nils-herrmann/clean_scirepeval huggingface dataset:
Neuroscience of Motivation and Organizational Behavior: Putting the Reinforcement Sensitivity Theory (RST) to Work

Neuroscience research on human motivation in the workplace is still in its infancy. There is a large industrial and organizational (IO) psychology literature containing numerous theories of motivation, relating to prosocial and productive, and, less so, "darker" antisocial and counter productive, behaviors. However, the development of a viable over arching theoretical framework has proved elusive. In this chapter, we argue that basic neuropsychological systems related to approach, avoidance, and their conflict, may provide such a framework, one which we discuss in terms of the Reinforcement Sensitivity Theory (RST) of personality. We argue that workplace behaviors may be understood by reference to the motivational types that are formed from the combination of basic approach, avoidance, and conflict related personalities. We offer suggestions for future research to explore workplace behaviors in terms of the wider literature on the neuroscience of motivation.
Effect of carboxymethyl cellulose coating enriched with clove oil on postharvest quality of 'Xinyu' mandarin oranges

Attempts to exploit natural preservatives to control postharvest diseases as an alternative technology to synthetic fungicides in citrus fruit have been drawing much attention.  The combined effects of carboxymethyl cellulose (CMC) coating and/or clove oil on the qualitative properties of cold stored 'Xinyu' mandarin oranges stored at 5 degC for 120 days were investigated.  The results showed that the addition of clove oil as an antifungal component to the CMC coating had a good effect on the inhibitory growth of fungal decay, and the coating treatments significantly decreased the decay rate and weight loss, as well as the maleic dialdehyde (MDA) concentration compared with control samples. The clove oil carboxymethyl cellulose (CO CMC) coating significantly maintained commercial quality and inhibited respiration. Meanwhile, the results showed that the activities of superoxide dismutase (SOD) catalase (CAT) polyphenol oxidase (PPO) and phenylalanine ammonia lyase (PAL) in fruit treated with CO CMC coating were higher than in those treated with CMC coating and control samples.  The CO CMC coating has good potential for application as an alternative to synthetic fungicides for improving postharvest quality and prolonging the shelf life of 'Xinyu' mandarin oranges during cold storage.
An overview and comparison of machine learning techniques for classification purposes in digital soil mapping

Machine learning is the automated process of uncovering patterns in large datasets using computer based statistical models, where a fitted model may then be used for prediction purposes on new data. Despite the growing number of machine learning algorithms that have been developed, relatively few studies have provided a comparison of an array of different learners typically, model comparison studies have been restricted to a comparison of only a few models. This study evaluates and compares a suite of 10 machine learners as classification algorithms for the prediction of soil taxonomic units in the Lower Fraser Valley, British Columbia, Canada. A variety of machine learners (CART, CART with bagging, Random Forest, k nearest neighbor, nearest shrunken centroid, artificial neural network, multinomial logistic regression, logistic model trees, and support vector machine) were tested in the extraction of the complex relationships between soil taxonomic units (great groups and orders) from a conventional soil survey and a suite of 20 environmental covariates representing the topography, climate, and vegetation of the study area. Methods used to extract training data from a soil survey included by polygon, equal class, area weighted, and area weighted with random over sampling (ROS) approaches. The fitted models, which consist of the soil environmental relationships, were then used to predict soil great groups and orders for the entire study area at a 100 m spatial resolution. The resulting maps were validated using 262 points from legacy soil data. On average, the area weighted sampling approach for developing training data from a soil survey was most effective. Using a validation of R 1 cell, the k nearest neighbor and support vector machine with radial basis function resulted in the highest accuracy of 72% for great groups using ROS; however, models such as CART with bagging, logistic model trees, and Random Forest were preferred due to the speed of parameterization and the interpretability of the results while resulting in similar accuracies ranging from 65 70% using the area weighted sampling approach. Model choice and sample design greatly influenced outputs. This study provides a comprehensive comparison of machine learning techniques for classification purposes in soil science and may assist in model selection for digital soil mapping and geomorphic modeling studies in the future.
Towards the Automatic Classification of Avian Flight Calls for Bioacoustic Monitoring
Venue: PloS one

Automatic classification of animal vocalizations has great potential to enhance the monitoring of species movements and behaviors. This is particularly true for monitoring nocturnal bird migration, where automated classification of migrants' flight calls could yield new biological insights and conservation applications for birds that vocalize during migration. In this paper we investigate the automatic classification of bird species from flight calls, and in particular the relationship between two different problem formulations commonly found in the literature: classifying a short clip containing one of a fixed set of known species (N class problem) and the continuous monitoring problem, the latter of which is relevant to migration monitoring. We implemented a state of the art audio classification model based on unsupervised feature learning and evaluated it on three novel datasets, one for studying the N class problem including over 5000 flight calls from 43 different species, and two realistic datasets for studying the monitoring scenario comprising hundreds of thousands of audio clips that were compiled by means of remote acoustic sensors deployed in the field during two migration seasons. We show that the model achieves high accuracy when classifying a clip to one of N known species, even for a large number of species. In contrast, the model does not perform as well in the continuous monitoring case. Through a detailed error analysis (that included full expert review of false positives and negatives) we show the model is confounded by varying background noise conditions and previously unseen vocalizations. We also show that the model needs to be parameterized and benchmarked differently for the continuous monitoring scenario. Finally, we show that despite the reduced performance, given the right conditions the model can still characterize the migration pattern of a specific species. The paper concludes with directions for future research.
Study on nonlinear damage creep constitutive model for high stress soft rock
Venue: Environmental Earth Sciences

Rock engineering especially deep rock engineering undergoing long term effects of external loading and gravity all or most may gradually damage deformation or creep deformation accumulation, leading rock structures to damage, crack, such as severe plastic deformation or even progressive failure. In this paper, based on the nonlinear damage creep characteristics of rock and damage variable, a new nonlinear damage creep constitutive model of high stress soft rock is defined in series with the improved Burgers model, Hooke model and St. Venant model. This new nonlinear damage creep constitutive model can work out fairly reasonably explanations for the soft rock creep deformation. A series of uniaxial compression creep tests were performed to study the creep damage characteristics of typical soft rock in Jinchuan No.2 Mine in the northwest of China. Using the increment step loading and single step loading, the results of creep experiments and nonlinear damage creep constitutive model results are very consistent in this study. The new model not only can reflect the whole course of creep deformation, but also can reasonably describe the soft rock under different initial creep stage, steady state creep stage and accelerated creep stage. Therefore, the new nonlinear creep damage model is a reasonable reference model for the research of soft rock creep.
Demographic differences in sport performers' experiences of organizational stressors
Venue: Scandinavian journal of medicine science in sports

Organizational stressors are particularly prevalent across sport performers' experiences and can influence their performance, health, and well being. Research has been conducted to identify which organizational stressors are encountered by sport performers, but little is known about how these experiences vary from athlete to athlete. The purpose of this study was to examine if the frequency, intensity, and duration of the organizational stressors that sport performers encounter vary as a function of gender, sport type, and performance level. Participants (n 1277) completed the Organizational Stressor Indicator for Sport Performers (OSI SP; Arnold et al. 2013) and the resultant data were analyzed using multivariate analyses of covariance. The findings show that demographic differences are apparent in the dimensions of the goals and development, logistics and operations, team and culture, coaching, and selection organizational stressors that sport performers encounter. More specifically, significant differences were found between males and females, between team and individual based performers, and between performers competing at national or international, regional or university, and county or club levels. These findings have important implications for theory and research on organizational stress, and for the development of stress management interventions with sport performers.
Integrating motivational interviewing with cognitive behavioral therapy for severe generalized anxiety disorder: An allegiance controlled randomized clinical trial.
Venue: Journal of consulting and clinical psychology

Although integrating motivational interviewing (MI) and cognitive behavioral therapy (CBT) has been recommended for treating anxiety, few well controlled tests of such integration exist.  In the present randomized trial for severe generalized anxiety disorder (GAD) we compared the efficacy of 15 sessions of CBT alone (N 43) versus 4 MI sessions followed by 11 CBT sessions integrated with MI to address client resistance/ambivalence (N 42) Clients were adults, predominantly female and Caucasian, with a high rate of diagnostic comorbidity. To control for allegiance, therapists were nested within treatment group and supervised separately by experts in the respective treatments.  Piecewise multilevel models revealed no between groups differences in outcomes from pre to posttreatment; however, there were treatment effects over the follow up period with MI CBT clients demonstrating a steeper rate of worry decline (g 0.13, p .03) and general distress reduction (g 0.12, p .01) than CBT alone clients. Also, the odds of no longer meeting GAD diagnostic criteria were ~5 times higher at 12 months for clients receiving MI CBT compared with CBT alone. There were also twice as many dropouts in CBT alone compared with MI CBT (23% vs. 10% a difference that approached significance (p .09) The treatments were competently delivered, and intraclass correlations revealed negligible between therapist effects on the outcomes.  The findings support the integration of MI with CBT for severe GAD and point to the importance of training therapists in appropriate responsivity to in session markers of resistance and ambivalence.
Measuring annual report narratives disclosure: Empirical evidence from forward looking information in the UK prior the financial crisis

This paper aims to investigate empirically the common alternative methods of measuring annual report narratives. Five alternative methods are employed, a weighted and un weighted disclosure index and three textual coding systems, measuring the amount of space devoted to relevant disclosures.  The authors investigate the forward looking voluntary disclosures of 30 UK non financial companies. They employ descriptive analysis, correlation matrix, mean comparison  The results reveal that while the alternative methods of forward looking voluntary disclosure are highly correlated, important significant differences do nevertheless emerge. In particular, it appears important to measure volume rather than simply the existence or non existence of each type of disclosure. Overall, we detect that the optimal method is content analysis by text unit rather than by sentence.  This paper contributes to the extant literature in forward looking disclosure by reporting important differences among alternative content analyses. However, the decision regarding whether this should be a computerised or a manual content analysis appears not to be driven by differences in the resulting measures. Rather, the choice is the outcome of a trade off between the time involved in setting up coding rules for computerised analysis versus the time saved undertaking the analysis itself.
Within and Cross Language Relations Between Oral Language Proficiency and School Outcomes in Bilingual Children With an Immigrant Background

Sixteen meta analyses were conducted to examine relations of typically developing bilingual immigrant background children's oral language proficiency in their first and second language with the school outcomes of early literacy (k 41) reading (k 61) spelling (k 9) mathematics (k 9) and academic achievement (k 9) Moderate to strong within language relations were found for all school outcomes .22 r .43) and cross language relations for early literacy and reading .12 r .22) Within language relations were stronger than cross language relations .14 d .35) Only 6 out of 96 moderator effects tested were significant. Based on our findings, we propose a task dependent bidirectional transfer hypothesis: The strength of cross language transfer depends on the type of language proficiency task and the type of school outcome. Stimulating oral language proficiency in both languages can be a key factor in improving school outcomes of bilingual immigrant background children.
The effect of language proficiency on executive functions in balanced and unbalanced Spanish English bilinguals

This study analyzed the association between levels of language proficiency and levels of bilingualism and performance on verbal and nonverbal executive functions (working memory, updating, shifting, and inhibition tasks) in young bilinguals. Forty balanced (high and low proficiency) 34 unbalanced bilinguals, and 40 English monolinguals, were selected. The Bilingual Verbal Ability Test was used as a measure of language proficiency; WAIS Block design test was used as a measure of non verbal intelligence. High proficiency balanced bilinguals performed better than low proficiency balanced bilinguals; unbalanced bilinguals scored in between both balanced groups. High proficiency monolinguals scored higher than low proficiency monolinguals and similar to high proficiency bilinguals. Regression analyses demonstrated that nonverbal intelligence significantly predicted performances on verbal working memory and verbal and nonverbal inhibition tasks. It was concluded that nonverbal intelligence scores are better predictors of executive function performance than bilingualism or language proficiency.
Medical language proficiency: A discussion of interprofessional language competencies and potential for patient risk.
Venue: International journal of nursing studies

In increasingly multilingual healthcare environments worldwide, ensuring accurate, effective communication is requisite. Language proficiency is essential, particularly medical language proficiency. Medical language is a universal construct in healthcare, the shared language of health and allied health professions. It is highly evolved, career specific, technical and cultural bound a language for specific purposes. Its function differs significantly from that of a standard language. Proficiency requires at minimum, a common understanding of discipline specific jargon, abstracts, euphemisms, abbreviations; acronyms. An optimal medical language situation demands a level of competency beyond the superficial wherein one can convey or interpret deeper meanings, distinguish themes, voice opinion, and follow directions precisely. It necessitates the use of clarity, and the ability to understand both lay and formal language characteristics not essential to standard language. Proficiency influences professional discourse and can have the potential to positively or negatively affect patient outcomes. While risks have been identified when there is language discordance between care provider and patient, almost nothing has been said about this within care teams themselves. This article will do so in anticipation that care providers, regulators, employers, and researchers will acknowledge potential language based communication barriers and work towards resolutions. This is predicated on the fact that the growing interest in language and communication in healthcare today appears to be rested in globalization and increasingly linguistically diverse patient populations. Consideration of the linguistically diverse healthcare workforce is absent. An argument will be posited that if potential risks to patient safety exist and there are potentials for disengagement from care by patients when health providers do not speak their languages then logically these language based issues can also be true for a care team of mixed linguistic backgrounds. Members may disengage from each other or adverse events may occur as a result of misunderstanding or other language based confounds. While the greater goal of the article is to address the issues of medical language across languages, English and medical English are used to illustrate points. Questions will be posed to stimulate thought and identify a need for research. Recommendations include collaboration between the health and language disciplines.
Investigating the relationship of target language proficiency and self efficacy among nonnative EFL teachers

Target language proficiency and pedagogical capabilities are considered to be the two main teacher attributes necessary for second/foreign language teaching. Drawing on this notion, two hypotheses were tested: (a) minimum threshold levels of language proficiency and pedagogical capabilities exist and (b) teachers' language proficiency and pedagogical capabilities are interdependent. A total of 167 Korean secondary school English as a foreign language teachers self reported their English proficiency, teaching efficacy, and frequency of English use in their English instruction. A sequential multiple regression with interaction was employed to investigate the relationship between these two teacher attributes and their contributions to English use as an outcome behavior. The results supported both hypotheses. Only teachers above the minimum threshold levels of both attributes showed positive associations among the two competences and English use. Above the minimum levels, language proficiency and self efficacy were interdependent, magnifying each other's impact on the teaching behavior. The results pointed to the beneficial potential of continuous development of linguistic and pedagogical competences even after teachers possess the minimum levels. Given that previous research has assumed nonnative teachers as one homogenous group and explored language proficiency and self efficacy separately, this study addresses important theoretical, methodological, and practical gaps.
Phenolic acids significantly contribute to antioxidant potency of Gynostemma pentaphyllum aqueous and methanol extracts

Cyclic voltammetry, as well as four well established spectrophotometric and fluorimetric assays, were applied to study the contribution of phenolic compounds to the antioxidant capacity of aqueous and methanol extracts of Jiaogulan tea (Gynostemma pentaphyllum) In addition, individual phenolic acid profiles of G. pentaphyllum extracts, determined using UPLC MS/MS, were reported for the first time in this study. Methanol extraction resulted in higher contents of phenolic compounds, as well as antioxidant capacity of tested extracts. Our results suggest that G. pentaphyllum aqueous and methanol extracts have high antioxidant capacity and are rich in phenolic compounds, such as chlorogenic acid, which might play a role in the prevention of type 2 diabetes mellitus and cardiovascular disease.
Knowledge Graph Construction Techniques

Googles knowledge graph technology has drawn a lot of research attentions in recent years. However,due to the limited public disclosure of technical details,people find it difficult to understand the connotation and value of this technology.In this paper,we introduce the key techniques involved in the construction of knowledge graph in a bottom up way,starting from a clearly defined concept and a technical architecture of the knowledge graph.Firstly,we describe in detail the definition and connotation of the knowledge graph,and then we propose the technical framework for knowledge graph construction,in which the construction process is divided into three levels according to the abstract level of the input knowledge materials,including the information extraction layer,the knowledge integration layer,and the knowledge processing layer,respectively.Secondly,the research status of the key technologies for each level are surveyed comprehensively and also investigated criticaly for the purposes of gradualy revealing the mysteries of the knowledge graph technology,the state of the art progress,and its relationship with related disciplines.Finaly,five major research chalenges in this area are summarized,and the corresponding key research issues are highlighted.
Application of Dc grid for Efficient use of solar PV System in Smart Grid
Venue: ANT/SEIT

This paper is about efficient use of smart dc grid technology for photovoltaic distributed generation and utilizing it in smart way, to build infrastructure more reliable and to achieve the goal to cater the need for tomorrow. As there are many conversion losses from ac to dc, world is moving towards dc appliances as most of the electronic appliances at home accept dc power supply. Receiving dc power from Photovoltaic solar, it is clear there would be benefits in avoiding the conversion losses, especially when most of the devices used at home run on dc. This benefit is further enhanced if dc is directly used for lighting, electric vehicle charging, Digital equipment etc. PV solar energy produces dc power and if used directly then power loss will be minimized. Exact calculation of solar panels and proper battery sizing leads to a reliable distributed generation system. 240Vdc grid will also help to minimize the power transmission losses for up rise buildings, this will further enhance the system efficiency. Proper selection of wire minimizes the electric corrosion. Series and parallel combination of PV and battery cells will enhance the use of suitable power supply for each electronic device. Other side where ac supply is required 240Vdc directly converts to 240Vac for Ac machines such as conventional appliances in order to minimize transformer losses. This paper also presents an idea for smart load shedding techniques and its practical implementation in the form of smart dc Grid. Its various applications will enhance the functionality of a smart Dc grid on residential load.