AIMC Topic: Climate

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Revolution and advances in gene editing and genomics technology for developing climate-resilient legume crops: developments and prospects.

Plant molecular biology
Legumes are essential for agriculture and food security. Biotic and abiotic stresses pose significant challenges to legume production, lowering productivity levels. Most legumes must be genetically improved by introducing alleles that give pest and d...

Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.

Journal of global health
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...

Exploring the spatiotemporal influence of climate on American avian migration with random forests.

Scientific reports
Birds have adapted to climatic and ecological cycles to inform their Spring and Fall migration timings, but anthropogenic global warming has affected these long-establish cycles. Understanding these dynamics is critical for conservation during a chan...

Research on the potential of the deep learning-based "decomposition-optimization-reconstruction" method in runoff prediction for typical climate- and human-regulated basins in northern China.

Journal of contaminant hydrology
River runoff may be affected mainly by the natural climate or human activities, and runoff series present complex characteristics, such as non-stationarity, which makes accurate prediction of runoff challenging. To address the problem that the predic...

Enhanced wheat yield prediction through integrated climate and satellite data using advanced AI techniques.

Scientific reports
Wheat plays a vital role in Pakistan's economy and food security, making accurate yield forecasting essential for planning and resource management. Traditional approaches-such as manual field surveys and remote sensing-have been widely used, but thei...

Forecasting malaria cases using climate variability in Sierra Leone.

Malaria journal
BACKGROUND: Malaria continues to pose a public health challenge in Sierra Leone, where timely and accurate forecasting can guide more effective interventions. Although seasonal models such as Seasonal Autoregressive Integrated Moving Average (SARIMA)...

A coupled machine-learning and sensitivity analysis framework to link dust activity in the Tigris-Euphrates basin to climatic and human-induced drivers.

Environmental research
This study analyzes the impact of climate-related stressors and water resources development in the Tigris-Euphrates basin on regional dust storm intensity and frequency. To this end, we first utilize remote sensing data on Aerosol Optical Depth (AOD)...

How monitoring crops and drought, combined with climate projections, enhances food security: Insights from the Northwestern regions of Bangladesh.

Environmental monitoring and assessment
Crop and drought monitoring are vital for sustainable agriculture, as they ensure optimal crop growth, identify stress factors, and enhance productivity, all of which contribute to food security. However, climate projections are equally important as ...

Forecasting invasive mosquito abundance in the Basque Country, Spain using machine learning techniques.

Parasites & vectors
BACKGROUND: Mosquito-borne diseases cause millions of deaths each year and are increasingly spreading from tropical and subtropical regions into temperate zones, posing significant public health risks. In the Basque Country region of Spain, changing ...

Forecasting dengue across Brazil with LSTM neural networks and SHAP-driven lagged climate and spatial effects.

BMC public health
BACKGROUND: Dengue fever is a mosquito-borne viral disease that poses significant health risks and socioeconomic challenges in Brazil, necessitating accurate forecasting across its 27 federal states. With the country's diverse climate and geographica...