Environmental monitoring and assessment
Nov 29, 2025
Accurately classifying forest successional stages remains a major challenge in applied ecology due to the continuum of succession, ecological heterogeneity, and limited interpretability of many machine learning (ML) approaches. Prevailing models typi...
We present MBPert, a generic computational framework for inferring species interactions and predicting dynamics in time-evolving ecosystems from perturbation and time-series data. In this work, we contextualize the framework in microbial ecosystem mo...
International journal of health geographics
Jul 28, 2025
BACKGROUND: Clonorchis sinensis, the liver fluke responsible for clonorchiosis, presents a persistent public health burden in Guangxi (Southern China) and Vietnam. Its transmission is influenced by a complex interplay of ecological, climatic, and soc...
Reservoir computing (RC) has emerged as a powerful computational paradigm, leveraging the intrinsic dynamics of complex systems to process temporal data efficiently. Here we propose to extend RC into ecological domains, where the ecosystems themselve...
This article attempts to show that current trends in bio-inspired robotics research are incompatible with the transformations needed to address the current ecological crisis. A large part of the scientific community takes refuge behind short-term cha...
Agriculture is a major contributor to water pollution through nutrient runoff and excessive water use, exacerbating global water scarcity and ecosystem degradation. Water Quality Trading (WQT) has emerged as a market-based mechanism to address this i...
Fungi play a critical role in ecosystems, contributing to biodiversity and providing economic and biotechnological value. In this study, we developed a novel deep learning-based framework for the classification of seven macrofungi species from the ge...
With the explosive increase in genome sequence data, perhaps the major challenge in natural-product-based drug discovery is the identification of gene clusters most likely to specify new chemistry and bioactivities. We discuss the challenges and stat...
The emergence of generative artificial intelligence (AI) models specializing in the generation of new data with the statistical patterns and properties of the data upon which the models were trained has profoundly influenced a range of academic disci...
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