Results 141 to 150 of about 122,876 (196)

Fractal Anatomy of Human Organs: A Narrative Review of Structure, Function, and Clinical Perspectives

Clinical Anatomy, EarlyView.
ABSTRACT Fractal geometry describes complex, self‐similar patterns that repeat across spatial scales and is increasingly recognized as relevant in anatomical research. Indeed, the fractal organization is consistently observed in respiratory, cardiovascular, gastrointestinal, nervous, renal, hepatic, and dermatological systems.
Immacolata Belviso, Jacopo Junio Valerio Branca, Giulia Guarnieri, Annamaria Morelli, Alessandra Pacini, Daniele Della Posta, Domenico Ribatti, Ferdinando Paternostro   +7 more
wiley   +1 more source

Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review. [PDF]

Brief Bioinform
Wang Y, Li J, Zha H, Liu S, Huang D, Fu L, Liu X.   +6 more
europepmc   +1 more source

Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions

Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.
Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley   +1 more source

Effects of <i>Tetranychus urticae</i> infection on phyllosphere microbial community assembly of <i>Vigna unguiculata</i>. [PDF]

PeerJ
Chen D, Xia G, Wang J, Luo Y, Wang H, Zhao J, Sun K.   +6 more
europepmc   +1 more source

Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches

Chemistry – A European Journal, EarlyView.
Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Bidhan Chandra Garain, Max Pinheiro Jr., Matheus de Oliveira Bispo, Mario Barbatti   +3 more
wiley   +1 more source

Reconstructing noisy gene regulation dynamics using extrinsic-noise-driven neural stochastic differential equations. [PDF]

PLoS Comput Biol
Zhang J, Li X, Guo X, You Z, Böttcher L, Mogilner A, Hoffmann A, Chou T, Xia M.   +8 more
europepmc   +1 more source

An observation‐driven state‐space model for claims size modelling

Canadian Journal of Statistics, EarlyView.
Abstract State‐space models are popular in econometrics. Recently, these models have gained some popularity in the actuarial literature. The best known state‐space models are of the Kalman‐filter type. These are called parameter‐driven because the observations do not impact the state‐space dynamics.
Jae Youn Ahn, Himchan Jeong, Mario V. Wüthrich   +2 more
wiley   +1 more source

Predicting Physical Appearance from Low Template: State of the Art and Future Perspectives. [PDF]

Genes (Basel)
Sessa F, Dervišević E, Esposito M, Francaviglia M, Chisari M, Pomara C, Salerno M.   +6 more
europepmc   +1 more source

On subset least squares estimation and prediction in vector autoregressive models with exogenous variables

Canadian Journal of Statistics, EarlyView.
Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne, Thanh‐Liem Huynh, Mylène Oscar   +2 more
wiley   +1 more source

An intelligent framework for dynamic modeling of therapeutic response using clinical compliance data. [PDF]

Front Pharmacol
Wang X, Xie H.
europepmc   +1 more source