For reducing adverse impact, the diversity-validity tradeoff curve approach (De Corte et al., 2007) provides sets of selection predictor weights that can often substantially enhance diversity (i.e., increase adverse impact ratio and number of minority job offers), with no loss of job performance in comparison to unit weights (Wee et al., 2014). A key limitation of this diversity-enhancing approach is the tendency for tradeoff curves to shrink, leading to lesser job performance and diversity outcomes upon cross-validation (Song et al., 2017). The current article evaluates and compares tradeoff curve shrinkage (both validity shrinkage and diversity shrinkage) using three types of validity evidence/calibration studies: (a) a local validity study, (b) a meta-analysis (Schmidt & Hunter, 1977), and (c) a Bayes analysis with empirical priors, which is a weighted combination of a local study with a meta-analysis (Newman et al., 2007). Using simulation, we show conditions where each approach performs best, offering recommendations on ideal methods for diversity improvement (reducing shrinkage and maximizing cross-validity) in local selection settings. Results guide selection practitioners in novel methods (integrating the advantages of meta-analysis, Bayes analysis, and Pareto-optimal weighting) to best combine predictors to simultaneously achieve job performance and diversity objectives in local selection settings. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

The medical expert witness plays a crucial role in providing objective, informed opinions that can influence the outcome of court trials and disciplinary proceedings. It is critical for physicians and surgeons with specialised knowledge in the local setting to provide relevant opinions to ensure fair and consistent outcomes when medical disputes occur in Singapore. This commentary draws from the author’s experience to highlight common errors and potential pitfalls which doctors may face in their capacity as an expert witness.

Several methods have been developed to identify marker genes that delineate cell populations in single-cell transcriptomic data, yet most emphasize enrichment within candidate populations without testing whether expression is significantly reduced outside those populations. We present Locat, a framework for identifying highly specific localized genes by testing whether expression is concentrated within compact regions of the cellular embedding and depleted elsewhere. For each gene, Locat fits weighted Gaussian mixture models to gene-specific and background densities, computes test statistics for concentration within compact regions and depletion outside those regions, and integrates the results into a unified localization score. Across synthetic benchmarks with controlled ground truth, Locat detects localized genes spanning uni-modal, multi-modal, and sparse expression patterns, and appropriately loses significance when simulated expression becomes indistinguishable from background structure. In biological datasets spanning developmental, perturbation, and differentiation contexts, Locat identifies compact marker sets that capture lineage organization, condition-specific programs, and temporal regulatory dynamics. Localized gene sets are often smaller than conventional feature selections such as highly variable genes, and embeddings constructed from localized gene sets tend to preserve separation of major cell populations and developmental programs. In murine dermis, embeddings computed using localized genes preserve differentiation and cell-cycle trajectories observed in the full dataset. In interferon- β -treated PBMCs, independent localization analysis of control and stimulated samples reveals stimulus-responsive programs and markers of shared immune populations without requiring batch correction or data integration. In retinoic acid-induced embryonic stem cell differentiation, localized genes exhibit reproducible stage-specific patterns across time points. Together, these results demonstrate that jointly assessing concentration and depletion yields specific, interpretable marker genes that enable direct cross-condition and multi-sample comparisons of marker genes across diverse biological settings.

Testing the national guidelines for pyelonephritis against the local setting in a Belgian secondary care emergency department

ABSTRACT The concept of the Twin Transition (TT) – the integration of green and digital transitions – has evolved from a loosely linked policy idea – especially in the EU’s post-COVID-19 recovery agenda – to an emerging topic in academic research. TT research has grown rapidly, focusing on the enabling role of digital technologies in addressing climate challenges and on the environmental impacts of digitalization. Recently, academic interest has turned toward an underexplored aspect: TT’s regional geography. Emerging evidence indicates that the development and adoption of green and digital technologies are shaped by regional characteristics, including local capabilities, institutional settings, and path dependencies. However, systematic understanding of these geographical dimensions remains limited. This paper addresses that gap through a bibliometric analysis of TT-related research with spatial relevance. Using network analysis and bibliographic coupling, the study identifies key research trends, clusters, and gaps. Findings show a fragmented but fast-growing field, with both qualitative and quantitative approaches offering insights across spatial scales. Patterns of scientific output suggest a ‘success-breeds-success’ dynamic, particularly in ICT-strong regions. The paper underscores the importance of place-sensitive policies and localized knowledge in shaping the TT and offers a roadmap for future research into how regional factors mediate this dual transformation.

How to bring nurse-led eHealth symptom monitoring in daily care: the Belgian SMILe integrated care model for allogeneic stem cell transplantation adaptation project.

This study examines the effect of green financial literacy on green accounting and tests whether social corporate social responsibility (CSR) strengthens that relationship among MSMEs in Baubau City. The study addresses a gap in prior research, which has mostly discussed financial literacy, environmental accounting, and CSR separately, or has focused on large firms rather than MSMEs in a local emerging-economy setting. A quantitative explanatory design was employed. One hundred questionnaires were collected from MSME owners or managers through purposive sampling, and 86 valid responses were retained after data screening. The instrument measured green financial literacy, green accounting, and social CSR using a five-point Likert scale. Data were analysed with descriptive statistics, classical assumption tests, simple regression, and moderated regression analysis using SPSS 16. The findings show that green financial literacy has a positive and significant effect on green accounting. Social CSR also moderates the relationship, indicating that literacy is translated into greener accounting practices more effectively when MSMEs are supported by socially oriented CSR programmes such as mentoring, training, and business assistance. The study contributes by offering an integrated model that links internal capability and external institutional support in explaining green accounting adoption among MSMEs. Practically, the results imply that local governments, firms implementing CSR, and MSME support institutions should integrate green finance education with sustainability-oriented empowerment programmes

Objective Structured Clinical Examinations (OSCEs) are widely used to assess clinical competence in health professions education. Although OSCEs are considered reliable and objective, their educational impact largely depends on the quality of feedback provided. Objective: To evaluate the faculty perceptions regarding OSCE feedback practices in local institutional settings. Methods: This descriptive cross-sectional study was conducted at Bashir Institute of Health Sciences, Islamabad, from January 2025 to June 2025. A total of 110 faculty members involved in OSCE conduction and evaluation were recruited using non-probability consecutive sampling. Data were collected using a structured, self-administered questionnaire developed using expert opinion and feedback from the literature, addressing demographic characteristics, perceptions of OSCE feedback, preferred feedback practices, and perceived barriers. Data were analyzed using SPSS version 26.0 with descriptive statistics and the Pearson Chi-square test. Results: The mean age of participants was 43.37 ± 8.17 years, with females comprising 52.7% of the sample. Most faculty agreed that feedback is essential for student learning (60.0%) and improves clinical competence (84.5%). Immediate feedback was preferred by 52.7% of participants, while written (33.6%) and one-to-one (31.8%) methods were most favored. Lack of formal training (57.3%), large student numbers (43.6%), and stressful OSCE environments (42.7%) were identified as key barriers. No significant associations were observed between overall perception of feedback and faculty characteristics. Conclusions: Faculty members value feedback in OSCEs but face practical challenges that limit its effective delivery. Focused faculty development and institutional support are needed to enhance feedback quality.

The aim of this study is to develop a valid and reliable measurement tool to assess athletes’ perceptions of sport technologies and their level of digital adaptation. The research was designed as a methodological, cross-sectional scale development study based on the Technology Acceptance Model. The sample consisted of 730 athletes aged between 18 and 25 who actively participated in organized sports activities. Of the participants, 47.3% were female and 52.7% were male. Participants were recruited from university sport environments and local training settings where sport technologies such as wearable monitoring devices, training applications, and digital performance tracking systems are regularly used. To examine construct validity, the dataset was divided into two independent subsamples. Data from 300 athletes were used for Exploratory Factor Analysis, and data from 430 athletes were used for Confirmatory Factor Analysis. The analyses revealed a two-factor structure: Perceived Technological Support and Digital Adaptation. The model demonstrated satisfactory validity and reliability. The findings indicate that the scale can be used to evaluate athletes’ performance-related perceptions of sport technologies and their ability to adapt to digital systems in training environments. The scale may provide a practical assessment tool for researchers, coaches, and sport organizations in the integration of technology into sport practice.

<p class="ql-align-justify">This study performs a semiotic-comparative literary analysis of contemporary climate fiction, utilizing ecosemiotics and cultural theory as frameworks. The research investigates the encoding of crisis indicators and planetary narratives across several semiospheres, concentrating on Kim Stanley Robinson’s <em>The Ministry for the Future</em> and Ghassān Shibārū 2022. The analysis employs Lotman’s semiosphere theory and Maran’s ecosemiotic typology to elucidate how symbolic, iconic, and indexical signs establish ecological significance, ethical responsibility, and cultural opposition. Robinson’s technocratic optimism converts nature into instruments for policy and systemic improvement, whereas Shibārū’s urban approach highlights grassroots involvement and deep melancholy. Prominent themes, including temporal disruption, stillness, and ecofeminist embodiment, act as ecosemiotic markers of both decline and resistance. Research demonstrates that climate fiction mirrors environmental disasters while concurrently reshaping cultural frameworks of compassion, recollection, and ecological responsibility in both global and local settings. Additionally, climate fiction conveys ecological themes through culturally particular semiotic frameworks. Robinson used symbolic and technical indicators (e.g., “carbon money”) to demonstrate systemic reform, while Shibārū utilizes indexical and iconic markers (e.g., polluted rivers) to inspire visceral pain and resistance.</p>

development (ESD) into music teacher education using the Green Songs Project, an undergraduate service-learning project in a music education module. Seven pre-service music teachers (PSMTs) composed and taught original environmental songs to pre-schoolers to foster ecological awareness through music. In this qualitative case study, I analysed the PSMTs’ journal reflections on the project, my observations, and our discussions exploring their experiences and the meanings they ascribed to writing and teaching green songs to pre-schoolers. We also discussed how the project could promote music education for sustainable development (MESD) in an early childhood setting. Five themes were generated, indicating that MESD can be promoted by 1) using movement and song to teach and learn about conservation; 2) integrating a mixture of excitement, laughter, and enthusiasm; 3) creating opportunities to make the world a better place to live in; 4) remembering things that impact our lives and 5) developing consistent, encouraging teaching strategies to foster learning and development for MESD. Findings show that creating and teaching culturally relevant green songs empowered PSMTs to connect global sustainability goals to local early childhood settings. The project demonstrates music’s potential as a transformative medium to support sustainability by fostering environmental awareness, social cohesion, and cultural appreciation in an early childhood setting. Key aspects include using song to explore nature, developing empathy through collaborative music-making, and teaching ecological responsibility while promoting creativity, sensory awareness, and emotional expression. Embedding ESD in music education can cultivate and equip educators with transferable, interdisciplinary skills to inspire sustainable thinking from the earliest years.

Healthcare professionals in Norwegian local hospitals have focused on the need for improved trauma care since the late 1990s. Because of lack of national guidelines the hospital management of patients with serious trauma varied. The authors and colleague health care providers felt a need for improvement. Therefore, a project called Better & Systematic Trauma care (BEST) was established. The goal was to improve trauma care through training and preparation for infrequently occurring situations, with a focus on the team. The project began as a bottom-up initiative in four local hospitals. Through cross-professional team training and local simulation, staff built competence in trauma care and practised non-technical skills such as communication, cooperation, leadership, and decision-making in their local setting. Creating a national meeting place for all hospitals was essential for fostering collaboration across institutions. A 1-day team course was developed and adopted nationwide. Network meetings have enabled the collaborative development of tools and training materials without national strategic leadership or external influence. Over time, the focus shifted from individual professions to the trauma team. A damage-control surgery course was created for all surgical teams. All materials remained freely available, and the project operated independently of the government, organisations, or industry. The BEST Project showed that local bottom-up initiatives can effectively improve clinical care. Facilitating professional interaction based on local needs is essential. The project also illustrates how a small, locally driven quality improvement effort can be scaled nationwide.

Abstract This article studies the itinerant life and professional activities of a mid-level calligrapher translator-poet of the later Ilkhanid period. The only contemporaneous information concerning Muḥammad b. Saʿd Nakhjavānī, known as Ibn al-Sāvajī (d. after 732/1332), lies in the manuscripts that he copied and the translations that he completed (or that were imputed to him). These materials suggest the profile of a scholar-intellectual active principally in local settings rather than at the level of the imperial administration or in the period’s leading scriptoriums. Among the features that emerge from a study of Ibn al-Sāvajī’s productivity are his mobility, his north-western Iranian familial background, his cultivation of diverse intellectual interests, his conspicuous Arabic and Persian bilingualism, and the indeterminate nature of his religious allegiance. In many of these respects, his life and career display parallels with the cases of near contemporaries, such as Aḥmad b. Muḥammad Kāmūsī (fl. c .700/1300) and Hindūshāh b. Sanjar Nakhjavānī (d. before 728/1327–8). To trace these parallels I refer to the recent manuscript-based studies of Bruno De Nicola and David Durand-Guédy, whose presentations of Kāmūsī and Hindūshāh respectively provide suggestive context for Ibn al-Sāvajī. Kāmūsī, Hindūshāh and Ibn al-Sāvajī occupied a middling position among the intellectuals and men of letters of late Ilkhanid Iran. Examined together, their cases permit a glimpse into patterns of life that, while less visible than the trajectories and accomplishments of the era’s most celebrated figures, must have been familiar among the many who – skilled, resourceful, versatile and adaptable – sought stability and security on the one hand and patronage and employment on the other. They illustrate the functioning of specific intellectual cultures and the dissemination of knowledge in local, rather than imperial or transregional, contexts.

Recent years have seen remarkable progress in deep learning on 3D point clouds, with hierarchical architectures becoming standard. Most work has focused on developing increasingly complex operators, such as self-attention, while enhancing the representational capacity of efficient point-wise MLP-based backbones has received less attention. We address this issue by proposing a differentiable module that learns to impose a task-driven canonical structure on local point sets. Our proposed SMA (Sort-Mix-Attend) layer dynamically serializes a neighborhood by generating a geometric basis and using a differentiable sorting mechanism. This enables an efficient MLP-based network to model rich feature interactions, adaptively modulating features prior to the final symmetric aggregation function. We demonstrate that SMA effectively enhances standard backbones for 3D classification and segmentation. Specifically, integrating SMA into PointNeXt-S achieves an Overall Accuracy (OA) of 88.3% on the challenging ScanObjectNN dataset, an improvement of 0.6% over the baseline. Furthermore, it boosts the classic PointNet++ architecture by a significant 5.2% in OA. We also introduce a highly efficient SMA-Tiny variant that achieves 86.0% OA with only 0.3 M parameters, proving the structural superiority, computational cost-effectiveness, and practical significance of our method for real-world 3D perception tasks.

Recurrent anterior shoulder instability with subcritical glenoid bone loss poses a treatment dilemma. Arthroscopic Bankart repair with additional remplissage and the open Latarjet procedure are commonly used, but their real-world economic impact in Latin America is poorly defined. To compare midterm clinical outcomes and real-world costs between the Latarjet procedure and arthroscopic Bankart repair with additional remplissage in Ecuadorian patients with subcritical glenoid bone loss, representing a surgical decision "gray zone" rather than prognostically equivalent populations. A retrospective cohort of 40 patients (20 per group) with ≥48 months of follow-up was analyzed. Functional outcomes (Constant, Rowe, SANE) and direct and indirect costs were assessed and standardized to 2022 USD. Functional outcomes were comparable, with no recurrent dislocations observed. Total costs were significantly lower for the Latarjet procedure (USD 4625 vs. USD 10,092), mainly due to implant-related expenses. When clinical outcomes are comparable, the Latarjet procedure was associated with lower overall costs, supporting a value-based surgical approach tailored to local healthcare settings. IV - Retrospective Comparative Study.

BACKGROUND Gestational diabetes mellitus (GDM), characterized by glucose intolerance, is an increasingly prevalent public health issue linked to both maternal and neonatal complications. Dyslipidemia, a cardiovascular risk factor associated with insulin resistance, can exacerbate GDM and lead to more severe maternal and fetal outcomes. While lipid changes are normal in pregnancy, excessive dysregulation may cause endothelial dysfunction, inflammation, and complications such as preeclampsia, macrosomia, and cesarean delivery. Understanding the burden of these conditions in local settings is crucial for early risk identification, targeted prevention, and improved maternal-fetal health. AIM To determine the prevalence and identify factors associated with GDM and its association with dyslipidemia among pregnant women attending health facilities in the Buea Health District (BHD), Cameroon. METHODS A cross-sectional hospital-based study was conducted from January 2024 to July 2024 in the BHD. A total of 113 pregnant women were selected by convenience. Sociodemographic, obstetric, and lifestyle data were collected using a structured and pretested questionnaire. Lipid profile was evaluated by enzymatic colorimetric methods. GDM was diagnosed by the oral glucose tolerance test using the National Institute for Health and Care Excellence 2015 criteria. Data were analyzed using the Statistical Package for Social Sciences version 26. The Student’s t -test was used to compare mean biochemical parameters between groups. Multivariate logistic regression analysis was conducted to assess the association between GDM and dyslipidemia. P < 0.05 was considered statistically significant. RESULTS The age of participants was 28.70 ± 5.19 years. The prevalence of GDM in the BHD was 10.6%. Pregnant women aged ≥ 34 years had an 11.47-fold higher risk of developing GD than their counterparts aged 20-26 years [adjusted odds ratio (aOR) = 11.47, 95% confidence interval (95%CI): 1.19-3.15; P = 0.03]. Also, unemployed women had an 8.80-fold higher risk of developing GDM compared to those who were employed (aOR = 8.80, 95%CI: 1.01-2.06; P = 0.04). Furthermore, women who exercised infrequently had a 10.31-fold higher risk of developing GDM than their counterparts who exercised daily (aOR = 10.31, 95%CI: 1.69-3.06; P = 0.02). Also, women who had a family history of diabetes were 4.35 times more at risk of developing GDM than their counterparts who had no family history (aOR = 4.35, 95%CI: 0.91-2.10; P = 0.04). The prevalence of dyslipidemia was 31.90%, and it was associated with the trimester of pregnancy (P = 0.003). Pregnant women in their third trimester of pregnancy had a 2.86-fold higher risk of developing dyslipidemia compared to those in their second trimester (aOR = 2.86, 95%CI: 1.06-7.70; P = 0.004). Also, GDM was associated with dyslipidemia (P = 0.037). CONCLUSION The prevalence of GDM and dyslipidemia among pregnant women in the BHD was 10.6% and 31.90%, respectively. Dyslipidemia was associated with GDM. Advanced maternal age, unemployment, less frequent exercise, and family history of diabetes mellitus were associated with GDM in the BHD.

We generalize the interpolative separable density fitting (ISDF) method, used for compressing the four-index electron repulsion integral (ERI) tensor, to incorporate adaptive real space grids for potentially highly localized single-particle basis functions. To do so, we employ a fast adaptive algorithm, the recently introduced dual-space multilevel kernel-splitting method, to solve the Poisson equation for the ISDF auxiliary basis functions. The adaptive grids are generated by using a high-order accurate, black-box procedure that satisfies a user-specified error tolerance. Our algorithm relies on the observation, which we prove, that an adaptive grid resolving the pair densities appearing in the ERI tensor can be straightforwardly constructed from one that resolves the single-particle basis functions, with the number of required grid points differing only by a constant factor. We find that the ISDF compression efficiency for the ERI tensor with highly localized basis sets is comparable to that for smoother basis sets compatible with uniform grids. To demonstrate the performance of our procedure, we consider several molecular systems with all-electron basis sets that are intractable using uniform grid-based methods. Our work establishes a pathway for scalable many-body electronic structure simulations with arbitrary smooth basis functions, making simulations of phenomena such as core-level excitations feasible on a large scale.

Sudden unexplained death (SUD) has been reported in localized rural settings worldwide, raising questions about whether drinking-water geochemistry may contribute to population-level health anomalies. The enigmatic occurrence of sudden unexplained death (SUD) in villages of the Ailao Mountains, China, represents one such case, yet the role of drinking water chemistry remains poorly constrained. This study presents the first comparative hydrochemical and health-risk assessment of drinking water from SUD-affected villages (SUDV) and neighboring non-affected villages (NSUDV), aimed at evaluating the potential role of groundwater geochemistry. A total of 63 water samples were analyzed for major ions and trace elements. Results show that waters from both village types are predominantly low-mineralization Ca-HCO3 type, controlled by carbonate weathering, with negligible anthropogenic influence, and all measured parameters comply with Chinese drinking water standards. Multivariate analyses reveal no fundamental compositional differences between SUDV and NSUDV waters. Critically, health risk assessments indicate negligible non-carcinogenic and carcinogenic risks for all SUDV samples, whereas a subset of NSUDV samples exhibits low-to-moderate risks primarily associated with geogenic arsenic and lithium. An Integrated Water Quality Index classifies all SUDV waters as excellent. These findings provide robust geochemical evidence excluding conventional groundwater contamination or elemental toxicity as the direct cause of the SUD phenomenon, thereby redirecting etiological inquiry toward interdisciplinary integration of genetic, biomedical, and other environmental cofactors.

ABSTRACT China’s human rights record, particularly regarding religious freedom, has faced widespread criticism. Although formal religious affiliation appears to have plateaued, diverse forms of religious and spiritual practice continue across the country, often in informal or localized settings. This reality presents both challenges and opportunities for the Chinese government: expressions of faith may be viewed as potential sources of instability, but can also be incorporated into ideological strategies that reinforce the legitimacy of the Socialist system and the Communist Party. This article explores how China’s political leadership navigates the paradox of managing religion within an officially atheist state and the extent to which spiritual and moral resources are co-opted for political purposes. Drawing on an analysis of recent Party and state documents, including new regulations and management measures issued by the National Religious Affairs Administration under the United Front Work Department, the study identifies an updated approach to the bureaucratization of religion. Under Xi Jinping, this includes aligning religious teachings with ideological and atheist principles to serve as extensions of Party governance, enforcing the Sinicization of religious practices, and strategically leveraging religion in international affairs.

Purpose This article develops a situated conceptual model that reinterprets institutional isomorphism in municipal digital transformation. It addresses the limitations of classical institutional theory by emphasizing interpretive agency, institutional multiplicity and legitimacy construction within structurally constrained local governance settings. Design/methodology/approach Building on institutional logics theory, this study conceptualizes municipalities as embedded in pluralistic fields shaped by bureaucratic, democratic, market and digital logics. It integrates prior research on municipal digital transformation and institutional isomorphism with insights from institutional work and sensemaking to construct a situated model of isomorphic response. Findings The model identifies three mechanisms – symbolic mandates, legitimacy signaling and localized normative referencing – through which municipalities interpret and navigate coercive, mimetic and normative pressures. These mechanism reveal digital transformation as a performative and context-dependent process, explaining variation in organizational change trajectories. Research limitations/implications As a conceptual article, empirical validation remains for future research through comparative and longitudinal studies. Practical implications Municipal leaders can apply the model to design reflexive transformation strategies aligned with local logic constellations. Social implications Understanding legitimacy construction fosters inclusive, participatory and context-sensitive public innovation. Originality/value The article reconceptualizes isomorphism as an interpretive and logic-mediated phenomenon, advancing institutional and change theory by highlighting symbolic and discursive dimensions of public sector transformation.