Results 111 to 120 of about 3,493,044 (354)

Vector space of linearizations for the quadratic two-parameter matrix polynomial [PDF]

arXiv, 2012
Given a quadratic two-parameter matrix polynomial Q, we develop a systematic approach to generating a vector space of linear two-parameter matrix polynomials. We identify a set of linearizations of Q that lie in the vector space. Finally, we determine a class of linearizations for a quadratic two- parameter eigenvalue problem.
arxiv  

Mapping Hsp104 interactions using cross‐linking mass spectrometry

FEBS Open Bio, EarlyView.
This study examines how cross‐linking mass spectrometry can be utilized to analyze ATP‐induced conformational changes in Hsp104 and its interactions with substrates. We developed an analytical pipeline to distinguish between intra‐ and inter‐subunit contacts within the hexameric homo‐oligomer and discovered contacts between Hsp104 and a selected ...
Kinga Westphal, Karolina Michalska, Andrzej Joachimiak, Lukasz A. Joachimiak   +3 more
wiley   +1 more source

Spherical Contours, IR Divergences and the geometry of Feynman parameter integrands at one loop [PDF]

arXiv, 2019
Spherical contours introduced in \cite{SphericalContours} translate the concept of "discontinuity across a branch cut" to Feynman parameter space. In this paper, we further explore spherical contours and connect them to the computation of leading IR divergences of 1 loop graphs directly in Feynman parameter space.
arxiv  

Constraining the Two-Higgs-Doublet-Model parameter space

, 2007
We confront the Two-Higgs-Doublet Model with a variety of experimental constraints as well as theoretical consistency conditions. The most constraining data are the \bar B\to X_s\gamma decay rate (at low values of M_{H^\pm}), and \Delta\rho (at both low ...
A. J. Buras, A. W. El Kaffas, Abdul Wahab El Kaffas, C. Q. Geng, J. F. Gunion, M. Bona, M. Ciuchini, M. Misiak, Odd Magne Ogreid, Per Osland, R. Grigjanis, S. Schael, S. M. Barr, T. Inami, W. Khater   +14 more
core   +1 more source

Bioengineering facets of the tumor microenvironment in 3D tumor models: insights into cellular, biophysical and biochemical interactions

FEBS Open Bio, EarlyView.
The tumor microenvironment is a dynamic, multifaceted complex system of interdependent cellular, biochemical, and biophysical components. Three‐dimensional in vitro models of the tumor microenvironment enable a better understanding of these interactions and their impact on cancer progression and therapeutic resistance.
Salma T. Rafik, Deniz Bakkalci, Alexander J. MacRobert, Umber Cheema   +3 more
wiley   +1 more source

Running into New Territory in SUSY Parameter Space

, 2004
The LEP-II bound on the light Higgs mass rules out the vast majority of parameter space left to the Minimal Supersymmetric Standard Model (MSSM) with weak-scale soft-masses.
A. Bartl, A. Finch, A.C. Bawa, Antonio Delgado, D. Cavalli ., D.E. Kaplan, David E Kaplan, E.L. Berger, E.L. Berger, G.D. Kribs, H.E. Haber, H.E. Haber, H.J. He, Higgs Working Group collaboration, J.A. Casas, J.F. Gunion, J.L. Hewett, J.R. Ellis, K.S. Babu, LEP Higgs Working group, LEP Higgs Working Group collaboration, M. Beneke ., M. Cvetic, M. Drees, P. Batra, Puneet Batra, Q.H. Cao, R. Harnik, R.S. Chivukula, S.P. Martin, Tim M.P Tait, U. Ellwanger, Y. Okada, Z. Chacko, Z. Sullivan   +34 more
core   +2 more sources

Matrigel inhibits elongation and drives endoderm differentiation in aggregates of mouse embryonic stem cells

FEBS Open Bio, EarlyView.
Stem cell‐based embryo models (SCBEMs) are valuable to study early developmental milestones. Matrigel, a basement membrane matrix, is a critical substrate used in various SCBEM protocols, but its role in driving stem cell lineage commitment is not clearly defined.
Atoosa Amel, Rachel Brown, Alexa Rabeling, Mubeen Goolam   +3 more
wiley   +1 more source

Reducing parameter space for neural network training

Theoretical and Applied Mechanics Letters, 2020
: For neural networks (NNs) with rectified linear unit (ReLU) or binary activation functions, we show that their training can be accomplished in a reduced parameter space.
Tong Qin, Ling Zhou, Dongbin Xiu
doaj  

Scalar phenomenology in type-II seesaw model

Journal of High Energy Physics, 2019
In this work we study the viable parameter space of the scalar sector in the type-II seesaw model. In identifying the allowed parameter space, we employ constraints from low energy precision measurements, theoretical considerations and the 125-GeV Higgs ...
R. Primulando, J. Julio, P. Uttayarat
doaj   +1 more source

Mixture Models: Building a Parameter Space [PDF]

arXiv, 2015
Despite the flexibility and popularity of mixture models, their associated parameter spaces are often difficult to represent due to fundamental identification problems. This paper looks at a novel way of representing such a space for general mixtures of exponential families, where the parameters are identifiable, interpretable, and, due to a tractable ...
arxiv