Search Results (8,696)

In many traditional villages in China, substantial government investment has been directed toward reconstructing public spaces for tourism development. Yet, many of these newly built spaces remain underused, revealing a persistent mismatch between top–down planning and villagers’ everyday needs. To address this gap, this study employs a mixed-methods approach to evaluate the quality of rural public spaces. Drawing on a systematic review, a four-dimensional assessment model—encompassing environmental, social, cultural, and economic attributes—was developed and operationalized through 17 specific indicators. The model was applied to three traditional villages in Chongqing, Southwest China, using field observation, questionnaire surveys, confirmatory factor analysis, and semi-structured interviews. The findings show that while environmental and cultural qualities are generally appreciated, villagers’ overall evaluations are strongly shaped by livelihood considerations and the extent to which public spaces support everyday practices. In tourism-oriented villages, public spaces often function primarily as attractions rather than as sites of daily life, limiting their social usefulness despite significant investment. The results demonstrate that economic indicators, which are often overlooked in existing studies, are essential for assessing the quality of public space in traditional villages and for strengthening community engagement. These insights contribute to a more comprehensive understanding of rural public space and offer practical guidance for rural revitalization and community-based planning. Full article

Accurate multi-leaf collimator (MLC) motion prediction is a prerequisite for precise dose delivery in advanced techniques such as IMRT and VMAT. Traditional patient-specific quality assurance (QA) methods remain resource-intensive and prone to physical measurement uncertainties. This study aimed to develop machine learning (ML) models to predict delivered MLC positions using kinematic parameters extracted from DICOM-RT plans for the Elekta Versa HD system. A dataset comprising 200 patient plans was constructed by pairing planned MLC positions, velocities, and accelerations with corresponding delivered values parsed from unstructured trajectory logs. Four regression models, including linear regression (LR), were trained to evaluate the deterministic nature of the Elekta servo-mechanism. LR demonstrated superior prediction accuracy, achieving the lowest mean absolute error (MAE) of 0.145 mm, empirically confirming the fundamentally linear relationship between planned and delivered trajectories. Subsequent dosimetric validation using ArcCHECK measurements on 17 clinical plans revealed that LR-corrected plans achieved statistically significant improvements in gamma passing rates, with a mean increase of 2.24% under the stringent 1%/1 mm criterion (p < 0.001). These results indicate that the LR model successfully captures systematic mechanical signatures, such as inertial effects. This study demonstrates that a computationally efficient LR model can accurately predict Elekta MLC performance, providing a robust foundation for implementing ML-based virtual QA. This approach is particularly valuable for time-sensitive workflows like adaptive radiotherapy (ART), as it significantly reduces reliance on physical QA resources. Full article

Efficient last-mile delivery remains a critical challenge for rural agricultural logistics, globally, particularly in cold-climate regions with dispersed agricultural operations. Truck–drone hybrids can reduce delivery times but face payload limits, cold-weather battery loss, and beyond-visual-line-of-sight regulations. This review evaluates the potential of GIS-enabled truck–drone hybrid systems to overcome infrastructural, environmental, and operational barriers in such settings. This study uses the state of North Dakota (USA) as a representative case because of its cold climate, low density, and weak connectivity. These conditions require different routing and system assumptions than typical regions. The study conducts a systematic review of 81 high-quality publications. It identifies seven interconnected research domains: GIS analytics, truck–drone coordination, smart agriculture integration, rural implementation, sustainability assessment, strategic design, and data security. The findings stipulate that GIS enhances hybrid logistics through route optimization, launch site planning, and real-time monitoring. Additionally, this study emphasizes the rural, low-density context and identifies specific gaps related to cold-weather performance, restrictions to line-of-sight operations, and economic feasibility in ultra-low-density delivery networks. The study concludes with a roadmap for research and policy development to enable practical deployment in cold-climate agricultural regions. Full article

In recent years, the demand for mobile robots to perform odor source localization tasks in dangerous environments has been increasing, and this technology has gradually become a focus of research. However, existing bio-inspired algorithms still have many limitations in real applications. Therefore, we attempt to design a moth-inspired algorithm integrated with a fuzzy control mechanism to enhance the robot’s ability to track odor sources in environments with dense obstacles. The goal is to improve the accuracy and efficiency of localization. Through multiple sets of simulation and real environment experiments, we observed that this algorithm achieved significant improvements in multiple indicators, including task success rate, search efficiency, and path planning quality. Compared with the traditional moth algorithm, its stability and adaptability in complex scenarios are also outstanding. Full article

Urban green space is essential for ecological functions, environmental quality, and human well-being, yet campus expansion can reduce vegetated areas. This study assessed UGS dynamics at Universitas Padjadjaran’s Jatinangor campus from 2015 to 2025 and evaluated an object-based machine learning approach for fine-scale land cover mapping. High-resolution WorldView-2, WorldView-3, and Legion-03 imagery were pan-sharpened, geometrically corrected, normalized, and used to compute NDVI and NDWI indices. Object-based image analysis segmented the imagery into homogeneous objects, followed by random forest classification into six land cover classes; UGS was derived from dense and sparse vegetation. Accuracy assessment included confusion matrices, overall accuracy 0.810–0.860, kappa coefficients 0.747–0.826, weighted F1 scores 0.807–0.860, and validation with 43 field points. The total UGS increased from 68.89% to 74.69%, bare land decreased from 13.49% to 5.81%, and building areas moderately increased from 10.36% to 11.52%. The maps captured vegetated and developed zones accurately, demonstrating the reliability of the classification approach. These findings indicate that campus expansion has been managed without compromising ecological integrity, providing spatially explicit, reliable data to inform sustainable campus planning and support green campus initiatives. Full article

This study examines the economic and humanistic burden associated with multimorbidity among adults in the United States. Using data from the 2019–2022 Medical Expenditure Panel Survey (MEPS), we identified individuals with two or more chronic conditions and assessed trends in healthcare expenditures, out-of-pocket costs, inpatient stays, and health-related quality of life (HRQL). Weighted analyses were conducted to estimate national patterns and annual changes across survey years. Outcomes were analyzed using generalized estimating equation (GEE) models with AR(1) working correlation to compare adjusted mean total and out-of-pocket expenditures, inpatient utilization, and mental and physical HRQL across multimorbidity profiles while controlling for sociodemographic and health factors. Findings showed that multimorbidity was associated with substantial economic burden, reflected in higher healthcare costs and out-of-pocket spending over time. HRQL consistently declined throughout the study years, highlighting the growing humanistic toll of chronic disease clustering. These findings provide longitudinal evidence of persistent disparities associated with multimorbidity and may inform future research and health system planning strategies. The results provide timely evidence for health policymakers and practitioners seeking to improve health system efficiency and equity in managing multimorbidity. Full article

This study presents a well-to-wheel life-cycle assessment (WTW-LCA) comparing battery-electric heavy-duty trucks (BEVs) with conventional diesel trucks, utilizing real-world fleet data from Southern California’s Volvo LIGHTS project. Class 7 and Class 8 vehicles were analyzed under ISO 14040/14044 standards, combining measured diesel emissions from portable emissions measurement systems (PEMSs) with BEV energy use derived from telematics and charging records. Upstream (“well-to-tank”) emissions were estimated using USLCI datasets and the 2020 Southern California Edison (SCE) power mix, with an additional scenario for BEVs powered by on-site solar energy. The analysis combines measured real-world energy consumption data from deployed battery electric trucks with on-road emission measurements from conventional diesel trucks collected by the UCR team. Environmental impacts were characterized using TRACI 2.1 across climate, air quality, toxicity, and fossil fuel depletion impact categories. The results show that BEVs reduce total WTW CO₂-equivalent emissions by approximately 75% compared to diesel. At the same time, criteria pollutants (NO_x, VOCs, SO_x, PM_2.5) decline sharply, reflecting the shift in impacts from vehicle exhaust to upstream electricity generation. Comparative analyses indicate BEV impacts range between 8% and 26% of diesel levels across most environmental indicators, with near-zero ozone-depletion effects. The main residual hotspot appears in the human-health cancer category (~35–38%), linked to upstream energy and materials, highlighting the continued need for grid decarbonization. The analysis focuses on operational WTW impacts, excluding vehicle manufacturing, battery production, and end-of-life phases. This use-phase emphasis provides a conservative yet practical basis for short-term fleet transition strategies. By integrating empirical performance data with life-cycle modeling, the study offers actionable insights to guide electrification policies and optimize upstream interventions for sustainable freight transport. These findings provide a quantitative decision-support basis for fleet operators and regulators planning near-term heavy-duty truck electrification in regions with similar grid mixes, and can serve as an empirical building block for future cradle-to-grave and dynamic LCA studies that extend beyond the operational well-to-wheels scope adopted here. Full article

The review has explored the application of Geographic Information Systems (GIS) in evaluating road traffic crashes, stressing its role in identifying crash spatial patterns and hotspots. GIS offers a framework for integrating spatial and non-spatial data, allowing scholars and planners to visualize crash-prone areas and understand their distribution. A total of 77 research articles from the publication period of 2010–2025 were included for final reviews. A Systematic Reviews and Meta-Analyses (PRISMA) approach is followed to provide well-structured, transparent, and standardized information on articles. The intention is to assess how different GIS techniques contribute to road safety analysis and to the development of effective intervention strategies. The review focused particularly on four key GIS-based spatial analysis methods: Kernel Density Estimation (KDE), Network KDE, Moran’s I (Global and Local), and Getis-Ord Gi*. Among these, KDE and Moran’s I were the most frequently adopted techniques, covering about 31.17% and 23.38% of reviewed articles, respectively. These techniques are essential for identifying statistically significant clusters and crash concentration. Despite their promising results, the studies also reveal limitations, including inconsistent data quality, high computational demands, and limited use of variables such as road geometry characteristics. Although GIS is an effective tool for planning and analyzing road safety, these deficiencies might be addressed by future studies that advance the use of real-time spatial analytics and incorporate more diversified information. Overall, the review has reinforced the critical role of GIS in improving traffic safety through real-time data-driven interventions. Full article

Water replenishment projects (WRP) are widely regarded by lake managers as an effective method for ecological restoration. But studies on multiple water receiving lakes indicate that multi-source water supplementation may exacerbate spatial heterogeneity in water quality. The primary causes are the uneven quality of external water sources and the morphology of the lakes themselves. Hangzhou’s West Lake, which relies on a single water source, also exhibits ecological differences between its lake areas. To explain this phenomenon from a hydrodynamic perspective, this study employs Delft3D model simulations to determine the spatiotemporal heterogeneity in the impact of artificial water replenishment on local water renewal times (LWRT) across different lake areas. The results indicate that, compared to natural conditions, WRP shortens the typical LWRT at most sites in West Lake and reduces the seasonal variation amplitude of LWRT. The WRP impedes local water exchange capacity in certain lake areas during specific months, potentially creating stagnant zones. Moreover, the spatiotemporal heterogeneity of its impact on West Lake’s hydrodynamic conditions amplifies differences in flow rhythms between lake regions, leading to fragmented water movement. This may ultimately compromise the integrity of the lake’s overall ecological environment. Managers of receiving lakes should consider increasing monitoring frequency and the number of monitoring stations to address more complex water quality conditions. Future designers of WRPs should incorporate the prevention of fragmented hydrodynamic conditions as an evaluation criterion in diversion scheme planning. This study provides references and evidence for lake ecological management and research on the impact mechanisms of WRPs on shallow lakes. Full article

Background/Objectives: Adult spinal deformity (ASD) is increasingly prevalent due to an ageing population and is associated with significant pain, disability, and reduced quality of life. While surgery is often considered for severe deformities, many patients are either unsuitable for major corrective procedures or prefer conservative care. This narrative review synthesizes the current evidence on nonoperative management strategies for ASD. Methods: A literature search on the PubMed and Cochrane databases identified relevant studies published up to 25 October 2025. Medical Subject Headings and keywords related to nonsurgical ASD management were used. Eligible studies included nonsurgical series with a minimum of 12 months’ follow-up, while case reports were excluded. Results: Seven studies met our inclusion criteria: three on bracing, three on physiotherapy and combined physical and cognitive rehabilitation programmes, and one on transforaminal epidural steroid injections (ESIs). Bracing was effective in slowing the curve progression rate. One study showed that the progression rate decreased from 1.47°/year to 0.24° for degenerative scoliosis (p < 0.0001) and from 0.70°/year to 0.24° for idiopathic scoliosis (p = 0.03). Another study showed that there was no statistically significant difference in the Cobb angle or anticipated worsening when comparing the initial measurement with the final control after treatment (p = 0.973). Finally, a third study reported reduced back pain, with Roland–Morris scores improving from 3.3 to 2.0 (p < 0.001) at 18 months. Physiotherapy and multidisciplinary rehabilitation programmes appeared to be effective in significantly reducing pain and disability levels. One study found that Oswestry Disability Index (ODI) scores improved from 39.5 to 31.8 (p < 0.001), while back pain, measured using the Numeric Pain Rating Scale (NPRS), improved from 58.4 to 42.1 (p < 0.001), with 51% achieving minimal clinically important change (MCIC). Another study reported ODI reductions from 38 to 17.6 and pain scores from 6.5 to 2.2 (p < 0.001), while in a third study, the “Koshimagari Exercise” programme yielded MCIDs in the ODI for 42% of patients. Finally, ESIs provided significant pain relief for at least a month in over half of the patients with degenerative scoliosis and radiculopathy, with diminishing effects throughout the first 2 years. More specifically, 37.2% of patients had a successful outcome at one year post-injection and 27.3% at 2 years (p < 0.01). Conclusions: Our study suggests that bracing, physiotherapy, and multidisciplinary rehabilitation programmes, as well as ESIs, can serve as effective short term alternatives for patients with ASD who are either unsuitable for surgery or do not wish to pursue it. As such, this review provides valuable evidence-based insights that can guide clinicians in developing a treatment plan and lay the foundations for establishing a novel pathway for this specific subgroup of patients with ASD. Full article

Background and Objectives: Airway management and ventilation during laryngotracheal surgery represent some of the most challenging tasks in anesthesiology. The shared airway between the surgeon and anesthesiologist requires continuous coordination to ensure optimal oxygenation while maintaining an unobstructed surgical field. Materials and Methods: This narrative review is based on a comprehensive literature search of PubMed, Embase, Scopus, and Google Scholar, covering all publications from inception to 30 June 2025. The literature search was performed using a defined Boolean strategy and explicit inclusion/exclusion criteria, focusing on adult human subjects. The search included combinations of the terms “laryngotracheal surgery,” “airway management,” “ventilation strategies,” “jet ventilation,” “Tritube,” and “Flow Controlled Ventilation.” Only English-language studies focused on human subjects were included. Results: Traditional ventilation strategies, such as apneic oxygenation and jet ventilation, remain widely used but present limitations in terms of gas exchange efficiency, risk of barotrauma, and surgical interference. In recent years, new devices and ventilation modes—particularly the Tritube^® combined with Flow-Controlled Ventilation—have emerged as promising alternatives. These approaches allow continuous ventilation with minimal airway diameter, improving surgical access and patient safety. FCV’s potential to optimize gas exchange and reduce mechanical power is physiologically compelling, but its supporting evidence remains limited and heterogeneous, primarily consisting of small, single-center studies and case series. Conclusions: Optimal airway and ventilation management in laryngotracheal surgery requires individualized planning, technical expertise, and close interdisciplinary communication. This approach must integrate objective neuromuscular monitoring to ensure patient safety and include a comprehensive strategy for safe postoperative airway management and extubation. While emerging technologies have significantly expanded available options, their successful application depends on training, experience, and appropriate case selection. Further high-quality clinical studies are needed to standardize protocols and validate long-term outcomes of these innovative ventilation strategies. Full article

Oil palm is an important economic crop that is widely cultivated, especially in Southeast Asia. Thailand is one of the world’s largest producers and exporters of palm oil. Efficient management of oil palm plantations is crucial for increasing yields and minimizing agricultural losses. This study aimed to develop a smart oil palm plantation and production management system. This system utilizes Internet of Things (IoT) technology and an integrated supervised machine learning model utilizing regression analysis to monitor and control agricultural equipment within the plantation. MySQL database was used for management of sensor data. Python (version 3.9.6) programming and Google Map API were used for data analysis, spatial analysis and data visualization suite in the system. The results showed that the data from the sensors are displayed in real-time, allowing plantation managers to monitor conditions remotely and make informed adjustments as needed. The system also includes data analysis and data visualization tools for decision-making regarding production management. The model attained an accuracy of over 95%, which reflects its reliability in performing the specified prediction task. The system serves as a support tool for automating soil quality monitoring, fertilization, and field maintenance in oil palm plantations. This enhances productivity, reduces operational costs, and improves yield planning. Full article

This study investigates the acoustic conditions of a design studio (Studio 130) in the Department of Interior Architecture and Environmental Design at Afyon Kocatepe University by integrating 14 weeks of continuous noise measurements with perception data collected from 192 students. Noise measurements were conducted in accordance with ISO 3382-3:2022 guidelines at three locations—window front, door side, and studio midpoint—during morning, noon, and evening periods, with 10 min recordings at each session. The results indicate that when students were present, the equivalent continuous noise level (Leq) reached an average of 65.5 dB(A), with peak levels rising to 72.3 dB(A) during jury sessions. These values substantially exceed the recommended 35 dB(A) classroom threshold by the World Health Organization and the 35–45 dB(A) limits specified in national regulations for indoor educational spaces. Survey findings reveal that 88% of students experienced loss of concentration, 72% reported decreased productivity, 60% had difficulty communicating, and 52% reported fatigue due to noise exposure. Pearson correlation analysis demonstrated a strong relationship between measured noise levels and reported negative effects (r = 0.966). Moreover, independent samples t-test results confirmed that student presence significantly increased studio noise levels (t = 4.98, p < 0.001). The novelty of this research lies in its combined use of longitudinal objective measurements and subjective perception data, addressing the unique open-plan, collaborative, and critique-based pedagogical structure of design studios. The findings highlight that acoustic comfort is a critical component of learning quality in studio-based education. Based on the results, the study proposes several design and material interventions—including spatial dividers, acoustic ceiling panels, fabric-wrapped absorbers, and impact-reducing flooring—to enhance auditory comfort. Overall, the study emphasizes the necessity of integrating acoustic design strategies into studio pedagogy to support concentration, communication, and learning performance. Full article

Amidst rapid urbanization, balancing ecological protection with development demands has become a critical challenge for sustainable planning. This article collected data on the natural geography and socio-economic aspects of Fuzhou City and quantified five key ecosystem services—crop production, water yield, carbon sequestration, soil conservation, and habitat quality—using the InVEST model. By using SOFM to identify different ESBs and combining sensitivity analysis to form different ecological functional zones, and using geographic detectors to detect their driving factors, this aims to provide a framework for urban green space management. The results indicate that ecosystem services have a significant northwest southeast spatial gradient and can be divided into five types of ESBs. Among them, the core ecological clusters account for 59.36% of the study area and are mainly distributed in the forest-covered northwest region. Based on different service bundles and sensitivity levels, it is divided into five ecological functional zones. Geographic detector analysis shows that the interaction effect between natural factors (such as altitude and precipitation) and socio-economic factors (such as GDP density and land use) significantly enhances the explanatory power of ESB distribution. This study provides a transferable model for ecological management in global coastal cities facing similar terrain complexity and urbanization pressures. The framework demonstrates how understanding ecosystem service packages and their driving factors can effectively guide urban ecological planning decisions and provide valuable insights into coordinating ecological protection and urban development through targeted green space management methods. Full article

China’s urban development model has shifted from incremental expansion to inventory quality improvement. The demand for planning and allocation of spatial resources has moved from “having or not having” to “being good or not”, and the importance of planning, implementation, evaluation, and feedback in urban spatial planning and construction has gradually increased. How to accurately allocate resources in response to the public’s demands for urban construction and effectively enhance the public’s satisfaction and sense of gain regarding urban construction has become an important issue in current planning decisions. To strengthen public perception and feedback in spatial planning governance, this paper conducts empirical research on methods such as the subjective and objective perception differences of urban public service facilities by using the social satisfaction survey data from the East Lake High-tech Development Zone of Wuhan. Thereby, it identifies the characteristics of subjective and objective perception differences of urban public service facilities and puts forward targeted optimization methods for planning decisions. This paper can provide a reference for the precision planning and decision-making of public service facilities in the next step. Full article