A new regional assessment shows that Southeast Asia is a major net source of greenhouse gases, with land-use change and rising fossil fuel use overwhelming natural carbon sinks, reservoirs that store carbon-containing chemical compounds for a long period. 

A research paper by scientists at University of Rome Tor Vergata introduced a novel deep learning framework based on a graph deviation network (GDN) to analyze spiking activity from human forebrain organoids (hFOs) and predict network-level alterations associated with autism spectrum disorder (ASD) risk..

Promoting sustainable development in both urban and rural areas has become a globally shared concern. Urban–rural interactions can contribute to wealth creation, poverty alleviation, employment growth, and improved social equity. It has been widely recognized as a key strategy for addressing sustainability challenges, although it may also bring some negative impacts, such as labor outmigration and imbalanced capital allocation. However, the impacts of urban–rural interactions on rural development and how these impacts contribute to sustainable rural transformation require further in-depth investigation.

In light of these pressing global ecological challenges, there is a compelling need to develop ecological theories and applied technologies for understanding, managing, and conserving macroecological systems at regional to global scales. Such efforts are essential to safeguarding natural resource environments, maintaining ecosystem stability, and ensuring the sustainability of human societies.

 In recent decades, the infusion of statistics and dynamic equations into geography has shifted the discipline from a descriptive endeavor to a modern science that builds predictive models through hypothesis testing. This progress, however, prompted doubts about the representativeness of sampling, the validity of discarded outliers, and the uniqueness of assumed distributions, parameters, and equations.