Analisis Hubungan Pengungkapan Corporate Social Responsibilitydengan Kinerja Keuangan Pada Perusahaan Pertambangan Yang Terdaftar Di Bursa Efek Indonesia

The purpose of this research is determine the quality of Corporate Social Responsibility disclosure on the Mining Company's through annual report, and analyze the relationship between social disclosure and financial performance on Mining Companies that are listed on Indonesia Stock Exchange. The sample in this research consist of 11 companies listed in Indonesia Stock Exchange in 2006, 2007, and 2008 period. Purposively used in this research. This research measures the variable of Corporate Social Responsibility by using a list of 79 items checklist issued by the Global Reporting Initiative (GRI) Guidelines, which is divided into 6 categories, there were Economy, Environtment, Human rights, Employee behavior, Responsibility of the product and Community. The result of this research indicates that Corporate Social Responsibility have positive relation with ROA and ROE company. This condition indicates company that have good finance performance, then disclosure of corporate social responsibilty will be wide, and company that wide disclosure of corporate social responsibility then company's finance performance will be good

Income, personality, and subjective financial well-being: the role of gender in their genetic and environmental relationships

Citation: Zyphur, M. J., Li, W. D., Zhang, Z., Arvey, R. D., & Barsky, A. P. (2015). Income, personality, and subjective financial well-being: the role of gender in their genetic and environmental relationships. Frontiers in Psychology, 6, 16. doi:10.3389/fpsyg.2015.01493Increasing levels of financial inequality prompt questions about the relationship between income and well-being. Using a twins sample from the Survey of Midlife Development in the U. S. and controlling for personality as core self-evaluations (CSE), we found that men, but not women, had higher subjective financial well-being (SFWB) when they had higher incomes. This relationship was due to 'unshared environmental' factors rather than genes, suggesting that the effect of income on SFWB is driven by unique experiences among men. Further, for women and men, we found that CSE influenced income and SFWB, and that both genetic and environmental factors explained this relationship. Given the relatively small and male-specific relationship between income and SFWB, and the determination of both income and SFWB by personality, we propose that policy makers focus on malleable factors beyond merely income in order to increase SFWB, including financial education and building self-regulatory capacity

Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs

Non-conding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting e.g. the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.Comment: review article, 29 pages, 7 figure

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors

The Sample Analysis at Mars Investigation and Instrument Suite

The Sample Analysis at Mars (SAM) investigation of the Mars Science Laboratory(MSL) addresses the chemical and isotopic composition of the atmosphere and volatilesextracted from solid samples. The SAM investigation is designed to contribute substantiallyto the mission goal of quantitatively assessing the habitability of Mars as an essentialstep in the search for past or present life on Mars. SAM is a 40 kg instrument suite locatedin the interior of MSLs Curiosity rover. The SAM instruments are a quadrupole massspectrometer, a tunable laser spectrometer, and a 6-column gas chromatograph all coupledthrough solid and gas processing systems to provide complementary information on thesame samples. The SAM suite is able to measure a suite of light isotopes and to analyzevolatiles directly from the atmosphere or thermally released from solid samples. In additionto measurements of simple inorganic compounds and noble gases SAM will conducta sensitive search for organic compounds with either thermal or chemical extraction fromsieved samples delivered by the sample processing system on the Curiosity rovers roboticarm

Technology and Discourse: A Comparison of Face-to-face and Telephone Employment Interviews

Very little research has investigated the comparability of telephone and face-to-face employment interviews. This exploratory study investigated interviewers' questioning strategies and applicants' causal attributions produced during semi structured telephone and face-to-face graduate recruitment interviews (N=62). A total of 2044 causal attributions were extracted from verbatim transcripts of these 62 interviews. It was predicted that an absence of visual cues would lead applicants to produce, and interviewers to focus on, information that might reduce the comparative anonymity of telephone interviews. Results indicate that applicants produce more personal causal attributions in telephone interviews. Personal attributions are also associated with higher ratings in telephone, but not face-to-face interviews. In face-to-face interviews, applicants who attributed outcomes to more global causes received lower ratings. There was also a non-significant tendency for interviewers to ask more closed questions in telephone interviews. The implications of these findings for research and practice are discussed

MicroRNAs can generate thresholds in target gene expression

MicroRNAs (miRNAs) are short, highly conserved noncoding RNA molecules that repress gene expression in a sequence-dependent manner. We performed single-cell measurements using quantitative fluorescence microscopy and flow cytometry to monitor a target gene's protein expression in the presence and absence of regulation by miRNA. We find that although the average level of repression is modest, in agreement with previous population-based measurements, the repression among individual cells varies dramatically. In particular, we show that regulation by miRNAs establishes a threshold level of target mRNA below which protein production is highly repressed. Near this threshold, protein expression responds sensitively to target mRNA input, consistent with a mathematical model of molecular titration. These results show that miRNAs can act both as a switch and as a fine-tuner of gene expression.National Institutes of Health (U.S.). Director's Pioneer Award (1DP1OD003936)National Cancer Institute (U.S.). Physical Sciences-Oncology Center (U54CA143874)United States. Public Health Service (Grant R01-CA133404)United States. Public Health Service (Grant R01-GM34277)National Cancer Institute (U.S.) (PO1-CA42063)National Cancer Institute (U.S.) Cancer Center Support (Grant P30-CA14051)Howard Hughes Medical Institute. Predoctoral FellowshipCleo and Paul Schimmel Foundation. FellowshipNatural Sciences and Engineering Research Council of Canada PGS Scholarshi

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant 0645960)National Institutes of Health (U.S.) (grant P01 NS055923)Pennsylvania State University. Center for Eukaryotic Gene Regulatio

Integrating Diverse Datasets Improves Developmental Enhancer Prediction

Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology. © 2014 Erwin et al

Why Do Situational Interviews Predict Performance? Is it Saying How You Would Behave or Knowing How You Should Behave?

Purpose: The present study examined two theoretical explanations for why situational interviews predict work-related performance, namely (a) that they are measures of interviewees’ behavioral intentions or (b) that they are measures of interviewees’ ability to correctly decipher situational demands. Design/Methodology/Approach: We tested these explanations with 101 students, who participated in a 2-day selection simulation. Findings: In line with the first explanation, there was considerable similarity between what participants said they would do and their actual behavior in corresponding work-related situations. However, the underlying postulated mechanism was not supported by the data. In line with the second explanation, participants’ ability to correctly decipher situational demands was related to performance in both the interview and work-related situations. Furthermore, the relationship between the interview and performance in the work-related situations was partially explained by this ability to decipher situational demands. Implications: Assessing interviewees’ ability to identify criteria might be of additional value for making selection decisions, particularly for jobs where it is essential to assess situational demands. Originality/Value: The present study made an effort to open the ‘black box’ of situational interview validity by examining two explanations for their validity. The results provided only moderate support for the first explanation. However, the second explanation was fully supported by these results