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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]

The article offers information on the 13th meeting of the European Society for Traumatic Stress Studies (ESTSS) in Bologna, Italy in 2013.

The creation of the Spanish Psychological Association (Spanish acronym, COP) was of enormous significance in the establishing of psychology in Spain, and in the creation of its identity. Since the publication of the 1980 Law of Creation [of the COP], this organization--aimed at regulating and representing the psychology profession--has not stopped growing, despite the serious internal and external issues it has had. The Spanish Psychological Association has gone through different stages over the past 40 years, which reflect and help us to characterize the short history of Spanish psychology, in particular the history of its delimitation with respect to other professions. This article presents an extensive legislative and documentary review, particularly based on its representative publication, Papeles del Psicólogo/Psychologist Papers. We analyze the complicated early years, up to 1993, under the direction of Carlos Camarero and Adolfo Hernández, a phase marked by the internal configuration of the organization, a serious challenge for the profession, and the fight to approve the master's degree. [ABSTRACT FROM AUTHOR]

Background: A new diagnosis of complex post‐traumatic stress disorder, CPTSD, has been agreed by the World Health Organization, WHO, and evidence is needed for what psychological treatment might be effective, particularly from those with experience of the disorder. We used a novel participatory approach to explore patient views and simultaneously studied the impact on the patient researchers of the research process itself. In this paper, we report on the latter section of the study how the involvement in research of patients with CPTSD affected their mental health. Symptoms of CPTSD may include emotional dysregulation, feelings of self‐worthlessness and difficulties in relationships. Objective: The aim of this study section was to explore whether patients' mental health could be promoted through empowering them to participate in research on CPTSD. Design: The study had a qualitative, participatory design. The clinician who led the research (first author) held group meetings with patient researchers to explore the impact of the research process. The clinician also kept notes on the process in a reflective log. Setting and participants: Six patient researchers participated in research with other patients with lived experience of CPTSD in an NHS outpatient unit in a London hospital. Intervention studied: The research process itself was analysed in group meetings with researchers which the clinician recorded and transcribed. Findings: Participation in research may promote increased self‐confidence and social inclusion for those with CPTSD. Conclusion: Involvement in research may be seen as an empowering intervention because patients felt it contributed to recovery. [ABSTRACT FROM AUTHOR]

Background: Mandrake (Mandragora spp.) is one of the most famous medicinal plant in western cultures since Biblical times and throughout written history. In many cultures, mandrake is related to magic and witchcraft, which is said to have a psychosomatic effect (especially when mandrake contains narcotic compounds) in addition to the pharmacological influence, as occurs with other narcotic magical plants. Due to its unique properties and related myths, it is not surprising that this plant has many names in many languages. Methods: This paper presents an attempt to reconstruct the historical, ethnobotanical, and folkloristic roots of 292 vernacular names of Mandragora spp. in forty-one languages. We used the plant's morphological data, philology, myths and legends, medicinal properties and uses, as well as historical evidence and folkloric data, to explain meaning, origin, migration, and history of the plant's names. Results: The names were classified into the following main categories: Derivatives of mandragora (19 languages), alraun (7) and of yabroukh (5). The salient groups of the plant's vernacular names are related to: Anthropomorphism (33 names in 13 languages); Similarity to other plants (28/9); Supernatural agents (28/9); Narcotic effects (21/8); Leaves, fruits, and seeds (21/8); Aphrodisiac properties (17/10); Use of a dog (15/9); Gallows (14/5); Black magic, sorcery, witchcraft (13/8), and Medicinal use (11/7). Conclusions: This frequency distribution of the mandrake's vernacular names reflects its widespread reputation as related to the doctrine of signatures, beliefs in its supernatural, natural, and mythic powers, and to a lesser extent, its uses in magic and medicine. A spatiotemporal analysis of the mandrake's names supports the old idea that the pulling ceremonies for this plant originated in the Near East and that various other myths related to this plant may have originated in different places and periods. [ABSTRACT FROM AUTHOR]

Paul Ekman is an American psychologist who pioneered the study of facial behaviour. Bringing together disciplinary history, life study, and history of science, this paper focuses on Ekman's early research during the twenty-year period between 1957 and 1978. I explicate the historical development of Ekman's semiotic model of facial behaviour, tracing the thread of iconicity through his life and works: from the iconic coding of rapid signs; through the eventual turn from classifying modes of iconic signification using gestalt categories to classifying modes of producing iconic sign-functions using minimal units; to the role and importance of iconicity for the study of the facial expression of emotion, both in terms of the similarities between iconic and analogue signs as well as the differences between facial coding and linguistic signification. In this intellectual genealogy, I argue not only that Ekman relied extensively upon conceptualizations and terminologies from semiotic thought for the creation of the Facial Action Coding System (FACS), but also that the question of iconicity is the pivotal problem across the many discoveries and innovations in what I term 'Ekmanian faciasemiotics'. [ABSTRACT FROM AUTHOR]

Numerous research efforts have been conducted to simulate the crowd movements, while relatively few of them are specifically focused on multihazard situations. In this paper, we propose a novel crowd simulation method by modeling the generation and contagion of panic emotion under multihazard circumstances. In order to depict the effect from hazards and other agents to crowd movement, we first classify hazards into different types (transient and persistent, concurrent and nonconcurrent, and static and dynamic) based on their inherent characteristics. Second, we introduce the concept of perilous field for each hazard and further transform the critical level of the field to its invoked-panic emotion. After that, we propose an emotional contagion model to simulate the evolving process of panic emotion caused by multiple hazards. Finally, we introduce an emotional reciprocal velocity obstacles (RVOs) model to simulate the crowd behaviors by augmenting the traditional RVO model with emotional contagion, which for the first time combines the emotional impact and local avoidance together. Our experimental results demonstrate that the overall approach is robust, can better generate realistic crowds and the panic emotion dynamics in a crowd. Furthermore, it is recommended that our method can be applied to various complex multihazard environments. [ABSTRACT FROM AUTHOR]

This paper considers valence-based framing, i.e. a description of equivalent outcomes in either a positive or negative light, in order to reduce transport-related CO 2 emissions. This nudge is easier to implement than more traditional tools, such as taxation, and does not rely on the stringent assumption that individuals are fully rational. The findings from a discrete choice experiment focusing on long-distance travel choice are reported herein. Results indicate that a loss framing on CO 2 emissions significantly increases the respondents' pro-environmental behaviors. Moreover, it is shown that the magnitude of the framing effect depends on individuals' motivational orientation, and that preferences are sensitive to individuals' psychological factors (i.e. preference for the future and environmental self-identity). • Some social psychological theories are tested in a split sample DCE on transportation. • The effect of attribute valence framing on preferences is investigated. • Loss framing on CO 2 emissions strengthens pro-environmental behaviors. • But gain framing for this CO 2 attribute has no significant effect. • Framing effects depend on individuals' motivational orientation. [ABSTRACT FROM AUTHOR]

The project of identifying the cognitive mechanisms or information-processing functions that cause people to categorize others by their race is one of the longest-standing and socially-impactful scientific issues in all of the behavioral sciences. This paper addresses a critical issue with one of the few hypotheses in this area that has thus far been successful—the alliance hypothesis of race—which had predicted a set of experimental circumstances that appeared to selectively target and modify people's implicit categorization of others by their race. Here, we will show why the evidence put forward in favor of this hypothesis was not in fact evidence in support of the hypothesis, contrary to common understanding. We will then provide the necessary and crucial tests of the hypothesis in the context of conflictual alliances, determining if the predictions of the alliance hypothesis of racial categorization in fact hold up to experimental scrutiny. When adequately tested, we find that indeed categorization by race is selectively reduced when crossed with membership in antagonistic alliances—the very pattern predicted by the alliance hypothesis. This finding provides direct experimental evidence that the human mind treats race as proxy for alliance membership, implying that racial categorization does not reflect attention to physical features per se, but rather to social relationships. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) based Speech Emotion Recognition (SER) has been widely used in the consumer field for control of smart home personal assistants, with many such devices on the market. However, with the increase in computational power, connectivity, and the need to enable people to live in the home for longer though the use of technology, then smart home assistants that could detect human emotion will improve the communication between a user and the assistant enabling the assistant of offer more productive feedback. Thus, the aim of this work is to analyze emotional states in speech and propose a suitable method considering performance verses complexity for deployment in Consumer Electronics home products, and to present a practical live demonstration of the research. In this article, a comprehensive approach has been introduced for the human speech-based emotion analysis. The 1-D convolutional neural network (CNN) has been implemented to learn and classify the emotions associated with human speech. The paper has been implemented on the standard datasets (emotion classification) Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) and Toronto Emotional Speech Set database (TESS) (Young and Old). The proposed approach gives 90.48%, 95.79% and 94.47% classification accuracies in the aforementioned datasets. We conclude that the 1-D CNN classification models used in speaker-independent experiments are highly effective in the automatic prediction of emotion and are ideal for deployment in smart home assistants to detect emotion. [ABSTRACT FROM AUTHOR]

Background: The most popular tool used for measuring personality traits is the Five-Factor Model (FFM). It includes neuroticism, extraversion, openness, agreeableness and conscientiousness. Many studies indicated the association of genes encoding neurotransmitter receptors/transporters with personality traits. The relationship connecting polymorphic DNA sequences and FFM features has been described in the case of genes encoding receptors of cannabinoid and dopaminergic systems. Moreover, dopaminergic system receives inputs from other neurotransmitters, like GABAergic or serotoninergic systems. Methods: We searched PubMed Central (PMC), Science Direct, Scopus, Cochrane Library, Web of Science and EBSCO databases from their inception to November 19, 2020, to identify original studies, as well as peer-reviewed studies examining the FFM and its association with gene polymorphisms affecting the neurotransmitter functions in central nervous system. Results: Serotonin neurons modulate dopamine function. In gene encoding serotonin transporter protein, SLC6A4, was found polymorphism, which was correlated with openness to experience (in Sweden population), and high scores of neuroticism and low levels of agreeableness (in Caucasian population). The genome-wide association studies (GWASs) found an association of 5q34-q35, 3p24, 3q13 regions with higher scores of neuroticism, extraversion and agreeableness. However, the results for chromosome 3 regions are inconsistent, which was shown in our review paper. Conclusions: GWASs on polymorphisms are being continued in order to determine and further understand the relationship between the changes in DNA and personality traits. [ABSTRACT FROM AUTHOR]

In Britain, mindfulness practice has increasingly been incorporated into preventative healthcare as a support for psychological resilience. An awareness practice originating in Buddhism, mindfulness is framed as a scientifically verified way of cultivating a skilful engagement with life to support mental health. What has led to this unprecedented interest in mindfulness? And how have British people come to think of cultivating a kindly relationship with their own minds as a constituent aspect of the "good life"? In this paper, I explore the specifically British history that informs the association between mindfulness and psychological resilience today. I show that the association between psychological resilience and mindfulness practice is the result of broader historical concerns about the nature of modern society and psychology. Taking a genealogical approach, I argue that changing patterns in British psychology and Buddhism, while framed in universalist registers, are constituted in and constitutive of a broader historical and political context. [ABSTRACT FROM AUTHOR]

This paper is the second part of a work that aims to rethink the concept of beauty as close as possible to its essence and in a way that integrates the science of aesthetics with the field of construction. Within other theoretical and practical works, this study may be further used to physically reflect the definition of beauty in areas such as architecture, civil engineering or urban planning and support professionals in designing and building beautiful objects and constructions. However, it has to be added that the assumption that there must be a particular original aspect related to beauty that leads a human-made object to success, needs to be further identified. The approach to the concept of beauty is through a general philosophical perspective and partially through the areas mentioned above. The second part of the study includes the synthesised guidance provided by Monroe Beardsley through the theories on beauty from the nineteenth century until today. In addition, it comprises the scheme of concepts that characterised the beautiful in this time, including the lines that guided its study, previous ideas that support our later views on presented theory, and a brief exposition of Maslow's theory of human motivation followed by our theory on beauty and the conclusions. [ABSTRACT FROM AUTHOR]

Background: Within days, the corona crisis has forced the "Lernzentrum", as well as all other places of training and further education, to discontinue classroom teaching at German universities and vocational schools. In order to start teaching online, tutors had to face the challenge to develop new digital learning formats (virtual classrooms) for the peer teaching of practical skills within a short time. This paper aims at outlining the project of developing e-tutorials with regard to the teaching of practical skills. Methodology: After analyzing the classroom lessons (n=30), some of the tutorials were transformed into digital formats. These so-called "e-tutorials" were held via a digital platform. They have been evaluated continuously with a standardized online questionnaire. The results of this evaluation have been analyzed descriptively. Results: From 27/04/2020 to 17/07/2020 eleven different e-tutorial formats were offered on 246 dates. The evaluation revealed a high degree of acceptance with these course offers as well as with the implementation by the tutors. Interpretation: During the pandemic crisis the substitution of peer teaching into forms of e-tutorials was considered valuable; however, these learning formats present challenges, especially with regard to the interaction between teachers and students. They cannot therefore fully replace the peer teaching of practical skills. [ABSTRACT FROM AUTHOR]

This retrospective describes the overall research project that gave rise to the authors’ paper “Neuronlike adaptive elements that can solve difficult learning control problems” that was published in the 1983 Neural and Sensory Information Processing special issue of the IEEE Transactions on Systems, Man, and Cybernetics. This look back explains how this project came about, presents the ideas and previous publications that influenced it, and describes our most closely related subsequent research. It concludes by pointing out some noteworthy aspects of this article that have been eclipsed by its main contributions, followed by commenting on some of the directions and cautions that should inform future research. [ABSTRACT FROM AUTHOR]

Background. Despite substantial progress in the treatment of hepatitis C through the use of direct-acting antivirals which have been shown to cure the disease, complementary and alternative medicines (CAM) are popular among patients as a substitute or complement of allopathic medicines. This study aimed to explore the perspectives of patients and CAM practitioners on the use of CAM for the treatment of hepatitis C in Pakistan. Methods. A cross-sectional design was adopted. Participants (CAM practitioners and patients) were recruited from the capital and two provinces: Khyber Pakhtunkhwa and Punjab of Pakistan. A survey using paper-based questionnaires, each specific for patients and CAM practitioners, was conducted to gather information pertaining to demography, disease status, treatment history, and participants' perspectives (about the disease, reasons to switch to CAM, and referring source). Results. A total of 417 respondents (n = 284 patients, n = 133 practitioners) were recruited. Of the total patients, 170 (59.9%) had started CAM during the previous three months. There were 168 (59.2%) of the total patients who had used allopathic treatments for hepatitis C prior to their use of CAM. The confidence in CAM (24.6%), high cost (19%), and unbearable side effects (52.1%) of allopathic medicines were the main reasons to switch to CAM treatment. Majority (49.3%) of the patients were referred to CAM on the recommendations of relatives or care givers (17.3%) whereas only 9.5% were referred by health care professionals. Out of 133 practitioners, 48 (36.1%) were practicing herbal medicines. From practitioners' perspectives, club-moss (Lycopodium clavatum) was the best treatment option for hepatitis C. The majority, 73 (54.9%), of the patients had chosen to use CAM because of the side effects of allopathic medicines. Patients who had previous "good experience" with CAM were the most common referral source (56.4%) for CAM use in hepatitis C. Conclusions. Patients' beliefs in CAM, side effects of allopathic therapy, high cost of allopathic medicines, and referrals from previous CAM users are key factors in the switching of hepatitis C patients to CAM. [ABSTRACT FROM AUTHOR]

Three Pillars of Conservation Psychology Authors in this special section investigated the first pillar of conservation psychology by identifying how context shapes behavior. Just how central values are to understanding human behavior in conservation contexts is highlighted by Wallen and Landon's (2020) systematic map of conservation psychology, which shows values are the second-most studied concept. Winkler-Schor et al. (2020 [this issue]) investigated relationships between a typology of values and self-reported conservation behaviors, finding that altruistic (i.e., concern for others' welfare), biospheric (i.e., concern about costs and benefits to ecosystems), and eudaimonic (i.e., concern about pursuit of meaning and self-realization) values are closely associated with private-sphere conservation behaviors that are more often reported than public-sphere behaviors. Next Steps for Conservation Psychology The papers in this special section demonstrate the potential of conservation psychology to enhance conservation theory and practice. [Extracted from the article]

Research problem: During humanitarian crises, communities of people face various types of dangers. To counter the dangers, they need information in a short period. Such need creates the opportunity for misinformation. Such misinformation can result in information harms that can generate short- or long-term consequences. Literature review: Prior researchers have tackled the situation by using technical or behavioral approaches. Research question: What are the harms from misinformation? We propose a taxonomy of 15 information harms grouped in 8 categories and assess the perception of risk regarding the harms through a survey of respondents who have experienced crisis response situations. Methodology: This paper examines two scenarios, the 2013 Boston Marathon bombing and the 2017 Oroville Dam evacuation order crises, through two dimensions: Likelihood of occurrence and Level of impacts of the harms. Results and conclusions: Findings are presented through visualization and test results for significant differences of harms between scenarios. Similar groups of harms are identified with different severity levels based on post hoc analyses: those with 1. high likelihood and low impact (psychological and confusion harms), 2. low likelihood and low impact (reputation and privacy harms), and 3. low likelihood and high impact (physical, financial, safety, and social harms). In addition to establishing the taxonomy of misinformation harms, findings will have practical value in emergency response and recovery activities to effectively prioritize resources to minimize specific harms from misinformation in crises. Further research directions are also discussed. [ABSTRACT FROM AUTHOR]

The developmental origins of synaesthesia have only recently become the focus of serious scientific research. Most existing theories posit a simple genetic mutation as the primary causal factor in synaesthetic development, but it is widely recognized that a complete theory will have to involve learning in some manner. Our paper presents the developmental learning hypothesis (DLH) of synaesthesia, which, as the name suggests, treats learning as a central component of the development of synaesthesia. According to the DLH, synaesthesia arises, at least in part, as a strategic response to specific learning challenges faced in childhood. The paper focusses on grapheme-colour synaesthesia, in which individuals associate specific colours with letters and numerals. We describe a number of the problems faced by children becoming literate, ranging from learning to identify individual letters to learning to keep phonemes in the correct order when reading, and illustrate ways in which grapheme-colour synaesthesia might be helpful in solving these problems. [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]

Background An increasing number of studies have suggested adverse effects of air pollution on mental health. Given the potentially negative impacts of ozone exposure on the immune and nervous system driven from animal experiments, ozone might also affect mental health. However, no systematic synthesis of the relevant literature has been conducted yet. This paper reviews the studies that assessed the link between ozone exposure and mental health thus far. Methods We followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA). PubMed, Web of Science, and EMBASE were systematically searched for epidemiological studies on ambient ozone exposure and mental or behavioral disorders according to the International Classification of Disease. The period was from January 1st, 1960 to December 14st, 2017. We evaluated the risk of bias by the Office of Health Assessment and Translation (OHAT) Approach and Navigation Guide for each included study. Results The keyword search yielded 567 results. 31 papers met the selection criteria and were included in the review. We found only inconclusive evidence that ozone affects autism spectrum disorders, impairment of cognitive functions and dementia, depression, and suicide. The large heterogeneity of study designs, outcome definitions and study quality in general prevented us from conducting meta-analyses. Conclusions Current evidence for an association between ambient ozone exposure and mental health outcomes is inconclusive and further high quality studies are needed to assess any potential links given the strong biologic plausibility. [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]

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]

This paper investigated the psychological effects of viewing ultra-high-resolution images. Many subjective evaluation experiments assessing the quality of images have been conducted. However, the psychological effects of viewing ultra-high-resolution images have not been well investigated, especially under non-standard viewing conditions. Although a higher image resolution has been reported to affect the sense of realness, more impressive factors that appeal to the general viewers have not been examined. This paper conducted subjective evaluation experiments, in which images with different resolutions using familiar subjects were presented to viewers with practical viewing distances, and their ratings of impressions were obtained. In addition, we examined the relationship between higher- and lower-order impressions. We found an enhancement of the impressions of “beautiful” or “delicious” with an increase in the resolutions of the presented images. Furthermore, the tendency of this impression enhancement was observed even when viewing it as far as four times the design viewing distance. The results of multiple regression analyses provide insight on the production and processing of ultra-high-resolution images for impression enhancement. [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]

There is an increasing interest in using healing gardens in general hospitals and in pediatric hospitals in particular since it has an important psychological impact on children for instance it reduces stress. The paper focuses on the impact of health care on hospitalized children, theories of environmental restoration and design guidelines for healing gardens in children's hospitals. The paper aims to prove the relation between the design of healing garden and hospitalized children behavior to discover if certain elements of design principles have indeed a positive impact on psychological recovery of children, and if so, what are these elements and how they can be improved. The paper examined the perceptions of 25 children towards the healing garden in the pediatric cancer hospital in Egypt and the results revealed that, 80% of children showed satisfaction toward the garden. 20% of them gave no negative comments. Additionally, fifth likert scale was conducted to identify the impact of healing garden on psychological recovery of children. The results showed that not only 95.6% of 50 specialized therapists and psychiatrists admitted that the communication with nature has a positive effect on psychological recovery of children. The most important survey was made with 50 volunteers who discussed the effectiveness of 25 elements from 6 design principles for a healing garden in pediatric cancer hospital. These principles was agreed on by the volunteers with different percentage sense of control (74.8%), Social support(74.6%), positive distractions(67.6%), sensorial dimensions(53.2%), movement and exercise(60.4 %) and Natural distractions(89.2%). Finally, the paper is concluding that healing gardens have an important role in increasing the communication between sick children and nature, improving cognitive performance and promoting psychological recovery. [ABSTRACT FROM AUTHOR]

Aim: To systematically review literature on health-related quality of life (HRQoL) of children and adolescents (≤18yo) with cerebral palsy (CP) from low- and middle-income countries (LMICs) to identify trends in HRQoL and areas for future research.Method: We systematically reviewed six key bibliographic databases and two reviewers independently screened results. Peer-reviewed original articles examining HRQoL of children from LMICs were eligible.Results: A total of 22 524 papers were identified, of which 16, from eight LMICs, were included. Four measures of HRQoL were used; Child Health Questionnaire Parent Form 50 (n=5); Paediatric Quality of Life Inventory 3.0 and 4.0 (n=4); CP Quality of Life Questionnaire for Children (n=4); Lifestyle Assessment Questionnaire CP (n=3). Children with CP from LMICs (n=1579; 2-18y) had significantly poorer HRQoL on all instrument dimensions when compared to age-matched controls (p<0.003) and on all except two dimensions when compared to peers in high-income countries (p<0.001). Physical well-being dimensions of HRQoL were poorest overall and associated with impaired motor function.Interpretation: Research to improve HRQoL in LMICs is required and should address all aspects of HRQoL. Future research is recommended to incorporate multi-respondent assessment, utilize both general and CP-specific measures of HRQoL, and delineate adolescents as a unique cohort. What this paper adds Children with cerebral palsy from low- and middle-income countries are at high risk of poor health-related quality of life (HRQoL). Physical well-being was poorest dimension of HRQoL and associated with impaired motor function. [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]

Pruning is applied in order to combat over-fitting problem where the tree is pruned back with the goal of identifying decision tree with the lowest error rate on previously unobserved instances, breaking ties in favour of smaller trees with high accuracy. In this paper, pruning with Bayes minimum risk is introduced for estimating the risk-rate. This method proceeds in a bottom-up fashion converting a parent node of a subtree to a leaf node if the estimated risk-rate of the parent node for that subtree is less than the risk-rates of its leaf. This paper proposes a post-pruning method that considers various evaluation standards such as attribute selection, accuracy, tree complexity, and time taken to prune the tree, precision/recall scores, TP/FN rates and area under ROC. The experimental results show that the proposed method produces better classification accuracy and its complexity is not much different than the complexities of reduced-error pruning and minimum-error pruning approaches. The experiments also demonstrate that the proposed method shows satisfactory performance in terms of precision score, recall score, TP rate, FP rate and area under ROC. [ABSTRACT FROM AUTHOR]

A considerable body of research has documented the negative effects of job burnout on employees and their organizations, emphasizing the importance of the identification of early signs of the phenomenon for the purposes of prevention and intervention. However, such timely identification is difficult due to the time and cost of assessing the burnout levels of all employees in an organization using established scales. In this paper, we propose an innovative way to identify employees at risk of job burnout by analyzing their e-mail communication patterns. Building on the Job Demands–Resources model, we theorize about the relationship between e-mail communication patterns and levels of employee exhaustion and disengagement (two dimensions of burnout). We analyzed 52,190 e-mails exchanged between 57 employees of a medium sized R&D company over a five-month period. We then related these employees’ communication patterns to their levels of burnout, collected using an established scale (the OLBI–Oldenburg Burnout Inventory). Our results provide support for the overall proposition of the paper, that e-mail communications can be used to identify individuals at risk of job burnout. Our models explain up to 34% of the variance of burnout and up to 37% and 19% respectively of the variance of exhaustion and disengagement. They also successfully distinguish between employees with a higher risk of burnout and those with lower levels of risk (F1 score of 84% with recall of 100% and 73% precision). We discuss the implications of our results and present suggestions for future research. [ABSTRACT FROM AUTHOR]

Aim: To determine whether any parent and child report sleep measure tools have been validated in children aged 0-18 years with cerebral palsy (CP).Method: A systematic search of five databases was performed up to June 2017. Studies were included if a sleep measure tool was used to evaluate sleep in children 0-18 years with CP based on international classifications of sleep. Sleep measures were assessed for psychometric data in children with CP.Results: Only one paper which used the Schlaffragebogen für Kinder mit Neurologischen und Anderen Komplexen Erkrankungen (SNAKE) questionnaire met the study criteria. The four other measures frequently used in children with CP had no psychometric data available for their use in children with CP. The SNAKE questionnaire has been validated only in children with CP in Gross Motor Function Classification System level V. The Sleep Disturbance Scale for Children and the Pediatric Sleep Questionnaire had the strongest psychometric properties in typically developing children, but has not yet been validated in children with CP.Interpretation: Current sleep measures being administered in typically developing children are also often used in children with CP, but have not been well validated in this group of children.What This Paper Adds: There are no condition specific measures of sleep in children with cerebral palsy (CP). The Schlaffragebogen für Kinder mit Neurologischen und Anderen Komplexen Erkrankungen (SNAKE) questionnaire is validated for children with CP in Gross Motor Function Classification System level V. A framework to design a CP specific sleep questionnaire is provided. [ABSTRACT FROM AUTHOR]

Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-of-the-art algorithms to rescan the entire database. Subsequently, the process incurs heavy computation cost and is not feasible for real-time applications. The paper addresses efficiently the problem of threshold dynamic updation for a given purpose. The paper contributes by presenting a novel ARM approach that creates an intermediate itemset and applies a threshold to extract categorical frequent itemsets with diverse threshold values. Thus, improving the overall efficiency as we no longer needs to scan the whole database. After the entire itemset is built, we are able to obtain real support without the need of rebuilding the itemset (e.g. Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. The proposed approach outperforms the extant state-of-the-art and shows promising results that reduce computation cost, increase accuracy, and produce all possible itemsets. [ABSTRACT FROM AUTHOR]

In previous papers, we introduced a normative scheme for scene construction and epistemic (visual) searches based upon active inference. This scheme provides a principled account of how people decide where to look, when categorising a visual scene based on its contents. In this paper, we use active inference to explain the visual searches of normal human subjects; enabling us to answer some key questions about visual foraging and salience attribution. First, we asked whether there is any evidence for ‘epistemic foraging’; i.e. exploration that resolves uncertainty about a scene. In brief, we used Bayesian model comparison to compare Markov decision process (MDP) models of scan-paths that did–and did not–contain the epistemic, uncertainty-resolving imperatives for action selection. In the course of this model comparison, we discovered that it was necessary to include non-epistemic (heuristic) policies to explain observed behaviour (e.g., a reading-like strategy that involved scanning from left to right). Despite this use of heuristic policies, model comparison showed that there is substantial evidence for epistemic foraging in the visual exploration of even simple scenes. Second, we compared MDP models that did–and did not–allow for changes in prior expectations over successive blocks of the visual search paradigm. We found that implicit prior beliefs about the speed and accuracy of visual searches changed systematically with experience. Finally, we characterised intersubject variability in terms of subject-specific prior beliefs. Specifically, we used canonical correlation analysis to see if there were any mixtures of prior expectations that could predict between-subject differences in performance; thereby establishing a quantitative link between different behavioural phenotypes and Bayesian belief updating. We demonstrated that better scene categorisation performance is consistently associated with lower reliance on heuristics; i.e., a greater use of a generative model of the scene to direct its exploration. [ABSTRACT FROM AUTHOR]

Highly automated driving will change driver's behavioural patterns. Traditional methods used for assessing manual driving will only be applicable for the parts of human-automation interaction where the driver intervenes such as in hand-over and take-over situations. Therefore, driver behaviour assessment will need to adapt to the new driving scenarios. This paper aims at simplifying the process of selecting appropriate assessment methods. Thirty-five papers were reviewed to examine potential and relevant methods. The review showed that many studies still relies on traditional driving assessment methods. A new method, the Failure-GAM2E model, with purpose to aid assessment selection when planning a study, is proposed and exemplified in the paper. Failure-GAM2E includes a systematic step-by-step procedure defining the situation, failures (Failure), goals (G), actions (A), subjective methods (M), objective methods (M) and equipment (E). The use of Failure-GAM2E in a study example resulted in a well-reasoned assessment plan, a new way of measuring trust through feet movements and a proposed Optimal Risk Management Model. Failure-GAM2E and the Optimal Risk Management Model are believed to support the planning process for research studies in the field of human-automation interaction. [ABSTRACT FROM AUTHOR]

Background: Collaboration between humans and computers has become pervasive and ubiquitous, however current computer systems are limited in that they fail to address the emotional component. An accurate understanding of human emotions is necessary for these computers to trigger proper feedback. Among multiple emotional channels, physiological signals are synchronous with emotional responses; therefore, analyzing physiological changes is a recognized way to estimate human emotions. In this paper, a three-stage decision method is proposed to recognize four emotions based on physiological signals in the multi-subject context. Emotion detection is achieved by using a stage-divided strategy in which each stage deals with a fine-grained goal.Methods: The decision method consists of three stages. During the training process, the initial stage transforms mixed training subjects to separate groups, thus eliminating the effect of individual differences. The second stage categorizes four emotions into two emotion pools in order to reduce recognition complexity. The third stage trains a classifier based on emotions in each emotion pool. During the testing process, a test case or test trial will be initially classified to a group followed by classification into an emotion pool in the second stage. An emotion will be assigned to the test trial in the final stage. In this paper we consider two different ways of allocating four emotions into two emotion pools. A comparative analysis is also carried out between the proposal and other methods.Results: An average recognition accuracy of 77.57% was achieved on the recognition of four emotions with the best accuracy of 86.67% to recognize the positive and excited emotion. Using differing ways of allocating four emotions into two emotion pools, we found there is a difference in the effectiveness of a classifier on learning each emotion. When compared to other methods, the proposed method demonstrates a significant improvement in recognizing four emotions in the multi-subject context.Conclusions: The proposed three-stage decision method solves a crucial issue which is 'individual differences' in multi-subject emotion recognition and overcomes the suboptimal performance with respect to direct classification of multiple emotions. Our study supports the observation that the proposed method represents a promising methodology for recognizing multiple emotions in the multi-subject context. [ABSTRACT FROM AUTHOR]

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles is a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.), dusty weather in arid and semi-arid regions, at night, etc. Also, it is very important to consider speed of vehicles in the complicated weather condition. In this paper, we improved our method to track and count vehicles in dusty weather with vibrating camera. For this purpose, we used a background subtraction based strategy mixed with an extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a generalized particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result, with Centroid of each blob we calculated distance between two frames by simple formula and hence dividing it by the time between two frames obtained from the video. Our proposed method was tested on several video surveillance records in different conditions such as dusty or foggy weather, vibrating camera, and in roads with medium-level traffic volumes. The results showed that the new proposed method performed better than our previously published method and other methods, including the Kalman filter or Gaussian model, in different traffic conditions. [ABSTRACT FROM AUTHOR]

What drives affective polarization in American politics? One common argument is that Democrats and Republicans are deeply polarized today because they are psychologically different--motivated by diametrically opposed and clashing worldviews. This paper argues that the same psychological motivation--authoritarianism--is positively related to partisan extremism among both Republicans and Democrats. Across four studies, this paper shows that authoritarianism is associated with strong partisanship and heightened affective polarization among both Republicans and Democrats. Thus, strong Republicans and Democrats are psychologically similar, at least with respect to authoritarianism. As authoritarianism provides an indicator of underlying needs to belong, these findings support a view of mass polarization as nonsubstantive and group-centric, not driven by competing ideological values or clashing psychological worldviews. [ABSTRACT FROM AUTHOR]