Results 91 to 100 of about 1,526,545 (357)
Eigenvalue-based Detection Techniques Using Finite Dimensional Complex Random Matrix Theory: A Review [PDF]
Detection of primary users without requiring information of signal is of great importance in spectrum sensing (SS) in Cognitive Radio. Therefore, in recent years, eigenvalue based spectrum sensing algorithms are under the spotlight.
Ayse Kortun
doaj +1 more source
Human cytomegalovirus infection is common in normal prostate epithelium, prostate tumor tissue, and prostate cancer cell lines. CMV promotes cell survival, proliferation, and androgen receptor signaling. Anti‐CMV pharmaceutical compounds in clinical use inhibited cell expansion in prostate cancer models in vitro and in vivo, motivating investigation ...
Johanna Classon+13 more
wiley +1 more source
Random matrix theory and the zeros of (s) [PDF]
We study the density of the roots of the derivative of the characteristic polynomial Z(U,z) of an N x N random unitary matrix with distribution given by Haar measure on the unitary group. Based on previous random matrix theory models of the Riemann zeta function zeta(s), this is expected to be an accurate description for the horizontal distribution of ...
openaire +5 more sources
Random matrix theory and symmetric spaces [PDF]
In this review we discuss the relationship between random matrix theories and symmetric spaces. We show that the integration manifolds of random matrix theories, the eigenvalue distribution, and the Dyson and boundary indices characterizing the ensembles are in strict correspondence with symmetric spaces and the intrinsic characteristics of their ...
CASELLE, Michele, ULRIKA MAGNEA
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We present a gravitational theory that interpolates between JT gravity, and a gravity theory with a fixed boundary Hamiltonian. For this, we consider a matrix integral with the insertion of a Gaussian with variance $\sigma^2$, centered around a matrix
Andreas Blommaert, Jorrit Kruthoff
doaj +1 more source
RKIP, a metastasis suppressor protein, modulates key oncogenic pathways in lung adenocarcinoma. In silico analyses linked low RKIP expression to poor survival. Functional studies revealed RKIP overexpression reduces tumor aggressiveness and enhances sensitivity to EGFR‐targeted therapies, while its loss promotes resistance.
Ana Raquel‐Cunha+10 more
wiley +1 more source
Large-$N_c$ gauge theory and chiral random matrix theory
We discuss how the $1/N_c$ expansion and the chiral random matrix theory ($\chi$RMT) can be used in the study of large-$N_c$ gauge theories. We first clarify the parameter region in which each of these two approaches is valid: while the fermion mass $m ...
Hanada, Masanori+2 more
core +1 more source
Vibrations in glasses and Euclidean Random Matrix theory [PDF]
We study numerically and analytically a simple off-lattice model of scalar harmonic vibrations by means of Euclidean random matrix theory. Since the spectrum of this model shares the most puzzling spectral features with the high-frequency domain of ...
Grigera, T. S.+3 more
core +3 more sources
Asymptotic Analysis of Large Cooperative Relay Networks Using Random Matrix Theory
Cooperative transmission is an emerging communication technology that takes advantage of the broadcast nature of wireless channels. In cooperative transmission, the use of relays can create a virtual antenna array so that multiple-input/multiple-output ...
H. Poor, Z. Han, Husheng Li
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Single‐cell transcriptomics of prostate cancer patient‐derived xenografts reveals distinct features of neuroendocrine (NE) subtypes. Tumours with focal NE differentiation (NED) share transcriptional programmes with adenocarcinoma, differing from large and small cell neuroendocrine prostate cancer (NEPC). Our work defines the molecular landscape of NEPC,
Rosalia Quezada Urban+12 more
wiley +1 more source