Results 31 to 40 of about 440,549 (202)

Geometric and algebraic classification of quadratic differential systems with invariant hyperbolas

Electronic Journal of Differential Equations, 2017
Let QSH be the whole class of non-degenerate planar quadratic differential systems possessing at least one invariant hyperbola. We classify this family of systems, modulo the action of the group of real affine transformations and time rescaling ...
Regilene D. S. Oliveira, Alex C. Rezende, Dana Schlomiuk, Nicolae Vulpe   +3 more
doaj  

MetaboSense: An Integrated Quantum Dot‐Mediated Aptamer Assay and Modular Microfluidic Platform for Continuous In‐Line Monitoring of Lung Metabolism During Ex Vivo Perfusion

Advanced Science, EarlyView.
MetaboSense is a first‐of‐its‐kind microfluidic platform enabling continuous, in‐line monitoring of glucose and lactate during ex vivo lung perfusion. Combining a quantum dot–mediated aptamer assay with mixing, depletion, and optofluidic detection modules, it achieves 60–s temporal resolution and shows strong agreement with standard blood gas analyzers,
Sanjana Srikant, Pouyan Keshavarz Motamed, Thomas Borrillo, Lielle Ronen, Gabriel Siebiger, Guillermo Garza, Hesam Abouali, Md Fahim Al Fattah, Ines Jaber, Dayan Ban, Marcelo Cypel, Mingyao Liu, Shaf Keshavjee, Andrew T. Sage, Mahla Poudineh   +14 more
wiley   +1 more source

On Sums of Locally Testable Affine Invariant Properties [PDF]

, 2011
Affine-invariant properties are an abstract class of properties that generalize some central algebraic ones, such as linearity and low-degree-ness, that have been studied extensively in the context of property testing.
Elena Grigorescu, Ben-Sasson, Eli, Madhu Sudan, Eli Ben-Sasson, Shpilka, Amir, Ghid Maatouk, Amir Shpilka, Maatouk, Ghid, Grigorescu, Elena, Sudan, Madhu   +9 more
core   +1 more source

Canonical Antibodies Adopt Distinct Binding Modes to Recognize Viral Glycan Shields

Advanced Science, EarlyView.
Canonical Y‐shaped antibodies recognize viral glycan shields through adaptive Fab assembly states shaped by glycan organization and somatic hypermutation. Structural analyses ofbroadly neutralizing antibodies VRC35 and VRC36 across glycoproteins of HIV‐1, influenza, SARS‐CoV‐2, and Lassa viruses reveal distinct Fab assembly states, spanning monovalent,
Jiaxuan Cheng, Evan M. Cale, Amirabbas Maghsoudi, Matthew S. Sutton, Nancy S. Longo, Rebecca A. Gillespie, Lingshu Wang, Ivan Kosik, Sue Chong, Atsuhiro Yasuhara, Tatsiana Bylund, Arne Schön, Prabhanshu Tripathi, Yaroslav Tsybovsky, Haotian Lei, Nicholas C. Morano, Allison B. Lupatkin, Abraham J. Morton, Zabrina C. Lang, Jordan E. Becker, Isabella R. Frascilla, Myungjin Lee, Ning Li, Cuiping Liu, Ryan S. Roark, Chen‐Hsiang Shen, I‐Ting Teng, David J. Van Wazer, Danyi Wang, Lingyuan Wu, Goran Ahlsen, Mike Castro, Haijuan Du, Michael J. Ernandes, Tiansheng Li, Bob C. Lin, Mark K. Louder, Krisha McKee, Jonah S. Merriam, Sijy O'Dell, Li Ou, Sergei Pletnev, David Prikryl, Qi Qiu, Sarah Rubin, Mallika Sastry, Stephen D. Schmidt, Asif Shajahan, Andrea R. Shiakolas, Sanjay Srivatsan, Baoshan Zhang, Qiong Zhou, Mark Connors, Jason G. Gall, Yicheng Guo, Rick K. Huang, Yaoxing Huang, Richard A. Koup, Q. Paula Lei, John R. Mascola, Reda Rawi, Leonid Serebryannyy, Lawrence Shapiro, Zizhang Sheng, David D. Ho, Patrick C. Wilson, Jonathan W. Yewdell, Theodore C. Pierson, Masaru Kanekiyo, Nicole A. Doria‐Rose, Peter D. Kwong, Tongqing Zhou   +71 more
wiley   +1 more source

Learning regime‐dependent governing equations: A symbolic decision tree approach

AIChE Journal, EarlyView.
Abstract Many chemical engineering systems are governed by mechanisms that switch across operating regimes, making the data‐driven discovery of regime‐dependent governing equations essential for predictive modeling, optimization, and control. We propose symbolic decision trees for the data‐driven discovery of regime‐dependent governing equations.
Ilias Mitrai, Tongjia Liu, Gabriel E. Sanoja   +2 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Family of quadratic differential systems with invariant hyperbolas:a complete classification in the space R^12

Electronic Journal of Differential Equations, 2016
In this article we consider the class QS of all non-degenerate quadratic systems. A quadratic polynomial differential system can be identified with a single point of R^{12} through its coefficients.
Regilene D. S. Oliveira, Alex C. Rezende, Nicolae Vulpe   +2 more
doaj  

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source