Implementing a molecular prescreening strategy for tumors without public NGS access in a cancer center network: Results from the PREICO project.

Location-based accessibility is widely assessed using zonal frameworks that aggregate high-resolution results into summary statistics. This aggregation-induced error is often assumed to be negligible, yet this assumption is rarely verified and may obscure critical disparities. This study introduces “Accessibility Misrepresentation” as the deviation between high-resolution accessibility and zonal proxies. Using building-level public transport accessibility in Metropolitan Melbourne, the research evaluates the magnitude, spatial patterns, and equity implications of misrepresentation. Results show systematic variation across travel time thresholds, built environment characteristics, aggregation methods, and service levels. Missed detection of populations without accessibility peaks at 15–20 min thresholds commonly used in neighbourhood accessibility policies, predominantly affecting densely populated middle suburbs where public transport catchments misalign with administrative boundaries. Continuous errors in accessibility values show no systematic directional bias; however, minorities can experience substantial misstatements sufficient to alter normative assessments. Equity analysis reveals disproportionate impacts on middle-status populations often overlooked by conventional frameworks. Population-weighted medians substantially outperform means in reducing misrepresentation. However, no single statistic adequately captures internal variation, particularly with multimodal distributions. A dual-scale approach is recommended: high-resolution computation to characterise within-zone distributions, combined with zonal summaries accompanied by distributional diagnostics, including share of residents without accessibility and upper-tail error indicators. This approach enhances transparency, supports equity-focused and defensible planning decisions without costing additional resources. • Zonal summaries cause “Accessibility Misrepresentation”. • Well-served zones may mask large accessibility gaps. • Middle socioeconomic group has large underserved subpopulations. • Medians outperform means as summaries of zonal accessibility. • Dual-scale analyses expose disparities and preserve interpretability.

The Adjusted Transit Accessibility Index: A proximity-independent measure of public transit accessibility

• Resilience of urban vitality during the COVID-19 pandemic was measured in Seoul. • Three resilience dimensions were resistance, recovery capacity, and adaptability. • Neighborhood characteristics shaped resilience differently across dimensions. • Context-specific effects revealed heterogeneous and dynamic resilience patterns. • Findings provide insights for sustainable urban planning and tailored strategies. Although urban vitality and resilience are often examined as distinct phenomena, little is known about how vitality evolves across different phases of resilience under external shocks. This study investigates the resilience of urban vitality in Seoul during the COVID-19 pandemic by distinguishing three dimensions: resistance, recovery capacity, and adaptability. Using de facto population data (2018–2024), we trace resilience trajectories with a dynamic measurement framework that operationalizes these dimensions. Structural equation modeling is then applied to identify how neighborhood-level indicators for 424 administrative units shaped these three dimensions. The results show that resilience varied across neighborhoods: resistance declined in office-dominated areas but was partially supported by lodging and school facilities, recovery capacity was constrained by industrial land use but strengthened by favorable demographic composition and green space, and adaptability was reinforced by high levels of public transport accessibility. By contrast, several land-use and facility variables demonstrated inconsistent or marginal effects, indicating that resilience was shaped more by social composition, spatial openness, and connectivity than by static density measures. These findings highlight the heterogeneous and dynamic nature of resilience and underscore the need for differentiated strategies in sustainable urban planning.

The accessibility-sustainability paradox: Optimizing the community pharmacist's role in public health.

Synthesised evidence on the formal recognition of advanced community pharmacists (ACPs) and their practice is limited. This review aims to explore global evidence on the practice of formally recognised ACPs. This scoping review followed the JBI Manual for Evidence Synthesis and PRISMA guidelines. Advanced practice was determined using the International Pharmaceutical Federation framework encompassing four pillars: professional practice, leadership, research, and education. Formal recognition referred to post-registration acknowledgement by authorised bodies. Twelve databases and Google Scholar were searched between 2004 and 2024, without country or language restrictions. Findings were thematically analysed using NVivo 14. Sixty-three studies from six high-income countries were included, predominantly from Canada (n=18) and the United States (n=16). Formally recognised ACPs provided clinical services including prescribing (n=27), vaccination (n=22), and medication review (n=20). Few studies reported ACPs practice within the research and education pillars. There was variation in the definition and formal recognition mechanisms of ACPs between studies. In addition, many studies reported practice corresponding to advanced services but did not describe prerequisite training or formal recognition. Reported challenges included inadequate remuneration, limited access to patient records, and low stakeholder awareness. Key facilitators were availability of formal recognition, interprofessional relationships, and appropriate training. ACPs have expanded public access to clinical services. However, formal recognition and practice of ACPs from low-middle-income-countries are underrepresented in the literature. More work is needed to recognise ACPs' practice in education and research. Future research should clearly operationalise advanced practice within existing frameworks, explicitly report recognition mechanisms, and engage broader stakeholders in the implementation, evaluation, and role development of ACPs.

ABSTRACT This study examines the current state and development potential of data journalism in Kyrgyzstan through comparison with practices in the United States, the United Kingdom, Kazakhstan, and several European countries. The analysis focuses on key data journalism resources and media platforms operating in these regions. The findings show that data journalism plays an important role in ensuring openness and public access to information in Kyrgyzstan. Television remains a significant driver of this genre, with the National Television and Radio Broadcasting of the Kyrgyz Republic making a substantial contribution to its development. At the same time, the availability and growth of online media have become an important factor, as several digital publications actively use data journalism to present complex information in a clear and accessible format. Before the study, participants’ mean scores ranged from 1.90–2.23, indicating low initial competence in data journalism skills. After the study, mean scores increased significantly to between 4.03 and 4.20, showing substantial improvement across all measured areas. Standard deviations remained low (0.09–0.12), suggesting that participants’ responses were consistent and the observed improvements were reliable.

Breaking data silos: How does public data open access influence enterprise collaborative innovation?

The proliferation of short-form educational video platforms has facilitated the public's access to health information; however, no research has assessed the characteristics and quality of videos related to atrial septal defect. ASD was selected because it is one of the most common congenital heart defects encountered across the lifespan, often requiring repeated explanations regarding diagnosis, follow-up, timing of intervention, and long-term prognosis for patients and families. In addition, although short-form video studies have been conducted for several other diseases, ASD-related content on major Chinese short-video platforms has not been systematically evaluated. This study aimed to evaluate the quality and reliability of short videos related to atrial septal defect on TikTok and Bilibili. The Chinese term "atrial septal defect" was used to search for related videos on TikTok and Bilibili, and a predefined sampling strategy was used to screen the first 100 algorithm-ranked videos from each platform on October 21, 2025. This sample size was determined a priori to provide a feasible and standardized cross-sectional sample for manual content evaluation and to maintain comparability between platforms, rather than being based on a formal sample size calculation. Duplicate, irrelevant videos, and videos published within seven days were excluded to reduce the instability of early engagement indicators. As a result, 155 videos were included for analysis. The overall quality of these videos was assessed using the Global Quality Score (GQS), VIQI, PEMAT, JAMA Benchmark, and the DISCERN tool. These instruments were used to evaluate educational quality, reliability, transparency, understandability, and actionability, but they did not constitute a direct assessment of factual accuracy or potentially harmful medical content. Interobserver reliability was assessed for the independently retained duplicate GQS ratings using quadratic weighted kappa. Because social media search results are algorithm-ranked and may be affected by platform personalization, the included sample should be interpreted as a snapshot of highly visible ASD-related videos on the sampling day rather than an exhaustive representation of all available videos. Among the 155 videos (Bilibili: n = 70; TikTok: n = 85), significant differences were observed across all engagement and quality metrics. TikTok videos demonstrated significantly higher values for likes (median 415.0 [IQR 186.0 to 961.0] vs. 11 [IQR 5.0 to 52.75]), collections (131.0 [IQR 50.0 to 332.0] vs. 26.5 [IQR 8.0 to 106.75]), shares (124.0 [IQR 35.0 to 583.0] vs. 7.5 [IQR 2.0 to 29.0]), and comments (61.0 [IQR 17.0 to 492.0] vs. 1.0 [IQR 0.0 to 9.5]) (all P < 0.05). In contrast, the Bilibili group had longer video durations (in seconds) (639.0 [IQR 327.0 to 1,106.0] vs. 326.0 [IQR 216.9 to 429.0]; P < 0.001) and longer times since upload (in days) (356.0 [IQR 71.25 to 770.25] vs. 60.0 [IQR 37.0 to 102.0]; P < 0.001). Content quality assessments also differed, with TikTok videos having higher median DISCERN scores (23.788 vs. 22.786; P = 0.001), JAMA_Benchmark (1.918 vs. 1.714; P = 0.001) and GQS scores (3.635 vs. 3.314]; P = 0.006). However, the proportion of professional uploaders differed markedly between platforms (TikTok: 96.47% vs. Bilibili: 44.29%), and uploader-level analyses suggested that part of the observed quality advantage on TikTok may be attributable to uploader composition rather than platform characteristics alone. Importantly, this conclusion was based on the absolute position of the observed scores on their respective validated scales rather than on an arbitrary composite cutoff. Specifically, median GQS values of 3.314 and 3.635 on a 1-5 scale indicate moderate rather than high educational quality, whereas median JAMA Benchmark values of 1.714 and 1.918 on a 0-4 scale indicate that, on average, fewer than half of the transparency/reliability criteria were met. Because no universally accepted single "target quality score" exists across GQS, JAMA, DISCERN, PEMAT, and VIQI, each instrument was interpreted according to its own published scale direction and anchors. TikTok videos related to atrial septal defect are more engaging and of higher content quality than those on Bilibili. Overall, health-related videos on both platforms showed only moderate educational quality, with notable limitations in transparency, reliability, source attribution, and actionable guidance. Professionally produced content tended to perform better, although between-platform differences should be interpreted cautiously because of differences in uploader composition. These findings suggest that greater participation by health professionals may help improve the quality and reliability of online health information. As this study assessed informational quality rather than factual accuracy and was limited to Chinese-language videos from two platforms at a single time point, the results should be interpreted as a platform- and time-specific snapshot.

Although public access defibrillation programs have expanded, real-world bystander automated external defibrillator (AED) use remains limited. The concept of functional accessibility, the realistic ability of bystanders to retrieve and use an AED within a time window that affects survival, has not yet been systematically evaluated. This study aimed to evaluate the functional accessibility of publicly installed AEDs by integrating factors influencing their usability in out-of-hospital cardiac arrest events. We conducted a population-based geospatial analysis of 39 563 out-of-hospital cardiac arrests in Gyeonggi-do, Korea (2021-2023). Each incident was matched to the nearest public AED using network-based walking routes. Functional accessibility was measured by walking time and distance, stratified by urbanization, time of day, and location of arrest. Multivariable logistic regression was used to assess the association of AED accessibility with bystander AED use and prehospital return of spontaneous circulation. The median walking time to the nearest AED was 1.9 minutes; only 25.4% of rural arrests were within 3 minutes. Among 17 285 resuscitation-attempted cases, bystander AED use occurred in 2.9%. Shorter walking time was a statistically significant predictor of AED use and prehospital return of spontaneous circulation. Nighttime and residential arrests showed markedly reduced AED use irrespective of proximity. Moreover, although home arrests accounted for 70% of cases, bystander defibrillation occurred in <2%. Functional accessibility determines both device use and survival outcomes. Policies should prioritize 24/7 external AED availability, integration of dispatcher-assisted public access defibrillation programs, and novel delivery systems, such as drones, to bridge the spatial and temporal gaps in access.

The continuous evolution of smart city infrastructure has created a growing demand for intelligent and user-oriented public information systems. People moving through unfamiliar urban locations often experience difficulty in identifying essential public services such as transportation centers, healthcare facilities, government offices, and emergency support services. Traditional navigation methods largely depend on static maps, text-based instructions, or list-oriented interfaces, which require constant interpretation and can result in confusion, time delays, and reduced awareness of surroundings. This paper introduces HoloComm, an augmented reality–based public information and navigation system that combines mobile Internet of Things (IoT) principles to deliver real-time and context-aware guidance. The proposed solution utilizes smartphones as mobile IoT edge devices by exploiting inbuilt components such as GPS, camera, orientation sensors, and network connectivity. By presenting location-specific public information directly within the user’s real-world camera view, HoloComm improves spatial perception and minimizes dependence on conventional map-based navigation. The system adopts a modular and extensible architecture that includes location identification, data processing, service category selection, and augmented reality visualization modules. Public service information is dynamically selected and filtered based on the user’s current position and chosen service type, enabling accurate and efficient visualization of nearby facilities. The integration of AR elements such as directional indicators and contextual markers enhances navigation efficiency and user engagement, particularly for first-time users and emergency scenarios. Experimental evaluation shows that HoloComm can be effectively implemented on commonly available Android smartphones, making it a practical and economical solution for smart city applications. Overall, the system demonstrates how the integration of augmented reality and mobile IoT concepts can transform public information access into a more immersive, intuitive, and interactive experience.

Adaptive reuse of industrial heritage from a tourism perspective presents a complex design challenge requiring a balance between heritage preservation, functional innovation, and diverse stakeholder expectations. However, current practices often face issues such as ambiguous demand interpretation and a disconnect between design generation and systematic evaluation. Addressing these limitations, this paper proposes and illustrates a human–machine collaborative design paradigm that integrates generative AI into a closed-loop process of “demand analysis–intelligent generation–comprehensive evaluation.” The method first employs Kansei Engineering and the KANO model to qualitatively extract and quantitatively prioritise heterogeneous user needs, translating subjective perceptions into structured design constraints and optimisation objectives. Next, these needs are encoded as text prompts to drive targeted spatial exploration by the generative AI tool Nano Banana AI. Finally, the TOPSIS method is applied for multi-criteria performance evaluation and solution selection. A case study of Shanghai Libo Brewery suggests that this paradigm can enhance design efficiency and show potential to outperform traditional methods across dimensions such as historical preservation, public accessibility, ecological integration, social inclusivity, and formal innovation. The research offers a quantifiable and systematically documented intelligent design methodology for industrial heritage renewal, while acknowledging the exploratory nature of the generative phase. Furthermore, it provides a visitor-demand-driven innovation pathway for developing industrial heritage tourism destinations, thereby potentially enhancing cultural experiences and tourism appeal at heritage sites. This research illustrates a move from an experience-driven paradigm toward a data- and value-driven approach, contributing theoretical methodologies to the intersection of cultural tourism and artificial intelligence.

Wikipedia is one of the most widely accessed sources of scientific information globally, serving as a critical platform for public understanding and engagement with science. Despite its influence, many scientific societies are underrepresented or insufficiently described on the platform, limiting their visibility, outreach potential, and opportunities for public scholarship. This gap is particularly significant given Wikipedia's high placement in search engine results and its role in shaping perceptions of scientific institutions. To address this issue, a structured case study was conducted focusing on the Wikipedia article for the American Association for Anatomy (AAA). A baseline evaluation revealed major deficiencies in article structure, historical coverage, citation quality, and alignment with Wikipedia's editorial standards. Using a methodical editing process informed by science communication principles and content guidelines, the article was substantially revised. High-quality secondary sources were used to develop new sections on AAA's mission, governance, publications, awards, meetings, and outreach efforts. Following these edits, the article's classification improved from Stub to Start-class, its visibility and connectivity within Wikipedia increased, and the number of internal and external references, links, and structural elements grew substantially. To complement these objective improvements, a survey of anatomy stakeholders (n = 29) indicated increased perceptions of credibility, trust in the AAA, and educational usefulness. These outcomes demonstrate that scholarly engagement with Wikipedia can meaningfully enhance institutional presence and public accessibility of scientific knowledge. This case study offers a transparent and replicable model for scientific organizations and educators seeking to improve digital visibility and contribute to open-access science.

ABSTRACT This article examines the accessibility, transparency, and interconnectivity of provenance research in museum collections. While the field originated in efforts to document Nazi-era looting, it now also addresses colonial contexts, state succession, and broader cultural heritage claims. Drawing on web-harvested data from 42 departments across 14 institutions in Germany and the United States, the article proposes a systematic framework for evaluating provenance information. The findings reveal differences in data quality, completeness, and standardization, alongside structural constraints shaped by institutional workflows, technology, and resources. Although digitization has expanded public access to provenance information, we still observe significant gaps between professional guidelines and institutional practices. The article therefore calls for standardized data models, interoperable infrastructures, and sustainable strategies for provenance documentation. By identifying both persistent barriers and emerging opportunities, it underscores the importance of interdisciplinary collaboration, shared standards, and wider public accessibility to strengthen equitable and trustworthy stewardship of cultural heritage.

ABSTRACT Academic libraries are increasingly integrating data science methods and computational workflows into research support services, particularly as traditional liaison models evolve to meet new demands for faculty engagement and research visibility. This article presents a reproducible, Python-based workflow that transforms open metadata from the OpenAlex API into department-level bibliometric reports for a College of Engineering at an R1 research institution. Report outputs include publication venues, cited references, funding sources, access models, topical keywords, and co-authorship networks. Designed for adaptability and transparency, the workflow is openly shared and can be reconfigured for use with other disciplinary units or metadata sources. Beyond its technical contribution, the project demonstrates how libraries can translate emerging skillsets into high-value, faculty-facing services – positioning themselves as strategic partners in research analytics and institutional assessment. The approach offers a scalable model for developing computationally derived outreach artifacts that are designed to prompt faculty engagement and showcase library expertise within increasingly data-intensive research environments.

Against the backdrop of high-quality urbanization in cities, the rapid expansion of metro networks has led to severe spatial mismatches in land use around station areas, which seriously restricts the full exertion of the comprehensive benefits of the transit-oriented development (TOD) model. Taking 139 operational metro stations in Xi’an in 2024 as the research sample, this study constructs a multi-objective land use optimization model with the richness of public services, transportation accessibility and population distribution balance as the three core maximization objectives. A hierarchically adaptive improved NSGA-III algorithm is proposed, with the following four key technical optimizations implemented: multi-dimensional adaptive reference point adjustment, design of real-integer hybrid coding genetic operators, construction of an enhanced multi-criteria environmental selection mechanism, and dynamic regulation of algorithm iteration. Experimental results show that the performance of the improved algorithm is significantly superior to that of the traditional NSGA-III algorithm: the values of the three core objectives are increased by 59.58%, 12.94% and 7.35% respectively compared with the original data; the algorithm achieves stable convergence after 25 iterations, with the convergence efficiency improved by 30%. The obtained Pareto optimal front features good uniformity (U = 0.92) and coverage (C = 0.95), and all the 80 non-dominated solutions meet all constraint conditions, with the solution set highly coupled with the urban functional zoning and spatial planning of Xi’an. This study proposes a zoned, prioritized and phased hierarchical land use optimization strategy for the areas around metro stations in Xi’an. The research findings provide a replicable research framework and methodological reference for the TOD practice and land use optimization of metro station areas in other rapidly urbanizing central cities in China and developing countries worldwide with the characteristic of rapid rail transit expansion.

Harm reduction strategies effectively minimize the immediate health consequences of drug use, such as syringe exchange and overdose prevention. However, the critical role of access to adequate Water, Sanitation, and Hygiene (WASH) services in mitigating these consequences remains underemphasized. This paper argues for the consideration of WASH services as an essential framework within the ongoing evolution of harm reduction, particularly for marginalized people who use drugs (PWUD) facing housing insecurity and limited access to public infrastructure. Lack of access to WASH services forces PWUD into high-risk practices, such as open defecation and using unsafe water for drug preparation and wound cleaning. WASH insecurity among PWUD is strongly associated with elevated risks of skin and soft tissue infections -a leading cause of hospitalization-as well as other infectious diseases, and the exacerbation of chronic conditions (e.g., HIV, Hepatitis C). Beyond direct morbidity, WASH insecurity diminishes dignity, contributing to social exclusion, hygiene-related stigma, and increased vulnerability to gender-based and other structural violence. Drawing on current evidence, this perspective article underscores the necessity of systemic intervention. Harm reduction programs are increasingly called to incorporate WASH items and services, including mobile hygiene units operating under principles of "radical hospitality," and advocate for broader policy solutions like 24/7 public restroom access and Housing First models with integrated WASH facilities. In sum I argue that integrating WASH is not merely a matter of basic amenity; it is a crucial, high-impact strategy for upholding the human rights of PWUD, substantially reducing preventable drug-related harms, and fostering greater social equity.

Purpose India lacks a comprehensive, village-level assessment of primary healthcare accessibility needed to guide policies for improving access. This article provides a nationwide, village-level baseline measure of public primary healthcare accessibility in India using three distinct spatial metrics. Design/methodology/approach A geocoded census of public healthcare facilities from the National Health Resource Repository is merged with spatial and demographic data for rural census villages. A multi-dimensional framework is developed to assess healthcare accessibility using three metrics: (1) a regional availability metric that captures infrastructure shortfalls relative to Indian Public Health Standards (IPHS) norms; (2) a measure using Euclidean distance to the nearest facility and (3) a capacity-constrained, catchment-based propensity-of-access metric conceptually aligned with the two-step floating catchment area method. Descriptive and spatial analyses are conducted at national and sub-national levels to highlight geographic variation in accessibility. Findings The first metric shows that a rural Primary Health Centre (PHC) serves an average of 33,800 people, exceeding the Indian Public Health Standards norm of 30,000. The second indicates an average village-to-PHC distance of 5.49 kilometres. The third shows that, when population pressure and distance are considered jointly, residents in 20% of villages are effectively crowded out, even at the national average distance. Originality/value This nationwide, village-level assessment is the first to integrate availability, proximity and capacity-adjusted access across India. The analysis challenges single-metric planning approaches and suggests that upgrading or expanding infrastructure alone cannot resolve persistent spatial and capacity gaps in rural healthcare. The insights extend beyond India, where similar metrics often misstate healthcare accessibility.

Climate change and rapid urbanization are intensifying urban pluvial flooding and threatening sustainable urban development. This study proposes a three-stage, four-dimensional framework (TSFD-UPFR) to assess urban pluvial flood resilience across resistance, response, and recovery phases that integrate natural, infrastructural, social, and economic dimensions. Using a representative urban catchment affected by a typical extreme rainfall event, we couple hydrological–hydrodynamic simulations with multi-source remote sensing and socio-economic indicators at a 100 m grid resolution to enable spatially explicit assessment. The results indicate moderate overall resilience with pronounced spatial heterogeneity. Resistance is primarily constrained by drainage capacity and impervious surfaces, response is shaped by road connectivity and public service accessibility, and recovery is determined by essential facility restoration and economic support. Low-resilience clusters are concentrated in dense built-up areas and transport hubs, revealing structural weaknesses in adaptive capacity. By linking flood processes with socio-economic recovery dynamics, the framework captures cross-stage interactions within urban systems. The findings support climate-adaptive planning, targeted infrastructure investment, and resilience-oriented governance, contributing to sustainable and equitable urban transformation in megacities facing intensifying extreme rainfall.

Abstract This article presents a Multimodal Retrieval-Augmented Generation (RAG) system for the digital preservation of traditional knowledge (TK) from the Jino ethnic group in China, a small indigenous community whose knowledge is primarily transmitted through oral narratives, ritual practices, and place-based ecological experience. The system integrates text, audio, and image data, using the m3e-base model for embedding generation and Facebook AI Similarity Search for semantic search. A Flask backend supports cross-modal queries, with OpenAI models handling keyword extraction and generation. Deployed via Docker and Cloudflare Tunnel, the system is embedded in a WordPress interface for public access. Beyond implementation, the study addresses challenges in data collection, intellectual property, and cultural authenticity. Results indicate that AI-driven multimodal retrieval can support sustainable TK transmission and inform future digital heritage infrastructures.