AIMC Topic: Seasons

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Predictive modelling of air pollution affecting human tuberculosis risk on Mainland China.

Scientific reports
In this study, we investigated the correlation between air pollution indicators and pulmonary tuberculosis (TB) incidence and mortality rates across provincial administrative regions of China from January 2013 to December 2020 to develop predictive m...

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...

Tracking the spatial and temporal evolution of salt marsh vegetation based on UAV sampling and seasonal phenology from Landsat data.

Journal of environmental management
Salt marshes, valued for their ecological importance, have been increasingly degraded in recent decades. Preserving salt marshes necessitates a critical approach that involves monitoring vegetation distribution and species composition. This study pre...

Changes in Epidemiological Characteristics of Varicella and Breakthrough Cases in Ningbo, China, From 2010 to 2023: Surveillance Study.

JMIR public health and surveillance
BACKGROUND: Varicella is a prevalent respiratory infectious disease. Continuous monitoring is essential to understand evolving epidemiological patterns, particularly given the impact of vaccination and recent nonpharmacological interventions.

Exploring the over-wintering and over-summering mechanisms of Ulva prolifera from physiological and transcriptome perspectives and their impacts on green tides.

Marine environmental research
Since 2007, the South Yellow Sea region of China has endured the world's largest recurrent green tide disaster for 18 consecutive years, resulting in substantial economic losses and ecological risks. Ulva prolifera the dominant species in these green...

Exploring Aerosol Vertical Distributions and Their Influencing Factors: Insight from MAX-DOAS and Machine Learning.

Environmental science & technology
Understanding aerosol vertical distribution is crucial for aerosol pollution mitigation but is hindered by limited observational data. This study employed multiaxis differential optical absorption spectroscopy (MAX-DOAS) technology with a coupled rad...

Enhancing particulate matter prediction in Delhi: insights from statistical and machine learning models.

Environmental monitoring and assessment
This study advances our approach to modeling particulate matter levels-specifically, PM and PM-in Delhi's dynamic urban environment through an extensive evaluation of traditional time series models (ARIMAX, SARIMAX) and machine learning models (RF, S...

Global dominance of seasonality in shaping lake-surface-extent dynamics.

Nature
Lakes are crucial for ecosystems, greenhouse gas emissions and water resources, yet their surface-extent dynamics, particularly seasonality, remain poorly understood at continental to global scales owing to limitations in satellite observations. Alth...

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)...

Machine learning-based quantification and separation of emissions and meteorological effects on PM in Greater Bangkok.

Scientific reports
This study presents the first-ever application of machine learning (ML)-based meteorological normalization and Shapley additive explanations (SHAP) analysis to quantify, separate, and understand the effect of meteorology on PM over Greater Bangkok (G...