Search Results (2,933)

Background/Objectives: Falls among older adults are a major public health concern. Although instrumented posturography provides objective balance and fall-risk assessment, its cost and limited portability restrict widespread use. This study aimed to examine the construct and concurrent validity of center of pressure (COP) path length measured using a Wii Balance Board (WBB) in relation to a clinically established posturographic fall-risk construct in community-dwelling older adults and to explore its discriminatory performance across multiple sensory postural conditions. Methods: Sixty adults aged ≥ 65 years participated in this cross-sectional study. COP path length was measured using a WBB under eight postural conditions and compared with the Fall Index derived from a conventional posturography system (Tetrax^Ⓡ). Functional performance was assessed using the Four Square Step Test and the Five Times Sit-to-Stand test. Pearson correlation, receiver operating characteristic (ROC), and exploratory regression analyses were performed. Results: COP path length showed significant positive correlations with the Tetrax^Ⓡ Fall Index across all conditions (r = 0.349–0.561, p < 0.01) and with functional performance tests under most postural conditions (p < 0.05), except for the Normal stability, Open eyes (NO) condition. ROC analysis demonstrated acceptable-to-good discriminatory performance for classifying Tetrax^Ⓡ Fall Index-based risk status (AUC = 0.783–0.865), with the NO condition showing the highest discriminatory capability (AUC = 0.865). Exploratory regression models based on selected postural conditions explained 12.1–40.7% of the variance in the reference Fall Index. Conclusions: COP path length measured using a WBB demonstrated construct validity and acceptable discriminatory capacity in relation to a conventional posturographic fall-risk construct in community-dwelling older adults. These findings support the exploratory feasibility of simplified WBB-based balance assessment approaches for community and clinical screening contexts. Further longitudinal studies incorporating prospective fall outcomes are required to establish predictive validity and broader clinical applicability. Full article

Rockfall from slope unstable rock masses is a typical geological hazard induced by brittle failure, with abrupt occurrence, limited macroscopic deformation before failure, and a short warning lead time. Conventional static analysis methods are useful for design-stage stability checks, but they cannot continuously capture structural-plane damage or update the stability state in real time. Dynamic evaluation based on structural dynamics links measurable parameters such as natural frequency, damping ratio, mode shape, vibration trajectory, wave velocity, and energy dissipation to the degradation of structural planes. This review synthesizes the dynamic behavior mechanism, parameter system, theoretical models, sensing technologies, and engineering applications for slope unstable rock masses. Different from previous reviews that mainly summarize rockfall monitoring or conventional slope stability analysis, this paper organizes the literature by failure mode, monitoring scale, model assumptions, field validation, uncertainty sources, and engineering applicability. The single-degree-of-freedom models for sliding-, toppling-, and falling-type rock masses, multi-block chain-collapse models, and data-physics dual-driven surrogate models are compared critically. Contact monitoring based on MEMS sensors, non-contact LDV monitoring, acoustic emission, microseismic monitoring, coda wave interferometry, and cloud-edge early-warning architectures are further reviewed. Key challenges include field-scale validation under heterogeneous and anisotropic geological conditions, environmental compensation, robust threshold calibration, and probabilistic linkage between dynamic indicators and failure probability. The review provides guidance for selecting dynamic evaluation models, designing field monitoring systems, and developing full-life-cycle digital-twin platforms for rockfall risk mitigation. Full article

Background Although cycling has definite health benefits, it is certainly not a risk-free activity; its increasing use is associated with a rise in accidents. This study aims to characterize cycling injuries and their associated factors in a tertiary trauma center, including injury severity, accident circumstances, and in-hospital costs. Methods: A retrospective observational study was conducted on patients over 15 years of age hospitalized after a cycling accident. Collected variables included the characteristics of the accident, the epidemiology of musculoskeletal injuries, helmet use, injury severity as assessed using the Abbreviated Injury Scale (AIS), the Injury Severity Score (ISS), and costs. Results: A total of 131 patients were included, of whom 90.8% were male, with a mean age of 43.2 ± 14.1 years. Most accidents were due to falls (83.7%). Accidents occurred in urban areas (56.3%), inter-urban roads (28.1%), and rural areas (15.6%). Upper limb fractures, particularly clavicle fractures (13.7%), were the most frequent injuries (31.0%). Traumatic brain injury (TBI) was present in 30.0% of patients, and 17.6% were polytraumatized. Injury severity was higher in males (p = 0.009) and in collisions compared with falls (p = 0.033). It was also correlated with length of hospital stay (r = 0.376). Patients with TBI exhibited significantly higher ISSs (p < 0.001). Helmet use was reported in 71.1% of patients and was more frequent in rural areas (p < 0.001) and associated with lower neurological AIS scores (p = 0.031). The mean cost per patient was €8545 ± 15,298, increasing with severity of injury (p < 0.001), and was higher in polytraumatized patients (p < 0.001) and in those with TBI. Conclusions: Cycling accidents most frequently resulted in upper limb fractures. Helmet use was more common where mandatory and was associated with less severe neurological injuries but not with a lower incidence of TBI. Costs increased with injury severity, particularly in patients with TBI and longer hospital stays. Full article

Objectives: Fear of falling (FoF) is a common psychological phenomenon in later life and is often accompanied by avoidance behavior and activity restriction. Although FoF is associated with anxiety, depressive symptoms, reduced self-efficacy, and fear of loss of autonomy, older adults with FoF may differ substantially in the configuration of these characteristics. The present study aimed to identify data-derived profiles of older adults based on FoF, avoidance behavior, self-efficacy, and fear of loss of autonomy, and to examine profile-specific psychological predictors of FoF and avoidance behavior. Methods: The main analytical sample included 217 older adults aged 60–97 years (M = 76.45, SD = 10.14) with Mini-Mental State Examination scores of 20 or higher. Latent profile analysis was conducted using FoF, avoidance behavior, self-efficacy, and fear of loss of autonomy. Anxiety components, depressive symptoms, coping strategies, pain catastrophizing, and loneliness-related indicators were examined in class-specific regression models. The stability of the class solution was tested across different MMSE cut-off scores. Between-class comparisons were conducted for functional, fall-related, socio-demographic, and psychological indicators. Results: A three-class solution was selected and interpreted as adaptive, vulnerable, and maladaptive profiles. The profile structure remained relatively consistent across MMSE cut-off scores, including in the broader sample with MMSE ≥ 15. The classes did not differ significantly in postural balance or number of falls, suggesting that the profiles could not be fully explained by objective fall-risk indicators. Significant between-class differences were found for age, daily pain level, and state social defense. Class-specific regression models suggested that psychological variables associated with FoF and avoidance behavior differed across profiles. Pain appraisal and emotion-related coping were more relevant in the adaptive profile, phobic anxiety and anxious appraisal of future events in the vulnerable profile, and anxiety-related, depressive, interpersonal, and coping-related factors in the maladaptive profile. All reported associations remained significant after false discovery rate correction. Conclusions: FoF and avoidance behavior are related but not identical phenomena and vary across data-derived psychological profiles. A profile-oriented approach may provide a more differentiated understanding of activity restriction in older adults and help identify profile-specific targets for psychological support. Full article

Why are essential workers (also known as key workers) priced out of the urban areas where essential services are concentrated? This paper addresses that question by linking residential sorting to the governance of land and housing markets in Auckland, New Zealand. Drawing on bid rent theory and motivated by Crane’s theoretical framework, this study examines how households trade off urban accessibility against housing costs with varying degrees of job location uncertainties and time pressure. The analysis uses the micro-level household data from Statistics New Zealand (Stats NZ)’s Integrated Data Infrastructure (IDI) to examine how key-worker households position themselves within the city’s rental market relative to other working households. The results show a clear urban land rent gradient: rents fall with distance from the city centre. However, access to the central location is not evenly distributed across workers. Key workers, whose jobs are typically tied to more fixed workplaces, are more inclined to live farther from the city centre to lower housing costs. By contrast, workers facing tighter time constraints, especially those working longer hours, show a stronger preference for living near the CBD to improve work proximity and reduce commuting burdens. This pattern remains evident among private vehicle commuters, suggesting that time pressure, rather than transport mode alone, is an important factor shaping residential location choice. The paper argues that this is not simply a housing market outcome but also a land-governance problem. When central land values rise without corresponding housing options for key workers, cities risk pushing socially necessary labour towards peripheral areas. The findings highlight the need for land-use and housing interventions that improve the spatial match between where key workers live and where urban services are most needed. Full article

Arthropod natural enemies—encompassing predators and parasitoids—form the backbone of sustainable agriculture, delivering irreplaceable ecosystem services via biological pest suppression. Driven by global demand for eco-friendly alternatives to synthetic pesticides, research in this domain has grown sharply over the past decade. Here, we report a systematic bibliometric analysis of 6515 Web of Science Core Collection papers focused on arthropod natural enemies in biological control (2016–2025), with the goal of charting the field’s intellectual structure. Performance metrics confirmed an initial rapid increase from 2016 to 2019 followed by a plateau and a slight rise in 2025, with the US, China, and Brazil dominating output. Keyword co-occurrence networks pinpointed core themes, including conservation biological control, predatory mites, and integrated pest management (IPM). Temporal trends further revealed a pivot toward applied work on invasive pest systems. Co-citation analysis uncovered six foundational research clusters, while bibliographic coupling of 2021–2025 papers uncovered five active emerging subfields: landscape ecology and habitat manipulation, tri-trophic interaction mechanisms, high-impact invasive pest biocontrol, non-target risk assessment for introduced agents, and fall armyworm integrated management. We synthesize cross-cutting implications and outline future priorities—including AI-enabled rearing systems, functional biodiversity boosting, climate adaptation, and multifunctional landscape tuning. By consolidating historical progress and forward-looking directions, this framework empowers researchers, extension practitioners, and policymakers to scale sustainable pest management worldwide. Full article

With the rapid proliferation in communication devices and the expansion of applications, future sixth-generation (6G) networks are expected to enable a truly connected world. They will allow large-scale use cases, such as the Internet of Things (IoT) and unmanned aerial vehicles (UAVs), providing significantly faster and more innovative services ubiquitously. However, challenges remain, particularly in security. The growing number of devices and increased connectivity may lead to a larger attack surface. Many emerging technologies are actively addressing these security and privacy concerns, ensuring that we can benefit from the advantages of 6G networks and applications without falling victim to malicious attacks. In this paper, we conduct a comprehensive literature review of emerging technologies for secure communication in 6G networks, including artificial intelligence (AI) and machine learning (ML), blockchain technology, quantum-safe communication, and physical-layer security. First, we discuss the architecture of 6G networks from a security perspective. Second, we review existing surveys on 6G security issues and provide a quantitative analysis to identify research gaps, including technology-driven silos and domain fragmentation. Third, we develop a hierarchical taxonomy of security challenges and attacks in 6G networks, covering physical-layer attacks, network-level threats, device vulnerabilities, data privacy concerns, and emerging application-specific risks. We then examine the roles of key enabling technologies and present a mapping between security threats and corresponding technological solutions, along with a unified evaluation framework to facilitate cross-technology comparison. Furthermore, we propose an integrated multi-technology security framework and discuss practical deployment challenges by bridging the gap between simulation-based studies and real-world implementations. Finally, we outline concrete future research directions for advancing secure 6G communication systems. Full article

Background/Objectives: Listeria monocytogenes is a critical foodborne pathogen, with poultry products serving as a potential reservoir. Its ability to form biofilms may aid in its persistence on processing equipment and food-contact surfaces, while antibiotic resistance complicates efforts to control and treat infections. This study aimed to characterize, in parallel, the biofilm-forming capacity and antibiotic susceptibility of a large collection of poultry-derived L. monocytogenes isolates (n = 93) to better understand their potential for persistence and to clarify how the biofilm phenotype may relate to the bacterial antibiotic response and to inform risk assessment and targeted control strategies along poultry processing and supply chains. Methods: Biofilms were evaluated on polystyrene microtiter plates at 12 and 30 °C in a nutrient-rich laboratory medium. Susceptibility to eight clinically and food-relevant antibiotics was tested using disk diffusion and interpreted according to European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints when available. Results: At 30 °C for 48 h, 69.9% of isolates were classified as weak biofilm formers and 30.1% as non-biofilm formers, whereas at 12 °C for 120 h, 55.9% were weak, 16.1% moderate, and 28.0% non-biofilm formers, with no strong biofilm producers identified under either condition. Overall, the isolates remained largely susceptible to ampicillin, penicillin G, vancomycin, tetracycline, and chloramphenicol, with 87.3% of inhibition zones across all drugs falling within the 20–29 mm and 30–39 mm categories, while small subpopulations showed reduced susceptibility or resistance to trimethoprim–sulphamethoxazole (TMP-SMX) and, particularly, erythromycin and streptomycin. No consistent correlation was found between biofilm-forming ability and antibiotic susceptibility, indicating that these phenotypic traits are largely independent in this collection. Conclusions: These findings reveal that poultry-derived L. monocytogenes isolates can form weak to moderate biofilms under the tested monoculture conditions while generally maintaining susceptibility to first-line antibiotics. However, the development of macrolide- and aminoglycoside-resistant subpopulations, along with the potential for increased colonization within complex multispecies biofilms in real processing environments, emphasizes the importance of ongoing integrated surveillance across animal food systems. Full article

The coexistence of obesity, osteoporosis, and sarcopenia has been associated with adverse outcomes such as risk of falls, fractures, immobility, disability and frailty, yet data from Latin American populations are scarce. This study aimed to determine the prevalence and associations of obesity, osteoporosis, and sarcopenia—individually and combined—with frailty in Mexican elderly women. We conducted a cross-sectional study in which patients with body mass index < 18.5 kg/m², uncorrected sensory deficits, immobility, musculoskeletal diseases, or patients with implanted devices were excluded. Frailty was assessed using the FRAIL scale, obesity by body fat percentage, osteoporosis according to American Association of Clinical Endocrinology (AACE) guidelines and sarcopenia following the European Working Group on Sarcopenia in Older People-2 (EWGSOP2) recommendations. A total of 115 participants aged ≥60 years were assessed between January and June 2025. Frailty was present in 21.7% of the patients; 67.0% had obesity, 72.2% osteoporosis, 20.0% sarcopenia and 13.0% osteosarcopenic obesity. Sarcopenic phenotypes were associated with frailty: odds ratios (95% CI) were 3.05 (1.12–8.26) for sarcopenia, 4.23 (1.42–12.55) for sarcopenic obesity and 3.98 (1.28–12.40) for osteosarcopenic obesity. Sarcopenic phenotypes showed associations with frailty in Mexican elderly women. Full article

Background and Objectives: Aging is associated with sarcopenia and increased adiposity, which may impair mobility and increase fall risk. Although sarcopenic obesity is associated with an increased fall risk compared with either condition alone, evidence regarding sex-specific associations remains limited. This study aimed to examine the sex-specific associations between sarcopenia, obesity parameters, and falls among older Korean community-dwellers. Materials and Methods: This cross-sectional study analyzed baseline data from the Korean Frailty and Aging Cohort Study, including 2039 participants aged 70–84 years (men, 973; women, 1066). Sarcopenia was defined using the Asian Working Group for Sarcopenia 2025 criteria, and obesity was categorized as general (body mass index and percentage body fat [PBF]) or central obesity (waist circumference [WC] and conicity index [C-index]). Falls were assessed by self-report. Logistic regression analyses were performed after adjusting for potential confounders. Results: Among 2039 participants, 395 (19.4%) reported falls. In the total population, higher PBF and C-index were independently associated with increased fall risk after adjustment. Men showed significantly higher odds of falls with low handgrip strength, high WC, PBF, and C-index than women. In women, only low appendicular skeletal muscle mass index was independently associated with falls. Sarcopenic obesity was not significantly associated with falls in either sex. Conclusions: Although sarcopenic obesity itself was not independently associated with falls in either sex, distinct sex-specific associations were observed between individual components of sarcopenia, obesity, and fall risk among older Korean adults. Reduced muscle strength and central obesity were more strongly associated with falls in men, whereas reduced muscle mass was independently associated with falls in women. These findings suggest that sex-specific approaches targeting muscle function and body composition may be important for fall prevention in aging populations. Full article

Falls among older adults are a major public health concern. Older adults living in low-income housing (LIH) are at higher risk of falls due to disadvantages linked to social determinants of health, yet remain underrepresented in research. This study aimed to assess the feasibility of a program addressing fear of falling and its consequences on activity levels among older adults living in LIH in Côte-des-Neiges (Montreal, QC, Canada). A mixed-methods pilot feasibility study was conducted using Bowen et al.’s framework, drawing on data collected through questionnaires, observation grids, attendance records, and semi-structured interviews. The program consisted of six 90 min sessions designed to enhance participants’ confidence in preventing falls while promoting engagement in activities. Fourteen older adults (mean age = 75.5 years) were recruited. Outcome data on fall-related psychological factors, activity engagement, and knowledge about falls were collected before and after the program. Moreover, older participants’ perceived benefits were assessed following program completion. Post-program interviews with older adults, facilitators, and a community field worker were conducted to further explore program feasibility, including its acceptability, implementation, and integration. The program showed strong acceptability and a high attendance rate (95%). Although no statistically significant pre-post changes were observed in the outcome variables, older participants reported several benefits at post-test, including improved knowledge about fall prevention (100%) and greater confidence in their ability to avoid falls (85%). These findings support the feasibility of implementing this culturally adapted fall prevention program in similar LIH settings and provide valuable insights for its refinement and future research. Further investigation is warranted to examine the program’s feasibility across other LIH settings and linguistic groups, as well as to assess its effectiveness. Full article

This study examines Connecticut’s strategic approach to electric vehicle (EV) workforce development within the framework of the Bipartisan Infrastructure Law (BIL) and its National Electric Vehicle Infrastructure (NEVI) program. Amid the U.S. goal to transition to a zero-emission vehicle fleet by 2050, this research investigates whether Connecticut’s current policies sufficiently address the need to reskill automotive mechanics into qualified EV technicians. Using a qualitative case study methodology, semi-structured interviews were conducted with state workforce representatives and analyzed through inductive coding within Kotter’s 8-Step Change Model. Findings reveal that while Connecticut aligns with federal NEVI goals for infrastructure, it lacks a dedicated budget and clearly defined pathways for technician training. Stakeholder collaboration remains fragmented, and efforts to empower workforce transformation are in the early stages. The study concludes that Connecticut risks falling behind unless it integrates a robust workforce development strategy that includes cross-sector partnerships, pilot training programs, and transparent certification pathways. These findings highlight the importance of aligning state-level EV infrastructure planning with human capital development and offer actionable insights for other states navigating similar transitions. Full article

This study systematically explores the underlying mechanisms of collaborative innovation driving the green transformation of traditional energy enterprises. Existing research primarily focuses on enterprise scale and overall competitiveness, rarely delving into these specific collaborative pathways. Furthermore, studies employing evolutionary game theory to analyze the tripartite relationship among the government, traditional energy, and emerging technology enterprises remain fragmented, failing to fully capture the dynamic mechanisms of multi-stakeholder strategic choices. To bridge these gaps, this paper constructs a tripartite evolutionary game model incorporating coordination costs and the benefit distribution ratio to explore their influence mechanisms. Replicator dynamics equations are employed to identify stable cooperation conditions, overcoming traditional two-party framework constraints. Additionally, MATLAB R2024b numerical simulations validate the theoretical findings. The results reveal two evolutionarily stable equilibrium points. First, higher initial willingness among participants accelerates the system’s evolution toward a stable cooperative state. Second, coordination costs induced by information asymmetry act as a core bottleneck that deters participation and risks collaborative collapse. Third, targeted government incentives and a rational benefit distribution ratio directly determine cooperation willingness; notably, enterprises adopt collaborative strategies only when this ratio falls between 0.27 and 0.69. Fourth, fair and transparent supervision is crucial for mitigating trust deficits and distribution disputes. Ultimately, scientifically designing incentives, optimizing benefit structures, promoting information sharing, and establishing robust supervision effectively facilitate a sustainable tripartite collaborative innovation pattern. Full article

Cadmium is a widespread environmental xenobiotic that poses serious risks to hepatic, renal, and male reproductive functions. Natural compounds such as silymarin, a bioactive extract from Silybum marianum, have gained attention for their protective potential against xenobiotic-induced toxicity. This study investigated whether subchronic oral administration of silymarin (30 mg/kg) mitigates cadmium-induced toxicity (5 mg/kg) in adult rats over six weeks. Twenty-four rats were assigned to four groups: control, cadmium-exposed, silymarin-treated, and co-treated. Biochemical, hematological, oxidative stress, and reproductive parameters were assessed. Sperm quality was evaluated using CASA, and testicular tissues were examined histologically. Cadmium exposure significantly reduced body weight (−30.8%), elevated transaminases (AST, ALT; p < 0.01), increased serum creatinine and total cholesterol, and induced multi-organ oxidative stress, as reflected by elevated malondialdehyde and markedly reduced SOD, CAT, and thiol group levels in testicular, hepatic, and renal tissues (p < 0.01). Sperm concentration dropped from 75.2 to 21.8 × 10⁶/mL, with total motility falling to 35% and progressive motility to 18%, accompanied by severe seminiferous tubule degeneration (Score III in 5 rats). Co-administration of silymarin partially restored these parameters, sperm concentration recovered to 38.5 × 10⁶/mL, total motility improved to 50.2%, and antioxidant enzyme activities and liver/kidney biomarkers showed significant but incomplete recovery (p < 0.05). Molecular docking revealed favorable binding affinities of silybin toward GPx (−8.4 kcal/mol), CAT (−8.3 kcal/mol), and SOD (−6.4 kcal/mol), offering a preliminary computational hypothesis suggesting possible interactions between silybin and antioxidant enzymes, pending experimental validation. Silymarin alone exerted no adverse effects. These findings establish silymarin as a partial but promising multi-organ cytoprotectant against cadmium toxicity, and highlight the need for future studies optimizing dosing strategies, exploring longer treatment durations, and investigating combination approaches with metal chelators or Nrf2-activating agents to achieve complete tissue recovery. Full article

Process data plays a vital role in diagnosing fault sources in chemical production. However, such data contain rich process information and are often sensitive, making direct analysis infeasible due to privacy concerns. Although federated learning mitigates data leakage risks, the conventional averaging strategy falls short in achieving high fault identification accuracy, especially under non-independent and identically distributed (non-IID) client data. To overcome this challenge, we propose a personalized federated learning framework, in which a Takagi–Sugeno (T–S) fuzzy fusion rule is designed. Then, the personalized model is constructed through a structured procedure: fuzzification of model parameter distances, definition of fuzzy rules, fuzzy inference, and defuzzification. Moreover, layer-wise fusion is employed to enhance the precision of aggregation. Evaluations on the Tennessee Eastman (TE) process demonstrate that our method achieves superior fault identification accuracy. The results validate the efficacy of the proposed Fuzzy Rule-Based Federated Layer-wise Fusion (FedFZ) framework in industrial fault diagnosis under heterogeneous data distributions. Full article