Improved Gaussian mixture model and Gaussian mixture regression for learning from demonstration based on Gaussian noise scattering

Learning from Demonstration (LfD) is an effectual approach for robots to acquire new skills by implementing intuitive learning through imitating human demonstration. As one of the mainstream learning models for LfD, Gaussian mixture modeling (GMM) and Gaussian mixture regression (GMR) exhibit the advantages of ease of use and robust learning capabilities. To further improve the learning and regression performance of GMM/GMR, in this paper, improved GMM/GMR based on a Gaussian noise scattering strategy is designed. The main contributions of this study include: 1) the Gaussian noise scattering strategy is developed to eliminate the requirement of creating multiple demonstrations and overcome the jitter and sharp-turning defects of the demonstration; 2) based on a new evaluation criterion IBF and the sparrow search algorithm (SSA), GMM/GMR is optimized to achieve the balance of feature retention of the demonstration and the smoothness of the reproduced solution. Experimental results show that with the Gaussian noise scattering strategy, the geometric similarity of the reproduced solution and the demonstration increased for approximately 33.16 %, and the smoothness improved for 19.83 %. The challenges of underfitting and overfitting in GMM/GMR were effectively mitigated after incorporating the evaluation criterion IBF and leveraging SSA. This demonstrates the potential applicability of the improved GMM/GMR in practical industrial scenarios

From stigma to strength?:the interrelations between sexual identity stigma, well-being, and accepting communities on Instagram amongst sexual minority youth

Initial evidence suggests that engaging with accepting communities on social media such as Instagram may inform sexual minority youths' sense of stigma and well-being. However, as existing research has predominately drawn upon cross-sectional or qualitative designs, it is currently unclear whether the positive experiences identified in previous research accumulate, endure, or evolve over time. We also know relatively little about whether engagement with accepting online communities is primarily a compensatory or enhancing behavior. Thus, drawing upon minority stress theory and broaden-and-build theory, this study explores the longitudinal reciprocal relationships between perceived stigma, well-being, and engagement with accepting Instagram communities. Three-wave panel data were collected from 460 sexual minority youth in the United States and Poland (M age = 18.58, SD = 1.64), and data were analyzed using a random intercept cross-lagged panel model. At the between-person level, engagement with accepting Instagram communities was positively associated with perceived stigma and negatively associated with well-being. No significant within-person associations emerged between perceived stigma and engagement with accepting Instagram networks. However, a positive reciprocal relationship was found between well-being and engagement with accepting Instagram communities. Cultural context had no moderating effect on the hypothesized model. Results suggest that whilst the interrelations between perceived stigma and engaging with accepting online networks may be short-lived, engaging with supportive Instagram communities may contribute to an upward spiral of positive emotions. Findings therefore extend the existing literature regarding the potential benefits of social media use amongst sexual minority youth. [Abstract copyright: © 2025 Foundation for Professionals in Services to Adolescents.

Chancel repair liability and leasehold property:are leaseholders at risk?

*L. & T. Review 98 The Law Commission agreed to conduct a project entitled "Chancel Repair Liability and Registration", focused on chancel repair liability as part of its 13th Programme of Law Reform (now rolled into the 14th Programme of Law Reform). The stated aim of the project is to "close the loophole and so achieve with certainty what was intended to be achieved by the Land Registration Act 2002". It is estimated that doing so would "eliminate the current standard practice of purchasers searching and/or insuring against the risk of liability, which costs an estimated 20 million each year": see Law Commission, The 13th Programme of Law Reform, Law Com. No.377, 2017 at 2.30–2.31. Concerns and issues surrounding chancel repair liability have been addressed previously by the Law Commission, and these matters have been considered by the courts, most notably in cases such as Aston Cantlow and Wilmcote with Billesley Parochial Church Council v Wallbank [2003] UKHL 37; [2004] 1 A.C. 546 , where the landowners were held liable for chancel repair costs in the region of tens of thousands of pounds. An aspect of chancel repair liability which receives less attention, however, is that connected with leasehold land. This article focuses on this aspect of chancel repair liability. In particular, it highlights the historical context of chancel repair liability and examines the arguments about how liability may arise in connection with leasehold land. It then explores the related practical issues, suggesting that these should be taken account of as part of the Law Commission’s efforts to reduce some of the uncertainty surrounding chancel repair liability

Interview with the Rosalie Ryrie Foundation

Domestic abuse affects far more than physical safety, reaching into the emotional, financial, and social lives of families and communities. In Wakefield, West Yorkshire, the Rosalie Ryrie Foundation (RRF) offers vital support by treating domestic abuse as a breakdown of family relationships. Founded by Ann Ramsden, the charity uses a tool called “Charlie” to help individuals and families recognise and change harmful patterns of behaviour. This inclusive, non-blaming approach focuses on building healthier relationships, offering families who want to stay together a chance to move forward in safer, more positive ways. The chapter presents Ann’s reflections, drawn from a recent interview conducted specifically for this book

A Hybrid Optimization Approach for Multi-Generation Intelligent Breeding Decisions

Multi-generation intelligent breeding (MGIB) decision-making is a technique used by plant breeders to select mating individuals to produce new generations and allocate resources for each generation. However, existing research remains scarce on dynamic optimization of resources under limited budget and time constraints. Inspired by advances in reinforcement learning (RL), a framework that integrates evolutionary algorithms with deep RL was proposed to fill this gap. The framework combines two modules: the Improved Look-Ahead Selection (ILAS) module and Deep Q-Networks (DQNs) module. The former employs a simulated annealing-enhanced estimation of the distribution algorithm to make mating decisions. Based on the selected mating individual, the latter module learns multi-generation resource allocation policies using DQN. To evaluate our framework, numerical experiments were conducted on two realistic breeding datasets, i.e., Corn2019 and CUBIC. The ILAS outperformed LAS on corn2019, increasing the maximum and mean population Genomic Estimated Breeding Value (GEBV) by 9.1% and 7.7%. ILAS-DQN consistently outperformed the baseline methods, achieving significant and practical improvements in both top-performing and elite-average GEBVs across two independent datasets. The results demonstrated that our method outperforms traditional baselines, in both generalization and effectiveness for complex agricultural problems with delayed rewards

Crisis Communication and Event Reputation in Saudi Arabia: The Moderating Role of the Distributed Leadership

The purpose of this study is to investigate the moderating role of distributed leadership between attributions to events, crises, and event reputation. Using Situational Crisis Communication Theory (SCCT), attribution of crisis responsibility, distributed leadership, and event reputation were assessed with questionnaires. Data were collected at a single point in time over two months across multiple sports events, involving 240 managers in Saudi Arabia. The findings showed that distributed leadership and attributions of crisis responsibility were significantly linked with event crises. However, the moderating effect of distributed leadership on the relationship between attributions of crisis responsibility and event reputation was not found. Event organizers should develop proactive crisis management plans that serve as guidelines for attributing responsibility. These plans should be evaluated after each crisis to address weaknesses and to learn from other mega events hosted by the kingdom. This study is the first to investigate crisis management in the Middle East by testing the moderating role of distributed leadership in Saudi Arabian event settings

A Hybrid Optimization Approach for Multi-Generation Intelligent Breeding Decisions

Multi-generation intelligent breeding (MGIB) decision-making is a technique used by plant breeders to select mating individuals to produce new generations and allocate resources for each generation. However, existing research remains scarce on dynamic optimization of resources under limited budget and time constraints. Inspired by advances in reinforcement learning (RL), a framework that integrates evolutionary algorithms with deep RL was proposed to fill this gap. The framework combines two modules: the Improved Look-Ahead Selection (ILAS) module and Deep Q-Networks (DQNs) module. The former employs a simulated annealing-enhanced estimation of the distribution algorithm to make mating decisions. Based on the selected mating individual, the latter module learns multi-generation resource allocation policies using DQN. To evaluate our framework, numerical experiments were conducted on two realistic breeding datasets, i.e., Corn2019 and CUBIC. The ILAS outperformed LAS on corn2019, increasing the maximum and mean population Genomic Estimated Breeding Value (GEBV) by 9.1% and 7.7%. ILAS-DQN consistently outperformed the baseline methods, achieving significant and practical improvements in both top-performing and elite-average GEBVs across two independent datasets. The results demonstrated that our method outperforms traditional baselines, in both generalization and effectiveness for complex agricultural problems with delayed rewards

Gender, relationships and desistance

This edited collection offers unique insight into the role and impact of relationships for women involved in the criminal justice system. Through drawing together academic research, lived experience and reflections of frontline perspectives, the collection interrogates the personal, public and professional themes of these relationships, broadening current analysis and calling for a reimagining of the future. Each author demonstrates the complexity of these themes with rich and powerful contributions that offer a crucial understanding into the complexity and nuance of this area. By connecting a range of perspectives and different forms of expression, this original collection extends and challenges current understanding and calls for reimaging and change