Results 61 to 70 of about 74,272 (306)

Building phenotypic character matrices for phylogenetic inference: exploration of 35 years of practice

Biological Reviews, EarlyView.
ABSTRACT Recent methodological development in phylogenetic inference has focused predominantly on molecular data. However, renewed interest in other data types, particularly morphological data, has followed from the increased recognition of the power of total evidence and tip‐dating approaches, including fossil data, for inference of time‐scaled trees ...
Melanie J. Hopkins, Mark C. Nikolic, James D. Holmes, Daniela S. Monti, Ernesto E. Vargas‐Parra, Russell D.C. Bicknell, Gregory D. Edgecombe, Katherine Jordan‐Burmeister, John R. Paterson, Shravya Srivastava‐Losey   +9 more
wiley   +1 more source

Beyond Structural Interventions: The Human Architecture Shaping ESG Integration in Corporate Systems

Business Strategy and the Environment, EarlyView.
ABSTRACT Despite the promotion of ESG in corporate discourse, substantive integration of ESG principles into business practices remains challenging. This study applies and extends Meadows' leverage framework to examine ESG integration in UAE‐listed firms.
M. Schulte, Dimitris Christopoulos
wiley   +1 more source

A Posteriori Estimates for Backward SDEs [PDF]

SIAM/ASA Journal on Uncertainty Quantification, 2013
Suppose an approximation to the solution of a backward SDE is precomputed by some numerical algorithm. In this paper we provide a posteriori estimates on the $L^2$-approximation error between true solution and approximate solution. These a posteriori estimates provide upper and lower bounds for the approximation error.
Christian Bender, Jessica Steiner
openaire   +1 more source

Combining vocal tract length normalization with hierarchial linear transformations [PDF]

, 2012
Recent research has demonstrated the effectiveness of vocal tract length normalization (VTLN) as a rapid adaptation technique for statistical parametric speech synthesis.
Dines, John, Saheer, Lakshmi, Garner, P.N., Dines, J., Junichi Yamagishi, Garner, Philip N., Yamagishi, Junichi, Yamagishi, J., John Dines, Lakshmi Saheer, Philip N. Garner, Saheer, L.   +11 more
core   +1 more source

Partial identification with categorical data and nonignorable missing outcomes

Canadian Journal of Statistics, EarlyView.
Abstract Nonignorable missing outcomes are common in real‐world datasets and often require strong parametric assumptions to achieve identification. These assumptions can be implausible or untestable, and so we may wish to forgo them in favour of partially identified models that narrow the set of a priori possible values to an identification region.
Daniel Daly‐Grafstein, Paul Gustafson
wiley   +1 more source

Adaptivity and A Posteriori Error Estimation For DG Methods on Anisotropic Meshes [PDF]

, 2006
Adaptivity and A Posteriori Error Estimation For DG Methods on Anisotropic ...
Hall, Edward, Emmanuil H. Georgoulis (7584863), Georgoulis, Emmanuil H., Paul Houston (400259), Edward Hall (2640643), Houston, Paul   +5 more
core  

An adaptive stabilized finite element method for the generalized Stokes problem [PDF]

, 2007
In this work we present an adaptive strategy (based on an a posteriori error estimator) for a stabilized finite element method for the Stokes problem, with and without a reaction term.
Araya, R., Huang, Pengzhan, Gabriel R. Barrenechea, Araya, Rodolfo, Poza, A., Barrenechea, Gabriel R., Zhang, Qiuyu, Abner Poza, Poza, Abner, Rodolfo Araya, Barrenechea, G.R.   +10 more
core   +1 more source

The Visual Predictive Check and Real‐World Data

Clinical Pharmacology &Therapeutics, EarlyView.
The visual predictive check (VPC) is a standard tool for assessing pharmacometric model suitability, producing visualizations that compare observed data with simulated data such that both model structure and model variability terms can be assessed. However, real‐world data commonly reflect clinical decision‐making that adapts therapy in response to ...
Jasmine H. Hughes, Martin Bergstrand, Ron J. Keizer   +2 more
wiley   +1 more source

Domain‐adapted driving scene understanding with uncertainty‐aware and diversified generative adversarial networks

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua, Jie Sui, Hui Fang, Chuan Hu, Dewei Yi   +4 more
wiley   +1 more source

Clinical Model‐Informed Precision Dosing Consult Service for Accelerating Personalized Medication in Pediatric Patients

Clinical Pharmacology &Therapeutics, EarlyView.
Traditional dosing strategies often rely on a “one‐size‐fits‐all” paradigm, assuming an “average” patient with typical demographic and pharmacological characteristics. In reality, this often overlooks existing between‐patient variability and can lead to suboptimal drug exposure or toxicity. This issue is especially pronounced in pediatric patients, who
Zachary L. Taylor, Takanobu Nadai, Kei Irie, Wen Rui Tan, Sanjana Parikh, Anhar Hosawi, Matthijs W. van Hoogdalem, Ronaldo Morales Junior, Sonya Tang Girdwood, Abbie D. Leino, Kana Mizuno, Alexander A. Vinks, Tomoyuki Mizuno   +12 more
wiley   +1 more source