London Metropolitan University

This qualitative study explores how family therapists ( n = 15) in Dhaka, Bangladesh, assist couples in navigating divorce decision‐making, addressing a gap in research on divorce ideation in non‐Western contexts. Thematic analysis of the interviews revealed four key themes: (1) Therapists as experts, (2) Respect for client autonomy, (3) Therapist neutrality, and (4) Clarity in the decision as the goal. Each of the themes is situated in the social context of Dhaka, the capital city, where couple therapy is a fairly new mental health practice and beliefs about marriage and divorce are culturally informed. These cultural beliefs include ideas that divorce is shameful, is not religiously sanctioned, and is harder on women. Future research could focus on the experiences of therapists or other community helpers (i.e., religious or kinship networks) in rural areas and among less‐educated populations to better understand the broader landscape of divorce decision‐making in Bangladesh.

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 that facilitate or inhibit behavioral intentions to intervene through three experimental studies. In each study, situational factors were manipulated using vignettes that 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 the 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.

The families of individuals who experience mental health difficulties play a crucial role in help-seeking behaviours, particularly in collectivist contexts, where the explanatory models (EM) that some families hold on the aetiology of mental health have been reported to differ from those of western-trained mental health professionals. The discrepancy in EM between care-seekers and caregivers has been reported to impact the patient’s duration of untreated illness (DUI) by mental health professionals. This can have a significant impact on the identified patient’s well-being. This study explores how culturally shaped explanatory psychological and psychiatric distress models impact help-seeking behaviour among family caregivers in Oman. A cross-sectional, analytic study that recruited Omani relatives of individuals who attended Sultan Al Qaboos University Hospital (SQUH) for the first episode of psychiatric complaints. Data collection spanned between November 2020 and April 2021, using tools that the researchers created after consulting local mental health professionals. A total of 116 participants were recruited. Half of the respondents endorsed more traditional and spiritual EM, and this perception influenced help-seeking behaviours (p = 0.0001), resulting in delays in accessing mental health services because of consultations with traditional healers first. The overall mean DUI by mental health services was (14.69 ± 15.72 months). Sociodemographic factors, such as caregivers’ educational level (p = 0.023), were significantly associated with seeking help from traditional healers. To avoid excluding certain groups from psychological and psychiatric care, it is essential to consider families' cultural beliefs and practices. Mental health professionals should work with indigenous healers to create awareness programs that meet the community's needs.

This paper focuses on the fault detection and diagnosis of terminal units (TUs) in a building located in London, utilizing real operational historical data to assess their performance and optimal placement across multiple floors. While precise locations of the TUs are unavailable, our method analyzes their operational behaviour for one month, applying popular machine learning models to detect and analyze faults effectively. By examining each TU individually and in the aggregate, we identify behavioural patterns that inform decisions regarding their positioning within the building. The dataset comprises over 2 million data points collected from 730 TUs, enabling a comprehensive analysis of their functionality and the impact of suboptimal thermostat placements. Our study employs three machine learning models-traditional multi-class Support Vector Machines and two ensemble methods: Random Forest (RF), and Adaptive Boosting (AdaBoost)-to classify TU behaviors into normal operation, heating faults, and cooling faults. Results indicate that RF outperforms the other models with an accuracy of 99.89%, while AdaBoost achieves an accuracy of 85% and SVM shows 47% accuracy. The findings underscore the potential of a data-driven approach to inform retrofitting decisions and enhance the reliability of HVAC systems. This research contributes valuable knowledge toward optimizing TU placement, ultimately leading to improved energy efficiency and indoor environmental quality.

The human microbiome plays a critical role in health and disease, with recent innovations in microbiome research offering groundbreaking insights that could reshape the future of healthcare. This study explored emerging methodologies, such as long-read sequencing, culturomics, synthetic biology, machine learning, and AI-driven diagnostics, that are transforming the field of microbiome–host interactions. Unlike traditional broad-spectrum approaches, these tools enable precise interventions, such as detecting foodborne pathogens and remediating polluted soils for safer agriculture. This work highlights the integration of interdisciplinary approaches and non-animal models, such as 3D cultures and organ-on-a-chip technologies, which address the limitations of current research and present ethical, scalable alternatives for microbiome studies. Focusing on food safety and environmental health, we examine how microbial variability impacts pathogen control in food chains and ecosystem resilience, integrating socioeconomic and environmental factors. The study also emphasizes the need to expand beyond bacterial-focused microbiome research, advocating for the inclusion of fungi, viruses, and helminths to deepen our understanding of therapeutic microbial consortia. The combination of high-throughput sequencing, biosensors, bioinformatics, and machine learning drives precision strategies, such as reducing food spoilage and enhancing soil fertility, paving the way for sustainable food systems and environmental management. Hence, this work offers a comprehensive framework for advancing microbiome interventions, providing valuable insights for researchers and professionals navigating this rapidly evolving field.

This paper presents a novel wideband circularly polarized (CP) cavity-backed slot antenna based on Substrate Integrated Waveguide (SIW) technology, designed for compact and high-efficiency performance. The proposed antenna utilizes a hexagonal SIW cavity to simultaneously excite two closely spaced resonant modes (TM₁₁₀ and TM₂₁₀), resulting in enhanced bandwidth for linear polarization (LP). To achieve circular polarization, a passive, single-layer linear-to-circular polarization converter is integrated above the cavity, offering a structurally simple and PCB-compatible solution. Unlike conventional CP designs that rely on complex feeding networks or multilayered structures, this configuration maintains a planar profile and efficient performance. A fabricated prototype demonstrates strong agreement between simulation and measurement, achieving a peak gain of 9.2 dBic and a 14% axial ratio (AR) bandwidth. These results highlight the antenna’s suitability for modern wireless systems requiring wideband CP functionality, including satellite communications, 5G modules, and compact embedded devices.

Cancer remains one of the leading causes of mortality worldwide, with breast cancer being a particularly prevalent form. Projections estimate nearly 20 million new cases globally over the next two decades. Early detection is critical for effective treatment; however, conventional diagnostic techniques often lack the necessary sensitivity and specificity, with some methods being invasive and labor-intensive. Recent advancements in microwave imaging (MWI) have shown significant potential as efficient, non-invasive tools for monitoring various cancer types. MWI operating in the terahertz (THz) range has emerged as a promising approach for bio-sensing, offering the precision needed to differentiate between healthy and cancerous tissues by analyzing small-scale biological features. Among the methods for breast cancer detection, the identification and analysis of MCF-7 breast cancer cells are particularly significant. THz waves interact uniquely with the intrinsic properties of MCF-7 cells, making THz-based biosensors ideal candidates for diagnostic tools. However, many existing sensors are limited in key performance areas, including operating bandwidth and absorption efficiency. This study introduces a novel multi-band metamaterial (MTM)-based biosensor specifically designed for the detection of MCF-7 breast cancer cells. The sensor features a compact geometry composed of multiple resonators made from 200-nm-thick aluminum (Al) layers on a 50-μm-thick polyethylene terephthalate (PET) substrate. With dimensions of only 198 × 198 μm², the proposed device is exceptionally compact. It operates in the 0.5 THz to 1.6 THz frequency range and achieves near-perfect absorption rates (>99%) across multiple bandwidths. These results are achieved through precise tuning of the sensor's geometry and architectural optimization, significantly enhancing its sensitivity for cancer detection. Comprehensive validation of the sensor is performed using full-wave electromagnetic analysis, which includes evaluating electric and magnetic field distributions, surface currents, and scattering parameters. Extensive benchmarking demonstrates the device’s superior performance compared to state-of-the-art biosensors, excelling in metrics such as quality-factor, figure of merit (FOM), and absorption efficiency. Additionally, the proposed sensor has been integrated into an MWI system to evaluate its practical application. The device successfully discriminated against subtle changes in the refractive index of biological tissues, confirming its ability to detect MCF-7 cells effectively. These findings highlight the sensor's suitability as a non-invasive, early-stage diagnostic tool for breast cancer.

This article investigates how leisure activities inform identification processes among British Bangladeshi Muslim women in Tower Hamlets, London. Focusing on women-only events organised in community centres that cater to British Bangladeshi women, we explore the significance of these spaces in the negotiation and maintenance of identity and community. Based on a two-year ethnography conducted as part of the research project Migrant Memory and Postcolonial Imagination , we argue that women-only leisure activities are part of a strategy of momentary self-exclusion, which is central to the articulation of a politics of location for participating women. The focus on leisure contributes to the literature on diaspora studies by providing a more holistic understanding of questions of belonging.

Forecasting human development is important for tracking sustainable growth and societal progress. However, this task presents statistical challenges. The primary difficulty is the limited nature of the available data, which is a typical problem encountered in forecasting many social time series. In this paper, we propose a novel approach for forecasting short time series based on the Theta method. The classical Theta method decomposes the time series into trend and short-run components. We propose an improved version of the Theta method, called $\theta$-comb, based on the combination of alternative forecasts for the short-run component. We apply the proposed method to forecast worldwide human development, measured with the Human Development Index, from 1990 to 2022. The results show that the $\theta$-comb method significantly improves the out-of-sample accuracy in comparison to existing approaches.

This paper analyzes the ethics of executive compensation governance in large UK publicly quoted companies. It combines content analysis of Financial Times Stock Exchange 100 (FTSE-100) remuneration committee reports with interviews with key decision-makers. A framework from business ethics and corporate governance literature helps understand the factors shaping this governance. Maintaining public trust requires aligning with societal norms and regulatory compliance. Findings indicate growing awareness of ethical considerations among decision-makers and highlight the need for a more holistic, values-based approach that strengthens stakeholder inclusivity. Interviews with decision-makers reveal challenges in translating ethical principles into practice. Governance mechanisms intended to align executive and shareholder interests face limitations, and perceived unfairness in executive rewards persists. This paper applies theory to analyse the interplay of external and internal factors shaping executive compensation governance, develops practical recommendations for enhancing its effectiveness and integrity, and provides a heat map tool to compare organisations’ ethical principles.

This paper presents a novel technique for detecting tumors in human breasts using a single high-gain antenna and a metasurface (MTS) layer. An artificial neural network (ANN) is employed to classify detected tumors as benign or malignant based on the permittivity of the tissue. The detection and classification process leverages the contrast in dielectric properties between normal and abnormal biological tissue, utilizing the actual permittivity as a distinguishing factor. This study highlights the effectiveness of the proposed technique in accurately detecting and localizing malignant tumors within human breasts. Electromagnetic analysis is conducted using voxel datasets derived from human models to validate the approach. Tumor localization is achieved with high precision based on the Specific Absorption Rate (SAR) magnitude. The study considers various fat layer thicknesses (10–100 mm) and tumor radii (2.5–10 mm), addressing scattering effects comparable to the wavelength of the applied microwave radiation. The proposed Vivaldi antenna operates at 3.5 GHz, achieving a gain of 15.5 dBi with a half-power beamwidth in the E-plane of ±12°. Results demonstrate minimal average errors and high-performance indices (PI) for fat thickness (0.1 %, 90 %), tumor size (0.06 %, 94 %), and tumor classification (0.11 %, 89 %). The experimental and simulation results exhibit strong agreement, confirming the feasibility and potential of the proposed antenna system for medical diagnostics and post-detection rehabilitation planning.

Using the case of Polish far‐right activists in Britain, this paper explores how migrants joining far‐right groups in countries of residence reconcile their own transnational lives with nativist attachment to the national soil. The paper adopts an anthropological framework on discursive and performative strategies used to navigate this contradiction. Drawing on interviews with Polish migrants and observer participation in their political rituals, we identify their ways of political home‐making in Britain. Special consideration is given to the symbolic elements that have always been at the heart of far‐right political thought—the national soil, the dead ancestors, and the heroic past—and, for our respondents, are brought to life in the Polish cemeteries in Britain. We explore mythopoeic narratives and ritualised performances around these ‘deathscapes’, which help activists establish an organic connection with symbolically significant locations in the country of residence and claim a special place in its ethnic hierarchy.

This article examines the transformation of Turkey’s foreign policy under the Justice and Development Party (AKP) through the lens of ontological security. While Turkey has historically been engaged with the European ideal as the manifestation of the ontological security, the AKP era has witnessed significant shifts driven by a multi-layered activism stemming from the self-claimed middle powerhood. The study argues that ontological security provides a crucial framework for understanding these changes, particularly Turkey’s pursuit of a stable state identity amid shifting foreign policy priorities. This study explores the ruptures and continuities in Turkey’s foreign policy and assesses how identity-based concerns shape its strategic actions. In doing so, it contributes to the broader discourse on ontological security and middle power dynamics, offering a nuanced perspective on Turkey’s evolving foreign policy and self-positioning in the international arena.

The world faces excessive challenges to conserve the environment and provide sustainable solutions for mankind. Adopting digital circular supply chain management is one initiative to tackle these issues. Academic literature shows that digital technologies are a vital enabler of adopting circular economy practices. However, there are various roadblocks regarding a realistic view of adopting Digital Circular Supply Chain Management (DCSCM). After reviewing the available literature, it is observed that critical success factors (CSFs) and performance outcomes (POs) of DCSCM need further investigation. Therefore, the presented study examines POs using the Z number integrated fuzzy-SWARA technique. In addition, the Z number integrated fuzzy-WASPAS tool is used to prioritize the critical success factors. Furthermore, sensitivity analysis is conducted to check the robustness of critical success factors. The results show that ‘Strategic vision to adopt DCSCM’ and ‘Increased awareness and understanding of circular economy principles and benefits’ are the most critical success factors. Among the performance outcomes, ‘Streamlined processes and reduced inefficiencies through automation and optimization’ and ‘Effective Demand Forecasting and optimized inventory management’ are the highest performance outcomes. Furthermore, the sensitivity analysis results show that a ranking of critical success factors slightly varies by changing weights of POs.

Gilles Deleuze was a major figure in Continental Philosophy of the late twentieth century and is pivotal to the adoption of Poststructuralism in the social sciences. Deleuze’s philosophy and relevance to Critical Social Psychology is not easily summarised because it is not singular and narrowly systematic, but rather plural, open and creative. Two major themes in his work are particularly valuable to psychology—his treatment of thought and sensemaking and his concern with being and becoming. In this chapter we show how these two themes combine in a number of distinct topics. Deleuze describes two kinds of multiplicity, quantitative and qualitative, and how experience is constituted through indivisible flows rather than clearly defined intervals and parts. His key concepts of virtual and actual provide a way to reformulate questions around realism and relativism, and to demonstrate that that the ideal is not abstract, but rather in the process of being determined through our actions. Deleuze approaches subjectivity as a continuously transforming and plural style of living rather than a self-contained ‘thing’. Affect is similarly treated in terms of what can be done within an assemblage and the relations we are capable of forming. Critical Social Psychologists will find in Deleuze’s work a rich series of resource to inform an experimental and transformative approach to theoretical and empirical work.

Vitamin D is vital for bone health, immune system support, and muscle function. Deficiency in Vitamin D is widespread, with up to 65% of individuals in certain populations, including Black students at London Metropolitan University, UK, being affected. This study focuses on the need for a deeper understanding of Vitamin D prescription patterns, specifically within an inner London borough, using advanced data analytics. Previous analysis, such as ones conducted by OpenPrescribing.net , has investigated NHS prescription data but lacked a focused examination on Vitamin D. Our study introduces a novel computational approach, integrating NHS datasets from 2013 to 2023. We developed a web‐hosted dashboard using Python, Flask, Cesium, PowerBI, and libraries such as Pandas, Scikit‐learn to provide real‐time data visualization and predictive analytics. Our methodology involved API‐driven ingestion of large‐scale data, focusing on Vitamin D prescriptions in a borough, and mapping this against patient numbers. We used feature manipulation and model training to gain insights into prescription counts, dosages, medication types, and formulations. This interactive platform supports dynamic reporting through PowerBI and Cesium. Our findings reveal significant variations in prescription patterns among GP surgeries influenced by socioeconomic factors. This interdisciplinary project, in future collaboration with local GP federations, United Kingdom, enhances computational health data analysis and aims to inform better prescription practices and healthcare policies, ultimately improving policy practice and public health outcomes.

Distributed Denial of Service (DDoS) attacks pose significant threats to Industrial Internet of Things (IIoT) environments, exacerbated by the resource constraints of IoT devices and the disruptive impact of such attacks. Conventional detection and prevention methods fall short of ensuring the availability and operational continuity required in industrial IIoT deployments. This article systematically analyses artificial intelligence (AI) techniques for detecting, preventing, and mitigating DDoS attacks in IIoT systems. We examine diverse AI-driven solutions, including machine learning (ML) and deep learning (DL) models, often integrated with traditional anomaly detection, signature-based systems, and blockchain technology. These hybrid approaches enhance real-time threat identification, adaptive defence mechanisms, and decentralized trust management, addressing the evolving sophistication of DDoS attacks. The study highlights AI’s potential to strengthen IIoT security and resilience, particularly in Critical National Infrastructures (CNIs), where uninterrupted operations are paramount. However, challenges such as computational overhead, model interpretability, and dataset scarcity in industrial settings remain critical barriers. Additionally, the dynamic IIoT topology and heterogeneous device ecosystems necessitate context-aware AI solutions. This analysis underscores the need for lightweight, explainable AI frameworks and collaborative defence strategies tailored to IIoT’s unique constraints. The paper identifies current research challenges and outlines future directions, emphasizing the integration of AI with emerging technologies like edge computing and federated learning to advance proactive, scalable DDoS defence mechanisms in industrial ecosystems

‘There is no alternative’ arguments are fundamentally capitalist propaganda to hide shameful impacts of capitalism and all its projects on people and the planet. Despite of the negative consequences of capitalism, in the labyrinth of modern societies, capitalism stands as the dominant economic system shaping our everyday realities in the form of mass domestication with American dream as dominant global dream. Embedded in the fabric of everyday lives, it dictates the dynamics of commerce, labour, production and consumption.