Machine-learning (ML) algorithms are increasingly valuable in health sciences because they can analyze complex, high-dimensional data and detect patterns that may not be easily identified using traditional statistical methods. These models can effici... read more
The escalating utilization of urban underground space frequently necessitates the construction of surface structures in close proximity to subterranean tunnels. This study investigates the bearing capacity of rigid strip footings above dual square tu... read more
In recent years of crude oil shortage and price rise, biodiesel has emerged as a new-age sustainable fuel, owing to its positives mainly providing lower amount of gas emissions and compatibility with prevailing petro-diesel engines. The contemporary ... read more
The clinical demand for paclitaxel necessitates novel strategies to enhance its production. While recent breakthroughs have elucidated the complete biosynthetic pathway in heterologous hosts, optimizing production within the native Taxus plant remain... read more
The demanding requirements of next-generation 6G wireless systems necessitate the development of compact, wideband, and high-isolation terahertz (THz) MIMO antennas, while conventional full-wave electromagnetic optimization remains computationally ex... read more
We externally validated the performance of deep learning (DL) solution for detection of spontaneous intracerebral (ICH), intraventricular (IVH) and subarachnoid hemorrhages (SAH) on non-contrast enhanced head CT scans (NCCTs). We analyzed 901 NCCTs c... read more
Construction delays remain a major challenge, especially in developing countries where financial, administrative, and resource constraints intensify schedule disruptions. This study identifies and prioritizes construction delay factors through a thre... read more
Reproducible brain-wide association studies remain challenging in structural MRI, in part because high-dimensional cortical measures yield unstable eigenspaces in small samples. Here, using cortical thickness data from the Human Connectome Project Yo... read more
Haze in remote sensing imagery severely degrades image quality and impedes accurate interpretation. While deep learning has advanced dehazing, its reliance on large-scale paired data is impractical for remote sensing applications. To overcome this, w... read more
Accurate prediction of nanofluid thermal conductivity is essential for the design of advanced thermal systems; however, existing approaches often face a trade-off between predictive accuracy and physical interpretability. In this study, a physics-gui... read more
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