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IntroductionThe COVID-19 pandemic has reduced system resilience, caused economic welfare loss, and widened disparities in healthcare access. This study aims to identify the macro-level factors contributing to COVID-19 va...

Deep learning has become the dominant approach in artificial intelligence to solve complex data-driven problems. Originally applied almost exclusively in computer-science areas such as image analysis and nature language ...

This study was conducted to potentially optimize the sustainable culture of Mozambique tilapia (Oreochromis mossambicus) in a periphyton-based aquaculture system with supplemental feeding to aqua dams using stochastic si...

IntroductionLiver diseases continue to impose a major global health burden, and therapeutic progress is constrained by the limited availability of validated small-molecule modulators. TEAD4, a central Hippo-YAP effector,...

This work introduces a novel geometrical and analytical modeling framework for predicting the stiffness properties of knitted composites, a class of materials known for their complex architectures and versatile mechanica...

Modelling and estimating relationships that combine time series and crosssectional data is often discussed in the statistical literature but in these considerations sampling errors are seldom taken into account. In the p...

The Gray-Scott (GS) model is a nonlinear reaction diffusion system widely used in applied sciences. This paper delves into the investigation of a spectral method for the GS model with homogeneous Neumann boundary conditi...