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Negative symptoms in schizophrenia are associated with significant burden and possess little to no robust treatments in clinical practice today. One key obstacle impeding the development of better treatment methods is the lack of an objective measure. Since negative symptoms almost always adversely affect speech production in patients, speech dysfunction have been considered as a viable objective measure. However, researchers have mostly focused on the verbal aspects of speech, with scant attention to the non-verbal cues in speech. In this paper, we have explored non-verbal speech cues as objective measures of negative symptoms of schizophrenia. We collected an interview corpus of 54 subjects with schizophrenia and 26 healthy controls. In order to validate the non-verbal speech cues, we computed the correlation between these cues and the NSA-16 ratings assigned by expert clinicians. Significant correlations were obtained between these non-verbal speech cues and certain NSA indicators. For instance, the correlation between Turn Duration and Restricted Speech is -0.5, Response time and NSA Communication is 0.4, therefore indicating that poor communication is reflected in the objective measures, thus validating our claims. Moreover, certain NSA indices can be classified into observable and non-observable classes from the non-verbal speech cues by means of supervised classification methods. In particular the accuracy for Restricted speech quantity and Prolonged response time are 80% and 70% respectively. We were also able to classify healthy and patients using non-verbal speech features with 81.3% accuracy. [ABSTRACT FROM AUTHOR]

Data analysis for flow-based in-vitro receptomics array, like a tongue-on-a-chip, is complicated by the relatively large variability within and between arrays, transfected DNA types, spots, and cells within spots. Simply averaging responses of spots of the same type would lead to high variances and low statistical power. This paper presents an approach based on linear mixed models, allowing a quantitative and robust comparison of complex samples and indicating which receptors are responsible for any differences. These models are easily extended to take into account additional effects such as the build-up of cell stress and to combine data from replicated experiments. The increased analytical power this brings to receptomics research is discussed. [ABSTRACT FROM AUTHOR]

In this paper, I aim to explore the effect of good governance on equity returns, and empirically investigate if governance at the country level has asset pricing implications and contributes to the idiosyncrasy of price jumps. Jumps are found to be far less systematic than the smooth (non-jump) component of country price indexes. Hence, if jumps are more idiosyncratic, governance should primarily affect the jump risk component. This is good news for international investors, because diversification provides insurance against jumps. Relying on an equilibrium asset-pricing model in an economy under jump diffusion, I decompose the moments of the returns of international stock markets into a diffusive (systematic) risk and a (idiosyncratic) jump risk part. For a balanced panel of 52 countries, my results suggest that governance is an important determinant of (idiosyncratic) jump risk. Stock markets in poorly governed countries are characterized by higher volatility and more negative return asymmetry, primarily driven by the higher jump risk. Regulatory quality, the government effectiveness and the control of corruption appear to be most important. Results are robust to the inclusion of various controls for other country- or market-specific characteristics. [ABSTRACT FROM AUTHOR]

Duchenne muscular dystrophy (DMD) is a muscular condition that leads to muscle loss. Orthotic devices may present a solution for people with DMD to perform activities of daily living (ADL). One such device is the active trunk support but it needs a control interface to identify the user’s intention. Myoelectric control interfaces can be used to detect the user’s intention and consequently control an active trunk support. Current research on the control of orthotic devices that use surface electromyography (sEMG) signals as control inputs, focuses mainly on muscles that are directly linked to the movement being performed (intuitive control). However in some cases, it is hard to detect a proper sEMG signal (e.g., when there is significant amount of fat), which can result in poor control performance. A way to overcome this problem might be the introduction of other, non-intuitive forms of control. This paper presents an explorative study on the comparison and learning behavior of two different control interfaces, one using sEMG of trunk muscles (intuitive) and one using sEMG of leg muscles that can be potentially used for an active trunk support (non-intuitive). Six healthy subjects undertook a 2-D Fitts’s law style task. They were asked to steer a cursor into targets that were radially distributed symmetrically in five directions. The results show that the subjects were generally able to learn to control the tasks using either of the control interfaces and improve their performance over time. Comparison of both control interfaces demonstrated that the subjects were able to learn the leg control interface task faster than the trunk control interface task. Moreover, the performance on the diagonal-targets was significantly lower compared to the one directional-targets for both control interfaces. Overall, the results show that the subjects were able to control a non-intuitive control interface with high performance. Moreover, the results indicate that the non-intuitive control may be a viable solution for controlling an active trunk support. [ABSTRACT FROM AUTHOR]

Orienteering problem (OP) is a routing problem, where the aim is to generate a path through set of nodes, which would maximize total score and would not exceed the budget. In this paper, we present an extension of classic OP—Orienteering Problem with Functional Profits (OPFP), where the score of a specific point depends on its characteristics, position in the route, and other points in the route. For solving OPFP, we developed an open-source framework for solving orienteering problems, which utilizes four core components of OP in its modular architecture. Fully-written in Go programming language our framework can be extended for solving different types of tasks with different algorithms; this was demonstrated by implementation of two popular algorithms for OP solving—Ant Colony Optimization and Recursive Greedy Algorithm. Computational efficiency of the framework was shown through solving four well-known OP types: classic Orienteering Problem (OP), Orienteering Problem with Compulsory Vertices (OPCV), Orienteering Problem with Time Windows (OPTW), and Time Dependent Orienteering Problem (TDOP) along with OPFP. Experiments were conducted on a large multi-source dataset for Saint Petersburg, Russia, containing data from Instagram, TripAdvisor, Foursquare and official touristic website. Our framework is able to construct touristic paths for different OP types within few seconds using dataset with thousands of points of interest. [ABSTRACT FROM AUTHOR]

Information about a person’s income can be useful in several business-related contexts, such as personalized advertising or salary negotiations. However, many people consider this information private and are reluctant to share it. In this paper, we show that income is predictable from the digital footprints people leave on Facebook. Applying an established machine learning method to an income-representative sample of 2,623 U.S. Americans, we found that (i) Facebook Likes and Status Updates alone predicted a person’s income with an accuracy of up to r = 0.43, and (ii) Facebook Likes and Status Updates added incremental predictive power above and beyond a range of socio-demographic variables (ΔR2 = 6–16%, with a correlation of up to r = 0.49). Our findings highlight both opportunities for businesses and legitimate privacy concerns that such prediction models pose to individuals and society when applied without individual consent. [ABSTRACT FROM AUTHOR]

This paper presents the first empirical investigation that compares Euler and linear diagrams when they are used to represent set cardinality. A common approach is to use area-proportional Euler diagrams but linear diagrams can exploit length-proportional straight-lines for the same purpose. Another common approach is to use numerical annotations. We first conducted two empirical studies, one on Euler diagrams and the other on linear diagrams. These suggest that area-proportional Euler diagrams with numerical annotations and length-proportional linear diagrams without numerical annotations support significantly better task performance. We then conducted a third study to investigate which of these two notations should be used in practice. This suggests that area-proportional Euler diagrams with numerical annotations most effectively supports task performance and so should be used to visualize set cardinalities. However, these studies focused on data that can be visualized reasonably accurately using circles and the results should be taken as valid within that context. Future work needs to determine whether the results generalize both to when circles cannot be used and for other ways of encoding cardinality information. [ABSTRACT FROM AUTHOR]

Early-age exposure to noise may have long-term health implications of which we have little knowledge of today. Age-specific hearing, learning inadequate coping strategies, and alterations in biological stress regulatory responses could play a role in the long-term health impacts. In Sweden about half a million children in the age between 1–5 years attend preschool. The noise exposure at preschools is intermittent and unpredictable and levels reach up to 84 dB LAeq (time indoors) with maximum levels of 118 dB LAF, mostly due to child activity. To increase the overall understanding of the possible implications of preschool noise environments for children, this paper describes children’s behavioral and emotional reactions to and coping with their everyday sound environment from a teachers perspective. A postal questionnaire study performed in 2013–2014 with answers from 3,986 preschool teachers provided the data. Content analysis was combined with quantitative analysis. Eighty-two percent of the personnel considered that children’s behavior was affected rather or very much by preschool noise. The most prevalent behaviors were categorized into: be heard, be distracted, show negative internal emotions, crowd, avoid, withdraw, be exhausted, and learning. The quantitative analyses confirmed an association between the perceived loudness and noise annoyance at preschool and affirmative reporting on noise affecting the children´s behavior. Age of the personnel, with the youngest age group reporting noise related behavior less often, and age distribution of the class, with 1–5 years old seeming less affected by noise, were also indicated, while pedagogic orientation was not a significant factor. Future studies should address the long-term health effects of these behaviors. [ABSTRACT FROM AUTHOR]

The Moral Foundations Dictionary (MFD) is a useful tool for applying the conceptual framework developed in Moral Foundations Theory and quantifying the moral meanings implicated in the linguistic information people convey. However, the applicability of the MFD is limited because it is available only in English. Translated versions of the MFD are therefore needed to study morality across various cultures, including non-Western cultures. The contribution of this paper is two-fold. We developed the first Japanese version of the MFD (referred to as the J-MFD) using a semi-automated method—this serves as a reference when translating the MFD into other languages. We next tested the validity of the J-MFD by analyzing open-ended written texts about the situations that Japanese participants thought followed and violated the five moral foundations. We found that the J-MFD correctly categorized the Japanese participants’ descriptions into the corresponding moral foundations, and that the Moral Foundations Questionnaire (MFQ) scores correlated with the frequency of situations, of total words, and of J-MFD words in the participants’ descriptions for the Harm and Fairness foundations. The J-MFD can be used to study morality unique to the Japanese and also multicultural comparisons in moral behavior. [ABSTRACT FROM AUTHOR]

The Google Books Ngram Viewer (Google Ngram) is a search engine that charts word frequencies from a large corpus of books and thereby allows for the examination of cultural change as it is reflected in books. While the tool's massive corpus of data (about 8 million books or 6% of all books ever published) has been used in various scientific studies, concerns about the accuracy of results have simultaneously emerged. This paper reviews the literature and serves as a guideline for improving Google Ngram studies by suggesting five methodological procedures suited to increase the reliability of results. In particular, we recommend the use of (I) different language corpora, (II) cross-checks on different corpora from the same language, (III) word inflections, (IV) synonyms, and (V) a standardization procedure that accounts for both the influx of data and unequal weights of word frequencies. Further, we outline how to combine these procedures and address the risk of potential biases arising from censorship and propaganda. As an example of the proposed procedures, we examine the cross-cultural expression of religion via religious terms for the years 1900 to 2000. Special emphasis is placed on the situation during World War II. In line with the strand of literature that emphasizes the decline of collectivistic values, our results suggest an overall decrease of religion's importance. However, religion re-gains importance during times of crisis such as World War II. By comparing the results obtained through the different methods, we illustrate that applying and particularly combining our suggested procedures increase the reliability of results and prevents authors from deriving wrong assumptions. [ABSTRACT FROM AUTHOR]

Given a real-world graph, how can we measure relevance scores for ranking and link prediction? Random walk with restart (RWR) provides an excellent measure for this and has been applied to various applications such as friend recommendation, community detection, anomaly detection, etc. However, RWR suffers from two problems: 1) using the same restart probability for all the nodes limits the expressiveness of random walk, and 2) the restart probability needs to be manually chosen for each application without theoretical justification. We have two main contributions in this paper. First, we propose R W E R (RWER), a random walk based measure which improves the expressiveness of random walks by using a distinct restart probability for each node. The improved expressiveness leads to superior accuracy for ranking and link prediction. Second, we propose SR (pervised start for RWER), an algorithm for learning the restart probabilities of RWER from a given graph. SR eliminates the need to heuristically and manually select the restart parameter for RWER. Extensive experiments show that our proposed method provides the best performance for ranking and link prediction tasks. [ABSTRACT FROM AUTHOR]

Current literature presents conflicting findings concerning the effect of religiosity on attitudes towards redistribution. This paper attempts to reconcile these findings by arguing that the belief and social behavior dimensions of religiosity affect support for redistribution via different mechanisms, and that these effects are moderated by state welfare generosity. Using multilevel path analysis models on data from the World Values Survey, we show that the effect of the religious belief on attitudes towards redistribution is mediated by competing personal orientations—prosocial values and conservative identification—while the religious social behavior dimension significantly decreases support for redistribution via increased levels of happiness. Lower levels of welfare generosity increase the positive effect of prosocial orientations and weaken the negative effect conservative identification, leading to positive or null indirect effect of religiosity. These findings show the importance of taking into account the multiple dimensions of religiosity and institutional context when studying the relationship between religion and redistribution attitudes. [ABSTRACT FROM AUTHOR]

This paper develops the ability of the normal inverse Gaussian distribution (NIG) to fit the returns of bitcoin (BTC). As the first cryptocurrency created, the behavior of this new asset is characterized by great volatility. The lack of a proper definition or classification under existing theory exacerbates this property in such a way that explosive periods followed by a rapid decline have been observed along the series, meaning bubble episodes. By detecting the periods in which a bubble rises and collapses, it is possible to study the statistical properties of such segments. In particular, adjusting a theoretical distribution may help to determine better strategies to hedge against these episodes. The NIG is an appropriate candidate not only because of its heavy-tailed property but also because it has been proven to be closed under convolution, a characteristic that can be implemented to measure multivariate value at risk. Using data on the price of BTC with respect to seven of the main global currencies, the NIG was able to fit every time segment despite the bubble behavior. In the out-of-sample tests, the NIG was proven to have an adjustment similar to that of a generalized hyperbolic (GH) distribution. This result could serve as a starting point for future studies regarding the statistical properties of cryptocurrencies as well as their multivariate distributions. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While violent political protests are statistically rare events, they often shape public perceptions of political and social movements. This is, in part, due to the extensive and disproportionate media coverage which violent protest participation receives relative to peaceful protest participation. In the past, when a small number of media conglomerates served as the primary information source for learning about political and social movements, viewership and advertiser demands encouraged news organizations to focus on violent forms of political protest participation. Consequently, much of our knowledge about political protest participation is derived from data collected about violent protests, while less is known about peaceful forms of protest. Since the early 2000s, the digital revolution shifted attention away from traditional news sources toward social media as a primary source of information about current events. This, along with developments in machine learning which allow us to collect and analyze data relevant to political participation, present us with unique opportunities to expand our knowledge of peaceful and violent forms of political protest participation through social media data. [ABSTRACT FROM AUTHOR]

Background: Modeling contributes to health program planning by allowing users to estimate future outcomes that are otherwise difficult to evaluate. However, modeling results are often not easily translated into practical policies. This paper examines the barriers and enabling factors that can allow models to better inform health decision-making. Description: The Decision Makers’ Program Planning Tool (DMPPT) and its successor, DMPPT 2, are illustrative examples of modeling tools that have been used to inform health policy. Their use underpinned Voluntary Medical Male Circumcision (VMMC) scale-up for HIV prevention in southern and eastern Africa. Both examine the impact and cost-effectiveness of VMMC scale-up, with DMPPT used initially in global advocacy and DMPPT 2 then providing VMMC coverage estimates by client age and subnational region for use in country-specific program planning. Their application involved three essential steps: identifying and engaging a wide array of stakeholders from the outset, reaching consensus on key assumptions and analysis plans, and convening data validation meetings with critical stakeholders. The subsequent DMPPT 2 Online is a user-friendly tool for in-country modeling analyses and continuous program planning and monitoring. Lessons learned: Through three iterations of the DMPPT applied to VMMC, a comprehensive framework with six steps was identified: (1) identify a champion, (2) engage stakeholders early and often, (3) encourage consensus, (4) customize analyses, (5), build capacity, and (6) establish a plan for sustainability. This framework could be successfully adapted to other HIV prevention programs to translate modeling results to policy and programming. Conclusions: Models can be used to mobilize support, strategically plan, and monitor key programmatic elements, but they can also help inform policy environments in which programs are conceptualized and implemented to achieve results. The ways in which modeling has informed VMMC programs and policy may be applicable to an array of other health interventions. [ABSTRACT FROM AUTHOR]

This paper investigates the behavioural effects of competitive, social-value and social-image incentives on men’s and women’s allocation of effort in a multi-task environment. Specifically, using two real-effort laboratory tasks, we investigate how competitive prizes, social-value generation and public awards affect effort allocation decisions between the tasks. We find that all three types of incentives significantly focus effort allocation towards the task they are applied in, but the effect varies significantly between men and women. The highest effort distortion lies with competitive incentives, which is due to the effort allocation decision of men. Women exert similar amount of effort across the three incentive conditions, with slightly lower effort levels in the social-image incentivized tasks. Our results inform how and why genders differences may persist in competitive workplaces. [ABSTRACT FROM AUTHOR]

Temperament and Psychological Types can be defined as innate psychological characteristics associated with how we relate with the world, and often influence our study and career choices. Furthermore, understanding these features help us manage conflicts, develop leadership, improve teaching and many other skills. Assigning temperament and psychological types is usually made by filling specific questionnaires. However, it is possible to identify temperamental characteristics from a linguistic and behavioral analysis of social media data from a user. Thus, machine-learning algorithms can be used to learn from a user’s social media data and infer his/her behavioral type. This paper initially provides a brief historical review of theories on temperament and then brings a survey of research aimed at predicting temperament and psychological types from social media data. It follows with the proposal of a framework to predict temperament and psychological types from a linguistic and behavioral analysis of Twitter data. The proposed framework infers temperament types following the David Keirsey’s model, and psychological types based on the MBTI model. Various data modelling and classifiers are used. The results showed that Random Forests with the LIWC technique can predict with 96.46% of accuracy the Artisan temperament, 92.19% the Guardian temperament, 78.68% the Idealist, and 83.82% the Rational temperament. The MBTI results also showed that Random Forests achieved a better performance with an accuracy of 82.05% for the E/I pair, 88.38% for the S/N pair, 80.57% for the T/F pair, and 78.26% for the J/P pair. [ABSTRACT FROM AUTHOR]

The 3D Tune-In Toolkit (3DTI Toolkit) is an open-source standard C++ library which includes a binaural spatialiser. This paper presents the technical details of this renderer, outlining its architecture and describing the processes implemented in each of its components. In order to put this description into context, the basic concepts behind binaural spatialisation are reviewed through a chronology of research milestones in the field in the last 40 years. The 3DTI Toolkit renders the anechoic signal path by convolving sound sources with Head Related Impulse Responses (HRIRs), obtained by interpolating those extracted from a set that can be loaded from any file in a standard audio format. Interaural time differences are managed separately, in order to be able to customise the rendering according the head size of the listener, and to reduce comb-filtering when interpolating between different HRIRs. In addition, geometrical and frequency-dependent corrections for simulating near-field sources are included. Reverberation is computed separately using a virtual loudspeakers Ambisonic approach and convolution with Binaural Room Impulse Responses (BRIRs). In all these processes, special care has been put in avoiding audible artefacts produced by changes in gains and audio filters due to the movements of sources and of the listener. The 3DTI Toolkit performance, as well as some other relevant metrics such as non-linear distortion, are assessed and presented, followed by a comparison between the features offered by the 3DTI Toolkit and those found in other currently available open- and closed-source binaural renderers. [ABSTRACT FROM AUTHOR]

Background: Centile curves and standard scores are common in epidemiological research. However, standardised norms and centile growth curves for language disorder that reflect the entire UK local school population do not exist. Methods: Scores on six language indices assessing receptive and expressive functioning of children were obtained from the SCALES population survey. Monolingual English speaking participants were aged between five and nine years. Children who attended special schools at study intake, or who were learning English as an additional language were excluded. We constructed language norms using the LMS method of standardisation which allows for skewed measurements. We made use of probability weights that were produced from a two-step logistic model. Distributions of estimated standard scores from an intensively assessed sub-population and from the full population were contrasted to demonstrate the role of weights. Results: Non-overlapping centile curves and standardised scores at each age were obtained for the six language indices. The use of weights was essential at retrieving the target distribution of the scores. An online calculator that estimates standardised scores for the measures was constructed and made freely available. Conclusions: The findings highlight the usefulness and flexibility of the LMS method at dealing with the standardisation of linguistic and educational measures that are sufficiently continuous. The paper adds to the existing literature by providing population norms for a number of language tests that were calculated from the same group of individuals. [ABSTRACT FROM AUTHOR]

Loot boxes are items in video games that contain randomised contents and can be purchased with real-world money. Similarities between loot boxes and forms of gambling have led to questions about their legal status, and whether they should be regulated as gambling. Previous research has suggested a link between the amount that gamers spend on loot boxes and their problem gambling: The more individuals spent on loot boxes, the more severe their problem gambling. However, the generalisability of prior work may be limited by both the self-selected nature of the sample under test, and the fact that participants were aware of the study’s aims. A large-scale survey of gamers (n = 1,172) was undertaken to determine if this link remained when these limitations of previous work were taken into account. These gamers did not self-select into a loot box study and were not aware of the study’s aims. This study found similar evidence for a link (η2 = 0.051) between the amount that gamers spent on loot boxes and the severity of their problem gambling. Previous research strongly suggested both the size and the direction of link between loot box use and problem gambling. This paper provides further support for this link. These results suggest either that loot boxes act as a gateway to problem gambling, or that individuals with gambling problems are drawn to spend more on loot boxes. In either case, we believe that these results suggest there is good reason to regulate loot boxes. [ABSTRACT FROM AUTHOR]

Background: Due to changes in Polish society resulting from a significant inflow of immigrants to Poland, the need to develop the cultural competences of various professional groups who have contact with immigrants in their work has increased. These groups should include healthcare professionals, especially because of the significant increase in the number of culturally diverse patients. Therefore, medical education in Poland has had to rapidly adapt to this novel situation. For instance, the teaching process should be now more focused on the development and evaluation of the cultural competences of prospective health care workers. However, there is still a lack of standardized, valid and reliable instruments to assess cross-cultural competences among healthcare professionals. The purpose of the present paper was to describe, for the first time, the translation, adaptation, and psychometric evaluation of the Polish version of the Cross-Cultural Competence Inventory. Methods: Across two studies, we examined psychometric properties of the Cross-Cultural Competence Inventory (CCCI) such as reliability (i.e. internal consistency, test-retest reliability, factor structure) and validity (i.e. theoretical, criteria, convergent). In the first study, 408 participants (75% were healthcare professionals) completed the Polish version of the CCCI and the Positive/Negative Attitude Towards Culturally Divergent People Questionnaire. In the second study, 317 participants (97% were healthcare professionals) completed the CCCI twice, with an interval of at least 22 days. In addition, across two study sessions, participants completed questionnaires constructed to measure (a) cultural intelligence, (b) need for cognitive closure, (c) emphatic sensitiveness, (d) emotional intelligence, (e) self-esteem, (f) social desirability, and (g) personality. Finally, to additionally examine the theoretical validity, 36 professional cross-cultural competence trainers completed the CCCI during a one-session study. Results: Our findings confirm the reliability and validity of the CCCI. More precisely, in study 1 we proved the theoretical validity and reliability (i.e. internal consistency) of the CCCI. While the assumed structure did not fit the data well, all items were significantly related to the general factor, thus providing strong support for the usage of the total score of the CCCI. In study 2, we additionally estimated the test-retest reliability and theoretical, criterion and convergent validity. Across two studies we were able to successfully confirm these psychometric properties. The reliability was satisfactory and ranged from .83 to .86. We also observed a high and significant positive correlation between CCCI and the Cultural Intelligence Scale, which measures a concept similar to the one measured by CCCI. In addition, a significant relationship between intercultural competences (CCCI) and other variables such as personality, empathic sensitivity, emotional intelligence, self-esteem (positive correlations) and the need for cognitive closure (mainly negative correlation) were demonstrated. Conclusions: The obtained results support the usage of the CCCI questionnaire in scientific research, such as, for example, among healthcare professionals (nurses, doctors) and students of medical fields (nursing, medicine). [ABSTRACT FROM AUTHOR]

Studio is critically important for design education, but few attempts have been made to demonstrate the parallels between studio factors and design performance. This paper adopts a coherent set of analyses to investigate the major studio factors and attempts to quantify the networking interactions among them. First, it describes how architectural studio is usually organised based on some major factors. Next, a theoretical model is established according to the described hypotheses and their mutual interactions. Third, the research method and statistical analysis with structural equation modelling (SEM) are presented. Finally, the results of this empirical examination are presented for discussion and suggestions. Our findings reveal that studio tutorials have no significant effect on undergraduate's design performance. In contrast, students’ subjective intention plays a more important role in shaping their behaviour, indicating the importance of transferring those exterior forces into internal benefits when the studio instructor attempts to optimise the pedagogy. These findings are also inspiring for all creative disciplines. [ABSTRACT FROM AUTHOR]

The understanding of human mobility patterns in different transportation modes is an interdisciplinary research field with a direct impact in aspects as varied as urban planning, traffic optimization, sustainability, the reduction of operating costs as well as the mitigation of pollution in urban areas. In this paper, we study the global activity of users in bike-sharing systems operating in the cities of Chicago and New York. For this transportation mode, we explore the temporal and spatial characteristics of the mobility of cyclists. In particular, through the analysis of origin-destination matrices, we characterize the spatial structure of the displacements of users. We apply a mobility model for the global activity of the system that classifies the displacements between stations in local and non-local transitions. In local transitions, cyclists move in a region around each station whereas, in the non-local case, bike users travel with long-range displacements in a similar way to Lévy flights. We reproduce the spatial dynamics by using Monte Carlo simulations. The obtained results are similar to the observed in real data and reveal that the model implemented captures important characteristics of the global spatial dynamics in the systems analyzed. [ABSTRACT FROM AUTHOR]

Recognizing a person in a crowded environment is a challenging, yet critical, visual-search task for both humans and machine-vision algorithms. This paper explores the possibility of combining a residual neural network (ResNet), brain-computer interfaces (BCIs) and human participants to create “cyborgs” that improve decision making. Human participants and a ResNet undertook the same face-recognition experiment. BCIs were used to decode the decision confidence of humans from their EEG signals. Different types of cyborg groups were created, including either only humans (with or without the BCI) or groups of humans and the ResNet. Cyborg groups decisions were obtained weighing individual decisions by confidence estimates. Results show that groups of cyborgs are significantly more accurate (up to 35%) than the ResNet, the average participant, and equally-sized groups of humans not assisted by technology. These results suggest that melding humans, BCI, and machine-vision technology could significantly improve decision-making in realistic scenarios. [ABSTRACT FROM AUTHOR]

More than ever, technical inventions are the symbol of our society’s advance. Patents guarantee their creators protection against infringement. For an invention being patentable, its novelty and inventiveness have to be assessed. Therefore, a search for published work that describes similar inventions to a given patent application needs to be performed. Currently, this so-called search for prior art is executed with semi-automatically composed keyword queries, which is not only time consuming, but also prone to errors. In particular, errors may systematically arise by the fact that different keywords for the same technical concepts may exist across disciplines. In this paper, a novel approach is proposed, where the full text of a given patent application is compared to existing patents using machine learning and natural language processing techniques to automatically detect inventions that are similar to the one described in the submitted document. Various state-of-the-art approaches for feature extraction and document comparison are evaluated. In addition to that, the quality of the current search process is assessed based on ratings of a domain expert. The evaluation results show that our automated approach, besides accelerating the search process, also improves the search results for prior art with respect to their quality. [ABSTRACT FROM AUTHOR]

Introduction: As a result of global migration, health professionals in destination countries are increasingly being called upon to provide care for women and girls who have experienced female genital mutilation/cutting (FGM/C). There is considerable evidence to suggest that their care experiences are sub-optimal. This systematic review sought to illuminate possible reasons for this by exploring the views, experiences, barriers and facilitators to providing FGM-related healthcare in high income countries, from health professionals’ perspectives. Methods: Sixteen electronic databases/resources were searched from inception to December 2017, supplemented by reference list searching and suggestions from experts. Inclusion criteria were: qualitative studies (including grey literature) of any design, any cadre of health worker, from OECD countries, of any date and any language. Two reviewers undertook screening, selection, quality appraisal and data extraction using tools from the Joanna Briggs Institute (JBI). Synthesis involved an inductive thematic approach to identify descriptive themes and interpret these into higher order analytical constructs. Confidence in the review findings was assessed using GRADE-CERQual. The review protocol was registered with PROSPERO (CRD420150300042015). Results: Thirty papers (representing 28 distinct studies) from nine different countries were included. The majority of studies focused on maternity contexts. No studies specifically examined health professionals’ role in FGM/C prevention/safeguarding. There were 20 descriptive themes summarised into six analytical themes that highlighted factors perceived to influence care: knowledge and training, communication, cultural (mis)understandings, identification of FGM/C, clinical management practices and service configuration. Together, these inter-linked themes illuminate the ways in which confidence, communication and competence at provider level and the existence and enactment of pathways, protocols and specialist support at service/system level facilitate or hinder care. Conclusions: FGM/C is a complex and culturally shaped phenomenon. In order to work effectively across cultural divides, there is a need for provider training, clear guidelines, care pathways and specialist FGM/C centres to support mainstream services. [ABSTRACT FROM AUTHOR]

There are more than one billion smokers globally according to the World Health Organization (WHO) report in 2017. Every year tobacco use causes nearly 6 million deaths worldwide. To deal with the smoking epidemic, society needs to invest resources efficiently. In this paper we introduce an optimal control model to determine the optimal mix of smoking initiation and cessation interventions to reduce smoking. We construct the model to reach a smoking prevalence target within a specific time horizon while minimizing cost. Our performance measure captures the cost of policy implementation over time, adjusting for inflation and social discounting. The analytical solutions to the model are presented in forms of ordinary differential equations (ODE). We then conduct several numerical simulations using data from the National Health Interview Survey (NHIS) and empirical studies. We first present analytical solutions for our model to solve for the optimal mix of smoking interventions. Then we simulate a public health policy to achieve 5% smoking prevalence in the US by 2030 using different combinations of real-life interventions. We examine the optimal trajectories, allocative efficiency and annual total cost of smoking cessation and initiation interventions. We find consistent results across all simulations. Our specific example reveals that the most efficient way to reach stated goal is by targeting cessation interventions first, and then gradually shifting resources to initiation interventions over time. While our numerical results are specific to the intervention we selected, our framework can be easily expanded to consider other potential interventions. We discuss the implications of our approach for the formulation of dynamic public health policies. [ABSTRACT FROM AUTHOR]

Background: Nutrition outcomes among young children in Nigeria are among the worse globally. Mother’s limited knowledge about food choices, feeding, and health care seeking practices contributes significantly to negative nutrition outcomes for children in most developing countries. Much less is known about the relationship between mother’s nutrition-related knowledge and child nutritional outcomes in rural Nigeria. This paper investigates therefore: (i) the association of mother’s nutrition-related knowledge with nutrition outcomes of young children living in rural Nigeria, where access to education is limited, and (ii) whether mother’s education has a complementary effect on such knowledge in producing positive child nutrition outcomes in such settings. Methods: Using the Demographic and Health Survey data for Nigeria, we employ both descriptive and regression analyses approaches in analyzing the study’s objectives. In particular, we apply ordinary least square (OLS) to investigate the association of mother’s nutrition-related knowledge with child HAZ and WHZ while controlling for maternal, child, household and regional characteristics. An index was constructed for mother’s nutrition-related knowledge using information on dietary practices, disease treatment and prevention, child immunization, and family planning. Results: We found that mother’s knowledge is independently and positively associated with HAZ and WHZ scores in young children. Higher levels of mother’s education, typically above primary, have a significant, positive association with child HAZ and WHZ scores. We argue that mother’s knowledge of health and nutrition may substitute for education in reducing undernutrition in young children among populations with limited access to formal education. However, the present level of mother’s education in rural Nigeria appears insufficient to reinforce knowledge in producing better nutrition outcomes for children. Conclusions: This study suggests promotion of out-of-school (informal) education, such as adult literacy and numeracy classes where women without formal education can gain health and nutrition knowledge, and practices that could enhance child nutrition outcomes in Nigeria. [ABSTRACT FROM AUTHOR]

Objective: Cultural changes faced by immigrants and ethnic minorities after moving to a host country may have a detrimental or beneficial influence on their oral health and oral health-related behaviors. Therefore, this paper reviews the literature to see the impact of acculturation on immigrants and ethnic minorities’ oral health outcomes. Methods: We searched seven electronic databases up to January 2018. All cross-sectional and longitudinal quantitative studies that examined associations between acculturation and oral health status and/or oral health behaviors among ethnic minority and immigrant population[s] were included. Study selection, data extraction, and risk of bias assessment were completed in duplicate. The Newcastle-Ottawa checklist was used to appraise the methodological quality of the quantitative studies. A meta-analytic approach was not feasible. Results: A total of 42 quantitative studies were identified. The studies showed a positive association between acculturation and oral health status/behaviors. The most frequently used acculturation indicators were language spoken by immigrant and ethnic minorities and length of stay at the host country. High-acculturated immigrant and ethnic minority groups demonstrated better oral health outcomes, oral health behaviors, dental care utilization, and dental knowledge. Conclusions: According to existing evidence, a positive effect of acculturation on oral health status and behaviors was found. Practical implications: Dental practitioners should be culturally competent to provide the appropriate services and treatments to immigrant and ethnic minorities. Policymakers should also be sensitive to cultural diversities and properly address the unique needs of each group in order to maintain oral health equity. [ABSTRACT FROM AUTHOR]

The increased mortality rate among the Acoli people of northern Uganda is anecdotally blamed on excessive consumption of cheap and widely available sachet-packaged alcohol in the region. In this paper, we quantify this perceived association by determining statistically the health risks associated with ingesting 20 heavy metals in 17 popular spirits products consumed in Acoli. Thirteen of these products were industrially packaged in sachets (locally known as ‘sachet,’ waragi, arege or moo lyec) and four were locally produced Lira-Lira spirits from Bolo, Awere and Teso Bar in the region and Nsambya in southern Uganda. A Scottish whisky purchased in San Diego (USA) was our reference. Risk assessment was performed according to standardized protocols developed by the United States Environmental Protection Agency (US EPA). Our results show that a strong correlation indeed exists between health risks and ingestion of spirits in Acoli. At >2.5 sachets/day for 240 day/year over a lifetime for example, the risk of developing cancer due to exposure to As, Pb and Cr alone is 1 in 102,041. This estimate excludes ethanol, a known carcinogen, and 17 heavy metals also studied due to lack of their cancer slope factors. The primary non-cancer related health risk factor in all samples tested is ethanol with unacceptably high health index of four. The Lira-Lira spirits, with 100–6000% copper above the US EPA limit for intake by oral ingestion in water, would be the ‘cleanest’ without copper and at par with the Scottish whisky. Collectively, we find that no amount of alcohol consumed in Acoli is safe. Preventive measures are therefore recommended to reduce mortality in Acoli in particular, and in Uganda in general. These measures should include public education, better public policies, creating productive economic activities other than brewing alcohol, and social activities that engage people away from drinking. [ABSTRACT FROM AUTHOR]

It is evident through biology research that, biological neural network could be implemented through two means: by congenital heredity, or by posteriority learning. However, traditionally, artificial neural network, especially the Deep learning Neural Networks (DNNs) are implemented only through exhaustive training and learning. Fixed structure is built, and then parameters are trained through huge amount of data. In this way, there are a lot of redundancies in the implemented artificial neural network. This redundancy not only requires more effort to train the network, but also costs more computing resources when used. In this paper, we proposed a bionic way to implement artificial neural network through construction rather than training and learning. The hierarchy of the neural network is designed according to analysis of the required functionality, and then module design is carried out to form each hierarchy. We choose the Drosophila’s visual neural network as a test case to verify our method’s validation. The results show that the bionic artificial neural network built through our method could work as a bionic compound eye, which can achieve the detection of the object and their movement, and the results are better on some properties, compared with the Drosophila’s biological compound eyes. [ABSTRACT FROM AUTHOR]

Background: In this paper we present a model of parameters to aesthetically characterize films using a multi-disciplinary approach: by combining film theory, visual low-level video descriptors (modeled in order to supply aesthetic information) and classification techniques using machine and deep learning. Methods: Four different tests have been developed, each for a different application, proving the model's usefulness. These applications are: aesthetic style clustering, prediction of production year, genre detection and influence on film popularity. Results: The results are compared against high-level information to determine the accuracy of the model to classify films without knowing such information previously. The main difference with other film characterization approaches is that we are able to isolate the influence of high-level descriptors to really understand the relevance of low-level features and, accordingly propose a useful set of low-level visual descriptors for that purpose. This model has been tested with a representative number of films to prove that it can be used for different applications. [ABSTRACT FROM AUTHOR]

This paper proposes a weighted generalization of the recently developed Euclidean Index. The weighting mechanism is designed to reflect the reputation of the journal within which an article appears. The weights are constructed using the Eigenfactor Article Influence percentiles scores. The rationale for assigning weights is that citations in more prestigious journals should be adjusted to logically reflect higher costs of production and higher vetting standards, and to partially counter several pragmatic issues surrounding truncated citation counts. Simulated and empirical demonstrations of the proposed approaches are included, which emphasize the flexibility and efficacy of the proposed generalization. [ABSTRACT FROM AUTHOR]

Modality exclusivity norms have been developed in different languages for research on the relationship between perceptual and conceptual systems. This paper sets up the first modality exclusivity norms for Chinese, a Sino-Tibetan language with semantics as its orthographically relevant level. The norms are collected through two studies based on Chinese sensory words. The experimental designs take into consideration the morpho-lexical and orthographic structures of Chinese. Study 1 provides a set of norms for Mandarin Chinese single-morpheme words in mean ratings of the extent to which a word is experienced through the five sense modalities. The degrees of modality exclusivity are also provided. The collected norms are further analyzed to examine how sub-lexical orthographic representations of sense modalities in Chinese characters affect speakers’ interpretation of the sensory words. In particular, we found higher modality exclusivity rating for the sense modality explicitly represented by a semantic radical component, as well as higher auditory dominant modality rating for characters with transparent phonetic symbol components. Study 2 presents the mean ratings and modality exclusivity of coordinate disyllabic compounds involving multiple sense modalities. These studies open new perspectives in the study of modality exclusivity. First, links between modality exclusivity and writing systems have been established which has strengthened previous accounts of the influence of orthography in the processing of visual information in reading. Second, a new set of modality exclusivity norms of compounds is proposed to show the competition of influence on modality exclusivity from different linguistic factors and potentially allow such norms to be linked to studies on synesthesia and semantic transparency. [ABSTRACT FROM AUTHOR]

As a sustainable mode of transportation, public bicycles significantly improve daily mobility. The location of stations is a key element for the success of a public bicycle system, as a long walking distance will reduce people’s willingness to use this mode of transportation. Building forms in China are different from the open type seen abroad. Many residential, office and school areas are enclosed by walls, and pedestrian flow is concentrated at the entrances/exits of these areas. Therefore, the station must be located close to the building entrance/exit. Previous studies on station location located the stations only per zone, without providing the exact locations of the stations in the zones. This paper considers the optimal distance between the building entrance/exit and the station to determine the exact station locations. The results can serve as a reference for the planning and optimization of public bicycle stations. A questionnaire survey was conducted in Beijing to determine users’ walking distances to the stations. The results indicated that the walking distance decay laws of stations were different for different land uses. Moreover, a binary logistic model was developed to verify that users with different travel purposes have different walking distances. Based on the above results, we explored the optimal distances and tolerable distances between the building entrance/exit and the station for different land uses. These distances can be used to determine exact station locations to meet users’ physiological and psychological needs. [ABSTRACT FROM AUTHOR]

Health care organizations are leveraging machine-learning techniques, such as artificial neural networks (ANN), to improve delivery of care at a reduced cost. Applications of ANN to diagnosis are well-known; however, ANN are increasingly used to inform health care management decisions. We provide a seminal review of the applications of ANN to health care organizational decision-making. We screened 3,397 articles from six databases with coverage of Health Administration, Computer Science and Business Administration. We extracted study characteristics, aim, methodology and context (including level of analysis) from 80 articles meeting inclusion criteria. Articles were published from 1997–2018 and originated from 24 countries, with a plurality of papers (26 articles) published by authors from the United States. Types of ANN used included ANN (36 articles), feed-forward networks (25 articles), or hybrid models (23 articles); reported accuracy varied from 50% to 100%. The majority of ANN informed decision-making at the micro level (61 articles), between patients and health care providers. Fewer ANN were deployed for intra-organizational (meso- level, 29 articles) and system, policy or inter-organizational (macro- level, 10 articles) decision-making. Our review identifies key characteristics and drivers for market uptake of ANN for health care organizational decision-making to guide further adoption of this technique. [ABSTRACT FROM AUTHOR]

Objectives: Professional sporting organisations invest considerable resources collecting and analysing data in order to better understand the factors that influence performance. Recent advances in non-invasive technologies, such as global positioning systems (GPS), mean that large volumes of data are now readily available to coaches and sport scientists. However analysing such data can be challenging, particularly when sample sizes are small and data sets contain multiple highly correlated variables, as is often the case in a sporting context. Multicollinearity in particular, if not treated appropriately, can be problematic and might lead to erroneous conclusions. In this paper we present a novel ‘leave one variable out’ (LOVO) partial least squares correlation analysis (PLSCA) methodology, designed to overcome the problem of multicollinearity, and show how this can be used to identify the training load (TL) variables that influence most ‘end fitness’ in young rugby league players. Methods: The accumulated TL of sixteen male professional youth rugby league players (17.7 ± 0.9 years) was quantified via GPS, a micro-electrical-mechanical-system (MEMS), and players’ session-rating-of-perceived-exertion (sRPE) over a 6-week pre-season training period. Immediately prior to and following this training period, participants undertook a 30–15 intermittent fitness test (30-15IFT), which was used to determine a players ‘starting fitness’ and ‘end fitness’. In total twelve TL variables were collected, and these along with ‘starting fitness’ as a covariate were regressed against ‘end fitness’. However, considerable multicollinearity in the data (VIF >1000 for nine variables) meant that the multiple linear regression (MLR) process was unstable and so we developed a novel LOVO PLSCA adaptation to quantify the relative importance of the predictor variables and thus minimise multicollinearity issues. As such, the LOVO PLSCA was used as a tool to inform and refine the MLR process. Results: The LOVO PLSCA identified the distance accumulated at very-high speed (>7 m·s-1) as being the most important TL variable to influence improvement in player fitness, with this variable causing the largest decrease in singular value inertia (5.93). When included in a refined linear regression model, this variable, along with ‘starting fitness’ as a covariate, explained 73% of the variance in v30-15IFT ‘end fitness’ (p<0.001) and eliminated completely any multicollinearity issues. Conclusions: The LOVO PLSCA technique appears to be a useful tool for evaluating the relative importance of predictor variables in data sets that exhibit considerable multicollinearity. When used as a filtering tool, LOVO PLSCA produced a MLR model that demonstrated a significant relationship between ‘end fitness’ and the predictor variable ‘accumulated distance at very-high speed’ when ‘starting fitness’ was included as a covariate. As such, LOVO PLSCA may be a useful tool for sport scientists and coaches seeking to analyse data sets obtained using GPS and MEMS technologies. [ABSTRACT FROM AUTHOR]

This paper assesses the psychometric properties of four child care quality instruments administered in 404 child care centers in Ecuador: the Classroom Assessment Scoring System for Toddlers, the Infant/Toddler Environment Rating Scale–Revised Edition, the Child Care Infant/Toddler Home Observation for Measurement of the Environment, and the Missouri Infant/Toddler Responsive Caregiving Checklist. We examined their internal consistency, tested the underlying subscale structure by means of confirmatory factor analysis (CFA), verified construct validity by testing associations with quality-related factors (e.g., child-caregiver ratio), and checked concurrent validity of the instruments’ total scores. We found high internal consistency of the instruments at the full scale level and moderate to high at the subscale/domain level. CFA showed high factor loadings, but goodness of fit statistics were low. Construct validity results varied from low to very low depending on the quality-related factor, and concurrent validity from low to very high depending on the instruments compared. This validity exercise provides useful information for policy-makers and researchers interested in using these instruments in the Ecuadorian context or elsewhere in the region. The findings will also inform future research and development of affordable and culturally-appropriate tools for monitoring process quality in child care centers in Latin American countries. [ABSTRACT FROM AUTHOR]

Aims: Research demonstrates a negative relationship between alcohol use and affect, but the value of deprecation is unknown and thus cannot be included in estimates of the cost of alcohol to society. This paper aims to examine this relationship and develop econometric techniques to value the loss in affect attributable to alcohol consumption. Methods: Cross-sectional (n = 129,437) and longitudinal (n = 11,352) analyses of alcohol consumers in UK Biobank data were undertaken, with depression and neuroticism as proxies of negative affect. The cross-sectional relationship between household income, negative affect and alcohol consumption were analysed using regression models, controlling for confounding variables, and using within-between random models that are robust to unobserved heterogeneity. The differential in household income required to offset alcohol’s detriment to affect was derived. Results: A consistent relationship between depression and alcohol consumption (β = 0.001, z = 7.64) and neuroticism and alcohol consumption (β = 0.001, z = 9.24) was observed in cross-sectional analyses, replicated in within-between models (depression β = 0.001, z = 2.32; neuroticism β = 0.001, z = 2.33). Significant associations were found between household income and depression (cross sectional β = -0.157, z = -23.86, within-between β = -0.146, z = -9.51) and household income and neuroticism (cross sectional β = -0.166, z = -32.02, within-between β = -0.158, z = -7.44). The value of reducing alcohol consumption by one gram/day was pooled and estimated to be £209.06 (95% CI £171.84 to £246.27). Conclusions: There was a robust relationship between alcohol consumption and negative affect. Econometric methods can value the intangible effects of alcohol use and may, therefore, facilitate the fiscal determination of benefit. [ABSTRACT FROM AUTHOR]

Introduction: Self-stigma–negative self-judgements resulting in shame, worthlessness and self-blame–may play a crucial role in emotional reactions and cause emotional distress among many people living with HIV and other chronic illnesses. Furthermore, self-stigma negatively impacts on self-agency, quality of life, adherence to treatment, and access to services. High levels of self-stigma have been reported across many countries, however few programmes or interventions exist to specifically tackle this phenomenon. This paper reports the findings of a pilot study carried out in Zimbabwe using a programme incorporating “Inquiry-Based Stress Reduction (IBSR): The Work of Byron Katie”–a guided form of self-inquiry which helps users to overcome negative thoughts and beliefs. Objectives: The primary objective of this uncontrolled pilot study was to examine the potential role of the IBSR intervention in helping people living with HIV to overcome self-stigma and associated states. Methods: 23 people living with HIV (17 Female, 6 male, average age 41 years) were recruited from a local HIV support network, via open call for volunteers. All participants received the intervention, consisting of a 12-week facilitated programme using techniques derived from IBSR: The Work of Byron Katie. Qualitative and quantitative data were collected and analysed pre- and post-programme. Results: After taking part in the intervention, participants reported significant improvements in factors including self-stigma (1-month follow-up vs baseline Z = 2.1, p = 0.039; 3-month follow-up vs baseline Z = 3.0, p = 0.003, n = 23, Wilcoxon Matched Pairs Signed Rank Test) and depression (1mo vs baseline Z = 3.7, p = <0.001; 3mo vs baseline Z = 3.3, p = 0.001). Qualitatively, participants reported improvements including lessened fears around disclosure of their HIV status, reduced feelings of life limitations due to HIV, and greater positive mentality. Improvements persisted at three-month follow-up. Conclusion: With further development and larger comparative studies to confirm effects, the IBSR programme could become a novel tool to enable people living with HIV to support themselves in overcoming self-stigma. [ABSTRACT FROM AUTHOR]

In 2010, the UK embarked on a self-imposed programme of contractionary measures signalling the beginning of a so-called “age of austerity” for the country. It was argued that budgetary cuts were the most appropriate means of eliminating deficits and decreasing national debt as percentage of General Domestic Product (GDP). Although the budget for the National Health Service (NHS) was not reduced, a below-the-average increase in funding, and cuts in other areas of public spending, particularly in social care and welfare spending, impacted significantly on the NHS. One of the areas where the impact of austerity was most dramatically felt was in Accidents and Emergency Departments (A&E). A number of economic and statistical reports and quantitative studies have explored and documented the effects of austerity in healthcare in the UK, but there is a paucity of research looking at the effects of austerity from the standpoint of the healthcare professionals. In this paper, we report findings from a qualitative study with healthcare professionals working in A&E departments in England. The study findings are presented thematically in three sections. The main theme that runs through all three sections is the perceptions of austerity as shaping the functioning of A&E departments, of healthcare professions and of professionals themselves. The first section discusses the rising demand for services and resources, and the changed demographic of A&E patients—altering the meaning of A&E from ‘Accidents and Emergencies’ to the Department for ‘Anything and Everything’. The second section in this study’s findings, explores how austerity policies are perceived to affect the character of healthcare in A&E. It discusses how an increased focus on the procedures, time-keeping and the operationalisation of healthcare is considered to detract from values such as empathy in interactions with patients. In the third section, the effects of austerity on the morale and motivations of healthcare professionals themselves are presented. Here, the concepts of moral distress and burnout are used in the analysis of the experiences and feelings of being devalued. From these accounts and insights, we analyse austerity as a catalyst or mechanism for a significant shift in the practice and function of the NHS–in particular, a shift in what is counted, measured and valued at departmental, professional and personal levels in A&E. [ABSTRACT FROM AUTHOR]

This paper studies the impact of managerial traits, i.e. optimism, confidence and risk aversion, on capital structure using a principle-agent framework. We discover that optimistic manager perceives equity as more undervalued than debt, while, confident manager perceives debt as more undervalued than equity. We also find that there exists the level of risk aversion eliminating the impact of optimism and confidence on the leverage. Furthermore, in contrast to rational manager, the optimistic/confident manger has higher level of effort. And then, the increasing in risk aversion reduces the level of effort. Our results are in line with some empirical findings. [ABSTRACT FROM AUTHOR]

The evolution in animals of a first possession convention, in which individuals retain what they are the first to acquire, has often been taken as a foundation for the evolution of human ownership institutions. However, among humans, individuals actually only seldom retain an item they have acquired from the environment, instead typically transferring what they possess to other members of the community, to those in command, or to those who hold a contractual title. This paper presents a novel game-theoretic model of the evolution of ownership institutions as rules governing resource transfers. Integrating existing findings, the model contributes a new perspective on the emergence of communal transfers among hominin large game hunters around 200,000 years ago, of command ownership among sedentary humans in the millennia prior to the transition to agriculture, and of titled property ownership around 5,500 years ago. Since today’s property institutions motivate transfers through the promise of future returns, the analysis presented here suggests that these institutions may be placed under considerable pressure should resources become significantly constrained. [ABSTRACT FROM AUTHOR]

This paper analyses the association between working conditions and physical health using data from the Sixth European Working Conditions Survey (EWCS6) released in 2017. The econometric analysis uses two indicators to describe health status: self-assessed health (SAH), which is a subjective indicator of health; and an objective indicator of health (SICK), which is based on the occurrence of any illness or health problem that has lasted or is expected to last for more than 6 months. The theoretical hypotheses concerning the association between working conditions and SAH and the association between working conditions and SICK are tested using a standard ordered probit model and a standard probit model, respectively. The results show that encouraging working conditions, work environment, and job support are associated with both better self-assessed health and better objective health. [ABSTRACT FROM AUTHOR]

Despite the extensive literature investigating stylometry analysis in authorship attribution research, translator stylometry is an understudied research area. The identification of translator stylometry contributes to many fields including education, intellectual property rights and forensic linguistics. In a two stage process, this paper first evaluates the use of existing lexical measures for the translator stylometry problem. Similar to previous research we found that using vocabulary richness in its traditional form as it has been used in the literature could not identify translator stylometry. This encouraged us to design an approach with the aim of identifying the distinctive patterns of a translator by employing network-motifs. Networks motifs are small sub-graphs which aim at capturing the local structure of a complex network. The proposed approach achieved an average accuracy of 83% in three-way classification. These results demonstrate that classic tools based on lexical features can be used for identifying translator stylometry if they get augmented with appropriate non-parametric scaling. Moreover, the use of complex network analysis and network motifs mining provided made it possible to design features that can solve translator stylometry analysis problems. [ABSTRACT FROM AUTHOR]

There is some evidence that liberal politicians use more complex language than conservative politicians. This evidence, however, is based on a specific set of speeches of US members of Congress and UK members of Parliament. This raises the question whether the relationship between ideology and linguistic complexity is a more general phenomenon or specific to this small group of politicians. To address this question, this paper analyzes 381,609 speeches given by politicians from five parliaments, by twelve European prime ministers, as well as speeches from party congresses over time and across countries. Our results replicate and generalize earlier findings: speakers from culturally liberal parties use more complex language than speakers from culturally conservative parties. Economic left-right differences, on the other hand, are not systematically linked to linguistic complexity. [ABSTRACT FROM AUTHOR]

To flexibly meet users’ demands in cloud computing, it is essential for providers to establish the efficient virtual mapping in datacenters. Accordingly, virtualization has become a key aspect of cloud computing. It is possible to consolidate resources based on the single objective of reducing energy consumption. However, it is challenging for the provider to consolidate resources efficiently based on a multiobjective optimization strategy. In this paper, we present a novel migration algorithm to consolidate resources adaptively using a two-level scheduling algorithm. First, we propose the grey relational analysis (GRA) and technique for order preference by similarity to the ideal solution (TOPSIS) policy to simultaneously determine the hotspots by the main selected factors, including the CPU and the memory. Second, a two-level hybrid heuristic algorithm is designed to consolidate resources in order to reduce costs and energy consumption, mainly depending on the PSO and ACO algorithms. The improved PSO can determine the migrating VMs quickly, and the proposed ACO can locate the positions. Extensive experiments demonstrate that the two-level scheduling algorithm performs the consolidation strategy efficiently during the dynamic allocation process. [ABSTRACT FROM AUTHOR]

There is a rich literature exploring emotional responses to engaging in artistic creative activities such as making music, writing, dancing and crafts. However, it remains unclear how such activities affect our emotions; specifically which mental processes (‘strategies’) are used to regulate our emotional responses. This paper therefore describes the design and validation of a novel instrument measuring types of emotional regulation strategies (ERSs) used when engaging in artistic creative activities: the Emotion Regulation Strategies for Artistic Creative Activities Scale (ERS-ACA). Using data from an initial pilot study (n = 740 adults, 80.4% female, median age 25–34) and a follow-up large internet sample (n = 47,924, 56.7% female, average age 47.3 ± 14.6 years), we followed a theory-driven iterative factor analysis process. Our analyses converged on a final 18-item scale comprising an overall ‘general’ factor of ERSs alongside three subscales: a 7-item factor comprising ‘avoidance strategies’ (such as distraction, suppression and detachment), a 6-item factor comprising ‘approach strategies’ (such as acceptance, reappraisal and problem solving), and a 5-item factor comprising ‘self-development strategies’ (such as enhanced self-identify, improved self-esteem and increased agency). All factors showed strong internal reliability (Cronbach’s alpha: General Factor = 0.93, Factor 1 = 0.9, Factor 2 = 0.88, Factor 3 = 0.88). We confirmed strong convergent and divergent validity, construct validity, consistency of internal reliability and test-retest reliability of the scale in a third study (n = 165, 82.2% female, average age 46.3 ± 12.2 years). In conclusion, artistic creative activities appear to affect our emotions via a number of ERSs that can be broadly classified into three categories: avoidance, approach and self-development. The ERS-ACA scale presented and validated here should support further research into the use of ERSs when engaging in artistic creative activities and enhance our understanding about how these activities affect mental health. [ABSTRACT FROM AUTHOR]

Recent work has shown that listeners process words faster if said by a member of the group that typically uses the word. This paper further explores how the social distributions of words affect lexical access by exploring whether access is facilitated by invoking more abstract social categories. We conduct four experiments, all of which combine an Implicit Association Task with a Lexical Decision Task. Participants sorted real and nonsense words while at the same time sorting older and younger faces (exp. 1), male and female faces (exp. 2), stereotypically male and female objects (exp. 3), and framed and unframed objects, which were always stereotypically male or female (exp. 4). Across the experiments, lexical decision to socially skewed words is facilitated when the socially congruent category is sorted with the same hand. This suggests that the lexicon contains social detail from which individuals make social abstractions that can influence lexical access. [ABSTRACT FROM AUTHOR]

The demand for district level statistics has increased tremendously in Bangladesh due to existence of decentralised approach to governance and service provision. The Bangladesh Demographic Health Surveys (BDHS) provide a wide range of invaluable data at the national and divisional level but they cannot be used directly to produce reliable district-level estimates due to insufficient sample sizes. The small area estimation (SAE) technique overcomes the sample size challenges and can produce reliable estimates at the district level. This paper uses SAE approach to generate model-based district-level estimates of diarrhoea prevalence among under-5 children in Bangladesh by linking data from the 2014 BDHS and the 2011 Population Census. The diagnostics measures show that the model-based estimates are precise and representative when compared to the direct survey estimates. Spatial distribution of the precise estimates of diarrhoea prevalence reveals significant inequality at district-level (ranged 1.1–13.4%) with particular emphasis in the coastal and north-eastern districts. Findings of the study might be useful for designing effective policies, interventions and strengthening local-level governance. [ABSTRACT FROM AUTHOR]