-adaptation, especially where they rely on unmediated market forces or where they fail to explicitly recognize aspects of social vulnerability in their design and implementation. I argue that social justice should be an explicit objective of adaptation strategy.
Predicting citation counts of papers

The task of citation counts prediction is to predict the citation counts of a paper after a given time period. Future citation counts of papers are an important metric to estimate potential influences of published papers, and will be helpful for researchers to choose representative literatures. This task can be treated as a regression problem. This paper proposes two types of predictive features to represent fundamental characteristics of papers and authors: six content features and ten author features. We introduce the IBM Model 1 to calculate the association probabilities between paper topics which are employed to extract content features, and use the bipartite network projection to obtain the author collaboration network which is utilized to extract author features. Further, we introduce the Gradient Boosted Regression Trees to predict citation counts of papers. Our approach combines contents and topics of papers and multi-dimensional measures of author collaborations in one learning process. Experimental results on the KDD CUP dataset demonstrate that our predicting features and models are effective to solve the problem of citation counts prediction of papers.
Effect of intravenous iron use on hospitalizations in patients undergoing hemodialysis: a comparative effectiveness analysis from the DEcIDE-ESRD study.

BACKGROUND Intravenous iron use in hemodialysis patients has greatly increased over the last decade, despite limited studies on the safety of iron. METHODS We studied the association of receipt of intravenous iron with hospitalizations in an incident cohort of hemodialysis patients. We examined 9544 patients from Dialysis Clinic, Inc. (DCI). We ascertained intravenous iron use from DCI electronic medical record and USRDS data files, and hospitalizations through Medicare claims. We examined the association between iron exposure accumulated over 1-, 3- or 6-month time windows and incident hospitalizations in the follow-up period using marginal structural models accounting for time-dependent confounders. We performed sensitivity analyses including recurrent events models for multiple hospitalizations and models for combined outcome of hospitalization and death. RESULTS There were 22 347 hospitalizations during a median follow-up of 23 months. Higher cumulative dose of intravenous iron was not associated with all-cause, cardiovascular or infectious hospitalizations [HR 0.97 (95% CI: 0.77-1.22) for all-cause hospitalizations comparing >2100 mg versus 0-900 mg of iron over 6 months]. Findings were similar in models examining the risk of hospitalizations in 1- and 3-month windows [HR 0.88 (95% CI: 0.79-0.99) and HR 0.88 (95% CI: 0.74-1.03), respectively] or the risk of combined outcome of hospitalization and death in the 6-month window [HR 0.98 (95% CI: 0.78-1.23)]. CONCLUSIONS Higher cumulative dose of intravenous iron may not be associated with increased risk of hospitalizations in hemodialysis patients. While clinical trials are needed, employing higher iron doses to reduce erythropoiesis-stimulating agents does not appear to increase morbidity in routine clinical care.
Customer Concentration and Corporate Tax Avoidance

Firms with a concentrated corporate customer base need to hold more cash and have a stronger incentive to manage earnings upwards. Since tax planning can increase both cash flow and accounting earnings, firms with a concentrated customer base may be more likely to engage in tax avoidance. We find evidence of a positive association between the level of corporate customer concentration and the extent of tax avoidance. In addition, we find that the positive relation between corporate customer concentration and tax avoidance is more pronounced when a firm has a lower Market Share in its industry, enjoys less revenue diversification, and engages less in real earnings management. In contrast to corporate major customers, governmental major customers provide stable cash flow to suppliers, which is likely to alleviate supplier firms’ need for tax avoidance. We find that firms engage in lower levels of tax avoidance when they have a governmental major customer, and that this association is less pronounced under Democratic presidencies. Taken together, our findings indicate that a firm's customer concentration (i.e., corporate and governmental major customers) has a significant effect on the extent to which it avoids taxes.
Security-Informed Safety Case Approach to Analysing MILS Systems

Safety cases are the development foundation for safety-critical systems and are often quite complex to understand depending on the size of the system and operational conditions. The recent advent of security aspects complicates the issues further. This paper describes an approach to analysing safety and security in a structured way and creating security-informed safety cases that provide justification of safety taking into particular consideration the impact of security. The paper includes an overview of the structured assurance case concept, a security-informed safety methodology and a layered approach to constructing cases. The approach is applied to a Security Gateway that is used to control data flow between security domains in a separation kernel based operating system in avionics environment. We show that a clear and structured way of presenting a safety case combining safety and security alleviates understanding important interactions taking into account the impact and, hence, increases safety.
Hierarchical Topical Segmentation with Affinity Propagation

We present a hierarchical topical segmenter for free text. Hierarchical Affinity Propagation for Segmentation (HAPS) is derived from a clustering algorithm Affinity Propagation. Given a document, HAPS builds a topical tree. The nodes at the top level correspond to the most prominent shifts of topic in the document. Nodes at lower levels correspond to finer topical fluctuations. For each segment in the tree, HAPS identifies a segment centre ‐ a sentence or a paragraph which best describes its contents. We evaluate the segmenter on a subset of a novel manually segmented by several annotators, and on a dataset of Wikipedia articles. The results suggest that hierarchical segmentations produced by HAPS are better than those obtained by iteratively running several one-level segmenters. An additional advantage of HAPS is that it does not require the “gold standard” number of segments in advance.
Evidence-Based Practice and the Consideration of Assistive Technology: Effectiveness and Outcomes.

The legislative and policy background for evidence-based practice (EBP) is presented with implications for research on assistive technology (AT) research in general and for the AT consideration process specifically. Requirements for the development of research-based evidence of AT effectiveness are presented as a guide for researchers and developers of AT and for practitioners who use findings of AT effectiveness. EBP as part of decision-making guidelines for AT consideration are presented.
A mathematical framework for inverse wave problems in heterogeneous media

This paper provides a theoretical foundation for some common formulations of inverse problems in wave propagation, based on hyperbolic systems of linear integro-differential equations with bounded and measurable coefficients. The coefficients of these time-dependent partial differential equations represent parametrically the spatially varying mechanical properties of materials. Rocks, manufactured materials, and other wave propagation environments often exhibit spatial heterogeneity in mechanical properties at a wide variety of scales, and coefficient functions representing these properties must mimic this heterogeneity. We show how to choose domains (classes of nonsmooth coefficient functions) and data definitions (traces of weak solutions) so that optimization formulations of inverse wave problems satisfy some of the prerequisites for application of Newton’s method and its relatives. These results follow from the properties of a class of abstract first-order evolution systems, of which various physical wave systems appear as concrete instances. Finite speed of propagation for linear waves with bounded, measurable mechanical parameter fields is one of the by-products of this theory.
WEB-BASED EXPLORATORY DATA ANALYSIS (WEB-EDA): VISUALISATION MEETS SPATIAL ANALYSIS

: This paper provides an overview of the development in visualisation and spatial analysis. It has been found that, from paper maps to web-based visualisation, the roles of maps have changed from “display and storage” to “display and exploration” and “storage and linking”. The variables for presentations have been expanded from traditional set of visual variables to fives set of variables, i.e. visual variable, screen variables, dynamic variable, exploratory acts and web variables. It has also been found that spatial analysis has also undergone similar transition. The concept of space has been expanded from Euclidean space to other spaces such as social space, perceptual space, topological space, scale space and so on. The analysis methods have also been expanded from traditional statistics to spatial statistics, and to a broader concept including modelling, computation and optimisation methods. However, visualisation and spatial analysis are moving together to form web-based exploratory data analysis (Web-EDA), which focuses on active collaboration between the visual and numeric/statistical analysis. (Indeed, the emerging of Web-EDA also justifies the grouping of these two topics into a working group).
Rapid Wastage of Alaska Glaciers and Their Contribution to Rising Sea Level

We have used airborne laser altimetry to estimate volume changes of 67 glaciers in Alaska from the mid-1950s to the mid-1990s. The average rate of thickness change of these glaciers was –0.52 m/year. Extrapolation to all glaciers in Alaska yields an estimated total annual volume change of –52 ± 15 km3/year (water equivalent), equivalent to a rise in sea level (SLE) of 0.14 ± 0.04 mm/year. Repeat measurements of 28 glaciers from the mid-1990s to 2000–2001 suggest an increased average rate of thinning, –1.8 m/year. This leads to an extrapolated annual volume loss from Alaska glaciers equal to –96 ± 35 km3/year, or 0.27 ± 0.10 mm/year SLE, during the past decade. These recent losses are nearly double the estimated annual loss from the entire Greenland Ice Sheet during the same time period and are much higher than previously published loss estimates for Alaska glaciers. They form the largest glaciological contribution to rising sea level yet measured.
Local voting of weak classifiers

Many data mining problems involve an investigation of relationships between features in heterogeneous datasets, where different learning algorithms can be more appropriate for different regions. We propose herein a technique of localized voting of weak classifiers. This technique identifies local regions which have similar characteristics and then uses the votes of each local expert to describe the relationship between the data characteristics and the target class. We performed a comparison with other well known combining methods on standard benchmark datasets and the accuracy of the proposed method was greater.
Recognizing human behaviors with vision sensors in a network robot system

A network robot system integrated with various types of robots via ubiquitous networks is a new concept which introduces an interactive robot living together with people. In this paper, we present a tangible network robot system composed of a mobile robot and vision sensors embedded in an environment, and show human behavior recognition methods necessary for providing diverse services desired by the people in good time. Typical human behaviors are described with logical sensors which are defined through data fusion processes spatially and temporally with the physical sensors of the mobile robot and those in the environment. Our system can be utilized to make human-robot communication and interaction friendlier and smarter
A multi-dimensional measure function for classifier performance

Evaluation of classifier performance is often based on statistical methods e.g. cross-validation tests. In these tests performance is often strongly related to or solely based on the accuracy of the classifier on a limited set of instances. The use of measure functions has been suggested as a promising approach to deal with this limitation. However, no usable implementation of a measure function has yet been presented. This article presents such an implementation and demonstrates its usage through a set of experiments. The results indicate that there are cases for which measure functions may be able to capture important aspects of the evaluated classifier that cannot be captured by cross-validation tests.
Moral Hazard in Health Insurance: Do Dynamic Incentives Matter?

Abstract Using data from employer-provided health insurance and Medicare Part D, we investigate whether health care utilization responds to the dynamic incentives created by the nonlinear nature of health insurance contracts. We exploit the fact that because annual coverage usually resets every January, individuals who join a plan later in the year face the same initial (“spot”) price of health care but a higher expected end-of-year (“future”) price. We find a statistically significant response of initial utilization to the future price, rejecting the null that individuals respond only to the spot price. We discuss implications for analysis of moral hazard in health insurance.
A Novel Organization of ACT Domains in Allosteric Enzymes Revealed by the Crystal Structure of Arabidopsis Aspartate Kinase[W]

Asp kinase catalyzes the first step of the Asp-derived essential amino acid pathway in plants and microorganisms. Depending on the source organism, this enzyme contains up to four regulatory ACT domains and exhibits several isoforms under the control of a great variety of allosteric effectors. We report here the dimeric structure of a Lys and S-adenosylmethionine–sensitive Asp kinase isoform from Arabidopsis thaliana in complex with its two inhibitors. This work reveals the structure of an Asp kinase and an enzyme containing two ACT domains cocrystallized with its effectors. Only one ACT domain (ACT1) is implicated in effector binding. A loop involved in the binding of Lys and S-adenosylmethionine provides an explanation for the synergistic inhibition by these effectors. The presence of S-adenosylmethionine in the regulatory domain indicates that ACT domains are also able to bind nucleotides. The organization of ACT domains in the present structure is different from that observed in Thr deaminase and in the regulatory subunit of acetohydroxyacid synthase III.
Deposited in DRO : 17 April 2013 Version of attached le : Accepted Version Peer-review status of attached

The k-Coloring problem is to test whether a graph can be colored with at most k colors such that no two adjacent vertices receive the same color. If a graph G does not contain a graph H as an induced subgraph, then G is called H-free. For any fixed graph H on at most 6 vertices, it is known that 3-Coloring is polynomial-time solvable on H-free graphs whenever H is a linear forest and NP-complete otherwise. By solving the missing case P2 + P3, we prove the same result for 4Coloring provided that H is a fixed graph on at most 5 vertices.
Stress-Related Immune Markers in Depression: Implications for Treatment

Major depression is a serious psychiatric disorder; however, the precise biological basis of depression still remains elusive. A large body of evidence implicates a dysregulated endocrine and inflammatory response system in the pathogenesis of depression. Despite this, given the heterogeneity of depression, not all depressed patients exhibit dysregulation of the inflammatory and endocrine systems. Evidence suggests that inflammation is associated with depression in certain subgroups of patients and that those who have experienced stressful life events such as childhood trauma or bereavement may be at greater risk of developing depression. Consequently, prolonged exposure to stress is thought to be a key trigger for the onset of a depressive episode. This review assesses the relationship between stress and the immune system, with a particular interest in the mechanisms by which stress impacts immune function, and how altered immune functioning, in turn, may lead to a feed forward cascade of multiple systems dysregulation and the subsequent manifestation of depressive symptomology. The identification of stress-related immune markers and potential avenues for advances in therapeutic intervention is vital. Changes in specific biological markers may be used to characterize or differentiate depressive subtypes or specific symptoms and may predict treatment response, in turn facilitating a more effective, targeted, and fast-acting approach to treatment.
Symptoms of posttraumatic stress disorder and coping strategies among female burn victims: An exploratory study

Objective: The current study aimed at investigating the relationship between symptoms of posttraumatic stress disorder (PTSD) and different coping strategies. Moreover, it is also aimed at exploring the differences in symptoms of PTSD among single and married female victims. Methodology: A cross-sectional correlational research design was used. Fifty burn women, 18–45 years of age were recruited from different burn units and nongovernmental organizations of two adjacent cities. PTSD checklist (Weather, Litz, Herman, Huska and Keane, 1993) for civilians was used to assess the symptoms of PTSD, while Brief COPE Inventory (Carver, 1997) was used to measure the coping strategies of female burn victims. Results: Results indicated that there is a negative relationship between symptoms of PTSD and self-distraction, use of emotional support, use of instrumental support, venting, positive reframing planning, humor, whereas self-blame and active coping are positively associated with symptoms of PTSD (P > 0.05). Conclusion: The findings indicated that coping strategies are associated with PTSDs. Positive and adaptive coping strategies help the individuals to cope effectively with symptoms of PTSD as compare to negative/avoidant coping strategies. Moreover, it has been found that single and married burn victims experience the same level of PTSD symptoms. Limitations and suggestions are also discussed.
Adaptive Image Deringing

This paper proposes new and original adaptive image ringing detection and ringing suppression methods. Ringing detection is performed using a scale-space based computational analysis of ideal low-pass filtering of step edges. Edge width conception is introduced and is used to approximate ringing parameter. Method to choose strong isolated edges which are the best suitable edges for ringing analysis is proposed. A method of ringing level estimation for 2D images with unknown ringing parameters is introduced and used to perform real image deringing. New image quality metrics sensible to ringing artifact are introduced and used to analyze image resampling methods.