Graphical abstract illustrating the transition from global biodiversity ambition to on‐the‐ground implementation of the Kunming–Montreal Global Biodiversity Framework after COP16, highlighting the roles of governments, non‐state actors, scientific knowledge systems, and resource mobilization in achieving transformative biodiversity outcomes.
Susan Enechojo Ogbe +3 more
wiley +1 more source
Remote Sensing Data as a Tool for Studying Environmental Aspects of Parkinson's Disease. [PDF]
Hegazi MN +5 more
europepmc +1 more source
ABSTRACT Current prostate cancer detection methods remain limited in non‐invasiveness and specificity, prompting interest in urinary biomarkers such as sarcosine. Here, we report a urine‐powered wearable platform for non‐invasive sarcosine detection as a proof‐of‐concept for decentralized early warning.
Jing Xu +10 more
wiley +1 more source
Remote Sensing Data Reveal a Significant Reduction in the Area of the Nesting Habitat of Rafetus euphraticus in the Tigris River, Southeastern Turkey. [PDF]
Biricik M, Safi K, Turğa Ş.
europepmc +1 more source
Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale +6 more
wiley +1 more source
Research on Assimilation of Unmanned Aerial Vehicle Remote Sensing Data and AquaCrop Model. [PDF]
Li W +7 more
europepmc +1 more source
Optimizing Deep Learning Models for Climate-Related Natural Disaster Detection from UAV Images and Remote Sensing Data. [PDF]
VanExel K, Sherchan S, Liu S.
europepmc +1 more source
BO-CNN-BiLSTM deep learning model integrating multisource remote sensing data for improving winter wheat yield estimation. [PDF]
Zhang L +5 more
europepmc +1 more source
Measurement of sulfur content in coal mining areas by using field-remote sensing data and an integrated deep learning model. [PDF]
Liu J, Le BT.
europepmc +1 more source

