Results 261 to 270 of about 601,117 (314)

Single‐Cell Profiling Identifies SLC2A5‐Mediated Fructose Metabolism as a Vulnerability in Primary CNS Lymphoma

Advanced Science, EarlyView.
Glucose deprivation in the primary CNS lymphoma (PCNSL) tumor microenvironment drives SLC2A5 (encoding GLUT5)‐dependent fructose metabolism in tumor cells, while hypoxia induces HIF‐mediated SLC2A5 expression in tumor‐supportive macrophages, revealing SLC2A5‐driven fructose utilization as a shared and targetable metabolic vulnerability across malignant
Qiaoli Wu, Qianru Zhang, Wenqiang Yan, Lu Sun, Yiran Cui, Bolin Liu, Guoqing Han, Feng Zhang, Ke Pu, Mingchao Zhang, Xiaobing Zhang, Qingguo Li, Gang An, Yuxuan Liu   +13 more
wiley   +1 more source

SSDBFAN: Scalable and Secure Cluster-Based Data Aggregation with Blockchain for Flying Ad Hoc Networks. [PDF]

Sensors (Basel)
Majmaie SA, Ghajari G, Bhatta NP, Ibrahem MI, Amsaad F.   +4 more
europepmc   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Safety of Sodium‐Ion Batteries: Evaluation and Perspective from Component Materials to Cells, Modules, and Packs

Advanced Energy Materials, EarlyView.
This review provides a bottom‐up evaluation of sodium‐ion battery safety, linking material degradation mechanisms, cell engineering parameters, and module/pack assembly. It emphasizes that understanding intrinsic material stability and establishing coordinated engineering control across hierarchical levels are vital for preventing degradation coupling ...
Won‐Gwang Lim, Seoa Kim, Erik A. Wu, Darren H. S. Tan, Shawn Peng, Xiaolin Li   +5 more
wiley   +1 more source

Prospective validation of an AI algorithm to identify adult-onset type 1 diabetes misclassification: protocol for a non-interventional multicentre study. [PDF]

BMJ Open
Brusini I, Lee S, Lai A, Sees A, Hackenberg M, Liptak G, Rao AD, Anastasopoulou C, Leavitt N.   +8 more
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Digital Twin-Enabled Waveform Optimization for VHF Radio Communication Systems. [PDF]

Sensors (Basel)
Zhong C, Liu B, Zhu W, Wang B, Tan Y, Wang X.   +5 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Research on online EDI order scheduling optimization strategy in manufacturing enterprises based on time-varying Markov chains. [PDF]

Sci Rep
Wulan Q.
europepmc   +1 more source