Search Results (1,002)

The aim of this study is to evaluate the biomechanical response of a seated operator subjected to whole-body vibrations generated by two agricultural tractors with different propulsion systems: a diesel model (TD80D) and an electric prototype (TE-0). An integrated experimental–numerical approach was employed, combining triaxial accelerometer measurements under real operating conditions (constant speed of 5 km/h on unprepared terrain) with random vibration response simulations performed in Altair SimSolid. The excitation input for the numerical model was defined using frequency-dependent power spectral density (PSD) functions derived from experimentally measured acceleration signals and scaled to a representative global RMS value. The analysis focused on the distribution of mechanical stress in key anatomical regions of a virtual human dummy in a seated posture, including the foot sole, knee, lumbar region, and head. The results indicate that, under the analysed conditions, the electric tractor (TE-0) exhibits improved vibration attenuation, leading to significant reductions in mechanical stress across all analysed regions, with decreases of up to 56.3% at the foot sole, 50.0% at the knee, 53.3% in the lumbar region, and 91.1% at the head compared to the diesel tractor (TD80D). These findings highlight the relevance of integrating experimental measurements with numerical simulation for assessing operator exposure to vibrations and suggest that electric tractor configurations may provide improved biomechanical comfort under the analysed operating conditions. Full article

Background and Objectives: Poor sleep is common in community and primary-care settings, yet very brief sleep measures suitable for routine use remain limited. We developed and evaluated the five-item Promoting Evaluation and Awareness of Comfort in Sleep (PEACE) scale and examined its associations with well-being and fatigue. Materials and Methods: In a cross-sectional, clinician-mediated online survey, 312 community-dwelling adults in Italy who were not receiving active treatment for major diseases completed PEACE, the World Health Organization-Five Well-Being Index (WHO-5), and a short fatigue questionnaire. The sample was stratified and split into exploratory and confirmatory subsamples for factor analyses. Results: Factor analyses supported the use of a single total score and showed acceptable reliability. Results were broadly similar in women and men, with no evidence of item-level bias, although some model-comparison indices were mixed. Higher PEACE scores were associated with better well-being and lower fatigue. Adding PEACE to a model predicting well-being from body mass index and sex increased explained variance from 4.0% to 11.5%. Conclusions: PEACE is a brief sleep-quality measure with promising initial psychometric properties. In this sample, it was associated with well-being and fatigue and may add information beyond body mass index and sex in community and primary-care settings. Full article

Understanding how climate change alters the thermal environment experienced by dairy cattle is critical for guiding adaptation in rapidly warming regions. Using meteorological data from 1961 to 2020, this study quantified long-term trends in temperature, precipitation, relative humidity, and wind speed across Jiangsu Province, China, and assessed their impacts on thermal stress using a temperature–humidity index (THI). The results reveal pronounced spatial heterogeneity in climatic change, with accelerated warming in southern and coastal prefectures, and continued winter cold stress in the northern plain. Over the past six decades, the annual number of heat-stress days (THI > 72) increased substantially and expanded northward, while cold-stress days (THI ≤ 38) declined but remained non-negligible in northern Jiangsu. Although the total number of thermally comfortable days changed little at the provincial scale, their seasonal distribution became increasingly compressed between longer summer heat-stress periods and shorter winter cold-stress windows, indicating a narrowing of the effective comfort range for dairy cattle. To link historical analysis with operational applications, a forecasting platform was developed to generate short-term predictions of THI and associated meteorological conditions, enabling spatially explicit visualization and early identification of periods with elevated thermal risk. Overall, these findings demonstrate an intensification and redistribution of thermal stress in Jiangsu, while also illustrating a transferable climate-risk mechanism relevant to other warming, humid dairy regions worldwide. Full article

Background: Magnesium sulfate (MgSO₄) has been investigated as an adjuvant in perioperative analgesia because of its antagonistic effects on the N-methyl-D-aspartate receptor (NMDA receptor) and its potential to attenuate central sensitization. However, clinical findings regarding its analgesic efficacy remain inconsistent across surgical procedures. Lumbar microdiscectomy is a common spinal procedure in which effective early postoperative pain control is important for patient comfort and early mobilization. This study aimed to evaluate the effect of intraoperative MgSO₄ administration on early postoperative analgesia and perioperative outcomes in patients undergoing lumbar microdiscectomy. Methods: This retrospective single-center cohort study included thirty-eight patients with American Society of Anesthesiologists (ASA) physical status I–II who underwent elective single-level lumbar microdiscectomy under general anesthesia. Patients were divided into two groups according to intraoperative magnesium administration: a control group receiving standard anesthesia without MgSO₄ (n = 19) and an MgSO₄ group receiving an intravenous MgSO₄ bolus of 30 mg/kg followed by a continuous infusion of 10 mg/kg/h until skin closure (n = 19). Postoperative pain intensity was assessed using the Numeric Rating Scale (NRS) at 0, 5, 10, 15, and 30 min after admission to the post-anesthesia care unit. Secondary outcomes included intraoperative remifentanil consumption, extubation time, and time to first mobilization. Complementary in silico analyses included molecular docking and protein–protein interaction (PPI) network analysis. Results: Postoperative NRS scores were numerically lower in the MgSO₄ group; however, between-group differences were not statistically significant. Mean intraoperative remifentanil consumption was numerically lower in the MgSO₄ group (236 ± 166 µg) compared with the control group (319 ± 298 µg), without statistical significance (p = 0.27). Repeated-measures analysis demonstrated the significant effect of time on postoperative NRS scores, whereas the overall group effect was not significant. Molecular analyses indicated stable morphine binding to opioid receptors and highlighted glutamatergic signaling components as central nodes within the interaction network. Conclusions: Intraoperative MgSO₄ administration was not associated with significant improvements in early postoperative pain scores or perioperative recovery parameters following lumbar microdiscectomy. Molecular analyses provide exploratory in silico insights and should be interpreted cautiously given the retrospective design and the in silico nature of these findings. Full article

Noise disturbances can cause conflicts in several areas, such as residences, civil constructions, highways, subways, and airports, measured by different scales of acoustic comfort for community well-being evaluation. These disturbances also have signatures such as frequency, amplitude, and temporal patterns to compare acoustic comfort with real-time parameters. In addition, acoustic sensors should be chosen based on accuracy, price, and calibration method, and acoustic insulation should be applied with the aim of achieving reliable measurements in indoor and outdoor environments for sustainable urban living. In some situations, the lack of noise control can lead to several human disorders, from hearing loss to cardiovascular complications. Therefore, legislation and regulation should be carefully studied and applied to achieve an equilibrium between energy-efficient and healthy building designs in entertainment, work, and rest activities with measured parameters visualized through the design of interface tools that should enable the collection and organization of sound data, with proper presentation for the final user. Finally, intellectual property registrations bring recent industrial applications with aspects of noise mitigation. All these features constitute noise disturbance mitigation in a multi-dimensional integration framework of technology, health, and law to improve the quality of life in human-centric environments. Full article

Rapid urbanisation and climate change are intensifying urban heat stress, posing significant challenges for climate-responsive urban planning. Digital and data-driven approaches, including GIS, remote sensing, microclimate simulation, and artificial intelligence (AI), have advanced urban climate analysis; however, their capacity to support human-centred planning remains insufficiently synthesised. This review analyses 78 peer-reviewed studies (2015–2025) to evaluate how digital methods address urban microclimate and outdoor thermal comfort. The reviewed studies are classified into four methodological groups: spatial data analytics, simulation-based models, parametric and optimisation workflows, and AI-driven or hybrid approaches. The results show that the majority of studies rely on proxy indicators, such as land surface temperature and sky view factor, while physiologically based comfort indices (e.g., PET and UTCI) are applied in a limited proportion of studies and remain largely confined to microscale simulations. A persistent scale mismatch is identified between large-scale analytics and pedestrian-level thermal experience, alongside geographic and climatic biases, particularly in hot-arid regions. Unlike previous reviews, this study integrates digital methodologies, urban microclimate processes, and human-centred thermal comfort within a unified framework. The findings provide actionable insights for planners and designers by supporting the integration of thermal comfort into multi-scale, climate-responsive decision-making. Full article

In recent decades, the Ucayali region, the main territory of the Asheninka communities, has experienced increasing socio-environmental pressures associated with climate change, educational inequality, and territorial vulnerability in rural and indigenous contexts. In response, this research proposes the design of a sustainable agricultural school for the Asheninka community, conceived as an educational building that integrates biophilic strategies to enhance environmental performance and spatial quality. The methodological approach comprises a literature review, site-specific environmental analysis based on hydrometeorological data, and the development of an architectural proposal focused on sustainable building design. Digital tools such as Revit and SketchUp were employed alongside official climatic data sources to support design decision-making. The proposal includes twelve biophilic agricultural classrooms incorporating passive design strategies, rainwater harvesting systems with a capacity of 22.5 m³ per day per classroom, and photovoltaic-powered public lighting systems. Results indicate that the integration of natural ventilation, green infrastructure, and locally sourced materials contributes to significant improvements in thermal comfort, humidity control, and energy autonomy within the educational facilities. The architectural complex is complemented by green corridors and collective open spaces that reinforce environmental performance at the site scale. This study demonstrates that sustainable educational buildings adapted to local ecosystems and climatic conditions can function as effective infrastructures for environmental mitigation and resilient rural development, contributing to more sustainable forms of urban and rural living. Full article

Highway landscape quality is important for visual comfort, environmental coordination, and infrastructure management. However, conventional assessment methods rely heavily on manual inspection and qualitative judgment, which are subjective and inefficient for large-scale applications. To address this issue, this study proposes an AI-based quantitative evaluation framework for highway landscape quality using an improved Panoptic-DeepLab model for panoramic image segmentation. The model identifies major landscape elements in highway scenes, including vegetation, sky, roads, buildings, and billboards. Based on the segmentation results, the proportions of natural elements, spatial openness, and artificial interference are integrated into a landscape quality score (LQS) model for quantitative assessment. Experimental results demonstrate that the proposed method achieves reliable segmentation performance and stable convergence in complex highway environments. Comparative analysis further shows that the method provides competitive accuracy with good computational efficiency. The proposed framework offers an effective tool for highway landscape evaluation and can support highway planning, landscape optimization, and visual environment management. Full article

Background/Objections: One of the most common surgical procedures performed internationally is the cesarean section. It is known to be associated with intense postoperative pain and a slow recovery process. Focusing on surgical techniques, especially the type of fascial closure, is an area that has received very little attention when it comes to postoperative pain and rapid recovery. Using a mixed-methods approach, the primary objective of this study was to assess the impact of guide-suture-assisted modified fascial closure on postoperative pain and early mobilization after cesarean sections. Methods: Women undergoing elective cesarean sections with Pfannenstiel’s incision were the study participants of this prospective, single-center, randomized mixed-methods study. Participants were enrolled in the study and randomized to either classical continuous fascial closure or guide-suture-assisted modified fascial closure, which was carried out in a 1:1 ratio. Quantitative data assessed postoperative pain through the Visual Analog Scale (VAS), a Numeric Rating Scale (NRS), and the Short-Form McGill Pain Questionnaire (SF-MPQ), and functional recovery was assessed through walking distances at postoperative 6, 12, 24, and 48 h. Qualitative data were collected via semi-structured interviews and analyzed through conventional content analysis to understand the patients’ perceptions of pain and recovery experiences. Results: The first 24 h postoperative period pain levels were significantly lower for the modified fascial closure group versus the classical closure group (p < 0.05). Moreover, the modified closure group had a significantly better functional recovery, evidenced by walking greater distances at 12, 24, and 48 h postoperative. Qualitative results indicated improved comfort and stronger early mobilization confidence, in addition to less movement apprehension, consistent with the above results, among those with the modified technique. Conclusions: The modified fascial closure technique with guide suture was linked to less pain in the early postoperative period and better functional recovery after cesarean section. This technique is a good candidate for addition to standard obstetric procedures since it is cost effective, easily added, and surgical practice will improve comfort for mothers and assist with early mobilization. Full article

Sleep quality is essential for maintaining physical health and psychological resilience. Because sleepwear remains in direct contact with the skin throughout the night, it may affect thermoregulation and comfort and, thereby, influence sleep. This randomized two-period, two-sequence crossover study investigated whether sleepwear infused with nanodiamond and nanoplatinum particles (DPV576) could improve sleep quality and promote fatigue recovery under free-living conditions. Fourteen healthy men (23.9 ± 1.7 years) wore DPV576 sleepwear and visually indistinguishable standard polyester sleepwear for one week each, separated by a one-week washout. Sleep was assessed using a wearable ECG-based actigraphy device; trained researchers additionally performed manual rescoring to verify automated outputs, including independent determination of sleep onset latency. Subjective sleep was assessed daily using the Sleep Quality Index of Daily Sleep and a visual analog scale; exploratory outcomes included voice-derived biomarkers and pre-/post-sleep grip strength. In manual rescoring, DPV576 was associated with higher sleep efficiency (93.0 ± 0.9% vs. 89.5 ± 1.5%, p < 0.05), fewer awakenings (8.4 ± 1.3 vs. 10.7 ± 1.4, p < 0.01), and shorter wake after sleep onset (30.4 ± 4.7 vs. 41.6 ± 6.0 min, p < 0.01), whereas total sleep time did not differ significantly (p = 0.096). These findings suggest that one-week use of DPV576 sleepwear may improve wearable ECG-derived sleep consolidation in young men, supporting a nonpharmacological wearable strategy to enhance sleep efficiency in everyday settings. Full article

Pavement rutting is caused by grooves formed by vehicle traffic, affecting driving comfort, safety, and service life. Rutting detection methods have evolved from manual and automated approaches to intelligent detection for smart cities and maintenance. However, lightweight intelligent detection still faces challenges such as insufficient accuracy and technical complexity, and a mature system has yet to be established. This study aims to develop a portable intelligent terminal for pavement rut detection, which can address the challenges associated with traditional pavement rut detection while providing accuracy and reliability. In this study, rutting detection experiments were performed on a full-scale accelerated loading track to collect data on vibration acceleration, angular velocity, and attitude angles. Comparative experiments were carried out between traditional and lightweight detection methods. Subsequently, GRU-CNN, LSTM–Transformer, GRU, and LSTM models were developed to analyze and compare their performance in predicting rutting depth. The results show that the terminal operates stably, offering convenient usability and reliable data acquisition. Furthermore, vehicle angular velocity and roll angle emerge as critical indicators reflecting rutting impacts on driving states and prove suitable for pavement rut depth detection. The proposed GRU-CNN model achieves superior accuracy and overall performance relative to widely used models. Under synchronous detection conditions, the lightweight method yields a mean absolute error (MAE) of 1.22 mm, achieving performance improvements of 17.32%, 8.74%, and 10.08% over the LSTM–Transformer, GRU, and LSTM models, respectively. Additionally, the method yields a mean absolute percentage error of approximately 10.6%, representing error reductions of 15.87%, 19.08%, and 23.74% compared to the aforementioned baseline models, which meets application requirements. Innovation lies in the development of a lightweight intelligent terminal and GRU-CNN hybrid model that integrates vehicle dynamic parameters for large-scale pavement rutting detection. This study presents a lightweight, real-time pavement rutting detection method based on vehicle operation data for the construction and maintenance of smart cities and intelligent transportation infrastructure, combining the features of high cost effectiveness, high accuracy, and ease of large-scale application. Full article

Lightweight and slender footbridges exemplify sustainable, material-efficient infrastructure, yet their vibration performance is frequently governed by high dynamic sensitivity, which directly affects serviceability, user comfort, and structural durability. This paper provides a critical review of full-scale experimental investigations and validated finite element simulations addressing the dynamic behavior of various footbridges, focusing on the influence of structural typology, material solutions, and excitation characteristics on vibration-related performance within sustainability-driven design objectives. This article is organized into three core research themes: (1) standards and guidelines in bridge engineering practice, (2) dynamics of footbridges with special structural response to human-induced loading, including walking, running, crowd actions, and higher harmonic contributions, and (3) case studies, based on which the gaps in the current approach are formulated. Based on a synthesis of findings from leading research on structural dynamics and sustainable infrastructure, this paper highlights critical gaps in current vibration serviceability guidance for footbridges. Concluding remarks delineate the principal research challenges and formulate evidence-based, practical recommendations to enhance the resilience, vibration comfort compliance, and sustainability of future footbridge infrastructure. Full article

This paper investigates crowd–structure interaction (CSI) on low-frequency floors during concert events. The findings are based on a full-scale experimental study conducted on a floor prototype designed for a specific infrastructure project. Both the structure and the participants were instrumented while performing various rhythmic activities, such as bouncing and jumping. The study emphasizes the necessity of defining load cases based on the music signal, as its frequency and amplitude may have a variable probability of occurrence. Furthermore, human sensitivity to floor vibrations is examined, with specific comfort thresholds identified for different activities. The core contribution of this work lies in quantifying coordination levels for groups of up to 97 jumping individuals, extending the limited existing literature and refining the definition of jumping crowd actions. Additionally, modal characterization of the unoccupied prototype was performed to evaluate the equivalent damping provided by individuals during standing, walking, bouncing, or jumping. The results demonstrate that while the crowd has a significant impact on the system’s equivalent damping, this effect remains highly variable. Finally, the implications of these findings for structural engineering and design practices are discussed. Full article

Camber in high-speed railway prestressed concrete (PC) girders increases with service time and affects profile control, ride comfort, and durability; reliable long-term midspan camber prediction is therefore required. Building on established hybrid physics–data modeling and discrepancy-correction ideas, we present a monitoring-oriented two-layer strategy for long-term camber prediction. In the physics layer, a physics-informed neural network (PINN) is formulated in a quasi-static, stage-aware manner to capture the physics-consistent low-frequency trend governed by creep, shrinkage, prestress loss, and staged loading. In the data layer, an XGBoost model learns a bounded, measurement-level residual correction from monitoring features to account for additional effects not explicitly represented in the physics layer, without altering the underlying physics-driven trend. The approach is evaluated using monitoring data from five 1:4 scaled specimens of a 24 m post-tensioned simply supported box girder and is compared against a theoretical calculation and a standalone PINN. Across prediction stages and specimens, the proposed strategy reproduces the measured camber evolution more closely than the benchmarks while preserving physically plausible trend behavior and yielding more consistent errors among girders. These results indicate that, under the present scaled-specimen and independently calibrated setting, a stage-aware physics baseline combined with bounded residual correction can provide closer agreement with the observed camber evolution than the benchmark models under sparse-monitoring conditions. Its engineering applicability can be repeatedly demonstrated across girders with different construction-condition combinations after girder-wise calibration. Full article

Background and Objectives: Soft denture lining materials improve stress distribution and patient comfort but can lose mechanical stability under routine chemical cleansing. This study aimed to evaluate the time-dependent effects of two alkaline peroxide-based denture cleansing tablets (i.e., Efferdent and Protefix) on Shore A hardness and weight change of three soft lining materials (i.e., Ufi Gel P, Ufi Gel SC, and Visco-gel) at days 1, 7, and 30. Materials and Methods: Ninety specimens (n = 10/group) were assigned to a 3 × 3 factorial design. Specimens were immersed in cleansing solutions for 8 h daily and stored in artificial saliva for 16 h; controls remained solely in artificial saliva. Shore A hardness was measured using a durometer, and weight was recorded with a precision scale. Data were analyzed by mixed-design ANOVA and linear regression (α = 0.05). Results: Material type significantly affected hardness and weight change (p < 0.001). Visco-gel showed a marked increase in Shore A hardness (from about 15–16 to 26–27 HA) and greater weight loss (approximately 0.04–0.06 g), whereas silicone-based materials (Ufi Gel P and Ufi Gel SC) demonstrated more stable hardness values (from about 24–25 to 31–32 HA) with minimal weight variation (generally below about 0.02 g). The type of cleansing tablet had a smaller but significant effect (p = 0.004), with Protefix causing greater alterations. Weight change was negatively correlated with hardness increase (R² = 0.33, p < 0.001). Conclusions: Within the limitations of this in vitro study, material composition was identified as the main determinant of degradation resistance, with silicone-based liners demonstrating greater durability under the tested conditions, while Efferdent may be considered a milder option for long-term cleansing. Full article