Digitalising social value for sustainable urban regeneration: governance, co-production gaps and delivery burdens in London

This paper investigates how social value is operationalised in urban regeneration and how digital reporting platforms shape the measurement and governance of social sustainability. Drawing on semi-structured interviews with UK social value professionals and a resident survey conducted within the Elephant and Castle regeneration programme in London, the study examines how platform-based systems translate procurement commitments into auditable performance categories. These systems embed predefined classification schemas, proxy valuation metrics and rule-based validation procedures that structure how outcomes become visible and comparable across projects. The findings indicate that digital reporting platforms enhance oversight and inter-project benchmarking but prioritise outcomes that align with measurable procurement indicators. Employment generation, apprenticeships and local procurement expenditure dominate reported performance, while relational and place-based outcomes, such as trust, belonging and neighbourhood continuity, remain marginal. Reporting requirements generate substantial evidencing burdens across supply chains, may introduce data distortions through proxy-based and threshold-led reporting, and can concentrate engagement at early project stages, limiting sustained community influence and creating technical barriers to participation. The analysis highlights how digital reporting platforms can operate as governance infrastructures within smart city environments, shaping what is prioritised, funded and recognised as credible impact. The findings provide practical insights for the design of more i

Situational facilitators and barriers of bystander intervention intent in image-based sexual abuse contexts

Image-based sexual abuse (IBSA) encompasses the taking, sharing, and/or making threats to share nude or sexual images of others without consent. Research shows that a large percentage of individuals have been a bystander to IBSA, but most do not intervene. Currently, there is little understanding of why this is the case. The research presented in this article begins to address this gap in the literature by identifying situational factors which facilitate or inhibit behavioural intentions to intervene through three experimental studies. In each study, situational factors were manipulated using vignettes which depicted the taking of images without consent (Study 1; n = 126), sharing images without consent (Study 2; n = 125), and threatening to share images (Study 3; n = 125). The dependent variable across studies was how likely they would be to intervene if they witnessed the scenario described. Study 1 investigated the effect of the presence of other bystanders (no other bystanders present, other bystanders present who were friends with each other, or other bystanders present who were strangers to each other) and no significant effect was found. Study 2 investigated the role of initial consent to take the image (self-taken or stealth-taken) and bystander relationship with the victim (friend or stranger). Likelihood to intervene was less likely when the image was self-taken and the victim was a stranger. Finally, Study 3 investigated the role of initial consent to take the image and bystander relationship with the perpetrator (friend or stranger). Perpetrator-focused intervention was more likely, but justice-focused intervention was less likely, when the perpetrator was a friend. These findings have implications for the development of educational materials, campaigns, and agendas aimed at encouraging bystander intervention

Participatory toolkit: participatory research with young people

This toolkit provides a practical guide to conducting participatory research with young people. It attempts to demonstrate what can be achieved when facilitating a research space where young people are in the driver’s seat. The toolkit draws on the experience gained and lessons learnt throughout the Youth Social Action (YSA) Ecosystem research project. The YSA project was commissioned by the Greater London Authority (GLA) Civil Society and Sports ‘Youth team,’ and was conducted by researchers from the Centre for Applied Research for Empowering Society (CARES)0F with young Londoners as peer researchers

The urgent need for biosecurity education within the agribusiness sector

Biosecurity within the agribusiness sector is an often-neglected and forgotten area. Biosecurity vulnerabilities within the sector hold significant global risks, which are emphasised by the ever-growing threat of climate change, the presence of global conflicts, and the advancements made in science and technology. Biosecurity vulnerabilities also hold a multitude of public health (physical and psychological), environmental, economic, and political consequences. In this study, we systematically surveyed 199 university-taught courses relating to agribusiness to determine the extent to which biosecurity risks were addressed. We found that only 4% of surveyed courses contained clear biosecurity elements, thus exhibiting a huge educational gap. Among these 4%, zero courses addressed agroterrorism, agro-crime, or bioweapons, including the economic, physical, psychological, and political implications. We therefore argue for the development of an internationally coordinated curriculum that embeds biosecurity concepts into established courses. This will hugely enhance existing topics taught in courses to meet the urgent need in new circumstances derived from new science and technology

Editorial: Sexuality and sexual dysfunctions

In an era in which access to information is greater than ever, the general population paradoxically holds increasing levels of misinformation about specific topics. This is particularly evident in the field of sexuality. Today, individuals often seek information on the internet that may originate from sources of questionable reliability, resulting in content that can be confusing or inaccurate. For this reason, scientifically grounded, evidence-based information becomes especially relevant. The aim of this Research Topic has been to provide accurate and useful information on this topic, both for the general population and for professionals, by presenting a diverse and compelling collection of articles that will equip professionals with practical tools and foster interest in sexological science among the public

Static output-feedback control for uncertain systems under input saturation and persistent disturbance

This paper addresses the static output-feedback (SOF) control problem for discrete-time systems subject simultaneously to input saturation, non-vanishing disturbances, and uncertainties described in a polytopic form. Level sets of the Lyapunov function are used to characterize the estimation of the domain of admissible initial states for the system and also to determine a region where the states of the closed-loop system will be confined in the presence of persistent disturbance. The proposed design conditions are formulated as Linear Matrix Inequalities (LMIs). Numerical experiments demonstrate the effectiveness of the method in providing SOF controllers that ensure the states of the closed-loop uncertain system are confined to a bounded region despite the presence of persistent disturbances

A preliminary waitlist-controlled randomised trial (WRCT) of mindful-compassion for improving sexual intimacy, well-being, and quality of life in women following cancer treatment in home hospice care

Psychosexual interventions remain limited in hospice care worldwide. This exploratory pilot study evaluated the feasibility of a mindful-compassion intervention to enhance psychosexual well-being among 22 women with advanced cancer receiving in-home hospice care. A mixed-methods design was employed, combining a waitlist-controlled randomised trial (WRCT) with qualitative content analysis of participant feedback. The intervention comprised four weekly mindful-compassion sessions. Co-primary outcomes were sexual function, mindful-compassion, well-being, and quality of life, assessed at baseline (week 0), week 4, and week 12. Participants were randomly allocated to an active intervention group or a delayed (waitlist-control) group. Potential benefits over time were observed across sexual functioning, mindful-compassion, well-being, and quality of life (p < .05). At week 4, outcomes in the active group suggested improvements in well-being, sexual functioning, and sexual pain compared with the delayed group (p < .05). By week 12, differences between groups had narrowed, suggesting similar benefits following intervention delivery. Qualitative analysis reported enhanced sexual intimacy, reflected in improved emotional connection, communication, touching, and kissing with partners. Participants emphasised that intimacy remains meaningful even in the final stages of life. These preliminary findings highlight the potential value of mindful-compassion psychosexual support in hospice care. Larger controlled studies are required to confirm and extend these results

From moral indignation to affective citizenship: public shaming of celebrity emigration from Russia during the war against Ukraine

The paper analyses the public shaming campaigns that emerged around celebrity emigration following the Russian invasion in Ukraine. It examines how the individual commentators on social media have been conducting symbolic destruction of these celebrities’ moral character and social status while at the same time constituting the moral meaning of emigration from Russian Motherland as an act of betrayal and reconstructing a national civil contract of national belonging. Thus, through interpretation of the social media discourse on celebrity emigration we reveal the affective relations of Russian patriotic citizens to their nation and the state

Addressing class imbalance in predicting student performance using SMOTE and GAN techniques

Virtual Learning Environments (VLEs) have become increasingly popular in education, particularly with the rise of remote learning during the COVID-19 pandemic. Assessing student performance in VLEs is challenging, and the accurate prediction of final results is of great interest to educational institutions. Machine learning classification models have been shown to be effective in predicting student performance, but the accuracy of these models depends on the dataset’s size, diversity, quality, and feature type. Class imbalance is a common issue in educational datasets, but there is a lack of research on addressing this problem in predicting student performance. In this paper, we present an experimental design that addresses class imbalance in predicting student performance by using the Synthetic Minority Over-sampling Technique (SMOTE) and Generative Adversarial Network (GAN) technique. We compared the classification performance of seven machine learning models (i.e., Multi-Layer Perceptron (MLP), Decision Trees (DT), Random Forests (RF), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CATBoost), K-Nearest Neighbors (KNN), and Support Vector Classifier (SVC)) using different dataset combinations, and our results show that SMOTE techniques can improve model performance, and GAN models can generate useful simulated data for classification tasks. Among the SMOTE resampling methods, SMOTE NN produced the strongest performance for the RF model, achieving a Region of Convergence (ROC) Area Under the Curve (AUC) of 0.96 and a Type II error rate of 8%. For the generative data experiments, the XGBoost model demonstrated the best performance when trained on the GAN-generated dataset balanced using SMOTE NN, attaining a ROC AUC of 0.97 and a reduced Type II error rate of 3%. These results indicate that the combined use of class balancing techniques and generative synthetic data augmentation can enhance student outcome prediction performance

Greensense: Cloud-IoT for smart plant monitoring

This paper presents a Cloud-IoT-based system designed for efficient and real-time monitoring of plant health, leveraging Raspberry Pi and Microsoft Azure services. The system integrates low-cost environmental sensors to collect key parameters, including temperature, humidity, and soil moisture. Sensor data is transmitted via Wi-Fi to the Azure cloud platform, where it is processed, visualized, and analyzed using integrated IoT and data analytics tools. Architecture emphasizes modularity, scalability, and remote accessibility, making it suitable for applications in precision agriculture and smart farming. The paper highlights the full data pipeline, including sensor integration, edge processing on Raspberry Pi, secure cloud communication, and real-time monitoring through an Azure-hosted dashboard