Results 91 to 100 of about 128,325 (262)
ABSTRACT This study examines the environmental, social and governance (ESG) scoring methodologies used by Bloomberg and S&P Global through the lens of Data Envelopment Analysis (DEA). It addresses a notable gap in the literature by identifying the underlying factors that shape ESG scores and providing practical insights for companies seeking to ...
Philipe Balan +4 more
wiley +1 more source
Con el fin de clasificar la corrosividad de las diferentes atmósferas colombianas, como parte de un proyecto de investigación extenso [1], se expusieron placas de acero al carbono en 21 estaciones distribuidas a lo largo de la infraestructura eléctrica ...
Esteban Velilla +2 more
doaj
A note on the singular value decomposition of (skew-)involutory and (skew-)coninvolutory matrices
The singular values $\sigma >1$ of an $n \times n$ involutory matrix $A$ appear in pairs $(\sigma, \frac{1}{\sigma}),$ while the singular values $\sigma = 1$ may appear in pairs $(1,1)$ or by themselves.
Faßbender, Heike, Halwaß, Martin
core +1 more source
Synopsis Imbalance in the GH‐IGF‐1 axis may restrict fetal growth and development, thereby increasing the risk of future metabolic diseases. Abstract Objective To ascertain the association between small for gestational age (SGA) and growth hormone (GH)‐insulin‐like growth factor (IGF) system status.
Jing Wen +3 more
wiley +1 more source
Computing feature matrices using PCA-SVD hybrid method on small-scale systems
The task of performing feature extraction from input matrices is a well-known problem in biometric recognition. This paper aims to develop an effective method for reduction and decomposition on large matrices with low required computational resources and
Le Tien Hung +3 more
doaj +1 more source
ABSTRACT Background Vascular cognitive impairment and dementia (VCID) is the second leading cause of dementia. Cerebrovascular reactivity (CVR) is a promising biomarker for VCID. However, CVR is not commonly measured in clinical practice due to logistical difficulties in applying a hypercapnia challenge during MR imaging. Purpose To investigate whether
Fariba Badrzadeh +5 more
wiley +1 more source
Probabilistic matrix clustering with feature priors for unbiased control selection
We propose a probabilistic matrix-clustering method that leverages a prior distribution of features and dimensionality reduction (Singular Value Decomposition, SVD). The approach identifies, within a large control pool, a cluster statistically comparable
D. A. Usoltsev
doaj +1 more source
Cardiac MR Fingerprinting at 0.55T Using a Deep Image Prior for Joint T1, T2, and M0 Mapping
ABSTRACT Background 0.55T systems offer unique advantages and may support expanded access to cardiac MRI. Purpose To assess the feasibility of 0.55T cardiac MR Fingerprinting (MRF), leveraging a deep image prior reconstruction to mitigate noise. Study Type Phantom and prospective in vivo assessment.
Zhongnan Liu +9 more
wiley +1 more source
BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines
A tissue phantom, containing fingerprint Raman spectra at each pixel, is developed to evaluate Raman signal processing pipelines. The phantom is created from a BCARS image of a murine hepatic tissue. ABSTRACT Broadband coherent anti‐Stokes Raman scattering (BCARS) microscopy is a powerful label‐free biological imaging technique, but the raw signal ...
Jessica Z. Dixon +5 more
wiley +1 more source
A new SVD approach to optimal topic estimation
In the probabilistic topic models, the quantity of interest---a low-rank matrix consisting of topic vectors---is hidden in the text corpus matrix, masked by noise, and Singular Value Decomposition (SVD) is a potentially useful tool for learning such a ...
Ke, Zheng Tracy, Wang, Minzhe
core

