Search Results (10,040)

Cataracts cause vision loss in rabbits, often either spontaneously or as secondary to uveitis. This study considers the ophthalmic presentation, treatment, and outcome of phacoemulsification in seven pet rabbits: six presenting with lens cloudiness and one presenting with a white mass in the iris. Ophthalmic examinations revealed cataracts. The treatment plan was phacoemulsification. Encephalitozoon cuniculi was identified via an enzyme-linked immunosorbent assay technique performed on all rabbits. Ocular ultrasonography was performed to rule out retinal detachment. Phacoemulsification using the one-handed technique without intraocular lens implantation was performed in 8 of the eyes of the 7 rabbits. After surgery, the corneal wounds healed within 2 weeks. All rabbits were comfortable with opening their eyes and had a positive dazzle reflex and a clear visual axis, with no other severe complications (such as retinal detachment, intraocular hemorrhaging, or uncontrolled glaucoma) throughout the post-operative period. Postoperative complications consisted of corneal edema around the surgical wound (2 eyes; 25%); partial anterior synechiae (1 eye; 12.5%); partial posterior synechiae (5 eyes; 3 eyes before surgery and 2 eyes after surgery; 25%); posterior capsular opacities (3 eyes; 37.5%); and lens fiber overgrowths (2 eyes; 25%). In conclusion, successful phacoemulsification was achieved in the seven pet rabbits. Full article

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative syndrome which often leads to progressive muscular dysfunction and therefore oral health deterioration. The aim of this scoping review is to evaluate oral health status in ALS patients focusing on the importance of dental care in improving patient’s quality of life. Methods: A comprehensive literature search was conducted on PubMed, Scopus, Web of Science, and Embase databases until June 2025 using a combination of keywords and MeSH terms related to ALS and oral health. Studies were screened and selected based on inclusion and exclusion criteria, focusing on human clinical data reporting oral health outcomes in ALS. Results: Eight studies met the inclusion criteria. The findings showed a high prevalence of oral complications in bulbar-onset ALS patients. Common issues included reduced tongue mobility, poor oral hygiene, sialorrhea, and decreased masticatory function were evaluated. Conclusions: Oral health impairment in ALS patients frequently contributes to systemic risks and reduced quality of life. A dental expert may play an important role in multidisciplinary care teams in terms of early diagnosis and conservative treatment of oral diseases ranging from periodontal disease to temporomandibular disorders (TMD). Personalized oral hygiene strategies and adjunctive therapies may serve as key elements in maintaining overall health and patient comfort in ALS. Therefore, the objective of the following review was to evaluate oral health complication in patients with ALS, highlighting the impact of oral care on patients’ quality of life. Full article

Fuel cell trucks are a promising solution to reduce the disproportionately high greenhouse gas emissions of heavy-duty long-haul transportation. However, unlike conventional diesel vehicles, they lack combustion engine waste heat for cabin heating. As a result, electric heaters are often employed, which increase auxiliary energy consumption and reduce driving range. To address this challenge, advanced control strategies are needed to improve heating efficiency while maintaining passenger comfort. This study proposes and validates a methodology for implementing Model Predictive Control (MPC) in the cabin heating system of a fuel cell truck. Vehicle experiments were conducted to characterize dynamic heating behavior, passenger comfort indices, and to provide validation data for the mathematical models. Based on these models, an MPC strategy was developed in a Model-in-the-Loop simulation environment. The proposed approach achieves energy savings of up to 8.1% compared with conventional control using purely electric heating, and up to 21.7% when cabin heating is coupled with the medium-temperature cooling circuit. At the same time, passenger comfort is maintained within the desired range (PMV within ±0.5 under typical winter conditions). The results demonstrate the potential of MPC to enhance the energy efficiency of fuel cell trucks. The methodology presented provides a validated foundation for the further development of predictive thermal management strategies in heavy-duty zero-emission vehicles. Full article

The building sector is under increasing pressure to lower its environmental impact, prompting renewed interest in raw soil as a low-carbon and locally available material. This study investigates the mechanical and thermal properties of clay-based masonry walls through a comprehensive experimental program on earthen mortars, bricks, and their interfaces, considering both stabilized and non-stabilized formulations. Compressive, bending, and shear tests reveal that strength is strongly influenced by mortar composition, hydration time, and the soil-to-sand ratio. The addition of 5–7.5% cement yields modest gains in compressive strength but increases the carbon footprint, whereas extended pre-hydration achieves similar improvements with lower environmental costs. Thermal characterization of the studied samples (SiO₂ ≈ 61.2 wt%, Al₂O₃ ≈ 11.7 wt%, MgO ≈ 5.1 wt%) revealed that SiO₂-enriched compositions significantly enhance thermal conductivity, whereas the presence of Al₂O₃ and MgO contributes to increased heat capacity and improved moisture regulation. These findings suggest that well-optimized clay-based mortars can satisfy the structural and thermal requirements of non-load-bearing applications, offering a practical and sustainable alternative to conventional construction materials. By reducing embodied carbon, enhancing hygrothermal comfort, and relying on locally available resources, such mortars contribute to the advancement of green building practices and the transition towards low-carbon construction. Full article

The hyperinsulinemic–euglycemic clamp technique is considered the gold standard for measuring insulin sensitivity in large animals. We developed a practical method for conducting concurrent glucose clamp experiments in a pair of sedated farm swine positioned in a sling. Descriptions of customized equipment and central venous access surgical procedures for blood collection are provided. Personnel functions are described for execution of the clamp protocol. A total of 24 hyperinsulinemic–euglycemic clamp studies were performed over 6 weeks. Infusaports remained functional for 1454 blood samples. There were three CSII catheter occlusions during bolus administration, and the swine showed no signs of infection or disease. IM telazol at 1.0 mg/kg, administered 1–2 h prior (mean of 3.26 mL ± 1.59) was effective in keeping animals comfortable. SpO₂ and heart rate remained within normal ranges. Means ± SD total infused volumes for octreotide, 10% dextrose, and saline were 9.7 ± 0.93 mL, 2328.0 ± 672.8 mL, and 690.3 ± 206.8 mL. Mean blood glucose was maintained between 75.7 and 87.8 mg/dL (CV 3.17%) for the 24 experiments. The GIR infusion rate peaked between 15 and 60 min after insulin bolusing, with insulin C_max of 108.5 pmol/L and t_max at 10 min. All aspects of the protocol were effectively carried out. The animals remained in good health, and the implanted infusion ports remained patent for over 700 blood draws per animal. This method could potentially reduce the number of animals used and the costs of other similar experiments. Full article

This study presents the design, development, and experimental validation of a novel cable-driven shoulder exosuit (CDSE) for upper limb rehabilitation and assistance. Unlike existing exoskeletons, which are often bulky, limited in degrees of freedom (DOFs), or impractical for home use, the proposed DSE offers a lightweight (≈2 kg), portable, and wearable solution capable of supporting three shoulder movements: abduction, flexion, and horizontal adduction. The system employs a bioinspired tendon-driven mechanism using Bowden cables, transferring actuation forces from a backpack to the arm, thereby reducing user load and improving comfort. Mathematical models and inverse kinematics were derived to determine cable length variations for targeted motions, while control strategies were implemented using a PID-based approach in MATLAB Simscape-Multibody simulations. The prototype was fabricated in three iterations using PLA, aluminum, and carbon fiber—culminating in a durable and ergonomic final version. Experimental evaluations on a healthy subject demonstrated high accuracy in position tracking (<5% error) and torque profiles consistent with simulation outcomes, validating system robustness. The CDSE successfully supported loads up to 4 kg during rehabilitation tasks, highlighting its potential for clinical and at-home applications. This research contributes to advancing wearable robotics by addressing portability, biomechanical alignment, and multi-DOF functionality in upper limb exosuits. Full article

A personalized framework for smart home automation is introduced, utilizing machine learning to predict user activities and allow for the context-aware control of living spaces. Predicting user activities, such as ‘Watch_TV’, ‘Sleep’, ‘Work_On_Computer’, and ‘Cook_Dinner’, is essential for improving occupant comfort, optimizing energy consumption, and offering proactive support in smart home settings. The Edge Light Human Activity Recognition Predictor, or EL-HARP, is the main prediction model used in this framework to predict user behavior. The system combines open-source software for real-time sensing, facial recognition, and appliance control with affordable hardware, including the Raspberry Pi 5, ESP32-CAM, Tuya smart switches, NFC (Near Field Communication), and ultrasonic sensors. In order to predict daily user activities, three gradient-boosting models—XGBoost, CatBoost, and LightGBM (Gradient Boosting Models)—are trained for each household using engineered features and past behaviour patterns. Using extended temporal features, LightGBM in particular achieves strong predictive performance within EL-HARP. The framework is optimized for edge deployment with efficient training, regularization, and class imbalance handling. A fully functional prototype demonstrates real-time performance and adaptability to individual behavior patterns. This work contributes a scalable, privacy-preserving, and user-centric approach to intelligent home automation. Full article

Urban school environments often face significant thermal discomfort due to extensive paved surfaces, limited vegetation, and outdated building designs. This study examines how green spaces can mitigate temperature extremes and improve thermal comfort at two secondary schools in Coimbra, Portugal: Escola Secundária José Falcão (ESJF) and Escola Secundária D. Dinis (ESDD). Using a mixed-methods approach that combined school community surveys with on-site microclimatic measurements, we integrated user feedback on comfort with data on temperature and humidity variations across different indoor and outdoor spaces. Results revealed that tree-shaded areas consistently maintained lower air temperatures and higher relative humidity than unshaded zones, which experienced intense heat accumulation—up to a 5 °C difference. At ESJF, the older infrastructure and large asphalt surfaces led to severe heat retention, with east-facing classrooms recording the highest indoor temperatures. ESDD’s pavilion-style layout and existing green spaces provided comparatively better thermal conditions, although insufficient vegetation maintenance and limited shade reduced their effectiveness. The findings demonstrate a clear correspondence between the school community’s perceptions of thermal comfort and the measured microclimatic data. Vegetation—particularly deciduous trees—plays a critical role in cooling the school microclimate through shading and evapotranspiration. Strategic interventions such as expanding tree cover in high-exposure areas, installing green roofs and walls, and carefully selecting species can significantly reduce temperature extremes and improve outdoor usability. In addition, fostering environmental education and participatory co-design programs can encourage sustainable behaviors within the school community, underlining the importance of inclusive, nature-based solutions for climate adaptation. This research highlights that integrating green infrastructure in school design and management is a cost-effective strategy for thermal regulation. Green spaces, when co-designed with community involvement, not only enhance climate resilience and student well-being but also contribute to broader sustainable urban development goals. Full article

This study numerically investigates the effect of hydrofoil installation on the motion responses and ride comfort of a 20 m monohull vessel operating at 10 knots in regular waves. Linear seakeeping analysis (Maxsurf Motions) and nonlinear computational fluid dynamics (CFD) simulations (STAR-CCM+) are performed to compute response-amplitude operators (RAOs); for the bare hull, the two methods agree within 5%, confirming methodological reliability. The CFD results show that hydrofoils reduce heave and pitch amplitudes by approximately 16% on average. Motion Sickness Incidence (MSI) analysis indicates negligible seasickness under Gentle Breeze conditions, even during prolonged exposure; under Moderate conditions, no seasickness is predicted within 30 min across all encounter frequencies. Although linear analysis cannot directly estimate MSI for hydrofoil-fitted cases, the observed reductions in RAOs imply improved ride comfort. Overall, these findings demonstrate that hydrofoils can enhance motion stability and passenger comfort in small, low-speed vessels, providing quantitative evidence to support design applications. Full article

Urban mobility plays a vital role in shaping sustainable cities, yet the effectiveness of public transportation is often undermined by poor last-mile connectivity (LMC). In the National Capital Region (NCR) of Delhi, despite the Delhi Metro Rail serving as a key transit system, limited integration with surrounding areas hinders accessibility, which particularly affects women, elderly adults, and socioeconomically disadvantaged groups. This study evaluates LMC performance at two key metro stations, Nehru Place and Botanical Garden, using a mixed-methods approach that includes user surveys, spatial survey, thematic analysis, and infrastructure scoring across five critical pillars: accessibility, safety and comfort, intermodality, service availability, and inclusivity. The findings communicate notable contrasts. Botanical Garden exhibits strong intermodal linkages, pedestrian-friendly design, and supportive signage, while Nehru Place indicates a need for infrastructural improvements, safety advancement and upgrades, and strengthened universal design features. These disparities limit effective metro usage and discourage a shift from private to public transport. The study highlights the importance of user-centered, multimodal solutions and the need for cohesive urban governance to address LMC gaps. By identifying barriers and opportunities for improvement, this research paper contributes to the formulation of more inclusive and sustainable urban transport strategies in Indian metropolitan regions. Full article

Arthritis and arthrosis are prevalent joint diseases that cause pain and disability, and their early diagnosis is crucial for preventing irreversible damage. Conventional diagnostic methods such as X-ray, ultrasound, and MRI have limitations in early detection, prompting interest in alternative techniques. This work presents the design and clinical evaluation of a prototype device for non-invasive early diagnosis of arthritis (inflammatory joint disease) and arthrosis (osteoarthritis) using infrared thermography and deep neural networks. The portable prototype integrates a Raspberry Pi 4 microcomputer, an infrared thermal camera, and a touchscreen interface, all housed in a 3D-printed PLA enclosure. A custom Flask-based application enables two operational modes: (1) thermal image acquisition for training data collection, and (2) automated diagnosis using a pre-trained ResNet50 deep learning model. A clinical study was conducted at a university clinic in a temperature-controlled environment with 100 subjects (70% with arthritic conditions and 30% healthy). Thermal images of both hands (four images per hand) were captured for each participant, and all patients provided informed consent. The ResNet50 model was trained to classify three classes (healthy, arthritis, and arthrosis) from these images. Results show that the system can effectively distinguish healthy individuals from those with joint pathologies, achieving an overall test accuracy of approximately 64%. The model identified healthy hands with high confidence (100% sensitivity for the healthy class), but it struggled to differentiate between arthritis and arthrosis, often misclassifying one as the other. The prototype’s multiclass ROC (Receiver Operating Characteristic) analysis further showed excellent discrimination between healthy vs. diseased groups (AUC, Area Under the Curve ~1.00), but lower performance between arthrosis and arthritis classes (AUC ~0.60–0.68). Despite these challenges, the device demonstrates the feasibility of AI-assisted thermographic screening: it is completely non-invasive, radiation-free, and low-cost, providing results in real-time. In the discussion, we compare this thermography-based approach with conventional diagnostic modalities and highlight its advantages, such as early detection of physiological changes, portability, and patient comfort. While not intended to replace established methods, this technology can serve as an early warning and triage tool in clinical settings. In conclusion, the proposed prototype represents an innovative application of infrared thermography and deep learning for joint disease screening. With further improvements in classification accuracy and broader validation, such systems could significantly augment current clinical practice by enabling rapid and non-invasive early diagnosis of arthritis and arthrosis. Full article

This research is based on the acoustic package design of new energy vehicles, investigating the application of the hybrid Finite Element–Statistical Energy Analysis (FE-SEA) model in predicting the high-frequency dynamic response of automotive structures, with a focus on the modeling and correction methods for hybrid point connections. New energy vehicles face unique acoustic challenges due to the special nature of their power systems and operating conditions, such as high-frequency noise from electric motors and electronic devices, wind noise, and road noise at low speeds, which directly affect the vehicle’s ride comfort. Therefore, optimizing the acoustic package design of new energy vehicles to reduce in-cabin noise and improve acoustic quality is an important issue in automotive engineering. In this context, this study proposes an improved point connection correction factor by optimizing the division range of the decision circle. The factor corrects the dynamic stiffness of point connections based on wave characteristics, aiming to improve the analysis accuracy of the hybrid FE-SEA model and enhance its ability to model boundary effects. Simulation results show that the proposed method can effectively improve the model’s analysis accuracy, reduce the degrees of freedom in analysis, and increase efficiency, providing important theoretical support and reference for the acoustic package design and NVH performance optimization of new energy vehicles. Full article

Ambient temperature and thermoregulation influence sleep quality. This study investigated the effects of a temperature-controlled mattress cover on sleep and perceptual outcomes in healthy adults. In a randomised, counterbalanced, crossover design, 34 healthy adults (20 F, 14 M; age, 30 ± 5 y) used a temperature-controlled mattress cover for 14 nights, following ≥3 nights of familiarisation. The temperature feature was on for 7 nights (POD) and off for 7 nights (CON). Sleep was assessed via wrist actigraphy, while heart rate (HR), heart rate variability (HRV), and respiratory rate (RR) were recorded by embedded sensors in the mattress cover. Participants completed daily and weekly questionnaires evaluating sleep quality, thermal comfort, and thermal sensation. Linear mixed models showed significant main effects of condition favouring POD over CON for all daily perceived outcomes (all p < 0.05). A large, significant improvement in perceived sleep quality was observed (p = 0.001, d = 0.92). No significant differences were found in objective sleep metrics or biometric measures (all p ≥ 0.05). A temperature-controlled mattress cover was associated with improved subjective sleep quality and thermal-related perceptions despite minimal changes in objective or biometric outcomes, which may in part reflect expectancy, or placebo effects. Further research is needed to explore whether these perceptual benefits lead to physiological improvements over time. Full article

The development of the Connected and Autonomous Vehicle (CAV) and Hybrid Electric Vehicle (HEV) provides a new effective means for the optimization of eco-driving strategies. However, the existing research has not effectively considered the cooperative speed optimization and power allocation problem of the Connected and Autonomous Plug-in Hybrid Electric Vehicle (CAPHEV) platoon. To this end, a hierarchical eco-driving strategy is proposed, which aims to enhance driving efficiency and fuel economy while ensuring the safety and comfort of the platoon. Firstly, an improved car-following model is proposed, which considers the motion states of multiple preceding vehicles. On this basis, a platoon cooperative car-following decision-making method based on model predictive control is designed. Secondly, a distributed energy management strategy is constructed, and a bionic optimization algorithm based on the behavior of nutcrackers is introduced to solve nonlinear problems, so as to solve the energy distribution and management problems of powertrain systems. Finally, the tests are conducted under the driving cycle of the Urban Dynamometer Driving Schedule (UDDS) and the Highway Fuel Economy Test (HWFET). The results show that the proposed strategy can ensure the driving safety of the CAPHEV platoon in different scenes, and has excellent tracking accuracy and driving comfort. Compared with the rule-based strategy, the equivalent energy consumption of UDDS and HWFET is reduced by 20.7% and 5.5% in the battery’s healthy charging range, respectively. Full article

This study presents a comprehensive assessment of lighting conditions in the Intensive Care Units (ICUs) of two major hospitals in the Democratic Republic of Congo (DRC): Hospital du Cinquantenaire in Kinshasa and Jason Sendwe Hospital in Lubumbashi. A mixed-methods approach was employed, integrating continuous illuminance monitoring with structured staff surveys to evaluate visual comfort in accordance with the EN 12464-1 standard for indoor workplaces. Objective measurements revealed that more than 52.2% of the evaluated ICU workspaces failed to meet the recommended minimum illuminance level of 300 lux. Subjective responses from healthcare professionals indicated that poor lighting significantly reduced job satisfaction by 40%, lowered self-rated task performance by 30%, decreased visual comfort scores from 4.1 to 2.6 (on a 1–5 scale), and increased the prevalence of well-being symptoms (eye fatigue, headaches) by 25–35%. Frequent complaints included eye strain, glare, and discomfort with posture, with these issues often exacerbated during the rainy season due to reduced natural daylight. The study highlights critical deficiencies in current lighting infrastructure and emphasizes the need for urgent improvements in clinical environments. Moreover, inconsistent energy supply to these healthcare settings also impacts the assurance of visual comfort. To address these shortcomings, the study recommends transitioning to energy-efficient LED lighting, enhancing access to natural light, incorporating circadian rhythm-based lighting systems, enabling individual lighting control at workstations, and ensuring a consistent power supply via the integration of solar inverters to the grid supply. These interventions are essential not only for improving healthcare staff performance and safety but also for supporting better patient outcomes. The findings offer actionable insights for hospital administrators and policymakers in the DRC and similar low-resource settings seeking to enhance environmental quality in critical care facilities. Full article