Search Results (436)

Introduction: This study evaluates the efficacy of a nurse practitioner-managed, computer algorithm-supported institutional fracture liaison service (FLS) that provides treatment recommendations for patients with hip fractures. Methods: A retrospective study included patients hospitalized in the Orthopedic ward with hip fractures between April 1 and October 31. The decision-making algorithm recommends zoledronic acid as the default medication, except for patients younger than 65 years, with estimated glomerular filtration rate (eGFR) <35 or prior osteoporosis therapy, who are ordered to undergo endocrinology consultation. Patients with vitamin D deficiency/insufficiency are given a loading dose. Results: Two hundred and eight hip fracture patients were identified. The cohort was predominantly female (137/208, 65.9%); the mean age was 79.9 ± 9.6 years. Nurse practitioner evaluation was performed in 200/208 patients (96.2%). The algorithm provided a treatment recommendation in 140 out of 200 (70.0%), while 60 out of 200 (30.0%) required an endocrinology consultation. A Vitamin D loading dose was given in 89/99 (89.9%) deficiency and 44/62 (71.0%) insufficiency cases. Conclusions: This simplified algorithm-based FLS model demonstrated practicality and feasibility in providing therapeutic recommendations with minimal physician intervention. Full article

This article presents an integrated assessment of pasture ecosystem degradation under conditions of extreme aridity in the Atyrau Region, where high livestock density, limited grazing capacity, and institutional fragmentation of land tenure exacerbate degradation risks. The study aimed to conduct a spatio-temporal analysis of pasture conditions and identify critical load zones to support sustainable management strategies. The methodology was based on a multi-factor Anthropogenic Load (AL) model integrating (1) calculation of pasture load (PL) using 2023 agricultural statistics with livestock numbers converted into livestock units; (2) spatial analysis of grazing concentration through Kernel Density Estimation in ArcGIS 10.8; (3) assessment of infrastructural accessibility (Accessibility Index, A_i); and (4) quantitative evaluation of institutional land use organization (Institutional Index, I_i). This integrative approach enabled the identification of stable, transitional, and critically overloaded zones and provided a cartographic basis for sustainable management. Results revealed persistent degradation hotspots within 3–5 km of water sources and settlements, while up to 40% of productive pastures remain excluded from use. The proposed AL model demonstrated high reproducibility and applicability for environmental monitoring and regional land use planning in arid regions of Central Asia. Full article

The intersection of autism and motherhood/parenthood remains largely underexplored, particularly within the Spanish context. Autistic mothers and birthing parents are often silenced, with limited representation and scarce accessible information, contributing to a broader social and institutional unawareness. This study explores the postpartum experiences of autistic and non-autistic mothers during the first two years following childbirth. Twelve semi-structured interviews were conducted with six autistic and six non-autistic mothers and analyzed using Reflexive Thematic Analysis. Three key themes were constructed, as follows: (1) Ups and Downs: Navigating Emotional and Sensory Experiences, highlighting the intense sensory and emotional load of early motherhood; (2) Lack of Information and Support: The Root of Increased Vulnerability, addressing gaps in institutional support and knowledge; and (3) The Social Dimensions of Early Postpartum: Tensions and Expectations, focusing on family and societal pressures as well as identity struggles. While experiences overlapped in several areas, two tentative distinctions were observed, as follows: autistic mothers appeared to favor self-guided strategies (e.g., books, personal guidelines), whereas non-autistic mothers relied more on professional guidance; additionally, autistic mothers expressed a stronger preference for autonomy, while non-autistic mothers often valued companionship. These findings underscore the urgent need for healthcare professionals to receive training on autistic motherhood/parenthood and for the development of tailored postpartum care guidelines to ensure inclusive, responsive support. Full article

Glazed façades play a decisive role in building energy performance, particularly in high-radiation equatorial climates. This study examines the thermal behavior and economic feasibility of three glazing systems—10 mm monolithic clear glass, laminated solar-control glass, and selective double glazing—applied to the Plataforma Gubernamental Norte, the largest institutional building in Ecuador. Dynamic simulations using DesignBuilder with the EnergyPlus engine assessed solar gains, HVAC demand, and operative temperatures, complemented by a sensitivity analysis of SHGC, U-value, and Tvis. Results indicate that selective double glazing reduced annual HVAC consumption by 78.21% (110.6 MWh), while laminated glazing achieved a 55.40% reduction. SHGC and U-value emerged as the most influential parameters, whereas Tvis had no impact on energy loads. Despite strong technical performance, the economic analysis revealed payback periods exceeding 235 years under Ecuador’s subsidized tariff (USD 0.10/kWh), compared to the 18–25 years commonly observed in Europe. This highlights the “efficiency paradox”: advanced glazing solutions deliver significant energy savings but remain financially unfeasible in subsidy-driven contexts. The findings underscore the need for policy reforms to better align façade design strategies with energy resilience, an issue particularly relevant after Ecuador’s 2024 electricity crisis and ongoing debates on subsidy elimination. Full article

Musculoskeletal injuries are a growing concern among adolescent athletes, with significant physical and psychological consequences. This integrative literature review aimed to analyze the risk factors associated with musculoskeletal injuries in adolescents engaged in sports and to explore the role of nursing interventions in their prevention. A systematic search was conducted across four databases and one gray literature source, including studies published between 2014 and 2024. Three descriptive studies were included, with evidence levels ranging from 3 to 4, according to the Joanna Briggs Institute classification. The main findings highlight that risk factors for musculoskeletal injuries include excessive training loads, inadequate sports technique, lack of professional supervision, improper use of equipment, and failure to recognize early signs of discomfort. Preventive nursing interventions were shown to be effective, particularly those focused on health education, proprioceptive training, and continuous monitoring. Multidisciplinary collaboration between nurses, coaches, and other health professionals emerged as a key strategy in creating safe sporting environments. Despite limitations such as the scarcity of studies on nursing-specific interventions in diverse sports contexts, this review supports the potential of structured, evidence-based nursing actions to reduce musculoskeletal injuries incidence, promote safer sports practices, and enhance adolescent athletes’ health outcomes. Full article

Accurate solar radiation data are essential for reliable building energy simulations, particularly for policy making. However, uncertainty in solar input, especially in regions with limited ground-based measurements, can significantly affect simulation outcomes. This study investigates the impact of different solar radiation datasets on building energy performance simulations across two climatically distinct years, 2015 and 2024, in a subtropical urban environment. Solar inputs from ERA5, CAMS, and NASA POWER were compared against a regional reference from the Brazilian National Institute for Space Research (INPE). In addition to energy simulations, the datasets were evaluated using statistical metrics including root mean square error (RMSE), mean bias error (MBE), and Pearson correlation. NASA POWER showed the best agreement with ground data and yielded simulation results that were reasonably aligned with observed cooling loads and thermal comfort in both years, with slight overestimations in cooling demand and overheating hours. CAMS maintained consistent performance across both years and produced the lowest cooling and overheating estimates, slightly underestimating results while closely matching monthly trends. ERA5 exhibited the largest positive bias in solar input, particularly in DNI, leading to substantial overestimation of cooling demand, up to 34% in 2024, especially during heatwaves. These discrepancies highlight the sensitivity of energy simulations to solar input selection and the importance of using validated high-quality datasets to ensure reliable modeling under increasing climate variability. Full article

The durability of Fiber-Reinforced Polymer (FRP) bars is typically evaluated using accelerated conditioning protocols (ACP), which are applied to bar samples, either directly exposed or embedded in small concrete specimens, under aggressive environmental conditions. Thus, this study investigates the applicability of the ACPs recommended by ACI440.9R (2015), from the American Concrete Institute, to assess the potential effects of chloride exposure on reinforced concrete beams. Twelve beams—six reinforced with steel and six with Glass Fiber-Reinforced Polymer (GFRP)—were tested under two scenarios: (1) a reference condition, with beams stored for 1000 h in a controlled laboratory environment, and (2) a conditioned condition, where beams were immersed in a 3.5% NaCl solution at 50 ± 3 °C for 1000 h prior to beam casting. After, the beams were evaluated through three-point bending tests, focusing on load–deflection behavior, failure modes, crack patterns, and strain distribution in concrete and reinforcement. The results indicated that chloride exposure adversely affected both steel and GFRP-reinforced beams. Steel-reinforced concrete beams exhibited a 12% reduction in load-bearing capacity due to steel corrosion, while the GFRP-reinforced concrete beams showed a 10% reduction in load-bearing capacity due to water absorption by the GFRP. Full article

This study examines how platform-based artificial intelligence resources (PAIRs) influence sustainable performance in e-business ecosystems by shaping stakeholder cognition and behavior. Guided by the Resource-Based View (RBV), the Theory of Planned Behavior (TPB), and institutional theory, we examine the psychological mechanisms—particularly trust in AI and environmental identity—that mediate the relationship between PAIRs and green value co-creation (GVC), with sustainable development (SD) acting as a moderating factor. Drawing on survey data from 466 platform managers in China’s digital economy hubs (Yangtze River Delta, Pearl River Delta, Beijing-Tianjin), covering diverse industries (e-commerce, consumer goods, healthcare), our data suggest that PAIRs may influence firm performance via GVC, and that this association appears to be stronger under high-SD contexts. Our results underscore the importance of responsible and psychologically informed AI design—such as algorithmic transparency, cognitive load reduction, and ethical calibration—to facilitate stakeholder trust and pro-environmental engagement. This research contributes both theoretically and practically to elucidating how AI integration in e-business can be leveraged for responsible innovation and sustainable value creation. Full article

Administrative law is about articulating norms and promoting the adoption and enforcement of human behaviour practices in areas where individual choice conflicts with the public good. Law must fairly describe to the citizenry what is allowed and what is conditionally restricted by administrative law and what is prohibited in criminal law. The conditional use of animals in industrial production of food and fibre for human consumption is allowed (non-criminal), but the conditions which are considered acceptable by society are changing. Humane transportation of livestock is a public concern and the temptation of transporters to load as many animals as possible is an easily understood risk to animal welfare. Livestock hauling has been regulated in Canada since 1857 and is currently regulated by the Health of Animals (Act) Regulations Part XII and enforced nationally by the Canadian Food Inspection Agency. After over 30 years of challenging industry consultation, a major revision to the humane transport provisions was proclaimed in 2020. Surprisingly, the revision failed to articulate numerical thresholds that clearly indicate an overcrowding violation. This paper reviews 20 cases from 2004 to 2024 where transporters appealed a penalty for overcrowding livestock transported by land. The paper describes the decision to penalize transporters where there is no bright line definition of an offence. The paper suggests both regulator and regulated choose to work in an intentionally inefficient institutional arrangement, preferring opacity to clarity in what constitutes a violation in law, because “that’s the way we like it”. Full article

Decentralized electricity markets are increasingly shaped by the proliferation of distributed energy resources, the rise of prosumers, and growing demands for privacy-aware analytics. In this context, federated learning (FL) emerges as a promising paradigm that enables collaborative model training without centralized data aggregation. This review systematically explores the application of FL in energy systems, with particular attention to architectures, heterogeneity management, optimization tasks, and real-world use cases such as load forecasting, market bidding, congestion control, and predictive maintenance. The article critically examines evaluation practices, reproducibility issues, regulatory ambiguities, ethical implications, and interoperability barriers. It highlights the limitations of current benchmarking approaches and calls for domain-specific FL simulation environments. By mapping the intersection of technical design, market dynamics, and institutional constraints, the article formulates a pluralistic research agenda for scalable, fair, and secure FL deployments in modern electricity systems. This work positions FL not merely as a technical innovation but as a socio-technical intervention, requiring co-design across engineering, policy, and human factors. Full article

Bridge cranes generally have a significant disparity between their actual service life and design life. If they are scrapped according to the design life, it is likely to result in resource wastage or pose potential safety hazards due to extended service. Existing studies have not thoroughly examined the coupling relationship among actual working conditions, structural damage, and load-matching strategies. It is difficult to achieve real-time and accurate adaptation between loads and the carrying capacity of equipment, and thus cannot effectively narrow this life gap. To this end, this paper defines a digital twin system framework for crane load adaptive matching, constructs a load adaptive matching optimization model, proposes a method for developing a digital twin system for bridge crane load adaptive matching, and builds a digital twin system platform centered on virtual-real mapping, IoT connectivity, and data interaction. Detailed experimental verification was conducted using the DQ40 kg-1.8 m-1.3 m light-duty bridge crane. The results demonstrate that this method and system can effectively achieve dynamic matching between the load and real-time carrying capacity. While ensuring the service life exceeds the design life, the difference between the two is controlled at around 3467 cycles, accounting for approximately 0.000462% of the design life. This significantly improves the equipment’s operational safety and resource utilization efficiency, breaks through the limitations of load reduction schemes formulated based on human experience under the traditional regular inspection mode, and provides a scientific load-matching decision-making basis and technical support for special equipment inspection institutions and users. Full article

In the paper, using the three-statement financial modelling methodology as applied to a representative development project, we aim to analyse, ex ante, the industry-level impact of transition to mandatory escrow schemes in residential and mixed-use construction in Tashkent city (due to be implemented in Uzbekistan from 2026). Modelling single-milestone escrow plans against the current steep-discount advance-based system of off-plans as a baseline, the model accounts for salient institutional features of the Tashkent city development market, including land auctioning, full-cycle Value-added tax (VAT) accounting, and Tax loss carryforward provisions. It also incorporates a framework for demand-driven residual valuations for the development land element. Our findings indicate practically unchanged cashflow profitability of developers on the market in question. Around 30% p.a. in nominal Free-cashflow-to-equity based IRRs expressed in the national currency, provided that the transition to the greater use of leverage in funding unfolds as expected. The disappearance of steep off-plan discounts while the transition to escrows unfolds will be countervailed by the reliance on costly loans from escrow banks. Absent the greater use of leverage, the IRR (FCFE) profitability of the developers is expected to decline by some 5%. For the apartment buyers, this is effectively equivalent to increasing property transaction prices on the primary market in line with their headline asking amounts. Thus-generated economic surplus will be partially captured by the developers and partially passed through to escrow banks, increasing their gross profits by up to $50M, p.a. due to their new role in financing Tashkent city residential developments that are still largely equity-driven. Apart from this effect, we find only a moderate financial leverage influence on developers’ profitability due to the high-interest-rate environment prevailing in Uzbekistan. We also find a demand-driven pressure on land auction prices suggested by increasingly back-loaded alterations in project cashflow profiles. This study also purports to make a material contribution to the evolving body of literature on financial modelling of apartment and mixed-use property developments by offering a flexible three-statement modelling framework with innovative endogenised equity management features. Full article

The structural responsiveness of urban energy systems has emerged as a central challenge in the governance of shrinking cities. Urban shrinkage entails more than a redistribution of resources—it reflects deep tensions embedded in population spatial configuration, functional redundancy, and institutional inertia. To investigate the evolutionary trajectory and driving mechanisms of urban energy consumption (UEC) under the context of urban shrinkage, this study focuses on China, a country undergoing rapid internal regional transformation. Drawing on panel data from 281 cities between 2008 and 2021, the study integrates two-way fixed effects (TWFE) models, mediation analysis, and spatial econometric models to ensure the scientific rigor and robustness of the quantitative analysis. Contrary to the intuitive assumption that declining population leads to reduced energy loads, the results reveal a non-linear and asymmetric trajectory wherein per capita energy consumption increases alongside continued demographic decline. Mechanism decomposition further shows that declines in population density and the share of secondary industry suppress UEC through spatial dispersal and the retreat of energy-intensive sectors, respectively. In contrast, fiscal contraction and institutional path dependency collectively elevate the share of traditional energy consumption, reinforcing the structural inertia of UEC. This study illuminates the non-linear dynamics of energy system evolution under urban shrinkage and argues for a shift away from linear and target-driven governance paradigms toward governance frameworks that emphasize structural adaptation, distributive equity, and systemic resilience—thereby offering a theoretical and empirical foundation for multi-objective sustainable urban transitions. Full article

Background: Exercise-induced fatigue arises primarily from energy substrate depletion and the accumulation of metabolites such as lactate and ammonia, which impair performance and delay recovery. Emerging evidence implicates gut microbiota modulation—particularly via probiotics—as a means to optimize host energy metabolism and accelerate clearance of fatigue-associated by-products. Objective: This study aimed to determine whether live or heat-inactivated Lacticaseibacillus paracasei NB23 can enhance exercise endurance and attenuate fatigue biomarkers in a murine model. Methods: Forty male Institute of Cancer Research (ICR) mice were randomized into four groups (n = 10 each) receiving daily gavage for six weeks with vehicle, heat-killed NB23 (3 × 10¹⁰ cells/human/day), low-dose live NB23 (1 × 10¹⁰ CFUs/human/day), or high-dose live NB23 (3 × 10¹⁰ CFUs/human/day). Forelimb grip strength and weight-loaded swim-to-exhaustion tests assessed performance. Blood was collected post-exercise to measure serum lactate, ammonia, blood urea nitrogen (BUN), and creatine kinase (CK). Liver and muscle glycogen content was also quantified, and safety was confirmed by clinical-chemistry panels and histological examination. Results: NB23 treatment produced dose-dependent improvements in grip strength (p < 0.01) and swim endurance (p < 0.001). All NB23 groups exhibited significant reductions in post-exercise lactate (p < 0.0001), ammonia (p < 0.001), BUN (p < 0.001), and CK (p < 0.0001). Hepatic and muscle glycogen stores rose by 41–59% and 65–142%, respectively (p < 0.001). No changes in food or water intake, serum clinical-chemistry parameters, or tissue histology were observed. Conclusions: Our findings suggest that both live and heat-treated L. paracasei NB23 may contribute to improved endurance performance, increased energy reserves, and faster clearance of fatigue-related metabolites in our experimental model. However, these results should be interpreted cautiously given the exploratory nature and limitations of our study. Full article

The convergence of artificial intelligence (AI) and nanomedicine has transformed cancer vaccine development, particularly in optimizing RNA-loaded lipid nanoparticles (LNPs). Stability and targeted delivery are major obstacles to the clinical translation of promising RNA-LNP vaccines for cancer immunotherapy. This systematic review analyzes the AI’s impact on LNP engineering through machine learning-driven predictive models, generative adversarial networks (GANs) for novel lipid design, and neural network-enhanced biodistribution prediction. AI reduces the therapeutic development timeline through accelerated virtual screening of millions of lipid combinations, compared to conventional high-throughput screening. Furthermore, AI-optimized LNPs demonstrate improved tumor targeting. GAN-generated lipids show structural novelty while maintaining higher encapsulation efficiency; graph neural networks predict RNA-LNP binding affinity with high accuracy vs. experimental data; digital twins reduce lyophilization optimization from years to months; and federated learning models enable multi-institutional data sharing. We propose a framework to address key technical challenges: training data quality (min. 15,000 lipid structures), model interpretability (SHAP > 0.65), and regulatory compliance (21CFR Part 11). AI integration reduces manufacturing costs and makes personalized cancer vaccine affordable. Future directions need to prioritize quantum machine learning for stability prediction and edge computing for real-time formulation modifications. Full article