Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas.

Predicting rainfall is a challenging and critical task due to its significant impact on society. Timely and accurate predictions are essential for minimizing human and financial losses. The dependence of approximately 60% of agricultural land in India on monsoon rainfall implies the crucial nature of accurate rainfall prediction.

Forecasting urban water demand using different hybrid-based metaheuristic algorithms' inspire for extracting artificial neural network hyperparameters.

This research offers a novel methodology for quantifying water needs by assessing weather variables, applying a combination of data preprocessing approaches, and an artificial neural network (ANN) that integrates using a genetic algorithm enabled particle swarm optimisation (PSOGA) algorithm. The PSOGA performance was compared with different hybrid-based metaheuristic algorithms' behaviour, modified PSO, and PSO as benchmarking techniques. Based on the findings, it is possible to enhance the standard of initial data and select optimal predictions that drive urban water demand through effective data processing.

Water volumes and mulches affect plant growth, leaf nutrient status and orchard soil mineral content of sweet orange cv. Mosambi.

Day-by-day increasing irrigation water scarcity requires the application of water-saving irrigation techniques to sustain agriculture production. A two-year field investigation was conducted during 2018 to 2020 to determine the effects of various mulches and irrigation volumes on the growth, leaf chemicals and soil properties of one-year-old sweet oranges (Citrus sinensis) cv. Mosambi.

Radiation Exposure During Invasive Cardiovascular Procedures: Portable Shielding System Versus Standard Lead Aprons.

Introduction Significant progress in the field of interventional cardiology has led to a rise in percutaneous procedures and an increase in the risk of radiation exposure at the workplace. Staff health has been put at risk due to the limitations of conventional radiation protective techniques. Innovative methods, such as RAMPART, have promising prospects for enhancing radiation safety.