nils-herrmann/clean_scirepeval huggingface dataset:
Isolation and characterization of exopolysaccharide from Leuconostoc lactis KC117496 isolated from idli batter.
Venue: International journal of biological macromolecules

Diverse exopolysaccharide (EPS) producing isolates were isolated from an Indian acidic fermented food (Idli) based on the colony morphology. One of the EPS producing microflora (Leuconostoc lactis KC117496) was selected for further characterization using FT IR, HPTLC, AFM, SEM, TGA and XRD analysis. FT IR spectroscopy revealed the a d glucose nature of the EPS. HPTLC analysis confirmed the presence of only glucose monomers, indicating the glucan nature of EPS. NMR spectra revealed the presence of 95% a (1 6) and 5% branching a (1 3) linkages. The SEM and AFM showed smooth surfaces and compact structure. TGA results showed higher degradation temperature of 272.01degC. XRD analysis proved the 33.4% crystalline nature of the EPS. Water solubility index and water holding capacity of EPS are 14.2+ 0.208% and 117+ 7.5% All the above characteristics of the EPS produced by L. lactis showed that the EPS is of a good quality polysaccharide with potential applications in the food industry.
A meta analysis of blood cytokine network alterations in psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression
Venue: Molecular Psychiatry

Schizophrenia, bipolar disorder and major depressive disorder (MDD) have all been associated with aberrant blood cytokine levels; however, neither the pattern of cytokine alterations nor the impact of clinical status have been compared across disorders. We performed a meta analysis of blood cytokines in acutely and chronically ill patients with these major psychiatric disorders. Articles were identified by searching the PubMed, PsycInfo and Web of Science, and the reference lists of these studies. Sixty eight studies met the inclusion criteria (40 schizophrenia, 10 bipolar disorder and 18 MDD) for acutely ill patients. Forty six studies met the inclusion criteria (18 schizophrenia, 16 bipolar disorder and 12 MDD) for chronically ill patients. Levels of two cytokines (interleukin 6 (IL 6) tumor necrosis factor a (TNF a) one soluble cytokine receptor (sIL 2R) and one cytokine receptor antagonist (IL 1RA) were significantly increased in acutely ill patients with schizophrenia, bipolar mania and MDD compared with controls (P<0.01) Following treatment of the acute illness, IL 6 levels significantly decreased in both schizophrenia and MDD (P<0.01) sIL 2R levels increased in schizophrenia; and IL 1RA levels in bipolar mania decreased. In chronically ill patients, the levels of IL 6 were significantly increased in schizophrenia, euthymic (but not depressed) bipolar disorder and MDD compared with controls (P<0.01) The levels of IL 1b and sIL 2R were significantly increased in both chronic schizophrenia and euthymic bipolar disorder. Overall, there were similarities in the pattern of cytokine alterations in schizophrenia, bipolar disorder and MDD during acute and chronic phases of illness, raising the possibility of common underlying pathways for immune dysfunction. Effects of treatment on cytokines were more robust for schizophrenia and MDD, but were more frequently studied than for acute mania. These findings have important implications for our understanding of the pathophysiology and treatment of major psychiatric disorders.
Voxel Based Meta Analytical Evidence of Structural Disconnectivity in Major Depression and Bipolar Disorder
Venue: Biological Psychiatry

Identification of white matter microstructure differences and similarities between major depression and bipolar disorder is a necessary step to better understand the underlying brain abnormalities in affective disorders and target more effective treatments. However, research has not yet yielded robust conclusions. We report here a meta analysis of diffusion tensor imaging studies in these conditions.  A comprehensive literature search was conducted up to 2014 to identify studies comparing fractional anisotropy (FA) between patients and control subjects. Results were combined to identify white matter abnormalities in major depression (736 patients vs. 668 control subjects) and bipolar disorder (536 patients vs. 489 control subjects) Effect size comparison and conjunction analysis allowed identification of similarities and differences between the disorders.  A significant decrease in FA in the genu of the corpus callosum characterized both conditions. The comparison between unipolar and bipolar disorders revealed a greater decrease in FA in the left posterior cingulum in bipolar disorder. Studies that adopted tract based spatial statistics methodology showed more pronounced reductions in these regions compared with voxel based analyses.  Major depression and bipolar disorder are characterized by abnormalities in white matter tracts of the genu of the corpus callosum that connect the two hemispheres of the prefrontal cortex implicated in mood regulation. Bipolar disorder was associated with reduced white matter integrity in the left posterior cingulum, which may contribute to cognitive impairment described in this condition. Tract based spatial statistics may be a more sensitive technique to detect white matter abnormalities in these regions compared with voxel based analyses.
The effect of perceived school climate and teacher efficacy in behavior management on job satisfaction and burnout: A longitudinal study

This study investigated how perceived school climate affects teachers' job satisfaction and burnout and how self efficacy and collective efficacy in behavior management mediate the effect of perceived school climate on job satisfaction and burnout. The questions were answered using longitudinal questionnaire data collected from 642 Finnish lower secondary school teachers. A structural equation model revealed that school climate had a positive effect, partly mediated by self efficacy, on job satisfaction. Collective efficacy in student discipline did not explain either job satisfaction or burnout. Self efficacy in managing behavior had a positive effect on job satisfaction and a negative effect on burnout.
Job Satisfaction and Burnout in Teachers: The Importance of Perceived Support from Principal and Work Motivation

The starting point of this study was the assumption that work in a supportive working environment increases work motivation and thus contributes to job satisfaction and in preventing burnout. The main objective of the study was to examine the role of perceived support from the principal and work motivation (work engagement and self efficacy) in explaining job satisfaction and burnout in Croatian primary school teachers. The study included a total of 1,892 primary school teachers, working in lower (class teachers, N 856) and higher grades (subject teachers, N 1036) employed in 101 primary schools in the Republic of Croatia. Male teachers comprised 12% of the total sample. The average age of participants was 41.7 years (SD 10.2) and length of service was 15.7 years (SD 10.7) The results of hierarchical regression analyses showed that the perceived support from principals and used measures of work motivation significantly contributed to the explanation of job satisfaction and two measures of burnout (emotional exhaustion and alienation) while the demographic variables used explained the small percentage of criterion measures' variance. In conclusion, support from the principal, as well as self efficiency and work engagement of teachers, has an important role in the prevention of job dissatisfaction and burnout in teachers.
More gyms or more psychological support? Preventing burnout and supporting job satisfaction in physical education teachers
Venue: Sport Sciences for Health

PurposeTeachers' burnout affects the learning process and students' achievement and reduces job satisfaction. Physical education (PE) teachers represent a group at greater risk of burnout, in whom psychological and environmental aspects, such as not having appropriate school equipment and facilities, can represent risk factors. This cross sectional study aimed to analyse the direct and the mediated effects of a range of psychological and environmental aspects as determinants of burnout and job satisfaction in PE teachers.MethodsOne hundred and eighty three PE teachers participated in the study. They filled out a booklet of questionnaires to assess self efficacy, enjoyment of physical activity, job satisfaction, burnout, mastery and performance goals, and the perceived quality of school facilities.ResultsCorrelation analyses showed negative relationships between burnout dimensions and job satisfaction. Burnout mediated the relationships between mastery goals, self efficacy, enjoyment, and job satisfaction, while the perceived quality of school facilities had just a direct effect on burnout.ConclusionsTo increase job satisfaction and decrease burnout in PE teachers it seems more effective to act mainly on psychological factors rather than on providing better facilities.
A Systematic Review of Function Based Replacement Behavior Interventions for Students With and At Risk for Emotional and Behavioral Disorders
Venue: Behavior modification

Students with emotional and behavioral disorders and students considered at risk often have social deficits. Although social skills interventions are often provided to this student population, there are some concerns regarding how these interventions are conceived and provided. One possible way to improve the effectiveness of social skills interventions is to use functional behavior assessment data to tailor the interventions to a student's individual needs and the contexts in which social skills deficits and problem behaviors occur. This approach is commonly referred to as replacement behavior training. In this study, the literature on function based replacement behavior interventions is systematically reviewed. In addition, studies are evaluated according to the What Works Clearinghouse design and evidence standards for single case research. Although this research base does not meet the What Works Clearinghouse replication standards, function based replacement behavior interventions appear to be a promising practice for addressing problem behaviors. Implications for practice, areas for future research, and study limitations are discussed.
Small Business Valuation with Use of Cash Flow Stochastic Modeling
Venue: 2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)

Enterprise can be described with vector of financial characteristics e.g. revenue, net profit, net working capital, depreciation, debt etc. Vector evolution can be modeled with use of system of recurrent equations. These equations can be combined in three groups: equations of the income statement, equations of sources and uses of funds and balance equations. System parameters can be obtained using financial performance analysis. Cash flow can be calculated using vector components. Discounted cash flow method is used for business valuation. In real systems there is an uncertainty in all parameters. This uncertainty can be modeled utilizing stochastic approach. Monte Carlo simulation can be adopted to forecast cash flow distribution and to predict the risks caused by uncertainty. We show that once simulation model is set up, it is a simple matter to analyze the principal sources of uncertainty in the cash flows and to see how much this uncertainty could be reduced by improving the forecasts of sales or costs. Practical realization of this approach is discussed in the paper. Finally, we demonstrate how changes in model parameters influence cash flows.
Bank Specific and Macroeconomic Variables Affecting Non Performing Loans of Nepalese Commercial Banks

This study examines the effect of firm specific and macroeconomic variables on non performing loans of Nepalese commercial banks. The study is based on the panel data analysis of 21 Nepalese commercial banks with 147 observations for the period of 2008 to 2014. As a first approximation to the theory, this study hypothesizes that the non performing loans depend on several bank specific and microeconomic variables such as return on asset, return on equity, loans to total deposit, capital adequacy ratio, inflation, gross domestic product and annual money supply growth. The multiple regression models are estimated to test the significance of non performing loans in Nepalese commercial banks.The result shows that return on asset has a positive and significant relationship with non performing loans. It implies that increase in return on assets, increases the non performing loans. Similarly, loans to total deposit ratio also has a positive and significant impact on non performing loans which means that increase in loans to total deposit would increase the non performing loans. Likewise, return on equity has negatively significant influence on non performing loans. Thus, the result indicates that lower the non performing loans, higher would be the return on equity. Hence, the overall study concludes that return on asset, return on equity and loans to total deposit ratio are major determinants of non performing loans in Nepalese commercial banks.
Wikken en wegen in het hoger onderwijs

Er zijn in het Nederlandse onderwijs verschillende routes naar het hoger onderwijs. Het hbo is niet alleen toegankelijk via de havo, maar ook via het mbo. Universitaire opleidingen zijn ook zonder vwo diploma toegankelijk via het hbo. In het hoger onderwijs verloopt de studieloopbaan echter niet altijd voorspoedig. Een aanzienlijk aantal studenten komt terug op de aanvankelijke studiekeuze door over te stappen naar een andere opleiding. Daarnaast is er een flinke groep studenten die zonder diploma uit het hoger onderwijs vertrekt. De afgelopen jaren heeft de overheid maatregelen genomen om een passende studiekeuze en studiesucces in het hoger onderwijs te bevorderen. In dit onderzoek is het gebruik van verschillende routes naar het hoger onderwijs in kaart gebracht, evenals de achtergronden van de studenten die deze routes benutten. Ook zijn veranderingen in studieloopbanen en verschillen tussen studenten met uiteenlopende vooropleidingen onderzocht. Daarnaast zijn met vertegenwoordigers van hogescholen en universiteiten gesprekken gevoerd over de wijze waarop deze instellingen invulling geven aan het beleid om studenten op de goede plek te krijgen en studiesucces te bevorderen, en hun ervaringen daarmee.
Do the benefits of chess instruction transfer to academic and cognitive skills? A meta analysis

In recent years, pupils' poor achievement in mathematics has been a concern in many Western countries. Chess instruction has been proposed as one way to remedy this state of affairs, as well as improving other academic topics such as reading and general cognitive abilities such as intelligence. The aim of this paper is to quantitatively evaluate the available empirical evidence that skills acquired during chess instruction in schools positively transfer to mathematics, reading and general cognitive skills. The selection criteria were satisfied by 24 studies (40 effect sizes) with 2788 young people in the chess condition and 2433 in the control groups. The results show (a) a moderate overall effect size (g 0.338) (b) a tendency for a stronger effect on mathematical (g 0.382) than reading skill (g 0.248) and (c) a significant and positive effect of duration of treatment (Q(1) 3.89, b 0.0038, p
A Tutorial on Machine Learning and Data Science Tools with Python
Venue: Machine Learning for Health Informatics

In this tutorial, we will provide an introduction to the main Python software tools used for applying machine learning techniques to medical data. The focus will be on open source software that is freely available and is cross platform. To aid the learning experience, a companion GitHub repository is available so that you can follow the examples contained in this paper interactively using Jupyter notebooks. The notebooks will be more exhaustive than what is contained in this chapter, and will focus on medical datasets and healthcare problems. Briefly, this tutorial will first introduce Python as a language, and then describe some of the lower level, general matrix and data structure packages that are popular in the machine learning and data science communities, such as NumPy and Pandas. From there, we will move to dedicated machine learning software, such as SciKit Learn. Finally we will introduce the Keras deep learning and neural networks library. The emphasis of this paper is readability, with as little jargon used as possible. No previous experience with machine learning is assumed. We will use openly available medical datasets throughout.
Emerging roles of interferon stimulated genes in the innate immune response to hepatitis C virus infection
Venue: Cellular and Molecular Immunology

Infection with hepatitis C virus (HCV) a major viral cause of chronic liver disease, frequently progresses to steatosis and cirrhosis, which can lead to hepatocellular carcinoma. HCV infection strongly induces host responses, such as the activation of the unfolded protein response, autophagy and the innate immune response. Upon HCV infection, the host induces the interferon (IFN) mediated frontline defense to limit virus replication. Conversely, HCV employs diverse strategies to escape host innate immune surveillance. Type I IFN elicits its antiviral actions by inducing a wide array of IFN stimulated genes (ISGs) Nevertheless, the mechanisms by which these ISGs participate in IFN mediated anti HCV actions remain largely unknown. In this review, we first outline the signaling pathways known to be involved in the production of type I IFN and ISGs and the tactics that HCV uses to subvert innate immunity. Then, we summarize the effector mechanisms of scaffold ISGs known to modulate IFN function in HCV replication. We also highlight the potential functions of emerging ISGs, which were identified from genome wide siRNA screens, in HCV replication. Finally, we discuss the functions of several cellular determinants critical for regulating host immunity in HCV replication. This review will provide a basis for understanding the complexity and functionality of the pleiotropic IFN system in HCV infection. Elucidation of the specificity and the mode of action of these emerging ISGs will also help to identify novel cellular targets against which effective HCV therapeutics can be developed.
Does Intellectual Capital Disclosure Matter for Audit Risk? Evidence from the UK and Italy

Disclosure theory argues that better information quality reduces audit risk, by decreasing information asymmetry in the market and consequently, information risk for firms. Extant literature on voluntary disclosure analyzes the relationships between Corporate Social Responsibility (CSR) and audit risk, finding that auditors charge lower fees and issue less going concern opinions to firms with good CSR performance. In this study, we test the relationship between intellectual capital disclosure (ICD) and audit risk and we assess the effect of ICD and audit risk on audit fees. To do so, we use data from the ESG Asset4 database (Thomson Reuters Datastream) on 166 UK and 27 Italian listed firms that issue stand alone social and intellectual capital statements. The audit risk is measured from both a qualitative and a quantitative perspective. Panel data analysis on 2004 2011 years has been used to test our research hypotheses. Empirical findings from a sample of UK and Italian listed companies show that auditors estimate a lower qualitative risk, albeit a higher quantitative one, for those companies reporting higher ICD scores, compared to those ones with lower disclosure scores on the intellectual capital. Furthermore, we find that reputation risk contributes to the relationship between ICD and audit risk.
Providing SCADA Network Data Sets for Intrusion Detection Research
Venue: CSET USENIX Security Symposium

High profile attacks such as Stuxnet and the cyber attack on the Ukrainian power grid have increased research in Industrial Control System (ICS) and Supervisory Control and Data Acquisition (SCADA) network security. However, due to the sensitive nature of these networks, there is little publicly available data for researchers to evaluate the effectiveness of the proposed solution. The lack of representative data sets makes evaluation and independent validation of emerging security solutions difficult and slows down progress towards effective and reusable solutions. This paper presents our work to generate representative labeled data sets for SCADA networks that security researcher can use freely. The data sets include packet captures including both malicious and non malicious Modbus traffic and accompanying CSV files that contain labels to provide the ground truth for supervised machine learning. To provide representative data at the network level, the data sets were generated in a SCADA sandbox, where electrical network simulators were used to introduce realism in the physical component. Also, real attack tools, some of them custom built for Modbus networks, were used to generate the malicious traffic. Even though they do not fully replicate a production network, these data sets represent a good baseline to validate detection tools for SCADA systems.
Query Efficient Imitation Learning for End to End Autonomous Driving
Venue: ArXiv

One way to approach end to end autonomous driving is to learn a policy function that maps from a sensory input, such as an image frame from a front facing camera, to a driving action, by imitating an expert driver, or a reference policy. This can be done by supervised learning, where a policy function is tuned to minimize the difference between the predicted and ground truth actions. A policy function trained in this way however is known to suffer from unexpected behaviours due to the mismatch between the states reachable by the reference policy and trained policy functions. More advanced algorithms for imitation learning, such as DAgger, addresses this issue by iteratively collecting training examples from both reference and trained policies. These algorithms often requires a large number of queries to a reference policy, which is undesirable as the reference policy is often expensive. In this paper, we propose an extension of the DAgger, called SafeDAgger, that is query efficient and more suitable for end to end autonomous driving. We evaluate the proposed SafeDAgger in a car racing simulator and show that it indeed requires less queries to a reference policy. We observe a significant speed up in convergence, which we conjecture to be due to the effect of automated curriculum learning.
Using the power of Word Of Mouth to leverage the effect of marketing activities on consumer responses

Research has studied Word Of Mouth (WOM) and the 4P marketing activities separately with no attention to how these two processes simultaneously influence consumer responses. This is unfortunate as a firm's marketing activities may also mobilise WOM, which then can leverage the activities' effect on consumer responses. The present study fills this research gap and investigates how WOM mediates the relationship between the 4Ps and consumer responses using the Partial Least Squares method on survey data with 400 broadband customers. Findings show that the 4Ps influence consumer responses directly and that this effect is leveraged when WOM mediates the relationship. The 4Ps primarily mobilise positive WOM (PWOM) making PWOM the strongest mediator. This has implications for marketing and communication strategies, as the 4Ps have to mobilise WOM and influence consumer responses directly. This challenges the composition of the 4Ps and how to design the marketing message so it is appealing for consumers to bring into their social milieu so WOM can take place. It also underlines the necessity to add PWOM as a fifth P, so the different marketing activities' effect can be amplified by the power of WOM and brands can be created as much out of PWOM as out of marketing activities.