Results 31 to 40 of about 18,885 (168)
A formal executable semantics of Verilog [PDF]
This paper describes a formal executable semantics for the Verilog hardware description language. The goal of our formalization is to provide a concise and mathematically rigorous reference augmenting the prose of the official language standard, and ultimately to aid developers of Verilog-based tools; e.g., simulators, test generators, and verification
Meredith, Patrick +3 more
openaire +2 more sources
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu +9 more
wiley +1 more source
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi +7 more
wiley +1 more source
Spatiotemporal Multi‐Omic Mapping Reveals Liver‐Muscle Metabolic Crosstalk in Cancer Cachexia
The interactive CCAtlas platform delineates cross‐species, spatiotemporal, and sex‐specific molecular dynamics and metabolic rewiring across organs during cancer cachexia. Hepatic Gamt downregulation curtails hepatic creatine synthesis to trigger systemic creatine insufficiency and consequent skeletal muscle atrophy in LLC tumour‐bearing mice ...
Zihan Tian +12 more
wiley +1 more source
Mechanically Reprogrammed Coaxial Fibers for Multiphysics Transduction and Human‐Machine Interfaces
A continuously wet‐spun coaxial fiber is developed to combine stretchable conductivity, resistive sensing, and self‐powered triboelectric sensing in a single architecture. A mechanically reprogrammed dual‐network sheath stabilizes large deformation and improves signal reliability. These fibers can be woven into textile interfaces for multichannel touch
Xinyi Cao +6 more
wiley +1 more source
Towards a Compositional Framework for Describing Human Phenotypes
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu +11 more
wiley +1 more source
scGEN combines attribute–structure encoding, adaptive hard‐sample weighting, and regularized zero‐inflated negative binomial loss to resolve ambiguous single‐cell states. In the developing human pituitary, refined annotations reveal Pre.Gonado cells at 7 weeks and previously obscured developmental communication networks.
Fang Huang +16 more
wiley +1 more source
What is Formal in Formal Semantics?
Formal semantics is understood either as a formal analysis of semantical features of natural language or as model-theoretic semantics of formal(ized) languages. This paper focuses on the second understanding. The problem is how to identify the formal aspects of formal semantics, if we understand 'formal' as 'independent of content'.
openaire +1 more source
DeepLNM: A Multimodal Model for Predicting Lymph Node Metastasis in Colorectal Cancer
Traditional diagnosis may miss positive LNM cases, and pathologists face a workload; therefore, we develop DeepLNM, a multimodal model that predicts lymph node metastasis in colorectal cancer from H&E WSIs, CT images, and text. DeepLNM is robust across internal, external, and prospective cohorts and, in a user study, improves diagnostic accuracy while ...
Zhengyu Zhang +24 more
wiley +1 more source
Disentangling Heterogeneous Molecular Networks for Multi‐Omics‐Driven Cancer Driver Discovery
DRIVE integrates PPI topology and pan‐cancer multi‐omics profiles through dual‐view graph disentanglement, contrastive representation learning, and joint optimization. Across six PPI networks, DRIVE outperforms ten baselines and remains robust to structural and annotation perturbations.
Xinjing Gong +8 more
wiley +1 more source

