Search Results (619)

This study investigates the engineering characteristics of a newly commissioned higher education building through the Bioharmological Conformity Assessment (BCA) method, specifically using the 2020vEB version. The BCA is a novel evaluation approach that assesses whether a building aligns with the identity of its users and its intended function. The engineering attributes of the structure were assessed across 12 core criteria, encompassing a total of 600 individual parameters. Findings from the BCA inspection indicate that the newly completed building falls into the category of “Near-Standard Building/Minor Modifications Required.” The BCA score was calculated as 398.73, corresponding to a deficiency rate of 25.50%. Notably, significant shortcomings were observed in categories such as user identity and intended use, Physical Characteristics of the Space, and Ecological and Seismological Suitability. Consequently, targeted improvements are necessary to align the building with bioharmological principles, requiring only minor adjustments to rectify the identified deficiencies. Full article

The extended operation of high-speed railways has led to an increased incidence of tunnel lining defects, with falling debris posing a significant safety threat. Within tunnels, single-train passage and trains-crossing events constitute the most frequent operational scenarios, both generating extreme aerodynamic environments that alter debris trajectories from free fall. To systematically investigate the aerodynamic differences and underlying mechanisms governing falling debris behavior under these two distinct conditions, a three-dimensional computational fluid dynamics (CFD) model (debris–air–tunnel–train) was developed using an improved delayed detached eddy simulation (IDDES) turbulence model. Comparative analyses focused on the translational and rotational motions as well as the aerodynamic load coefficients of the debris in both single-train and trains-crossing scenarios. The mechanisms driving the changes in debris aerodynamic behavior are elucidated. Findings reveal that under single-train operation, falling debris travels a greater distance compared with trains-crossing conditions. Specifically, at train speeds ranging from 250–350 km/h, the average flight distances of falling debris in the X and Z directions under single-train conditions surpass those under trains crossing conditions by 10.3 and 5.5 times, respectively. At a train speed of 300 km/h, the impulse of C_Fx and C_Fz under single-train conditions is 8.6 and 4.5 times greater than under trains-crossing conditions, consequently leading to the observed reduction in flight distance. Under the conditions of trains crossing, the falling debris is situated between the two trains, and although the wind speed is low, the flow field exhibits instability. This is the primary factor contributing to the reduced flight distance of the falling debris. However, it also leads to more pronounced trajectory deviations and increased speed fluctuations under intersection conditions. The relative velocity (CRV) on the falling debris surface is diminished, resulting in smaller-scale vortex structures that are more numerous. Consequently, the aerodynamic load coefficient is reduced, while the fluctuation range experiences an increase. Full article

In the field of high-altitude operations, the frequent occurrence of fall accidents is usually closely related to safety measures such as the incorrect use of safety locks and the wrong installation of safety belts. At present, the manual inspection method cannot achieve real-time monitoring of the safety status of the operators and is prone to serious consequences due to human negligence. This paper designs a new type of high-altitude operation safety device based on the STM32F103 microcontroller. This device integrates ultra-wideband (UWB) ranging technology, thin-film piezoresistive stress sensors, Beidou positioning, intelligent voice alarm, and intelligent safety lock. By fusing five modes, it realizes the functions of safety status detection and precise positioning. It can provide precise geographical coordinate positioning and vertical ground distance for the workers, ensuring the safety and standardization of the operation process. This safety device adopts multi-modal fusion high-altitude operation safety monitoring technology. The UWB module adopts a bidirectional ranging algorithm to achieve centimeter-level ranging accuracy. It can accurately determine dangerous heights of 2 m or more even in non-line-of-sight environments. The vertical ranging upper limit can reach 50 m, which can meet the maintenance height requirements of most transmission and distribution line towers. It uses a silicon carbide MEMS piezoresistive sensor innovatively, which is sensitive to stress detection and resistant to high temperatures and radiation. It builds a Beidou and Bluetooth cooperative positioning system, which can achieve centimeter-level positioning accuracy and an identification accuracy rate of over 99%. It can maintain meter-level positioning accuracy of geographical coordinates in complex environments. The development of this safety device can build a comprehensive and intelligent safety protection barrier for workers engaged in high-altitude operations. Full article

Background: Older adults are at high risk of falls, and head injuries following these events can have devastating consequences. The In-Patient Post Fall Clinical Pathway is a tool utilised in many hospitals in Queensland, Australia, to guide the need for CT brain imaging post-inpatient fall. This audit aimed to assess the use of CT imaging following inpatient falls in older adults, evaluate adherence to the In-Patient Post Fall Clinical Pathway, and explore factors associated with serious head injury. Methods: A retrospective audit was conducted across two regional Queensland hospitals over 2.5 years. Falls involving patients aged over 65 years were included. Data were analysed using descriptive and bivariate statistical tests. Results: Among 874 eligible falls, the mean patient age was 80.4 years, and approximately two-thirds were male. While 90.6% of patients who had fallen met clinical pathway criteria for a CT head scan, only 50.1% of them received a scan. Serious head injuries were uncommon (2.25% of total falls), with subdural haematoma being most frequent. Only one patient underwent neurosurgical intervention. No missed serious injuries were identified. No individual characteristic was significantly associated with serious head injury, although trends were observed for unwitnessed falls, falls from bed, falls with a head strike, new symptoms four hours post-fall, and anticoagulant use. Conclusions: There is a gap between clinical pathway recommendations and imaging practices, with clinicians often relying on judgement over strict adherence to guidelines. Further research is needed to inform evidence-based and practical decision-making to balance imaging use with clinical risk. Full article

Sustainable development is increasingly challenged by the growing threats of climate change. There is a close relationship between climate change, public health, and Sustainable Development Goals (SDGs). This study investigates the temperature anomalies in the Kingdom of Bahrain and their potential effects on human health. Furthermore, it proposes solutions to support Bahrain’s SDG-related goals. Data were collected from global studies and statistics and the Bahrain Meteorological Directorate over 50 years, which were then used to calculate the temperature anomalies and the heat indices, thereby exploring the past and present monthly and annual national temperature and sociated risks to human health. The results show that Bahrain is located in an area of high temperature anomalies and high rates of cardiovascular diseases. Furthermore, anomaly calculations indicate a critical rise in temperature, ranging from 1 to 4 °C higher than the averages recorded in the 1960s, 1970s, and 1980s. Such an increase could significantly affect human health, particularly since the heat index results show that summers consistently fall within the extreme danger ranges. In contrast, other seasons have occasionally reached the danger level or required extreme caution in certain years. Consequently, this study offers recommendations to help mitigate the rise in temperature and associated risks in the future. Full article

(1) Background: Detecting long-lie incidents—where individuals remain immobile after a fall—is essential for timely intervention and preventing severe health consequences. However, most existing systems focus only on fall detection, neglect post-fall monitoring, and raise privacy concerns, especially in real-time, non-invasive applications; (2) Methods: This study proposes a lightweight, privacy-preserving, long-lie detection system utilizing thermal imaging and a soft-voting ensemble classifier. A low-resolution thermal camera captured simulated falls and activities of daily living (ADL) performed by ten healthy participants. Human pose keypoints were extracted using MediaPipe, followed by the computation of five handcrafted postural features. The top three classifiers—automatically selected based on cross-validation performance—formed the soft-voting ensemble. Long-lie conditions were identified through post-fall immobility monitoring over a defined period, using rule-based logic on posture stability and duration; (3) Results: The ensemble model achieved high classification performance with accuracy, precision, recall, and an F1 score of 0.98. Real-time deployment on a Raspberry Pi 5 demonstrated the system is capable of accurately detecting long-lie incidents based on continuous monitoring over 15 min, with minimal posture variation; (4) Conclusion: The proposed system introduces a novel approach to long-lie detection by integrating privacy-aware sensing, interpretable posture-based features, and efficient edge computing. It demonstrates strong potential for deployment in homecare settings. Future work includes validation with older adults and integration of vital sign monitoring for comprehensive assessment. Full article

An aging society increases the demand for solutions that enable quick reactions, such as calling for help in response to events that may threaten life or health. One of such events is a fall, which is a common cause (or consequence) of injuries among the elderly, that can lead to health problems or even death. Fall may be also a symptom of a serious health problem, such as a stroke or a heart attack. This study addresses the fall detection problem. We propose a fall detection solution based on accelerometer data from smartphone devices. The proposed model is based on a Recurrent Neural Network employing a Gated Recurrent Unit (GRU) layer. We compared the results with the state-of-the-art solutions available in the literature using the UniMiB SHAR dataset containing accelerometer data collected using smartphone devices. The dataset contains the validation dataset prepared for evaluation using the Leave-One-Subject-Out (LOSO-CV) and 5-Fold Cross-Validation (CV) strategies; consequently, we used them for evaluation. Our solution achieves the highest result for Leave-One-Subject-Out and a comparable result for the k-Fold Cross-Validation strategy, achieving 98.99% and 99.82% accuracy, respectively. We believe it has the potential for adoption in production devices, which could be helpful, for example, in nursing homes, improving the provision of assistance especially when combined into a multimodal system with other sensors. We also provide all the data and code used in our experiments publicly, allowing other researchers to reproduce our results. Full article

Renewable energy-driven water electrolysis is widely regarded as a pivotal approach for achieving carbon-free hydrogen production. The development of highly efficient electrocatalysts is crucial to advancing the efficiency and scalability of electrolytic water splitting. Recent advancements in characterization techniques have revealed that catalysts often undergo surface reconstruction during the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), leading to the formation of real active species. Understanding the surface reconstruction process through advanced characterization methods is essential for the rational design of high-performance catalysts. However, the surface reconstruction of catalysts is a highly complex phenomenon, and conventional ex situ characterization techniques often fall short of capturing the dynamic evolution of the catalyst surface. Consequently, in situ characterization methods have emerged as indispensable tools for elucidating the surface reconstruction process. This paper provides a detailed review of the process of surface reconstruction, the reasons behind it, and the in situ characterization methods, and finally discusses the challenges faced by the characterization methods for the reconstruction of water electrolysis catalysts in future development. Full article

Floating aquatic vegetation and algal blooms are increasing with global warming, potentially reducing UVB exposure and, consequently, vitamin D (vit-D) synthesis in freshwater turtles. Vit-D mediates calcium metabolism and overall health, yet the effects of floating aquatic vegetation on vit-D levels remain unclear, as is whether turtles actively avoid habitats with abundant floating vegetation. Here, we address these questions by quantifying vit-D₃ levels in the blood of adult female painted turtles (Chrysemys picta) exposed to high-vegetation (darker/colder) or clear-water (lighter/warmer) treatments for one month outdoors and one month indoors at a single temperature during late summer and early fall. The observed circulating vit-D₃ levels resembled those reported for other freshwater turtles, declined over time in both treatments, and were marginally lower under high vegetation after 60 days compared to clear water. However, this difference disappeared after correcting for lymph contamination and multiple comparisons, suggesting that perhaps adult females are robust to the effect of floating vegetation, but whether they were buffered by vit-D₃ stores in lipids is unclear. Additionally, in subsequent years, females were exposed to habitat choice experiments and exhibited a strong preference for high floating vegetation over clear water, both as a group (outdoors) and individually (outdoors, and indoors at 21 °C and 26 °C), consistent with known benefits conferred by floating vegetation (food, predator avoidance). While no ill effects of high vegetation nor behavioral avoidance were detected here, longer experiments at different seasons on both sexes and varying ages are warranted before concluding whether painted turtles are truly resilient in their vit-D levels or if, instead, a tradeoff exists between the known benefits of floating vegetation and potential [yet unidentified] detrimental effects (lower dissolved oxygen or vit-D) when vegetation is overgrown for extended periods. Full article

Progressive global aging has increased the number of elderly individuals living alone. The consequent rise in fall accidents has worsened physical injuries, reduced the quality of life, and increased medical expenses. Existing wearable fall-detection devices may cause discomfort, and camera-based systems raise privacy concerns. Here, we propose a non-contact fall-detection system that integrates 4D imaging radar sensors with artificial intelligence (AI) technology to detect falls through real-time monitoring and visualization using a web-based dashboard and Unity engine-based avatar, along with immediate alerts. The system eliminates the need for uncomfortable wearable devices and mitigates the privacy issues associated with cameras. The radar sensors generate Point Cloud data (the spatial coordinates, velocity, Doppler power, and time), which allow analysis of the body position and movement. A CNN model classifies postures into standing, sitting, and lying, while changes in the speed and position distinguish falling actions from lying-down actions. The Point Cloud data were normalized and organized using zero padding and k-means clustering to improve the learning efficiency. The model achieved 98.66% accuracy in posture classification and 95% in fall detection. This study demonstrates the effectiveness of the proposed fall detection approach and suggests future directions in multi-sensor integration for indoor applications. Full article

A model for a fast and reliable evaluation of the impact of MOSFETs’ switching losses in the global performances of a high-frequency wireless power converter is proposed. The frequency domain model for an LCC-S wireless resonant converter is presented. The contribution of MOSFET behavior is counted considering a trapezoidal input voltage in the converter instead of the classic square wave or Pulse Width Modulation wave to take into account MOSFETs’ rise and fall times. These times are evaluated with a simplified first-order circuit able to model the MOSFET behavior during commutations. Two commercial MOSFETs have been integrated in the converter model. The predictions of the proposed approach are compared (for validation) with results coming from Simulink environment, where the converter behavior can be reproduced in a very realistic way. An evaluation of switching losses is presented, and the consequent impact on converter performances is evaluated by comparing the converter output voltage (and output power) predicted with the proposed model and that one is achievable by the converter considering ideal switches. The analysis has been performed considering different values of input voltage and load resistance. This approach can be easily generalized to every resonant converter topology. Full article

Simulator training offers a safe and cost-effective approach to providing new operators opportunities to become familiar with operating modern machinery. However, in Korea, the current programs are insufficient in training skilled operators capable of handling advanced forestry machinery. Consequently, these programs fall short of developing the required technical expertise, leading to difficulties in workforce employment. We compared the performance of simulator-trained participants with that of machine-trained participants by testing operators on real equipment and assessing their stress levels. Participants were categorized as those with and without excavator certificates. Within each category, participants were further divided into those receiving training via simulators or those who were trained using actual equipment. Although we detected no significant differences in the overall performance of simulator- and machine-trained participants, compared with real machine training, simulator training promoted better performance, lower levels of frustration, and a reduced mental workload due to the safer and more controlled virtual environment. These findings can be used to develop more effective training programs by incorporating simulator-based modules that enhance skill acquisition whilst reducing risks. They can also inform policy decisions to improve workforce training in industries dependent on the operation of advanced machinery, thereby ensuring that operators achieve higher levels of competence and safety. Full article

The rise in temperature worldwide, especially in hot regions with extreme weather conditions, has made climate change one of the critical issues that degrades the solar photovoltaic (PV) system performance. In this paper, a new design of solar cells based on plasmonic thin-film Silver (Ag) technology is introduced. The new design is characterized by enhancing thermal effects, optical power absorption, and output power significantly, thus compensating for the deterioration in the solar cells efficiency when the ambient temperature rises to high levels. The temperature distribution on a PV solar module is determined using a three-dimensional computational fluid dynamics (CFD) model that includes the front glass, crystalline cells, and back sheet. Experimental and analytical results are presented to validate the CFD model. The parameters of temperature distribution, absorbed optical power, and output electrical power are considered to evaluate the device performance during daylight hours in summer. The effects of solar radiation falling on the solar cell, actual temperature of the environment, and wind speed are investigated. The results show that the proposed cells’ temperature is reduced by 1.2 °C thanks to the plasmonic Ag thin-film technology, which leads to enhance 0.48% real value as compared to that in the regular solar cells. Consequently, the absorbed optical power and output electrical power of the new solar cells are improved by 2.344 W and 0.38 W, respectively. Full article

During the electromagnetic launching process, the actual current input into the launcher is obtained by controlling the discharge of the pulsed power supply. Generally, the waveform of the pulse current is determined by the discharge characteristics and discharge time of the pulse power supply. Due to the limitation of control accuracy, the driving current is not an ideal trapezoidal wave, but there is a certain fluctuation (current ripple) in the flat top portion of the trapezoidal wave. The fluctuation of the current will affect the thickness of the liquefied layer at the armature–rail interface as well as the magnitude of the contact pressure, thereby inducing instability at the armature–rail interface and generating micro-arcs, which result in a reduction in the service life of the rails within the launcher. Consequently, it is imperative to conduct an in-depth analysis of the influence of current ripple on the liquefied layer during electromagnetic launching. In this paper, a thermoelastic magnetohydrodynamic model is constructed by coupling temperature, stress, and electromagnetic fields, which are predicated on the Reynolds equation of the metal liquefied layer at the armature–rail contact interface. The effects of current fluctuations on the melting rate of the surface of the armature, the thickness of the liquefied layer, and the hydraulic pressure of the liquefied layer under four different current ripple coefficients (RCs) were analyzed. The results show the following: (1) The thickness and the pressure of the liquefied layer at the armature–rail interface fluctuate with the fluctuation of the current, and, the larger the ripple coefficient, the greater the fluctuations in the thickness and pressure of the liquefied layer. (2) The falling edge of the current fluctuation leads to a decrease in the hydraulic pressure of the liquefied layer, which results in the instability of the liquefied layer between the armature and rails. (3) As the ripple coefficient increases, the time taken for the liquefied layer to reach a stable state increases. In addition, a launching experiment was also conducted in this paper, and the results showed that, at the falling edge of the current fluctuation, the liquefied layer is unstable, and a phenomenon such as the ejection of molten armature and transition may occur. The results of the experiment and simulations mutually confirm that the impact of current fluctuations on the armature–rail interface increases with increases in the ripple coefficient. Full article

Energy depletion and environmental pollution have emerged as pressing global concerns, demanding the urgent promotion of green and clean energy sources. As such, the efficient utilization of solar energy for hydrogen production has gained significant research attention, with semiconductor photocatalysis emerging as an effective strategy. However, harnessing the full potential of semiconductor photocatalysis still poses great challenges. Notably, the limited utilization of visible light and the substantial recombination of photogenerated electron–hole pairs adversely affect photocatalytic performance, ultimately impeding the further development and practical application of semiconductor photocatalysis. Perylene diimide (PDI), an n-type semiconductor distinguished by its conjugated π-π bonds, exhibits remarkable photoelectric properties. Its energy band gap falls within the absorption range of visible light, ensuring remarkable light absorption efficiency. Furthermore, the photogenerated charge can be efficiently conducted along the π-π stacking in its structural unit, significantly reducing electron–hole recombination. Consequently, PDI holds immense potential for achieving visible-light-driven photocatalytic hydrogen production. Yet, despite these attributes, the photocatalytic efficiency of pure PDI is still far from practical use, necessitating innovative modifications to elevate its catalytic performance. In this review, we begin with an in-depth exploration of the principles underlying photocatalytic hydrogen production and discuss various strategies aimed at enhancing photocatalytic performance. We also engage in a comprehensive discussion and summation of the challenges encountered and the future prospects of PDI-based materials. Our endeavor is to pave the way for groundbreaking advancements in the field of photocatalysis, ultimately contributing to a cleaner and more sustainable future. Full article