AIMC Topic: Seasons

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Probability-Based Early Warning for Seasonal Influenza in China: Model Development Study.

JMIR medical informatics
BACKGROUND: Seasonal influenza is a major global public health concern, leading to escalated morbidity and mortality rates. Traditional early warning models rely on binary (0/1) classification methods, which issue alerts only when predefined threshol...

The First Seasonal Green View Index Mapping Dataset across Chinese cities powered by deep learning.

Scientific data
Multi-temporal mapping of the Green View Index (GVI) is crucial for understanding how urban residents perceive seasonal changes in streetscape greenness. Compared to street view imagery (SVI), remote sensing data offers higher temporal frequency and ...

Optimization of spatio-temporal ozone (O) pollution modeling using an ensemble machine model learning with a swarm-based metaheuristic algorithm.

Ecotoxicology and environmental safety
The future of ozone (O) pollution presents significant environmental and public health challenges worldwide. High O levels can harm respiratory health, exacerbating conditions such as asthma and increasing the risk of cardiovascular diseases. Address...

Widespread increasing negative vegetation sensitivity to phenology reshapes GPP dynamics in alpine grassland.

Journal of environmental management
Satellite evidence indicates a significant phenological changes in alpine vegetation. However, the effect of phenological changes on vegetation gross primary productivity (GPP) is still poorly understood, which limits understanding of climate changes...

Advanced spatiotemporal downscaling of MODIS land surface temperature: utilizing Sentinel-1 and Sentinel-2 data with machine learning technique in Qazvin Province, Iran.

Environmental monitoring and assessment
This study presents a spatiotemporal downscaling framework for MODIS land surface temperature (LST) using Sentinel-1 and Sentinel-2 data with machine learning techniques on the Google Earth Engine (GEE) platform. Random Forest regression was applied ...

Predictiveness and drivers of highly pathogenic avian influenza outbreaks in Europe.

Scientific reports
Avian Influenza (AI) outbreaks are on an increasing trajectory. This disease carries a substantial economic burden, resulting in considerable losses to farmers with profound impacts on economies. As the outbreaks continue in birds and other unusual h...

Modeling impacts of climate-induced yield variability and adaptations on wheat and maize in a sub-tropical monsoon climate - using fuzzy logic.

Scientific reports
Climate change is causing more frequent and extraordinary extreme weather events that are already negatively affecting crop production. There is a need for improved climate risk assessment by developing smart adaptation strategies for sustainable fut...

Exploring the contrasting lake CO fluxes and influencing variables in four large shallow subtropical lakes with different hydrological connectivity.

Journal of environmental management
Lake carbon dioxide (CO) evasion is a crucial component of global carbon cycle, yet the influence of environmental factors on CO emissions within different hydrological connectivity remains uncertain. Based on multiple machine learning methods, we in...

Tecomella undulata under threat: The impact of climate change on the distribution of a valuable tree species using a machine learning model.

PloS one
Climate change has emerged as a significant driver of biodiversity loss, with profound implications for species distribution. This study assessed the current and future distribution of Tecomella undulata (Desert teak), an economically and medicinally...

Predictive analysis of pediatric gastroenteritis risk factors and seasonal variations using VGG Dense HybridNetClassifier a novel deep learning approach.

Scientific reports
Pediatric gastroenteritis is a major reason for sickness and death among children worldwide, especially in places where healthcare and clean sanitation are scarce. Conventional methods of diagnosis overlook possible risks and seasonal trends, which r...