Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures

The paper presents the formalism of an intelligent decision-making system based on multi-agent neurocognitive architectures, which has an architectural similarity to the human brain. An invariant of the organizational and functional structure of the intellectual decision-making process based on the multi-agent neurocognitive architecture is developed. An algorithm for teaching intelligent decision-making systems based on the self-organization of the invariant of multi-agent neurocognitive architectures is presented. Using this algorithm, an intelligent agent was trained and the architecture of the learning process was built on the basis of an invariant of neurocognitive architecture. Further research is related to training an intelligent agent in more complex behavior and expanding the capabilities of an intelligent decision-making system based on multi-agent neurocognitive architectures.     

Citizen Advocacy Observed: Tool or Tokenism?

Citizen advocacy, where a volunteer works in partnership with a vulnerable person, compliments self- and legal advocacy. In the context of mental health services, citizen advocacy is a tool for enabling and empowering people who use these services, and is founded on the recognition that mental health service users are frequently socially oppressed and disadvantaged. This article describes the development of a Citizen Advocacy service for people with mental health difficulties, and also the problems they brought to this service. The problems encountered in sustaining the service are noted and lessons are drawn for the future.     

Creation and humanity: Veli-Matti Kärkäinen's answer to the ultimate question

This article focuses on the third volume of Vel-Matti Kärkkäinen's systematic theology, titled Creation and Humanity. After a brief overview of the volume the article offers some clarification on the tenth chapter, especially on its interaction with paleontology. After that, two constructive observations follow. The first is related to Kärkkäinen's notion of the embeddedness of human nature, and the second is to further employ systems thinking in his constructive work on creation and human evolution.     

Exploring Processes in Day-to-Day Parent–Adolescent Conflict and Angry Mood: Evidence for Circular Causality

Parent–adolescent conflict has been studied both as a precursor of long-term macrolevel developmental risks and as an outcome of microlevel, moment-to-moment interaction patterns. However, the family-level processes underlying the maintenance or regulation of conflict in daily life are largely overlooked. A meso-level understanding of parent–adolescent conflict offers important practical insights that have direct implications for interventions. The present study explores day-to-day reciprocal processes and carryover in parents’ and adolescents’ experiences of anger and conflict. Daily diary data provided by parent–adolescent dyads (N = 151) from two-caregiver households (adolescents: 61.59% female, mean age = 14.60 years) over 21 days were examined using a multivariate Poisson multilevel model to evaluate the circular causality principle in parents’ and adolescents’ daily conflict and anger. Findings offer empirical support for the theory, suggesting that parents’ and adolescents’ anger and conflict exist together in a feedback loop wherein conflict is both a consequence of past anger and also an antecedent of future anger, both within and across persons. Increased understanding of the daily interaction patterns and maintenance of parent–adolescent conflict can guide more informed, targeted, and well-timed interventions intended to ameliorate the consequences of problematic parent–adolescent conflict sequences.     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Human factors evaluation of an in-vehicle active traffic and demand management (ATDM) system

This research study focused on the evaluation of an emulated in-vehicle Active Traffic and Demand Management (ATDM) system on Interstate 66 in Northern Virginia. Traditional ATDM systems rely on infrastructure-mounted variable message signs (VMS) to provide information (speed limits, lane availability, etc.) to the traveling public. By providing information about dynamic roadway conditions on an in-vehicle device, the ATDM may improve driving safety and performance by allowing drivers to remain consistently aware of forthcoming traffic conditions and roadway requirements; even when external signage is inaccessible. This study represents an initial investigation of an emulated in-vehicle ATDM to provide developers with design guidance and ensure that unintended consequences, such as distraction, do not undermine the potential benefits.Twenty younger and 20 older participants, accompanied by a member of the research team, experienced the following ATDM features on an in-vehicle device (IVD) mounted to the dashboard: (1) dynamic speed limits, (2) dynamic lane use/shoulder control, (3) High Occupancy Vehicle (HOV) restrictions, and (4) roadway information from variable message signs. The IVD was equipped with auditory and visual alerts notifying the driver when relevant visual information was updated. Research questions addressed distraction and driver behavior associated with use of the system. Qualitative and quantitative participant data was acquired from the instrumented vehicle, various questionnaires, and researcher observation.Several key findings were uncovered: (1) The IVD, as tested, did not warrant classification as a source of distraction according to the NHTSA guidelines; v2) There was a significant difference in eye-glance durations to the IVD when comparing the VMS alerts to both the speed limit and lane management alerts; and (3) The speed limit alert motivated participants to alter their speed (per survey results and participant speed data).     

A focus group study on the potential of autonomous vehicles as a viable transportation option: Perspectives from people with disabilities and public transit agencies

Autonomous vehicle (AV) technology is becoming one of the most promising alternatives to improve mobility for people with disabilities. Nevertheless, how people with disabilities perceive AV as transportation services has not been explored. Also, limited information exists about how public transit agencies comprehend and perceive autonomous vehicle transportation (AVT) services. This study discusses mobility issues for people with disabilities and explores the potential of AVT to serve that population, particularly those with visual impairments or physical disabilities. Researchers conducted six focus groups comprising people with disabilities (N = 23) and public transit service experts (N = 10) in Austin, Texas and Houston, Texas. Each session was audio-recorded and analyzed using conventional content analysis. This study identified people with disabilities’ mobility issues related to: (1) current transit services (including fixed-route and paratransit services) and (2) the quality of neighborhood built environments. Both people with disabilities and transit experts expected that AVT could mitigate current mobility issues, especially in improved built environments. However, participants with disabilities also expressed concerns and anxieties regarding AVT. Transit experts agreed that more targeted strategies would be needed to overcome possible barriers to AVT for people with disabilities. This study provides insights on shaping AVT strategies and policies relevant to improving mobility for people with disabilities.     

Barriers and facilitators affecting the sustainability of dialectical behaviour therapy programmes: A qualitative study of clinician perspectives

Dialectical behaviour therapy (DBT) is a psychological treatment developed for individuals experiencing chronic suicidality and high‐risk behaviours. Despite the substantial evidence supporting the effectiveness of DBT, many programmes have problems with its sustainability. The goals of the current qualitative study were to identify factors that impact the sustainability of DBT programmes within a publicly funded mental health system and identify factors that are particularly relevant for youth DBT programmes. Interviews with trained adult and youth DBT clinicians (N = 31) were conducted to explore their experiences providing DBT. Three major themes that emerged as barriers to the sustainability of DBT programmes included the following: systemic challenges, conflicts within the consultation teams and clinician burnout. Factors influencing the success of DBT programmes included the following: systemic support, clinician commitment and “buy in”, and team cohesion. Factors specific to providing DBT with youth (i.e. level of commitment, simplifying the language, and parental investment) and recommendations for sustainability for adults and youth programmes were also identified. Findings of this study provide valuable information on factors impacting DBT programmes within the unique context of a Canadian mental health service system, where community‐based services are publicly funded. These findings have clear clinical utility and can be used to generate solutions to clinicians' perceived barriers and to foster perceived facilitators within similar contexts.     

人口统计学特征对公共服务动机有什么影响?来自元分析的证据

采用元分析方法探讨人口统计学特征与公共服务动机之间的关系。经筛选, 共纳入138篇492个独立样本(N = 1078442)。结果发现, 性别、年龄、教育程度、组织任期、工作任期、职位等级和收入与公共服务动机之间均呈显著的正相关关系, 且与公共服务动机不同维度之间的关系均存在差异, 婚姻状况与公共服务动机间不存在显著的相关关系。此外, 公共服务动机测量工具、测量时间点和文化背景对部分人口统计学特征与公共服务动机之间的关系有调节作用。研究结果为人口统计学特征如何影响公共服务动机提供了较为精确的估计, 对于发展公共服务动机理论, 激励员工工作积极性, 提高公共部门服务水平都有重要意义。