Results 101 to 110 of about 142,210 (310)
Advanced Science, EarlyView.Fibronectin 1 (FN1)‐expressing subicular subpopulations encode novel object preference and selectively govern retrieval of novel object recognition (NOR) via affecting excitability of entorhinal‐projecting circuit through large conductance Ca2+‐activated potassium (BK) channel. ABSTRACT Novel object recognition (NOR), referring to the cognitive ability
Fan Fei +15 more
wiley +1 more source
Modelling the Density of Inflation Using Autoregressive Conditional Heteroscedasticity, Skewness, and Kurtosis Models [PDF]
The paper aimed at modelling the density of inflation based on time-varying conditional variance, skewness and kurtosis model developed by Leon, Rubio, and Serna (2005) who model higher-order moments as GARCH-type processes by applying a Gram-Charlier ...
Doaa Akl Ahmed
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Targeting the PDK1/c‐Myc/SOX10 Signaling in Oligodendrocytes Alleviates Neuropathic Pain
Advanced Science, EarlyView.This work reveals that oligodendrocyte homeostasis, mediated by PDK1, is a critical determinant of neuropathic pain (NPP) pathogenesis. Disruption of PDK1 in oligodendrocytes impairs SOX10‐dependent myelination programs through c‐Myc accumulation, leading to disrupted myelination and the pathophysiology of NPP.
Pingping Qiao +7 more
wiley +1 more source
Advanced Science, EarlyView.This study identifies an immunometabolic axis wherein SAM‐driven PRMT1 methylates LDHA, enhancing its activity. The resultant lactate induces STAT3 K709 lactylation, which stabilizes an active conformation to promote STAT3 phosphorylation and IL‐10 expression.
Hui Wang +12 more
wiley +1 more source
An Extended Result on the Optimal Estimation Under the Minimum Error Entropy Criterion
Entropy, 2014 The minimum error entropy (MEE) criterion has been successfully used in fields such as parameter estimation, system identification and the supervised machine learning.
Badong Chen +3 more
doaj +1 more source
On conditional truncated densities Bayesian networks
International Journal of Approximate Reasoning, 2018 The majority of Bayesian networks learning and inference algorithms rely on the assumption that all random variables are discrete, which is not necessarily the case in real-world problems. In situations where some variables are continuous, a trade-off between the expressive power of the model and the computational complexity of inference has to be done:
Cortijo, Santiago, Gonzales, Christophe
openaire +2 more sources
Distribution Dynamics of Food Price Inflation Rates in EU: An Alternative Conditional Density Estimator Approach [PDF]
Concepts and developments in the literature of economic growth and convergence have recently been adopted and used in the study of inflation rate convergence.
Angelos Liontakis, Christos T. Papadas
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Advanced Science, EarlyView.ABSTRACT Inflammatory bowel disease (IBD) is characterized by dysregulated T cell responses. RNA helicases, including DExD‐box helicase 21 (DDX21), are pivotal in RNA metabolism, but their role in T cell‐mediated pathology during IBD remains unclear. Here, we demonstrate that DDX21 expression in CD4+ T cells correlates with cell cycle and translation ...
Yujuan Zhang +11 more
wiley +1 more source
The density condition and the strong dual density condition by operator
Collectanea Mathematica, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
Nonparametric Density Estimation for Positive Time Series [PDF]
The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions have been put forward to solve this boundary problem. In this paper we propose
Jeroen V.K. Rombouts, Taoufik Bouezmarni
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