Results 251 to 260 of about 238,744 (335)
Regioisomeric effects are a critical design parameter in self‐assembled monolyaer (SAM) engineering, underscoring their importance for optimizing buried interface properties and advancing the performance and stability of inverted perovskite solar cells.
Myeong‐Ho Hong +5 more
wiley +1 more source
Genome-wide association studies on leaf midrib architecture in maize. [PDF]
Dang D +7 more
europepmc +1 more source
Plant Disease Recognition Based on Leaf Images Using Sequential-Based DenseNet Architecture
Mariana Purba
openalex +2 more sources
A multifaceted chemical strategy, integrating bacterial tropism, metal‐ion interference therapy, and immunotherapy, resulted in significant tumor regression in murine models. A pioneering paradigm for the design of biohybrid materials was established, highlighting how sophisticated chemical engineering of living systems can unlock new avenues for ...
Tingting Zhang +7 more
wiley +1 more source
A federated learning with Large-Small Kernel Attention Network for image classification. [PDF]
Liu T, Xie J, Dong H.
europepmc +1 more source
Corn Leaf Disease Classification Optimization Using Resnet50 Architecture Utilizing Bayesian Optimization [PDF]
Yahya Auliya Abdillah, Kusrini Kusrini
openalex +1 more source
Bacterial Outer Membrane Vesicles in Potentiating Cancer Vaccines: Progress and Prospects
Bacterial outer membrane vesicles (OMVs) have emerged as versatile platforms for cancer vaccine development owing to their intrinsic immunostimulatory properties and high engineering flexibility. This review summarizes OMV biology, immune mechanisms, and engineering strategies that enhance vaccine efficacy, discusses key translational challenges, and ...
Jiabeini Zhang +9 more
wiley +1 more source
Bigger is not always better: Optimizing leaf area index with narrow-leaf shape in soybean. [PDF]
Tamang BG +4 more
europepmc +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source

