Results 81 to 90 of about 1,693,613 (285)

A comparative analysis of parametric survival models and machine learning methods in breast cancer prognosis

open access: yesScientific Reports
Accurate prediction of breast cancer survival is critical for optimizing treatment strategies and improving clinical outcomes. This study evaluated a combination of parametric statistical models and machine learning algorithms to identify the most ...
Sonia Kaindal, B. Venkataramana
doaj   +1 more source

Probability density function of turbulent velocity fluctuations in rough-wall boundary layer

open access: yes, 2003
The probability density function of single-point velocity fluctuations in turbulence is studied systematically using Fourier coefficients in the energy-containing range.
A. Noullez   +17 more
core   +1 more source

A light‐triggered Time‐Resolved X‐ray Solution Scattering (TR‐XSS) workflow with application to protein conformational dynamics

open access: yesFEBS Open Bio, EarlyView.
Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei   +3 more
wiley   +1 more source

Adaptive Nonparametric Kernel Density Estimation Approach for Joint Probability Density Function Modeling of Multiple Wind Farms

open access: yesEnergies, 2019
The uncertainty of wind power brings many challenges to the operation and control of power systems, especially for the joint operation of multiple wind farms.
Nan Yang   +6 more
doaj   +1 more source

The Luminosity Function of Galaxies as modeled by a left truncated beta distribution

open access: yes, 2014
A first new luminosity functions of galaxies can be built starting from a left truncated beta probability density function, which is characterized by four parameters.
Zaninetti, L.
core   +1 more source

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

open access: yesFEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes   +32 more
wiley   +1 more source

Finite-size scaling in unbiased translocation dynamics

open access: yes, 2014
Finite-size scaling arguments naturally lead us to introduce a coordinate-dependent diffusion coefficient in a Fokker-Planck description of the late stage dynamics of unbiased polymer translocation through a membrane pore.
Baldovin, Fulvio   +3 more
core   +1 more source

Chameleon sequences reveal structural effects in proteins representing micelle‐like distribution of hydrophobicity

open access: yesFEBS Open Bio, EarlyView.
Amino acids sequence of two different proteins with the same sequence (chameleon sequence—black boxes) represent in 3D structure of the proteins different secondary structures: HHHH—helical and BBB—Beta‐structural. The chains folded in water environment adopt different III‐order structures in which the chameleon fragments appear to adopt similar status
Irena Roterman   +4 more
wiley   +1 more source

Large‐scale bidirectional arrayed genetic screens identify OXR1 and EMC4 as modifiers of αSynuclein aggregation

open access: yesFEBS Open Bio, EarlyView.
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane   +11 more
wiley   +1 more source

Probability density functions involving a generalized r–Gauss hypergeometric function

open access: yesLe Matematiche, 2010
The aim of this paper is to study r–generalized gamma functions of a particular form.Moreover, we define a new probability density function (p.d.f) involving these new generalized functions.
Y. Ben Nakhi, S. L. Kalla
doaj  

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