Results 111 to 120 of about 11,772 (267)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

A Soft Matrix Microenvironment Promotes Laterally Spreading Tumors via Oxidative Phosphorylation‐Dependent Cell Adhesion

Advanced Science, EarlyView.
Laterally spreading tumors (LSTs) are precancerous colorectal lesions characterized by a flat morphology. This study reveals a mechanochemical pathway through which a soft matrix microenvironment diminishes spatial constraints in intestinal adenomas. This process promotes deficiencies in tight junction proteins, mediated by the mechanoreceptor ADORA2B ...
Jiamin Zhong, Jingyi Lu, Haopeng Li, Jun Zhong, Xiaobei Luo, Yiyi Hu, Xianfei Wang, Pengfei Wang, Yanning Zhang, Zhenjiang Wang, Qiuhua Lai, Zhenyu Chen, Wenting Mi, Wang Tin San‐to, Weize Li, Shuping Tan, Qihong Cheng, Ruijia Li, Yida Nie, Side Liu, Bing Huang, Zelong Han   +21 more
wiley   +1 more source

Machine‐Learning‐Guided Design of Incommensurate Antiferroelectrics via Field‐Driven Phase Engineering

Advanced Science, EarlyView.
The key to enhancing the energy storage performance of antiferroelectrics lies in regulating the phase transition and reverse phase transition. A phase‐field‐machine learning framework is employed to predict the energy storage performance of Pb‐based incommensurate antiferroelectrics with multi‐scale regulation strategy, thereby revealing the dynamic ...
Ke Xu, Xiaoming Shi, Zhaochen Xi, Shouzhe Dong, Changqing Guo, Rongzhen Gao, Letao Yang, Jing Wang, Di Zhou, Houbing Huang   +9 more
wiley   +1 more source

Fluency Is Good, but Comprehension Is Better: The Impact of Fluency and Comprehension on Mathematical Word Problem Solving. [PDF]

Dyslexia
Treutlein A.
europepmc   +1 more source

Beyond the Non‐Hermitian Skin Effect: Scaling‐Controlled Topology from Exceptional‐Bound Bands

Advanced Science, EarlyView.
ABSTRACT We establish a novel mechanism for topological transitions in non‐Hermitian systems that are controlled by the system size. Based on a new paradigm known as exceptional‐bound (EB) band engineering, its mechanism hinges on the unique critical scaling behavior near an exceptional point, totally unrelated to the well‐known non‐Hermitian skin ...
Mengjie Yang, Ching Hua Lee
wiley   +1 more source

The Language of Numbers: Reading Comprehension and Applied Math Problem-Solving. [PDF]

Behav Sci (Basel)
Sury D, Pilchin L.
europepmc   +1 more source

Students, texts and mathematics : an analysis of mathematics texts and the construction of mathematics knowledge

, 2001
Bibliography: leaves 149-155.
openaire   +1 more source

DC‐magnetometry Analytical Tool Driven by Spin Ordering Phenomena for Sensing Chemical Interactions at the Surface of Nanomaterials

Advanced Science, EarlyView.
The adsorption of AsV on akaganeite nanorods was found to provide a magnetic signature. A change in the surface spin order gave rise to a second peak in the zero‐field cooled curve. AsIII adsorption does not provide any change in the magnetic behavior of the sorbent.
Marco Sanna Angotzi, Valentina Mameli, Alessandra Fantasia, Cesare Atzori, Giovanni Bertoni, Vincenzo Grillo, Giorgio Divitini, Dominika Zakutna, Jana Vejpravova, Martin Kalbac, Jan Plšek, Carla Cannas   +11 more
wiley   +1 more source

Eye-Tracking Data in the Exploration of Students' Engagement with Representations in Mathematics: Areas of Interest (AOIs) as Methodological and Conceptual Challenges. [PDF]

J Eye Mov Res
Nedaei M, Säljö R, Kanwal S, Goodchild S.   +3 more
europepmc   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source