Results 61 to 70 of about 11,682 (203)

Engineering Neuronal Network Connectivity Through Precise and Scalable Electrical Modulation

open access: yesAdvanced Science, EarlyView.
This study presents a scalable all‐electrical method for precise neuronal‐circuit reconfiguration based on high‐density microelectrode arrays. By employing biologically inspired plasticity rules, targeted connectivity changes were successfully induced and quantified across diverse neuronal preparations.
Sreedhar S. Kumar   +10 more
wiley   +1 more source

Natural Resistance to Ovarian Hyperstimulation Syndrome in Estrildid Finches Reveals Macrophage GPR183 as a Potential Therapeutic Target

open access: yesAdvanced Science, EarlyView.
Ovarian macrophage depletion reverses OHSS resistance in estrildid finches and exacerbates OHSS symptoms in rats. Activating macrophage GPR183 alleviates OHSS by reducing pro‐inflammatory factors, increasing immunomodulatory molecules, remodeling CD44/SDC4‐mediated communication, and restoring immune homeostasis.
Xiaofei Yan   +11 more
wiley   +1 more source

A Multi-Stage Hybrid Retrieval Framework for the Scientific Literature with Cross-Encoder Re-Ranking

open access: yesApplied Sciences
Effective scientific literature retrieval requires moving beyond surface-level term matching toward structured semantic reasoning. This paper presents a controlled empirical study of multi-stage retrieval for scientific literature, integrating lexical ...
Walaa Al-Joofi   +2 more
doaj   +1 more source

Combining Spatial Multi‐Omics Data to Decipher Spatial Domains and Elucidate Cell Heterogeneity Based on Self‐Supervised Graph Learning

open access: yesAdvanced Science, EarlyView.
A self‐supervised multi‐view graph fusion framework integrates spatial multi‐omics, excelling in domain identification and denoising. It reconstructs spatial pseudo‐expression, jointly analyzes multi‐omics data, infers RNA velocity, predicts spatial omics features from single‐cell multi‐omics, and detects spatially dark genes and transcription factors,
Yuejing Lu   +8 more
wiley   +1 more source

Risk-Aware Selective Neural Refinement for Reliable Dense Retrieval

open access: yesIEEE Access
Neural retrieval pipelines increasingly rely on refinement mechanisms such as pseudo-relevance feedback and cross-encoder reranking to improve ranking effectiveness.
Khaled Albishre
doaj   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

open access: yesAdvanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu   +5 more
wiley   +1 more source

Query dependent pseudo-relevance feedback based on wikipedia

open access: yesProceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, 2009
Pseudo-relevance feedback (PRF) via query-expansion has been proven to be e®ective in many information retrieval (IR) tasks. In most existing work, the top-ranked documents from an initial search are assumed to be relevant and used for PRF. One problem with this approach is that one or more of the top retrieved documents may be non-relevant, which can ...
Xu, Yang, Jones, Gareth J.F., Wang, Bin
openaire   +2 more sources

From Label‐Free Multiphoton Imaging to Pathological Reports: A Vision‐Language Breast Cancer Margin Pathological Diagnosis System

open access: yesAdvanced Science, EarlyView.
MarginPath is a novel vision‐language system that automates breast cancer margin assessment using a single label‐free multiphoton microscopy image. By integrating tumor‐associated collagen signatures with virtual H&E imaging, it generates accurate margin heatmaps and comprehensive diagnostic reports.
Shu Wang   +15 more
wiley   +1 more source

How Advanced Artificial Intelligence Technologies Shape Drug–Drug and Drug–Target Interaction Modeling

open access: yesAdvanced Science, EarlyView.
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

Multiferroic‐Centric Materials and Systems Engineering for Battery Applications: An Insight Into Mechanisms, Strategies, and Characterizations

open access: yesAdvanced Science, EarlyView.
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su   +13 more
wiley   +1 more source

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