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[Display omitted] • The physical and chemical properties of PS and PC were studied systematically. • The reactivity of PC combustion reaction was significantly affected by PS. • PC:PS = 4:1 has the lowest combustion activation energy. • The Kissinger Akahira Sunose model shows a good fitting effect. The co-combustion reactivity and kinetics of petroleum coke (PC) and paper sludge-derived hydrochar (PS) were investigated via thermogravimetric analysis. The physical and chemical structure features were also systematically tested. The results show that the combustion process of PS could be divided into three stages, while for PC only one stage could be clarified. Due to high volatile content, developed pore structure and low carbon-order degree, the combustion reactivity of PS was higher than that of PC. Although the ignition property of the blends could be significantly improved by addition of PS, it changed little for the burnout temperature and as a result the combustion intensity was deteriorated. For the samples with addition of PS from 20 % to 80 %, the comprehensive combustion index decreased from 3.69 × 10-15 to 2.12 × 10-15. The Kissinger AkahiraSunose model-free method was used in the co-combustion reaction of PC and PS, and good fitting results were obtained. For different samples with varying addition of PS, the activation energies were in the range of 107.51–198.44 kJ/mol, with the lowest value obtained at 20 % of PS, which was also the optimum proportion for co-combustion of PC and PS. [ABSTRACT FROM AUTHOR]

In behavior analysis, research on stimulus equivalence has been an area of high activity for more than 45 years. Murray Sidman's contribution was crucial in the development of this field, and, thus, it seems informative to highlight the experiments that were necessary in the development of the descriptive model of equivalence relations and behavior. The purpose of this paper is to provide an overview of the significant work that gave the historical context for Sidman and colleagues' conceptualization of stimulus equivalence as it was presented in 1982. This article emphasizes the 31 papers and chapters written by Sidman and colleagues that focus on research questions within stimulus control. The chapters and papers are organized according to their dimensions in behavior analysis and according to whether they can be categorized as instruction programs or experimental studies. The issues discussed regarding these papers and chapters include types of stimuli, matching, discriminations, and others. Collectively, this early work influenced methods and considerations about stimulus control issues that have been important to the development of stimulus equivalence. [ABSTRACT FROM AUTHOR]

Reproduction in cooperative animal groups is often dominated by one or a few individuals, with the remaining group members relegated to nonreproductive helping roles. This reproductive skew can evolve if helpers receive fitness benefits such as potential future inheritance of the breeding position, but the mechanisms by which inheritance is determined are not well resolved. Polistes paper wasps form highly reproductively skewed groups and inheritance of the breeding position is likely to play a key role in the maintenance of this social structure, making them excellent models for the processes by which simple societies are maintained. Reproductive succession is thought to be determined via an age-based convention in some Polistes species, but there is also evidence for contest-based succession systems in which the replacement queen uses physical aggression to overpower and thereby subordinate her nestmates. Here, we provide evidence that queen succession in colonies of the European paper wasp Polistes dominula is determined via convention rather than contest, with little disruption to the colony's social functioning. We use queen removal experiments and fine-scale behavioral analyses to confirm that age is a strong predictor of succession, and that behavioral responses to queen removal are restricted to the oldest individuals rather than being experienced equally across the group. We provide the most comprehensive and detailed experimental analysis on the dynamics of breeder succession in a cooperatively breeding invertebrate to date, thereby shedding light on the mechanisms by which animal societies are able to maintain cohesion in the face of within-group conflict. [ABSTRACT FROM AUTHOR]

The complexity of school management tasks requires specific training. Studies on leadership agree that such training should be based on reflective practice favored by coaching. This article presents the analysis of the behaviors and intervention strategies of coaches and their relation with reflective learning processes undertaken in discussion groups for the training of principals within the framework of a specific program. The results indicate that coaching requires rigorous training in relation to both leadership and social skills and abilities through which a relationship of trust can be built. Group synergies that encourage reflection on one's own leadership require syntheses and extensions to establish relationships between the facts and avoid valuations and advice, while promoting active listening, the capacity to manage time and formulate questions, and challenge but not disqualify comments that are key to the improvement and quality of the training process. Given the multiple demands for coaches' work to be effective, we observe the need for appropriate and rigorous training in expert knowledge through social skills and abilities that promote a relationship of trust with the participants. [ABSTRACT FROM AUTHOR]

The purpose of this study is to present an exhaustive analysis on research paper recommender systems which have become very popular and gained a lot of research attention. Though the major focus is on developing new recommendation algorithms, other research dimensions are left untouched. Renown recommendation classes include content-based approaches, collaborative filtering, link-based algorithms, co-occurrence based approaches, global relevance and hybrid methods. These approaches mainly differ in background knowledge and modes of user behavior analysis. For instance, content-based filtering uses paper descriptions which are mostly word-based features. Collaborative filtering makes predictions based on peers' interests. Link-based algorithms utilize academic associations that exist between different entities in academia. Co-occurrence based techniques incorporate event occurrences to locate related papers. Global relevance adopts a 'one-for-all' policy for recommending popular articles. Hybrid methods combine the above approaches to design efficient algorithms. We have reviewed articles implementing several versions of these classes, however minor customizations make it difficult to categorize the new methods to one of the base classes. We have defined the concept of 'background knowledge and operating principle' for proper classification and to make a clear distinction among the recommendation approaches. We have used a combination of systematic literature review, critical review, and conceptual review to conduct this survey which presents current advancements in the field and discusses popular recommendation approaches. This paper reveals the factors affecting users' behavior and introduces a taxonomy of knowledge acquisition sources. Moreover, various evaluation methods and important performance criteria are explored. Finally, this paper examines the research trends and reports major loopholes in current research to foster the development of efficacious recommender systems. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) driving simulators are very promising tools for driver assessment since they provide a controlled and adaptable setting for behavior analysis. At the same time, wearable sensor technology provides a well-suited and valuable approach to evaluating the behavior of drivers and their physiological or psychological state. This review paper investigates the potential of wearable sensors in VR driving simulators. Methods: A literature search was performed on four databases (Scopus, Web of Science, Science Direct, and IEEE Xplore) using appropriate search terms to retrieve scientific articles from a period of eleven years, from 2013 to 2023. Results: After removing duplicates and irrelevant papers, 44 studies were selected for analysis. Some important aspects were extracted and presented: the number of publications per year, countries of publication, the source of publications, study aims, characteristics of the participants, and types of wearable sensors. Moreover, an analysis and discussion of different aspects are provided. To improve car simulators that use virtual reality technologies and boost the effectiveness of particular driver training programs, data from the studies included in this systematic review and those scheduled for the upcoming years may be of interest. [ABSTRACT FROM AUTHOR]

The Repetitive Behaviours Questionnaire for Adults (RBQ-2A) measures two factors of restricted and repetitive behaviours (RRBs) associated with autism. However, the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) provides four criteria for RRBs: repetitive motor behaviours, insistence on sameness, restricted interests, and interest in sensory aspects of the environment (or atypical sensitivity). The current paper aimed to examine whether the RBQ-2A is a psychometrically sound measure of these four factors. Study 1 had university students (N = 368) complete the RBQ-2A and other related measures online and revealed that the RBQ-2A can assess the factors highlighted in the DSM-5 and that these four factors comprise a general RRB construct. Study 2 had individuals disclosing a diagnosis of autism (N = 283) complete the RBQ-2A and other related measures online and supported that this four-factor structure provided good psychometric properties. While the current paper provides findings for an online autistic population, further research is needed to generalize these findings to autistic individuals less likely to partake in online studies (e.g., those with intellectual or language disabilities). Overall, the results suggest that the RBQ-2A reliably and validly assesses RRBs. [ABSTRACT FROM AUTHOR]

In this paper, the compatibility, phase behavior, and crystallization properties of the binary blends of palm kernel stearin (PKS) and anhydrous milk fat (AMF) were investigated by analyzing the solid fat content (SFC), thermal properties, polymorphism, and microstructure, with the aim of providing theoretical guidance for the blending of oils. The results showed that the PKS content primarily determined the SFC trend of the binary blends. However, the binary blends demonstrated poor miscibility and eutectic behavior was predominantly observed in the system, particularly at higher temperatures. Only α and β′ forms appeared in this blended system. Simultaneously, the addition of PKS elevated the liquid phase transition temperature of the binary blends, considerably significantly increased their crystallization rate when the addition of PKS was more than 20% and increased the density and size of the fat crystals. Finally, the mixing design optimization method was used to get the most suitable ratio of the binary blends in the refrigerated cream system with PKS:AMF to be 0.914:0.086. The cream prepared with the above binary blends was indeed superior in overrun and firmness and had high stability. Practical Application: Some fats with special advantages are often limited in their wide application because of their poor crystallization ability. In this paper, the crystallization ability of fats is improved, and their application scenarios are increased through the combination of fats, so as to provide reference for the production of special fats for food. [ABSTRACT FROM AUTHOR]

This paper introduces a special issue of Housing, Theory and Society entitled "Behavioural biases in the housing market". First, we provide a brief overview of theoretical considerations and empirical research applying the behavioural economics approach to housing market studies. Second, we summarize the topics of the papers included in the special issue and, finally, point out directions for future analyses involving behavioural economics and the housing market. [ABSTRACT FROM AUTHOR]

Tail suspension test (TST) and forced swimming test (FST) are widely used in basic research and pharmaceutical screening of potential antidepressant treatments in rodents. In both tests, the measurement of immobility behavior is the main parameter to assess the rats' depressive-like behavior. [Extracted from the article]

With the increasing demand for road traffic safety assessment, global concerns about road safety have been rising. This is particularly evident with the widespread adoption of V2X (Vehicle-to-Everything) technology, where people are more intensively focused on how to leverage advanced technological means to effectively address challenges in traffic safety. Through the research of driving style recognition technology, accurate assessment of driving behavior and the provision of personalized safety prompts and warnings have become crucial for preventing traffic accidents. This paper proposes a risk field construction technique based on environmental data collected by in-vehicle sensors. This paper introduces a driving style recognition algorithm utilizing risk field visualization and mask learning technologies. The research results indicate that, compared to traditional classical models, the improved algorithm performs excellently in terms of accuracy, stability, and robustness, enhancing the accuracy of driving style recognition and enabling a more effective evaluation of road safety. [ABSTRACT FROM AUTHOR]

A significant proportion of malaria infections in humans exhibit no symptoms, but it is a reservoir for maintaining malaria transmission. A time periodic reaction-diffusion model for malaria spread is introduced in this paper, incorporating spatial heterogeneity, incubation periods, symptomatic and asymptomatic carriers. This paper introduces the concept of the basic reproduction number R 0 , which is defined as the spectral radius of the next generation operator, and we present some preliminary results by elementary analysis. The threshold dynamic behavior analysis shows that when R 0 < 1 , the disease is extinct, and when R 0 > 1 , the disease is persistent. We investigate the case of constant system parameters, focusing on the global asymptotic stability of the disease-free steady state when R 0 = 1 . In the numerical simulation section, we validate the theoretical results obtained, and then use elasticity analysis methods to explore the influence of parameters on the output solution. In addition, sensitivity analysis of the basic reproduction number under homogeneous conditions indicates direction of controlling malaria transmission. And several control measures are evaluated in the following steps. [ABSTRACT FROM AUTHOR]

In order to fully utilize the control degrees of freedom of a multi-three-phase-star smooth-pole permanent magnet synchronous motor (PMSM), this paper first develops a modeling approach using a new matrix transformation method. The proposed transformation produces decoupled and independent star windings, removing the inductive couplings and preserving the model and torque control's consistency as the number of phases increases. The model, together with a new vector control scheme, is superior for studying the effect of the winding phase angle shift on motor performance. Based on a numerical simulation, this paper focuses on the quality analysis of phase currents, non-sequential currents, and torque ripple with different phase angles for double- and triple-star PMSM drives. The control of a triple-star PMSM is validated, and the behavior analysis is investigated by OPAL-RT. [ABSTRACT FROM AUTHOR]

Since the emergence of big data, the popularity of deep learning models has increased and they are being implemented in a wide range of applications, including people detection and counting in congested environments. Detecting and counting people for human behavior analysis in retail stores is a challenging research problem due to the congested and crowded environment. This paper proposes a deep learning approach for detecting and counting people in the presence of occlusions and illuminance variation in a crowded retail environment, utilizing deep CNNs (DCNNs) for semantic segmentation of top-view depth visual data. Semantic segmentation has been implemented using (DCNNs) in recent years since it is a powerful approach. The objective of this paper is to design a novel architecture that consists of an encoder–decoder architecture. We were motivated to use transfer learning to solve the problem of insufficient training data. We used ResNet50 for the encoder, and we built the decoder part as a novel contribution. Our model was trained and evaluated on the TVHeads dataset and the people counting dataset (PCDS) that are available for research purposes. It consists of depth data of people captured from a top-view RGB-D sensor. The segmentation results indicate high accuracy and demonstrate that the proposed model is robust and accurate. [ABSTRACT FROM AUTHOR]

In this paper, we study the constrained minimization problem for an energy functional which is related to a Kirchhoff-type equation. For s = 1 , there many articles have analyzed the limit behavior of minimizers when η > 0 as b → 0 + or b > 0 as η → 0 + . When the equation involves a varying non-local term ∫ R 3 | ∇ u | 2 d x s , we give a detailed limit behavior analysis of constrained minimizers for any positive sequence { η k } with η k → 0 + . The present paper obtains an interesting result on this topic and enriches the conclusions of previous works. [ABSTRACT FROM AUTHOR]

Due to the digitization of data and the dynamic requirements of the users, cloud computing is one of the most used technologies in the present scenario. Cloud computing provides a platform to store, process, and share data remotely for heterogeneous users and provides services according to the requests generated by those users. However, its rapid growth has led to one of the major challenges in the environment; the security and privacy of the data. To address the security and privacy concerns, in this paper, our major contribution is a trusted computing framework namely Secure Framework using Behavior and Role Analysis (SFBRA) for cloud data security. The framework utilizes user log monitoring data, pattern recognition algorithms, and role-based access mechanisms to detect malicious and suspicious activities of different users. Our proposed framework provides two levels of security for cloud users. In Level-1, we calculate the trust value of the logged-in users by analyzing the existing log table and pattern of request access. In Level-2, we calculate the trust of the request (storage, processing, sharing) data packet using behavior analysis of the user and a role-based access mechanism and finally detect the malicious activities. The efficacy of our proposed framework is demonstrated through experimentation, where we compare our framework with existing research works. The results show 95% accuracy in potential attack detection and prevention,approximately 8 Mbps throughput, and 0.003% packet drop on average. [ABSTRACT FROM AUTHOR]

The zebrafish (Danio rerio) is becoming a critical component of new approach methods (NAMs) in chemical risk assessment. As a whole organism in vitro NAM, the zebrafish model offers significant advantages over individual cell-line testing, including toxicokinetic and toxicodynamic competencies. A transcriptomic approach not only allows for insight into mechanism of action for both apical endpoints and unobservable adverse outcomes, but also changes in gene expression induced by lower, environmentally relevant concentrations. In this study, we used a larval zebrafish model to assess the behavioral and transcriptomic alterations caused by subphenotypic concentrations of 2 chemicals with the same structural backbone, the endocrine-disrupting chemicals bisphenol A and tetrabromobisphenol A. Following assessment of behavioral toxicity, we used a transcriptomic approach to identify molecular pathways associated with previously described phenotypes. We also determined the transcriptomic point of departure for each chemical by modeling gene expression changes as continuous systems which allows for the identification of a single concentration at which toxic effects can be predicted. This can then be investigated with confirmatory cell-based testing in an integrated approach to testing and assessment to determine risk to human health and the environment with greater confidence. This paper demonstrates the impact of using a multi-faceted approach for evaluating the physiological and neurotoxic effects of exposure to structurally related chemicals. By comparing phenotypic effects with transcriptomic outcomes, we were able to differentiate, characterize, and rank the toxicities of related bisphenols, which demonstrates methodological advantages unique to the larval zebrafish NAM. [ABSTRACT FROM AUTHOR]

Introduction Method Results Discussion and Conclusions Police‐issued barring notices are currently used in Western Australia in response to alcohol‐related disorderly and anti‐social behaviour. This paper examines the type, severity and trajectory of the offending behaviours associated with served barring notices.WA Police Force de‐identified the data for 3815 individuals who had received one or more police‐imposed barring notice/s between 2011 and 2020. The offence category associated with each barring notice was examined to explore the overall breakdown and whether/how offending categories change for recipients of subsequent barring notices.For single and multiple barring notice recipients, the most common offence categories were fighting/physical violence and public order offences. Within a subset of the data, non‐anti‐social offences also spiked. Aggressive behaviours predominate for recipients in metropolitan areas, compared with public order offences in regional locations.For recipients of multiple barring notices, behaviours do not become more serious but neither do they moderate to any notable extent. The low number of repeat barring notices (5%) may suggest an overall beneficial effect on recipient behaviours but more analysis is needed to examine the potential confounding effects of factors, such as fly‐in/fly‐out workers, policing and locational differences. [ABSTRACT FROM AUTHOR]

Abstract\nIMPLICATIONS FOR REHABILITATIONRobotic technology-aided instruction and interventions have been designed to support both Applied Behavior Analysis (ABA) and Pivotal Response Treatment (PRT) interventions for children with ASD. However, to the best of our knowledge, this field has not been systematically reviewed. Thus, we aimed to systematically review the literature to determine whether ABA or PRT methods in a robotic therapeutic context yield better outcomes for individuals with ASD, specifically in terms of approaching and accepting robots. A comprehensive search of electronic databases including PubMed, EMBASE, and Google Scholar was conducted. Randomized control trials (RCT) and pre-post-test design investigations that assessed the impact of ABA vs. PRT approach via robot-mediated technology vs. human trainers on intervention outcomes of children with ASD were selected and included in this systematic review. Finally, 13 papers met the criteria for inclusion in the systematic review. Two independent reviewers extracted the associated data from each selected study according to the standardized data extraction form. Two reviewers also assessed the quality of each study independently using the Cochrane Back Review Scale and JBI tool for quasi-experimental studies. We categorized two general classifications of findings including ABA vs. PRT as well as robotic technology vs. human. In conclusion, the existing investigations on the effect of robotic assistive technology using ABA or PRT approach are promising particularly in therapeutic contexts with a more natural context and social flavor.Assistive robotic technology could teach social skills with both Applied Behavior Analysis (ABA) and Pivotal Response Treatment (PRT) approach to children with Autism Spectrum Disorders (ASD) with an acceptable efficiency and efficacy as human delivered therapies.The use of robotic technology as a means of delivering ABA or PRT interventions could offer a valuable alternative approach to human trainers in the treatment of children with ASD, potentially enhancing their acceptance and engagement with therapy.Assistive robotic technology could teach social skills with both Applied Behavior Analysis (ABA) and Pivotal Response Treatment (PRT) approach to children with Autism Spectrum Disorders (ASD) with an acceptable efficiency and efficacy as human delivered therapies.The use of robotic technology as a means of delivering ABA or PRT interventions could offer a valuable alternative approach to human trainers in the treatment of children with ASD, potentially enhancing their acceptance and engagement with therapy. [ABSTRACT FROM AUTHOR]

ABSTRACT Objective Methods Results Discussion Dialectical behavior therapy (DBT) is an evidence‐based treatment for disorders characterized by recurrent binge eating. Yet, access to specialized treatment like DBT remains limited. To increase the accessibility of DBT, we developed a DBT skills training app (Resilience: eDBT) for the management of eating disorder (ED) symptoms. This paper delineates the developmental process of Resilience and tests its usability.Descriptive information on the development and features of Resilience is provided, including its framework, content structure and delivery formats, functionality, data storage procedure, and privacy protocols. Usability was assessed via a mixed methods approach in 10 symptomatic individuals. Qualitative data were organized based on an existing framework, which included six themes: usability, visual design, user engagement, content, therapeutic persuasiveness, and therapeutic alliance.Resilience demonstrated good usability via a Systems Usability Scale score of 85.5, which exceeded the recommended cutoff of 68. Positive aspects of the app, according to interview data, were the ease of use and the visual design, while the addition of peer support was suggested as an opportunity for improvement.A novel DBT‐based app may serve as an acceptable, low‐intensity option or adjunct to traditional treatment for targeting ED symptoms that emerge in daily life. However, notable limitations include the small sample size and the single time point at which the usability assessment was conducted. [ABSTRACT FROM AUTHOR]

We study the autowave front propagation in a medium with discontinuous characteristics and the conditions for its stabilization to a stationary solution with a large gradient at the interface between media in the one-dimensional case. The asymptotic method of differential inequalities, based on constructing an asymptotic approximation of the solution, is the main method of study. We develop an algorithm for constructing such an approximation for the solution of the moving front form in a medium with discontinuous characteristics. The application of such an algorithm requires a detailed analysis of the behavior of the solution in neighborhoods of two singular points: the front localization point and the medium discontinuity point. As a result, we obtain a system of equations for the front propagation speed; this distinguishes this paper from the previously published ones. The developed algorithm can be used to describe autowave propagation in layered media. The results can also be extended to the multidimensional case. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the existence of solutions and analyze the large-time behavior for Gurtin–Maccamy population model involving conformable fractional derivatives. As a preliminary step, we construct a generic structure of the solution associated with our proposed model by utilizing some basic properties and tools of conformable fractional calculus. We establish the existence of a unique solution of the given model with the given initial conditions. At last, by using the upper and lower solutions for the characteristic equation, we define the upper and lower boundaries for the obtained solution and describe the large-time behavior of the total population. [ABSTRACT FROM AUTHOR]

Democratic theory asserts that the legitimacy of contemporary international and regional organisations rests on a degree of consensus expressed by various actors. The quest for diffuse support now extends beyond member states and explains the opening up of IOs/ROs to transnational civil society's participation. Despite both notions being familiar to IR scholars, a more precise understanding is needed concerning the relationship between each concept, particularly with regard to the inclusion/exclusion nexus and in the still neglected study of organisations in the global South. Using a practice perspective, the paper offers a contribution to that understanding by proposing a micro-level analysis of the behavioural practices of both ROs and TCS using MERCOSUR and the OAS as case studies. A nalysis of the opening up of these organisations, and the concurrent engagement of civil society reveals how inclusion is still both incomplete and unequal. Political liberalisation of ROs thus remains an unfulfilled mandate. [ABSTRACT FROM AUTHOR]

Aim: To examine the effects of the Pathways and Resources for Engagement and Participation (PREP) intervention during the COVID‐19 pandemic on (1) activity performance and satisfaction, and (2) motor, cognitive, and affective body functions. Method: An interrupted time‐series design with multiple baselines across 21 young people (13 females, eight males) aged 16 to 25 years (median = 21 years 5 months) with physical disabilities was employed. The young people engaged in an 8‐week self‐chosen leisure activity (e.g. football, piano, photography) at their home or community. The Canadian Occupational Performance Measure (COPM) assessed activity performance and satisfaction weekly. Mental health problems, including affective and cognitive outcomes, were assessed weekly using the Behavior Assessment System for Children, Third Edition. Motor functions (e.g. trunk control, reaching, strength) were assessed biweekly. Linear mixed‐effects models were used. Results: The intervention had large effects on activity performance (0.78) and satisfaction (0.88) with clinically significant change in COPM scores (2.6 [95% confidence interval {CI}: 2.0–3.2] and 3.2 points [95% CI: 2.4–3.9] respectively). Young people without mental health problems at baseline benefited more from the intervention (p = 0.028). Improvements in at least one domain of body function occurred in 10 young people especially for motor outcomes. Interpretation: Results demonstrate the effectiveness of PREP during adverse times and suggest benefits going beyond participation, involving outcomes at the body‐function level. What this paper adds: Environmental‐based interventions can improve participation even during adverse times such as the COVID‐19 pandemic.Significant improvement with large effect sizes occurred in both activity performance and satisfaction.Intervention was effective for all; those without mental health problems benefited more.Improvements in body‐function outcomes were partially observed, especially in motor‐related outcomes.Body functions may improve through participation even if not targeted by the intervention. [ABSTRACT FROM AUTHOR]

Literature on human trafficking suggests the vulnerability to commercial sexual exploitation of children (CSEC) and child sexual abuse (CSA) changes by the prevalence of certain risk factors (e.g., runaway), trafficker-used lures (e.g., isolation), and the environmental conditions present at the time of victimization (e.g., foster care). Often, youth in foster care are at high risk for CSEC and CSA victimization associated with runaway instances. This scoping review aims to identify prevention and intervention strategies for CSEC/CSA of youth who run away from foster care. PRISMA scoping review guidelines were followed to review the literature across two search parameters (CSEC; CSA). An electronic review was conducted between August 2022 and January 2023 across four databases: PubMed, SAGE Journals Online, ScienceDirect, and Web of Science. The CSEC and CSA search parameters comprised three domains (sexual exploitation, foster care, and runaway; sexual abuse, foster care, and runaway, respectively). Literature published between 2012 and 2022 was included regardless of the methodological approach. Literature not concerning youth who run from foster care was excluded. Database searches yielded 206 publications for CSEC and 351 for CSA, reduced to 185 and 212, respectively, after removing duplicates. Seventy-one articles were identified, of which, 64 articles (28 CSEC, 36 CSA) were categorized as prevention strategies and seven (five CSEC, two CSA) as interventions. The intersection and dual victimization of CSEC and CSA of youth who run away from foster care are discussed. This paper also discusses applied behavior analysis principles for developing function-based interventions. [ABSTRACT FROM AUTHOR]

Background: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait. Method: The approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset. Results: VARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications. Conclusion: The instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common. [ABSTRACT FROM AUTHOR]

Background: Canada, Australia, the World Health Organization and other countries have released 24-hour movement guidelines for the early years which integrate physical activity, sedentary behaviour, and sleep, focusing on supporting children to achieve a healthy 24-hour day. The guideline evidence synthesis, however, highlighted the dearth of high-quality evidence, particularly from large-scale studies. The Sleep and Activity Database for the Early Years (SADEY) project aims to assemble a large, pooled database of 24-hour movement behaviours and health indicators in young children (birth to 5.99 years), to advance knowledge in these areas. This paper describes the SADEY design and methods. Methods: Data sets were identified with > 100 children and device-measured (hip-worn ActiGraph accelerometers) physical activity and sedentary behaviour, parent-reported or device-measured sleep, and at least one health outcome: physical (BMI, waist circumference, blood pressure), social-emotional (Strength and Difficulties Questionnaire), cognitive (Early Years Toolbox), or motor development (Test of Gross Motor Development 2). Led by the University of Wollongong co-ordinating centre, the SADEY project collates the datasets to create a pooled database. Findings: To date, 13 studies from 7 countries have been included in the database. Ethics clearance and data sharing agreements have been secured for all studies and the SADEY 1.0 database is being assembled including ~ 8,000 participants. Discussion: SADEY will be used to address questions of global importance to public health policy and practice, for example – Is the mix of movement behaviours across the 24-hour day associated with healthy development?, What is the optimal mix of these behaviours?, and; What factors can be targeted to support young children in achieving the optimal mix of 24-hour movement behaviours? Additionally, SADEY seeks to develop and disseminate protocols, develop capacity on the device-based measurement of movement behaviours, and seeks partnerships with stakeholders that promote knowledge translation on movement behaviours to support healthy development among young children. [ABSTRACT FROM AUTHOR]

Independent component analysis (ICA), as a statistical and computational approach, has been successfully applied to digital signal processing. Performance analysis for the ICA approach is perceived as a challenging task to work on. This contribution concerns the complex-valued FastICA algorithm in the range of ICA over the complex number domain. The focus is on the robust and equivariant behavior analysis of the complex-valued FastICA estimator. Although the complex-valued FastICA algorithm as well as its derivatives have been widely used methods for approaching the complex blind signal separation problem, rigorous mathematical treatments of the robust measurement and equivariance for the complex-valued FastICA estimator are still missing. This paper strictly analyzes the robustness against outliers and separation performance depending on the global system. We begin with defining the influence function (IF) of complex-valued FastICA functional and followed by deriving its closed-form expression. Then, we prove that the complex-valued FastICA algorithm based on the optimizing cost function is linear-equivariant, depending only on the source signals. [ABSTRACT FROM AUTHOR]

Abstracts. Forty-two medication adherence concepts were reported and grouped into 10 domains. Eight forms of medication adherence were reported during interviews, along with 27 drivers of non-adherence, all of which were incorporated into a conceptual model. Participants reported skipping medication doses (n=36/57; 63.2%) or taking medication later in the day than prescribed (n=29/57; 50.9%). Common drivers of non-adherence included forgetfulness (n=35/57; 61.4%), being out of the usual routine (n=31/57; 54.4%) and being busy (n=22/57; 38.6%). US participants were more likely to report non-adherence due to low perceived efficacy (n=6/21, 28.6%) and cost (n=5/21, 23.8%) than German (n=1/18, 5.6%; n=0/18, 0.0%) or Spanish (n=2/18, 11.1%; n=1/18, 5.6%) participants. Conclusion: Findings highlight the diverse forms and drivers of medication non-adherence, informing the development of a comprehensive conceptual model of medication adherence. The conceptual model builds on and advances previous models of medication adherence and can be used by healthcare professionals to understand and interpret barriers to medication adherence and how best to support patients in taking their medication as intended. Plain Language Summary: Medication adherence is the extent to which a patient takes their medication as prescribed. This paper describes a literature review and concept elicitation interviews to identify forms and drivers of medication adherence across a diverse sample of participants. Forms of non-adherence identified included: deviating from the prescription, skipping a dose, taking a different amount, and taking medication at a different time. Behaviours and drivers can vary by condition, treatment modality, and dosing schedule.This research highlights the variation in the prevalence of medication non-adherence, and the different forms and drivers of non-adherence, based on individuals' demographic and clinical characteristics. The conceptual model developed advances previous models of medication adherence and may support healthcare professionals in the management of patients and how they can be supported to take medication as intended. The research ultimately informed the development of the Adelphi Adherence Questionnaire (ADAQ©), a novel generic patient-reported outcome measure. [ABSTRACT FROM AUTHOR]

Ensuring the sufficient residual resistance of glass structures after the failure of one glass ply to the failure of all the glass plies is an integral part of the design of glass structures. This paper presents an experimental study of bolted connections in laminated glass during three stages of a glass specimen: an intact glass specimen, a specimen with one ply of glass broken, and a specimen with both plies of glass broken. The effect of the type of glass was observed. The experiment proved that laminated glass made from thermally-toughened glass with bolted connections in its unfractured state has significantly higher resistance than laminated glass made from annealed glass. In a state of both plies of glass broken, the specimens made from annealed glass showed a higher residual resistance than specimens made from thermally toughened glass. The performance at this stage was also influenced by the temperature and loading speed. The expected strength of the glass was calculated on the basis of numerical models. [ABSTRACT FROM AUTHOR]

Bonica's (Am J Polit Sci 58(2):367–386, 2014) campaign finance-based ideology scores, or CFscores, create an ideological common space that allows researchers to compare a wide variety of actors. Because relatively few citizens donate to candidates, however, the public is not well represented in this common space. This paper addresses that gap. It uses random forest machine learning on data from the 2012 Cooperative Congressional Election Study to impute CFscores for respondents who did not donate to candidates, based on how their policy views compared to those who did. These new scores are robust to differences in issue importance between donors and non-donors, and they outperform other ideological measures in predicting vote choice. The scores are then applied to a substantive exercise. Past research shows that extreme candidates for governor are penalized more by voters than those in lower-profile races. The implied mechanism—that vote choice for governor is more ideologically-driven—can be directly tested with imputed CFscores, since they uniquely allow comparisons between voters and candidates across races. An analysis of voting behavior in 2012 confounds expectations. Ideology appears to factor no more into vote choice for governor than for US House. These novel findings underscore the value of extending CFscores to non-donating survey respondents, and while current efforts are limited by data availability, this study offers encouragement and a roadmap to that end. [ABSTRACT FROM AUTHOR]

This paper presents a solution verification and validation study for an overset mesh based numerical wave tank in OPENFOAM, which considers the coupling between a free-surface hydrodynamic flow model, a rigid body motion model, and an overset mesh. The coupling between the rigid body motion solver and the free-surface flow solver was achieved in a segregated manner. Free decay of roll motion of a barge was modeled using the numerical wave tank, and the damping coefficient was selected as the target quantity for solution verification. The least-square based solution verification procedure was adopted, where one of the four types of error estimators was fit to the data in the least-square sense. Both structured and unstructured mesh were tested, and their effects on the convergence order, numerical uncertainty, and error were carefully investigated. From the numerical tests, it is found that the numerical wave tank exhibits a very good convergence property for the floating body problems with structured mesh, i.e., nearly second order in space and first order in time. However, when switching the body-fitted mesh to unstructured mesh, the grid convergence is reduced to first order. Unstructured mesh does not significantly affect the convergence order in time domain, but results in a larger uncertainty due to data scattering. [ABSTRACT FROM AUTHOR]

This paper plans to propose a general numerical model for investigating the free and forced vibration behaviors of the multi-stepped functionally graded porous graphene platelet-reinforced composite (FGP-GPLRC) curved beam with various boundary conditions based on the first-order shear deformation Timoshenko beam theory by employing Rayleigh–Ritz method in conjunction with Jacobi polynomials. Different porosity and GPL distribution types are considered. The general boundary conditions of the multi-stepped FGP-GPLRC curved beam and connecting conditions of the FGP-GPLRC curved beam elements are simulated by employing boundary springs and connecting springs, respectively. The convergence and validation of the proposed numerical model are demonstrated by comparing the proposed results with the corresponding results which come from open literature and finite element software ABAQUS. The free and forced vibration behavior analysis of multi-stepped FGP-GPLRC curved beam is carried out by investigating the influences of material property and geometric parameters on the natural frequency and displacement response in the frequency and time domains of multi-stepped FGP-GPLRC curved beam structure. The investigation results can offer the technique guidance for the design and manufacture of the multi-stepped FGP-GPLRC curved beam. [ABSTRACT FROM AUTHOR]

Nationality is considered a highly relevant determinant of tourism expenditure. In this paper, we use survey data to estimate the main determinants of daily tourism expenditure in 2019 for five nationalities of a major coastal destination, the Canary Islands. A total of 38 regressors, based on literature, are used with the help of quantile regression analysis to understand the behaviour patterns of different expenditure segments. To obtain segmented information on the determinants of expenditure, independent quantile regression models for each nationality are estimated and compared. Results show that there are similarities but also some remarkable differences between nationalities regarding income, age, travel group, educational level, or content of the package that can be used in destination management and marketing. [ABSTRACT FROM AUTHOR]

Chicken behavior recognition is crucial for a number of reasons, including promoting animal welfare, ensuring the early detection of health issues, optimizing farm management practices, and contributing to more sustainable and ethical poultry farming. In this paper, we introduce a technique for recognizing chicken behavior on edge computing devices based on video sensing mosaicing. Our method combines video sensing mosaicing with deep learning to accurately identify specific chicken behaviors from videos. It attains remarkable accuracy, achieving 79.61% with MobileNetV2 for chickens demonstrating three types of behavior. These findings underscore the efficacy and promise of our approach in chicken behavior recognition on edge computing devices, making it adaptable for diverse applications. The ongoing exploration and identification of various behavioral patterns will contribute to a more comprehensive understanding of chicken behavior, enhancing the scope and accuracy of behavior analysis within diverse contexts. [ABSTRACT FROM AUTHOR]

• A new method is proposed for the behavioral analysis of bars charts images from documents. • The method consists of supervised learning combined with formal analysis. • Extracted information is mapped into Stochastic Petri-net to deduce the monotonic behavior of the chart data. • User-based and mathematical evaluation against state of-the-art tools proves the efficiency of our approach. The accurate understanding of documents depends on the effective processing of its individual modalities such as text, diagrams, tables, charts, and etc. While many research papers focus on extracting the illustrated values in bars charts, little work has been conduced regarding the analysis of this data to deduce behavioral information. In this paper, we present a methodology for the recognition and behavioral analysis of bar chart images. In particular, a Convolutional Neural Network model is trained for the initial chart classification and keypoints are extracted for the translation of identified columns into curves. By analyzing the curves associations and interactions with each other, and converting them into Stochastic Petri-nets, the methodology can perform behavioral analysis and deduce their functional characteristics. Empirical evaluation against state-of-the-art chart analysis tools shows high user-approval scores for the proposed method regarding the depth of extracted information and quality of responses. [ABSTRACT FROM AUTHOR]

The primary objective of this paper is to investigate the performance of C-D (converging-diverging) nozzles with slanted perforated tabs through numerical simulations. Specifically, the paper focuses on the simulation of supersonic jets controlled by these slanted perforated tabs to evaluate their effectiveness in enhancing mixing efficiency. The simulation methodology involves developing a computational model of the jet and the tabs, utilizing mathematical equations and numerical techniques to solve for fluid flow, pressure, and other relevant variables. This computational approach enables the prediction of jet behaviour and the assessment of how different types of control tabs impact the system. This helps for the design of improved jet engines and other fluid systems that require effective mixing capabilities. The introduction of tabs introduces changes to the potential core and velocity profiles, primarily due to enhanced mixing effects facilitated by the tabs. In a supersonic flow, the potential core is typically shorter than in subsonic flows due to the compressibility effects of the fluid. Even though in literature many studies have been done on sonic jets with perforated tabs and some on supersonic jets with perforated tabs, the uniqueness in this paper is on the blockage area. Blockage area has been kept at a minimum of around one percent for solid tab and for 30° perforated tab it's as low as 0.5%. By incorporating perforated tabs into a supersonic jet, the size of the potential core can be further reduced through enhanced mixing between the jet and the surrounding fluid. Thus, with minimal thrust loss this paper explores maximum benefit of potential core reduction and thereby better mixing efficiency and lesser noise production. Solid tab has better potential core reduction but with lesser blockage area, 30º perforated tab is better in ratio of potential core reduction to blockage area. [ABSTRACT FROM AUTHOR]

In this paper, we explore the properties of the generalized Lambert transform, the L-transform, the generalized Stieltjes transform, and the Stieltjes–Poisson transform within the framework of Lebesgue spaces. We establish Parseval-type relations for each transform, providing a comprehensive analysis of their behaviour and mathematical characteristics. [ABSTRACT FROM AUTHOR]

In the recycling of low-value metallic elements, heap leaching is commonly employed. The particle size distribution is a crucial parameter in heap leaching implementation, and the percolation behavior of a heap has always been a focal point in heap leaching technology. This paper utilizes a novel form of ultraviolet fluorescence image acquisition and fluorescence image analysis to investigate the percolation process with different fractal dimension particle size distributions, where the maximum particle diameter is 10 mm. The ore used was low-grade copper ore. The results indicate that the new fluorescence image analysis method can reveal different percolation regions during the heap leaching process, aiding in a better understanding of heap leaching behavior. The combined study found that under irrigation conditions of 10 mL/min, seepage was more uniform under the heap structure formed by a particle gradation with a fractal dimension of 2.2. [ABSTRACT FROM AUTHOR]

Persuasive gamified systems are effective tools for motivating behaviour change using various persuasive strategies. In line with the reinforcement theory, some persuasive gamified systems employ reward and punishment in their design to achieve the intended behavioural outcome. Research has argued both in favour and against using these strategies in behaviour change applications due to mixed results with respect to their effectiveness. However, there is a lack knowledge about how interventions using these strategies could motivate or demotivate behaviours. Therefore, this paper explores the mechanism through which Reward and Punishment motivate or demotivate behaviours with respect to their strengths and weaknesses. The results of large-scale exploratory studies (N = 1768) uncover important strengths and weaknesses that could facilitate or hinder the effectiveness of Reward and Punishment at motivating behaviour change. These include their ability to engage users and make behaviour fun, reinforce commitments to goals, and reveal some consequences of bad behaviour. We also compared the perceived effectiveness of reward and punishment quantitatively. [ABSTRACT FROM AUTHOR]

Grain crushing underpins key mechanical behaviours of granular materials. A variety of factors, including grading, particle shapes and loading conditions, have been recognised to affect the crushability of grains and the overall behaviour of a granular material. Among them, the role of intermediate principal stress in a general stress condition on the shear behaviour of crushable granular sand remains less understood, owing to the scarcity of experimental data and analytical tools available. In this paper, a multi-scale computational approach is employed to investigate the shear behaviour of crushable granular sand under general stress conditions with varying intermediate principal stresses and confining pressures. The computational approach features multi-scale coupling between non-smooth contact dynamics and peridynamics, and offers a rigorous way to consider the intertwined evolution of particle size and shape during the process of grain crushing. The numerical study helps to quantify comprehensively and analyse the grain crushing-induced changes of macro- and micro-scale material behaviours including strength, deformability, particle size and shape evolution, particle-scale forces and contact conditions, and the development of anisotropy. The competition between a void-filling mechanism due to grain size change and enhanced friction and interlocking due to grain shape change in dictating the deformation of crushable sand is further discussed. The findings offer insights into the complex behaviours of crushable granular materials under general stress conditions and facilitate future development of physics-based constitutive theories on crushable sand. [ABSTRACT FROM AUTHOR]