Search Results (6,349)

The Nationality and Borders Act 2022 was enacted despite significant opposition from refugee charity and legal sectors. It is without question that the Act changes the domestic landscape of the refugee status determination system and has the potential to also negatively influence refugee status determinations in other jurisdictions. There are several sections of the Act that are particularly problematic for women’s claims of asylum. The Act reverses well-established international and regional human rights and refugee law principles and standards. The reversal, in some cases, of decades of jurisprudence on the interpretation of the Refugee Convention poses a concern for the integrity of the law and administrative justice. While the Act imposes barriers for all claimants, it disproportionately affects some of the most complex cases, including refugee women fleeing gender-based persecution. Of the various changes brought about by the Act, this article focuses on three that are particularly relevant to women asylum seekers: first, the regressive way in which membership of a particular social group has been framed; second, the heightened standard of proof now required; and third, the associated evidential burdens in relation to trauma and disclosure. Ultimately, these changes are likely to have a disproportionate and discriminatory impact on women seeking asylum, particularly those fleeing gender-based persecution. Full article

Background: Human papillomavirus (HPV)-associated oral and oropharyngeal squamous cell carcinomas have risen dramatically in incidence over recent decades. Yet, unlike cervical neoplasia, there is no established screening paradigm for HPV-driven oropharyngeal dysplasia, as precursor lesions are often occult and are not easily accessible for examination. This drives an urgent need for non-invasive biomarkers to enable early detection, risk stratification, and timely intervention. Objective of this review is to highlight advances in liquid biopsy modalities, specifically saliva- and blood-based biomarkers—in the context of HPV-driven oral carcinogenesis—and to evaluate their utility in early cancer detection, prognostic, post-treatment surveillance, and recurrence monitoring. Methods: We performed a narrative review of PubMed-indexed studies (2015–2025) focusing on HPV-positive oral and oropharyngeal squamous cell carcinomas. and liquid biopsy analytes. Key sources were high-impact original studies and meta-analyses from 2020–2025 examining circulating tumor DNA (ctDNA), viral nucleic acids, circulating tumor cells (CTCs), extracellular vesicles (EVs), and related biomarkers in saliva and blood. Reported data on assay performance, biases, and validation were reviewed to highlight how oral cancer findings align with trends seen in other solid tumors. Results: In reviewing recent studies (2015–2025), we found consistent evidence that saliva best captures locoregional tumor signals while plasma circulating tumor HPV DNA (ctHPV DNA) reflects systemic disease, and that using both matrices improves detection over either alone. Dual-fluid testing will potentially enable earlier identification of molecular residual disease with clinically meaningful lead time before radiographic recurrence, supporting risk-adapted surveillance. Overall, literature favors standardized pre-analytics and combined saliva plus plasma workflows to enhance early detection and follow-up in HPV-positive oral and oropharyngeal squamous cell carcinomas. Conclusions: Liquid biopsy approaches offer promising tools for the early, non-invasive detection and real-time monitoring of HPV-associated oral cancers. Realizing their full clinical potential will require robust prospective validation and standardization of pre-analytical protocols. Integrating salivary and blood biomarkers into tailored surveillance programs may further support earlier intervention and improved patient outcomes, while potentially reducing reliance on unnecessary invasive procedures. Full article

The gut microbiota greatly influences host physiology, including immune regulation, metabolic balance, and brain health. Aging is associated with alterations in the gut microbiome, including reduced microbial diversity and increased pro-inflammatory bacteria, which are linked to age-related decline and chronic diseases. This review examines the impact of the gut microbiota on key indicators of aging, including cellular senescence, mitochondrial dysfunction, alterations in gene expression, and immune system modifications. It also examines microbiome-related diseases associated with aging, including neurodegeneration, cardiovascular issues, metabolic syndrome, and frailty. Additionally, it highlights evidence-based methods to restore a youthful microbial profile. New findings suggest that certain microbial substances, including short-chain fatty acids, urolithins, and bile acids, play a role in regulating inflammation, maintaining barrier integrity, and influencing metabolism. Age-related diseases are often associated with molecular pathways driven by an imbalance in the gut microbiome. Various intervention strategies, from dietary changes and probiotics to personalized nutrition and fecal microbiota transplantation, have shown promise in reversing signs of microbial aging and improving health outcomes in both lab and human studies. Overall, the gut microbiome serves as both a marker and a regulator of healthy aging. Treatments that restore microbial balance offer hopeful ways to extend healthy living. Future studies should focus on developing long-term, multifaceted, and personalized methods to identify causal pathways and enhance microbiota-based strategies for various aging populations. Full article

This study presents the development of a prototype anthropomorphic soft robotic gripper intended for applications in rehabilitation and assistive robotics, where safe and adaptive interaction with humans is required. The device consists of three elastomeric fingers, fabricated in TPU via FFF 3D printing and actuated through pneumatic soft actuators that ensure compliant contact with both biological tissue and rigid objects. A custom 3D-printed pneumatic rotary actuator enables finger reconfiguration, thereby extending the range of grasping modalities. The actuation system comprises six 2/2 solenoid valves controlled by an Arduino Uno and integrated into a dedicated pneumatic circuit. Experimental characterization demonstrated a peak grasping force exceeding 17 N on rigid targets, while functional tests in table-picking scenarios confirmed adaptability to objects of varying shapes and sizes. Owing to its anthropomorphic configuration, mechanical compliance, and ease of fabrication and control, the proposed gripper represents a versatile solution for rehabilitation-oriented devices as well as assistive robotic end-effectors in pick-and-place tasks. Full article

Traffic accidents remain a major global burden, causing mortality, disability, and socio-economic losses that hinder sustainable development. Beyond human suffering, crashes place long-term pressures on health systems, labor markets, and national economies, disproportionately impacting low- and middle-income countries. Estimating the true societal costs of accidents is therefore essential for designing effective, equitable, and sustainable road safety policies. This study applies the Willingness-to-Pay (WTP) method to evaluate the external costs of traffic-related deaths and injuries in Türkiye between 2008 and 2018. By incorporating material and immaterial losses, the WTP framework captures a broader spectrum of impacts than traditional approaches, offering valuable insights into the scale of welfare losses and the value of risk reduction. The findings reveal that external costs rose substantially over the decade, from 1.63% to 2.72% of national Gross Domestic Product (GDP), underscoring that economic losses from road crashes are growing faster than the economy. These results highlight the need for systematic interventions that integrate road safety into national sustainability agendas, including safer infrastructure, behavioral programs, advanced vehicle technologies, and efficient emergency response systems. The evidence presented strengthens the case for prioritizing traffic safety as a fundamental component of sustainable transport and public health strategies. Full article

Per- and polyfluoroalkyl substances (PFASs) have attracted global attention due to their persistence and biological toxicity, becoming critical emerging contaminants in river and lake environments worldwide. Building upon existing studies, this work aims to comprehensively understand the pollution patterns, environmental behaviors, and potential risks of PFASs in freshwater systems, thereby providing scientific evidence and technical support for precise pollution control, risk prevention, and the protection of aquatic ecosystems and human health. Based on publications from 2002 to 2025 indexed in the Web of Science (WoS), bibliometric analysis was used to explore the temporal evolution and research hotspots of PFASs, and to systematically review their input pathways, pollution characteristics, environmental behaviors, influencing factors, and ecological and health risks in river and lake environments. Results show that PFAS inputs originate from both direct and indirect pathways. Direct emissions mainly stem from industrial production, consumer product use, and waste disposal, while indirect emissions arise from precursor transformation, secondary releases from wastewater treatment plants (WWTPs), and long-range atmospheric transport (LRAT). Affected by source distribution, physicochemical properties, and environmental conditions, PFASs display pronounced spatial variability among environmental media. Their partitioning, degradation, and migration are jointly controlled by molecular properties, aquatic physicochemical conditions, and interactions with dissolved organic matter (DOM). Current risk assessments indicate that PFASs generally pose low risks in non-industrial areas, yet elevated ecological and health risks persist in industrial clusters and regions with intensive aqueous film-forming foam (AFFF) use. Quantitative evaluation of mixture toxicity and chronic low-dose exposure risks remains insufficient and warrants further investigation. This study reveals the complex, dynamic environmental behaviors of PFASs in river and lake systems. Considering the interactions between PFASs and coexisting components, future research should emphasize mechanisms, key influencing factors, and synergistic control strategies under multi-media co-pollution. Developing quantitative risk assessment frameworks capable of characterizing integrated mixture toxicity will provide a scientific basis for the precise identification and effective management of PFAS pollution in aquatic environments. Full article

Analyzing accident reports to absorb past experiences is crucial for construction site safety. Current methods of processing textual accident reports are time-consuming and labor-intensive. This research applied the LDA topic model to analyze construction accident reports, successfully identifying five main types of accidents: Falls from Height (23.5%), Struck-by and Contact Injuries (22.4%), Slips, Trips, and Falls (21.8%), Hot Work & Vehicle Hazards (18.1%), and Lifting and Machinery Accidents (14.2%). By mining the rich contextual details within unstructured textual descriptions, this research revealed that environmental factors constituted the most prevalent category of contributing causes, followed by human factors. Further analysis traced the root causes to deficiencies in management systems, particularly poor task planning and inadequate training. The LDA model demonstrated superior effectiveness in extracting interpretable topics directly mappable to engineering knowledge and uncovering these latent factors from large-scale, decade-spanning textual data at low computational cost. The findings offer transformative perspectives for improving construction site safety by prioritizing environmental control and management system enhancement. The main theoretical contributions of this research are threefold. First, it demonstrates the efficacy of LDA topic modeling as a powerful tool for extracting interpretable and actionable knowledge from large-scale, unstructured textual safety data, aligning with the growing interest in data-driven safety management in the construction sector. Second, it provides large-scale, empirical evidence that challenges the traditional dogma of “human factor dominance” by systematically quantifying the critical role of environmental and managerial root causes. Third, it presents a transparent, data-driven protocol for transitioning from topic identification to causal analysis, moving from assertion to evidence. Future work should focus on integrating multi-dimensional data for comprehensive accident analysis. Full article

Background: International and national policies increasingly call for person-centred approaches in disability services, yet little is known about how support intensity needs influence the allocation of resources for individuals with intellectual and developmental disabilities (IDDs). In Italy, where integrated socio-health systems operate within a human rights framework, this quantitative study investigates how individual and contextual factors shape resource use in individualized support planning. Methods: We analyzed data from 1152 adults with IDDs enrolled in 23 service centres across 13 Italian regions. Case managers developed Individualized Support Plans (ISPs) informed by the Supports Intensity Scale and socio-ecological variables. Resource use was measured as weekly counts of adaptive skills training, community participation supports, habilitation services, prosthetics, and assistive technologies. We applied multivariate count models (Sarmanov–Lee) to capture the interdependence across support types. Results: Findings show that gender and level of intellectual functioning did not significantly affect resource allocation. However, individuals with the highest support intensity needs often received fewer supports, particularly in adaptive skills and community participation. Residential settings were associated with higher levels of support provision compared to family or independent living. Assistive technologies and prosthetics were linked with more comprehensive support packages. Conclusions: While person-centred planning frameworks are being implemented, systemic inequities remain, with those at the highest levels of need at risk of receiving fewer enabling supports. Multivariate modelling provides a robust tool for understanding resource use and highlights the importance of equity-focused planning. These findings support policy and practice reforms that operationalize human rights principles and align with the UNCRPD, ensuring more inclusive and responsive systems of support. Full article

Establishing a sustainable human presence on the Moon and Mars will require the use of locally available resources for construction. A binder material similar to concrete is a promising candidate, provided that its production and performance under reduced gravity can be reliably understood. Previous microgravity investigations demonstrated the feasibility of mixing cementitious materials in space but produced irregular or low-quality specimens that limited standardized mechanical testing. To address these limitations, the MASON (Material Science on Solidification of Concrete) team developed the first-generation MASON Concrete Mixer (MCM), which enabled the safe production of cylindrical specimens aboard the International Space Station (ISS). However, its fully manual operation introduced variability and required significant astronaut time. Building on this foundation, the development of an automated MCM prototype is presented in this study. It integrates motorized mixing and programmable process control into the established containment architecture. This system enables reproducible specimen production by eliminating operator-dependent variations while reducing crew workload. In comparison to manually mixed samples, the automated MCM demonstrated reduced variability in the tested concrete properties. The automated MCM represents a first step toward autonomous space instrumentation for high-quality materials research and provides a scalable path to uncrewed missions and future extraterrestrial construction technologies. Full article

Glioblastoma (GB) is an extremely aggressive tumor for which effective therapy is still in its infancy. Although several candidate therapeutics have been identified in functional preclinical assays, clinical trials have not supported their effectiveness in GB patients. The poor clinical efficacy of the treatments can be attributed to the insufficient mimicry of GB in patients by the preclinical models used. In this review article, we provide a comprehensive overview of the available GB preclinical models, which are classified according to their origin (animal or human), species, type and modeling strategy (two- or three-dimensional cell culture, in vivo grafting or in silico modeling). Moreover, the article compares developing cutting-edge technologies, including GB-derived organoids, bioprinting, microfluidic devices, and their multimodal integration in GB-on-chip systems, which aim to replicate the GB microenvironment with high precision. In silico and in vivo approaches are also reviewed, including zebrafish transplantation models. The costs, benefits, applications and clinical relevance of each model system and/or modeling strategy are discussed in detail and compared. We highlight that the most appropriate, or combination of, GB preclinical models must be selected (or even customized) based on the specific aims and constraints of each study. Finally, to improve the reliability and translational relevance of GB research, we propose a practical roadmap that addresses critical challenges in preclinical assay development, ranging from short-term adjustments to long-term strategic planning. Full article

While robotic technologies have shown great promise in enhancing productivity and safety, their integration into the mining sector, particularly for search and rescue (SAR) missions, remains limited. The success of these systems depends not only on their technical capabilities, but also on the effectiveness of human–robot interaction (HRI) in high-risk, time-sensitive environments. This review synthesizes key human factors, including cognitive load, situational awareness, trust, and attentional control, that critically influence the design and operation of robotic interfaces for mine rescue missions. Drawing on established cognitive theories such as Endsley’s Situational Awareness Model, Wickens’ Multiple Resource Theory, Mental Model and Cognitive Load Theory, we identified core challenges in current SAR interface design for mine rescue missions and mapped them to actionable design principles. We proposed a human-centered framework tailored to underground mine rescue operations, with specific recommendations for layered feedback, multimodal communication, and adaptive interfaces. By contextualizing cognitive science in the domain of mining emergencies, this work offers a structured guide for designing intuitive, resilient, and operator-supportive robotic systems. Full article

Deteriorating check dams pose significant threats to human safety and property, while impeding eco-environmental restoration in soil–water conservation systems in vulnerable watersheds like the Jiuyuangou Basin on China’s Loess Plateau. This study aimed to develop a comprehensive risk assessment framework for the check dam system in the Jiuyuangou Basin, China, to mitigate its threats to safety and eco-environmental restoration. A multi-index and multilevel risk evaluation system was established for check dam systems in the Jiuyuangou Basin, utilizing data gathering, hydrological statistics, numerical computation, and various methodologies. The index weights were determined via the fuzzy analytic hierarchy process with an integrated modeling framework for key parameters. Finally, the risk level of the check dam system in the Jiuyuangou Basin was assessed based on the comprehensive score. The results show that (1) nearly half of the check dams are at mild risk, approximately 25% are at moderate risk, and a few are basically safe. (2) Among various types of risk, the distribution of engineering risk is relatively uniform, environmental risk is generally high, loss risk is relatively concentrated, and management risk is particularly prominent. This research provides a scientific foundation for optimizing check dam governance, enhancing sediment control, and strengthening ecological service functions in vulnerable watersheds. Full article

The rising demand for elderly care amid ongoing nursing shortages has highlighted the limitations of conventional alert systems, which frequently generate excessive alerts and contribute to alarm fatigue. The objective of this study is to develop a hybrid, context-aware nurse alerting framework for long-term care (LTC) facilities that minimizes redundant alarms, reduces alarm fatigue, and enhances patient safety and caregiving balance during multi-person care scenarios such as mealtimes. To do so, we aimed to intelligently suppress, delay, and validate alerts by integrating rule-based logic with Large Language Model (LLM)-driven semantic reasoning. We conducted an experimental study in a real-world LTC environment involving 28 elderly residents (6 high, 8 medium, and 14 low care levels) and four nurses across three rooms over seven days. The proposed system utilizes video-derived skeletal motion, care-level annotations, and dynamic nurse–elderly proximity for decision making. Statistical analyses were performed using F1 score, accuracy, false positive rate (FPR), and false negative rate (FNR) to evaluate performance improvements. Compared to the baseline where all nurses were notified (100% alarm load), the proposed method reduced average alarm load to 27.5%, achieving a 72.5% reduction, with suppression rates reaching 100% in some rooms for some nurses. Performance metrics further validate the system’s effectiveness: the macro F1 score improved from 0.18 (baseline) to 0.97, while accuracy rose from 0.21 (baseline) to 0.98. Compared to the baseline error rates (FPR 0.20, FNR 0.79), the proposed method achieved drastically lower values (FPR 0.005, FNR 0.023). Across both spatial (room-level) and temporal (day-level) validations, the proposed approach consistently outperformed baseline and purely rule-based methods. These findings demonstrate that the proposed approach effectively minimizes false alarms while maintaining strong operational efficiency. By integrating rule-based mechanisms with LLM-based contextual reasoning, the framework significantly enhances alert accuracy, mitigates alarm fatigue, and promotes safer, more sustainable, and human-centered care practices, making it suitable for practical deployment within real-world long-term care environments. Full article

This study proposes a high-contrast photoacoustic (PA) imaging methodology based on a dual-wavelength confocal metalens, designed to monitor the dissemination of cancer cells and to inform subsequent cancer treatment strategies. The metalens is composed of two metasurfaces that perform filtering and focusing functions, effectively reducing the cross-talk between the two wavelengths of light in space and achieving a confocal effect. Furthermore, to minimize process complexity, a uniform material system of silicon dioxide (SiO₂) and titanium dioxide (TiO₂) is employed across the different metasurfaces of the metalens. The designed metalens has a radius of 25 µm and an operational focal length of 98.5 µm. The results confirm that this dual-metasurface design achieves high focusing efficiency alongside precise focusing capability, with the deviations of the actual focal lengths for both beams from the design values being within 1.5 µm. Additionally, this study developed a skin tissue model and simulated multi-wavelength photoacoustic imaging of cancer cells within the human body by integrating theories of radiative transfer, photothermal conversion, and the wave equation. The results demonstrate that the enhancement trend of the reconstructed signal closely matches the original signal, confirming the model’s excellent fitting performance. The sound pressure values generated by cancer cells are significantly higher than those of normal cells, proving that this method can effectively distinguish cancerous tissue from healthy tissue. This research provides new theoretical support and methodological foundations for the clinical application of multi-wavelength photoacoustic imaging technology. Full article

This paper represents initial research with the aim to establishes a baseline for subsequent research into AI-based construction monitoring, building upon the NORMENG project in Croatia, which previously integrated photogrammetry, laser scanning, and BIM-based methods. The study tests general purpose AI’s ability to detect materials and estimate quantities, aiming to assess whether a broad, context-aware AI system can match the precision of specialized, domain-specific tools or even human work needed for productivity estimations. While the AI demonstrated potential for basic entity detection and preliminary quantity estimations, it showed significant limitations in delivering fine-grained, temporally accurate breakdowns without targeted adaptation. The findings underscore the need for domain-specific fine-tuning and human-in-the-loop validation to transform AI into a reliable tool for construction management. This initial contribution provides empirical insights and actionable recommendations for advancing automated progress monitoring in the construction sector. Full article