This paper presents the results of the first qualitative empirical study on digital legacy and post-mortem privacy in the UK, shedding light on experiences, practices, perceptions, and limitations in the field. Our research confirms and extends existing theoretical and doctrinal work, validating key arguments, assumptions and ideas. The study unveils critical issues surrounding awareness, platform behaviours, and the limitations of current practices, exacerbated by the global impacts of the Covid-19 pandemic. Central to our findings is the overwhelming lack of awareness among users, practitioners, platforms, and regulators, highlighting a pressing need for increased engagement from the media, academics, and professional associations. The study identifies key drivers for change, emphasising the role of individual grief, high-profile cases, and technological advancements. Legal professionals, facing obstacles in the absence of clear regulations, exhibit leadership and creativity in addressing client needs, claiming a new expertise in the evolving field of digital legacy. Contrary to the clear call for law reform among practitioners, regulators acknowledge the growing importance but prioritise other areas, necessitating a cross-cutting reform approach. Concerns about platform cooperation, jurisdictional differences, and the inadequacy of existing solutions emerge, urging a re-evaluation of technological and in-service solutions, such as Facebook or Apple Legacy Contact. Education and media literacy are identified as pivotal components, addressing the broader landscape of digital legacy and privacy. Our findings underscore the urgent need for legal and policy reform, conceptual clarity, and a review of technological solutions. The study's impact extends beyond empirical evidence, informing subsequent research on user perceptions and guiding the development of policy and law reform proposals in the underexplored realm of digital legacy and post-mortem privacy.

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions.

ABSTRACT During the COVID-19 pandemic, governments relied on the police to enforce COVID-19 rules. However, little is known about police enforcement of these norms and use of discretion in this process. The current study draws on a sample of 3,866 police officers from 10 countries across the globe and examines officers’ use of discretion when encountering violations of COVID-19 rules. We assess the relative significance of factors such as the perceptions of community adherence to COVID-19 rules, assessments of the police agency’s support to deal with the pandemic, evaluations of COVID-19 seriousness, and psychological adjustments to the pandemic on police officers’ willingness to react when observing a COVID-19 violation. Our findings highlight the complexity of officer responses to violations of rules, which include not only enforcement actions such as giving advice and warning, issuing tickets, and making arrests, but also non-actions.

Corruption is a global problem in itself, and it presents a particular issue when it appears in the healthcare system. The healthcare system of every country is sensitive to corruption regardless of the level at which it occurs. The objectives of the research are: to determine the existence of documents that prevent corrupt activities in healthcare institutions; to ascertain whether the institution possesses Standard Operating Procedures that regulate the methods of employment and the inductionof new employees; and to examine the knowledge, attitudes, and practices of employees regarding the awareness of anti-corruption prevention mechanisms.The research is quantitative, exploratory, descriptive, cross-sectional, and comparative. Available strategicdocuments from institutions were used and analyzed. The research did not require financial costs and investments from the researchers. The results show that 39.4% of respondents believe that healthcare work workers take bribes, with 19.7% indicating that this occurs entirely, and 19.7% partially. Additionally, 51.2% of respondents stated they would report bribery if they had certain knowledge about it, with 45.7% indicating they would do so entirely, and 5.5% partially.

The aim of the current research was to investigate the association between plasma endocan levels and metabolic control parameters, as well as to evaluate its predictive value for clinical complications in patients with type 2 diabetes mellitus (DMT2). A total of 100 DMT2 patients participated in this prospective observational study. Plasma endocan levels were significantly elevated in DMT2 patients with HbA1c > 7% (1.38 ± 0.33 vs 0.68 ± 0.23 ng/mL; P < 0.0001), compared to patients with HbA1c ≤ 7%. Patients with plasma endocan concentrations >1.10 ng/mL (median value of 1.10 ng/mL) demonstrated significantly higher levels of metabolic parameters: body mass index (BMI), HbA1c (%), fasting glucose level, LDL cholesterol, total cholesterol, triglycerides, along with significantly lower HDL cholesterol levels. Furthermore, patients with plasma endocan levels >1.10 ng/mL were found to have an increased risk for the following complications: retinopathy (relative risk [RR]: 2.7500; 95% confidence interval [CI]: 1.2150–6.2244; P ═ 0.0152, nephropathy (RR: 2.0952; 95% CI: 1.2294–3.5710; P ═ 0.0065), neuropathy (RR: 1.9945; 95% CI: 1.2025–3.3081; P ═ 0.0075), angina pectoris (RR: 2.4881; 95% CI: 1.0865–5.6979; P = 0.0311, hypertension (RR: 1.1372; 95% CI: 1.0060–1.2856; P = 0.0398), cardiomyopathy (RR: 2.6190; 95% CI: 1.1507–5.9612; P = 0.0218), myocardial infarction (RR: 9.4286; 95% CI: 1.2742–69.7697; P = 0.0280) and stroke (RR: 4.4638; 95% CI: 1.3765–14.4758; P = 0.0127). Correlation analysis revealed that plasma endocan levels were positively correlated with HbA1c (%) (r ═ 0.856, P < 0.0001), fasting glucose level (r ═ 0.631, P < 0.0001), LDL (r ═ 0.347, P ═ 0.0004), cholesterol (r ═ 0.282, P ═ 0.0045), and triglycerides (r ═ 0.366, P ═ 0.0002). Conversely, plasma endocan levels were negatively correlated with HDL cholesterol (r ═ −0.429, P < 0.0001). In conclusion, higher plasma endocan levels were strongly associated with poor metabolic control in DMT2 patients and exhibited significant predictive value for both microvascular and macrovascular complications.

With the rapid growth of electric vehicle (EV) production, efficient battery life cycle management has become increasingly critical, especially as the demand for second-life battery applications is mandated considering environmental aspects. The European Union's introduction of battery passports, aimed at enhancing battery traceability, presents new challenges for existing Battery Management Systems (BMS). The proposed solution of QR code tracking shows drawbacks when addressing scalability, local real-time monitoring, and data security concerns. Our work implements RFID technology as an extension of modular BMS architectures designed to meet the evolving requirements of battery passports and second-life battery use cases. By integrating NFC tags and leveraging this technology, the system enables secure, real-time data transmission between battery pack components and external readers, overcoming the limitations of QR codes. A demonstrator setup based on automotive-grade components validates the system's capability to monitor static and dynamic key battery parameters. The proposed solution offers a forward-looking approach to battery management, aligning with upcoming regulatory requirements while advancing the adoption of second-life battery management.

Sensitivity analyses are frequently performed to determine the robustness of MCDM methods, of which there are more than 200 types. In the past, rankings were compared to each other rather than to an external ranking. Thus, the direction and meaning of sensitivity can become unclear and complex. In addition, sensitivity analysis is usually performed only based on weight coefficients, but the effect of the normalization type is neglected. In this study, the most appropriate data conversion technique was investigated through an innovative sensitivity procedure to select the e-Small Van, which is an environmentally friendly logistics and transportation vehicle. Seven different normalization types based on the PROBID method (and two additional alternative MCDM methods) were used as parameters, resulting in 105 different MCDM rankings. According to the findings, MCDM rankings, which have low sensitivity, were also the performing methods that produced the highest correlation with price. What is striking is that careless choice of normalization type can be so effective as to manipulate the results. Although the most appropriate technique may vary depending on the data type, the fixed gold standard we recommend offers a flexible solution for all applications. A suitable data converter will result in the choice of a reliable electric vehicle.

AI potential to recolonise language practices by reproducing existing marginalisations in novel ways has already instilled fears of a ‘contemporary dystopia’ (Miras et al., 2022) — a space of cultural and linguistic erasure. Accents represent a distinctive aspect of language practice associated with one’s sociocultural, and ethno-racial characteristics. They account for one’s social identity, status, and proficiency (De Klerk & Bosch, 1995). This makes practices of artificially modifying accents particularly concerning, since they play into the ‘zero’ accent ideology. As a result, any deviation from the norm is marked as abnormal or deficient, and in need of, artificial correction. Using AI accent generators, therefore, has the capacity to further aggravate power inequalities between the linguistically privileged and underprivileged, and to encourage changes in self-representation towards what is perceived as the normative Standard. Artificial modification of self to match a desired representation is not new, given the long-standing discussions on digital image alterations and their negative relationships to self-perceived attractiveness (Ozimek et al., 2023). This conceptual paper explores the (re)colonial and subversive linguistic potential of AI accent generators through the lens of the social tendency of individuals to strive to meet a given Standard. Using the notion of ‘technologies of the self’ (Foucault, 1988), we draw a parallel between self-perceived attractiveness of bodies and accents, to explain how artificial modifications do not straightforwardly support diversities, but instead encourage ‘self-corrections’ in line with those standardized sets of features which seem to promise a ‘better’ socioeconomic and educational standing within neoliberal societies.

Self-supervised foundation models for digital pathology encode small patches from H\&E whole slide images into latent representations used for downstream tasks. However, the invariance of these representations to patch rotation remains unexplored. This study investigates the rotational invariance of latent representations across twelve foundation models by quantifying the alignment between non-rotated and rotated patches using mutual $k$-nearest neighbours and cosine distance. Models that incorporated rotation augmentation during self-supervised training exhibited significantly greater invariance to rotations. We hypothesise that the absence of rotational inductive bias in the transformer architecture necessitates rotation augmentation during training to achieve learned invariance. Code: https://github.com/MatousE/rot-invariance-analysis.

The rapid advancement of Large Language Models (LLMs) has transformed natural language processing, yet comprehensive evaluation methods are necessary to ensure their reliability, particularly in Retrieval-Augmented Generation (RAG) tasks. This study aims to evaluate and compare the performance of open-source LLMs by introducing a rigorous evaluation framework. We benchmark 20 LLMs using a combination of established metrics such as BLEU, ROUGE, BERTScore, along with and a novel metric, RAGAS. The models were tested across two distinct datasets to assess their text generation quality. Our findings reveal that models like nous-hermes-2-solar-10.7b and mistral-7b-instruct-v0.1 consistently excel in tasks requiring strict instruction adherence and effective use of large contexts, while other models show areas for improvement. This research contributes to the field by offering a comprehensive evaluation framework that aids in selecting the most suitable LLMs for complex RAG applications, with implications for future developments in natural language processing and big data analysis.

BACKGROUND Limited joint mobility is the proven risk factor for diabetic foot ulceration when present in the subtalar and first metatarsophalangeal joints. Evidence shows that a foot-related exercise program, combined with a health-promoting program, can improve the signs and symptoms of diabetic polyneuropathy, enhance gait, restore mobility in the foot and ankle joints, redistribute pressure while walking, and increase foot strength and function. As a result, these exercise programs can help mitigate the risk factors for diabetic foot ulceration. AIM To determine the effect of supervised stretching, strengthening, functional and walking exercises on joint mobility and muscle strength in patients with diabetic polyneuropathy. METHODS This was a randomized controlled trial conducted in a tertiary hospital. The study included 82 participants allocated into the intervention group (alpha-lipoic acid and exercise on 15 consecutive therapeutic days, n = 42) and control group (alpha lipoic acid only, n = 40). Muscle strength included dorsal and plantar flexors dynamometry and strength score, while range of motion included ankle, subtalar and first metatarsophalangeal joint goniometry. RESULTS Change of motion range was significantly higher in the intervention group compared to the control group regarding ankle joint on day 15 (9.9 ± 7.2 vs 0.1 ± 3.3; P = 0.006) and month 6 (2.8 ± 7.3 vs -0.9 ± 4.1; P < 0.001), subtalar joint on day 15 (7.5 ± 5.1 vs -0.25 ± 2.25; P < 0.001) and month 6 (3.9 ± 6.4 vs -0.13 ± 3.49; P < 0.001). Change in dorsal flexors was significantly higher in the intervention group compared to the control group on day 15 (2.62 ± 1.69 vs 0.10 ± 1.35; P < 0.001) and month 6 (0.66 ± 2.38 vs -0.75 ± 1.94; P = 0.004) as well as plantar flexors on day 15 (3.3 ± 1.6 vs 0.3 ± 1.5; P < 0.001) and month 6 (1.8 ± 2.2 vs -0.9 ± 2.1; P < 0.001). Muscle strength score change was significantly lower in the intervention group compared to the control group on day 15 (-1.45 ± 1.42 vs -0.03 ± 0.16; P < 0.001) and month 6 (-1.17 ± 1.53 vs 0.20 ± 0.56; P < 0.001). CONCLUSION Exercise in combination with alpha-lipoic acid can improve joint mobility, as well as strength of the foot and lower leg muscles in patients with diabetic polyneuropathy.