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Abstract concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological issues, and recommendations for future research. In this paper, we urge researchers to go beyond the traditional abstract-concrete dichotomy and consider the multiple dimensions that characterize concepts (e.g., sensorimotor experience, social interaction, conceptual metaphor), as well as the mediating influence of linguistic and cultural context on conceptual representations. We also promote the use of interactive methods to investigate both the comprehension and production of abstract concepts, while also focusing on individual differences in conceptual representations. Overall, we argue that abstract concepts should be studied in a more nuanced way that takes into account their complexity and diversity, which should permit us a fuller, more holistic understanding of abstract cognition. [ABSTRACT FROM AUTHOR]

Reading primary research literature is an essential skill for all scientists and students on science degree programmes, however little is known about how researchers at different career stages interact with and interpret scientific papers. To explore this, we conducted a survey of 260 undergraduate students and researchers in Biological Sciences at a research intensive UK university. Responses to Likert scale questions demonstrated increases in confidence and skill with reading the literature between individuals at each career stage, including between postdoctoral researchers and faculty academics. The survey indicated that individuals at different career stages valued different sections of scientific papers, and skill in reading the results section develops slowly over the course of an academic career. Inexperienced readers found the methods and results sections of research papers the most difficult to read, and undervalued the importance of the results section and critical interpretation of data. These data highlight a need for structured support with reading scientific literature at multiple career stages, and for senior academics to be aware that junior colleagues may prioritise their reading differently. We propose a model for the development of literature processing skills, and consider the need for training strategies to help inexperienced readers engage with primary literature, and therefore develop important skills that underpin scientific careers. We also encourage researchers to be mindful of language used when writing papers, and to be more inclusive of diverse audiences when disseminating their work. [ABSTRACT FROM AUTHOR]

The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing. [ABSTRACT FROM AUTHOR]

The need to complete multiple tasks concurrently is a common occurrence both daily life and in occupational activities, which can often include simultaneous cognitive and physical demands. As one example, there is increasing availability of head-worn display technologies that can be employed when a user is mobile (e.g., while walking). This new method of information presentation may, however, introduce risks of adverse outcomes such as a decrement to gait performance. The goal of this study was thus to quantify the effects of a head-worn display (i.e., smart glasses) on motor variability during gait and to compare these effects with those of other common information displays (i.e., smartphone and paper-based system). Twenty participants completed four walking conditions, as a single task and in three dual-task conditions (three information displays). In the dual-task conditions, the information display was used to present several cognitive tasks. Three different measures were used to quantify variability in gait parameters for each walking condition (using the cycle-to-cycle standard deviation, sample entropy, and the “goal-equivalent manifold” approach). Our results indicated that participants used less adaptable gait strategies in dual-task walking using the paper-based system and smartphone conditions compared with single-task walking. Gait performance, however, was less affected during dual-task walking with the smart glasses. We conclude that the risk of an adverse gait event (e.g., a fall) in head-down walking conditions (i.e., the paper-based system and smartphone conditions) were higher than in single-task walking, and that head-worn displays might help reduce the risk of such events during dual-task gait conditions. [ABSTRACT FROM AUTHOR]

Do highly productive researchers have significantly higher probability to produce top cited papers? Or do high productive researchers mainly produce a sea of irrelevant papers—in other words do we find a diminishing marginal result from productivity? The answer on these questions is important, as it may help to answer the question of whether the increased competition and increased use of indicators for research evaluation and accountability focus has perverse effects or not. We use a Swedish author disambiguated dataset consisting of 48.000 researchers and their WoS-publications during the period of 2008–2011 with citations until 2014 to investigate the relation between productivity and production of highly cited papers. As the analysis shows, quantity does make a difference. [ABSTRACT FROM AUTHOR]

An editorial is presented which discusses the collaborative writing with multiple authors which has additional challenges including varied levels of engagement of coauthors, provision of fair credit through authorship or acknowledgements and acceptance of diversity of work styles. Also discussed are the 10 simple rules for collaboratively writing a multi-authored paper which include to build a writing team wisely; to create a data management plan and to jointly decide on authorship guidelines.

All papers will be fully peer reviewed with publication of the full issue scheduled for later in the same year. Belief in conspiracy theories has become widespread, from COVID-19 and vaccinations to climate change and QAnon. [Extracted from the article]

This essay takes up the framework of Semiotic Cultural Psychology, which in last decade was very productive in analyzing societal phenomena. Digging into complex sensemaking mechanisms, underlying the interaction between individual and his surrounding environment, has consolidated a base of empirical data gathered from different societies. Aiming to better understand the role of culture in this interaction, the current paper proposes to bridge these findings of observable macro-processes with the ones from the Active inference theory and cognitive science. Similarities between the two frameworks, as well as possible benefits of employing them for one goal, are discussed in this paper. [ABSTRACT FROM AUTHOR]

In this paper, we reexamined the typical analysis methods of a visuomotor sequence learning task, namely the ASRT task (J. H. Howard & Howard, 1997). We pointed out that the current analysis of data could be improved by paying more attention to pre-existing biases (i.e. by eliminating artifacts by using new filters) and by introducing a new data grouping that is more in line with the task’s inherent statistical structure. These suggestions result in more types of learning scores that can be quantified and also in purer measures. Importantly, the filtering method proposed in this paper also results in higher individual variability, possibly indicating that it had been masked previously with the usual methods. The implications of our findings relate to other sequence learning tasks as well, and opens up opportunities to study different types of implicit learning phenomena. [ABSTRACT FROM AUTHOR]

Personal motivation is a key factor in the service of foster care, impending both on the welfare of the child and on the satisfaction of the carer. This paper explores the benefits, challenges and dilemmas involved in the job of professional (i.e. state-supported) foster carer in Romania–a country where the issue of child protection has drawn a great deal of international attention over the last thirty years. The principal hypothesis concerns whether the benefits, challenges and dilemmas identified by foster carers are influenced by the factors that led to their taking up this kind of work. Quantitative research was conducted using a questionnaire as the main tool. The paper takes a descriptive, cross-sectional and multifactorial approach. Sampling was carried out by self-selecting method, and the study involved 51 participants. The research project identified a statistically significant variation in the challenges and dilemmas reported by foster carers. Thus, the results of the study show that the majority of the carers indicate a primarily intrinsic motivation for their work. By way of conclusion, it is argued that social workers, operating in collaboration with multidisciplinary teams, can offer carers support in managing more difficult periods in the child–carer relationship, thus enhancing the sustainability of the foster care service. [ABSTRACT FROM AUTHOR]

The interaction between phenotypic plasticity, e.g. learning, and evolution is an important topic both in Evolutionary Biology and Machine Learning. The evolution of learning is commonly studied in Evolutionary Biology, while the use of an evolutionary process to improve learning is of interest to the field of Machine Learning. This paper takes a different point of view by studying the effect of learning on the evolutionary process, the so-called Baldwin effect. A well-studied result in the literature about the Baldwin effect is that learning affects the speed of convergence of the evolutionary process towards some genetic configuration, which corresponds to the environment-induced plastic response. This paper demonstrates that learning can change the outcome of evolution, i.e., lead to a genetic configuration that does not correspond to the plastic response. Results are obtained both analytically and experimentally by means of an agent-based model of a foraging task, in an environment where the distribution of resources follows seasonal cycles and the foraging success on different resource types is conditioned by trade-offs that can be evolved and learned. This paper attempts to answer a question that has been overlooked: whether learning has an effect on what genotypic traits are evolved, i.e. the selection of a trait that enables a plastic response changes the selection pressure on a different trait, in what could be described as co-evolution between different traits in the same genome. [ABSTRACT FROM AUTHOR]

Several lifetime distributions have played an important role to fit survival data. However, for some of these models, the computation of maximum likelihood estimators is quite difficult due to presence of flat regions in the search space, among other factors. Several well-known derivative-based optimization tools are unsuitable for obtaining such estimates. To circumvent this problem, we introduce the AdequacyModel computational library version 2.0.0 for the R statistical environment with two major contributions: a general optimization technique based on the Particle Swarm Optimization (PSO) method (with a minor modification of the original algorithm) and a set of statistical measures for assessment of the adequacy of the fitted model. This library is very useful for researchers in probability and statistics and has been cited in various papers in these areas. It serves as the basis for the Newdistns library (version 2.1) published in an impact journal in the area of computational statistics, see . It is also the basis of the Wrapped library (version 2.0), see . A third package making use of the AdequacyModel library can be found in . In addition, the proposed library has proved to be very useful for maximizing log-likelihood functions with complex search regions. The library provides a greater control of the optimization process by introducing a stop criterion based on a minimum number of iterations and the variance of a given proportion of optimal values. We emphasize that the new library can be used not only in statistics but in physics and mathematics as proved in several examples throughout the paper. [ABSTRACT FROM AUTHOR]

The use of elasticities of substitution between inputs is a standard method for addressing the effect of a change in the mix of inputs used for production from a technical or cost standpoint. Most estimation methods use parametric production or cost functions or frontiers to estimate these elasticities. A potentially useful nonparametric alternative is data envelopment analysis (DEA). The purpose of this paper is to derive elasticities of input substitution for both technical and cost frontiers using DEA, extending the use of this approach in the field of economics and associated fields. The paper provides derivations for both Hicksian (production and cost frontier) and Morishima (cost frontier) elasticities of input substitution, as well as a parsimonious method for estimating them using DEA. The derivations are presented using an agricultural example form Kansas, USA. [ABSTRACT FROM AUTHOR]

Executives act based on their experiences, values, personality and personal interpretation of the situations which they face in their companies. Investigations in the field of Behavioral Corporate Finance have determined that there are some relations between CEOs’ personal traits and financial decisions of large companies, but these results are based on indirect personal trait measurements and on public companies. To see whether such relations also exist between CEOs’ personal traits and the financial structure of large private companies, we used psychometric tests to measure their level of optimism, risk attitude and affect heuristic, collected financial data for a period of fourteen years, and considered the economic situation of the country as a key factor in these relations. This paper reports the relationship of executives’ personal traits with the financial structure of large Spanish companies for the period 2001–2014. We observed that executives’ high optimism (and risk aversion attitude) is positively (negatively) related to long-term debt, whilst positive affect is directly associated to the financial leverage and short-term debt. This paper also reports a change of relations when taking into account the country’s economic situation. In effect, by considering this new variable, executives’ risk aversion is seen to be associated to financial leverage and short-term debt, whilst CEOs’ positive affect is linked to long-term debt. These relations are strongly moderated and they become statistically significant in a contracting economic period. In conclusion, the links between CEOs’ personal traits and financial structure of large private Spanish companies make sense when the effect of the economic situation is taken into account. Furthermore, the awareness of these links helps to understand the financial decisions taken within large Spanish companies. [ABSTRACT FROM AUTHOR]

By utilizing cognitive mapping and leveraging georeferenced text data, this paper aims to suggest a new visualization method that combines the advantages of both conventional and state-of-the-art research techniques to depict the collective identity of place in a single image. The study addressed two research questions: (1) Can crowd-sourced text data be utilized in representing place identity? (2) Can collective place identity be expressed in the form of a cognitive map? By confirming that text data gathered from social media effectively demonstrate people’s behaviors and perceptions related to places, we propose a novel method to create a visual representation of urban identity–a “crowd-sourced cognitive map”. In particular, to improve the conventional cognitive mapping method to depict the collective identity of a city, we draw cognitive maps of Bundang and Ilsan developed in the 1990s, as well as Songdo and Dongtan developed in the 2000s, just outside of the administrative boundaries of Seoul in Korea, through a computational method based on crowd-sourced opinions collected from social media. We open the possibility for the use of social media text data to capture the identity of cities and suggest a graphical image through which people without prior information could also easily apprehend the overall image of a city. The work in this paper is expected to provide a methodological technique for appropriate decision-making and the evaluation of urban identity to shape a more unique and imageable city. [ABSTRACT FROM AUTHOR]

The paper introduces structural diversity as a new approach to quantify the complexity of technologies. By modeling technologies as combinatorial networks, a measure of technological complexity is derived that represents the diversity of (sub-)network topologies in these networks. It is further argued that this measure can be empirically approximated with the Network Diversity Score (NDS). The paper also presents an application of this approach to European patent data from 1980 to 2015. On this basis, the measure of structural diversity is shown to replicate a number of stylized facts commonly associated with technological complexity: Complexity increases over time and younger technologies are more complex than older technologies. Complex technologies are also associated to larger R&D efforts and require more collaborative R&D activities. Lastly, when controlling for technologies’ size, technologies scoring high on structural diversity are also shown to concentrate in space. [ABSTRACT FROM AUTHOR]

In this paper, we propose an Emotional Trigger System to impart an automatic emotion expression ability within the humanoid robot REN-XIN, in which the Emotional Trigger is an emotion classification model trained from our proposed Word Mover’s Distance(WMD) based algorithm. Due to the long time delay of the WMD-based Emotional Trigger System, we propose an enhanced Emotional Trigger System to enable a smooth interaction with the robot in which the Emotional Trigger is replaced by a conventional convolution neural network and a long short term memory network (CNN_LSTM)-based deep neural network. In our experiments, the CNN_LSTM based model only need 10 milliseconds or less to finish the classification without a decrease in accuracy, while the WMD-based model needed approximately 6-8 seconds to give a result. In this paper, the experiments are conducted based on the same sub-data sets of the Chinese emotional corpus(Ren_CECps) used in former WMD experiments: one comprises 50% data for training and 50% for testing(1v1 experiment), and the other comprises 80% data for training and 20% for testing(4v1 experiment). The experiments are conducted using WMD, CNN_LSTM, CNN and LSTM. The results show that CNN_LSTM obtains the best F1 score (0.35) in the 1v1 experiment and almost the same accuracy of F1 scores (0.366 vs 0.367) achieved by WMD in the 4v1 experiment. Finally, we present demonstration videos with the same scenario to show the performance of robot control driven by CNN_LSTM-based Emotional Trigger System and WMD-based Emotional Trigger System. To improve the comparison, total manual-control performance is also recorded. [ABSTRACT FROM AUTHOR]

The University of KwaZulu-Natal has introduced a new language policy requiring all students who have not done Zulu as a first (or second) language at school to complete a six-month course in Zulu as part of their undergraduate curriculum. Given that English is the medium of instruction that is being used for all their other courses, the time that these students have had to spend learning this new language may be adversely affecting the marks that they could be getting for their other courses. Having to do a course in Zulu is also preventing them from being able to take another course in their chosen area of study. If one were able to randomly assign students to the group who have to take the Zulu course, then any difference in performance between the two groups could be directly attributed to the new language policy that is being introduced at the university. Given the context of this paper, however, such a random allocation is not possible. Students who have not done Zulu at school have to eventually complete a course in Zulu before graduating. If this cohort differs (in any other way) from those who do not have to take this course, then any observed difference in overall performance between the two groups may be a result of these group differences rather than the new rule that has been implemented. Methodology: This paper uses regression adjustment and entropy matching to achieve an appropriate balance between the two groups. Having achieved this balance any difference in the overall performance between the two groups can then be attributed directly to the new language policy that has been implemented. Our results indicate, after matching, that a significant difference in performance between the two groups occurs with Black African Zulu home language speakers in particular not performing as well as students from the other race and language groups. The data came from the University of KwaZulu-Natal and the study has been approved by the University Ethics committee and Research committee. Results and conclusions: Using a weighted mean of marks to measure performance, the ATT estimates that result indicate that students in the treated group would all perform significantly better had they been allowed instead to enrol in the non-treated group. Furthermore, Zulu home language speakers, who are not actually forced to take this course, are significantly underperforming whether they have chosen to take this course in Zulu or not. Surprisingly, their underperformance is worse in the treated group. Because one would expect them to be scoring a higher mark for Zulu in this treated group, forfeiting the chance to take another course in their chosen area of study is clearly affecting the type of mark they could be getting for their other courses had they chosen to remain in the non-treated group. With English being the medium of instruction at this university, should the university not also consider introducing a compulsory course in English for these Zulu home language speakers? Females are doing better than males in both groups. The effect being stronger in the treated group suggests that females appear to cope better with the learning of a new language. Significant college effects are also being observed, suggesting that this new language rule possibly needs to be adjusted for the college a student wants to study in. [ABSTRACT FROM AUTHOR]

Due to their simplicity and operating mode, magnetic loops are one of the most used traffic sensors in Intelligent Transportation Systems (ITS). However, at this moment, their potential is not being fully exploited, as neither the speed nor the length of the vehicles can be surely ascertained with the use of a single magnetic loop. In this way, nowadays the vast majority of them are only being used to measure traffic flow and count vehicles on urban and interurban roads. This is the reason why we presented in a previous paper the double magnetic loop, capable of improving the features and functionalities of the conventional single loop without increasing the cost or introducing additional complexity. In that paper, it was introduced their design and peculiarities, how to calculate their magnetic field and three different methods to calculate their inductance. Therefore, with the purpose of improving the existing infrastructure and providing it with greater potential and reliability, this paper will focus on justifying and demonstrating the advantages offered by these double loops versus the conventional ones. This will involve analyzing the magnetic profiles generated by the passage of vehicles over double loops and comparing them with those already known. Moreover, it will be shown how the vehicle speed, the traffic direction and many other data can be obtained more easily and with less margin of error by using these new inductance signatures. [ABSTRACT FROM AUTHOR]

Background: Up to 1.45 billion people currently suffer from soil transmitted helminth infection, with the largest burden occurring in Africa and Asia. Safe and cost effective deworming treatment exists, but there is a debate about mass distribution of this treatment in high prevalence settings. While the World Health Organization recommends mass administration of anthelmintic drugs for preschool and school-aged children in high (>20%) prevalence settings, and several long run follow up studies of an influential trial have suggested large benefits that persist over time, recent systematic reviews have called this recommendation into question. Methods and findings: This paper analyzes the long-term impact of a cluster-randomized trial in eastern Uganda that provided mass deworming treatment to preschool aged children from 2000 to 2003 on the numeracy and literacy skills of children and young adults living in those villages in 2010-2015. This study uses numeracy and literacy data collected seven to twelve years after the end of the deworming trial in a randomly selected subset of communities from the original trial, by an education-focused survey that had no relationship to the deworming study. Building on an earlier working paper which used data from 2010 and 2011 survey rounds, this paper uses an additional four years of numeracy and literacy data (2012, 2013, 2014, and 2015). Aggregating data from all survey rounds, the difference between numeracy scores in treatment versus control communities is 0.07 standard deviations (SD) (95% CI -0.10, 0.24, p = 0.40), the difference in literacy scores is 0.05 SD (95% CI -0.16, 0.27, p = 0.62), and the difference in total scores is 0.07 SD (95% CI -0.11, 0.25, p = 0.44). There are significant differences in program impact by gender, with numeracy and literacy differentially positively affected for girls, and by age, with treatment effects larger for the primary school aged subsample. There are also significant treatment interactions for those living in households with more treatment-eligible children. There is no evidence of differential treatment effects on age at program eligibility or number of years of program eligibility. Conclusions: Mass deworming of preschool aged children in high prevalence communities in Uganda resulted in no statistically significant gains in numeracy or literacy 7-12 years after program completion. Point estimates were positive but imprecise; the study lacked sufficient power to rule out substantial positive effects or more modest negative effects. However, there is suggestive evidence that deworming was relatively more beneficial for girls, primary school aged children, and children living in households with other treated children. Research approval: As this analysis was conducted on secondary data which is publicly available, no research approval was sought or received. All individual records were anonymized by the data provider prior to public release. [ABSTRACT FROM AUTHOR]

Background: In order to make informed decisions about how best to support children and young people with disabilities, effective strategies that facilitate active and meaningful participation in school are required. Clinical factors, diagnosis or impairments somewhat helpful in determining what should be provided in interventions. However, clinical factors alone will not offer a clear view of how to support participation. It is helpful then to look at wider psychosocial and environmental factors. The aim of this review was to synthesise evidence of psychosocial and environmental factors associated with school participation of 4–12 year old children with disabilities to inform the development of participation-fostering interventions. Methods: A systematic search and synthesis using realist methods was conducted of published research. Papers had to include consideration of psychosocial and/or environment factors for school participation of children with disabilities. The review was completed in accordance with the Realist and Meta-narrative Evidence Syntheses: Evolving Standards (RAMESES) and Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Papers were identified via Boolean search of the electronic databases MEDLINE, CINAHL, PhycINFO and ERIC (January 2006-October 2018). Appraisal focussed on contributions in terms of whether the articles are appropriate for the review (relevance) and research quality (rigour). Data were analyzed using content and thematic analysis methods using a realist framework. A narrative synthesis of results was reported. Results and implications: We identified 1828 papers in the initial search. Seventy two papers were included in the final synthesis. Synthesis of findings led to three overarching mechanisms representing psychosocial factors for children (1) identity (2) competence and (3) experience of mind and body. Environmental aspects (context) compromised five interrelated areas: (1) structures and organization, (2) peers, (3) adults, (4) space and (5) objects. Our synthesis provides insights on how professionals may organize efforts to improve children’s participation. Consideration of these findings will help to proactively deal with suboptimal participation outcomes. Development of theoretically determined assessments and interventions for management of school participation are now required. [ABSTRACT FROM AUTHOR]

Understanding expression levels of proteins and their interactions is a key factor to diagnose and explain the Down syndrome which can be considered as the most prevalent reason of intellectual disability in human beings. In the previous studies, the expression levels of 77 proteins obtained from normal genotype control mice and from trisomic Ts65Dn mice have been analyzed after training in contextual fear conditioning with and without injection of the memantine drug using statistical methods and machine learning techniques. Recent studies have also pointed out that there may be a linkage between the Down syndrome and the immune system. Thus, the research presented in this paper aim at in silico identification of proteins which are significant to the learning process and the immune system and to derive the most accurate model for classification of mice. In this paper, the features are selected by implementing forward feature selection method after preprocessing step of the dataset. Later, deep neural network, gradient boosting tree, support vector machine and random forest classification methods are implemented to identify the accuracy. It is observed that the selected feature subsets not only yield higher accuracy classification results but also are composed of protein responses which are important for the learning and memory process and the immune system. [ABSTRACT FROM AUTHOR]

Text representation can map text into a vector space for subsequent use in numerical calculations and processing tasks. Word embedding is an important component of text representation. Most existing word embedding models focus on writing and utilize context, weight, dependency, morphology, etc., to optimize the training. However, from the linguistic point of view, spoken language is a more direct expression of semantics; writing has meaning only as a recording of spoken language. Therefore, this paper proposes the concept of a pronunciation-enhanced word embedding model (PWE) that integrates speech information into training to fully apply the roles of both speech and writing to meaning. This paper uses the Chinese language, English language and Spanish language as examples and presents several models that integrate word pronunciation characteristics into word embedding. Word similarity and text classification experiments show that the PWE outperforms the baseline model that does not include speech information. Language is a storehouse of sound-images; therefore, the PWE can be applied to most languages. [ABSTRACT FROM AUTHOR]

Background: Until recently, the Chagas disease vector, Triatoma infestans, was widespread in Arequipa, Perú, but as a result of a decades-long campaign in which over 70,000 houses were treated with insecticides, infestation prevalence is now greatly reduced. To monitor for T. infestans resurgence, the city is currently in a surveillance phase in which a sample of houses is selected for inspection each year. Despite extensive data from the control campaign that could be used to inform surveillance, the selection of houses to inspect is often carried out haphazardly or by convenience. Therefore, we asked, how can we enhance efforts toward preventing T. infestans resurgence by creating the opportunity for vector surveillance to be informed by data? Methodology/principal findings: To this end, we developed a mobile app that provides vector infestation risk maps generated with data from the control campaign run in a predictive model. The app is intended to enhance vector surveillance activities by giving inspectors the opportunity to incorporate the infestation risk information into their surveillance activities, but it does not dictate which houses to surveil. Therefore, a critical question becomes, will inspectors use the risk information? To answer this question, we ran a pilot study in which we compared surveillance using the app to the current practice (paper maps). We hypothesized that inspectors would use the risk information provided by the app, as measured by the frequency of higher risk houses visited, and qualitative analyses of inspector movement patterns in the field. We also compared the efficiency of both mediums to identify factors that might discourage risk information use. Over the course of ten days (five with each medium), 1,081 houses were visited using the paper maps, of which 366 (34%) were inspected, while 1,038 houses were visited using the app, with 401 (39%) inspected. Five out of eight inspectors (62.5%) visited more higher risk houses when using the app (Fisher’s exact test, p < 0.001). Among all inspectors, there was an upward shift in proportional visits to higher risk houses when using the app (Mantel-Haenszel test, common odds ratio (OR) = 2.42, 95% CI 2.00–2.92), and in a second analysis using generalized linear mixed models, app use increased the odds of visiting a higher risk house 2.73-fold (95% CI 2.24–3.32), suggesting that the risk information provided by the app was used by most inspectors. Qualitative analyses of inspector movement revealed indications of risk information use in seven out of eight (87.5%) inspectors. There was no difference between the app and paper maps in the number of houses visited (paired t-test, p = 0.67) or inspected (p = 0.17), suggesting that app use did not reduce surveillance efficiency. Conclusions/significance: Without staying vigilant to remaining and re-emerging vector foci following a vector control campaign, disease transmission eventually returns and progress achieved is reversed. Our results suggest that, when provided the opportunity, most inspectors will use risk information to direct their surveillance activities, at least over the short term. The study is an initial, but key, step toward evidence-based vector surveillance. [ABSTRACT FROM AUTHOR]

Knowledge and motivation of a teacher are two unchallenged, essential characteristics for successful education. Whilst the relevance of teachers’ professional knowledge for successful students’ learning has been studied in a sophisticated manner for years, the meaning of teachers’ motivational orientations for students’ performance still lacks a differentiated consideration. This construct is conceptualized by three domains: (1) self-efficacy, (2) subject-specific enthusiasm, and (3) enthusiasm for teaching the subject. Motivational orientations overall have shown to be relevant predictors of students’ learning. However, there are several dimensions of motivation and their relative importance remains unclear. Our study goes beyond the available findings by considering in detail each of the three domains’ relations to students’ performance. Thus, we aim to further contribute to the clarification of the predictors of students’ performance in school teaching. For this purpose, we conducted a study with 48 biology teachers and their 1036 students. To assess the three domains of teachers’ motivational orientations, we applied paper and pencil tests. Concept maps and paper and pencil tests were used to measure students’ performance. By specifying multilevel structural equation models, we examined the relationship between the domains of teachers’ motivational orientations and the performance of the students. Our results reveal no relationship between teachers’ self-efficacy and students’ performance, but a significant positive relationship between the latter and teachers’ subject-specific enthusiasm. Moreover, our results show a positive trend in the relationship between enthusiasm for teaching the subject and students’ performance. The results provide a differentiated picture about the importance of motivational orientations for the characterisation of an effective teacher. We discuss our findings in terms of possible effect mechanisms and their relevance for further research on teacher motivation and the improvement of teacher education programmes. [ABSTRACT FROM AUTHOR]

This paper uses text data mining to identify long-term developments in tourism academic research from the perspectives of thematic focus, geography, and gender of tourism authorship. Abstracts of papers published in the period of 1970–2017 in high-ranking tourist journals were extracted from the Scopus database and served as data source for the analysis. Fourteen subject areas were identified using the Latent Dirichlet Allocation (LDA) text mining approach. LDA integrated with GIS information allowed to obtain geography distribution and trends of scholarly output, while probabilistic methods of gender identification based on social network data mining were used to track gender dynamics with sufficient confidence. The findings indicate that, while all 14 topics have been prominent from the inception of tourism studies to the present day, the geography of scholarship has notably expanded and the share of female authorship has increased through time and currently almost equals that of male authorship. [ABSTRACT FROM AUTHOR]

In clinical neuropsychology the cognitive abilities of neurological patients are commonly estimated using well-established paper-based tests. Typically, scores on some tests remain relatively well preserved, whilst others exhibit a significant and disproportionate decline. Scores on those tests that measure preserved cognitive functions (so-called ‘hold’ tests) may be used to estimate premorbid abilities, including scores in non-hold tests that would have been expected prior to the onset of cognitive impairment. Many hold tests entail word reading, with each word being graded as correctly or incorrectly pronounced. Inevitably, such tests are likely to contain words that provide little or no diagnostic power (i.e., can be eliminated without negatively affecting prediction accuracy). In this paper, a genetic algorithm is developed and demonstrated, using n = 92 neurologically healthy participants, to identify optimal word subsets from the National Adult Reading Test that minimize the mean error in predicting the most widely used clinical measure of IQ and cognitive ability, the Wechsler Adult Intelligence Scale Fourth Edition IQ. In addition to requiring only 17–20 of the original 50 words (suggesting that this test could be revised to be up to 66% shorter) and minimizing mean prediction error, the algorithm increases the proportion of the variance in the predicted variable explained in comparison to using all words (from r2 = 0.46 to r2 = 0.61). In a clinical setting this would improve estimates of premorbid cognitive function and, if an abbreviated revision to this test were to be adopted, reduce the arduousness of the test for patients. The proposed method is evaluated with jackknifing and leave one out cross validation. The general approach may be used to optimize the relationship between any two psychological tests by finding the question subset in one test that minimizes the prediction error in a second test by training the genetic algorithm using data collected from participants upon whom both tests have been administered. This approach may also be used to develop new predictive tests, since it provides a method to identify an optimal subset of a set of candidate questions (for which empirical data have been collected) that maximizes prediction accuracy and the proportion of variance in the predicted variable that can be explained. [ABSTRACT FROM AUTHOR]

Ratings are present in many areas of assessment including peer review of research proposals and journal articles, teacher observations, university admissions and selection of new hires. One feature present in any rating process with multiple raters is that different raters often assign different scores to the same assessee, with the potential for bias and inconsistencies related to rater or assessee covariates. This paper analyzes disparities in ratings of internal and external applicants to teaching positions using applicant data from Spokane Public Schools. We first test for biases in rating while accounting for measures of teacher applicant qualifications and quality. Then, we develop model-based inter-rater reliability (IRR) estimates that allow us to account for various sources of measurement error, the hierarchical structure of the data, and to test whether covariates, such as applicant status, moderate IRR. We find that applicants external to the district receive lower ratings for job applications compared to internal applicants. This gap in ratings remains significant even after including measures of qualifications and quality such as experience, state licensure scores, or estimated teacher value added. With model-based IRR, we further show that consistency between raters is significantly lower when rating external applicants. We conclude the paper by discussing policy implications and possible applications of our model-based IRR estimate for hiring and selection practices in and out of the teacher labor market. [ABSTRACT FROM AUTHOR]

Objective: To explore intersections of social determinants of maternal healthcare utilization using the Classification and Regression Trees (CART) algorithm which is a machine-learning method used to construct prediction models. Methods: Institutional review board approval for this study was granted from Public Health Service—Ethical Review Board (PHS-ERB) and from the Health Ministry Screening Committee (HMSC) facilitated by Indian Council for Medical Research (ICMR). IRB review and approval for the current analyses was obtained from University of California, San Diego. Cross-sectional data were collected from women with children aged 0–11 months (n = 5,565) from rural households in 25 districts of Uttar Pradesh, India. Participants were surveyed on maternal healthcare utilization including registration of pregnancy (model-1), receipt of antenatal care (ANC) during pregnancy (model-2), and delivery at health facilities (model -3). Social determinants of health including wealth, social group, literacy, religion, and early age at marriage were captured during the survey. The Classification and Regression Tree (CART) algorithm was used to explore intersections of social determinants of healthcare utilization. Results: CART analyses highlight the intersections, particularly of wealth and literacy, in maternal healthcare utilization in Uttar Pradesh. Model-1 documents that women who are poorer, illiterate and Muslim are less likely to have their pregnancies registered (71.4% vs. 86.0% in the overall sample). Model-2 documents that poorer, illiterate women had the lowest ANC coverage (37.7% vs 45% in the overall sample). Model-3, developed for deliveries at health facilities, highlighted that illiterate and poor women have the lowest representation among facility deliveries (59.6% vs. 69% in the overall sample). Conclusion: This paper explores the interactions between determinants of maternal healthcare utilization indicators. The findings in this paper highlights that the interaction of wealth and literacy can play a very strong role in accentuating or diminishing healthcare utilization among women. The study also reveals that religion and women’s age at marriage also interact with wealth and literacy to create substantial disparities in utilization. The study provides insights into the effect of intersections of determinants, and highlights the importance of using a more nuanced understanding of the impact of co-occurring forms of marginalization to effectively tackle inequities in healthcare utilization. [ABSTRACT FROM AUTHOR]

This paper proposes a computer model of information behavior to study information security professionals and an architecture, which mimics the way our brain learns new concepts to simulate this behavior computationally. Used to represent and describe any domain of knowledge, ontologies may be used to study human information behavior and show some of the concepts and relationships involved in this field of knowledge. A deep knowledge of the core concepts underpinning this field can provide us with a solid basis for constructing a model. Computer-programming tools can be used not only to capture the ideas that make up this field of Knowledge but can also simulate the human information behavior. The use of computers also allows us to crawl data over the Internet and process large amounts of them in order to find patterns with some specific characteristics. In the paper, we also present the current state of this research and the challenges of the model. [ABSTRACT FROM AUTHOR]

It was recently reported that men self-cite >50% more often than women across a wide variety of disciplines in the bibliographic database JSTOR. Here, we replicate this finding in a sample of 1.6 million papers from Author-ity, a version of PubMed with computationally disambiguated author names. More importantly, we show that the gender effect largely disappears when accounting for prior publication count in a multidimensional statistical model. Gender has the weakest effect on the probability of self-citation among an extensive set of features tested, including byline position, affiliation, ethnicity, collaboration size, time lag, subject-matter novelty, reference/citation counts, publication type, language, and venue. We find that self-citation is the hallmark of productive authors, of any gender, who cite their novel journal publications early and in similar venues, and more often cross citation-barriers such as language and indexing. As a result, papers by authors with short, disrupted, or diverse careers miss out on the initial boost in visibility gained from self-citations. Our data further suggest that this disproportionately affects women because of attrition and not because of disciplinary under-specialization. [ABSTRACT FROM AUTHOR]

Glioma detection and segmentation is a challenging task for radiologists and clinicians. The research reported in this paper seeks to develop a better clinical decision support algorithm for clinicians diagnosis. This paper presents a probabilistic method for detection and segmentation between abnormal tissue regions and brain tumour (tumour core and edema) portions from Magnetic Resonance Imaging (MRI). A framework is constructed to learn structure of undirected graphical models that can represent the spatial relationships among variables and apply it to glioma segmentation. Compared with the pixel of image, the superpixel is more consistent with human visual cognition and contains less redundancy, thus, the superpixels are considered as the basic unit of structure learning and glioma segmentation scheme. ℓ1-regularization techniques are applied to learn the appropriate structure for modeling graphical models. Conditional Random Fields (CRF) are used to model the spatial interactions among image superpixel regions and their measurements. A number of features including statistics features, the combined features from the local binary pattern as well as gray level run length, curve features, and fractal features were extracted from each superpixel. The features are then passed by ℓ1-regularization to ensure a robust classification. The proposed method is compared with support vector machine and Fuzzy c-means to classify each superpixel into normal and abnormal tissue. The proposed system is tested for the presence of low grade as well as high grade glioma tumors on images collected from BRATS2013, BRATS2015 data set and Henan Provincial People’s Hospital (HNPPH) data set. The experiments performed provides similarity between segmented and truth image up to 91.5% by correlation method. [ABSTRACT FROM AUTHOR]

Since 1997 a considerable effort has been spent on the study of the swap (switch) Markov chains on graphic degree sequences. All of these results assume some kind of regularity in the corresponding degree sequences. Recently, Greenhill and Sfragara published a breakthrough paper about irregular normal and directed degree sequences for which rapid mixing of the swap Markov chain is proved. In this paper we present two groups of results. An example from the first group is the following theorem: let be a directed degree sequence on n vertices. Denote by Δ the maximum value among all in- and out-degrees and denote by the number of edges in the realization. Assume furthermore that . Then the swap Markov chain on the realizations of is rapidly mixing. This result is a slight improvement on one of the results of Greenhill and Sfragara. An example from the second group is the following: let d be a bipartite degree sequence on the vertex set U ⊎ V, and let 0 < c1 ≤ c2 < |U| and 0 < d1 ≤ d2 < |V| be integers, where c1 ≤ d(v) ≤ c2: ∀v ∈ V and d1 ≤ d(u) ≤ d2: ∀u ∈ U. Furthermore assume that (c2 − c1 − 1)(d2 − d1 − 1) < max{c1(|V| − d2), d1(|U| − c2)}. Then the swap Markov chain on the realizations of d is rapidly mixing. A straightforward application of this latter result shows that when a random bipartite or directed graph is generated under the Erdős—Rényi G(n, p) model with mild assumptions on n and p then the degree sequence of the generated graph has, with high probability, a rapidly mixing swap Markov chain on its realizations. [ABSTRACT FROM AUTHOR]

Over the past decades, plagiarism has been classified as a multi-layer phenomenon of dishonesty that occurs in higher education. A number of research papers have identified a host of factors such as gender, socialisation, efficiency gain, motivation for study, methodological uncertainties or easy access to electronic information via the Internet and new technologies, as reasons driving plagiarism. The paper at hand examines whether such factors are still effective and if there are any differences between German and Slovene students’ factors influencing plagiarism. A quantitative paper-and-pencil survey was carried out in Germany and Slovenia in 2017/2018 academic year, with a sample of 485 students from higher education institutions. The major findings of this research reveal that easy access to information-communication technologies and the Web is the main reason driving plagiarism. In that regard, there are no significant differences between German and Slovene students in terms of personal factors such as gender, motivation for study, and socialisation. In this sense, digitalisation and the Web outrank national borders. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we argue that awareness comes in degrees, and we propose a novel multi‐factor account that spans both subjective experiences and perceptual representations. At the subjective level, we argue that conscious experiences can be degraded by being fragmented, less salient, too generic, or flash‐like. At the representational level, we identify corresponding features of perceptual representations—their availability for working memory, intensity, precision, and stability—and argue that the mechanisms that affect these features are what ultimately modulate the degree of awareness. We conclude the paper by demonstrating why the original interpretations of certain empirical findings that apparently pose problems for our account are, in fact, flawed. [ABSTRACT FROM AUTHOR]

The cognitive science of religion (CSR) is distinctive in its systematic methodology and its interdisciplinary nature. In the field of the study of religion, however, scholars are hardly receptive to CSR because of its "scientific" nature. The reason for this is that CSR is understood as distinct from other studies, nevertheless it has humanistic backgrounds. In order to investigate the intellectual backgrounds of CSR, the paper will describe the initial development of CSR by introducing researches and academic cooperation in the period from the 1990s to the early 2000s. Moreover, by examining academic contexts, what the emergence of CSR brought about to the study of religion will be clarified. CSR emerged as a result of the debate between modernist and postmodernist, connecting various views and resulting in a great shift in the intellectual landscape. This interdisciplinary role can be seen as the most important achievement of CSR. [ABSTRACT FROM AUTHOR]

This paper examines how to maximize contribution in public good dilemmas by arranging people into homogeneous or heterogeneous subgroups. Past studies on the effect of homogeneity of efficacy have exclusively manipulated group composition in their experimental designs, which might have imposed a limit on ecological validity because group membership may not be easily changed in reality. In this study, we maintained the same group composition but varied the subgroup composition. We developed a public good dilemmas paradigm in which participants were assigned to one of the four conditions (high- vs. low-efficacy; homogeneous vs. heterogeneous subgroup) to produce their endowments and then to decide how much to contribute. We found that individuals in homogeneous and heterogeneous subgroups produced a similar amount and proportion of contribution, which was due to the two mediating effects that counteracted each other, namely (a) perceived efficacy relative to subgroup and (b) expectation of contribution of other subgroup members. This paper demonstrates both the pros and cons of arranging people into homogeneous and heterogeneous subgroups of efficacy. [ABSTRACT FROM AUTHOR]

With the convergence of various broadcasting systems, the amount of content available in mobile terminals including IPTV has significantly increased. In this paper, we propose a system that enables users to schedule programs considering both section video clips and full video clips based on the user detection method with similar preference. And, since the system constituting the contents can be classified according to the program, the proposed method can store a program desired by the user, and thus create and schedule a kind of individual channel. Experimental results show that the proposed method has a higher prediction accuracy; this is accomplished by comparing existing channel recommendation methods with the program recommendation methods proposed in this paper. [ABSTRACT FROM AUTHOR]

Background: Due to the disease’s progressive nature, advance care planning (ACP) is recommended for people with early stage dementia. General practitioners (GPs) should initiate ACP because of their longstanding relationships with their patients and their early involvement with the disease, however ACP is seldom applied. Aim: To determine the barriers and facilitators faced by GPs related to ACP with people with dementia. Data sources: We systematically searched the relevant databases for papers published between January 1995 and December 2016, using the terms: primary healthcare, GP, dementia, and ACP. We conducted a systematic integrative review following Whittemore and Knafl’s method. Papers containing empirical data about GP barriers and/or facilitators regarding ACP for people with dementia were included. We evaluated quality using the Mixed-Method-Appraisal-Tool and analyzed data using qualitative content analysis. Results: Ten qualitative, five quantitative, and one mixed-method paper revealed four themes: timely initiation of ACP, stakeholder engagement, important aspects of ACP the conversation, and prerequisites for ACP. Important barriers were: uncertainty about the timing of ACP, how to plan for an uncertain future, lack of knowledge about dementia, difficulties assessing people with dementia’s decisional capacities, and changing preferences. Facilitators for ACP were: an early start when cognitive decline is still mild, inclusion of all stakeholders, and discussing social and medical issues aimed at maintaining normal life. Conclusion: Discussing future care is difficult due to uncertainties about the future and the decisional capacities of people with dementia. Based on the facilitators, we recommend that GPs use a timely and goal-oriented approach and involve all stakeholders. ACP discussions should focus on the ability of people with dementia to maintain normal daily function as well as on their quality of life, instead of end-of-life-discussions only. GPs need training to acquire knowledge and skills to timely initiate collaborative ACP discussions. [ABSTRACT FROM AUTHOR]

This paper studies the drive-response synchronization for quaternion-valued shunting inhibitory cellular neural networks (QVSICNNs) with mixed delays. First, QVSICNN is decomposed into an equivalent real-valued system in order to avoid the non-commutativity of the multiplicity. Then, the existence of almost periodic solutions is obtained based on the Banach fixed point theorem. An novel state-feedback controller is designed to ensure the global exponential almost periodic synchronization. At the end of the paper, an example is given to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Aiming to solve the safety problems of high-speed railway operation and management, one new method is urgently needed to construct on the basis of the rough set theory and the uncertainty measurement theory. The method should carefully consider every factor of high-speed railway operation that realizes the measurement indexes of its safety operation. After analyzing the factors that influence high-speed railway safety operation in detail, a rough measurement model is finally constructed to describe the operation process. Based on the above considerations, this paper redistricts the safety influence factors of high-speed railway operation as 16 measurement indexes which include staff index, vehicle index, equipment index and environment. And the paper also provides another reasonable and effective theoretical method to solve the safety problems of multiple attribute measurement in high-speed railway operation. As while as analyzing the operation data of 10 pivotal railway lines in China, this paper respectively uses the rough set-based measurement model and value function model (one model for calculating the safety value) for calculating the operation safety value. The calculation result shows that the curve of safety value with the proposed method has smaller error and greater stability than the value function method’s, which verifies the feasibility and effectiveness. [ABSTRACT FROM AUTHOR]

This paper discusses situated problem solving accomplished in the three constituent domains of Kashmiri carpet weaving practice viz. designing, coding and weaving. While, the designers’ problem relates to carving spatial regions on graph-sheets, the coders’ problem relates to cognitively demarcating relevant coding area in those graphs while generating code. Likewise, the weavers’ problem lies in demarcating weaving-territory on the loom, while the manufacturers’ problem relates to determining a particular spatial area for quality assessment. The paper discusses how the actors create fixed, transient and negotiable boundaries on the graph, the loom and the carpet to solve this problem of area determination and demarcation. Section 1 introduces this practice, its task domains and the problem of area determination and demarcation, Section 2 discusses the methodology, Section 3 discusses in detail the problem of area-determination in each task domain and the problem solving strategies employed by the actors using material available in their task-environments itself. In addition, the problem and resolution of area determination as encountered by the manufacturers is discussed. The paper concludes with a discussion on findings of this study with larger findings in cognitive science and accentuates the role played by situated and distributed cognition in unearthing the findings reported in this paper. [ABSTRACT FROM AUTHOR]

Geographers are increasingly interested in understanding the significance of developments in neuroscience, psychology and the behavioural sciences. Indeed, consideration of these disciplines has arguably shaped the trajectories of human geography since at least the 1960s, but its “neural turn” has only recently been acknowledged. This paper provides an original analysis of the intersections of research on neuroscience and geography. With reference to qualitative interviews with cognitive scientists and neuroscientists based in the UK, it identifies how geographical concepts have been approached within contemporary neuroscience while also identifying the broad trajectories of geographers’ engagements with neuroscience. The discussion demonstrates the political implications of these disciplinary trends for a geographical account of brain culture and brain‐based explanations in policy and practice. Specifically it proposes the development of a “critical neuro‐geography” capable of providing an overarching analysis of these phenomena. The paper's novel synthesis of hitherto disconnected engagements between geography, cognitive science and neuroscience establishes the rationale for a more sustained and critical engagement between neuroscience and geography sensitive to issues of situated subjectivity, power, inequality and difference. [ABSTRACT FROM AUTHOR]

In business replenishment, discount offers of multi-item may either provide different discount schedules with a single discount type, or provide schedules with multiple discount types. The paper investigates the joint effects of multiple discount schemes on the decisions of multi-item joint replenishment. In this paper, a joint replenishment problem (JRP) model, considering three discount (all-unit discount, incremental discount, total volume discount) offers simultaneously, is constructed to determine the basic cycle time and joint replenishment frequencies of multi-item. To solve the proposed problem, a heuristic algorithm is proposed to find the optimal solutions and the corresponding total cost of the JRP model. Numerical experiment is performed to test the algorithm and the computational results of JRPs under different discount combinations show different significance in the replenishment cost reduction. [ABSTRACT FROM AUTHOR]

China’s fast economic growth contributes to the rapid development of its urbanization process, and also renders a series of industrial accidents, which often cause loss of life, damage to property and environment, thus requiring the associated risk analysis and safety control measures to be implemented in advance. However, incompleteness of historical failure data before the occurrence of accidents makes it difficult to use traditional risk analysis approaches such as probabilistic risk analysis in many cases. This paper aims to develop a new methodology capable of assessing regional industrial safety (RIS) in an uncertain environment. A hierarchical structure for modelling the risks influencing RIS is first constructed. The hybrid of evidential reasoning (ER) and Analytical Hierarchy Process (AHP) is then used to assess the risks in a complementary way, in which AHP is hired to evaluate the weight of each risk factor and ER is employed to synthesise the safety evaluations of the investigated region(s) against the risk factors from the bottom to the top level in the hierarchy. The successful application of the hybrid approach in a real case analysis of RIS in several major districts of Beijing (capital of China) demonstrates its feasibility as well as provides risk analysts and safety engineers with useful insights on effective solutions to comprehensive risk assessment of RIS in metropolitan cities. The contribution of this paper is made by the findings on the comparison of risk levels of RIS at different regions against various risk factors so that best practices from the good performer(s) can be used to improve the safety of the others. [ABSTRACT FROM AUTHOR]

Public transport (PT) is a key element in most major cities around the world. With the development of smartphones, available journey planning information is becoming an integral part of the PT system. Each traveler has specific preferences when undertaking a trip, and these preferences can also be reflected on the smartphone. This paper considers transit assignment in urban public-transport networks in which the passengers receive smartphone-based information containing elements that might influence the travel decisions in relation to line loads, as well as passenger benefits, and the paper discusses the transition from the current widespread choosing approach to a personalized decision-making approach based on smartphone information. The approach associated with smartphone guidance that considers passengers’ preference on travel time, waiting time and transfer is proposed in the process of obtaining his/her preferred route from the potential travel routes generated by the Deep First Search (DFS) method. Two other approaches, based on the scenarios reflecting reality, include passengers with access to no real time information, and passengers that only have access to the arrival time at the platform are used as comparisons. For illustration, the same network proposed by Spiess and Florian is utilized on the experiments in an agent-based model. Two experiments are conducted respectively according to whether each passenger’s choosing method is consistent. As expected, the results in the first experiment showed that the travel for consistent passengers with smartphone guidance was clearly shorter and that it can reduce travel time exceeding 15% and weighted cost exceeding 20%, and the average saved time approximated 3.88 minutes per passenger. The second experiment presented that travel cost, as well as cost savings, gradually decreased by employing smartphone guidance, and the maximum cost savings accounted for 14.2% of the total weighted cost. [ABSTRACT FROM AUTHOR]

Drawing on job design theories and a conceptual framework of work-related goals and motivation in later adulthood, the aim of this paper is to explore how work-related and individual factors are separately and jointly related to psychological work ability and bridge employment intentions via late job mobility. The cross-sectional study is based on a sample of 171 older Spanish workers aged 45–65 and beyond. We differentiated between groups of older workers in mid career (45–55 years of age) and in their later careers (56 years and beyond). Our results confirm that task characteristics and, secondarily, knowledge characteristics are the most relevant factors in perceptions of psychological work ability among aged workers. Both age groups display a very marked personal mastery trait, which mediates the relationships between job characteristics and both psychological work ability and late job mobility intentions. The paper concludes with a discussion of theoretical and practical implications and suggestions for future research on the issues implied in the psychological adjustment of older workers in their mid and late careers. [ABSTRACT FROM AUTHOR]

Background: In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. Methodology: In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. Results: In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. Conclusions: This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment. This research can help practitioners and decision makers to gain better understanding on the dynamics and complexities of precision intervention in healthcare. It can aid the improvement of the optimal allocation of resources for targeted group (s) and the achievement of maximum utility. As this technology becomes more mature, one can design policy flight simulators by which policy/intervention designers can test a variety of assumptions when they evaluate different alternatives interventions. [ABSTRACT FROM AUTHOR]

Background: Routine Data Quality Assessments (RDQAs) were developed to measure and improve facility-level electronic medical record (EMR) data quality. We assessed if RDQAs were associated with improvements in data quality in KenyaEMR, an HIV care and treatment EMR used at 341 facilities in Kenya. Methods: RDQAs assess data quality by comparing information recorded in paper records to KenyaEMR. RDQAs are conducted during a one-day site visit, where approximately 100 records are randomly selected and 24 data elements are reviewed to assess data completeness and concordance. Results are immediately provided to facility staff and action plans are developed for data quality improvement. For facilities that had received more than one RDQA (baseline and follow-up), we used generalized estimating equation models to determine if data completeness or concordance improved from the baseline to the follow-up RDQAs. Results: 27 facilities received two RDQAs and were included in the analysis, with 2369 and 2355 records reviewed from baseline and follow-up RDQAs, respectively. The frequency of missing data in KenyaEMR declined from the baseline (31% missing) to the follow-up (13% missing) RDQAs. After adjusting for facility characteristics, records from follow-up RDQAs had 0.43-times the risk (95% CI: 0.32–0.58) of having at least one missing value among nine required data elements compared to records from baseline RDQAs. Using a scale with one point awarded for each of 20 data elements with concordant values in paper records and KenyaEMR, we found that data concordance improved from baseline (11.9/20) to follow-up (13.6/20) RDQAs, with the mean concordance score increasing by 1.79 (95% CI: 0.25–3.33). Conclusions: This manuscript demonstrates that RDQAs can be implemented on a large scale and used to identify EMR data quality problems. RDQAs were associated with meaningful improvements in data quality and could be adapted for implementation in other settings. [ABSTRACT FROM AUTHOR]

In political campaigns, perceived candidate credibility influences the persuasiveness of messages. In campaigns aiming to influence people’s beliefs, micro-targeted campaigns (MTCs) that target specific voters using their psychological profile have become increasingly prevalent. It remains open how effective MTCs are, notably in comparison to population-targeted campaign strategies. Using an agent-based model, the paper applies recent insights from cognitive models of persuasion, extending them to the societal level in a novel framework for exploring political campaigning. The paper provides an initial treatment of the complex dynamics of population level political campaigning in a psychologically informed manner. Model simulations show that MTCs can take advantage of the psychology of the electorate by targeting voters favourable disposed towards the candidate. Relative to broad campaigning, MTCs allow for efficient and adaptive management of complex campaigns. Findings show that disliked MTC candidates can beat liked population-targeting candidates, pointing to societal questions concerning campaign regulations. [ABSTRACT FROM AUTHOR]