Results 131 to 140 of about 356,775 (282)

From Cell‐Free Transcriptomes to Single‐Cell Landscapes: Biomarker Discovery and Originating Cell Alteration Analysis via Graph Matrix Factorization

Advanced Science, EarlyView.
CellFreeGMF traces plasma cfRNA to likely originating cell types by integrating single‐cell atlases with graph‐regularized matrix factorization. The method decomposes cfRNA profiles into sample–cell contributions to reconstruct pseudo single‐cell expression.
Wenxiang Zhang, Wenjing Zhang, Hang Wei, Shiyan Liu, Junliang Shang, Weijie Gong, Hanwen Cheng, Xiujuan Lei, Yuhui Kou, Baoguo Jiang   +9 more
wiley   +1 more source

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

Advanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang, Yiming Xia, Ali Shakiba, Hongrui Zhang, Xiaojing Hao, Priyank V. Kumar, Mahesh P. Suryawanshi   +6 more
wiley   +1 more source

On modeling the log-returns of Bitcoin and Ethereum prices against the USA Dollar

Alexandria Engineering Journal
The study and investigation of the behavior of monetary phenomena is an interesting subject for actuaries and practitioners. In the recent age and development in the monetary and financial phenomena, cryptocurrency has gained much attention from ...
Mustafa Kamal, Sabir Ali Siddiqui, Nayabuddin, Afaf Alrashidi, Maha M. Helmi, Hassan M. Aljohani, Aned Al Mutairi, Ibrahim AlKhairy, Eslam Hussam, M. Yusuf, Samhi Abdelaty Difalla   +10 more
doaj   +1 more source

Extended Weibull log-logistic distribution

Journal of Nonlinear Sciences and Applications, 2019
T. H. M. Abouelmagd, Mohammed S. Hamed, Jehan. A. Almamy Almamy, M. Masoom Ali, Haitham M. Yousof, Mustafa C. Korkmaz   +5 more
openaire   +2 more sources

Organic Thin‐Film Transistors for Neuromorphic Computing

Advanced Electronic Materials, EarlyView.
Organic thin‐film transistors (OTFTs) are reviewed for neuromorphic computing applications, highlighting their power‐efficient, and biological time‐scale operation. This article surveys OFET and OECT devices, compares them with memristors and CMOS, analyzes how fabrication parameters shape spike‐based metrics, proposes standardized characterization ...
Luke McCarthy, Mohan V. Jacob, Mostafa Rahimi Azghadi   +2 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

Further results involving Marshall-Olkin log-logistic distribution: reliability analysis, estimation of the parameter, and applications. [PDF]

Springerplus, 2016
Alshangiti AM, Kayid M, Alarfaj B.
europepmc   +1 more source

SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range

Advanced Electronic Materials, EarlyView.
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel, Aleix Barrera, Lluís Balcells, Narcís Mestres, Enrique Miranda, Anna Palau, Jordi Suñé   +6 more
wiley   +1 more source

A parametric method for cumulative incidence modeling with a new four-parameter log-logistic distribution. [PDF]

Theor Biol Med Model, 2011
Shayan Z, Ayatollahi SM, Zare N.
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