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Christopher R Bodle, Josephine H Schamp, Joseph B O'Brien, Michael P Hayes, Meng Wu, Jonathan A Doorn, David L Roman
Regulator of G protein signaling (RGS) proteins temporally regulate heterotrimeric G protein signaling cascades elicited by G protein-coupled receptor activation and thus are essential for cell homeostasis. The dysregulation of RGS protein expression has been linked to several pathologies, spurring discovery efforts to identify small-molecule inhibitors of these proteins. Presented here are the results of a high-throughput screening (HTS) campaign targeting RGS17, an RGS protein reported to be inappropriately upregulated in several cancers...
January 1, 2018: SLAS Discovery
Yilin Dong, Xinde Li, Yihai Liu
In many applications involving epistemic uncertainties usually modeled by belief functions, it is often necessary to approximate general (non-Bayesian) basic belief assignments (BBAs) to subjective probabilities (called Bayesian BBAs). This necessity occurs if one needs to embed the fusion result in a system based on the probabilistic framework and Bayesian inference (e.g. tracking systems), or if one needs to make a decision in the decision making problems. In this paper, we present a new fast combination method, called modified rigid coarsening (MRC), to obtain the final Bayesian BBAs based on hierarchical decomposition (coarsening) of the frame of discernment...
2018: PloS One
Peter Warneck
The dependences on ionic strength of the hydrolysis constants of Fe3+ and of the first dissociation constant of sulfurous acid are briefly reviewed. The data are needed to derive from apparent stability constants reported in the literature the stability constants for the three iron-sulfito complexes defined by the equilibria (c1) FeOH2+ + HSO3- = FeSO3+ + H2O, (c2) FeSO3+ + HSO3- = Fe(SO3)2- + H+, (c3a) Fe(SO3)2- + HSO3- = Fe(SO3)3H2-, where Kc1 = 1982 ± 518 dm3 mol-1, Kc2 = 0.72 ± 0.08, Kc3a = 189 ± 9 dm3 mol-1 (ionic strength μ = 0...
January 19, 2018: Physical Chemistry Chemical Physics: PCCP
Emmanuelle Cambois, Clémentine Garrouste, Ariane Pailhé
This study investigated the relationship between women's disadvantage in mental health and physical functioning and gender differences in career backgrounds. Sexual division of labor persists and key career characteristics are overrepresented in women: low-skilled first job, downward occupational trajectory, interruptions. These interrelated characteristics are usually linked to poor health. Their overrepresentation in women may be related to the female-male health gap; however, it may not if overrepresentation transposed into substantially weaker associations with poor health outcomes...
December 2017: SSM—Population Health
Wenshuai Yu, Shengjie Zhao, Yongcui Wang, Brian Nlong Zhao, Weiling Zhao, Xiaobo Zhou
The rapid accumulation of cancer-related data owing to high-throughput technologies has provided unprecedented choices to understand the progression of cancer and discover functional networks in multiple cancers. Establishment of co-expression networks will help us to discover the systemic properties of carcinogenesis features and regulatory mechanisms of multiple cancers. Here, we proposed a computational workflow to identify differentially co-expressed gene modules across 8 cancer types by using combined gene differential expression analysis methods and a higher-order generalized singular value decomposition...
December 22, 2017: Oncotarget
Tong Li, Junhui He, Yue Zhang, Lin Yao, Tingting Ren, Binbin Jin
Unprecedented in situ formation of artificial moth-eye structure is demonstrated by spontaneous nano-phase separation of a silica-based system on substrate. The moth-eye thin film with a homogenously distributed nipples array shows broadband antireflection functionalities. The mechanism of nano-phase separation is unveiled as spinodal decomposition by chemical freezing method and thermodynamic analysis. The current method may provide a new avenue to ready fabrication of patterned nanostructures toward a variety of applications...
January 18, 2018: Scientific Reports
Martin Girard, Trung Dac Nguyen, Monica Olvera de la Cruz
Coarse-grained potentials are ubiquitous in mesoscale simulations. While various methods to compute effective interactions for spherically symmetric particles exist, anisotropic interactions are seldom used, due to their complexity. Here we describe a general formulation, based on a spatial decomposition of the density fields around the particles, akin to atomic orbitals. We show that anisotropic potentials can be efficiently computed in numerical simulations using Fourier-based methods. We validate the field formulation and characterize its computational efficiency with a system of colloids that have Gaussian surface charge distributions...
November 2017: Physical Review. E
Horacio V Guzman, Christoph Junghans, Kurt Kremer, Torsten Stuehn
Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls...
November 2017: Physical Review. E
Mathijs F J Vermeulen, Anwesha Bose, Cornelis Storm, Wouter G Ellenbroek
Disordered spring networks that are undercoordinated may abruptly rigidify when sufficient strain is applied. Since the deformation in response to applied strain does not change the generic quantifiers of network architecture, the number of nodes and the number of bonds between them, this rigidity transition must have a geometric origin. Naive, degree-of-freedom-based mechanical analyses such as the Maxwell-Calladine count or the pebble game algorithm overlook such geometric rigidity transitions and offer no means of predicting or characterizing them...
November 2017: Physical Review. E
Mehrez Agnaou, Didier Lasseux, Azita Ahmadi
Inertial flow in porous media occurs in many situations of practical relevance among which one can cite flows in column reactors, in filters, in aquifers, or near wells for hydrocarbon recovery. It is characterized by a deviation from Darcy's law that leads to a nonlinear relationship between the pressure drop and the filtration velocity. In this work, this deviation, also known as the nonlinear, inertial, correction to Darcy's law, which is subject to controversy upon its origin and dependence on the filtration velocity, is studied through numerical simulations...
October 2017: Physical Review. E
Tameem Albash, Gene Wagenbreth, Itay Hen
We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a decomposition of the quantum partition function that can be viewed as a series expansion about its classical part. We argue that the algorithm not only provides a theoretical advancement in the field of quantum Monte Carlo simulations, but is optimally suited to tackle quantum many-body systems that exhibit a range of behaviors from "fully quantum" to "fully classical," in contrast to many existing methods...
December 2017: Physical Review. E
S S Melnik, O V Usatenko
The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order). This allows us to introduce a family of Markov chain models and to construct artificial sequences via a method of successive iterations, taking into account at each step increasingly high correlations among random elements...
July 2017: Physical Review. E
G Torres-Vargas, R Fossion, C Tapia-Ignacio, J C López-Vieyra
We apply the singular value decomposition (SVD) method, based on normal-mode analysis, to decompose the spectra of finite random matrices of standard Gaussian ensembles in trend and fluctuation modes. We use the fact that the fluctuation modes are scale invariant and follow a power law, to characterize the transition between the extreme regular and chaotic cases. Thereby, we quantify the quantum chaos in systems described by random matrix theory in a direct way, without performing any previous unfolding procedure, and therefore, avoiding possible artifacts...
July 2017: Physical Review. E
Giulio G Giusteri, Filippo Recrosi, Gernot Schaller, G Luca Celardo
We analyze an open quantum system under the influence of more than one environment: a dephasing bath and a probability-absorbing bath that represents a decay channel, as encountered in many models of quantum networks. In our case, dephasing is modeled by random fluctuations of the site energies, while the absorbing bath is modeled with an external lead attached to the system. We analyze under which conditions the effects of the two baths can enter additively the quantum master equation. When such additivity is legitimate, the reduced master equation corresponds to the evolution generated by an effective non-Hermitian Hamiltonian and a Haken-Strobl dephasing super-operator...
July 2017: Physical Review. E
Paul Expert, Sarah de Nigris, Taro Takaguchi, Renaud Lambiotte
There is recent evidence that the XY spin model on complex networks can display three different macroscopic states in response to the topology of the network underpinning the interactions of the spins. In this work we present a way to characterize the macroscopic states of the XY spin model based on the spectral decomposition of time series using topological information about the underlying networks. We use three different classes of networks to generate time series of the spins for the three possible macroscopic states...
July 2017: Physical Review. E
Berend Christopher Rinderspacher, Jaydeep P Bardhan, Ahmed E Ismail
We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions...
July 2017: Physical Review. E
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
The analysis of nonlinear dynamical systems based on the Koopman operator is attracting attention in various applications. Dynamic mode decomposition (DMD) is a data-driven algorithm for Koopman spectral analysis, and several variants with a wide range of applications have been proposed. However, popular implementations of DMD suffer from observation noise on random dynamical systems and generate inaccurate estimation of the spectra of the stochastic Koopman operator. In this paper, we propose subspace DMD as an algorithm for the Koopman analysis of random dynamical systems with observation noise...
September 2017: Physical Review. E
Michael M Cândido, Welles A M Morgado, Sílvio M Duarte Queirós
We analyze a model describing an anharmonic macroscopic chain in contact with general reservoirs that follow the Lévy-Itô theorem on the Gaussian-Poissonian decomposition of the measure. We do so by considering a perturbative approach to compute the heat flux and the (canonical) temperature profile when the system reaches the steady state. This approach allows observing a macroscopic violation of the law of the heat conduction equivalent to that found for small (N=2) systems in contact with general reservoirs, which conveys the ascendency of the nature of the reservoirs over the size of the system...
September 2017: Physical Review. E
Adrien Deliège, Samuel Nicolay
This paper consists in the description and application of a method called wavelet-induced mode extraction (WIME) in the context of time-frequency analysis. WIME aims to extract the oscillating components that build amplitude modulated-frequency modulated signals. The essence of this technique relies on the successive extractions of the dominant ridges of wavelet-based time-frequency representations of the signal under consideration. Our tests on simulated examples indicate strong decomposition and reconstruction skills, trouble-free handling of crossing trajectories in the time-frequency plane, sharp performances in frequency detection in the case of mode-mixing problems, and a natural tolerance to noise...
September 2017: Physical Review. E
Inês Campos-Matos, Giuliano Russo, Luzia Gonçalves
Background: We explore how health inequalities (HI) changed in Portugal over the last decade, considering it is one of the most unequal European countries and has gone through major economic changes. We describe how inequalities in limitations changed considering different socioeconomic determinants, in order to understand what drove changes in HI. Methods: We used cross-sectional waves from the European Survey on Income and Living Conditions database to determine how inequalities in health limitations changed between 2004 and 2014 in Portugal in residents aged 16 years and over...
February 1, 2018: European Journal of Public Health
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