Objectives To examine the association between exposure to greenness and hospital admissions for mental disorders, and to ...
Background Anti-C1q autoantibodies can disrupt normal complement function, contributing to the formation of pathogenic immune ...
Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...
Introduction Timely detection, notification and response are critical for mitigating outbreak impact, yet evidence linking timeliness to public health outcomes is limited.Methods We hypothesised that ...
Objectives To evaluate the long-term efficacy of remote ischaemic postconditioning (RIPC) on functional outcomes in patients ...
This paper is concerned with the long-time behavior of solutions for a class of stochastic semilinear degenerate equations with memory driven by nonlinear noise on ℝ n ...
This study offers a valuable advance for neuroscience by extending a visualization tool that enables intuitive assessment of how dendritic and synaptic currents shape the output of neurons. The ...
The authors used a Bayesian modeling framework to fit behavior and serotonin neuron activity to reward history across multiple timescales. A key goal was to distinguish value coding from other ...
The table below comprises the names of units which are part of the latest syllabus for the 2025 exams. These chapters are intact with minor additions. Discovery of Electron, Proton, and Neutron, ...
A six-metabolite plasma panel was developed and validated for gastric cancer (GC) diagnosis using UPLC-MS and machine ...
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