Results 91 to 100 of about 12,301 (257)

Deep Generative Symbolic Regression

, 2023
Comment: In the proceedings of the Eleventh International Conference on Learning Representations (ICLR 2023).
Holt, Samuel, Qian, Zhaozhi, van der Schaar, Mihaela   +2 more
openaire   +1 more source

3D Soft Hydrogels Induce Human Mesenchymal Stem Cells “Deep” Quiescence

Advanced Healthcare Materials, EarlyView.
Three‐dimensional soft hydrogels mimicking the bone marrow niche induce deep quiescence in human mesenchymal stem cells. Unlike 2D culture, 3D matrices halt proliferation, regulate cell‐cycle and quiescence markers, and downregulate mTORC1 signaling, preserving stem cell phenotype and therapeutic potential ex vivo.
David Boaventura Gomes, Timo Rademakers, Ana Filipa Henriques Lourenço, Andrea Calore, Clarissa Tomasina, Denis van Beurden, Jinjie Venema, Bryan Chömpff, Hong Liu, Nicole Bouvy, Sandra Camarero‐Espinosa, Lorenzo Moroni   +11 more
wiley   +1 more source

Analysis and prediction of carbon emission factors based on genetic programming

Results in Engineering
In recent years, frequent extreme weather events such as storms and floods globally have made carbon emission reduction a critical issue for addressing environmental challenges through sustainable green pathways.
Wenchao Pan, Tsungxian Lin, Tzuhsiung Lin, Qilin Du, Lili Wu, Qinyi Lin   +5 more
doaj   +1 more source

Mixed‐Metal Promotion in a Manganese‐Molybdenum Oxynitride as Catalyst to Integrate C─C and C─N Coupling Reactions for the Direct Synthesis of Acetonitrile from Syngas and Ammonia

Advanced Materials, EarlyView.
Transition metal oxy/carbo‐nitrides show great promise as catalysts for sustainable processes. A Mn‐Mo mixed‐metal oxynitride attains remarkable performance for the direct synthesis of acetonitrile, an important commodity chemical, via sequential C─N and C─C coupling from syngas (C1) and ammonia (N1) feedstocks.
M. Elena Martínez‐Monje, Wilson Henao, Tania Rodenas, Patricia Concepción, Virginia Pérez Dieste, Alexander Missyul, Giovanni Agostini, Gonzalo Prieto   +7 more
wiley   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Automated Regression Testing using Symbolic Execution

Elektronika ir Elektrotechnika, 2011
The aim of this paper is to describe a way to construct tests which validate that changes made during software evolution did not introduce regression faults. Developers usually run a new version of the program against the same set of tests. In order to achieve this goal, symbolic execution was used for test input generation and full structural code ...
Barisas, D., Milasius, T., Bareisa, E., Kauno technologijos universitetas   +3 more
openaire   +2 more sources

Light‐Induced Entropy for Secure Vision

Advanced Materials, EarlyView.
This work realized a ternary true random number generator by exploiting stochastic traps emerging within multiple junction interfaces, and quantitatively validated the generation of high‐quality random numbers. Furthermore, it successfully demonstrated diverse applications, including AI‐resilient image security, thereby providing a valuable guide for ...
Juhyung Seo, Seungme Kang, Chaehyun Kim, Taehyun Park, Youngwoo Yoo, Yeong Kwon Kim, Wonjun Shin, Byung Chul Jang, Young‐Joon Kim, Hocheon Yoo   +9 more
wiley   +1 more source

Navigating Ternary Doping in Li‐ion Cathodes With Closed‐Loop Multi‐Objective Bayesian Optimization

Advanced Materials, EarlyView.
The search for advanced battery materials is pushing us into highly complex composition spaces. Here, a space with about 14 million unique combinations is efficiently explored using high‐throughput experimentation guided by Bayesian optimization with a deep kernel trained on both the Materials Project database and our data.
Nooshin Zeinali Galabi, Cheng‐Hao Liu, Moksh Jain, Marc Kamel, Shipeng Jia, Yoshua Bengio, Eric McCalla   +6 more
wiley   +1 more source

Symbolic regression as a feature engineering method for machine and deep learning regression tasks

Machine Learning: Science and Technology
In the realm of machine and deep learning (DL) regression tasks, the role of effective feature engineering (FE) is pivotal in enhancing model performance. Traditional approaches of FE often rely on domain expertise to manually design features for machine
Assaf Shmuel, Oren Glickman, Teddy Lazebnik   +2 more
doaj   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, EarlyView.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source