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The purpose of this paper is to determine the efficacy of the Peer Education Project (PEP), a school-based, peer-led intervention designed to support secondary school students to develop the skills and knowledge they need to safeguard their mental health and that of their peers.

Six schools from across England and the Channel Islands took part in an evaluation of the PEP across the 2016/2017 academic year. In total, 45 trained peer educators from the sixth form and 455 Year 7 students completed pre- and post-questionnaires assessing their emotional and behavioural difficulties, perceived school climate, and knowledge, skills and confidence related to mental health.

Results indicate that participation in the PEP is associated with significant improvement in key skills among both peer educators and student trainees, and in understanding of key terms and readiness to support others among trainees. Most students would recommend participation in the programme to other students.

While peer education has been found to be effective in some areas of health promotion, research on the effectiveness of peer-led mental health education programmes in schools is limited. This study contributes evidence around the efficacy of a new peer education programme that can be implemented in secondary schools.

The wider research literature indicates that health professionals’ ability to identify possible child maltreatment varies, and that this can lead to under-reporting of possible maltreatment to local authority (LA) statutory child protection agencies. The purpose of this paper is to understand how acute trust paediatric and LA services work together in suspected cases of child maltreatment, and what is viewed locally as good practice.

A mixed-method approach, consisting of an online survey, qualitative case studies and good practice examples, was used to describe key features of current practice in joint working between acute trusts and LA services, and to generate insights that could help improve practice.

Holistic assessment and information gathering, supported by training and expert input, were identified as being critical to a comprehensive approach to identifying maltreatment. Both in-hospital and community-based social work arrangements can be effective bases for joint working in respect of child maltreatment. Effective joint working relies on shared vision and values, and investment in, and commitment to, collaborative working.

This study covered arrangements in emergency departments (EDs) and maternity departments only, so future research could usefully look more broadly within acute care settings. Study respondents were also limited to safeguarding leads so, in future, there would be real value in exploring the experiences, practices and views of frontline practitioners.

The study includes practical implications for hospital and social work teams working to safeguard children.

The study highlights the characteristics of effective liaison between acute trust maternity and EDS and social work teams.

This paper aims to investigate a multi-objective electric vehicle’s (EV’s) synergetic scheduling problem in the automotive industry, where a synergetic delivery mechanism to coordinate multiple EVs is proposed to fulfill part feeding tasks.

A chaotic reference-guided multi-objective evolutionary algorithm based on self-adaptive local search (CRMSL) is constructed to deal with the problem. The proposed CRMSL benefits from the combination of reference vectors guided evolutionary algorithm (RVEA) and chaotic search. A novel directional rank sorting procedure and a self-adaptive energy-efficient local search strategy are then incorporated into the framework of the CRMSL to obtain satisfactory computational performance.

The involvement of the chaotic search and self-adaptive energy-efficient local search strategy contributes to obtaining a stronger global and local search capability. The computational results demonstrate that the CRMSL achieves better performance than the other two well-known benchmark algorithms in terms of four performance metrics, which is inspiring for future researches on energy-efficient co-scheduling topics in manufacturing industries.

This research fully considers the cooperation and coordination of handling devices to reduce energy consumption, and an improved multi-objective evolutionary algorithm is creatively applied to solve the proposed engineering problem.

Purpose – This chapter focuses on notions of community as related to the discourse around “community living” for people with labels of developmental disabilities, especially as they emerged during and after deinstitutionalization. Following Foucault, this chapter asks whether institutionalization and community living should be conceived of as two separate epochs or as governed by similar logic. The second focus of the chapter is in the ways notions of “community” were evoked by various stakeholders such as parents of children with labels of mental retardation, professionals in the field of developmental disability, and those of formerly institutionalized peoples themselves.

Methodology/approach – This chapter employs the methodological aspects of the work of Michel Foucault and constructs a genealogy of notions of community in relation to deinstitutionalization and the field of developmental disabilities.

Findings – “Community” has been discursively produced in several forms: as a binary opposite of “institution,” as a set of human relationships, and as a paradigm shift in relation to the way developmental disabilities should be conceptualized. It remains unclear whether we have truly moved from an institutional model to a “community-based” model for those with developmental disabilities.

Originality/value of the chapter – Reconceptualizing deinstitutionalization and community living as discursive formations aids in the understanding of the difference between abolition of institutionalization as a mindset and other formulations of the concept of “community” in the field of developmental disabilities.

The purpose of this study is to develop a new parallel metaheuristic algorithm for solving unconstrained continuous optimization problems.

The proposed method brings several metaheuristic algorithms together to form a coalition under Weighted Superposition Attraction-Repulsion Algorithm (WSAR) in a parallel computing environment. The proposed approach runs different single solution based metaheuristic algorithms in parallel and employs WSAR (which is a recently developed and proposed swarm intelligence based optimizer) as controller.

The proposed approach is tested against the latest well-known unconstrained continuous optimization problems (CEC2020). The obtained results are compared with some other optimization algorithms. The results of the comparison prove the efficiency of the proposed method.

This study aims to combine different metaheuristic algorithms in order to provide a satisfactory performance on solving the optimization problems by benefiting their diverse characteristics. In addition, the run time is shortened by parallel execution. The proposed approach can be applied to any type of optimization problems by its problem-independent structure.