Search Results (1,841)

A healthy vasculature with well-regulated perfusion and pulsatility is essential for the brain. One vascular structure that has received little attention is the carotid siphon. The proximal portion of the siphon is stiff due to the narrow location in the skull base, whilst the distal portion is highly flexible. This flexible part in combination with the specific curves lead to lower pulsatility at the cost of energy deposition in the arterial wall. This deposited energy contributes to damage and calcification. Severe siphon calcification stiffens the distal part of the siphon, leading to less damping of the pulsatility. Increased blood flow pulsatility is a possible cause of stroke and cognitive disorders. In this review, based on comprehensive multimodality imaging, we first describe the anatomy and physiology of the carotid siphon. Subsequently, we review the in vivo imaging data, which indeed suggest that the siphon attenuates pulsatility. Finally, the data as available in the literature are shown to provide convincing evidence that severe siphon calcifications and the calcification pattern are linked to incident stroke and dementia. Interventional studies are required to test whether this association is causal and how an assessment of pulsatility and the siphon calcification pattern can improve personalized medicine, working to prevent and treat brain disease. Full article

Residential areas are characterized by closely packed buildings which disturb wind flow resulting in low wind speeds (below 2 m/s) with a high turbulence intensity (above 20%). In order to interface between off-the-shelf wind turbines and low-quality wind, the Increased velocity (INVELOX) wind delivery system is an attractive wind augmentation option for such regions. The INVELOX setup can harness more energy than conventional bare wind turbines under the same incident wind conditions. However, these systems also have drawbacks and challenges that they face in their operation, which amplify the need to review, understand, and expose gaps and flaws in pursuit of increased power production in low wind quality environments. This paper seeks to review and simplify the advances done by various scholars towards improving the INVELOX delivery system. It provides the mathematical foundation on which these advances are rooted and gives an understanding of how the improvements better the geometric properties of INVELOX. The article concludes by proposing future research directions. Full article

A square patch metasurface is designed, simulated, fabricated, and experimentally tested to investigate polarization characteristics quantitatively. The metasurface consists of one layer unit cell in the form of a square patch with one via and a lumped resistor, which is used for harvesting RF (radio frequency) energy. FR4 dielectric is used as a substrate supported by a metal ground plane. Polarization-dependent properties with specific surface current patterns and voltage dip are obtained when simulating under normal incidence of a plane wave. This characteristic results from changes in surface current conditions when the polarization angle is varied. A voltage dip appears at a specific polarization angle when the surface current pattern is symmetrical. This condition occurs when the position of the lumped resistor from the center of the patch is perpendicular to the linearly polarized incident electric field. A couple of 10 × 10 arrays with different resistor positions are fabricated and tested. The experimental results are in good agreement with the simulated results. The proposed design demonstrates a symmetric unit cell structure with one via and a resistor that exhibits polarization-dependent behavior for linear polarization. An asymmetric patch design is explored through both simulation and measurement to mitigate polarization dependence by suppressing the dip behavior, albeit at the expense of reduced absorption efficiency. This study provides a complete polarization analysis for both symmetric and asymmetric patch metasurfaces with a single via and a single lumped resistor, and introduces a predictive relation between the position of the resistor relative to the center of the patch and the resulting voltage dip behavior. Full article

The improvement of environmental conditions has become a priority for governments and legislators. New electrified mobility systems are increasingly present in our environment, as they enable the reduction of polluting emissions. Electric vehicles (EVs) are one of the fastest-growing alternatives to date, with exponential growth expected over the next few years. In this article, the various charging modes for EVs are explored, and the risks associated with charging technologies are analysed, particularly for charging systems in high-power DC with Lithium battery energy storage, given their long market deployment and characteristic behaviour. In particular, the Arc Flash (AF) risk present in high-power DC chargers will be studied, involving numerous simulations of the charging process. Subsequently, the Incident Energy (IE) analysis is carried out at different specific points of a commercial high-power ‘Mode 4’ charger. For this purpose, different analysis methods of recognised prestige, such as Doan, Paukert, or Stokes and Oppenlander, are applied, using the latest version of the ETAP^® simulation tool version 22.5.0. This study focuses on quantifying the potential severity (consequences) of an AF event, assuming its occurrence, rather than performing a probabilistic risk assessment according to standard methodologies. The primary objective of this research is to comprehensively quantify the potential consequences for workers involved in the operation, maintenance, repair, and execution of tasks related to EV charging systems. This analysis makes it possible to provide safe working conditions and to choose the appropriate and necessary personal protective equipment (PPE) for each type of operation. It is essential to develop this novel process to quantify the consequences of AF and to protect the end users of EV charging systems. Full article

Background/Objectives: In digital radiography imaging, dual-layer flat-panel detectors (DFDs), in which two flat-panel detector layers are stacked with a minimal distance between the layers and appropriate alignment, are commonly used in material decompositions as dual-energy applications with a single x-ray exposure. DFDs also enable more efficient use of incident photons, resulting in x-ray images with improved noise power spectrum (NPS) and detection quantum efficiency (DQE) performances as single-energy applications. Purpose: Although the development of DFD systems for material decomposition applications is actively underway, there is a lack of research on whether single-energy applications of DFD can achieve better performance than the single-layer case. In this paper, we experimentally observe the DFD performance in terms of the modulation transfer function (MTF), NPS, and DQE with discussions. Methods: Using prototypes of DFD, we experimentally measure the MTF, NPS, and DQE of the convex combination of the images acquired from the upper and lower detector layers of DFD. To optimize DFD performance, a two-step image registration is performed, where subpixel registration based on the maximum amplitude response to the transform based on the Fourier shift theorem and an affine transformation using cubic interpolation are adopted. The DFD performance is analyzed and discussed through extensive experiments for various scintillator thicknesses, x-ray beam conditions, and incident doses. Results: Under the RQA 9 beam conditions of 2.7 μGy dose, the DFD with the upper and lower scintillator thicknesses of 0.5 mm could achieve a zero-frequency DQE of 75%, compared to 56% when using a single-layer detector. This implies that the DFD using 75 % of the incident dose of a single-layer detector can provide the same signal-to-noise ratio as a single-layer detector. Conclusions: In single-energy radiography imaging, DFD can provide better NPS and DQE performances than the case of the single-layer detector, especially at relatively high x-ray energies, which enables low-dose imaging. Full article

Although Unmanned Aircraft Systems (UASs) offer valuable services, they also introduce certain risks—particularly to individuals on the ground—referred to as third-party risk (TPR). In general, ground-level TPR tends to rise alongside the density of people who might use these services, leading current regulations to heavily restrict UAS operations in populated regions. These operational constraints hinder the ability to gather safety insights through the conventional method of learning from real-world incidents. To address this, a promising alternative is to use dynamic simulations that model UAS collisions with humans, providing critical data to inform safer UAS design. In the automotive industry, the modelling and simulation of car crashes has been well developed. For small UAS, this dynamical modelling and simulation approach has focused on the effect of the varying weight and kinetic energy of the UAS, as well as the geometry and location of the impact on a human body. The objective of this research is to quantify the effects of UAS material and shape on-ground TPR through dynamical modelling and simulation. To accomplish this objective, five camera–drone types are selected that have similar weights, although they differ in terms of airframe structure and materials. For each of these camera–drones, a dynamical model is developed to simulate impact, with a biomechanical human body model validated for impact. The injury levels and probability of fatality (PoF) results, obtained through conducting simulations with these integrated dynamical models, are significantly different for the camera–drone types. For the uncontrolled vertical impact of a 1.2 kg UAS at 18 m/s on a model of a human head, differences in UAS designs even yield an order in magnitude difference in PoF values. Moreover, the highest PoF value is a factor of 2 lower than the parametric PoF models used in standing regulation. In the same scenario for UAS types with a weight of 0.4 kg, differences in UAS designs even considered yield an order when regarding the magnitude difference in PoF values. These findings confirm that the material and shape design of a UAS plays an important role in reducing ground TPR, and that these effects can be addressed by using dynamical modelling and simulation during UAS design. Full article

Ubiquitous digital array radar (UDAR) extends the integration time of moving targets by deploying a wide transmitting beam and multiple narrow receiving beams to cover the entire observed airspace. By exchanging time for energy, it effectively improves the detection ability for weak targets. Nevertheless, target motion introduces severe across-range unit (ARU), across-Doppler unit (ADU), and across-beam unit (ABU) effects, dispersing target energy across the range–Doppler-beam space. This paper proposes a beam domain angle rotation compensation and keystone-matched filtering (BARC-KTMF) algorithm to address the “three-crossing” challenge. This algorithm first corrects ABU by rotating beam–domain coordinates to align scattered energy into the final beam unit, reshaping the signal distribution pattern. Then, the KTMF method is utilized to focus target energy in the time-frequency domain. Furthermore, a special spatial windowing technique is developed to improve computational efficiency through parallel block processing. Simulation results show that the proposed approach achieves an excellent signal-to-noise ratio (SNR) gain over the typical single-beam and multi-beam long-time coherent integration (LTCI) methods under low SNR conditions. Additionally, the presented algorithm also has the capability of coarse estimation for the target incident angle. This work extends the LTCI technique to the beam domain, offering a robust framework for high-speed weak target detection. Full article

Background/Objectives: Colorectal cancer is a leading cause of cancer-related death worldwide, with rising incidence in younger adults. Unhealthy diets high in red and processed meat and low in fiber are key modifiable risk factors, highlighting the need for preventive nutritional strategies targeting CRC through dietary interventions. Methods: A one-day sample diet for colorectal cancer prevention, consisting of fiber-rich meals excluding red meat and incorporating whole grains, legumes, vegetables, fruits, nuts, and lean protein alternatives (such as fish and poultry), was developed. Its acceptability was assessed in a cross-sectional study using an online questionnaire among healthy Romanian adults aged 18–50, with a total of 395 included participants. Results: Of the 395 respondents meeting the inclusion criteria (aged 18–50, no cancer or chronic gastrointestinal disorders), 63.5% were females, predominantly urban (90.1%), and highly educated. Mean age was 32.4 years; mean BMI was 25.07 kg/m². The proposed colorectal cancer-preventive diet was rated as “quite attractive” and “very attractive” by 74.9% of participants. All meals received high ratings, with dinner and the first snack being most favored. Most respondents (77.2%) found the diet satisfying and the satiety level and energy adequate, and 90.4% were willing to adopt it at least a few times per week. Financial accessibility was affirmed by 77.2% of the respondents. However, 61.8% reported difficulty eliminating red meat consumption. Female participants rated the diet significantly more attractive than males did (p = 0.041). Willingness to adopt the diet strongly correlated with higher acceptability (p < 0.0001), while BMI and education level showed no significant effect. Conclusions: The proposed colorectal cancer-preventive diet was well accepted by Romanian adults aged 18–50, with higher receptivity among women and those with higher education; willingness to adopt the diet at least a few days per week was high, especially among those psychologically ready for dietary change, while key barriers included red meat reduction and perceived cost, underscoring the need for gender-sensitive, culturally adapted interventions and further research on long-term adherence and clinical impact. Full article

Remote sensing has emerged as a promising technology for large-scale detection and updating of global wind turbine databases. High-resolution imagery (e.g., Google Earth) facilitates the identification of offshore wind turbines (OWTs) but offers limited offshore coverage due to the high cost of capturing vast ocean areas. In contrast, medium-resolution imagery, such as 10-m Sentinel-2, provides broad ocean coverage but depicts turbines only as small bright spots and shadows, making accurate detection challenging. To address these limitations, We propose a novel deep learning approach to capture the variability in OWT appearance and shadows caused by changes in solar illumination and satellite viewing geometry. Our method learns intrinsic, imaging geometry-invariant features of OWTs, enabling robust detection across multi-seasonal Sentinel-2 imagery. This approach is implemented using Faster R-CNN as the baseline, with three enhanced extensions: (1) direct integration of imaging parameters, where Geowise-Net incorporates solar and view angular information of satellite metadata to improve geometric awareness; (2) implicit geometry learning, where Contrast-Net employs contrastive learning on seasonal image pairs to capture variability in turbine appearance and shadows caused by changes in solar and viewing geometry; and (3) a Composite model that integrates the above two geometry-aware models to utilize their complementary strengths. All four models were evaluated using Sentinel-2 imagery from offshore regions in China. The ablation experiments showed a progressive improvement in detection performance in the following order: Faster R-CNN < Geowise-Net < Contrast-Net < Composite. Seasonal tests demonstrated that the proposed models maintained high performance on summer images against the baseline, where turbine shadows are significantly shorter than in winter scenes. The Composite model, in particular, showed only a 0.8% difference in the F1 score between the two seasons, compared to up to 3.7% for the baseline, indicating strong robustness to seasonal variation. By applying our approach to 887 Sentinel-2 scenes from China’s offshore regions (2023.1–2025.3), we built the China OWT Dataset, mapping 7369 turbines as of March 2025. Full article

Data center virtualization has grown rapidly alongside the expansion of application-based services but continues to face significant challenges, such as downtime caused by suboptimal hardware selection, load balancing, power management, incident response, and resource allocation. To address these challenges, this study proposes a combined machine learning method that uses an MDP to choose which VMs to move, the RF method to sort the VMs according to load, and NSGA-III to achieve multiple optimization objectives, such as reducing downtime, improving SLA, and increasing energy efficiency. For this model, the GWA-Bitbrains dataset was used, on which it had a classification accuracy of 98.77%, a MAPE of 7.69% in predicting migration duration, and an energy efficiency improvement of 90.80%. The results of real-world experiments show that the hybrid machine learning strategy could significantly reduce the data center workload, increase the total migration time, and decrease the downtime. The results of hybrid machine learning affirm the effectiveness of integrating the MDP, RF method, and NSGA-III for providing holistic solutions in VM placement strategies for large-scale data centers. Full article

The Industrial Internet of Things (IIoT) offers transformative potential for supply chain management by enabling automation, real-time monitoring, and predictive analytics. However, fragmented standardization, interoperability challenges, and cybersecurity risks hinder its sustainable adoption. This study aims to develop and validate an ISO-based framework to optimize IIoT networks for sustainable supply chain operations. A quantitative time-series research design was employed, analyzing 150 observations from 10–15 industrial firms over five years. Analytical methods included ARIMA, structural equation modeling (SEM), and XGBoost for predictive evaluation. The findings indicate a 6.2% increase in system uptime, a 4.7% reduction in operational costs, a 2.8% decrease in lead times, and a 55–60% decline in security incidents following ISO standard implementation. Interoperability improved by 40–50%, and integration cost savings ranged from 35–40%, contributing to a 25% boost in overall operational efficiency. These results underscore the critical role of ISO frameworks such as ISO/IEC 30141 and ISO 50001 in enhancing connectivity, energy efficiency, and network security across IIoT-enabled supply chains. While standardization significantly improves key performance indicators, the persistence of lead time variability suggests the need for additional optimization strategies. This study offers a structured and scalable methodology for ISO-based IIoT integration, delivering both theoretical advancement and practical relevance. By aligning with internationally recognized sustainability standards, it provides policymakers, practitioners, and industry leaders with an evidence-based framework to accelerate digital transformation, enhance operational efficiency, and support resilient, sustainable supply chain development in the context of Industry 4.0. Full article

This study aimed to investigate the effects of resistance training (RT) experience on bone mineral density (BMD) and stress fractures (SFs) in female collegiate athletes. Overall, 492 female athletes from 16 competitive sports were included. Sports were categorized into four groups based on exercise load. Data on sports participation, RT experience, and SF history were obtained using a questionnaire. Total body and lumbar spine BMD were measured using dual-energy X-ray absorptiometry. Athletes with RT experience in both senior high school (ages 15–18) and university (ages 18–22), as well as those with experience from junior high school (ages 12–15) through university, had significantly higher BMD than those with no RT experience or RT experience only in senior high school (p < 0.05). Logistic regression analysis revealed that athletes with RT experience had significantly lower odds ratios for SFs compared to those with no RT experience. In the adjusted model that included sport type and university year, athletes with RT experience in junior high school, senior high school, and university had a significantly lower OR for SFs compared with no RT experience (OR = 0.06, 95% CI: 0.01–0.59, p = 0.016). No significant BMD differences were found between athletes with and without SFs (p > 0.05). The study findings suggest that initiating RT in junior high school may be associated with a reduced incidence of SFs during university. Full article

Compton backscattering is a versatile non-destructive technique for material characterization and structural evaluation in reinforced concrete. This methodology enables a single-sided inspection of large structures—which is particularly useful where only one side of the material is accessible for examination—is relatively inexpensive, and can be made portable for field applications. This study aims to assess the influence of basaltic coarse aggregates on the accurate localization and dimensioning of rebar in reinforced concrete using the gamma-ray Compton backscattering technique at two distinct incident photon energies—59.5 keV and 1170 keV. The analysis was performed through Monte Carlo simulations using the FLUKA code, providing insights into the feasibility and limitations of this non-destructive method for structural evaluation. Both photon energies successfully detected the rebar embedded at a 3 cm depth in mortar, achieving a good spatial resolution and contrast, despite the presence of a significant amount of iron oxide within the aggregate. Among the evaluated sources, ⁶⁰Co yielded the highest contrast and count values, demonstrating its potential for rebar detection at greater depths within concrete structures. The single-sided Compton scattering technique proved to be effective for the investigated application and presents a promising alternative for the non-destructive assessment of real-world reinforced concrete structures. Full article

Suicide in children is a major global health crisis, with profound impacts on families, friends, and society. Understanding ways to ameliorate the rate of suicide attempt (SA) is critical given that it is a key factor in predicting future suicide risk. SA is the deliberate act of causing physical injury to oneself with the intent of death. The incidence of SA may be influenced by physical activity (PA). PA includes bodily movement via skeletal muscles that results in energy expenditure and physical fitness. While there is evidence to suggest that PA improves dysregulation of the parasympathetic nervous system which underpins the physiology of suicidal behaviour, evaluating the impact of PA on SA in children is required. Objectives: This systematic review aims to determine the relationship between PA and SA in children to inform alternative preventative and interventional strategies. Methods: This systematic review was registered with PROSPERO: CRD42023389415. Eight electronic databases were systematically searched. References were transferred to Covidence software for title and abstract screening and full text review were performed based on eligibility criteria: (1) children aged 6–18 years old; (2) participated in PA (individual, group exercise, or team sports); and (3) examined SA as a dependent variable. The JBI Checklist was used to measure the quality and level of bias of included studies. Results: Of the 2322 studies identified, 21 were included in the final analysis of the review. Twenty studies were cross-sectional in design, and one implemented a prospective study design. Thirteen studies (61.9%) yielded statistically significant results, indicating that increased PA, particularly team sport, may be associated with reduced odds of SA. There was some evidence to suggest that certain intensities and frequencies of PA may be beneficial to some and detrimental to other subgroups. Conclusions: The results suggest that PA may reduce the risk of suicide attempts. Although PA may be associated with reduced SA in children, future research is required, which (1) uses standardised outcome variables; (2) adopts longitudinal and experimental study designs; (3) explores qualitative research to determine distinctive factors that influence participation in PA not captured by quantitative research; and (4) examines different target populations such as children with a broad range of mental health issues. Full article

Monopile foundation is an important foundation form for offshore wind turbines, and the stability of the seabed around it is affected by the combined effects of wave and pile vibration. Based on the Biot consolidation theory and elastoplastic constitutive model, a multi-physical field coupling model of wave–vibration–seabed–monopile is constructed, and the dynamic characteristics of seabed pore pressure around the monopile under the joint action of wave–vibration are systematically investigated, and the influences of waves, vibrations, and seabed parameters on the distribution of pore pressure amplitude are analysed in depth. The results show that the increase in wave incident energy will increase the seabed wave pressure, and the suction and pressure generated by pile vibration will change the soil force state; the coupling of waves and vibrations results in pile displacement difference, causing the seabed pore pressure dissipation depth dissimilarity, and the peak relative amplitude of pore pressure and the peak of vibration displacement are in a linear relationship; the wave parameters and seabed characteristics have a significant effect on the change in pore pressure amplitude distribution. Full article