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Previous studies have demonstrated that skin vibration is an important factor affecting the roughness perception of fine textures. For coarse textures, the determining physical factor is much less clear and there are indications that this might be participant-dependent. In this paper, we focused on roughness perception of both coarse and fine textures of different materials (glass particle surfaces and sandpapers). We investigated the relationship between subjective roughness ratings and three physical parameters (skin vibration, friction coefficient, and particle size) within a group of 30 participants. Results of the glass particle surfaces showed both spatial information (particle size) and temporal information (skin vibration) had a high correlation with subjective roughness ratings. The former correlation was slightly but significantly higher than the latter. The results also indicated different weights of temporal information and spatial information for roughness ratings among participants. Roughness ratings of a different material (sandpaper versus glass particles) could be either larger, similar or smaller, indicating differences among individuals. The best way to describe our results is that in their perceptual evaluation of roughness, different individuals weight temporal information, spatial information, and other mechanical properties differently., Competing Interests: The authors have declared that no competing interests exist.

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.

Past research has largely ignored children's ability to conjointly manipulate spatial and temporal information, but there are indications that the capacity to do so may provide important support for reasoning about causal processes. We hypothesised that spatial-temporal thinking is central to children's ability to identify the invisible mechanisms that tie cause and effect together in continuous casual processes, which are focal in primary school science and crucial to understanding of the natural world. We investigated this in two studies (N = 107, N = 124), employing two methodologies, one shorter, the other more in depth. Further tasks assessed spatial-temporal (flow of liquid, extrapolation of relative speed, distance-time-velocity), spatial (two mental rotation, paper folding), verbal (expressive vocabulary), and nonverbal (block design) ability. Age dependent patterns were detected for both causal and predictor tasks. Two spatial-temporal tasks were unique and central predictors of children's causal reasoning, especially inference of mechanism. Nonverbal ability predicted the simpler components of causal reasoning. One mental rotation task predicted only young children's causal thinking. Verbal ability became significant when the sample included children from a wide range of socioeconomic backgrounds. Causal reasoning about continuous processes, including inferences of causal mechanism, appears to be within the reach of children from school entry age, but mechanism inference is uncommon. Analytic forms of spatial-temporal capacity seem to be important requirements for children to progress to this rather than merely perceptual forms. [ABSTRACT FROM AUTHOR]

The challenge of detecting research topics in a specific research field has attracted attention from researchers in the bibliometrics community. In this study, to solve two problems of clustering papers, i.e., the influence of different distributions of citation links and involved textual features on similarity computation, the authors propose a hybrid self-optimized clustering model to detect research topics by extending the hybrid clustering model to identify “core documents”. First, the Amsler network, consisting of bibliographic coupling and co-citation links, is created to calculate the citation-based similarity based on the cosine angle of papers. Second, the cosine similarity is also used to compute the text-based similarity, which consists of the textual statistical and topological features. Then, the cosine angle of the linear combination of citation- and text-based similarity is considered as the hybrid similarity. Finally, the Louvain method is applied to cluster papers, and the terms based on term frequency are used to label clusters. To test the performance of the proposed model, a dataset related to the data envelopment analysis field is used for comparison and analysis of clustering results. Based on the benchmark built, different clustering methods with different citation links or textual features are compared according to evaluation measures. The results show that the proposed model can obtain reasonable and effective clustering results, and the research topics of data envelopment analysis field are also analyzed based on the proposed model. As different features are considered in the proposed model compared with previous hybrid clustering models, the proposed clustering model can provide inspiration for further studies on topic identification by other researchers. [ABSTRACT FROM AUTHOR]

Background: Impairments in social cognition have been described in several psychiatric and neurological disorders. Given the importance of the relationship between social cognition and functioning and quality of life in these disorders, there is a growing interest in social cognition remediation interventions. The aim of this study was to carry out a systematic mapping review to describe the state of the art in social cognition training and remediation interventions. Methods: Publications from 2006 to 2016 on social cognition interventions were reviewed in four databases: Scopus, PsycINFO, PubMed and Embase. From the initial result set of 3229 publications, a final total of 241 publications were selected. Results: The study revealed an increasing interest in social cognition remediation interventions, especially in the fields of psychiatry and psychology, with a gradual growth in the number of publications. These were frequently published in high impact factor journals and underpinned by robust scientific evidence. Most studies were conducted on schizophrenia, followed by autism spectrum disorders. Theory of mind and emotional processing were the focus of most interventions, whilst a limited number of studies addressed attributional bias and social perception. Targeted interventions in social cognition were the most frequent practice in the selected papers, followed by non-specific treatment interventions and broad-based interventions. Conclusions: Research in social cognition remediation interventions is growing. Further studies are needed on attributional bias and social perception remediation programs, while the comparative efficacy of different interventions also remains unclear. [ABSTRACT FROM AUTHOR]

Skillful utilization of mental arithmetic can significantly improve students' mathematical computation ability. However, it was observed that primary school students often resort to reiterating the process of written arithmetic in their minds during mental arithmetic, which is not conducive to their numerical ability improvement. This paper devises a set of graphic teaching aids for primary school students' mental arithmetic improvement based on mental arithmetic strategies, schema theory, and working memory. To validate the effectiveness of schema teaching in enhancing mental arithmetic ability among primary school students, a controlled experiment was conducted with two groups of third-grade students randomly selected from a primary school in Jingshan City. The results, obtained through descriptive statistical analysis and the multitrait-multimethod approach (MTMM), indicated that the experimental group (n = 52) demonstrated significant improvements in speed, accuracy, and stability in mental addition and subtraction after a 14-day instruction period in schema teaching. This study offers a potent mental arithmetic teaching strategy for elementary mathematics education, which can lead to a comprehensive enhancement of students' mental calculation abilities. It also holds promise for inspiring innovative teaching methodologies in primary and secondary mathematics education in the future., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper investigates models of working memory in which memory traces evolve according to stochastic attractor dynamics. These models have previously been shown to account for response-biases that are manifest across multiple trials of a visual working memory task. Here we adapt this approach by making the stable fixed points correspond to the multiple items to be remembered within a single-trial, in accordance with standard dynamical perspectives of memory, and find evidence that this multi-item model can provide a better account of behavioural data from continuous-report tasks. Additionally, the multi-item model proposes a simple mechanism by which swap-errors arise: memory traces diffuse away from their initial state and are captured by the attractors of other items. Swap-error curves reveal the evolution of this process as a continuous function of time throughout the maintenance interval and can be inferred from experimental data. Consistent with previous findings, we find that empirical memory performance is not well characterised by a purely-diffusive process but rather by a stochastic process that also embodies error-correcting dynamics., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 W. Penny. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Safety and reliability are the basis of the development of a distribution network. To analyze the risk transmission process in the distribution network and ensure the safe and reliable operation of the power system, this paper intends to use the knowledge graph method to realize the risk analysis of the distribution network information system. Firstly, the knowledge graph method is used to extract and integrate the risk knowledge of the multi-dimensional information collected by the distribution network. Secondly, the knowledge graph model of distribution network risk analysis is constructed, and the multi-dimensional distribution network fault handling and knowledge graph construction oriented to the feeder and platform area are designed. The distribution line parameters of the low-voltage distribution network model, neutral point grounding mode, and different fault types are analyzed, and the non-planned island is searched based on the knowledge graph adjacency matrix. Finally, combined with the simulation experiment, it is verified that the proposed method can effectively depict the information risk process of the distribution network. The structure of this paper starts from the multi-node complex distribution network, combined with a knowledge graph and deep learning method, which can solve the distribution network fault more quickly., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: The CONSORT extension for patient reported outcomes (PROs) aims to improve reporting, but guidance on the optimal integration with clinical data is lacking. This study examines in detail the reporting of PROs and clinical data from randomized controlled trials (RCTs) in gastro-intestinal cancer to inform design and reporting of combined PRO and clinical data from trials to improve the ‘take home’ message for clinicians to use in practice. Materials and Methods: The case study was undertaken in gastro-intestinal cancer trials. Well-conducted RCTs reporting PROs with validated instruments were identified and categorized into those combining PRO and clinical data in a single paper, or those separating data into linked primary and supplemental papers. Qualitative methods were developed to examine reporting of the critical interpretation of the trial results (trial exegesis) in the papers in relation of the PRO and clinical outcomes and applied to each publication category. Results were used to inform recommendations for practice. Results: From 1917 screened abstracts, 49 high quality RCTs were identified reported in 36 combined and 15 linked primary and supplemental papers. In-depth analysis of manuscript text identified three categories for understanding trial exegesis: where authors reported a “detailed”, “general”, or absent PRO rationale and integrated interpretation of clinical and PRO results. A total of 11 (30%) and 6 (16%) combined papers reported “detailed” PRO rationale and integrated interpretation of results although only 2 (14%) and 1 (7%) primary papers achieved the same standard respectively. Supplemental papers provide better information with 11 (73%) and 3 (20%) achieving “detailed” rationale and integrated interpretation of results. Supplemental papers, however, were published a median of 20 months after the primary RCT data in lower impact factor journals (median 16.8 versus 5.2). Conclusion: It is recommended that single papers, with detailed PRO rationale and integrated PRO and clinical data are published to optimize trial exegesis. Further work to examine whether this improves the use of PRO data to inform practice is needed. [ABSTRACT FROM AUTHOR]

Virtual Reality (VR) has emerged as a promising tool in many domains of therapy and rehabilitation, and has recently attracted the attention of researchers and clinicians working with elderly people with MCI, Alzheimer’s disease and related disorders. Here we present a study testing the feasibility of using highly realistic image-based rendered VR with patients with MCI and dementia. We designed an attentional task to train selective and sustained attention, and we tested a VR and a paper version of this task in a single-session within-subjects design. Results showed that participants with MCI and dementia reported to be highly satisfied and interested in the task, and they reported high feelings of security, low discomfort, anxiety and fatigue. In addition, participants reported a preference for the VR condition compared to the paper condition, even if the task was more difficult. Interestingly, apathetic participants showed a preference for the VR condition stronger than that of non-apathetic participants. These findings suggest that VR-based training can be considered as an interesting tool to improve adherence to cognitive training in elderly people with cognitive impairment. [ABSTRACT FROM AUTHOR]

The large group of left-behind children with the absence of parental accompanying are likely to have serious physical and psychological problems, which may lead to serious public safety and social economic troubles in adulthood. Such unique phenomenon calls us attention on the impact of parents on household educational investment. Based on the data of China Family Panel Studies in 2014, This paper examines the effects of parents' cognitive ability on household educational investment for their children. The research propositions were tested using multiple regression analysis methods. Results indicate that parents' cognitive ability can significantly improve the level of monetary and non-monetary investment in education. We also find that compared with their counterparts, the cognitive ability of left-behind children's parents fails to affect their household educational investment, due to the "parent-child separation effect". Further analysis shows that improving the regional informatization level of parents of left-behind children can alleviate the "parent-child separation effect", and finally facilitate cognitive ability's role in increasing household educational investment. These findings enlighten education policy makers and households a feasible way to alleviate the imbalance and insufficiency of household educational investment among left-behind children families., Competing Interests: The authors report there are no competing interests to declare., (Copyright: © 2023 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The prevalence of dyslexia identification has increased significantly over the last two decades. Yet there is debate over whether there are distinct biological and cognitive differences between those with literacy difficulties and the subgroup of people identified as dyslexic. This is the first paper that provides evidence for this ongoing debate by investigating the socio-demographic factors, outside biology and cognition, that predict whether a child is identified as dyslexic in the UK. Using secondary data from the UK's Millennium Cohort Study, this paper examines the socio-demographic factors that predict whether a child's teacher identifies them as dyslexic at age 11. Gender, season of birth, socio-economic class and parental income are found to be significant predictors of the dyslexia label. Therefore, factors seemingly unrelated to the clinical aspects of dyslexia influence whether a child is identified as dyslexic in England and Wales. This suggests that label may not be evenly distributed across a population; furthermore, it may also indicate that resources for support may not be fairly allocated. The findings further support the argument that a 'dyslexic sub-group' within poor readers is created due to the impact of environmental factors. The results from this national-scale study thus questions the reliability, validity and moral integrity of the allocation of the dyslexia label across current education systems in the UK. [ABSTRACT FROM AUTHOR]

Introduction: Aging in rural settings worldwide, from the perspective of cognition, physical function, and life purpose essential constructs for a prosperous old age, still needs comprehensive discussion. This systematic review protocol aims to highlight the prevalence of cognitive decline, physical functioning, and life purpose in older adults aging in rural community settings. Methods and analysis: We will include cross-sectional studies published until April 2023 found in 8 databases: Embase, MEDLINE, LILACS, PsycINFO, Scopus, SciELO, and Web of Science. Ryyan software will be used for the first selection, and the Observational Study Quality Evaluation (OSQE) will assess methodological quality and risk of bias. Primary analysis will involve titles and abstracts using MeSH descriptors such as "Physical functioning," "Cognition," "Cognitive function," "Life purpose," "Elderly," "Older," "Rural aging," "Rural population," "Communities, rural," "Distribution, rural spatial," "Medium communities," "Rural settlement," "Small community." If necessary, secondary analysis will include a complete reading of selected articles by two blinded reviewers, confirmed by a third person. Publication bias will be assessed using cross-sectional analytical study quality. Sensitivity analyses will identify manuscripts significantly influencing combined prevalence of endpoints. [ABSTRACT FROM AUTHOR]

Discrete choice experiments (DCEs) are a way to assess priority-setting in health care provision. This approach allows for the evaluation of individuals’ preferences as a means of adding criteria to traditional quality-adjusted life year analysis. The aim of this systematic literature review was to identify attributes for designing a DCE in order to then develop and validate a framework that supports decision-making on health technologies. Our systematic literature review replicated the methods and search terms used by de Bekker-Grob et al. 2012 and Clark et al. 2014. The Medline database was searched for articles dated between 2008 and 2015. The search was limited to studies in English that reflected general preferences and were choice-based, published as full-text articles and related to health technologies. This study included 72 papers, 52% of which focused on DCEs on drug treatments. The average number of attributes used in all included DCE studies was 5.74 (SD 1.98). The most frequently used attributes in these DCEs were improvements in health (78%), side effects (57%) and cost of treatment (53%). Other, less frequently used attributes included waiting time for treatment or duration of treatment (25%), severity of disease (7%) and value for money (4%). The attributes identified might inform future DCE surveys designed to study societal preferences regarding health technologies in order to better inform decisions in health technology assessment. [ABSTRACT FROM AUTHOR]

Accurate Origin-Destination (OD) prediction is significant for effective traffic monitor, which can support operation decision in traffic planning and management field. The enclosed expressway network system like toll gates system in China can collect mounts of trip records which can be gathered for OD prediction. The paper develops a novel neural network, which is named Expressway OD Prediction Neural Network (EODPNN) for toll data-based prediction. The network consists of the following three modules: The Feature Extension Module, the Memory Module, and the Prediction Module. In the process, the attributes data which can reflect the city attribute such as GDP, population, and the number of vehicles are considered to embeded into the notwork to increase the accuracy of the model. For the applicability improvment of the model, we categorize the cities in multiple classes based on their economy and population scales in this paper, which can provide a higher accurate prediction of OD by EODPNN. The results shows that, comparing to the traditional model like ARIMA and SVM, or typical neural networks like Bidirectional Long Short-term Memory, the EODPNN delivers a better prediction performance. The method proposed in this paper has been fully verified and has a potential to transplant to the other OD data-based management systems for a more accurate and flexible prediction. [ABSTRACT FROM AUTHOR]

Methods for obtaining valuable knowledge from the vast amount of mixed-quality information have become a top priority for knowledge demanders. As an online knowledge-sharing channel, the socialized question and answer (Q&A) platform provides important support services for knowledge payment. Based on the personal psychological dimensions of users and social capital theory, this paper aims to study the behavior mechanisms of knowledge payment users and examine the significant factors affecting user payment. Our research was conducted in two steps: a qualitative study to find these factors and a research model based on a quantitative study for testing the hypothesis. The results show that the three dimensions of individual psychology are not all positively correlated with cognitive and structural capital. Our results fill a gap in the literature on the formation of social capital in the knowledge payment environment by showing how individual psychological dimensions affect cognitive and structural capital differently. Thus, this study offers effective countermeasures for knowledge producers on social Q&A platforms to better amass their social capital. This research also makes practical recommendations for social Q&A platforms to strengthen the knowledge payment model. [ABSTRACT FROM AUTHOR]

The last decade has witnessed a significant rise in European secessionist movements leading to considerable political turmoil (e.g., protest, repression, imprisonment of political leaders). While scholars have identified a number of economic and political factors that influence the support for secessionist movements, fewer studies have focused on its psychological roots. Using evidence from Catalonia, this paper investigates the role of two fundamental individual traits, Need for Affect (NFA) and Need for Cognition (NFC), in influencing the support for Catalan independence. It analyzes a large representative sample of adult Catalans in 2013, during the peak of the secessionist movement, to examine the influence of NFA and NFC, and their interaction, on the intention to vote in favor of seceding from Spain. Results indicate that individuals who have high levels in NFA and those who have high levels of NFA and low levels of NFC are more likely to support independence. In other words, individuals who have low levels of both NFA and NFC have the lowest support for independence. In conclusion, these findings highlight the importance of considering individual differences in psychological motives in order to fully understand support for secessionist movements., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Joan Barceló. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper aims to expand the literature on the determinants of the Cognitive Reflection Test scores, exploring the effects that the items sequence has on (1) Cognitive Reflection Test scores, (2) response time, (3) the relationship between Cognitive Reflection Test scores and response time, and (4) Cognitive Reflection scores, response time, and the relationship between both variables on men and women. The current study also explored the sex differences on Cognitive Reflection Test and response time according to items sequence. The results showed that manipulating the items sequence, the performance on the Cognitive Reflection Test improved significantly, but the response time were not significantly affected, although the results suggest that first items of the sequence could be working as training items. A positive relationship between Cognitive Reflection Test scores and response time was also found, except when the scores were maximized. Finally, some differences between men and women on the results were also found. The implications of these findings are discussed., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Otero, Alonso. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Research into paranormal beliefs and cognitive functioning has expanded considerably since the last review almost 30 years ago, prompting the need for a comprehensive review. The current systematic review aims to identify the reported associations between paranormal beliefs and cognitive functioning, and to assess study quality. Method: We searched four databases (Scopus, ScienceDirect, SpringerLink, and OpenGrey) from inception until May 2021. Inclusion criteria comprised papers published in English that contained original data assessing paranormal beliefs and cognitive function in healthy adult samples. Study quality and risk of bias was assessed using the Appraisal tool for Cross-Sectional Studies (AXIS) and results were synthesised through narrative review. The review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was preregistered as part of a larger registration on the Open Science Framework (https://osf.io/uzm5v). Results: From 475 identified studies, 71 (n = 20,993) met our inclusion criteria. Studies were subsequently divided into the following six categories: perceptual and cognitive biases (k = 19, n = 3,397), reasoning (k = 17, n = 9,661), intelligence, critical thinking, and academic ability (k = 12, n = 2,657), thinking style (k = 13, n = 4,100), executive function and memory (k = 6, n = 810), and other cognitive functions (k = 4, n = 368). Study quality was rated as good-to-strong for 75% of studies and appears to be improving across time. Nonetheless, we identified areas of methodological weakness including: the lack of preregistration, discussion of limitations, a-priori justification of sample size, assessment of nonrespondents, and the failure to adjust for multiple testing. Over 60% of studies have recruited undergraduates and 30% exclusively psychology undergraduates, which raises doubt about external validity. Our narrative synthesis indicates high heterogeneity of study findings. The most consistent associations emerge for paranormal beliefs with increased intuitive thinking and confirmatory bias, and reduced conditional reasoning ability and perception of randomness. Conclusions: Although study quality is good, areas of methodological weakness exist. In addressing these methodological issues, we propose that authors engage with preregistration of data collection and analysis procedures. At a conceptual level, we argue poorer cognitive performance across seemingly disparate cognitive domains might reflect the influence of an over-arching executive dysfunction. [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]

The neural processes underpinning cognition and language development in infancy are of great interest. We investigated EEG power and coherence in infancy, as a reflection of underlying cortical function of single brain region and cross-region connectivity, and their relations to cognition and early precursors of speech and language development. EEG recordings were longitudinally collected from 21 infants with typical development between approximately 1 and 7 months. We investigated relative band power at 3-6Hz and 6-9Hz and EEG coherence of these frequency ranges at 25 electrode pairs that cover key brain regions. A correlation analysis was performed to assess the relationship between EEG measurements across frequency bands and brain regions and raw Bayley cognitive and language developmental scores. In the first months of life, relative band power is not correlated with cognitive and language scales. However, 3-6Hz coherence is negatively correlated with receptive language scores between frontoparietal regions, and 6-9Hz coherence is negatively correlated with expressive language scores between frontoparietal regions. The results from this preliminary study contribute to the existing literature on the relationship between electrophysiological development, cognition, and early speech precursors in this age group. Future work should create norm references of early development in these domains that can be compared with infants at risk for neurodevelopmental disabilities. [ABSTRACT FROM AUTHOR]

Recently, researchers have proposed four superordinate emotion beliefs that supposedly influence emotion regulation and emotion reactivity. Two of these proposed emotion beliefs are captured in the cognitive mediation beliefs questionnaire (CMBQa), namely stimulus-response (S-R) generation beliefs and cognitive mediation (C-M) change beliefs. The remaining two proposed emotion beliefs, C-M generation beliefs and S-R change beliefs, are yet to be operationalised in psychometric form. It is important to validate measurement for all four emotion beliefs in order for them to be used in research and practice. The current paper reports the development and initial validity testing of the CMBQb (studies 1-3), which concerns only C-M generation beliefs and S-R change beliefs, and then tests the four-factor structure of the combined CMBQa (S-R generation, C-M change) and CMBQb (C-M generation, S-R change): the CMBQc (study 4). Some support was found for the four-factor structure of the CMBQc, with factor analyses revealing good fit to the data with a four-factor solution. Also, scores indicating greater C-M generation and change beliefs, and lower S-R generation and change beliefs, were related to more adaptive, and less maladaptive, emotion regulation tendencies. In addition, there was some evidence that greater C-M change beliefs, and lower S-R generation and change belief, were related to better affective and emotion reactivity outcomes. Implications of the CMBQc for research and practice are discussed within the context and emotion regulation science, and cognitive behavioural psychotherapy., Competing Interests: The authors have declared that no competing interests exist.

Frailty is a common condition in older age and is a public health concern which requires integrated care and involves different stakeholders. This meta-synthesis focuses on experiences, understanding, and attitudes towards screening, care, intervention and prevention for frailty across frail and healthy older persons, caregivers, health and social care practitioners. Studies published since 2001 were identified through search of electronic databases; 81 eligible papers were identified and read in full, and 45 papers were finally included and synthesized. The synthesis was conducted with a meta-ethnographic approach. We identified four key themes: Uncertainty about malleability of frailty; Strategies to prevent or to respond to frailty; Capacity to care and person and family-centred service provision; Power and choice. A bottom-up approach which emphasises and works in synchrony with frail older people's and their families' values, goals, resources and optimisation strategies is necessary. A greater employment of psychological skills, enhancing communication abilities and tools to overcome disempowering attitudes should inform care organisation, resulting in more efficient and satisfactory use of services. Public health communication about prevention and management of frailty should be founded on a paradigm of resilience, balanced acceptance, and coping. Addressing stakeholders’ views about the preventability of frailty was seen as a salient need. [ABSTRACT FROM AUTHOR]

Open source software has been widely used in various industries due to its openness and flexibility, but it also brings potential security problems. Therefore, security analysis is required before using open source software. The current mainstream open source software vulnerability analysis technology is based on source code, and there are problems such as false positives, false negatives and restatements. In order to solve the problems, based on the further study of behavior feature extraction and vulnerability detection technology, a method of using dynamic behavior features to detect open source software vulnerabilities is proposed. Firstly, the relationship between open source software vulnerability and API call sequence is studied. Then, the behavioral risk vulnerability database of open source software is proposed as a support for vulnerability detection. In addition, the CNN-IndRNN classification model is constructed by improving the Independently Recurrent Neural Net-work (IndRNN) algorithm and applies to open source software security vulnerability detection. The experimental results verify the effectiveness of the proposed open source software security vulnerability detection method based on dynamic behavior features. [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]

To solve the problem of the deadline-constrained task scheduling in the cloud computing system, this paper proposes a deadline-constrained scheduling algorithm for cloud computing based on the driver of dynamic essential path (Deadline-DDEP). According to the changes of the dynamic essential path of each task node in the scheduling process, the dynamic sub-deadline strategy is proposed. The strategy assigns different sub-deadline values to every task node to meet the constraint relations among task nodes and the user’s defined deadline. The strategy fully considers the dynamic sub-deadline affected by the dynamic essential path of task node in the scheduling process. The paper proposed the quality assessment of optimization cost strategy to solve the problem of selecting server for each task node. Based on the sub-deadline urgency and the relative execution cost in the scheduling process, the strategy selects the server that not only meets the sub-deadline but also obtains much lower execution cost. In this way, the proposed algorithm will make the task graph complete within its deadline, and minimize its total execution cost. Finally, we demonstrate the proposed algorithm via the simulation experiments using Matlab tools. The experimental results show that, the proposed algorithm produces remarkable performance improvement rate on the total execution cost that ranges between 10.3% and 30.8% under meeting the deadline constraint. In view of the experimental results, the proposed algorithm provides better-quality scheduling solution that is suitable for scientific application task execution in the cloud computing environment than IC-PCP, DCCP and CD-PCP. [ABSTRACT FROM AUTHOR]

Background: Early identification of preschool children who are at risk of faltering in their development is essential to ensuring that all children attain their full potential. Electroencephalography (EEG) has been used to measure neural correlates of cognitive and social development in children for decades. Effective portable and low-cost EEG devices increase the potential of its use to assess neurodevelopment in children at scale and particularly in low-resource settings. We conducted a systematic review aimed to synthesise EEG measures of cognitive and social development in 2-5-year old children. Our secondary aim was to identify how these measures differ across a) the course of development within this age range, b) gender and c) socioeconomic status (SES). Methods and findings: A systematic literature search identified 51 studies for inclusion in this review. Data relevant to the primary and secondary aims was extracted from these studies and an assessment for risk of bias was done, which highlighted the need for harmonisation of EEG data collection and analysis methods across research groups and more detailed reporting of participant characteristics. Studies reported on the domains of executive function (n = 22 papers), selective auditory attention (n = 9), learning and memory (n = 5), processing of faces (n = 7) and emotional stimuli (n = 8). For papers investigating executive function and selective auditory attention, the most commonly reported measures were alpha power and the amplitude and latency of positive (P1, P2, P3) and negative (N1, N2) deflections of event related potential (ERPs) components. The N170 and P1 ERP components were the most commonly reported neural responses to face and emotional faces stimuli. A mid-latency negative component and positive slow wave were used to index learning and memory, and late positive potential in response to emotional non-face stimuli. While almost half the studies described changes in EEG measures across age, only eight studies disaggregated results based on gender, and six included children from low income households to assess the impact of SES on neurodevelopment. No studies were conducted in low- and middle-income countries. Conclusion: This review has identified power across the EEG spectrum and ERP components to be the measures most commonly reported in studies in which preschool children engage in tasks indexing cognitive and social development. It has also highlighted the need for additional research into their changes across age and based on gender and SES. [ABSTRACT FROM AUTHOR]

Are humans instinctively good or is it only our capacity for reflection that enables us to restrain our selfish traits and behave prosocially? Against the background of dual-process theory, the question of whether people tend to behave prosocially on intuitive grounds has been debated controversially for several years. Central to this debate is the so-called social heuristic hypothesis (SHH), which states that subjects orient their behavior more closely to their deeply ingrained norms and attitudes when the behavior comes about in an intuitive rather than reflective manner. In this paper, we apply the SHH to a novel setting and investigate whether its implications hold true in a non-reactive field experiment, in which subjects are unaware that they are part of a study. We test whether subjects report a misdirected email or try to use the opportunity to reap a monetary benefit. Since all subjects participated six months prior to the field experiment in a lab experiment, we have solid measures of the subjects' general tendency to behave intuitively and their prosocial attitudes. In addition, participants were asked in a follow-up survey to self-report their intuitiveness at the time of the decision. While we observe a significant and positive effect on prosocial behavior for self-reported intuitiveness (but not for general intuitiveness) in the bivariate analyses, this effect becomes insignificant when controlling for interaction effects with attitudes. In addition, for both forms of intuitiveness, we find a significant and positive interaction effect with subjects' prosocial attitudes on prosocial behavior. Hence, this study confirms previous findings from laboratory as well as online studies and provides external validity by demonstrating that the SHH applies in a real-life situation., Competing Interests: The authors have declared that no competing interests exist.

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]

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]

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]

This paper aims to optimize a desirable fare structure for the public transit service along a bus-subway corridor with the consideration of those factors related to equity in trip, including travel distance and comfort level. The travel distance factor is represented by the distance-based fare strategy, which is an existing differential strategy. The comfort level one is considered in the area-based fare strategy which is a new differential strategy defined in this paper. Both factors are referred to by the combined fare strategy which is composed of distance-based and area-based fare strategies. The flat fare strategy is applied to determine a reference level of social welfare and obtain the general passenger flow along transit lines, which is used to divide areas or zones along the corridor. This problem is formulated as a bi-level program, of which the upper level maximizes the social welfare and the lower level capturing traveler choice behavior is a variable-demand stochastic user equilibrium assignment model. A genetic algorithm is applied to solve the bi-level program while the method of successive averages is adopted to solve the lower-level model. A series of numerical experiments are carried out to illustrate the performance of the models and solution methods. Numerical results indicate that all three differential fare strategies play a better role in enhancing the social welfare than the flat fare strategy and that the fare structure under the combined fare strategy generates the highest social welfare and the largest resulting passenger demand, which implies that the more equity factors a differential fare strategy involves the more desirable fare structure the strategy has. [ABSTRACT FROM AUTHOR]

In this paper, new Network Data Envelopment Analysis (NDEA) models are developed to evaluate the efficiency of regional electricity power networks. The primary objective of this paper is to consider perturbation in data and develop new NDEA models based on the adaptation of robust optimization methodology. Furthermore, in this paper, the efficiency of the entire networks of electricity power, involving generation, transmission and distribution stages is measured. While DEA has been widely used to evaluate the efficiency of the components of electricity power networks during the past two decades, there is no study to evaluate the efficiency of the electricity power networks as a whole. The proposed models are applied to evaluate the efficiency of 16 regional electricity power networks in Iran and the effect of data uncertainty is also investigated. The results are compared with the traditional network DEA and parametric SFA methods. Validity and verification of the proposed models are also investigated. The preliminary results indicate that the proposed models were more reliable than the traditional Network DEA model. [ABSTRACT FROM AUTHOR]

Previous studies have suggested that virtual reality (VR) can elicit emotions in different visual modes using 2D or 3D headsets. However, the effects on emotional arousal by using these two visual modes have not been comprehensively investigated, and the underlying neural mechanisms are not yet clear. This paper presents a cognitive psychological experiment that was conducted to analyze how these two visual modes impact emotional arousal. Forty volunteers were recruited and were randomly assigned to two groups. They were asked to watch a series of positive, neutral and negative short VR videos in 2D and 3D. Multichannel electroencephalograms (EEG) and skin conductance responses (SCR) were recorded simultaneously during their participation. The results indicated that emotional stimulation was more intense in the 3D environment due to the improved perception of the environment; greater emotional arousal was generated; and higher beta (21-30 Hz) EEG power was identified in 3D than in 2D. We also found that both hemispheres were involved in stereo vision processing and that brain lateralization existed in the processing., Competing Interests: The authors have declared that no competing interests exist.

Existing research shows that evaluations of the risks and benefits of various hazards (i.e., technologies and activities) are inversely related. The affect heuristic explains the negative relation between risks and benefits, as based on the strength of positive or negative affect associated with a hazard. Research on the affect heuristic previously investigated under which conditions people judge risk and benefits independently, focusing on expertise as a factor that might exempt from inversely related judgements of risk and benefits. Measurements within Dual Process Theories have been found to be associated with rational, analytical decision making and accurate judgments. In this paper we investigated the extent to which rational information processing styles can predict the risk-benefit relation of technologies in a medical and food applications and whether the attitudes influence the strength or direction of the relationship. Using the Need for Cognition Scale (NFC), a psychometric-based risk scale and an explicit measure of attitude, in a representative sample of 3228 Swedes, we found that the high NFC group judged the risks and benefits of technologies to be inversely related. In contrast, the low NFC group judged the risks and benefits to be positively related. These results were confirmed across all studied technologies by applying moderation analysis. We discuss the results in light of recent research on cognitive processing and polarization over technologies' risks., Competing Interests: The authors have declared that no competing interests exist.

A wide body of literature has demonstrated that the neural representation of healthy swallowing is mostly bilateral, with one hemisphere dominant over the other. While several studies have demonstrated the presence of laterality for swallowing related functions among young adults, the data on older adults are still growing. The purpose of this paper is to investigate potential changes in hemispheric dominance in healthy aging adults for swallowing related tasks using a behavioral dual-task paradigm. A modified dual-task paradigm was designed to investigate the potential reduction in hemispherical specialization for swallowing function. Eighty healthy right-handed participants in the study were divided into two groups [Group 1: young adults (18-40 years) and Group 2: older adults (65 and above)]. All the participants performed a timed water swallow test at baseline and with two interference conditions (silent word repetition, and facial recognition). The results of the study revealed the following 1) a statistically significant effect of age on swallow performance; 2) statistically significant effect of each of the interference tasks on two of the swallow measures (VPS and VPT) in younger adults; and 3) no significant effect of the interference tasks on the swallowing performance of older adults. These findings suggest that aging substantially affects swallowing in older individuals, and this potentially accompanies a reduction in the hemispheric specialization for swallowing related tasks., Competing Interests: The authors have declared that no competing interests exist.

With the development of computer network bandwidth, packet classification algorithms which are able to deal with large-scale rule sets are in urgent need. Among the existing algorithms, researches on packet classification algorithms based on hierarchical trie have become an important packet classification research branch because of their widely practical use. Although hierarchical trie is beneficial to save large storage space, it has several shortcomings such as the existence of backtracking and empty nodes. This paper proposes a new packet classification algorithm, Hierarchical Trie Algorithm Based on Expectation-Maximization Clustering (HTEMC). Firstly, this paper uses the formalization method to deal with the packet classification problem by means of mapping the rules and data packets into a two-dimensional space. Secondly, this paper uses expectation-maximization algorithm to cluster the rules based on their aggregate characteristics, and thereby diversified clusters are formed. Thirdly, this paper proposes a hierarchical trie based on the results of expectation-maximization clustering. Finally, this paper respectively conducts simulation experiments and real-environment experiments to compare the performances of our algorithm with other typical algorithms, and analyzes the results of the experiments. The hierarchical trie structure in our algorithm not only adopts trie path compression to eliminate backtracking, but also solves the problem of low efficiency of trie updates, which greatly improves the performance of the algorithm. [ABSTRACT FROM AUTHOR]

This paper examined, with a behavioral paradigm, to what extent people choose to view stimuli that portray death, violence or harm. Based on briefly presented visual cues, participants made choices between highly arousing, negative images and positive or negative alternatives. The negative images displayed social scenes that involved death, violence or harm (e.g., war scene), or decontextualized, close-ups of physical harm (e.g., mutilated face) or natural threat (e.g., attacking shark). The results demonstrated that social negative images were chosen significantly more often than other negative categories. Furthermore, participants preferred social negative images over neutral images. Physical harm images and natural threat images were not preferred over neutral images, but were chosen in about thirty-five percent of the trials. These results were replicated across three different studies, including a study that presented verbal descriptions of images as pre-choice cues. Together, these results show that people deliberately subject themselves to negative images. With this, the present paper demonstrates a dynamic relationship between negative information and behavior and advances new insights into the phenomenon of morbid curiosity. [ABSTRACT FROM AUTHOR]

Sentence-initial temporal clauses headed by before, as in "Before the scientist submitted the paper, the journal changed its policy", have been shown to elicit sustained negative-going brain potentials compared to maximally similar clauses headed by after, as in "After the scientist submitted the paper, the journal changed its policy". Such effects may be due to either one of two potential causes: before clauses may be more difficult than after clauses because they cause the two events in the sentence to be mentioned in an order opposite the order in which they actually occurred, or they may be more difficult because they are ambiguous with regard to whether the event described in the clause actually happened. The present study examined the effect of before and after clauses on sentence processing in both sentence-initial contexts, like those above, and in sentence-final contexts ("The journal changed its policy before/after the scientist submitted the paper"), where an order-of-mention account of the sustained negativity predicts a negativity for after relative to before. There was indeed such a reversal, with before eliciting more negative brain potentials than after in sentence-initial clauses but more positive in sentence-final clauses. The results suggest that the sustained negativity indexes processing costs related to comprehending events that were mentioned out of order. [ABSTRACT FROM AUTHOR]

In this paper, complex network theory is used to make time-series analysis of key indicators of governance structure and financing data. We analyze scientific listed companies’ governance data from 2010 to 2014 and divide them into groups in accordance with the similarity they share. Then we select sample companies to analyze their financing data and explore the influence of governance structure on financing decision and the financing preference they display. This paper reviews relevant laws and regulations of financing from the perspective of law and economics, then proposes reasonable suggestions to consummate the law for the purpose of regulating listed companies’ financing. The research provides a reference for making qualitative analysis on companies’ financing. [ABSTRACT FROM AUTHOR]

Stochastic link capacity degradations are common phenomena in transport network which can cause travel time variations and further can affect travelers’ daily route choice behaviors. This paper formulates a deterministic dynamic model, to capture the day-to-day (DTD) flow evolution process in the presence of degraded link capacity degradations. The aggregated network flow dynamics are driven by travelers’ study of uncertain travel time and their choice of risky routes. This paper applies the exponential-smoothing filter to describe travelers’ study of travel time variations, and meanwhile formulates risk attitude parameter updating equation to reflect travelers’ endogenous risk attitude evolution schema. In addition, this paper conducts theoretical analyses to investigate several significant mathematical characteristics implied in the proposed DTD model, including fixed point existence, uniqueness, stability and irreversibility. Numerical experiments are used to demonstrate the effectiveness of the DTD model and verify some important dynamic system properties. [ABSTRACT FROM AUTHOR]

China is facing severe pressure on its water resources and water environments. Calculating the industrial water efficiency of each province is an important index for the central government to evaluate local governments. In the traditional water resources evaluation index, the industrial water use efficiency and pollutant discharge are evaluated separately. In this paper, we collected industrial input data, output data and pollutant discharge data with a four-stage data envelopment analysis to calculate China's industrial water use efficiency with and without considering pollutant discharge, and then analyzed the factors influencing the industrial water use efficiency. The results show that the eastern coastal provinces of China have the highest water use efficiency and are less affected by pollutant discharge than other provinces. The industrial water use efficiency of the central and western provinces is lower than that of the other provinces, and the industrial water use efficiency in the central provinces is greatly affected by pollutant discharge. Factor endowment, economic development level, scientific and technological progress, industrial structure, proportion of foreign investment, water consumption per 10000 yuan of value-added by industry, industrial sewage treatment capacity and educational investment have a significant influence on the industrial water use efficiency of China. We suggest that the government strengthen the construction of sewage plants and other related infrastructure in central provinces when conducting the industrial transfer of heavy polluting enterprises. [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]

The 5Rights Youth Juries are an educational intervention to promote digital literacy by engaging participants (i.e. jurors) in a deliberative discussion around their digital rights. The main objective of these jury-styled focus groups is to encourage children and young people to identify online concerns and solutions with a view to developing recommendations for government policy-makers and industry chiefs. The methodology included a series of dramatized scenarios that encourage jurors to deliberate about their digital rights. This paper compares two formats for these scenarios: live actors and professionally recorded and edited videos of the same actors. Results failed to show any major differences between formats indicating the cost-effectiveness of the video-recorded format and the possibility for others to run the 5Rights Youth Juries with the support of an online open educational resource. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of energy management of mixed criticality applications in a multi-core partitioned architecture. Instead of focusing on new scheduling algorithms to adjust frequency in order to save energy, we propose a partition to CPU allocation that takes into account not only the different frequencies at which the CPU can operate but the level of criticality of the partitions. The goal is to provide a set of pre-calculated allocations, called profiles, so at run time the system can switch to different modes depending on the battery level. These profiles achieve different levels of energy saving and performance applying different strategies. We also present a comparison in terms of energy saving of the most used bin-packing algorithms for partition allocation. As this is an heuristic, it is not possible to ensure that our results involve the minimum energy consumption. For this reason, we also provide a comparison with a exact method, such as constraint programming. [ABSTRACT FROM AUTHOR]

A recurrent criticism concerning the use of online social media data in political science research is the lack of demographic information about social media users. By employing a face-recognition algorithm to the profile pictures of Facebook users, the paper derives two fundamental demographic characteristics (age and gender) of a sample of Facebook users who interacted with the most relevant British parties in the two weeks before the Brexit referendum of 23 June 2016. The article achieves the goals of (i) testing the precision of the algorithm, (ii) testing its validity, (iii) inferring new evidence on digital mobilisation, and (iv) tracing the path for future developments and application of the algorithm. The findings show that the algorithm is reliable and that it can be fruitfully used in political and social sciences both to confirm the validity of survey data and to obtain information from populations that are generally unavailable within traditional surveys. [ABSTRACT FROM AUTHOR]

New democracies go to great lengths to implement institutional protections of the electoral process. However, in this paper we present evidence that shows that even in the United States—where the secret ballot has been in place for generations—doubts about the secrecy of the voting process are surprisingly prevalent. Many say that their cast ballot can be matched to their name or that others could observe their vote choices while they were voting. We find that people who have not previously voted are particularly likely to harbor doubts about the secrecy of voters’ ballots. Those who vote by mail in the privacy of their own homes also feel that others are able to discover their vote choices. Taken together, these findings suggest an important divergence between public perceptions about and the institutional status of the secret ballot in the United States, a divergence that may affect patterns of voting behavior and political participation. [ABSTRACT FROM AUTHOR]