Results 31 to 40 of about 2,720,483 (215)

Longitudinal Morphomolecular Monitoring of Head and Neck Carcinogenesis

open access: yesAdvanced Science, EarlyView.
A miniaturized endoscopic probe that integrates Raman spectroscopy and optical coherence tomography, enabling simultaneous molecular and structural imaging of living tissue, was developed. Applied longitudinally in a mouse model of head and neck cancer, the system tracks disease progression from precancerous lesions to invasive cancer.
Jianrong Qiu   +7 more
wiley   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

open access: yesAdvanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne   +12 more
wiley   +1 more source

Self-concatenated code design and its application in power-efficient cooperative communications

open access: yes, 2012
In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis.
Butt, Muhammad Fasih   +2 more
core   +1 more source

Stochastic Entanglement of Deterministic Origami Tentacles For Robust Robotic Grasping

open access: yesAdvanced Science, EarlyView.
This study introduces an origami tentacle gripper to robustly grasp objects‐in air, underwater, and even in orbital space‐by exploiting a synergy between local, deterministic deformation programming and global, stochastic entanglements. A single origami tentacle can be designed to coil with a simple tendon pull.
Alec Boron   +4 more
wiley   +1 more source

Concatenated Space Time Block Codes and TCM, Turbo TCM Convolutional as well as Turbo Codes

open access: yes, 2000
Space-time block codes provide substantial diversity advantages for multiple transmit antenna systems at a low decoding complexity. In this paper, we concatenate space-time codes with Convolutional Codes (CC), Turbo Convolutional codes (TC), Turbo BCH ...
Pliquett, J.   +4 more
core   +1 more source

Unveiling the Taxonomic Diversity and Unprecedented Biosynthetic Treasure of the Phylum Myxococcota

open access: yesAdvanced Science, EarlyView.
Natural products remain vital sources of therapeutics, and the phylum Myxococcota constitutes an especially rich reservoir for them. Based on decades of microbiological efforts, we present 154 new Myxococcota genomes and revise taxonomy quadrupling the number of families and genera.
Amay Ajaykumar Agrawal   +25 more
wiley   +1 more source

TSTScope Unifies Single‐Cell Multi‐Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

open access: yesAdvanced Science, EarlyView.
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao   +8 more
wiley   +1 more source

On the Error Statistics of Turbo Decoding for Hybrid Concatenated Codes Design

open access: yesJournal of Communications Software and Systems, 2019
In this paper we propose a model for the generation of error patterns at the output of a turbo decoder. One of the advantages of this model is that it can be used to generate the error sequence with little effort.
Fulvio Babich, Francesca Vatta
doaj  

Trustworthy Multimodal Attention Framework for Creep Rupture Life Prediction Under Data‐Scarce Conditions: A Case Study on IN718

open access: yesAdvanced Science, EarlyView.
An attention‐based multimodal deep learning framework is developed to predict the creep life of Ni‐based superalloys by fusing processing parameters with microstructural micrographs. The model achieves high accuracy (R2 = 0.92), aligns with metallurgical principles by capturing δ‐phase influence, and incorporates uncertainty quantification, offering a ...
Haopeng Lv   +10 more
wiley   +1 more source

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

open access: yesAdvanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao   +6 more
wiley   +1 more source

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