Results 71 to 80 of about 8,087 (250)
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou +8 more
wiley +1 more source
High performance short-block binary regular LDPC codes
LDPC code shows a good performance with long-block codes. However, certain channels are constrained to use short-block codes due to latency. Therefore, concatenated LDPC codes with iterative decoding is a good choice to get a good performance ...
Latifa Mostari, Abdelmalik Taleb-Ahmed
doaj +1 more source
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li +9 more
wiley +1 more source
Novel low-delay scheme for parallel Turbo decoding
In order to decrease decoding delay because of the iterative and recursive computation in MAP class algo-rithms,a novel parallel decoding scheme was proposed.The key of the novel scheme was to design a novel collision-free(CF) interleaver.After the ...
REN De-feng +3 more
doaj +2 more sources
We design low-complexity bi-directional (forward and backward) modified Soft-Output Viterbi Algorithm (SOVA) decoders to exploit source memory from binary Markov and hidden Markov model (HMM) sources, respectively, for decoding in serially concatenated ...
Zhijie Guo, Lei Cao
doaj +1 more source
Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng +7 more
wiley +1 more source
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao +9 more
wiley +1 more source
We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung +4 more
wiley +1 more source
Low Complexity Approach for High Throughput Belief-Propagation based Decoding of LDPC Codes
The paper proposes a low complexity belief propagation (BP) based decoding algorithm for LDPC codes. In spite of the iterative nature of the decoding process, the proposed algorithm provides both reduced complexity and increased BER performances as ...
BOT, A. +3 more
doaj +1 more source
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio +6 more
wiley +1 more source

