In recent years, skeleton-based human action recognition has garnered significant research attention, with proposed recognition or segmentation methods typically validated on large-scale coarse-grained action datasets. However, there remains a lack o...
Action recognition based on 3D heatmap volumes has received increasing attention recently because it is suitable for application to 3D CNNs to improve the recognition performance of deep networks. However, it is difficult for models to capture global...
Tornado damage estimation is important for providing insights into tornado studies and assisting rapid disaster response. However, it is challenging to precisely estimate tornado damage because of the large volumes of perishable data. This study pres...
Skeleton representation learning offers substantial advantages for action recognition by encoding intricate motion details and spatial–temporal dependencies among joints. However, fully supervised approaches necessitate large amounts of annotat...
Background/Objectives: Colorectal anastomotic leak (CAL) is one of the most severe postoperative complications in colorectal surgery, impacting patient morbidity and mortality. Current risk assessment methods rely on clinical and intraoperative facto...
Amid growing urban climate uncertainty and complex water demand, conventional standalone rainwater harvesting (RWH) systems often fail to ensure supply reliability and overflow control. Most existing studies focus on single-function building clusters...
In this work we present the shape optimization of a 2000 L water tank placed behind the rear axle of a forestry skidder. The main criterion is the static stability of the vehicle. The purpose of the research is to decrease the impact of the tank on s...
With a shortage of sulfur in the soil and an increasing world population and, thus, food consumption volume, the demand for this important nutrient is likely to increase, both globally and regionally. The purpose of this model incubation study was to...
We are now generating exponentially more data from more sources than a few years ago. Big data, an already familiar term, has been generally defined as a massive volume of structured, semi-structured, and/or unstructured data, which may not be effect...
Estrogen receptor (ER)-positive progesterone receptor (PR)-negative breast cancers are infrequent but clinically challenging. Despite the volume of genomic data available on these tumors, their biology remains poorly understood. Here, we aimed to ide...
Cold chain logistics are crucial for reducing agricultural product loss, yet the environmental impact of energy and packaging consumption, among others, demands attention, making the search for eco-friendly development modes essential. Based on data...
Background/Objectives: Rutin (RT), a promising bioflavonoid, faces clinical limitations due to its poor solubility and bioavailability. In this study, we formulated RT-loaded phytosome nanoparticles (RT-PNPs) via thin-layer hydration and characterize...
Radiomics is the process of extracting useful quantitative features of high-dimensional data that allows for automated disease classification, including atherosclerotic disease. Hence, this study aimed to quantify and extract the radiomic features fr...
Liquidambar formosana is a multipurpose tree species native to China. There has been increasing interest in L. formosana due to its leaves being rich in shikimic acid, which plays a key role in the synthesis of the antiviral drug oseltamivir phosphat...
A preventive excavation performed in 2018 prior to development work led to the discovery of more than 213 subjects buried from the 4th to the 11th centuries in the 1850 m2 dug area. This is a cemetery located in Olonne-sur-Mer in France (46.53723, −1...
In high-density built environments, perceived density (PD)—shaped by physical, socio-cultural, and perceptual factors—often induces sensations of crowding, stress, and spatial oppression. Although green spaces are recognised for their str...