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Studying ionic wind is crucial for deepening our comprehension of electrical discharge processes and refining their application in industrial technologies. This research investigates the behavior of needle–needle electrode using high-speed schlieren imaging techniques, focusing on the dynamics of ionic wind and its influence on spark discharge channel formation. Observations indicate that the ionic wind generated during corona discharge provides a structured pathway that significantly guides the development of spark discharge channels, particularly evident in horizontal configurations. Our findings reveal that the velocity and density of the ionic wind increase with decreasing curvature radius of the needle tip, thereby enhancing its guiding effect. Furthermore, the spark discharge channel forms through the convergence of positive and negative streamers, which meet near the cathode, leading to substantial disturbances in the surrounding flow field post-discharge. This research highlights the intricate relationship between corona and spark discharges, demonstrating the critical role of ionic wind in influencing discharge channel morphology and offering insights for future applications in plasma and electrostatic-based technologies. [ABSTRACT FROM AUTHOR]

Cybersecurity is a present and growing concern that needs to be addressed with both behavioral and design-oriented research. Public cloud providers such as Amazon Web Services and federal funding agencies such as the National Science Foundation have invested billions of dollars into developing high-performance computing resources accessible to users through configurable virtual machine (VM) images. This approach offers users the flexibility of changing and updating their environment for their computational needs. Despite the substantial benefits, users often introduce thousands of vulnerabilities by installing open-source software packages and misconfiguring file systems. Given the scale of vulnerabilities, security personnel struggle to identify and prioritize vulnerable assets for remediation. In this research, we designed a novel unsupervised deep learning-based Multi-View Combinatorial-Attentive Autoencoder (MV-CAAE) to capture multi-dimensional vulnerability data and automatically identify groups of similar vulnerable compute instances to help facilitate the development of targeted remediation strategies. We rigorously evaluated the proposed MV-CAAE against state-of-the-art methods in three technical clustering experiments. Experiment results indicate that the MV-CAAE achieves V-measure scores (metric of cluster quality) 8 percent-48 percent higher than benchmark methods. We demonstrated the practical value through a comprehensive case study by clustering vulnerable VMs and gathering qualitative feedback from experienced security professionals through semi-structured interviews. The results indicated that clustering vulnerable assets can help prioritize vulnerable instances for remediation and enhance decision-making tasks. The present design-research work also contributes to our theoretical knowledge of cyber-defense. [ABSTRACT FROM AUTHOR]

Over the past 50 years, consumer researchers have presented extensive evidence that consumer preference can be swayed by the decision context, particularly the configuration of the choice set. Importantly, behavioral research on context effects has inspired prominent quantitative research on multialternative decision-making published in leading psychology, management, economics, and general interest journals. While both streams of research seem to agree that context effects are an important research area, there has been relatively limited interaction, communication, and collaboration between the two research camps. In this article, we seek to initiate an active dialogue between the two sides. We begin by providing a critical overview of the two literatures on context effects, discussing both their strengths and weaknesses, as well as disparities and complementarities. Here, we place particular emphasis on deepening consumer researchers' understanding of context effects by drawing on prominent quantitative research published in non-marketing journals over the last decades. Importantly, we provide a roadmap for the future that can inspire further research and potential collaborations between the two camps, overcoming silos in knowledge creation. [ABSTRACT FROM AUTHOR]

The early years, which encompass the first 4 years of life, are a critical period for development and have long-term implications for health. Physical activity is an important behavior that supports healthy development during this time. However, research on movement behaviors in the early years is still limited compared to other age groups. This article highlights the current evidence and future research directions for understanding movement behaviors in the early years, including the need for longitudinal studies, standardized measurement tools, and interventions that target all movement behaviors. Additionally, there is a call for research that focuses on children aged <3 years, as well as low- and middle-income countries, to address health inequities and promote population health. [Extracted from the article]

We analyze how individual investors respond to inflation. We introduce a unique data set containing information on local inflation and security portfolios of more than 2,000 clients of a German bank between 1920 and 1924, covering the German hyperinflation. We find that individual investors buy fewer (sell more) stocks when facing higher local inflation. This effect is more pronounced for less sophisticated investors. Moreover, we document a positive relation between local inflation and forgone returns following stock sales. Our findings are consistent with individual investors suffering from money illusion. Alternative explanations, such as consumption needs, are unlikely to drive our results. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

The article discusses the potential benefits of using artificial intelligence (AI) and machine learning (ML) tools and algorithms in physical activity and sedentary behavior research. While AI and ML have been widely utilized in healthcare and medicine, their application in studying physical activity and sedentary behavior is still underutilized. The article highlights the capabilities of AI and ML in generating novel hypotheses, improving measurement of behaviors, predicting health indicators, and advancing precision medicine. However, there are challenges in implementing these techniques, including ethical concerns and limitations in identifying cause-effect relationships. Overall, integrating AI and ML tools can contribute to a deeper understanding of physical activity and sedentary behavior. [Extracted from the article]

Existing research on the effects of women's descriptive representation on citizens' attitudes has mainly investigated potential positive effects, namely on political engagement or the legitimacy of outcomes. However, trends in representation have rarely been theorized as potential causes of resentment among women. While a male backlash to increasing representation has been theorized, this article argues that women may also be discontent with their trajectory of representation, if they perceive it as stagnating. Using a survey experiment fielded in Germany, the results show that a stagnating representation trajectory mobilizes women to vote for a progressive party, the German Greens. In contrast, the paper demonstrates that men do not lash back against women's increasing representation, even if they realize that this means a lower standing for themselves. This article contributes to research on political behavior by highlighting that discontent with persisting inequality is a mobilizing factor for progressive parties. [ABSTRACT FROM AUTHOR]

Water security as a concept recognizes the profound connections between the physical and social aspects of water. Yet, water security research features limited perspectives from two disciplines directly concerned with human behavior—the behavioral and psychological sciences. This review aims to characterize the main areas of research on water (including floods and droughts) which do feature concepts and methods from the behavioral and psychological sciences, discuss knowledge gaps, and draw attention to their potential to contribute to water‐related research. Bibliometric mapping of published water research identifies five research clusters and associated sub‐clusters: risk perception and flood, climate change and drought, water quality and water conservation, drinking water and bottled water, and mental health and WASH. A summary of research in each cluster and sub‐cluster highlights the application of many conceptual frameworks and behavioral determinants associated with water‐related behavior. Few articles focus on the role of governance or structural factors, and studies in low‐ and middle‐income countries are less represented in some clusters. The discussion considers the scope to apply higher level organizing frameworks for structuring behavioral and psychological science applications in water security and for exploring synergies with the physical and wider social sciences. In conclusion, further engagement with behavioral and psychological science within, between, and beyond the clusters identified here, could potentially deepen understanding of human–water interactions and enhance the design of measures to promote water security. This article is categorized under:Human Water > Water GovernanceHuman Water > Water as Imagined and RepresentedScience of Water > Water and Environmental Change [ABSTRACT FROM AUTHOR]

We argue that research aiming to understand or change human behavior must measure real behavior, not just behavioral intentions, to draw valid conclusions. The work highlights the well-established gap between people's intentions and behavior across various tourism and hospitality contexts. Methodologically, we encourage authors not to rely on behavioral intentions and instead measure real behavior. We provide an overview of methods available to capture real behavior either automatically or manually in tourism contexts. The article also introduces a special issue in the Journal of Sustainable Tourism that showcases the measurement of real environmentally significant tourist behavior using diverse methods, such as biometric techniques, big data analytics, field observations, and experiments. We conclude by discussing five issues that prevent studies form drawing causal conclusions about behavior, namely, (i) reliance on behavioral intentions; (ii) a sample that does not reflect the population of interest; (iii) errors in measuring latent psychological constructs; (iv) consumer hypocrisy and social desirability bias; and (v) situational factors and habits. By advocating for a transition towards measuring real behavior, the article and the special issue aim to increase the validity and impact of research seeking to understand human behavior and drive effective behavior change for addressing global challenges. Highlights: Much tourism research aims to understand or change behavior. Yet, behavior is not routinely measured, limiting the validity of findings. This article discusses the many possible approaches to capturing real behavior. This article outlines the most valid research design to study behavior (change). This article introduces the special issue on measuring real behavior. [ABSTRACT FROM AUTHOR]

In behavioral and social research, questionnaires are an important assessment tool, through which individuals can be categorized according to how they classify themselves in respect to a personal trait. One example is the Major Depression Inventory (MDI), which is widely used for the assessment of depression. It can also be used as a depression severity scale, with scores ranging from 0 to 50 constructed considering the same weight for each item in the MDI. However, the dependence among the items of the questionnaire suggests that a score with better properties could be obtained through factor models, which besides allowing to reduce the dimensionality of multivariate data, provides the estimation of common factors and factor loadings that often have an interesting theoretical interpretation. Additionally, auxiliary information could be available and, the effect of these variables in the latent factor could be estimated and provide interesting results. Thus, the main aim of this paper is to propose a factor model for ordered categorical data which incorporates auxiliary variables to explain the latent factors. The proposed model provides an alternative score to MDI based on the estimated latent factors that takes the uncertainty in the data and auxiliary information into account. [ABSTRACT FROM AUTHOR]

Behavioral research demonstrates a critical transition in preschooler's mental‐state understanding (i.e., theory of mind; ToM), revealed most starkly in performance on tasks about a character's false belief (e.g., about an object's location). Questions remain regarding the neural and cognitive processes differentiating children who pass versus fail behavioral false‐belief tasks and the extent to which there is continuity versus change in the ToM neural network. To address these questions, we analyzed event‐related spectral power in the electroencephalogram (EEG) to investigate how preschoolers' neural activity during passive viewing of false‐belief scenarios related to their explicit behavioral ToM performance. We found that neural activity during passive viewing of false‐belief events (6–9 Hz EEG 'alpha' suppression in right temporoparietal [RTP] electrodes) strongly related to children's explicit ToM. However, children's RTP alpha suppression differed depending on their explicit behavioral ToM performance: Children who did better on a broad battery of standard ToM tasks and who passed explicit behavioral false‐belief tasks showed greater RTP alpha suppression when the character's belief first became false (during the 'location‐change' event); whereas children who did worse on the ToM battery and who failed explicit behavioral false‐belief tasks showed greater RTP alpha suppression only later when they could evaluate the character's behavior in the context of prior events (during the 'active‐search' event). Findings shed light on what differentiates preschoolers who pass versus fail explicit false‐belief tasks and raise questions about how to interpret existing neuroscience data from ToM tasks across infancy to adulthood. Research Highlights: Preschool children's neural activity (EEG 6–9 Hz suppression in right temporoparietal [RTP] electrodes) during passive‐viewing of false‐belief events was related to their explicit behavioral theory‐of‐mind performance.Children who did better on a theory‐of‐mind (ToM) battery and passed explicit false‐belief tasks showed greater RTP alpha suppression when the character's belief first became false.Children who performed worse on the ToM battery and failed explicit false‐belief tasks showed greater RTP alpha suppression later when observing the character's search behavior.Findings reveal change in preschoolers' ToM neural correlates and suggest that the presence of RTP activity does not necessarily indicate 'mature' theory of mind. [ABSTRACT FROM AUTHOR]

Purpose: This scoping review article examined research on information behavior in communities over the past two decades (2000–2023). The review aims to uncover the characteristics and types of communities studied, the featured information behaviors, and the research methods employed. Design/methodology/approach: The PRISMA-ScR guidelines were followed to conduct this review. Five databases were selected to search for relevant empirical research. A total of 57 studies met the inclusion criteria for review. Thematic synthesis was used to analyze the multidimensional findings of included studies. Findings: A steady increase in the number of articles is evident in the past two decades. The review suggests that information behavior in community studies involved collaboration from other disciplines, such as public health and business management. More than half of the communities studied are virtual communities (56.1%), followed by communities of identity, professional communities and support communities, communities of interest, geographic communities, and academic communities. There are overlaps among these categories. Information sharing (63.2%) and information seeking (57.9%) were the most studied behavior of communities, followed by information use, information needs, and information judgment. Questionnaires (38.6%) and interviews (35.1%) were the most commonly used data collection techniques in studying information behavior in communities. It is noteworthy that eleven (19.3%) mentioned utilizing community-engaged approaches. Originality/value: This is the first scoping review to explore the intersecting constructs of community research and information behavior studies. We call for further research to understand the contextual factors that shape the community's information environments and to increase awareness of the partnership between communities and researchers. [ABSTRACT FROM AUTHOR]

Background: Explanations for why social media users propagate misinformation include failure of classical reasoning (over-reliance on intuitive heuristics), motivated reasoning (conforming to group opinion), and personality traits (e.g., narcissism). However, there is a lack of consensus on which explanation is most predictive of misinformation spread. Previous work is also limited by not distinguishing between passive (i.e., "liking") and active (i.e., "retweeting") propagation behaviors. Methods: To examine this issue, 858 Twitter users were recruited to engage in a Twitter simulation task in which they were shown real tweets on public health topics (e.g., COVID-19 vaccines) and given the option to "like", "reply", "retweet", "quote", or select "no engagement". Survey assessments were then given tomeasure variables corresponding to explanations for: classical reasoning [cognitive reflective thinking (CRT)], motivated reasoning (religiosity, political conservatism, and trust in medical science), and personality traits (openness to new experiences, conscientiousness, empathy, narcissism). Results: Cognitive reflective thinking, conscientiousness, openness, and emotional concern empathy were all negatively associated with liking misinformation, but not significantly associated with retweeting it. Trust in medical scientists was negatively associated with retweeting misinformation, while grandiose narcissism and religiosity were positively associated. An exploratory analysis on engagement with misinformation corrections shows that conscientiousness, openness, and CRT were negatively associated with liking corrections while political liberalism, trust in medical scientists, religiosity, and grandiose narcissism were positively associated. Grandiose narcissism was the only factor positively associated with retweeting corrections. Discussion: Findings support an inhibitory role for classical reasoning in the passive spread of misinformation (e.g., "liking"), and a major role for narcissistic tendencies and motivated reasoning in active propagating behaviors ("retweeting"). Results further suggest differences in passive and active propagation, as multiple factors influence liking behavior while retweeting is primarily influenced by two factors. Implications for ecologically valid study designs are also discussed to account for greater nuance in social media behaviors in experimental research. [ABSTRACT FROM AUTHOR]

Data in behavioral research is often quantified with event-logging software, generating large data sets containing detailed information about subjects, recipients, and the duration of behaviors. Exploring and analyzing such large data sets can be challenging without tools to visualize behavioral interactions between individuals or transitions between behavioral states, yet software that can adequately visualize complex behavioral data sets is rare. TIBA (The Interactive Behavior Analyzer) is a web application for behavioral data visualization, which provides a series of interactive visualizations, including the temporal occurrences of behavioral events, the number and direction of interactions between individuals, the behavioral transitions and their respective transitional frequencies, as well as the visual and algorithmic comparison of the latter across data sets. It can therefore be applied to visualize behavior across individuals, species, or contexts. Several filtering options (selection of behaviors and individuals) together with options to set node and edge properties (in the network drawings) allow for interactive customization of the output drawings, which can also be downloaded afterwards. TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. The web application and usage instructions are available at tiba.inf.uni-konstanz.de. The source code is publicly available on GitHub: github.com/LSI-UniKonstanz/tiba. [ABSTRACT FROM AUTHOR]

Introduction: Aggressive behavior among college students is a concerning issue that not only affects the mental health and personal development of those involved but also poses a threat to societal stability. Existing literature has consistently demonstrated a positive correlation between childhood maltreatment and aggressive behavior. However, the specific mechanisms through which childhood maltreatment leads to aggressive behavior remain unclear. This study aims to explore the impact of childhood maltreatment on aggressive behavior among college students and to examine the mediating roles of authenticity and alexithymia in this relationship. Methods: To investigate these relationships, we conducted an online survey among 1,148 Chinese college students. Participants completed the Childhood Trauma Questionnaire-Short Form (CTQ-SF), Authenticity Scale, Toronto Alexithymia Scale (TAS-20), and 12-item Aggression Questionnaire (12-AQ). These instruments allowed us to measure the variables of interest and to analyze the potential mediating effects of authenticity and alexithymia. Results: The findings of our study indicate that both authenticity and alexithymia mediate the positive relationship between childhood maltreatment and aggressive behavior. Specifically, the mediating effect of authenticity was 0.04 (95% CI [0.01, 0.06]), while that of alexithymia was 0.10 (95% CI [0.07, 0.13]). Moreover, we observed a chain-mediating effect involving both authenticity and alexithymia, with a chain-mediating effect of 0.03 (95% CI [0.02, 0.05]). Conclusions: This study demonstrates that childhood maltreatment can positively predict aggressive behavior in college students, and this relationship is mediated individually and sequentially by authenticity and alexithymia. Our findings contribute valuable insights to the existing research on aggressive behavior and provide a theoretical framework for developing interventions aimed at reducing aggressive behaviors among college students. [ABSTRACT FROM AUTHOR]

AbstractIn this study, the buckling behavior of double-walled carbon nanotubes (DWCNTs) is investigated using the initial value method (IVM) combined with the approximate transfer matrix (ATM) approach within the framework of nonlocal elasticity theory. The aim is to provide a method that best estimates the critical buckling loads with improved accuracy and computational efficiency. To validate the method, the critical buckling loads obtained without considering nonlocal effects were compared with results from the literature, showing a high degree of agreement. Various boundary conditions, including simply supported (S-S), clamped-simply supported (C-S), clamped-free (C-F), and clamped-clamped (C-C), have been considered for investigation. The effects of nonlocal parameters, aspect ratios, and boundary conditions on the critical buckling loads are analyzed. The findings emphasize the importance of accounting for these parameters in mechanical analyses to ensure accurate predictions. The proposed framework provides an efficient alternative to existing numerical methods and offers valuable benchmarks for future research on the mechanical behavior of nanostructures. [ABSTRACT FROM AUTHOR]

Social media has provided everyday actors with a platform to share their personal stories and ideas. This has had a profound effect on activism, as movements are increasingly built up and amplified through the circulation of participants’ individualized motivations, experiences, and sentiments. TikTok has emerged as a salient site for studying this turn: it has proven to be a highly successful tool in activist campaigns, strongly affords personalized communication, and supports a main user base of young people known for emphasizing self-expression in their online participation. Since remix is the core form of sharing on TikTok, users are encouraged to insert and articulate themselves not only in the process of content creation, but in the process of circulation as well. Here, we focus on the way remix is exploited as a mode of personalizing activist content on TikTok, particularly among young users. We do so by qualitatively coding and analyzing remixed content associated with the digital activist organization Gen-Z for Change. We find that, despite expectations based on prior research and the observed behavior of older users, young users tended to resist personalization in their remix strategies. Yet, they simultaneously managed to assert their presence in ways that are meaningful on the app. Our results elaborate on digital activist strategies and the role of platform affordances therein, and add important nuance to common conceptions of youth political participation styles. [ABSTRACT FROM AUTHOR]

AbstractThis study investigated the bystander effect by examining intentions to intervene in simulated Facebook Live scenarios. A 4 (number of other viewers: 0 vs. 4 vs. 49 vs. 224) x 2 (level of urgency: non-urgent vs. urgent video) between-subjects experimental design was conducted with 210 participants to examine how the number of bystanders and the perceived urgency of a situation influence self-reported bystander intentions. With individual empathy levels controlled, an ANCOVA test revealed no significant main effect of the number of other viewers on the intention to intervene, but a significant difference was found between the 0 and 224 viewer conditions. Urgent situations elicited higher intervention intentions compared to non-urgent ones, without an interaction effect with viewer number. With the number of other viewers and urgency level as separate independent variables, mediation analysis found patterns differing from the traditional five-step bystander intervention model. These findings enhance our understanding how bystander intentions manifest in social media contexts and highlight the influence of perceived danger and audience size. The implications for online bystander behavior and future research directions are discussed. [ABSTRACT FROM AUTHOR]

Despite considerable behavioral and organizational research on advice from human advisors, and despite the increasing study of artificial intelligence (AI) in organizational research, workplace-related applications, and popular discourse, an interdisciplinary review of advice from AI (vs. human) advisors has yet to be undertaken. We argue that the increasing adoption of AI to augment human decision-making would benefit from a framework that can characterize such interactions. Thus, the current research invokes judgment and decision-making research on advice from human advisors and uses a conceptual "fit"-based model to: (1) summarize how the characteristics of the AI advisor, human decisionmaker, and advice environment influence advice exchanges and outcomes (including informed speculation about the durability of such findings in light of rapid advances in AI technology), (2) delineate future research directions (along with specific predictions), and (3) provide practical implications involving the use of AI advice by human decision-makers in applied settings. [ABSTRACT FROM AUTHOR]

Automation of experimental setups is a promising direction in behavioral research because it can facilitate the acquisition of data while increasing its repeatability and reliability. For example, research in spatial cognition can benefit from automated control by systematic manipulation of sensory cues and more efficient execution of training procedures. However, commercial solutions are often costly, restricted to specific platforms, and mainly focused on the automation of data acquisition, stimulus presentation, and reward delivery. Animal welfare considerations as well as experimental demands may require automating the access of an animal or animals to the experimental arena. Here, we provide and test a low‐cost, versatile Raspberry Pi‐based solution for such use cases. We provide four application scenarios of varying complexities, based on our research of spatial orientation and navigation in weakly electric fish, with step‐by‐step protocols for the control of gates in the experimental setups. This easy‐to‐implement, platform‐independent approach can be adapted to various experimental needs, including closed‐loop as well as field experiments. As such, it can contribute to the optimization and standardization of experiments in a variety of species, thereby enhancing the comparability of data. [ABSTRACT FROM AUTHOR]

Introduction: Sensorimotor synchronization (SMS) is the human ability to align body movement rhythms with external rhythmic stimuli. While the effects of rhythmic stimuli containing only temporal information on SMS have been extensively studied, less is known about how spatial information affects SMS performance. This study investigates the neural mechanisms underlying SMS with rhythmic stimuli that include both temporal and spatial information, providing insights into the influence of these factors across different sensory modalities. Methods: This study compared the effects temporal information and spatial information on SMS performance across different stimuli conditions. We simultaneously recorded the electroencephalogram (EEG), the electromyogram (EMG), and behavioral data as subjects performed synchronized tapping to rhythmic stimuli. The study analyzed SMS performance under conditions including auditory, visual, and auditory-visual motion stimuli (containing both temporal and spatial information), as well as auditory, visual, and auditory-visual non-motion stimuli (containing only temporal information). Specifically, the research examined behavioral data (i.e., mean asynchrony, absolute asynchrony, and variability), neural oscillations, cortico-muscular coherence (CMC), and brain connectivity. Results: The results demonstrated that SMS performance was superior with rhythmic stimuli containing both temporal and spatial information compared to stimuli with only temporal information. Moreover, sensory-motor neural entrainment was stronger during SMS with rhythmic stimuli containing spatial information within the same sensory modality. SMS with both types of rhythmic stimuli was found to be dynamically modulated by neural oscillations and cortical-muscular coupling in the beta band (13-30 Hz). Discussion: These findings provide deeper insights into the combined effects of temporal and spatial information, as well as sensory modality, on SMS performance. The study highlights the dynamic modulation of SMS by neural oscillations and CMC, particularly in the beta band, offering valuable contributions to understanding the neural basis of sensorimotor synchronization. [ABSTRACT FROM AUTHOR]

ABSTRACT Behavioural analysis has been attracting significant attention as a broad indicator of sub‐lethal toxicity and has secured a place as an important subdiscipline in ecotoxicology. Among the most notable characteristics of behavioural research, compared to other established approaches in sub‐lethal ecotoxicology (e.g. reproductive and developmental bioassays), are the wide range of study designs being used and the diversity of endpoints considered. At the same time, environmental hazard and risk assessment, which underpins regulatory decisions to protect the environment from potentially harmful chemicals, often recommends that ecotoxicological data be produced following accepted and validated test guidelines. These guidelines typically do not address behavioural changes, meaning that these, often sensitive, effects are not represented in hazard and risk assessments. Here, we propose a new tool, the EthoCRED evaluation method, for assessing the relevance and reliability of behavioural ecotoxicity data, which considers the unique requirements and challenges encountered in this field. This method and accompanying reporting recommendations are designed to serve as an extension of the “Criteria for Reporting and Evaluating Ecotoxicity Data (CRED)” project. As such, EthoCRED can both accommodate the wide array of experimental design approaches seen in behavioural ecotoxicology, and could be readily implemented into regulatory frameworks as deemed appropriate by policy makers of different jurisdictions to allow better integration of knowledge gained from behavioural testing into environmental protection. Furthermore, through our reporting recommendations, we aim to improve the reporting of behavioural studies in the peer‐reviewed literature, and thereby increase their usefulness to inform chemical regulation. [ABSTRACT FROM AUTHOR]

The safety management of laboratories is of utmost importance in the construction and management of university laboratories. Abnormal behaviors such as smoking, incorrect wearing of personal protective equipment (PPE) like lab coats, hats, masks, and gloves pose significant safety hazards. In this paper, in order to improve the level of laboratory safety management and effectively provide an alert in the case of unsafe behaviors, video analysis technology is employed to achieve abnormal behavior recognition and monitoring through steps such as human key point detection, posture estimation, and behavior recognition. Firstly, the human pose estimation algorithm YOLO is used for human detection, followed by the extraction of human key points after segmentation. Finally, spatiotemporal graph convolution is used for feature detection and classification of abnormal behaviors. The experimental results show that the accuracy of abnormal behavior detection and recognition based on human key points reaches over 85%, which is of great significance for safety management and behavior warning in university laboratories, and thus, improves the efficiency and level of laboratory safety management. [ABSTRACT FROM AUTHOR]

Introduction: Evidence from neuroscience and behavioral research has indicated that language meaning is grounded in our motor–perceptual experiences of the world. However, the question of whether motor embodiment occurs at the sentence level in L2 (second language) comprehension has been raised. Furthermore, existing studies on motor embodiment in L2 have primarily focused on the lexical and phrasal levels, often providing conflicting and indeterminate results. Therefore, to address this gap, the present eye-tracking study aimed to explore the embodied mental representations formed during the reading comprehension of L2 action sentences. Specifically, it sought to identify the types of motor representations formed during L2 action sentence comprehension and the extent to which these representations are motor embodied. Methods: A total of 56 advanced L2 learners participated in a Sentence–Picture Verification Task, during which their response times (RTs) and eye movements were recorded. Each sentence–picture pair depicted an action that either matched or mismatched the action implied by the sentence. Data analysis focused on areas of interest around the body effectors. Results and discussion: RTs in the mismatch condition indicated an impeding effect. Furthermore, fixations on the body effector executing an action were longer in the mismatch condition, especially in late eye-movement measures. [ABSTRACT FROM AUTHOR]

As a follow-up to a prior article that examined articles published in the Journal of Organizational Behavior Management from 1982 through 2012 to assess the use of Michael’s motivating operations (MO) concept in organizational behavior management research, we evaluated articles published therein from 2013 through 2022 that contained the term “motivating operation” or a related term. Forty articles used a relevant term. The terms were used in attempts to categorize and explain diverse behavioral effects of many kinds of variables. Many articles construed verbal stimuli, such as rules and goals, as MOs. Michael did not consider verbal stimuli in his seminal work on MOs, and we, like other authors, suggest broadening the concept to include such stimuli. [ABSTRACT FROM AUTHOR]

This article explores the influence of sadness in ethical decision-making and behavior. In three laboratory studies, we found that an incidental state of sadness reduced individuals' propensity to engage in morally questionable behavior, including both unethical and selfish acts (Studies 1 to 3). We found this effect to be mediated by the role of sadness in prompting people to pay more attention to the negative consequences of morally questionable acts and perceive those consequences as more problematic (Studies 2 and 3). This effect was consistent using different decision-making contexts and held when rewards to be gained from such behavior were relatively high. Several implications of these findings for business ethics and organizations are discussed. [ABSTRACT FROM AUTHOR]

The Wind–Vehicle–Bridge (WVB) coupling method is extensively applied in engineering practices for the dynamic analysis of railway bridges. However, research on the dynamic behaviors of the vehicle on curved bridges in wind conditions remains limited due to the complexities of interactions involved. In this study, the railway alignment and an actual curved bridge were chosen and modeled. The framework of the WVB system was detailed, and four excitation cases were investigated, considering mean wind, fluctuating wind and track irregularities. Three distinct scenarios, including vehicle on a curved bridge subjected to Inward Blowing Wind (IBW), Outward Blowing Wind (OBW) and vehicle on a straight bridge subjected to wind, were explored. The main conclusions are as follows: (1) wind direction significantly affects wheel unloading rate, lateral force, and derailment coefficient; (2) under mean wind condition, critical wind speed increases with the vehicle speed increasing under IBW, while it decreases with the vehicle speed increasing under OBW; (3) Combined wind and track irregularities reveal that wind direction significantly influences dynamic responses, and lower speeds are not necessarily equal to safer conditions for vehicles on curved bridges. [ABSTRACT FROM AUTHOR]

New legal regimes in various jurisdictions have increased the accountability of senior individuals in financial services to attempt to prevent wrongdoing. This article critically evaluates these efforts using insights from the behavioural sciences research on accountability, the regulatory theory on enforcement, and the criminological literature on compliance. This inquiry is pursued through an analysis of the Senior Managers and Certification Regime (SMCR) and the Banking Executive Accountability Regime (BEAR) in the UK and Australia respectively. These individual accountability regimes (IARs) are designed to make it easier to identify which senior individual is responsible for failing to address wrongdoing within their area of activity. Though often championed for ratcheting up accountability to tackle perceived impunity for wrongdoing, this article explores the limits of IARs. While acknowledging their strengths and merits, it troubles the expectations that such regimes are necessarily effective ways of priming certain anticipated behaviours and increasing cognitive load to slow decision-making processes. It considers the extent to which these regimes may be ineffective given what is known about the miserly nature of human cognition, the tendency to circumvent efforts to encourage ‘right’ decisions, and the inability of individual accountability regimes to address broader structural issues in financial markets. [ABSTRACT FROM AUTHOR]

The key of current research on behavior recognition algorithms based on deep learning lies in enhancing the accuracy and stability of key point extraction, in order to achieve more accurate action recognition of targets. However, many current algorithms tend to just add attention mechanisms that appear to perform better in the feature extraction stage of the target, without considering the impact of different attention mechanisms on different models and tasks. Therefore, this study proposes an algorithmic model for pose estimation based on various attention mechanisms, which further highlights the importance of selecting an appropriate attention mechanism by comparing the impact of different attention mechanisms on the model. In addition, considering the stability of key point extraction, the initialization of the model is fine tuned to select a more suitable initialization method that improves the performance by increasing the category of weights on network layer judgments. Compared with the performance of the benchmark network model, the model enhances all evaluation metrics on both multiscale and no multiscale CrowdPose datasets, where the average accuracy improvement in both cases is more than 1%. [ABSTRACT FROM AUTHOR]

Agonistic behavior is a common behavior among agonistic Chinese mitten crabs (Eriocheir sinensis). Such behavior often leads to limb loss or physical impairment, and significantly affects the survival, growth, and quality of the crabs, and even the yield and economic value for E. sinensis. Agonistic behavior often occurs in agonistic crabs, which is closely related to personality traits and interactive behavior of animals. E. sinensis has personality traits such as boldness, aggression, and exploration as evidenced by the partition-crossing experiment, mirror experiment, and shelter experiment. Agonistic crabs were identified as individuals with boldness, high aggression, and high exploration. The interactive behavior spectrum of E. sinensis was first obtained, consisting of 15 behaviors. This spectrum described and summarized all interactive behaviors of E. sinensis during fights. The interactive behavior characteristics of agonistic crabs were identified as darting, intimidating, grabbing, pushing, stretching, and visitation. These results lay a theoretical basis for in-depth behavioral research on E. sinensis in the future. The technique of identifying agonistic crabs by personality traits and interactive behaviors not only allows for the elimination of agonistic crabs from the aquaculture process and the reduction in negative impacts caused by aggressive crabs, but also allows for the breeding of non-agonistic crabs and the further reduction in the economic losses caused by fighting behaviors. [ABSTRACT FROM AUTHOR]

Women researchers in postdoc career stages still do not participate to the same extent in international academic mobility as men do. As a novel approach to better understand gender inequalities in international academic mobility, we investigate the structure of research collaborations and bring into focus the host researchers. Our central theoretical tool is the distinction between compositional and behavioral homophily. Using quantitative data from two German Humboldt Foundation programs sponsoring collaborations between international researchers and academic hosts in Germany, we ask (a) to what extent are gender-homophilous research collaborations caused by compositional or behavioral homophily; (b) what factors influence gender-based homophily; and (c) whether men or women tend more towards gender-homophilous collaborations. We detected behavioral homophily in research collaborations mainly when taking the potential pool of eligible women researchers as the reference group. The results on influencing factors are ambiguous and need further investigation. Furthermore, our results show that men tended more towards gender-homophilous collaborations than women. Our results suggest that gender inequalities in international academic mobility are linked to behavioral homophily and that exploring the role of host researchers is crucial to understanding—and overcoming—the under-representation of women in international academic mobility. [ABSTRACT FROM AUTHOR]

This document provides a list of references cited in research articles on topics such as workplace trust, employee attitudes, organizational resilience, employee wellness programs, and the impact of the COVID-19 pandemic on the workplace. The articles offer diverse perspectives and research methodologies, making them valuable resources for library patrons conducting research in these areas. It is important to note that this document does not provide a comprehensive summary of the articles, but rather serves as a reference list for further exploration. [Extracted from the article]

Background In the coming years, major governance changes in the form of policy directives and regulations will catalyse major top-down change with respect to animal health on European farms in an effort to combat the OneHealth threat of antimicrobial resistance. This top-down approach must be met with bottom-up strategies to ensure target actors (namely, farmers and vets) are supported and motivated to change their practices, thus, avoiding unintended consequences of forced change. Although much behavioural research has explored the factors influencing antimicrobial practices on farms, a gap exists translating these findings into evidence-based behaviour change interventions that can be put into practice. The current study aims to fill this gap. It provides insights into identifying, understanding, and changing the behaviours of farmers and veterinarians with respect to the responsible use of antimicrobials in farming. Results Through an inter-disciplinary and multi-actor approach, the study combines scientific knowledge from the behavioural sciences and animal health sciences, coupled with tacit knowledge from a co-design, participatory approach to recommend seven behaviour change interventions that can help to support good practices amongst farmers and vets, with respect to animal health, and reduce the use of antimicrobials on farms. The behaviour change interventions include message framing; OneHealth awareness campaign; specialised communications training; onfarm visual prompts and tools; social support strategies (for both farmers and vets); and antimicrobial use monitoring. The study details each intervention with respect to their evidence base and scientific concept, grounded in behavioural science, along with stakeholder feedback on design and delivery of the interventions. Conclusions These behaviour change interventions can be taken, adapted, and put into practice by the agri-food community to support good animal health practices and responsible antimicrobial use on farms. [ABSTRACT FROM AUTHOR]

Bots are automated software programs that pose an ongoing threat to psychological research by invading online research studies and their increasing sophistication over time. Despite this growing concern, research in this area has been limited to bot detection in existing data sets following an unexpected encounter with bots. The present three-condition, quasi-experimental study aimed to address this gap in the literature by examining the efficacy of three types of bot screening tools across three incentive conditions ($0, $1, and $5). Data were collected from 444 respondents via Twitter advertisements between July and September 2021. The efficacy of five task-based (i.e., anagrams, visual search), question-based (i.e., attention checks, ReCAPTCHA), and data-based (i.e., consistency, metadata) tools was examined with Bonferroni-adjusted univariate and multivariate logistic regression analyses. In general, study results suggest that bot screening tools function similarly for participants recruited across incentive conditions. Moreover, the present analyses revealed heterogeneity in the efficacy of bot screening tool subtypes. Notably, the present results suggest that the least effective bot screening tools were among the most commonly used tools in existing literature (e.g., ReCAPTCHA). In sum, the study findings revealed highly effective and highly ineffective bot screening tools. Study design and data integrity recommendations for researchers are provided. Public Significance Statement: In recent years, psychologists conducting online research have described escalating cyber threats to online research resulting from survey bots. This study sought to identify effective and cost-efficient ways to detect and prevent bots from enrolling in online research by using recruitment methods that were likely to recruit bots and systematically examining responses. The data collected in this study allowed us to generate a preliminary list of empirically supported recommendations for psychological researchers. [ABSTRACT FROM AUTHOR]

Understanding variation in social organization that lacks a strong phylogenetic signal represents a key focus of research in behavioural ecology. Accordingly, we established a framework that identifies whether a range of ecological and social factors are affecting the social maintenance of taxa across multiple categories of social variation (ranging from large to fine‐scale): 1) forms of sociality, 2) degree of sociality, 3) social plasticity and 4) hierarchy maintenance. Each category of variation can then be assessed in combination to provide an outlook for social maintenance in light of predictor factors. We modelled this framework by quantifying each category over time, space and disturbance regime using multiple species of coral‐dwelling gobies, genus Gobiodon. Gobies are an interesting model system as they vary in social structure, have within‐group cooperation, and form mutualisms with coral hosts, which are vulnerable to climatic disturbances. We found that gobies varied in forms of sociality – from being more solitary or pair‐forming in high disturbance regimes, versus group‐forming in moderate disturbance regimes at some locations. Only low or moderate degrees of sociality were observed in gobies, with location or disturbance regime affecting some species. The size of coral hosts influenced the social plasticity of gobies, which was affected by climatic disturbances. Gobies did not exhibit direct changes to hierarchy maintenance, as location and disturbance regime did not affect their size‐based hierarchies. Lastly, by combining the four categories of variation, we found a high loss of sociality in coral‐dwelling gobies due to environmental disturbances, which likely affects overall goby survival as group‐forming can improve survival and fitness. By using our structured framework, we identified which categories of social variation were influenced by ecological factors like location and disturbance. This framework therefore provides an excellent tool for predicting future responses of animal societies to environmental stressors. [ABSTRACT FROM AUTHOR]

While the literature is well represented in accounting for how aging influences segmental properties of speech, less is known about its influences on suprasegmental properties such as lexical tones. In addition, foreign language learning is increasingly endorsed as being a potential intervention to boost cognitive reserve and overall well-being in older adults. Empirical studies on young learners learning lexical tones are aplenty in comparison with older learners. Challenges in this domain for older learners might be different due to aging and other learner-internal factors. This review consolidates behavioural and neuroscientific research related to lexical tone, speech perception, factors characterising learner groups, and other variables that would influence lexical tone perception and learning in older adults. Factors commonly identified to influence tone learning in younger adult populations, such as musical experience, language background, and motivation in learning a new language, are discussed in relation to older learner groups and recommendations to boost lexical tone learning in older age are provided based on existing studies. [ABSTRACT FROM AUTHOR]

To investigate the flexural behavior of hybrid reinforced concrete (Hybrid‐RC) beams with Basalt fiber‐reinforced polymer (BFRP) bars and steel bars, this paper designed 14 Hybrid‐RC beams and studied the effect of different reinforcement forms on the flexural behavior of Hybrid‐RC beams. The research results indicated that when ρ≈2.28%$$ \rho \approx 2.28\% $$, an increase in Af/As$$ {A}_{\mathrm{f}}/{A}_{\mathrm{s}} $$ leads to a decrease in the cracking moment, ultimate moment, and ductility of Hybrid‐RC beams, the maximum crack width and deflection will increase. When ρ≈0.86%$$ \rho \approx 0.86\% $$, an increase in Af/As$$ {A}_{\mathrm{f}}/{A}_{\mathrm{s}} $$ will lead to a decrease in the cracking moment, deflection, and ductility of the Hybrid‐RC beams, while the maximum crack width and ultimate moment will increase. In addition, when ρ≤1.87%$$ \rho \le 1.87\% $$, the area of BFRP bars (the area of steel bars remains unchanged) should be changed to improve the flexural behavior of the Hybrid‐RC beams; When ρ>1.87%$$ \rho >1.87\% $$, the Hybrid‐RC beams should change the area of steel bars (the area of BFRP bars remains unchanged) to improve the flexural behavior of the beams. In addition, the ductility index prediction equation for Hybrid (BFRP and steel)‐RC beams was fitted based on the results of the theoretical model research. [ABSTRACT FROM AUTHOR]

Background: In recent years, with the rapid development of technology, research on behavioral addiction concepts such as digital gaming disorders and problematic internet use has increased. As anime-watching has become widespread worldwide, it is thought that this behavior may be one of the areas of problematic technology use, especially in adolescence. However, studies evaluating problematic anime-watching behaviors within the framework of behavioral addictions are quite limited in the literature. In this study, problematic anime-watching behaviors, comorbid psychiatric disorders, and possible psychosocial factors were evaluated in 86 anime watchers aged between 12 and 18 years. Problematic anime-watching behaviors were evaluated according to the diagnostic criteria of other defined disorders related to addictive behaviors in ICD-11. A semi-structured interview tool was used to assess psychiatric comorbidities, and the IGDS9-SF adapted form for anime-watching, the Self-Efficacy Scale for Children, KIDCOPE, and the Social Anxiety Scale for Adolescents were used to collect other data. Results: It was determined that 36.8% of the 86 adolescents in our study had problematic anime-watching behavior. Compared to other adolescents, the problematic anime-watching group had significantly lower self-efficacy scores and significantly higher social anxiety and avoidant coping scores. A significant relationship was found between social anxiety disorder and watching problematic anime. Conclusions: The present study showed that problematic watching of anime may be a variant of behavioral addiction. In conclusion, the relationship between problematic anime-watching behaviors and mental health warrants further examination. [ABSTRACT FROM AUTHOR]

This note is concerned with the benefits that can result from the use of the maximal reliability and optimal linear combination concepts in educational and psychological research. Within the widely used framework of unidimensional multi-component measuring instruments, it is demonstrated that the linear combination of their components that possesses the highest possible reliability can exhibit a level of consistency considerably exceeding that of their overall sum score that is nearly routinely employed in contemporary empirical research. This optimal linear combination can be particularly useful in circumstances where one or more scale components are associated with relatively large error variances, but their removal from the instrument can lead to a notable loss in validity due to construct underrepresentation. The discussion is illustrated with a numerical example. [ABSTRACT FROM AUTHOR]

The intellectually gifted have been found to have higher levels of many prosocial dispositions, but there is limited evidence of increased prosocial behavior. The present research used existing and original datasets to examine relations between intellectual giftedness and prosocial behavior and dispositions. In Study 1, those identified as intellectually gifted engaged in more political and helping behaviors than those not identified as intellectually gifted. In Study 2, gifted-identified undergraduate students reported more prosocial behavior (e.g., volunteering and giving) than nonidentified students; however, there were no clear differences in dispositions (e.g., personality and motivation) between gifted-identified and nonidentified students. Implications of these consistent linkages between intellectual giftedness and engaging in prosocial behavior for future research and practical applications are discussed. [ABSTRACT FROM AUTHOR]

When clinicians address dangerous behavior via remote telehealth consultation, it may be especially important to ensure remote implementers can apply behavioral interventions in a manner that keeps recipients and implementers safe while still achieving effective outcomes. We present the case of a 13-year-old autistic adolescent with limited communication skills, living in South India, whose dangerous behavior was escalating and becoming more pervasive during the pandemic quarantine, putting himself and his family at risk. In this study, we evaluated the effects of an enhanced choice model of skill-based treatment—informed by a practical functional assessment of dangerous behavior. We systematically replicated and extended procedures that have been shown to address dangerous behavior while avoiding difficult situations that place the individual and others at risk. The intervention yielded elimination of dangerous and associated non-dangerous behavior and socially valid acquisition of multiple alternative behaviors. We report multiple strategies to overcome barriers unique to remotely addressing dangerous behavior and discuss implications for the safe, telehealth application of behavior analysis in research and practice. [ABSTRACT FROM AUTHOR]

Online experiments are increasingly gaining traction in the behavioral sciences. Despite this, behavioral researchers have largely continued to use keyboards as the primary input devices for such online studies, overlooking the ubiquity of touchscreens in everyday use. This paper presents an open-source touchscreen extension for jsPsych, a JavaScript framework designed for conducting online experiments. We additionally evaluated the touchscreen extension assessing whether typical behavioral findings from two distinct perceptual decision-making tasks – the random-dot kinematogram and the Stroop task – can similarly be observed when administered via touchscreen devices compared to keyboard devices. Our findings indicate similar performance metrics for each paradigm between the touchscreen and keyboard versions of the experiments. Specifically, we observe similar psychometric curves in the random-dot kinematogram across the touchscreen and keyboard versions. Similarly, in the Stroop task, we detect significant task, congruency, and sequential congruency effects in both experiment versions. We conclude that our open-source touchscreen extension serves as a promising tool for data collection in online behavioral experiments on forced-choice tasks. [ABSTRACT FROM AUTHOR]

Investigating how infants first establish relationships between words is a necessary step towards understanding how an interconnected network of semantic relationships develops in the adult lexical-semantic system. Stimuli selection for these child studies is critical since words must be both familiar and highly imageable. However, there has been a reliance on adult word association norms to inform stimuli selection in English infant studies to date, as no resource currently exists for child-specific word associations. We present three experiments that explore the strength of word–word relationships in 3-year-olds. Experiment 1 collected children's word associations (WA) (N = 150; female = 84, L1 = British English) and compared them to adult associative norms (Moss & Older, 1996; Nelson et al., 2004 (Behavior Research Methods, Instruments, & Computers, 36(3), 402–407)). Experiment 2 replicated WAs from Experiment 1 in an online adaptation of the task (N = 24: 13 female, L1 = British English). Both experiments indicated a high proportion of child-specific WAs not represented in adult norms (Moss & Older, 1996; Nelson et al., 2004 (Behavior Research Methods, Instruments, & Computers, 36(3), 402–407)). Experiment 3 tested noun–noun WAs from these responses in an online semantic priming study (N = 40: 19 female, L1 = British English) and found that association type modulated priming (F(2.57, 100.1) = 13.13, p <. 0001, generalized η2 =.19). This research presents a resource of child-specific imageable noun–noun word pair stimuli suitable for testing young children in word recognition and semantic priming studies. [ABSTRACT FROM AUTHOR]

Online experiments have been transforming the field of behavioral research, enabling researchers to increase sample sizes, access diverse populations, lower the costs of data collection, and promote reproducibility. The field of developmental psychology increasingly exploits such online testing approaches. Since infants cannot give explicit behavioral responses, one key outcome measure is infants' gaze behavior. In the absence of automated eyetrackers in participants' homes, automatic gaze classification from webcam data would make it possible to avoid painstaking manual coding. However, the lack of a controlled experimental environment may lead to various noise factors impeding automatic face detection or gaze classification. We created an adult webcam dataset that systematically reproduced noise factors from infant webcam studies which might affect automated gaze coding accuracy. We varied participants' left-right offset, distance to the camera, facial rotation, and the direction of the lighting source. Running two state-of-the-art classification algorithms (iCatcher+ and OWLET) revealed that facial detection performance was particularly affected by the lighting source, while gaze coding accuracy was consistently affected by the distance to the camera and lighting source. Morphing participants' faces to be unidentifiable did not generally affect the results, suggesting facial anonymization could be used when making online video data publicly available, for purposes of further study and transparency. Our findings will guide improving study design for infant and adult participants during online experiments. Moreover, training algorithms using our dataset will allow researchers to improve robustness and allow developmental psychologists to leverage online testing more efficiently. [ABSTRACT FROM AUTHOR]

This manuscript presents a novel geofencing method in behavioral research. Geofencing, built upon geolocation technology, constitutes virtual fences around specific locations. Every time a participant crosses the virtual border around the geofenced area, an event can be triggered on a smartphone, e.g., the participant may be asked to complete a survey. The geofencing method can alleviate the problems of constant location tracking, such as recording sensitive geolocation information and battery drain. In scenarios where locations for geofencing are determined by participants (e.g., home, workplace), no location data need to be transferred to the researcher, so this method can ensure privacy and anonymity. Given the widespread use of smartphones and mobile Internet, geofencing has become a feasible tool in studying human behavior and cognition outside of the laboratory. The method can help advance theoretical and applied psychological science at a new frontier of context-aware research. At the same time, there is a lack of guidance on how and when geofencing can be applied in research. This manuscript aims to fill the gap and ease the adoption of the geofencing method. We describe the current challenges and implementations in geofencing and present three empirical studies in which we evaluated the geofencing method using the Samply application, a tool for mobile experience sampling research. The studies show that sensitivity and precision of geofencing were affected by the type of event, location radius, environment, operating system, and user behavior. Potential implications and recommendations for behavioral research are discussed. [ABSTRACT FROM AUTHOR]

Although performance information is widely promoted to improve the accountability of public service provision, behavioral research has revealed that motivated reasoning leads recipients to update their beliefs inaccurately. However, the reasoning processes of service users have been largely neglected. We develop a theory of public service users' motivated reasoning about performance information stemming from their identification with the organization providing their services. We address a significant challenge to studying motivated reasoning—that widely used existing research designs cannot rule out alternative cognitive explanations, especially Bayesian learning, such that existing findings could be driven by strong prior beliefs rather than biased processing of new information. We use a research design incorporating Bayesian learning as a benchmark to identify departures from accuracy motivated reasoning process. We assess the empirical implications of the theory using a preregistered information provision experiment among parents with children using public schools. To assess their identity-based motivated reasoning, we provide them with noisy, but true, performance information about their school. Overall, we find no evidence of directionally motivated reasoning. Instead, parents change their beliefs in response to performance feedback in a way that largely reflects conservative Bayesian learning. Performance reporting to service users is less vulnerable to motivational biases in this context than suggested by the general literature on motivated reasoning. Furthermore, exploratory findings show that performance information can correct erroneous beliefs among misinformed service users, suggesting that investment in reporting performance to service users is worthwhile to inform their beliefs and improve accountability. [ABSTRACT FROM AUTHOR]

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Based on an analysis of the extant literature, this paper summarizes the research progress on the mechanical properties and long-term behavior of corrugated steel web (CSW) box girder bridges. First, the research results of CSW box girder bridges in terms of the shear buckling performance (local shear buckling, overall shear buckling, and interaction buckling), bending performance, bending capacity, torsional capacity, and coefficient of internal force increase are summarized, along with the main factors affecting the mechanical performance of CSW box girder bridges. Second, based on research on the self-oscillation characteristics and dynamic response of CSW box girder bridges, the influence of structural parameters on the self-oscillation characteristics is analyzed. Finally, the long-term mechanical behavior of the CSW box girder bridges is analyzed in terms of fatigue, creep, and temperature effects. The existing research results demonstrate that there still exist deficiencies in the mechanical properties and long-term behavior of CSW box girder bridges, and this paper thus suggests a future research focus on CSW box girder bridges to provide a reference for further improving their basic theoretical system. [ABSTRACT FROM AUTHOR]

Ductility dip cracking (DDC) is a solid-state failure occurring during multi-pass solidification processes (e.g., welding, additive manufacturing) for FCC alloys that exhibit a distinct dip in their ductility at intermediate temperatures. While the phenomenon has been studied for over a century, the majority of current research focuses on a subset of DDC-susceptible FCC alloys (Ni–Cr–Fe). The review paper herein presents an analysis of published data to evaluate the current state of understanding regarding the materials mechanisms at work. Recent advances in test methods have permitted highly controlled approaches for testing and quantifying DDC, but the wide range of unique tests often provide conflicting results regarding the fundamental materials behaviors and underlying mechanisms. At present, three mechanisms have been proposed for DDC: grain boundary sliding, precipitate-induced strain, and impurity element segregation. While the majority of published studies support grain boundary sliding as the primary mechanism of DDC, an examination of the aggregate data available across multiple studies suggests combinatorial impact of simultaneous (and competing) mechanisms for DDC. Further, the long-held assumptions regarding the negative impact of key alloying elements become less convincing when comparing results across studies. There are considerable future opportunities for research on DDC behaviors in other alloy systems, and there are a lacunae of data when considering the effect of welding process parameters on DDC and the use of modeling and simulation approaches to understand the DDC behavior in the highly susceptible FCC alloy systems. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion The positive valence system (PVS) is increasingly recognised as an important target in facilitating recovery from anxiety and depression. Amplification of positivity (AMP), a cognitive and behavioural intervention, targets the PVS through repeated and intentional activities (e.g. savouring positive experiences, gratitude and acts of kindness). Initial data demonstrate that AMP engages positive valence targets (e.g. positive affect) and outcomes (e.g. social connectedness) in people seeking treatment for anxiety or depression; however, client perspectives on AMP are not well understood. This study aimed to qualitatively explore clients' experiences to better understand post‐treatment client changes and advance the development and effectiveness of AMP and other emerging positive valence‐focussed interventions.Transcripts were analysed from 11 participants who completed an optional qualitative interview after completing AMP treatment in a randomised controlled trial (NCT04945239).Two superordinate themes with several subthemes emerged. The first theme, Changes in Self, revealed common changes consistent with the core targets of AMP, as well as changes less explicitly targeted by AMP. The second theme, The Positivity Pivot, uncovered clients' perceptions on the emphasis of positive emotions in treatment. Overall, clients enjoyed and reaped benefits from amplifying positivity; some clients also reported wanting more time and space to discuss negative valence symptoms.People seeking treatment for anxiety or depression are receptive to amplifying positivity and experience the mental and social benefits of doing so. Positive valence‐centred treatments may therefore be valuable for some clients. Treatment protocols that integrate positive valence‐ and negative valence‐targeted approaches may be preferred by some clients. [ABSTRACT FROM AUTHOR]