Results 141 to 150 of about 38,175 (260)

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

Advanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng, Mingwei He, Jeff Zhu, Sujit K. Sahoo, Liheng Bian, Cuong Dang   +5 more
wiley   +1 more source

Impacts of land use/land cover change on ecosystem service values in the Dinki Watershed, central highlands of Ethiopia. [PDF]

Sci Rep
Worku Y, Asmamaw M, Ambelu A.
europepmc   +1 more source

Scalable Engineering of Bio‐Manufactured Extracellular Vesicles for Selective Delivery in Ovarian Cancer Patient‐Derived Models

Advanced Science, EarlyView.
Engineered extracellular vesicles displaying Ephrin‐B2 selectively target Ephrin‐B4–expressing ovarian cancer cells, enabling precise delivery in patient‐derived models. This scalable bio‐manufacturing platform reveals a versatile strategy to exploit Ephrin signaling for highly specific therapeutic payload delivery and motivates exploration of tailored
Nihar Godbole, Andrew Lai, Alexander Quinn, Marianne Gillard, Dominic Guanzon, Katherin Scholz‐Romero, Alexis Salas‐Burgos, Bastián Lillo Dapremont, Rohan Lourie, Naven Chetty, Richard Lobb, Kate Beecher, Amy E. McCart Reed, Kaltin Ferguson, Biao Sun, Yaowu He, John D. Hooper, Carlos Salomon   +17 more
wiley   +1 more source

Multi-Level Variable Selection Using a BART-Enhanced Mixed-Effects Framework. [PDF]

Stat Med
Zhang K, Li Y, Zou J, Wang S, Fausto BA, Hu L.   +5 more
europepmc   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

SpaMode: A Broadly Applicable Framework for Deciphering Spatial Multi‐Omics Using Multimodal Mixture of Disentangled Experts

Advanced Science, EarlyView.
SpaMode introduces a versatile framework for spatial multi‐omics integration across vertical, horizontal, and mosaic scenarios. By disentangling modality‐invariant and variant features through a mixture‐of‐experts mechanism, it adaptively reconfigures spatially heterogeneous signals.
Xubin Zheng, Xinlei Huang, Xiang Zhou, Dian Meng, Ziyue Qiao, Zhiyuan Yuan, Lixin Cheng   +6 more
wiley   +1 more source

The First Year Matters: Lifestyle Behaviors and Five-Year Cardiometabolic Risk Factor Accumulation After Traumatic Brain Injury. [PDF]

Med Sci (Basel)
Calderone A, Bonanno L, Famà F, Ciancarelli I, Currò A, Quartarone A, Rifici C, Calabrò RS.   +7 more
europepmc   +1 more source

A Bone Marrow–Mimetic Hydrogel Enables Dual‐Phase Hemostasis and Vascularized Osteogenesis for Cranial Defects

Advanced Science, EarlyView.
A biomimetic, fiber‐reinforced hydrogel (FE‐PDA@Fib/Gel‐TG) that enables dual‐phase cranial defect repair. The system provides: instant hemostasis in the early stage, and sustained co‐delivery of pro‐angiogenic and osteogenic signals for synergistic vascularized bone regeneration.
Lingbin Che, Donghong Li, Huan Zhang, Tingting Xu, Juhan Li, Xuanzhou Chen, Louis D. Zhang, Shuguang Wang, Dianwen Song, Dongyong Sha   +9 more
wiley   +1 more source

Variable rate neural compression for sparse detector data. [PDF]

Patterns (N Y)
Huang Y, Go Y, Huang J, Li S, Luo X, Marshall T, Osborn JD, Pinkenburg C, Ren Y, Shulga E, Yoo S, Yoon BJ.   +11 more
europepmc   +1 more source

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

Advanced 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, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source