Function Perturbation Research Articles

Function Perturbation Impact on Robust Stability and Stabilization of Boolean Networks With Disturbances

Function Perturbation Impact on Robust Stability and Stabilization of Boolean Networks With Disturbances

Robust Weak Detectability Analysis of Boolean Networks Subject to Function Perturbation

As a class of state estimation issues, detectability is widely used in fault diagnosis, circuit design, and disease status detection. This brief analyzes the robust weak detectability of Boolean networks (BNs) under function perturbation. A simplified parallel system is constructed for BNs. Based on the transition of state pairs in the simplified parallel system, a new criterion is proposed for the weak detectability of BNs. Using the reachability from perturbed state pairs to attractors in indistinguishable pairs, the robust weak detectability of BNs subject to function perturbation is analyzed. A practical example of p53-MDM2 negative feedback regulatory loop is used to illustrate the obtained criteria.

Differentially private distributed logistic regression with the objective function perturbation

Distributed learning is a very effective divide-and-conquer strategy for dealing with big data. As distributed learning algorithms become more and more mature, network security issues including the risk of privacy disclosure of personal sensitive data, have attracted high attention and vigilance. Differentially private is an important method that maximizes the accuracy of a data query while minimizing the chance of identifying its records when querying from the given data. The known differentially private distributed learning algorithms are based on variable perturbation, but the variable perturbation method may be non-convergence and the experimental results usually have large deviations. Therefore, in this paper, we consider differentially private distributed learning algorithm based on objective function perturbation. We first propose a new distributed logistic regression algorithm based on objective function perturbation (DLR-OFP). We prove that the proposed DLR-OFP satisfies differentially private, and obtain its fast convergence rate by introducing a new acceleration factor for the gradient descent method. The numerical experiments based on benchmark data show that the proposed DLR-OFP algorithm has fast convergence rate and better privacy protection ability.

Robust Stabilization of Impulsive Boolean Control Networks with Function Perturbation

This paper studies the robust stabilization of impulsive Boolean control networks (IBCNs) with function perturbation. A Boolean control network (BCN) with a state-dependent impulsive sequence is converted to an equivalent BCN by the semi-tensor product method. Based on the equivalence of stabilization between the IBCN and the corresponding BCN, several criteria are proposed for the robust stabilization of IBCNs. Furthermore, when the IBCN is not robustly stabilizable after the function perturbation, an algorithm is presented to modify the control or the impulse-triggered set. Finally, an example is given to verify the obtained results.

Erratum: Wannier Function Perturbation Theory: Localized Representation and Interpolation of Wave Function Perturbation [Phys. Rev. X 11 , 041053 (2021)

Erratum: Wannier Function Perturbation Theory: Localized Representation and Interpolation of Wave Function Perturbation [Phys. Rev. X <b>11</b> , 041053 (2021)

A hybrid ensemble feature selection design for candidate biomarkers discovery from transcriptome profiles

Discovering disease biomarkers from gene expression data has been greatly advanced by feature selection (FS) methods, especially using ensemble FS (EFS) strategies with perturbation at the data (i.e., homogeneous EFS) or method level (i.e., heterogeneous EFS). Here, we proposed a hybrid EFS design that explores both types of perturbation to disrupt associations of good performance with a single dataset, single algorithm, or a specific combination of both, which is particularly interesting for better reproducibility of genomic biomarkers. We investigated the adequacy of our approach for microarray data in four types of cancer, extensively comparing it with other ensemble and single FS approaches. Five FS algorithms were analyzed: Wx, Symmetrical Uncertainty, Gain Ratio, Characteristic Direction, and ReliefF. We observed that, across distinct datasets, the hybrid and heterogeneous approaches attenuated the large performance variation of most methods without function perturbation. Additionally, the proposed hybrid EFS has superior performance to the heterogeneous EFS. Interestingly, the ranks produced by our method reached greater biological plausibility, with a notably high enrichment for cancer-related genes and pathways. Thus, our experiments suggest the potential of the proposed hybrid EFS design for discovering candidate biomarkers from microarray data. Finally, we provide an open-source framework to support similar analyses in this and other domains, being available as a user-friendly application and a programmable Python package.

Neutral Mode Dominates the Forced Global and Regional Surface Temperature Response in the Past and Future

AbstractUsing a large suite of Green's function perturbation experiments, we construct the emergent dynamical operator for surface temperature and extract the most excitable mode. The leading mode turns out to be the most dominant mode excited by the climate forcing of doubling CO2, alone capturing 56% of the total spatial variances of the surface temperature response. The pattern of the leading mode is partly organized by the atmospheric annular modes in both hemispheres, and further modulated by the feedbacks from ocean circulations. Though derived from a single model, the leading mode can capture the spatio‐temporal variabilities of the global mean surface temperature over the past century in both the CMIP6 model simulations and observations. Moreover, the leading mode is most efficiently excited by radiative forcings from the midlatitude bands centered around 45°N and 25°S, where most human activities take place, suggesting the potency of human influence on the climate change.

Comparison of flame response characteristics between Non‐premixed and premixed flames under acoustic excitation

A comparative study was conducted on the response characteristics according to the increase in velocity perturbation intensity (u'/u) under acoustic excitation conditions of non-premixed and premixed flames. In addition, the flame dynamic characteristics and flame structure according to acoustic excitation were analyzed, and the response characteristics were compared according to the two flame types through the flame transfer function (FTF) and flame height perturbation analysis. In a non-premixed flame, the number of waveforms (undulations) on the flame surface increased according to the forcing frequency in the flame structure according to the acoustic excitation. On the other hand, as the velocity perturbation intensity increased, the flame height decreased. Thus, in the low forcing frequency range, the magnitude of the flame fluctuation increases, and in the high forcing frequency, the magnitude of the flame fluctuation tends to decrease. Therefore, the Strouhal number and FTF gain are nonlinear properties, and the nonlinear effect depends on the magnitude of the gain and the critical Strouhal number. In a premixed flame, various flame structures are shown according to acoustic excitation. The average flame height does not change much with increasing (u'/u¯). The correlation between the Strouhal number and FTF gain is linear. The flame height perturbation parameters were introduced to examine the flame dynamic characteristics according to the acoustic excitation, and non-premixed and premixed flames were analyzed. As a result, it shows the trend and similarity of the FTF gain, suggesting its potential as a parameter for simple analysis of the heat-release rate. In the correlation between the Strouhal number and FTF gain, the non-premixed flame has a nonlinear characteristic and agrees with the analytical study. On the other hand, the premixed flame is not consistent with analytic studies when the Strouhal number is greater than 1. The reason for various flame structures is to consider parameters such as the unusual flame structure and laminar flame speed by external perturbation.

Robust stability of Switched Boolean Networks with function perturbation

In genetic regulatory networks, gene mutations are one of natural phenomena, which attract much attention by biological researchers. In modeling gene networks using switched Boolean networks (SBNs), gene mutations can be described by function perturbations, which is a meaningful issue in analyzing function perturbation of SBNs. This paper studies robust stability of SBNs with function perturbation. With the help of semi-tensor product (STP) of matrices, one equivalent algebraic form of SBNs is established. By constructing two state sets, a criterion for global stability of SBNs under arbitrary switching signals is proposed. In order to relax the conditions of global stability, pointwise stabilizability and consistent stabilizability of SBNs are further considered. Based on state reachable sets, several criteria are established for the proposed kinds of stability. Finally, the obtained results are verified by two examples and lac operon in the Escherichia coli, respectively.

Mitochondria-Related Apoptosis Regulation by Minocycline: A Study on a Transgenic Drosophila Model of Alzheimer's Disease.

Alzheimer’s disease (AD) is a very complicated and multifactorial neurological disorder having limited therapeutic interventions illustrated by the impairment in memory and cognitive function. Several lines of confirmation are stoutly connected with mitochondrial function perturbation as a significant causative factor in AD, while the molecular mechanisms involved in AD pathogenesis are still poorly understood. Minocycline, a well-known antibiotic, has confirmed efficacy against mitochondrial defects and oxidative stress as a neuroprotective effect. In view of this property, we examined the remedial effect of minocycline on AD. To attain insight into the molecular machinery responsible for AD pathogenesis, we preferred the UAS/GAL4 scheme for the development of AD in flies that overexpress the Aβ42 protein in the brain of Drosophila. The warning signs like the declined lifespan, locomotion deficit and memory loss, impaired mitochondrial membrane potential, and increased caspase 3 expression with mitogen-associated protein kinases linked with AD pathogenesis were examined in the existence of minocycline. Minocycline halted the Aβ42-induced symptoms including behavioral changes and altered the mitochondrial membrane potential along with apoptotic factors’ protein expression (JNK/p-JNK and caspase 3). Thus, the current study could be functional to find out the role of minocycline in human Aβ42-overexpressed transgenic AD flies.

Unusual SMG suspects recruit degradation enzymes in nonsense-mediated mRNA decay.

Degradation of eukaryotic RNAs that contain premature termination codons (PTC) during nonsense-mediated mRNA decay (NMD) is initiated by RNA decapping or endonucleolytic cleavage driven by conserved factors. Models for NMD mechanisms, including recognition of PTCs or the timing and role of protein phosphorylation for RNA degradation are challenged by new results. For example, the depletion of the SMG5/7 heterodimer, thought to activate RNA degradation by decapping, leads to a phenotype showing a defect of endonucleolytic activity of NMD complexes. This phenotype is not correlated to a decreased binding of the endonuclease SMG6 with the core NMD factor UPF1, suggesting that it is the result of an imbalance between active (e.g., in polysomes) and inactive (e.g., in RNA-protein condensates) states of NMD complexes. Such imbalance between multiple complexes is not restricted to NMD and should be taken into account when establishing causal links between gene function perturbation and observed phenotypes.

Cluster Synchronization of Boolean Networks Under Probabilistic Function Perturbation

In practical gene regulatory networks, gene expression is often accompanied by stochastic gene mutation. This brief investigates the cluster synchronization problem of Boolean networks (BNs) and Boolean control networks (BCNs) under probabilistic function perturbation, which can better characterize stochastic gene mutation and explore internal synchronization mechanism of the system. By transforming BN into an equivalent stochastic logical system, the algebraic expression of BN (BCN) under probabilistic function perturbation is derived. Then, necessary and sufficient conditions are provided so as to distinguish whether systems can achieve cluster synchronization with probability one under probabilistic function perturbation. Corresponding state feedback controllers are designed as well. The effectiveness is demonstrated by numerical examples.

Ensemble Variable Selection for Naive Bayes to Improve Customer Behaviour Analysis

Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner. Further investigation of customer patterns helps the firm to develop efficient decisions and in turn, helps to optimize the enterprise’s business and maximizes consumer satisfaction correspondingly. To conduct an effective assessment about the customers, Naive Bayes(also called Simple Bayes), a machine learning model is utilized. However, the efficacious of the simple Bayes model is utterly relying on the consumer data used, and the existence of uncertain and redundant attributes in the consumer data enables the simple Bayes model to attain the worst prediction in consumer data because of its presumption regarding the attributes applied. However, in practice, the NB premise is not true in consumer data, and the analysis of these redundant attributes enables simple Bayes model to get poor prediction results. In this work, an ensemble attribute selection methodology is performed to overcome the problem with consumer data and to pick a steady uncorrelated attribute set to model with the NB classifier. In ensemble variable selection, two different strategies are applied: one is based upon data perturbation (or homogeneous ensemble, same feature selector is applied to a different subsamples derived from the same learning set) and the other one is based upon function perturbation (or heterogeneous ensemble different feature selector is utilized to the same learning set). Furthermore, the feature set captured from both ensemble strategies is applied to NB individually and the outcome obtained is computed. Finally, the experimental outcomes show that the proposed ensemble strategies perform efficiently in choosing a steady attribute set and increasing NB classification performance efficiently.

Seismic Characterization of Decoupled Orthorhombic Fractures Based on Observed Surface Azimuthal Amplitude Data

Commonly-used seismic fracture characterization method assumes one single fracture set, and this article aims to relax the limitation and demonstrate the feasibility of seismic characterization for two sets of orthorhombic fractures. Elastic properties of orthorhombic fractures can be studied using a model of horizontal and vertical fractures as linear-slip interfaces embedded in an isotropic background. High fracture density in hydrocarbon reservoirs is the “sweet spot” of effective permeability for fluid flow, and seismic characterization of orthorhombic fractures using the variations in reflection amplitude versus offset and azimuth (AVOAz) helps to optimize the production of naturally fractured reservoirs. Based on an effective orthorhombic linear-slip model, we first construct the effective elastic stiffness matrix in terms of elastic moduli and decoupled horizontal and vertical fracture densities under the assumption of weak anisotropy (WA) or small fracture densities. Using the scattering function and first-order perturbation in effective elastic stiffness components, we derive a WA and linearized PP-wave reflection coefficient containing decoupled orthorhombic fracture densities to describe the characteristics of horizontal and vertical fracture sets. We then propose an efficient AVOAz inversion method to perform the seismic characterization of decoupled orthorhombic fracture densities based on observed surface azimuthal amplitude data in a Bayesian framework. We finally apply the inversion approach to synthetic and field datasets to demonstrate its feasibility and reasonability in orthorhombic fracture characterization.

Determining the global threshold of an epidemic model with general interference function and high-order perturbation

&lt;abstract&gt;&lt;p&gt;This research provides an improved theoretical framework of the Kermack-McKendrick system. By considering the general interference function and the polynomial perturbation, we give the sharp threshold between two situations: the disappearance of the illness and the ergodicity of the higher-order perturbed system. Obviously, the ergodic characteristic indicates the continuation of the infection in the population over time. Our study upgrades and enhances the work of Zhou et al. (2021) and suggests a new path of research that will serve as a basis for future investigations. As an illustrative application, we discuss some special cases of the polynomial perturbation to examine the precision of our outcomes. We deduce that higher order fluctuations positively affect the illness extinction time and lead to its rapid disappearance.&lt;/p&gt;&lt;/abstract&gt;

ADG: automated generation and evaluation of many-body diagrams

The goal of the present paper is twofold. First, a novel expansion many-body method applicable to superfluid open-shell nuclei, the so-called Bogoliubov in-medium similarity renormalization group (BIMSRG) theory, is formulated. This generalization of standard single-reference IMSRG theory for closed-shell systems parallels the recent extensions of coupled cluster, self-consistent Green’s function or many-body perturbation theory. Within the realm of IMSRG theories, BIMSRG provides an interesting alternative to the already existing multi-reference IMSRG (MR-IMSRG) method applicable to open-shell nuclei. The algebraic equations for low-order approximations, i.e., BIMSRG(1) and BIMSRG(2), can be derived manually without much difficulty. However, such a methodology becomes already impractical and error prone for the derivation of the BIMSRG(3) equations, which are eventually needed to reach high accuracy. Based on a diagrammatic formulation of BIMSRG theory, the second objective of the present paper is thus to describe the third version (v3.0) of the ADG code that automatically (1) generates all valid BIMSRG(n) diagrams and (2) evaluates their algebraic expressions in a matter of seconds. This is achieved in such a way that equations can easily be retrieved for both the flow equation and the Magnus expansion formulations of BIMSRG. Expanding on this work, the first future objective is to numerically implement BIMSRG(2) (eventually BIMSRG(3)) equations and perform ab initio calculations of mid-mass open-shell nuclei.

Control Design for State transition of Open Quantum System

State transition control of open quantum systems is a research hotspot and difficulty. The control method in the light of the Lyapunov stability theory is a common method. Current research shows that if the open quantum systems meet the constraints that the free Hamiltonian is strong regular and the interaction Hamiltonian is fully connected, by devising appropriate control fields in the light of the Lyapunov stability theory, the open quantum system can move to the desired final state. In view of the fact that most practical open quantum systems do not meet these two constraints, this paper propose a control method. The implicit function perturbation terms are introduced into the control fields to resolve the problem that the open quantum systems do not meet these two convergence constraints. And the main control fields are devised in the light of the Lyapunov stability theory to make the state transition of the open quantum systems converging to the desired final state.

One-Bit Function Perturbation Impact on Attractors of Large-Scale Probabilistic Logical Networks

The state space of logical networks is exponentially dependent on the number of nodes, which makes it challenging to deal with large-scale logical networks. In this paper, a brief review of existing methods in large-scale logical networks is firstly presented, including network aggregation, approximation and logical matrix factorization. Then, the network aggregation method is extended to study large-scale probabilistic logical networks (PLNs). Some new criteria are established for the robustness of positive-probability attractors of large-scale PLNs with one-bit function perturbation. Finally, the results are applied to analyze the robustness of positive-probability attractors in the neurotransmitter signaling pathway.

Wannier Function Perturbation Theory: Localized Representation and Interpolation of Wave Function Perturbation

Thanks to the nearsightedness principle, the low-energy electronic structure of solids can be represented by localized states such as the Wannier functions. Wannier functions are actively being applied to a wide range of phenomena in condensed matter systems. However, the Wannier-functionbased representation is limited to a small number of bands and thus cannot describe the change of wavefunctions due to various kinds of perturbations, which require sums over an infinite number of bands. Here, we introduce the concept of the Wannier function perturbation, which provides a localized representation of wavefunction perturbations. Wannier function perturbation theory allows efficient calculation of numerous quantities involving wavefunction perturbation, among which we provide three applications. First, we calculate the temperature-dependent indirect optical absorption spectra of silicon near the absorption edge nonadiabatically, i.e., differentiating phonon-absorption and phonon-emission processes, and without arbitrary temperature-dependent shifts in energy. Second, we establish a theory to calculate the shift spin conductivity without any band-truncation error. Unlike the shift charge conductivity, an exact calculation of the shift spin conductivity is not possible within the conventional Wannier function methods because it cannot be obtained from geometric quantities for low-energy bands. We apply the theory to monolayer WTe$_2$. Third, we calculate the spin Hall conductivity of the same material again without any band-truncation error. Wannier function perturbation theory is a versatile method that can be readily applied to calculate a wide range of quantities related to various kinds of perturbations.

Momentum and energy relaxation in femtosecond-scale energy transport in metals

In the current report we investigate the processes of heat transport and energy relaxation in metals using Boltzmann transport equation for the electron distribution function perturbation, simultaneously accounting both energy and momentum relaxation. Mutual influence of electron-electron and electron-phonon energy relaxation on the electron distribution function is considered using linearized integro-differential collision integrals. These energy exchange effects provide main contribution to the difference between results obtained using Boltzmann equation solution and widely considered two-temperature model.