Results 161 to 170 of about 413,007 (211)

Experimental Immigration Mediates Ecological Selection and Drift in Monarch Microbiome Assembly. [PDF]

Ecol Lett
Catano CP, DuBose JG, Fuller-Hall L, Chavez J, de Roode JC.   +4 more
europepmc   +1 more source

Design for flexibility: An adjustable robust optimization approach with decision‐dependent uncertainty

AIChE Journal, EarlyView.
ABSTRACT Flexibility is a crucial characteristic of industrial systems that face increasing volatilities and is therefore essential to ensure feasible operation under uncertainty. Flexibility is often closely tied to the design of a system, and careful consideration must be taken to understand the trade‐off between design cost and operational ...
Jnana Sai Jagana, Sreekanth Rajagopalan, Satyajith Amaran, Qi Zhang   +3 more
wiley   +1 more source

Beyond metaphor: quantitative reconstruction of Waddington landscape and exploration of cellular behavior. [PDF]

Brief Bioinform
Han Y, Chen B, Zhang J, Shang X.
europepmc   +1 more source

Designing Memristive Materials for Artificial Dynamic Intelligence

Advanced Intelligent Discovery, EarlyView.
Key characteristics required of memristors for realizing next‐generation computing, along with modeling approaches employed to analyze their underlying mechanisms. These modeling techniques span from the atomic scale to the array scale and cover temporal scales ranging from picoseconds to microseconds. Hardware architectures inspired by neural networks
Youngmin Kim, Ho Won Jang
wiley   +1 more source

Optimal input signal design for closed loop aircraft flutter model analysis. [PDF]

Sci Rep
Jianhong W.
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Predicting NMR Relaxation Using a First-Principles Brownian Dynamics Approach. [PDF]

J Chem Theory Comput
Zerbetto M, Rampino S, Polimeno A.
europepmc   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

A dual-stochastic real options model for sports tourism investment: A case study in China. [PDF]

PLoS One
Liu T, Cheng J, Huang Y.
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source