Miracle-dz/UniFAR-FTUs huggingface dataset:
Stratégies événementielles de réinitialisation pour un consensus dans les systèmes multi-agents

Cet article porte sur le probleme du consensus dans un reseau partitionne en plusieurs clusters. Au sein de chaque cluster, les agents interagissent de maniere continue. En plus chaque cluster contient un agent specifique appele leader ayant la capacite de communiquer avec d'autres leaders en vue de s'accorder avec eux. Ces interactions s'averent couteuses puisqu'elles requierent des echanges sur des distances longues ou mal protegees. Neanmoins, ces interactions sont necessaires pour accomplir l'objectif global du reseau. Nous traitons dans cet article differentes strategies d'interconnections entre les leaders en vue d'optimiser le cout et la consommation d'energie et nous essayons de mettre l'accent sur l'apport de la technique evenementielle par rapport aux approches quasi-periodiques classiques.
Moral identity in psychopathy

Several scholars have recognized the limitations of theories of moral reasoning in explaining moral behavior. They have argued that moral behavior may also be influenced by moral identity, or how central morality is to one’s sense of self. This idea has been supported by findings that people who exemplify moral behavior tend to place more importance on moral traits when defining their self-concepts (Colby & Damon, 1995). This paper takes the next step of examining individual variation in a construct highly associated with immoral behavior — psychopathy. In Study 1, we test the hypothesis that individuals with a greater degree of psychopathic traits have a weaker moral identity. Within a large online sample, we found that individuals who scored higher on a measure of psychopathic traits were less likely to base their self-concepts on moral traits. In Study 2, we test whether this reduced sense of moral identity can be attributed to differences in moral judgment, which is another factor that could influence immoral behavior. Our results indicated that the reduced sense of moral identity among more psychopathic individuals was independent of variation in moral judgment. These results suggest that individuals with psychopathic traits may display immoral behavior partially because they do not construe their personal identities in moral terms.
A hybrid AC/DC microgrid control scheme with voltage-source inverter-controlled interlinking converters

This paper proposes a fully decentralized control scheme for hybrid AC/DC microgrids. It proportionally shares the loads in a hybrid AC/DC microgrid among its sub-grids. By controlling the interlinking converters as voltage source inverters, the scheme enables the hybrid microgrid to operate with or without AC sources. It is possible to shut down all the power sources in the AC sub-grid to minimize the fuel consumption. Moreover, any fault in the AC sources will not cause the collapse of the entire AC sub-grid. Consequently, the hybrid microgrid under the control scheme can have higher efficiency, reliability and flexibility as compared to the existing decentralized schemes.
Visualising knowledge maps for encyclopedia articles

This publication presents a prototype visualisation system for navigation of encyclopedia articles based on knowledge maps connecting articles to each other. A turning table is used as a metaphor to depict a result set as a whole, while three-dimensional objects of various shapes placed on top of the table represent individual encyclopaedia articles. The system employs a number of depth cues to enhance spatial perception and uses depth-dependent semi-transparency of labels to avoid display cluttering. A concrete implementation for the German language "Brockhaus Multimedial" electronic encyclopaedia is presented and discussed.
Systematic Distress Risk : Evidence from State-Contingent Failure Prediction * Preliminary and incomplete

We develop a measure of firm-specific systematic distress risk using an empirical model of state-contingent probability of failure, where states correspond to economic recessions and expansions. We find a positive distress risk premium of 5-8% per annum associated with this measure in the cross-section of stock returns. This result stands in stark contrast to the previously documented distress risk anomaly—a negative correlation between unconditional probability of failure and stock returns. A distress-risk mimicking portfolio that is long (short) in high (low) recessionary failure probability stocks can track aggregate incidence of failure and future macroeconomic conditions. JEL classification: G11, G12, G32, G33.
Implementation of coded cooperation using a kind of convolutional codes

User cooperative communication can bring spatial diversity, and improve cell boundary uplink quality. This paper gives a kind of convolutional codes suitable for user cooperation with lower complexity than Turbo codes and LDPC codes, and can guarantee good inter-user communication quality when cooperation succeeds, and also good uplink communication quality when cooperation defeats. Simulation results show that when we use 50% cooperation, under the condition that the two users have similar uplink quality and perfect inter-user channel, at BER=10−3, this kind of coded cooperation can provide almost 11 dB performance gains, compared with non-cooperation. Moreover, performance of user cooperation using this kind of convolutional codes is better than that using rate-compatible punctured convolutional codes.
PENGARUH CORPORATE SOCIAL RESPONSIBILITY TERHADAP KINERJA KEUANGAN

The aims of this research were to know : (1) The influence of CSR variables (employee, environment, community) as independent varables either partially or simultaneously towards Return on Assets (2) The influence of CSR variables(employee, environment, community) as independent varables either partially or simultaneously towards Tobin’s Q. The method of this research is multiple linear regression analysis. The research sample were taken from Corporate’s data on IDX through annual report and financial information from financial reports for manufacturers, developers, and miners (just typically pure trading corporates were not included) in the period 2010 to 2012 with the purposive sampling method. There were 95 of the companies that met the criteria and were accumulated for three years, so total of samples became 285 samples. The result of research showed that all of CSR variables gave positive significant influence simultaneously towards the dependent variables of ROA and Tobin’s Q. Partially, the variables of employees and community were positively significant influencing the dependent variable of ROA, and only employees as the independent variable had positive influence towards Tobin’s Q
Ferroportin 1 is expressed basolaterally in rat kidney proximal tubule cells and iron excess increases its membrane trafficking

Ferroportin 1 (FPN1) is an iron export protein expressed in liver and duodenum, as well as in reticuloendothelial macrophages. Previously, we have shown that divalent metal transporter 1 (DMT1) is expressed in late endosomes and lysosomes of the kidney proximal tubule (PT), the nephron segment responsible for the majority of solute reabsorption. We suggested that following receptor mediated endocytosis of transferrin filtered by the glomerulus, DMT1 exports iron liberated from transferrin into the cytosol. FPN1 is also expressed in the kidney yet its role remains obscure. As a first step towards determining the role of renal FPN1, we localized FPN1 in the PT. FPN1 was found to be located in association with the basolateral PT membrane and within the cytosolic compartment. FPN1 was not expressed on the apical brush‐border membrane of PT cells. These data support a role for FPN1 in vectorial export of iron out of PT cells. Furthermore, under conditions of iron loading of cultured PT cells, FPN1 was trafficked to the plasma membrane suggesting a coordinated cellular response to export excess iron and limit cellular iron concentrations.
A review of multilevel theory for ecologic analyses

This paper reviews multilevel and conventional models for the analysis of ecologic (group, aggregate) data. It emphasizes the non‐separability of contextual (group‐level) effects and individual‐level effects that arises from the multilevel structure of the underlying effects. Contrary to common misperceptions, this problem afflicts ecologic studies in which the sole objective is to estimate contextual effects, as well as studies in which the objective is to estimate individual effects. Multilevel effects also severely complicate causal interpretations of model coefficients. Copyright © 2002 John Wiley & Sons, Ltd.
Targeting potassium channels for increasing delivery of imaging agents and therapeutics to brain tumors

Every year in the US, 20,000 new primary and nearly 200,000 metastatic brain tumor cases are reported. The cerebral microvessels/capillaries that form the blood–brain barrier not only protect the brain from toxic agents in the blood but also pose a significant hindrance to the delivery of small and large therapeutic molecules. Different strategies have been employed to circumvent the physiological barrier posed by blood–brain tumor barrier (BTB). Studies in our laboratory have identified significant differences in the expression levels of certain genes and proteins between normal and brain tumor capillary endothelial cells (ECs). In this study, we validated the non-invasive and clinically relevant dynamic contrast enhancing-magnetic resonance imaging (DCE-MRI) method with invasive, clinically irrelevant but highly accurate quantitative autoradiography method using rat glioma model. We also showed that DCE-MRI metric of tissue vessel perfusion-permeability is sensitive to changes in blood vessel permeability following administration of calcium-activated potassium (BKCa) channel activator NS-1619. Our results show that human gliomas and brain tumor ECs that overexpress BKCa channels can be targeted for increased BTB permeability for MRI enhancing agents to brain tumors. We conclude that monitoring the outcome of increased MRI enhancing agents’ delivery to microsatellites and leading tumor edges in glioma patients would lead to beneficial clinical outcome.
Design of PV powered SR motor driven irrigation pumps utilizing boost converter

This paper presents the design of a cost-effective and efficient solar powered irrigation pump utilizing a switched reluctance motor (SRM). It utilizes a simple DC-DC boost converter as a power conditioning stage between SPV array and the motor drive. The control of solar photovoltaic (SPV) array output power at maximum power point (MPP) and facilitating the soft-starting to the SRM drive, are two prime functions of the boost converter. The use of a 4-phase SRM drive minimizes the torque ripple and increases the number of strokes without incrementing the number of rotor poles. The low number of switches in a mid-point converter used to energize SRM phases further enhances the performance of the system. The speed control of the motor using the pulse width modulation (PWM) switching of split-capacitor converter eliminates the requirement of additional sensors on the motor to control its speed. The proposed water pumping system is designed, modeled and its performance is simulated on MATLAB/Simulink platform and its responses are analyzed, under the varying environmental conditions, which authenticate its appropriateness as an irrigation pump.
Incorporating Near-Infrared Information into Semantic Image Segmentation

Recent progress in computational photography has shown that we can acquire near-infrared (NIR) information in addition to the normal visible (RGB) band, with only slight modifications to standard digital cameras. Due to the proximity of the NIR band to visible radiation, NIR images share many properties with visible images. However, as a result of the material dependent reflection in the NIR part of the spectrum, such images reveal different characteristics of the scene. We investigate how to effectively exploit these differences to improve performance on the semantic image segmentation task. Based on a state-of-the-art segmentation framework and a novel manually segmented image database (both indoor and outdoor scenes) that contain 4-channel images (RGB+NIR), we study how to best incorporate the specific characteristics of the NIR response. We show that adding NIR leads to improved performance for classes that correspond to a specific type of material in both outdoor and indoor scenes. We also discuss the results with respect to the physical properties of the NIR response.
Feature Classification for Robust Shape-Based Collaborative Tracking and Model Updating

A new collaborative tracking approach is introduced which takes advantage of classified features. The core of this tracker is a single tracker that is able to detect occlusions and classify features contributing in localizing the object. Features are classified in four classes: good, suspicious, malicious, and neutral. Good features are estimated to be parts of the object with a high degree of confidence. Suspicious ones have a lower, yet significantly high, degree of confidence to be a part of the object. Malicious features are estimated to be generated by clutter, while neutral features are characterized with not a sufficient level of uncertainty to be assigned to the tracked object. When there is no occlusion, the single tracker acts alone, and the feature classification module helps it to overcome distracters such as still objects or little clutter in the scene. When more than one desired moving objects bounding boxes are close enough, the collaborative tracker is activated and it exploits the advantages of the classified features to localize each object precisely as well as updating the objects shape models more precisely by assigning again the classified features to the objects. The experimental results show successful tracking compared with the collaborative tracker that does not use the classified features. Moreover, more precise updated object shape models will be shown.
Changes in Body Image Perceptions Upon Leaving Elite Sport: The Retired Female Athlete Paradox

Little is known about the evolution of female athlete body image into retirement. In this study, 218 retired athletes from aesthetic sports answered a series of closed- and open-ended questions regarding bodily changes since retirement. Years since retirement were unrelated to current weight status (e.g., underweight and normal weight), what they were doing about their current weight (e.g., lose weight), and satisfaction with current weight (all ps > .69). Overall, 74.3% thought they were normal weight, yet 55% were dissatisfied with their weight, and 59.6% were trying to lose weight. A rigorous thematic analysis of the qualitative data yielded 4 core themes that characterized participants’ experiences: (a) a move toward the feminine ideal; (b) feeling fat, flabby, and ashamed; (c) a continued commitment to a former self; and (d) conflicting ideals: the retired female athlete paradox. Perceived muscle loss was considered indicative of either increased fat (dissatisfaction) or increased femininity (satisfaction). For some retired athletes, the satisfaction brought on by newfound femininity was complicated by a coinciding and conflicting commitment to a muscular athletic physique. Practical applications include strategies for sport psychologists to better support athletes in coping with the body changes that occur on retirement from elite sport.
Racial and ethnic disparities among individuals with Alzheimer’s disease in the United States: A literature review

This study reviews the published literature on racial and ethnic disparities among people with Alzheimer’s disease (AD) and related dementias in the United States. To identify relevant studies, we searched electronic sources for peer-reviewed journal articles and unpublished research reports that were published through July 2014; related to the AD population and their caregivers; and provided evidence of racial and ethnic disparities, discussed reasons for disparities, or described interventions to address disparities. The literature shows consistent and adverse disparities among blacks and Hispanics compared with non-Hispanic whites concerning AD, including the disease’s prevalence and incidence, mortality, participation in clinical trials, use of medications and other interventions, use of long-term services and supports, health care expenditures, quality of care, and caregiving. The literature suggests numerous underlying causes, including factors related to measurement of the disease, genetics, socioeconomic factors, cultural differences, lack of culturally competent clinicians, and discrimination. Although these disparities are well known, little is known about the effectiveness of various strategies, such as cultural competence training, to address these differences, and very few studies evaluate possible interventions.
An efficient algorithm for XML type projection

In the contexts of data integration and data exchange, schema mappings are primarily used for query answering. As a consequence, their maintenance and, in particular, the detection of corrupted mappings, i.e., mappings that fail in matching the source and/or the target schema, is crucial.Corruption checking can be automatically performed by relying on an operation called type projection. This work describes an efficient algorithm for checking XML type projection, based on a characterization of type projection in terms of type simulation.
Evaluation of Missing Value Estimation for Microarray Data

Microarray gene expression data contains missing values (MVs). However, some methods for downstream analyses, including some predic- tion tools, require a complete expression data matrix. Current methods for estimating the MVs include sample mean and K-nearest neighbors (KNN). Whether the accuracy of estimation (imputation) methods depends on the actual gene expression has not been thoroughly investigated. Under this set- ting, we examine how the accuracy depends on the actual expression level and propose new methods that provide improvements in accuracy relative to the current methods in certain ranges of gene expression. In particular, we propose regression methods, namely multiple imputation via ordinary least squares (OLS) and missing value prediction using partial least squares (PLS). Mean estimation of MVs ignores the observed correlation structure of the genes and is highly inaccurate. Estimating MVs using KNN, a method which incorporates pairwise gene expression information, provides substan- tial improvement in accuracy on average. However, the accuracy of KNN across the wide range of observed gene expression is unlikely to be uniform and this is revealed by evaluating accuracy as a function of the expression level.
RARGE: a large-scale database of RIKEN Arabidopsis resources ranging from transcriptome to phenome

The RIKEN Arabidopsis Genome Encyclopedia (RARGE) database houses information on biological resources ranging from transcriptome to phenome, including RIKEN Arabidopsis full-length (RAFL) complementary DNAs (cDNAs), their promoter regions, Dissociation (Ds) transposon-tagged lines and expression data from microarray experiments. RARGE provides tools for searching by resource code, sequence homology or keyword, and rapid access to detailed information on the resources. We have isolated 245 946 RAFL cDNA clones and collected 11 933 transposon-tagged lines, which are available from the RIKEN Bioresource Center and are stored in RARGE. The RARGE web interface can be accessed at http://rarge.gsc. riken.jp/. Additionally, we report 90 000 new RAFL cDNA clones here.
Artificial Neural Networks in Sports: New Concepts and Approaches

Artificial neural networks are tools, which - similar to natural neural networks - can learn to recognize and classify patterns, and so can help to optimise context depending acting. These abilities, which are very useful in a lot of technical approaches, seem to be as well useful in particular in analysing and planning tactical patterns in sport games or patterns of learning behaviour in training processes. In a first attempt, in co-operation with LAMES from the University of Rostock, tactical structures in volleyball could successfully be analysed using neural networks. However, the problem is that the special type of network that has to be used for such analyses (i.e. the so called Kohonen Feature Map or KFM) needs a huge amount of data and lacks the necessary dynamic in continuous learning. So in order to describe, analyse, and evaluate continuous learning processes in sports a dynamically controlled network (“DYCON”) has been developed, which consists of a conventional KFM combined with a time-independent neurone-driven control: Each neurone is imbedded in a dynamic performance potential control system, which had been developed for analysis and control of physiological adaptation processes in sport. Two main advantages of DYCON are: Its learning efficiency is very high. In practice, it needs only some hundred data to coin a pattern, where a conventional KFM normally needs about 10.000 to 20.000. Moreover, it can learn continuously and so can recognise and analyse time depending pattern changes. So, DYCON can support the study of processes in sport games in an easier and more efficient way. Moreover, it can help to analyse tactical changes of a team during a season or even during a tournament, as has been done with squash in co-operation with MCGARRY, University of Fredericton. Finally, in a co-operation with RAAB, University of Heidelberg, we try to find out if and how DYCON can be used for analysis and optimisation of training processes in sport.
Two endothelin 1 effectors, hand2 and bapx1, pattern ventral pharyngeal cartilage and the jaw joint

A conserved endothelin 1 signaling pathway patterns the jaw and other pharyngeal skeletal elements in mice, chicks and zebrafish. In zebrafish, endothelin 1 (edn1 or sucker) is required for formation of ventral cartilages and joints in the anterior pharyngeal arches of young larvae. Here we present genetic analyses in the zebrafish of two edn1 downstream targets, the bHLH transcription factor Hand2 and the homeobox transcription factor Bapx1, that mediate dorsoventral (DV) patterning in the anterior pharyngeal arches. First we show that edn1-expressing cells in the first (mandibular) and second (hyoid) pharyngeal arch primordia are located most ventrally and surrounded by hand2-expressing cells. Next we show that along the DV axis of the early first arch primordia, bapx1 is expressed in an intermediate domain, which later marks the jaw joint, and this expression requires edn1 function. bapx1 function is required for formation of the jaw joint, the joint-associated retroarticular process of Meckel's cartilage, and the retroarticular bone. Jaw joint expression of chd and gdf5 also requires bapx1 function. Similar to edn1, hand2 is required for ventral pharyngeal cartilage formation. However, the early ventral arch edn1-dependent expression of five genes (dlx3, EphA3, gsc, msxe and msxb) are all present in hand2 mutants. Further, msxe and msxb are upregulated in hand2 mutant ventral arches. Slightly later, an edn1-dependent ventral first arch expression domain of gsc is absent in hand2 mutants, providing a common downstream target of edn1 and hand2. In hand2 mutants, bapx1 expression is present at the joint region, and expanded ventrally. In addition, expression of eng2, normally restricted to first arch dorsal mesoderm, expands ventrally in hand2 and edn1 mutants. Thus, ventral pharyngeal specification involves repression of dorsal and intermediate (joint region) fates. Together our results reveal two critical edn1 effectors that pattern the vertebrate jaw: hand2 specifies ventral pharyngeal cartilage of the lower jaw and bapx1 specifies the jaw joint.