Results 51 to 60 of about 585 (260)
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley +1 more source
On the Challenges and Opportunities of Fuzzing via Large Language Models: A Review
Fuzzing is an important automated testing technique for discovering vulnerabilities and abnormal software behavior, but conventional and pre-LLM learning-based approaches often struggle with strict validity constraints, limited semantic understanding ...
Yiqing Sun +3 more
doaj +1 more source
FuzzE, Development of a Fuzzing Approach for Odoo's Tours Integration Testing Plateform
For many years, Odoo, an open-source add-on-based platform offering an extensive range of functionalities, including Enterprise Resource Planning, has constantly expanded its scope, resulting in an increased complexity of its software. To cope with this evolution, Odoo has developed an integration testing system called tour execution, which executes ...
Gabriel Benoit +4 more
openaire +1 more source
A fluorinated hydrogen‐bonded organic framework nanocarrier (PFC‐1‐F) loaded with PYR and coated with HACC enables multi‐stimuli‐responsive (enzyme/ROS/pH) release at infection sites. Exhibiting targeted antifungal activity against Sclerotium rolfsii, modulating plant antioxidant defense, and demonstrating favorable biosafety across plant, soil, and ...
Guangming Ma +6 more
wiley +1 more source
AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi +4 more
wiley +1 more source
Trapezoidal Generalization over Linear Constraints [PDF]
We are developing a model-based fuzzing framework that employs mathematical models of system behavior to guide the fuzzing process. Whereas traditional fuzzing frameworks generate tests randomly, a model-based framework can deduce tests from a behavioral
David Greve, Andrew Gacek
doaj +1 more source
TDP‐43 Aggregation: The Healthy‐Toxic Balance of the Prion‐Like Domain
TDP‐43 function relies on a delicate balance between reversible phase‐separated states and irreversible aggregation. Under physiological conditions, TDP‐43 forms dynamic droplets and oligomers that support normal cellular functions. In pathological contexts, this balance shifts toward aberrant aggregation, leading to toxic species.
Luca Zangrando +2 more
wiley +1 more source
Grammar-aware test case trimming for efficient hybrid fuzzing
In recent years, hybrid fuzzing has garnered significant attention by combining the benefits of both fuzzing and concolic execution. However, existing hybrid fuzzing techniques face problems such as the performance overhead of concolic execution and low ...
Yiru Zhao, Long Gao, Qihan Wan, Lei Zhao
doaj +1 more source
Research on Collision-Free Grey Box Fuzzing Method
Grey-box fuzzing technology has been proved to be an efficient and practical vulnerability mining technology. It is widely used in the field of vulnerability mining, and many high-risk vulnerabilities are found through grey-box fuzzing.
WANG Song, FANG Yong, JIA Peng
doaj
An optimized single‐cell transcriptomic framework profiles over 60 000 cells to map the ovine rumen microbiome, partitioning the ecosystem into seven cross‐species functional clusters. In heat‐resistant hosts, a lineage‐specific metabolic shift in Anaerovibrio lipolyticus toward a highly glycolytic phenotype contributes to a “nutritional sparing ...
Sanbao Zhang +8 more
wiley +1 more source

