Temporal convolutional networks and data rebalancing for clinical length of stay and mortality prediction.

It is critical for hospitals to accurately predict patient length of stay (LOS) and mortality in real-time. We evaluate temporal convolutional networks (TCNs) and data rebalancing methods to predict LOS and mortality. This is a retrospective cohort study utilizing the MIMIC-III database.

Appraising the availability of biomass residues in India and their bioenergy potential.

Biomass produced from agriculture at present provides most energy services in developing nations. In India, enormous quantities of biomass are produced for conversion into valuable energy. Bioenergy production from agricultural leftovers, animal manure, and municipal waste has the potential to meet of the rising need sustainable energy.

On collaborative reinforcement learning to optimize the redistribution of critical medical supplies throughout the COVID-19 pandemic.

Objective: This work investigates how reinforcement learning and deep learning models can facilitate the near-optimal redistribution of medical equipment in order to bolster public health responses to future crises similar to the COVID-19 pandemic.

Materials And Methods: The system presented is simulated with disease impact statistics from the Institute of Health Metrics, Centers for Disease Control and Prevention, and Census Bureau. We present a robust pipeline for data preprocessing, future demand inference, and a redistribution algorithm that can be adopted across broad scales and applications.

Life-cycle assessment of sewage sludge-based large-scale biogas plant.

The aim of this work was to study the life-cycle assessment (LCA) and impact of a biogas plant based on the municipal sewage sludge (6000 m capacity biogas plant at Wastewater Treatment Plant (WWTP), Delawas, Jaipur - Rajasthan, India), analyzing the environmental effects instigated due to basic systems of biogas production and also to examine the impact of using biogas as an alternate fuel using ReCiPe and midpoint methods. The results indicatedthat the construction of plant was insignificant to the whole life cycle impacts. Biogas plant showed negative GHG emissions (-0.