Results 81 to 90 of about 23,153,291 (313)

Isoorientin Promotes Early Porcine Embryonic Development by Alleviating Oxidative Stress and Improving Lipid Metabolism

open access: yesAnimals
Isoorientin (ISO) is a natural lignan glycoside flavonoid found in various plants, including Charcot and Stonecrop. ISO exhibits diverse physiological and pharmacological effects, such as antioxidative, anti-inflammatory, hepatoprotective, antiviral ...
Zilong Meng   +7 more
doaj   +1 more source

Building Automation and Control Systems and Electrical Distribution Grids: A Study on the Effects of Loads Control Logics on Power Losses and Peaks

open access: yesEnergies, 2018
Growing home comfort is causing increasing energy consumption in residential buildings and a consequent stress in urban medium and low voltage distribution networks.
Salvatore Favuzza   +6 more
doaj   +1 more source

Hybrid Predictive Model: When an Interpretable Model Collaborates with a Black-box Model [PDF]

open access: yesarXiv, 2019
Interpretable machine learning has become a strong competitor for traditional black-box models. However, the possible loss of the predictive performance for gaining interpretability is often inevitable, putting practitioners in a dilemma of choosing between high accuracy (black-box models) and interpretability (interpretable models).
arxiv  

Refining the NaV1.7 pharmacophore of a class of venom‐derived peptide inhibitors via a combination of in silico screening and rational engineering

open access: yesFEBS Letters, EarlyView.
Venom peptides have shown promise in treating pain. Our study uses computer screening to identify a peptide that targets a sodium channel (NaV1.7) linked to chronic pain. We produced the peptide in the laboratory and refined its design, advancing the search for innovative pain therapies.
Gagan Sharma   +8 more
wiley   +1 more source

Hierarchical Models as Marginals of Hierarchical Models

open access: yes, 2016
We investigate the representation of hierarchical models in terms of marginals of other hierarchical models with smaller interactions. We focus on binary variables and marginals of pairwise interaction models whose hidden variables are conditionally ...
Montufar, Guido, Rauh, Johannes
core   +1 more source

Models as hypothesis generators and models as roadmaps [PDF]

open access: yes, 2010
In this reply to Kroll, Van Hell, Tokowicz and Green (this issue) we present an analysis of the citations made to the Revised Hierarchical Model (RHM).
Brysbaert, Marc   +2 more
core   +2 more sources

The power of microRNA regulation—insights into immunity and metabolism

open access: yesFEBS Letters, EarlyView.
MicroRNAs are emerging as crucial regulators at the intersection of metabolism and immunity. This review examines how miRNAs coordinate glucose and lipid metabolism while simultaneously modulating T‐cell development and immune responses. Moreover, it highlights how cutting‐edge artificial intelligence applications can identify miRNA biomarkers ...
Stefania Oliveto   +2 more
wiley   +1 more source

Fast Calculation Methods in Collective Dynamical Models of Beam/Plasma Physics

open access: yes, 2002
We consider an application of modification of our variational-wavelet approach to some nonlinear collective model of beam/plasma physics: Vlasov/Boltzmann-like reduction from general BBGKY hierachy related to modeling of propagation of intense charged ...
Antonina N. Fedorova   +2 more
core   +2 more sources

Identification of novel small molecule inhibitors of ETS transcription factors

open access: yesFEBS Letters, EarlyView.
ETS transcription factors play an essential role in tumourigenesis and are indispensable for sprouting angiogenesis, a hallmark of cancer, which fuels tumour expansion and dissemination. Thus, targeting ETS transcription factor function could represent an effective, multifaceted strategy to block tumour growth. The evolutionarily conserved E‐Twenty‐Six
Shaima Abdalla   +9 more
wiley   +1 more source

Trust the Model When It Is Confident: Masked Model-based Actor-Critic [PDF]

open access: yesarXiv, 2020
It is a popular belief that model-based Reinforcement Learning (RL) is more sample efficient than model-free RL, but in practice, it is not always true due to overweighed model errors. In complex and noisy settings, model-based RL tends to have trouble using the model if it does not know when to trust the model.
arxiv  

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