Results 71 to 80 of about 3,622,028 (257)

Inequalities for Information Potentials and Entropies

open access: yesMathematics, 2020
We consider a probability distribution p0(x),p1(x),… depending on a real parameter x. The associated information potential is S(x):=∑kpk2(x). The Rényi entropy and the Tsallis entropy of order 2 can be expressed as R(x)=−logS(x) and T(x)=1−S(x).
Ana Maria Acu   +3 more
doaj   +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

Tight Lower Bounds for Greedy Routing in Higher-Dimensional Small-World Grids

open access: yes, 2013
We consider Kleinberg's celebrated small world graph model (Kleinberg, 2000), in which a D-dimensional grid {0,...,n-1}^D is augmented with a constant number of additional unidirectional edges leaving each node.
Dietzfelbinger, Martin, Woelfel, Philipp
core   +1 more source

Fault probability identification method for distribution networks based on mov-MF distribution

open access: yesFrontiers in Energy Research
To address the fault identification challenge in distribution networks, a method leveraging a mixture of the von Mises–Fisher (mov-MF) distribution model for fault probability identification is proposed.
Jiang Li, Zhengran Sun, Bo Liu
doaj   +1 more source

Assessment of Riverine Currents to Estimate the Theoretical Hydrokinetic Power and Energy Using Hydraulic Geometry [PDF]

open access: yesJournal of Agricultural Machinery
IntroductionThere are two types of hydropower harvesting methods: conventional and unconventional. In the conventional method, the potential energy of water is harvested using a dam or barrage. However, in the unconventional method, the kinetic energy of
M. Sadeghi-Delooee   +2 more
doaj   +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

Transmuted Lindley-Geometric Distribution and its applications

open access: yes, 2013
A functional composition of the cumulative distribution function of one probability distribution with the inverse cumulative distribution function of another is called the transmutation map.
Elbatal, Ibrahim, Merovci, Faton
core   +1 more source

DAUD: A data driven algorithm to find discrete approximations of unknown continuous distributions

open access: yesSoftwareX
Discrete approximation of continuous probability distributions is applied in solving large-scale intractable stochastic models in engineering, business and economics.
Atiq W. Siddiqui   +2 more
doaj   +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

Estimating Functions of Probability Distributions from a Finite Set of Samples, Part 1: Bayes Estimators and the Shannon Entropy

open access: yes, 1994
We present estimators for entropy and other functions of a discrete probability distribution when the data is a finite sample drawn from that probability distribution. In particular, for the case when the probability distribution is a joint distribution,
Wolf, David R., Wolpert, David H.
core   +1 more source

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