Results 151 to 160 of about 17,106 (295)

Integrating Atomistic Insights With Circuit Simulations via Transformer-Driven Symbolic Regression

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
This article introduces a framework that establishes a cohesive link between the first principles-based simulations and circuit-level analyses using a machine learning-based compact modeling platform.
Md Rahatul Islam Udoy, Jack Hutchins, Shamiul Alam, Catherine Schuman, Ahmedullah Aziz   +4 more
doaj   +1 more source

Data-driven modelling using symbolic regression [PDF]

, 2016
This research aims at automating the process of system identification and control synthesis for complex systems by means of evolutionary symbolic tools that result in interpretable models and control laws, enabling compact and efficient controller ...
Tóth, Roland Roland, Khandelwal, D., Toth, R.; id_orcid, Toth, R., Khandelwal, D   +4 more
core  

ANKS1B in the Nucleus Accumbens Controls Escalated Cocaine Self‐Administration via Regulating CBP‐FoxO3 Complex

Advanced Science, EarlyView.
ANKS1B in the nucleus accumbens plays a critical role in the transition from controlled to escalated cocaine intake. Mechanistically, ANKS1B interacts with CBP to epigenetically suppress FoxO3 through H3K27 acetylation. The ANKS1B‐CBP‐FoxO3 signaling cascade presents a novel theraputic target for the treatment of cocaine addiction.
Liping Yang, Xiaoxuan Wu, Xuan Chen, Chao Peng, Zihang Li, Shumin Gao, Shiqiu Meng, Jing Dong, Dong Wu, Liying Lv, Ying Han, Yanxue Xue, Lin Lu, Jie Shi, Jianfeng Liu, Yan Sun   +15 more
wiley   +1 more source

Exploring Symbolic Regression and Genetic Algorithms for Astronomical Object Classification

The Open Journal of Astrophysics
This study explores the use of symbolic regression (SR) combined with genetic algorithms (GA) to classify astronomical objects. Using the SDSS17 dataset from Kaggle, which includes 100,000 observations of stars, galaxies, and quasars, we applied SR to 10%
Fabio Ricardo Llorella, José Antonio Cebrian   +1 more
doaj   +1 more source

Astrocytic Phenotypic Switching in Posterior Piriform Cortex Orchestrates Bone Cancer Pain–Depression Comorbidity via Purinergic–Noradrenergic Signaling

Advanced Science, EarlyView.
Bone cancer pain and depression share a common origin: astrocytic A2‐to‐A1 transition in the posterior piriform cortex. This phenotypic shift disrupts the ATP–adenosine–A2AR–norepinephrine axis, simultaneously driving nociceptive and affective dysfunction.
Jiang‐Ping Liu, Jun‐Han Zhang, Zhi‐Xuan Tan, Wei‐Bing Yan, Ya‐Ru Yuan, Yao Liu, Bing‐Di Wei, Meng‐Qi Ding, Zhuo‐Min Fu, Ying Liu, An‐Qi Wang, Lin Ma, Yong‐Hong Li, Er‐Qing Chai, Chao‐Jun Wei   +14 more
wiley   +1 more source

SPINEX-symbolic regression: similarity-based symbolic regression with explainable neighbors exploration

The Journal of Supercomputing
Abstract This article introduces a new symbolic regression algorithm based on the SPINEX (similarity-based predictions with explainable neighbors exploration) family. This new algorithm (SPINEX_SymbolicRegression) adopts a similarity-based approach to identifying high-merit expressions that satisfy accuracy- and structural similarity metrics.
Mohannad Z. Naser, Ahmad Z. Naser
openaire   +1 more source

Construction of a MOF‐Based Snap‐Top Delivery Nanosystem for Powerful Dual‐Responsive Synergistic Colitis Treatment

Advanced Science, EarlyView.
A snap‐top delivery nanosystem based on an azobenzene metal–organic framework achieves targeted release of 6‐mercaptopurine via acid‐stable frameworks and hypoxia/pH dual‐responsive β‐cyclodextrin gates. This multifunctional platform integrates three synergistic mechanisms: precision drug delivery to inflammatory sites, intrinsic antioxidant properties
Xin Li, Miao Xu, Heran Li, Huan Jiang, Xin Wang, Lianjun Ma, Ying‐Wei Yang   +6 more
wiley   +1 more source

Temporal Feature Selection with Symbolic Regression

, 2017
Building and discovering useful features when constructing machine learning models is the central task for the machine learning practitioner. Good features are useful not only in increasing the predictive power of a model but also in illuminating the ...
Fusting, Christopher Winter
core  

Multimodal Imaging Reveals Rapid Catecholamine Uptake and Release by Neutrophils

Advanced Science, EarlyView.
We show that immune cells (neutrophils) synthesize, uptake, and store catecholamine neurotransmitters such as dopamine or adrenaline. They also release them in response to specific stimuli (serotonin), which we directly visualize using fluorescent nanosensors. We further demonstrate that catecholamines affect neutrophil functions (NETosis) and platelet
Jennifer Mohr, Anne Schmitz, Meshkat Dinarvand, Franziska Wulfert, Sangeetha Shankar, Bjoern F. Hill, Michael Wojak, Juliana Gretz, Marie Britz, Elsa Neubert, Magdalena Shumanska, Sofia Kaushik, Linda Kartaschew, Ivan Bogeski, James Daniel, Sebastian Jung, Johannes Eble, Guido Wabnitz, Luise Erpenbeck, Sebastian Kruss   +19 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source