Miracle-dz/UniFAR-FTUs huggingface dataset:
KNOWLEDGE SHARING IN AN ORGANIZATION FROM THE PERSPECTIVE OF THE INDIVIDUAL

Authors introduce a theoretical model of knowledge sharing in an organization through individual perspective. The social exchange theory offers a clarification of fundamental assumptions regarding individual action and is therefore appropriate for explaining why and when an individual is ready to share her/his knowledge in an organization. The article aims to reveal what shapes employees’ decisions to share knowledge in a work situation and what is needed in an organization to facilitate individuals to share and not to hoard their knowledge. These assumptions have never been included in the literature of knowledge management up until now.
Carcass Characteristics and Meat Quality of Swamp Buffaloes (Bubalus bubalis) Fattened at Different Feeding Intensities

Twenty-four male 1-year old swamp buffaloes (Bubalus bubalis) were randomly allocated to 4 groups. One group grazed on guinea grass (GG) and another on guinea grass and the legume Stylosanthes guianensis (GL). The other two groups were kept in pens and fed freshly cut guinea grass and concentrate at an amount of 1.5% (GC1.5) and 2.0% (GC2.0) of body weight, respectively. The effect of the different feeding intensities on carcass characteristics and meat quality were assessed. The mean body weight at slaughter was 398 (±16) kg. Average daily gain was higher in concentrate-supplemented groups (570 and 540 g/d in GC1.5 and GC2.0, respectively) when compared to GG (316 g/d) and GL (354 g/d) (p<0.01). Likewise, the warm carcass weight was higher in GC1.5 and GC2.0 compared to GG and GL. Dressing percentage was 48.1% and 49.5% in GC1.5 and GC2.0 in comparison to 42.9% and 44.8% observed in GG and GL, respectively. Meat of Longissimus throracis from GC1.5 and GC2.0 was redder in color (p<0.01), while water holding capacity (drip and thawing loss) was improved in pasture-fed groups (p<0.05). Protein and fat content of Longissimus thoracis was higher in animals supplemented with concentrate (p<0.01), as was cholesterol content (p<0.05), whereas PUFA:SFA ratio was higher and n-6/n-3 ratio lower (p<0.01) in pasture-fed buffaloes. Results of the present study showed that the supplementation of pasture with concentrate enhances the growth and carcass characteristics of swamp buffaloes expressed in superior dressing percentage, better muscling, and redder meat with a higher content of protein and fat, whereas animals grazing only on pasture had a more favorable fatty acid profile and water holding capacity. In conclusion, the supplementation of concentrate at a rate of about 1.5% of body weight is recommended to improve the performance and carcass quality of buffaloes.
Sport in the underlife of a total institution: Social control and resistance in Canadian prisons

While it is clear from a small body of scholarly literature that sport and physical activity play important roles in the daily lives of many inmates in diverse prison contexts around the world, there remains relatively little research that sociologically explores the significance of these physical practices in correctional environments. This paper helps to address this gap by examining one of the key tensions in prison sport: its deployment by corrections policymakers and administrators as a form of social control and its simultaneous use by prisoners as a vehicle for resistance and subversion. Situating the research in Goffman’s concept of the total institution, the paper explores how prisoners, though stripped of many resources for self presentation and collective subversion, refashion sport activities, materials, and spaces to their own purposes – and, in doing so, how they resist, in a limited fashion, the prison’s social control aims. More broadly, these findings point to the potential social significance of sport and physical activity as vehicles for the limited expression of agency in situations of extreme deprivation or imposing disciplinary regimes.
Acuity of Sound Localisation: A Topography of Auditory Space. I. Normal Hearing Conditions

Eight subjects were required to localise a sound source (white noise through a speaker) which varied in position on both sides of the head over a range of elevations (-40° to +40°) and azimuths (0° to 180°) at 10° intervals. The perceived position of the source was indicated by pointing a special gun. Depression of the trigger activated a photographic system which recorded two views of the subject, the sound source, and the gun. The absolute and algebraic, azimuth and elevation errors were measured for all subjects at each position of the source. The variability of azimuth and elevation error was also computed. In a second experiment, four of the same subjects performed the same task but in this case visually located the sources. This experiment provided an estimate of inherent motor error in the pointing task. No differences in localisation acuity between sides were found, but there were significant differences between front and back regions. Azimuth and elevation error were well matched and low in the front. However, azimuth error increased in the regions behind the head, particularly for azimuth positions 120° to 160°. Larger increases were found for positions in the upper elevations of this region. Elevation error also increased in the upper elevations behind the head. A comparison of the auditory and visual data indicates that this pattern of error is not due to motor factors. The results are discussed in relation to the structural characteristics of the pinnae and modifications that they impose on incoming sound energy.
Detecting robot-directed speech by situated understanding in object manipulation tasks

In this paper, we propose a novel method for a robot to detect robot-directed speech, that is, to distinguish speech that users speak to a robot from speech that users speak to other people or to themselves. The originality of this work is the introduction of a multimodal semantic confidence (MSC) measure, which is used for domain classification of input speech based on the decision on whether the speech can be interpreted as a feasible action under the current physical situation in an object manipulation task. This measure is calculated by integrating speech, object, and motion confidence with weightings that are optimized by logistic regression. Then we integrate this measure with gaze tracking and conduct experiments under conditions of natural human-robot interaction. Experimental results show that the proposed method achieves a high performance of 94% and 96% in average recall and precision rates, respectively, for robot-directed speech detection.
Channel Training for MIMO Relay Systems in the Presence of Interference

In this paper, we propose an optimal channel training method in the sense of linear minimum mean square error for multiple-input multiple-output amplify-and-forward relay systems in the presence of interference. By using a relay processing matrix, the received interference is cancelled or mitigated. To make the problem tractable, we first derive the optimal structure of the training signal and the relay processing matrix. Then, we propose an optimal channel training method. In order to reduce the complexity, we also propose an asymptotically optimal channel training method. Simulation results demonstrate that the two proposed methods outperform the conventional training signal design methods in terms of both the mean square error and in the bit error rate.
Active Learning on Trees and Graphs

We investigate the problem of active learning on a given tree whose nodes are assigned binary labels in an adversarial way. Inspired by recent results by Guillory and Bilmes, we characterize (up to constant factors) the optimal placement of queries so to minimize the mistakes made on the non-queried nodes. Our query selection algorithm is extremely efficient, and the optimal number of mistakes on the non-queried nodes is achieved by a simple and efficient mincut classifier. Through a simple modification of the query selection algorithm we also show optimality (up to constant factors) with respect to the trad e-off between number of queries and number of mistakes on non-queried nodes. By using spanning trees, our algorithms can be efficiently applied to general graphs, although the problem of finding optimal and efficient active learning algorithms for general graphs remains open. Towards this end, we provide a lower bound on the number of mistakes made on arbitrary graphs by any active learning algorithm using a number of queries which is up to a constant fraction of the graph size.
Strains and Strategies for Large-Scale Gene Deletion Studies of the Diploid Human Fungal Pathogen Candida albicans

ABSTRACT Candida albicans is the most common human fungal pathogen and causes significant morbidity and mortality worldwide. Nevertheless, the basic principles of C. albicans pathogenesis remain poorly understood. Of central importance to the study of this organism is the ability to generate homozygous knockout mutants and to analyze them in a mammalian model of pathogenesis. C. albicans is diploid, and current strategies for gene deletion typically involve repeated use of the URA3 selectable marker. These procedures are often time-consuming and inefficient. Moreover, URA3 expression levels—which are susceptible to chromosome position effects—can themselves affect virulence, thereby complicating analysis of strains constructed with URA3 as a selectable marker. Here, we describe a set of newly developed reference strains (leu2Δ/leu2Δ, his1Δ/his1Δ; arg4Δ/arg4Δ, his1Δ/his1Δ; and arg4Δ/arg4Δ, leu2Δ/leu2Δ, his1Δ/his1Δ) that exhibit wild-type or nearly wild-type virulence in a mouse model. We also describe new disruption marker cassettes and a fusion PCR protocol that permit rapid and highly efficient generation of homozygous knockout mutations in the new C. albicans strains. We demonstrate these procedures for two well-studied genes, TUP1 and EFG1, as well as a novel gene, RBD1. These tools should permit large-scale genetic analysis of this important human pathogen.
Interaction of Fatty Acid Genotype and Diet on Changes in Colonic Fatty Acids in a Mediterranean Diet Intervention Study

A Mediterranean diet increases intakes of n-3 and n-9 fatty acids and lowers intake of n-6 fatty acids. This can impact colon cancer risk as n-6 fatty acids are metabolized to proinflammatory eicosanoids. The purpose of this study was to evaluate interactions of polymorphisms in the fatty acid desaturase (FADS) genes, FADS1 and FADS2, and changes in diet on fatty acid concentrations in serum and colon. A total of 108 individuals at increased risk of colon cancer were randomized to either a Mediterranean or a Healthy Eating diet. Fatty acids were measured in both serum and colonic mucosa at baseline and after six months. Each individual was genotyped for four single-nucleotide polymorphisms in the FADS gene cluster. Linear regression was used to evaluate the effects of diet, genotype, and the diet by genotype interaction on fatty acid concentrations in serum and colon. Genetic variation in the FADS genes was strongly associated with baseline serum arachidonic acid (n-6) but serum eicosapentaenoic acid (n-3) and colonic fatty acid concentrations were not significantly associated with genotype. After intervention, there was a significant diet by genotype interaction for arachidonic acid concentrations in colon. Subjects who had all major alleles for FADS1/2 and were following a Mediterranean diet had 16% lower arachidonic acid concentrations in the colon after six months of intervention than subjects following the Healthy Eating diet. These results indicate that FADS genotype could modify the effects of changes in dietary fat intakes on arachidonic acid concentrations in the colon. Cancer Prev Res; 6(11); 1212–21. ©2013 AACR.
Extracellular group A Streptococcus induces keratinocyte apoptosis by dysregulating calcium signalling

Group A Streptococcus (GAS) colonizes the oropharynx and damaged skin. To cause local infection or severe invasive syndromes the bacteria must gain access into deeper tissues. Host cell death may facilitate this process. GAS internalization has been identified to induce apoptosis. We now report an alternate mechanism of GAS‐mediated apoptosis of primary human keratinocytes, initiated by extracellular GAS and involving dysregulation of intracellular calcium to produce endoplasmic reticulum stress. Two bacterial virulence factors are required for effective induction of apoptosis by extracellular GAS: (i) hyaluronic acid capsule that inhibits bacterial internalization and (ii) secreted cytolysin, streptolysin O (SLO), that forms transmembrane pores that permit extracellular calcium influx into the cytosol. Induction of keratinocyte apoptosis by wild‐type GAS was accompanied by cell detachment and loss of epithelial integrity, a phenomenon not observed with GAS deficient in capsule or SLO. We propose that cell signalling initiated by extracellular GAS compromises the epithelial barrier by inducing premature keratinocyte differentiation and apoptosis, thereby facilitating GAS invasion of deeper tissues.
THE SOROKIN MULTIDIMENSIONAL INVENTORY OF LOVE EXPERIENCE (SMILE): DEVELOPMENT, VALIDATION, AND RELIGIOUS DETERMINANTS*

This paper describes the development and validation of the Sorokin Multidimensional Inventory of Love Experience (SMILE), a 24-item scale based on the writing of soci ologist Pitirim Sorokin. The SMILE contains six subscales of four items each, corre sponding to what Sorokin termed the religious, ethical, ontological, biological, psychological, and social domains of love. Through confirmatory factor analysis, all factor loadings were found to be strong and statistically significant. A model speci fying intercorrelations among all subscales exhibited good overall fit, although bio logical love was only weakly related to the other factors. Finally, through hierarchical OLS regression, religious measures were found to be significant determinants ofscores on five of six subscales. This confirms Sorokin s hypothesis that affirming the expe rience of love is in part a function of religiousness. The SMILE promises to broaden the scope of social research on love and to promote investigation of this neglected psychosocial construct.
Using neutral speech models for emotional speech analysis

Abstract Since emotional speech can be regarded as a variation onneutral (non-emotional) speech, it is expected that a robust neu-tral speech model can be useful in contrasting different emo-tions expressed in speech. This study explores this idea by cre-ating acoustic models trained with spectral features, using theemotionally-neutral TIMIT corpus. The performance is testedwith two emotional speech databases: one recorded with a mi-crophone (acted), and another recorded from a telephone ap-plication (spontaneous). It is found that accuracy up to 78%and 65% can be achieved in the binary and category emotiondiscriminations, respectively. Raw Mel Filter Bank (MFB) out-put was found to perform better than conventional MFCC, withboth broad-band and telephone-band speech. These results sug-gest that well-trained neutral acoustic models can be effectivelyused as a front-end for emotion recognition, and once trainedwith MFB, it may reasonably work well regardless of the chan-nel characteristics.Index Terms: Emotion recognition, Neutral speech, HMMs,Mel ﬁlter bank (MFB), TIMIT
Blocking Universal Constructions

In this paper, we present two new blocking universal constructions. The first one, called CC-BSim, is very efficient in systems that support coherent caches (CC), while the second one, called DSM-BSim, is more efficient in cache-less NUMA machines (where processors do not have caches). CC-BSim performs at most O(h + t) remote memory references (RMR), where h is an upper bound on the number of operations that a process may help, and t is the size of the part of the object’s state that it should be accessed in order to execute these h operations. DSM-BSim performs at most O(hw) RMR, where w is the number of memory words accessed by the sequential version of an operation applied on a sequential data structure. DSM-BSim is better suited in a distributed shared memory (DSM) model. Algorithm CC-BSim uses just one Swap object in addition to read-write registers, thus exhibiting a performance advantage in machines that support Swap objects. On the other hand, DSM-BSim uses CAS, Swap, and read-write registers. Our experiments show that CC-BSim and DSM-BSim outperform state-of-the-art synchronization techniques, like Sim (SPAA 2001), flat-combining (SPAA 2010), and others. We also present and experimentally analyze common shared data structures (like shared stacks and queues) based on CC-BSim and DSM-BSim. Our experiments show that these implementations have very good performance in practice.
Giuliani Time: The Revanchist 1990s

When he was reelected to his second mayoral term in November 1997, Neil Smith New York's Rudy Giuliani stood before the television cameras on election night and, Nixonesque, his arms making a V in the air, exalted, "I am the king of the world! " By the following spring, however, it was not royalty but a fascist dictator to which Giuliani was being openly compared. Jokes about Benito Giuliani swept through city streets and tabloid newsprint faster than fires through Florida. The governor's office joined in. Even the congenitally sober New York Times asked on the front page of its Metro section whether Giuliani was the "Mussolini of Manhattan. "' Little Hitler
Testing Hypotheses with Induction Trees

Les arbres d'induction sont largement utilises en data mining tant dans un but exploratoire que comme outil de classification supervisee. Rares sont cependant les outils inferentiels disponibles pour valider statistiquement la description fournie par un arbre induit. Nous proposons ici une astuce qui permet d'appliquer aux arbres les outils inferentiels utilises par exemple en modelisation log-lineaire de tables de contingence multidimensionnelles. Parmi ces outils, la deviance se prete en particulier a divers test sur la structure de l'arbre induit. De la statistique de vraisemblance, on deduit egalement les criteres d'information AIC et BIC qui permettent d'arbitrer entre la complexite et la qualite d'ajustement d'arbres non emboites. Ces outils inferentiels pour arbres d'induction sont particulierement apprecies par les chercheurs de sciences sociales qui s'interessent en priorite a comprendre comment les facteurs explicatifs interagissent sur la variable reponse, et ne sont donc guere concernes par le taux d'erreur de classification habituellement utilise pour juger de la qualite des arbres. La possibilite de tester des hypotheses sur la structure de l'arbre contribue a la connaissance du phenomene etudie. Elle constitue une illustration de ce que le raisonnement statistique traditionnel peut apporter au data mining.
Proteomics: the move to mixtures.

Proteomics can be defined as the systematic analysis of proteins for their identity, quantity and function. In contrast to a cell's static genome, the proteome is both complex and dynamic. Proteome analysis is most commonly accomplished by the combination of two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS). However, this technique is under scrutiny because of a failure to detect low-abundance proteins from the analysis of whole cell lysates. Alternative approaches integrate a diversity of separation technologies and make use of the tremendous peptide separation and sequencing power provided by MS/MS. When liquid chromatography is combined with tandem mass spectrometry (LC/MS/MS) and applied to the direct analysis of mixtures, many of the limitations of 2DE for proteome analysis can be overcome. This tutorial addresses current approaches to identify and characterize large numbers of proteins and measure dynamic changes in protein expression directly from complex protein mixtures (total cell lysates).
Binary Data Matrix Model for Document Clustering

This paper presents new approach, Binary Data matrix Model for Document Clustering. The proposed Binary Data matrix Model approach is based on rows and columns of the data matrix with Similarity and Dissimilarity. In this paper we have used Similarity and Dissimilarity from Binary Data matrix Model . The steps, Document collection, Text Pre-processing, Feature Selection, Indexing, Clustering Process and Results Analysis are used. Twenty News group data sets are used in the Experiments. The experimental results are evaluated using the Analytical SAS 9.0 Software. The experimental results show the proposed approach better performs. Keywords— Binary Data matrix, Data set, Clustering, Similarity and Dissimilarity.
Teaching hand-washing with pictorial cues

Applied behavior analysis has been shown to be an effective means to teach daily living skills to individuals with intellectual disability. In the present study pictorial cues based on task analysis, system of least prompts, and social reinforcement were used to teach a man with mild intellectual disability to wash his hands correctly. An ABAB reversal design was used with follow-up after two weeks. The results show a rapid increase in hand-washing skills.
CHICKEN BROTH FLAVOR AND PH.

Abstract INTRODUCTION BOUTHILET (1949) found that a pH range of 1 to 5.8 favored development of strong chicken flavor and attributed the effect to a volatile, unidentified, and acidic constituent. Peterson (1957) found that several flavor and odor characteristics of chicken broth were affected unfavorably when the pH was changed from 6.4 to 8.7. Kazeniac (1961) determined that the quantities of ammonia, sulfide, and diacetyl produced by chicken dark meat increased over the pH range 5 to 8, but did not relate these results to chicken flavor. Brant and Hanson (1962), using the triangle test, observed that the percent correct judgments increased as the pH difference between chicken broth samples became greater and found that judges associated more intense flavor with lower pH values. The objectives of this study were to determine if pH differences during cooking or after cooking cause flavor differences in chicken broth. A pH value that differed…