Results 61 to 70 of about 9,772 (283)
Diffusion State Distances: Multitemporal Analysis, Fast Algorithms, and Applications to Biological Networks [PDF]
arXiv, 2020 Data-dependent metrics are powerful tools for learning the underlying structure of high-dimensional data. This article develops and analyzes a data-dependent metric known as diffusion state distance (DSD), which compares points using a data-driven diffusion process.
arxiv
Operationalizing Digital Self Determination [PDF]
arXiv, 2022 We live in an era of datafication, one in which life is increasingly quantified and transformed into intelligence for private or public benefit. When used responsibly, this offers new opportunities for public good. However, three key forms of asymmetry currently limit this potential, especially for already vulnerable and marginalized groups: data ...
arxiv
Enhancing the performance of an in vitro RNA biosensor through iterative design of experiments
Biotechnology Progress, EarlyView.Abstract The quality control of RNA has become increasingly crucial with the rise of mRNA‐based vaccines and therapeutics. However, conventional methods such as LC–MS often require specialized equipment and expertise, limiting their applicability to high throughput experiments.
Rochelle Aw, Karen Polizzi
wiley +1 more source
A Survey of Densest Subgraph Discovery on Large Graphs [PDF]
arXiv, 2023 With the prevalence of graphs for modeling complex relationships among objects, the topic of graph mining has attracted a great deal of attention from both academic and industrial communities in recent years. As one of the most fundamental problems in graph mining, the densest subgraph discovery (DSD) problem has found a wide spectrum of real ...
arxiv
Physicochemical, Morphological, and Digestibility Properties of Round and Wrinkled Pea Starches
Cereal Chemistry, EarlyView.ABSTRACT Background and Objectives Pea protein isolation results in a significant amount of starch‐rich byproduct. Efficient utilization of this byproduct can be crucial for economic feasibility of protein isolation process. In this study, we examined the physicochemical, morphological, and digestibility properties of starches derived from round and ...
Sintayehu D. Daba +2 more
wiley +1 more source
DSD: Dense-Sparse-Dense Training for Deep Neural Networks [PDF]
arXiv, 2016 Modern deep neural networks have a large number of parameters, making them very hard to train. We propose DSD, a dense-sparse-dense training flow, for regularizing deep neural networks and achieving better optimization performance. In the first D (Dense) step, we train a dense network to learn connection weights and importance.
arxiv
Sexuality in Adults with Differences/Disorders of Sex Development (DSD): Findings from the dsd-LIFE Study [PDF]
Journal of Sex & Marital Therapy, 2019 For various reasons, sexuality of individuals with differences/disorders of sex development (DSD) may be affected. The aim of the study was to describe sexual activity, satisfaction with sex life, satisfaction with genital function, and sexual problems in people with different DSD conditions. Data were collected from 1,040 participants in Europe.
Kreukels, Baudewijntje P. C. +21 more
openaire +3 more sources
Dense Coconut Oil‐in‐Water (CO‐Water) Emulsification via a Vortex‐Based Cavitation Device
Chemical Engineering &Technology, EarlyView.This study investigates the emulsification of coconut oil‐in‐water (CO‐water) emulsions using a vortex‐based hydrodynamic cavitation (HC) device. The present study explores the influence of dispersed phase on produced O/W emulsions without changing the surfactant type and concentration.
Mukesh Upadhyay, Vivek V. Ranade
wiley +1 more source
Disorders of sex development: timing of diagnosis and management in a single large tertiary center
Endocrine Connections, 2018 Background: We describe the phenotypic spectrum and timing of diagnosis and management in a large series of patients with disorders of sexual development (DSD) treated in a single pediatric tertiary center.
E Kohva +5 more
doaj +1 more source
Computing Diffusion State Distance using Green's Function and Heat Kernel on Graphs [PDF]
arXiv, 2014 The diffusion state distance (DSD) was introduced by Cao-Zhang-Park-Daniels-Crovella-Cowen-Hescott [{\em PLoS ONE, 2013}] to capture functional similarity in protein-protein interaction networks. They proved the convergence of DSD for non-bipartite graphs.
arxiv