Robert Gordon University

This article analyses the correlation between boardroom gender parity and environmental sustainability in corporate governance. While economic and environmental factors are critical considerations, other factors must also be taken into account. In this regard, the study emphasises the importance of both issues to stakeholders and the wider society. Despite the progress made, gender disparities still exist in boardrooms. The research delves into the impact of including women in business strategies on organisational success, highlighting the need for board composition that is both environmentally conscious and dedicated to achieve gender balance. Ultimately, the study concludes by urging proactive measures towards strategic planning and addressing gender imbalances in boardrooms. This study delves into the most recent research on corporate governance, boardroom gender diversity, social stereotypes, environmental sustainability, and the integration of environmental concerns in board decision-making. The primary objective of the study was to examine the correlation between gender diversity in the boardroom and corporate environmental sustainability. A methodical analysis of pertinent literature released between 2015 and 2024 was conducted, covering topics such as corporate governance, board of directors, gender diversity, and corporate environmental sustainability. This research paper explores the relationship between gender diversity in boardrooms and initiatives for environmental sustainability. The paper offers a unique perspective on the subject, transcending the conventional emphasis on financial performance. Instead, it underscores the significance of gender balance in driving corporate environmental sustainability. The study critically evaluates current corporate culture and management practices, emphasising the necessity of a board composition that is not only gender-balanced but also committed to environmentally responsible business operations. The research serves as a valuable foundation for future research on the interplay between boardroom gender parity and corporate sustainability. While the notion of achieving gender parity in boardrooms is conceptually appealing, its practical implementation poses significant challenges. The absence of gender diversity on boards renders research in this area somewhat inconclusive, as the requisite data to measure progress is lacking. Moreover, previous studies have been limited in scope and, therefore, lack the necessary breadth to allow for the generalisation of results. Furthermore, the confidential nature of boardroom deliberations renders the evaluation of boardroom dynamics a complex and onerous task, impeding the ability to conduct a robust analysis of board proceedings. As a result, conducting an exhaustive evaluation of boardroom dynamics is a practically daunting and challenging endeavour. The findings in this research provide critical insights for regulatory authorities and policymakers to reconsider the significance of gender parity within boardrooms, particularly in relation to corporate environmental sustainability. The outcomes of this research can benefit academics, government agencies, business leaders, investors, and policymakers alike. The results can help these stakeholders gain a better understanding of the value of gender diversity in the boardroom, particularly regarding environmental sustainability. As such, it can contribute to the development of more effective policies and frameworks for achieving business sustainability goals through gender-balanced leadership.

Malicious use of face forgery technology will lead to serious negative effects, so there is an urgent need for an effective face forgery detection approach. Most existing approaches directly take the cropped face regions from the whole image as input and leverage the extracted visual features to predict real and fake through a binary classifier. However, advanced forgery methods will leave no obvious visual forgery artifacts, especially under real-world high compression conditions. To address such limitations, a Dual-branch Pre-activation Bottleneck Transformer (DPBoT) is proposed for face forgery detection in this paper. Instead of directly extracting appearance features, this method designs a dual-branch model to capture both visual forgery artifacts and local noise feature inconsistencies. Furthermore, to reduce information loss and ensure smoother information propagation within the model, attention mechanisms are introduced into face forgery detection, and a novel PBoT backbone architecture is designed. Finally, features from both branches are fused by bilinear pooling. Extensive experimental results on four well-known datasets show that the proposed method achieves promising results, which outperform the state-of-the-art face forgery detection methods.

Aim/Purpose: This paper focuses on app review analysis techniques, driven by the rapid advancement of the mobile app market and NLP techniques in optimizing mobile app user experiences. Background: Owing to technological advancements, app review analysis has rapidly evolved. This study examines both conventional and emerging techniques, including current advancements such as large language models (LLMs) in app review analysis. It provides an overview of the various methods used across different categories of app review analysis, comparing effective strategies for identifying user concerns and enhancing app functionality. Methodology: A systematic review was utilized based on two major standard guidelines, PRISMA and Kitchenham’s guidelines, for the period of 2014 to 2024. After defining the review protocol, papers were identified through keyword-based searches on six major online databases: Scopus, Web of Science, IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Following screening and excluding papers based on defined quality criteria, 53 papers were considered for this study. The use of Large Language Models. PRISMA ensures a transparent and reproducible review process, while Kitchenham’s guidelines provide a structured and rigorous approach for evaluating and synthesizing the literature. Contribution: This review study aims to evaluate the current state of knowledge on app review analysis techniques to improve mobile app user experiences. This study categorized the existing state-of-the-art papers into eight different categories, such as sentiment analysis, review classification, summarization, and prioritization, and examined challenges related to app review analysis. Furthermore, the study emphasizes the potential of LLMs for optimizing and automating app review analysis and provides future directions to address gaps in user-centric app development. Findings: Among the eight main categories defined in app review analysis, sentiment analysis is the most prevalent, followed by review classification and information extraction. Most studies use a combination of these categories to achieve a comprehensive goal. Prioritization techniques such as risk matrices, thumbs-up count-based approach, and anomaly detection are widely used to identify emerging issues. Extracting meaningful information and evaluating the proposed approach are the most common challenges identified. Novel LLMs, like Chat-GPT, significantly enhance review analysis by automating the process, improving feature extraction, and enabling context-aware review classification. Recommendations for Practitioners: The combination of conventional approaches and novel LLM-based methods can enhance both the efficiency and accuracy in identifying and addressing critical issues raised through mobile app user reviews. It effectively prioritizes user concerns by leveraging the strengths of both traditional preprocessing techniques and advanced LLMs. Recommendations for Researchers: Researchers are encouraged to explore the integration of emerging technologies like LLMs to enhance the of app review analysis, particularly in feature-specific sentiment analysis. Impact on Society: The results of this study contribute to enhancing the mobile app user experience through effective app review analysis, which improves user satisfaction and supports user-centered app development. This ultimately leads to a better mobile app ecosystem, benefiting both users and developers. Future Research: In the future, this research can be extended in multiple directions. Researchers can address the existing research gaps that LLMs have yet to address, particularly in prioritizing user concerns. Additionally, there is potential for further research on tool implementations focusing on identifying persistent issues through time series analysis by considering the app version and date of the app reviews. Moreover, there is a need to develop comprehensive frameworks that are more generalizable across different apps and categories, with a focus on identifying user concerns related to specific features.

Applying circular economy principles to the renovation of existing buildings is increasingly recognized as essential to achieving Europe’s climate and energy goals. However, current decision-making frameworks rarely integrate life cycle carbon assessment with multi-criteria evaluation to support circular renovation strategies. This paper introduces an innovative framework that combines life cycle carbon assessment with multi-criteria decision analysis to identify and sequence circular renovation measures. The framework was applied to a residential case study in the Netherlands, using IES VE for operational carbon assessment and One Click LCA for embodied carbon assessment, with results evaluated using PROMETHEE multi-criteria analysis. Renovation measures were assessed based on operational and embodied carbon (including Module D), energy use intensity, cost, payback period, and disruption. The evaluation also introduced the embodied-to-operational carbon ratio (EOCR), a novel metric representing the proportion of embodied carbon, including Module D, relative to operational carbon savings over the building’s lifecycle. The homeowner’s preferences regarding these criteria were considered in determining the final ranking. The findings show that circular insulation options involving reused materials and designed for disassembly achieved the lowest embodied carbon emissions and lowest EOCR scores, with reused PIR achieving a 94% reduction compared to new PIR boards. The impact of including Module D on the ranking of renovation options varies based on the end-of-life scenario. The framework demonstrates how circular renovation benefits can be made more visible to decision-makers, promoting broader adoption.

Neurodegenerative diseases (NDs) are complex, multifaceted conditions that require novel, multi-targeted therapeutic approaches. This study aimed to develop a multifunctional polymer–drug conjugate (PDC) by employing a novel strategy of utilizing PDC-based nano-polyplexes as a multi-target treatment for NDs. The nano-polyplex (N5NM15) was formulated by combining polyallylamine hydrochloride-vanillin (NM15) and polyacrylic acid–naphthalimidohexylamine (N5) conjugates. Antioxidant capacity was measured via ORAC assay, and cholinesterase inhibition was evaluated using Ellman's assay. Cytotoxicity, neuroprotective effects, and anti-inflammatory activity were tested in undifferentiated SH-SY5Y and BV-2 cells via MTT assay. Amyloid-beta aggregation was assessed using Thioflavin T assay and TEM imaging in a cell-free system. The results demonstrated that N5NM15 resulted in uniform nanoparticles with an average size of 30.5 ± 7.9 nm, confirmed via cryo-TEM. Cytotoxicity studies indicated high biocompatibility with SH-SY5Y cells (viability >90%) and moderate toxicity in BV-2 cells (viability 75%, p ≤ 0.001). Furthermore, N5NM15 demonstrated significantly enhanced in vitro antioxidant activity (p ≤ 0.001, after adjustment) and cholinesterase inhibition (p ≤ 0.0001 for AChE and p ≤ 0.01 for BuChE, after adjustment) compared to starting materials. N5NM15 also protected SH-SY5Y cells from hydrogen peroxide-induced oxidative stress (p ≤ 0.0001), reduced lipopolysaccharide-induced inflammation in BV-2 cells (p ≤ 0.05), inhibited BuChE activity in SH-SY5Y cells (p ≤ 0.01), and reduced amyloid-beta aggregation (p ≤ 0.01). Notably, polyacrylic acid demonstrated protective and anti-inflammatory effects in both cell lines (p ≤ 0.0001) and inhibited amyloid-beta aggregation (P ≤ 0.001). These findings suggest the potential use of N5NM15 and polyacrylic acid as treatment options for NDs.

Introduction There is growing qualitative evidence that antenatal education on relaxation practices can enable women to deliberately induce a deep state of emotional calmness. Learning to shift focus from distressing emotions such as anxiety and fear to this altered state of calmness may significantly enhance women's confidence, thereby protecting maternal psychological wellbeing and leading to more positive childbirth experiences. However, the generalisability of these findings remains uncertain. This study aimed to bridge this gap by using quantitative methods to validate and extend the qualitative evidence. Methods Through an observational study with a prospective longitudinal cohort design, ninety-one women attending a single antenatal relaxation class at a Scottish NHS maternity service completed online surveys including Childbirth Self-Efficacy Inventory (CBSEI), Warwick Edinburgh Mental Well-Being Scale (WEMWBS), Wijma Delivery Expectancy/Experience Questionnaire (W-DEQ), and Six-item State-Trait Anxiety Inventory (STAI-6) at pre-class, post-class and post-birth. Results Findings indicated significant improvements in childbirth self-efficacy expectancy, mental wellbeing, fear of childbirth, and both trait and state anxiety after attending the class, and these improvements remained stable until 4–8 weeks after birth. Women widely reported using relaxation practices, with the majority perceiving a positive influence on their pregnancy and childbirth experiences. The majority also viewed their overall childbirth experiences as positive. Discussion Consequently, maternity services should consider reforming current antenatal education to align with these findings.

This article constitutes a Patient Perspective, grounded in lived experience, its primary aim is to enhance awareness of antidepressant-induced anhedonia by providing experience-based insights, relevant to clinicians, researchers, and caregivers. My own experiences with treatment-resistant depression-anxiety have been significant and long-lasting. In my 22-year-plus journey of illness experience—and having taken over 23 antidepressant medications—emotional-blunting, anhedonia, and mania have all, at times, been side-effect-related factors. This work explores the conundrum of antidepressant-induced anhedonia, developing an in-depth patient perspective useful for mental health practitioners, psychiatrists, psychologists, and for wider formal professional and informal nonprofessional caring actors. I write this via a reflexive lens as a long-term mental health patient, while also recognizing my dual-positionality as a Chartered Psychologist and an academic with a PhD working in the field of mental health. Thus, my dual-perspective provides a unique lens useful for translating the patient experience to a wider caregiving audience: fostering understanding and deepened awareness of the anhedonia experience. Implications for patient care are discussed.

Academic resilience is vital in students’ success, but its mechanisms in promoting academic well-being remain underexplored. This study investigated the direct effects of resilience on well-being, grit, and motivation and examined the mediating roles of grit and motivation in these relationships among Senior High School (SHS) students in Ghana. A descriptive correlational design was used, sampling 190 SHS students through stratified random sampling. Data were gathered using validated instruments for academic resilience (ARS-30), well-being (SSWQ), grit (AGS), and motivation (MSLQ). Partial Least Squares Structural Equation Modeling (PLS-SEM) analysed relationships and mediation effects, with bootstrapping (10,000 samples) employed for hypothesis testing. The analysis confirmed significant direct effects of academic resilience on grit (β = 0.518, p < 0.001), motivation (β = 0.479, p < 0.001), and well-being (β = 0.168, p = 0.022). Grit (β = 0.321, p < 0.001) and motivation (β = 0.356, p < 0.001) were significant predictors of well-being. Mediation analysis showed that grit (β = 0.166, p < 0.001) and motivation (β = 0.170, p < 0.001) partially mediated the relationship between resilience and well-being. This study underscores the significant role of academic resilience in enhancing students' well-being, with grit and motivation as key mediators. The findings suggest that fostering resilience, grit, and motivation can improve academic outcomes. Educational institutions should integrate strategies that promote these traits, such as resilience-building programs and mental health support. Policymakers are encouraged to prioritize initiatives that nurture these qualities to enhance students' academic success and well-being.

Aim Infant food insecurity (IFI) is a critical and often overlooked issue in high-income countries. This scoping review aims to identify and summarise interventions that reduce food insecurity or improve nutrition amongst families with infants in these regions. Subject and methods We searched the major electronic databases and websites of relevant UK and international organisations from 2010 to 2023 to identify reports written in English assessing food insecurity affecting infants (aged 0 to 2 years). The findings were presented in tables and summarised narratively. Results Out of 6194 records identified, 104 studies were screened, with only two studies meeting the inclusion criteria. Both studies were conducted in the USA. The KIND (Keeping Infants Nourished and Developing) intervention improved preventive care for food-insecure families, increasing lead level test completion rates and well-infant visits, but it did not affect weight-for-length at 9 months. The GWCC (Group Well-Child Care) intervention aimed at promoting responsive feeding amongst low-income caregivers but showed no significant impact on infant growth in the first year. However, caregiver interviews revealed important feeding-related themes. Conclusion Evidence on interventions addressing infant food insecurity is limited, with none found in the UK. The KIND and GWCC interventions showed mixed outcomes, improving some aspects of care but not significantly affecting infant growth metrics. These findings highlight the need for further research to develop more effective strategies to address the nutritional needs of vulnerable infants in high-income countries.

Background This study examines anecdotal reports from online discussion forums suggesting possible links between SSRI antidepressants and loss of lean muscle mass, particularly in men. Given limited existing scientific research, this study bolsters academic discourse. Objective Do self-reported experiences from internet forums indicate a perceived connection between SSRI use and muscle mass reductions? Method A Google keyword search identified 202 posts from 14 randomly selected online antidepressant discussion forums. Posts were collected and thematically analysed. Results Forum users reported difficulties in maintaining or gaining lean muscle after commencing SSRI treatment. Key themes included frustration, confusion, and attempts to rationalise perceived changes. Conclusion Findings suggest an area for further exploration, regarding the physiological impact of SSRIs on muscle composition. While reports remain anecdotal, they highlight concerns immediately relevant to both patients and healthcare professionals. As the study is based on self-reported experiences from anonymous sources, findings lack scientific validation but highlight requirements for further studies to explore prevalence and broader applicability. Research observations spotlight a need for further, structured clinical research to investigate possible effects of SSRIs on muscle mass. Future research should include controlled clinical trials and longitudinal studies to examine a potential association in more detail.

Correspondence-based Point Cloud Registration (PCR) is crucial for 3D visualization applications, especially in change detection. Most PCR models depend on precise initialization using a set of closest points to establish correspondences, a method that often fails due to random variations in point positions and the influence of outliers. The presence of noise and outliers significantly compromises the quality of initial correspondences, leading to inaccuracies in alignment. While some correspondence-prediction methods inspired by nonconvex techniques show promise, they remain sensitive to the underlying data structure and are not well-suited for complex scenarios involving dynamic point clouds. In this paper, we propose a new approach: the Correspondence Evolving Assistant Network (CEANet), a point transformer-inspired mechanism designed to enhance point cloud registration. Unlike existing methods, CEANet leverages a unique conditional correspondence-fitness function that dynamically assesses and prioritizes inliers, allowing for more robust and accurate correspondence predictions through context-aware random sampling of key points. This allows CEANet to generate accurate correspondence coordinates while effectively accounting for rotation and translation in the registration process. Additionally, the model prioritizes inliers, systematically disregarding outlier points to refine transformation calculations and update point cloud alignment. The iterative process gradually removes outliers until all points fit within a defined bounding box (bbx), ensuring robust performance even in challenging environments. Specifically, registering static-to-mobile point clouds is challenging due to temporal misalignment and varying viewpoints, but the received results are notable on SABRE and Kitti dataset. Extensive experiments proved that the proposed method produced competitive results with state-of-the-art methods, achieving accurate fitness performance of +5.18E+08 and +7.33E+04 on SABRE and Kitti, respectively, and the git https://github.com/Vladimyr23/SabreProject_code link.

An overrepresentation of athletes born earlier in the year compared with those born later in the year is known as the relative age effect (RAE). This is perceived to be due to physical selection bias which leads to higher degrees of exposure to coaching, physical training and competition at a younger age. Even with increasing knowledge and established interventions, clubs in Europe’s top leagues still present a strong RAE. Scottish clubs have limited resources in comparison meaning academy efficiency is paramount. The main study aim was to assess changes in the RAE over a ten-year period in Scottish soccer. A secondary aim was to establish if physical differences exist across each quarter due to findings in English academy players that maturation status and not RAE is the main discrepancy for physicality. A retrospective analysis of 512 players from a Scottish academy over a ten year period was granted ethical approval. The impact of relative age effect was assessed against anthropometric and physical characteristics. The range of players in each quarter was Q1 37.0–42.9% versus Q2 22.8–32.4%, Q3 11.9–26.0% and Q4 7.1–14.3% with no impact of time on RAE profiles. Odds Ratio analysis indicate a greater chance of selection within the academy when assessing Q1vsQ4 players quarter comparisons (ranging 3.2–5.2 times more likely to be signed). When controlling for age group, multilevel modelling showed there were no significant differences across quarters in physical measures with the exception of a trivial CMJ difference. The lack of progression in the RAE profiles is disappointing however presents an opportunity for increased efficiency. By viewing the RAE as an under representation of Q4 players and using established corrective procedures, this can contribute to the unnecessary release of players from academies due to RAE, thus addressing challenges in financially restricted environments that resource rich environments such as Europe’s elite have not yet overcome.

Although there are over 100,000 distinct human metabolites, their biological significance is often not fully appreciated. Metabolites can reshape the protein pockets to which they bind by COLIG formation, thereby influencing enzyme kinetics and altering the monomer–multimer equilibrium in protein complexes. Binding a common metabolite to a set of protein monomers or multimers results in metabolic entanglements that couple the conformational states and functions of nonhomologous, nonphysically interacting proteins that bind the same metabolite. These shared metabolites might provide the collective behavior responsible for protein pathway formation. Proteins whose binding and functional behavior is modified by a set of metabolites are termed an “entabolon”a portmanteau of metabolic entanglement and metabolon. 55%–60% (22%–24%) of pairs of nonenzymatic proteins that likely bind the same metabolite have a p-value that they are in the same pathway, which is <0.05 (0.0005). Interestingly, the most populated pairs of proteins common to multiple pathways bind ancient metabolites. Similarly, we suggest how metabolites can possibly activate, terminate, or preclude transcription and other nucleic acid functions and may facilitate or inhibit the binding of nucleic acids to proteins, thereby influencing transcription and translation processes. Consequently, metabolites likely play a critical role in the organization and function of biological systems.

Portland cement is the primary barrier material for well abandonment. However, the limitations of cement, especially under harsh downhole conditions, are necessitating research into alternative barrier materials. While several alternatives have been proposed, the screening process leading to their selection is scarcely discussed in the literature, resulting in the non-repeatability of the selection process. This study develops a dynamic multi-criteria decision-making technique for assessing the material options for the abandonment of high-pressure high-temperature (HPHT) wells with exposure to harsh reservoir fluids. The material screening process is performed in ANSYS Granta and a combined technique for order of preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) approach is used for ranking the shortlisted material alternatives based on seven material properties proven in the literature to be critical to the long-term integrity of well barrier materials. Nine alternative materials are ranked against Portland cement and high alumina cement. The results show that the top-ranking materials are from the phenol formaldehyde and polyamide–imide groups. Of these, the primary production CO2 of the polyamide–imide is, on average, about 25 times higher than the primary production CO2 of the phenol formaldehyde material. A sensitivity analysis of the methodology confirms that the criteria with the highest initial weights are the most impactful in terms of the final rank. The material property values also have an impact on the extent to which variations in their weights affect the hierarchical position of the materials in the TOPSIS-AHP analysis. Despite their higher cost per unit volume, the alternative materials consistently outperformed cement—even when average price was weighted more heavily than the most influential mechanical property.

We report here the upcycling of PET (polyethylene terephthalate) waste via semi-hydrogenation to make ethyl 4-(hydroxymethyl)benzoate. The reaction is catalysed by a ruthenium pincer catalyst at 80 °C in bio-derived solvents – a combination of 2-methyl THF and ethanol. A detailed mechanistic investigation through kinetic studies and chemical exchange saturation transfer (CEST) NMR spectroscopy provides insights into the nature of active species and factors that promote and inhibit the catalytic hydrogenation of PET. Using this mechanistic knowledge, a record high turnover number of > 30,000 was achieved. The semi-hydrogenation product, ethyl 4-(hydroxymethyl)benzoate, was utilised to make precursors of various known pharmaceutical drugs, an agrochemical, as well as a new and recyclable polyester.

People living with diabetes and food insecurity in high-income countries have poorer health-related outcomes than those who are food secure. Diabetes is a significant global health challenge. At the same time, the prevalence of household food insecurity continues to increase. This qualitative systematic review and synthesis explored the lived experience of diabetes self-management and support for self-management for people living with diabetes and food insecurity in high-income countries. Keywords and search terms were developed using the PICo framework with searches conducted between January 2008 and August 2024. Titles and abstracts were screened against inclusion and exclusion criteria, and the methodological quality of included papers was assessed using the Critical Appraisal Checklist for Qualitative Research and CERQual. Findings from 18 articles (detailing 17 studies) identified four interlinked themes: structural challenges, day-to-day challenges, ways of being for people living with food insecurity and diabetes, and self and support for self-management needs. Structural challenges (poverty, sociocultural and discrimination) were identified as the main determinants of the day-to-day challenges for people living with diabetes and food insecurity. Those challenges included the following: (i) limited access to suitable foods and food management resources; (ii) stress, (iii) poverty and diabetes stigma, (iv) limited informal support, (v) perceived lack of appropriate support from healthcare practitioners, and limited knowledge, confidence and understanding and access to information. The resulting ways of being for people affected were characterised by experiences of subsisting, avoiding, balancing and prioritising. Self and support for self-management needs were characterised by two themes improve[ing] clinical conversations and, support beyond health services. People living with diabetes and food insecurity are adopting methods of self-management, due to economic necessity, which may not be appropriate from a healthcare perspective, and which may be impacting their short and long-term health. There is an urgent need to address these issues in the post COVID-19 pandemic context for effective diabetes prevention and management.

The study investigated the relationships between students' grit, academic engagement, motivation and self‐regulated learning (SRL). It explored the mediating role of academic motivation and SRL in the relationship between students' grit and academic engagement. Understanding these dynamics can help educators foster environments that enhance student engagement through targeted interventions. A predictive correlational design was used to model the relationships among the variables. Stratified random sampling selected 190 senior high school students from the Kwahu Afram Plains District in Ghana. Data were collected using validated instruments: the University Student Engagement Inventory (USEI); Academic Grit Scale (AGS); Motivated Strategies for Learning Questionnaire (MSLQ); and Self‐Regulated Learning Scale (SRLS). Analysis was performed using partial least squares structural equation modelling to handle non‐normality in the data. The results indicated that academic grit positively influenced academic motivation (β = 0.631, p < 0.001), academic engagement (β = 0.320, p = 0.001) and SRL (β = 0.756, p < 0.001). Academic motivation and SRL partially mediated the relationship between grit and academic engagement. The model demonstrated strong reliability and validity, with significant indicator loadings and acceptable variance inflation factors, indicating no multicollinearity issues. Grit significantly impacts academic engagement directly and indirectly through academic motivation and SRL. These findings highlight the importance of fostering grit, motivation and self‐regulation in students to enhance their academic engagement. Hence, educators are encouraged to design cognitive‐behavioural interventions to promote these attributes in order to ultimately improve educational outcomes.

Estimating the battery’s state-of-charge (SOC) is essential for determining how safe electric cars are and their remaining range. An SOC estimation technique for lithium-ion batteries based on the Transformer architecture is presented in this paper. In order to effectively interpret the original data information, the variational mode decomposition (VMD) algorithm is applied to decompose the Panasonic datasets, enabling effective interpretation of the original data information by isolating intrinsic mode functions (IMFs) with distinct frequency characteristics. The decomposition state is then evaluated using the center-frequency method. After that, the Transformer is altered by giving the decoder more positional encoding. The problem of manually setting the network hyper-parameters in SOC estimation is finally resolved by optimizing the tuned Transformer neural network’s learning rate parameters, regularization coefficients, and the number of self-attention mechanism heads using the polar lights optimization algorithm. This optimization technique guarantees that the model can more successfully adjust to the varied data characteristics of particular application scenarios while maintaining Transformer-GRU’s benefits in terms of long-range dependency modeling and low computational cost. The accuracy, stability, and applicability of the method were verified through experimental comparison of various estimation methods, working conditions, and temperature conditions.

COVID-19 impacted globally, on individual health, care systems and social reproduction. Excessive death, lockdowns and social policy change had immediate and long-term national and global implications. Attention has been given to the immediate consequences, including its disproportionate impact on parts of society such as older people, “black” and “ethnic minorities”, and migrants. This raises questions for social work about wider enduring lessons including social inequality and globalisation. Reflecting across three countries, we encourage debate on future professional lessons, recognising constraints the pandemic has imposed and the dilemma of relying on historical precedents, of which we now find we have none.