Buildings constructed prior to the implementation of seismic design standards or those built based on lower standards are susceptible to earthquake risks, resulting in substantial loss of life and property during an imminent earthquake. Although conventional rapid visual screening (RVS) methods have been extensively developed, both nationally and in the literature, they have limitations in accurately determining the vulnerability of buildings. Additionally, RVS methods developed on the basis of a single algorithm have limitations. Therefore, this study extends the existing body of work by integrating multiple AI algorithms, including fuzzy logic, machine learning, and neural networks, in the context of building damage data from the 2015 Gorkha earthquake, overcoming the limitations of previous studies by introducing an automated AI-based RVS methodology that enhances accuracy, transparency, and adaptability. The newly developed RVS method demonstrates an accuracy rate of 45.89% for testing in the three-class classification, while also delivering promising results in the two-class classification, with an accuracy rate of 60%, surpassing both conventional RVS methods and the baseline accuracy rate.

The purpose of this study is to examine value elements related to hybrid electric vehicles and their impact on consumers’ brand-related (brand identification) and corporate-related (corporate image) responses, which are expected to influence buying intention. Data was collected from 294 owners of hybrid electric vehicles in South Korea and analyzed using PLS-SEM and NCA (necessary condition analysis). The study finds that all four elements of value have a significant impact on either brand identification or corporate image. The study shows that brand identification and corporate image predict buying intention. Brand identification is found to play a mediating role in the relationship between aesthetic value and corporate image and between eco-friendliness and corporate image. The study finds that corporate image mediates the relationship between brand identification and buying intention. The study contributes to the understanding of the psychological process that explains buying intention of the hybrid electric vehicle (HEV) users.

The spatial distribution of tourism attractions plays an important role in shaping visitor travel behaviour, accessibility to tourism locations, and tourist destination management and planning. This study examines the spatial patterns of tourism attractions in Luxor Governorate, Egypt, and the factors influencing these spatial relationships using a variety of geospatial analysis techniques. These techniques include Nearest Neighbour Index (NNI), Standard Deviational Ellipse (SDE), Kernel Density Estimation (KDE), and Local Moran’s I. In addition, a combination of the Analytic Hierarchy Process (AHP) and Geodetector were applied to determine which of sixteen identified factors influenced the distribution of tourist attractions in Luxor. Finally, the spatial relationships between the identified factors and the distribution of tourist attractions were analysed through the use of Multiscale Geographically Weighted Regression (MGWR). The results show that there is a strong clustering of tourism attractions in Luxor within three main hubs: Luxor City (East Bank), Qurna (West Bank), and Esna. The results further indicate that the most influential factors influencing the distribution of tourist attractions in Luxor include regional services centrality, GDP index, proximity to urban centres, tourism workforce localisation, urbanisation level, and environmental quality, respectfully. The implications of this research provide practical applications for developing more sustainable and balanced tourism development strategies in heritage-rich regions such as Luxor.

A multitude of interventions have been designed to tackle doping in sport. Despite significant advances in understanding the role of motivation, the environment, policies and education in addressing doping, there is a lack of nuanced knowledge concerning the design and implementation of these interventions. The present study adopted an intervention mapping evaluation perspective, critically evaluating a selection of 12 antidoping programs across three sports in Austria, Russia, South Africa, and the United Kingdom, using a mixed-methods, sequential, explanatory design. Findings confirm that the antidoping intervention landscape is diverse and complicated, incorporating multiple strands, sites, ambitions and stakeholders. It also suggests that the drive for policy compliance led by WADA has promoted considerable isomorphism across diverse cultural and economic communities and sports. Antidoping educational interventions appear to have been informed more by the moral imperatives for clean and fair sport rather than sound theoretical bases. While the theoretical basis on which most interventions were based can operate across culturally and economically divergent contexts, this is undermined by differences in their interpretation and the context of their implementation. Several lacunae in the design and implementation of antidoping interventions are also identified and discussed.

Traditional one size fits all pharmacotherapy often yields suboptimal clinical outcomes, preventable adverse drug reactions (ADRs), and significant drug waste, imposing substantial economic and ecological burdens on healthcare systems. This review evaluates the transformative potential of pharmacogenomics (PGx) testing, particularly cytochrome P450 (CYP) gene variants, as a foundation for an ecosystem-centric accountability framework for green pharmacy and links human metabolic variability to specific environmental outcomes. Personalized CYP profiling is shown to minimize the environmental release of unused drugs and potentially ecotoxic metabolites into aquatic ecosystems, in contrast to standard uniform drug use approaches. The limitations of ethnicity-based dosing models, which rely on population genetic variation, are examined in the context of increasing global genetic admixture. It is argued that individual genetic profiling, conceptualized as a PGx-Green Passport, provides a reliable safety standard that accounts for individual differences, thereby enhancing efficiency and well-being in a globalized society. By integrating clinical data, including real-world evidence on hospital utilization, with sustainability frameworks, this review demonstrates that PGx-guided therapy is not only a tool for clinical efficiency but also a fundamental requirement for systematically achieving environmentally sustainable healthcare.

Background/Objectives: The aim of this study was to describe seasonal trends in match-average External Load (EL) variables across three (2022/23, 2023/24, 2024/25) consecutive competitive seasons in a Hungarian professional second-division soccer team (Gyirmót FC Győr), using the Catapult Vector S7 Global Navigation Satellite System (GNSS). Specifically, Average Distance (AD; m), Average Player Load^TM (PL; AU), and Acceleration–Deceleration Efforts (>2 m·s⁻²) (ADE) were examined. The study aimed to provide descriptive reference values and characterize seasonal variation in match EL demands within a professional second-division context. Methods: A descriptive seasonal comparison was conducted based exclusively on aggregated match average EL values. The unit of analysis was the match, with each match contributing one aggregated value per variable derived from players who completed the full match. A total of 94 matches were included (2022/23: N = 38; 2023/24: N = 29; 2024/25: N = 27); matches with red cards were excluded. EL data were collected using a 10 Hz Catapult Vector S7 GNSS. Results: The median AD decreased continuously from the 2022/23 season (10.210 m) to the 2024/25 season (9.795 m). The median PL decreased from 1002 (2022/23 and 2023/24) to 846 in the 2024/25 season. The median ADE decreased from 220.8 (2022/23) to 199.0 (2024/25). Conclusions: Lower values were observed across match EL variables, with the most pronounced reduction in PL. These findings provide descriptive reference values and may support the interpretation of seasonal variation in match EL demands in professional second-division soccer.

Background: Lower respiratory infections (LRIs) remain the world's leading infectious cause of death. This analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 provides global, regional, and national estimates of LRI incidence, mortality, and disability-adjusted life-years (DALYs), with attribution to 26 pathogens, including 11 newly modelled pathogens, across 204 countries and territories from 1990 to 2023. With new data and revised modelling techniques, these estimates serve as an update and expansion to GBD 2021. Through these estimates, we also aimed to assess progress towards the 2025 Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea (GAPPD) target for pneumonia mortality in children younger than 5 years. Methods: Mortality from LRIs, defined as physician-diagnosed pneumonia or bronchiolitis, was estimated using the Cause of Death Ensemble model with data from vital registration, verbal autopsy, surveillance, and minimally invasive tissue sampling. The Bayesian meta-regression tool DisMod-MR 2.1 was used to model overall morbidity due to LRIs. DALYs were calculated as the sum of years of life lost (YLLs) and years lived with disability (YLDs) for all locations, years, age groups, and sexes. We modelled pathogen-specific case-fatality ratios (CFRs) for each age group and location using splined binomial regression to create internally consistent estimates of incidence and mortality proportions attributable to viral, fungal, parasitic, and bacterial pathogens. Progress was assessed towards the GAPPD target of less than three deaths from pneumonia per 1000 livebirths, which is roughly equivalent to a mortality rate of less than 60 deaths per 100 000 children younger than 5 years. Findings: In 2023, LRIs were responsible for 2·50 million (95% uncertainty interval [UI] 2·24–2·81) deaths and 98·7 million (87·7–112) DALYs, with children younger than 5 years and adults aged 70 years and older carrying the highest burden. LRI mortality in children younger than 5 years fell by 33·4% (10·4–47·4) since 2010, with a global mortality rate of 94·8 (75·6–116·4) per 100 000 person-years in 2023. Among adults aged 70 years and older, the burden remained substantial with only marginal declines since 2010. A mortality rate of less than 60 deaths per 100 000 for children younger than 5 years was met by 129 of the 204 modelled countries in 2023. At a super-regional level, sub-Saharan Africa had an aggregate mortality rate in children younger than 5 years (hereafter referred to as under-5 mortality rate) furthest from the GAPPD target. Streptococcus pneumoniae continued to account for the largest number of LRI deaths globally (634 000 [95% UI 565 000–721 000] deaths or 25·3% [24·5–26·1] of all LRI deaths), followed by Staphylococcus aureus (271 000 [243 000–298 000] deaths or 10·9% [10·3–11·3]), and Klebsiella pneumoniae (228 000 [204 000–261 000] deaths or 9·1% [8·8–9·5]). Among pathogens newly modelled in this study, non-tuberculous mycobacteria (responsible for 177 000 [95% UI 155 000–201 000] deaths) and Aspergillus spp (responsible for 67 800 [59 900–75 900] deaths) emerged as important contributors. Altogether, the 11 newly modelled pathogens accounted for approximately 22% of LRI deaths. Interpretation: This comprehensive analysis underscores both the gains achieved through vaccination and the challenges that remain in controlling the LRI burden globally. Furthermore, it demonstrates persistent disparities in disease burden, with the highest mortality rates concentrated in countries in sub-Saharan Africa. Globally, as well as in these high-burden locations, the under-5 LRI mortality rate remains well above the GAPPD target. Progress towards this target requires equitable access to vaccines and preventive therapies—including newer interventions such as respiratory syncytial virus monoclonal antibodies—and health systems capable of early diagnosis and treatment. Expanding surveillance of emerging pathogens, strengthening adult immunisation programmes, and combating vaccine hesitancy are also crucial. As the global population ages, the dual challenge of sustaining gains in child survival while addressing the rising vulnerability in older adults will shape future pneumonia control strategies. Funding: Gates Foundation.

This work presents a case study detailing an end-to-end workflow for reconstructing a damaged plastic component when no original design data are available. The approach integrates microscopic inspection of fracture surfaces, selective enhancement of 3D scan data, CAD-based modification of geometrically and functionally critical features, and continuous fibre-reinforced additive manufacturing. The component examined functions as a structural mounting element in an automotive lighting module, where it maintains correct alignment and provides mechanical support in service. The study concentrates on the cost-effective replacement of unique parts produced in very small batches. The results indicate that this fracture-analysis-informed reverse engineering strategy offers a practical solution for reproducing low-volume, custom, or replacement components in situations where standard manufacturing methods are not economically viable. The reconstructed part matched the geometry necessary for installation in the original assembly and successfully passed initial functional checks; however, this study did not include quantitative measurements of mechanical performance.

Background/Objectives: Cervical cancer remains a global health burden. The loop electrosurgical excision procedure (LEEP) is effective for cervical intraepithelial neoplasia. Positive margins often complicate decisions about repeat conization. HPV testing is standard in post-treatment surveillance, but its limited specificity shows the need for additional, cost-effective biomarkers. This study evaluated whether changes in systemic inflammatory indices—platelet-to-lymphocyte ratio (PLR), systemic inflammation response index (SIRI), and systemic immune-inflammation index (SII)—can predict residual high-grade lesions after incomplete excision. Methods: This multicenter retrospective study included 125 patients who underwent repeat surgery after LEEP due to positive margins. Changes in preoperative inflammatory indices (ΔPLR, ΔSIRI, ΔSII) between the first and second procedures were analyzed by the histopathological findings of the second surgery. Group differences were assessed using the Mann–Whitney U test, and receiver operating characteristic (ROC) analysis was used to evaluate discriminatory performance. Results: Significant differences were found in ΔPLR (p = 0.032) and ΔSII (p = 0.048) between patients with and without residual high-grade lesions or invasive cancer. ΔSIRI showed borderline significance (p = 0.050). For invasive cancer alone, ΔSIRI was significantly associated with malignancy (p = 0.035). ROC analysis showed modest predictive performance (AUC ≈ 0.60). Conclusions: Dynamic changes in PLR, SIRI, and SII may be as inexpensive adjunct biomarkers to support risk stratification after incomplete LEEP and can complement HPV testing in certain clinical settings.