Results 71 to 80 of about 3,643,927 (240)

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

Frontiers 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]

Journal 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, R. Alimardani, H. Mousazadeh   +2 more
doaj   +1 more source

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

FEBS 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, Fredrik Orädd, Konstantinos Magkakis, Magnus Andersson   +3 more
wiley   +1 more source

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

SoftwareX
Discrete approximation of continuous probability distributions is applied in solving large-scale intractable stochastic models in engineering, business and economics.
Atiq W. Siddiqui, Manish Verma, Syed Arshad Raza   +2 more
doaj   +1 more source

Probability Thermodynamics and Probability Quantum Field

, 2019
In this paper, we introduce probability thermodynamics and probability quantum fields. By probability we mean that there is an unknown operator, physical or nonphysical, whose eigenvalues obey a certain statistical distribution. Eigenvalue spectra define
Dai, Wu-Sheng, Li, Wen-Du, Liu, Tong, Zhang, Ping   +3 more
core  

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

FEBS 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, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

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

, 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

Work probability distribution and tossing a biased coin

, 2010
We show that the rare events present in dissipated work that enters Jarzynski equality, when mapped appropriately to the phenomenon of large deviations found in a biased coin toss, are enough to yield a quantitative work probability distribution for ...
A. Dembo, Arnab Saha, D. M. Carberry, H. Cramer, Jayanta K. Bhattacharjee, M. Kardar, S. R. S. Varadhan, Sagar Chakraborty, W. Feller   +8 more
core   +1 more source

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

FEBS 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, Katarzyna Stapor, Leszek Konieczny, Krzysztof Gądek, Piotr Nowakowski   +4 more
wiley   +1 more source

Determination of Maximum Bayesian Entropy Probability Distribution [PDF]

Journal of Sciences, Islamic Republic of Iran, 2005
In this paper, we consider the determination methods of maximum entropy multivariate distributions with given prior under the constraints, that the marginal distributions or the marginals and covariance matrix are prescribed.
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