Results 101 to 110 of about 807,423 (305)

Entropy scaling for diffusion coefficients in fluid mixtures

Nature Communications
Abstract Entropy scaling is a powerful technique that has been used for predicting transport properties of pure components over a wide range of states. However, modeling mixture diffusion coefficients by entropy scaling is an unresolved task.
Sebastian Schmitt, Hans Hasse, Simon Stephan   +2 more
openaire   +4 more sources

Robust Mixture Regression Based on the Skew t Distribution

Revista Colombiana de Estadística, 2017
In this study, we explore a robust mixture regression procedure based on the skew t distribution in order to model heavy-tailed and/or skewed errors in a mixture regression setting.
FATMA ZEHRA Doğru, OLCAY ARSLAN
doaj   +1 more source

Engineered extracellular vesicles enriched with the miR‐214/199a cluster enhance the efficacy of chemotherapy in ovarian cancer

Molecular Oncology, EarlyView.
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang, Ayesha Alvero, Yi Qin, Mingjin Wang, Alexandra Fox, Yanfeng Li, Michael Millman, Amy Kemper, Gil Mor, Xian Shuang Liu, Michael Chopp, Zheng Gang Zhang, Yi Zhang   +12 more
wiley   +1 more source

A semiparametric Bayesian approach to the analysis of financial time series with applications to value at risk estimation [PDF]

Financial time series analysis deals with the understanding of data collected on financial markets. Several parametric distribution models have been entertained for describing, estimating and predicting the dynamics of financial time series ...
Concepción Ausín, Pulak Ghosh, Pedro Galeano   +2 more
core  

Scale Mixture Models with Applications to Bayesian Inference [PDF]

, 2003
Scale mixtures of uniform distributions are used to model non‐normal data in time series and econometrics in a Bayesian framework. Heteroscedastic and skewed data models are also tackled using scale mixture of uniform distributions.
Walker, Stephen G., Qin, Zhaohui Steve, Damien, Paul   +2 more
core   +1 more source

Robust mixture modeling based on scale mixtures of skew-normal distributions

Computational Statistics & Data Analysis, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rodrigo M. Basso, Victor H. Lachos, Celso Rômulo Barbosa Cabral, Pulak Ghosh   +3 more
openaire   +1 more source

Keratin 19 as a prognostic marker and contributing factor of metastasis and chemoresistance in high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch, Isabel Vogel, Sina Nokodian, Johanna Moeller, Antonia Blechschmidt, Vicky Hecht, Vanessa Kuentzel, Katharina Thiedig, Melissa Schwab, Oliver Schilling, Holger Bronger, Marion Kiechle, Viktor Magdolen, Tobias Dreyer   +13 more
wiley   +1 more source

Extremes of scale mixtures of multivariate time series

Journal of Multivariate Analysis, 2015
Factor models have large potencial in the modeling of several natural and human phenomena. In this paper we consider a multivariate time series $\mb{Y}_n$, ${n\geq 1}$, rescaled through random factors $\mb{T}_n$, ${n\geq 1}$, extending some scale mixture models in the literature.
Helena Ferreira, Marta Ferreira
openaire   +4 more sources

Weighted Total Variation for Hyperspectral Image Denoising Based on Hyper-Laplacian Scale Mixture Distribution

Remote Sensing
Conventional total variation (TV) regularization methods based on Laplacian or fixed-scale Hyper-Laplacian priors impose uniform sparsity penalties on gradients.
Xiaoyu Yu, Jianli Zhao, Sheng Fang, Tianheng Zhang, Liang Li, Xinyue Huang   +5 more
doaj   +1 more source

Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma

Molecular Oncology, EarlyView.
The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic, Anne Nørremølle, Lilian Bomme Ousager, Lars van Brakel Andersen, Marie Louise Mølgaard Binderup, Mads Thomassen   +5 more
wiley   +1 more source