Slight Changes In Parameters Research Articles

Infection patterns in simple and complex contagion processes on networks.

Contagion processes, representing the spread of infectious diseases, information, or social behaviors, are often schematized as taking place on networks, which encode for instance the interactions between individuals. The impact of the network structure on spreading process has been widely investigated, but not the reverse question: do different processes unfolding on a given network lead to different infection patterns? How do the infection patterns depend on a model's parameters or on the nature of the contagion processes? Here we address this issue by investigating the infection patterns for a variety of models. In simple contagion processes, where contagion events involve one connection at a time, we find that the infection patterns are extremely robust across models and parameters. In complex contagion models instead, in which multiple interactions are needed for a contagion event, non-trivial dependencies on models parameters emerge, as the infection pattern depends on the interplay between pairwise and group contagions. In models involving threshold mechanisms moreover, slight parameter changes can significantly impact the spreading paths. Our results show that it is possible to study crucial features of a spread from schematized models, and inform us on the variations between spreading patterns in processes of different nature.

Magneto-thermo-elastic coupling vibration and bifurcation characteristics of functionally graded rotating cylindrical shell

The magneto-thermo-elastic coupling vibration of rotating ferromagnetic functionally graded cylindrical shell is investigated in this paper. Based on the physical neutral surface theory and Donnell's theory, the expressions of kinetic energy and strain energy are obtained by introducing geometric nonlinearity. The magneto-thermo-elastic vibration equations of the rotating ferromagnetic functionally graded cylindrical shell in multi-physical field are derived via the Hamilton's principle. Considering the magnetization effect of ferromagnetic shell in magnetic field, the expression of magnetization force is obtained according to the nonlinear magnetic constitutive relation. For simply supported boundary conditions, Galerkin's method is used to obtain the discretized ordinary differential equations, and the static deflection of the shell under static load is solved. The steady-state response of the system during primary resonance and the stability of solutions are given by the multi-scale method and the Lyapunov stability theory. Through numerical examples, the characteristic curves and surfaces of amplitude are plotted, and the parameter ranges corresponding to regions of multi-valued solutions and stable solutions are determined. The system dynamics laws describing the coupling effect between multiple parameters such as force, magnetism, heat, and rotational speed are evaluated. The Global bifurcation diagrams and the maximum Lyapunov exponent spectrums under different control parameters are plotted to analyze the effect of parameter changes on the dynamic response of system. The results show that the vibration characteristics of the system are significantly influenced by the external physical fields, in addition to the shell size and material volume fraction. Slight changes in parameters can lead to violent changes in the dynamic response of the system, exhibiting intermittent, jumping, and chaotic characteristics.

Tumor Detection and Sectional Analysis in 3D Model

Tumor detection is a necessary task that identifies the presence of the tumor with the help of image processing. In this paper, image processing is used for the detection of the tumor with enough precision for doctors to understand about shape and size of a tumor. The 3D mapping task of a tumor is followed by image processing of each MRI (Magnetic Resonance Imaging) slice. This 3D plotting is performed with the Plotly Python library. This approach is helpful for doctors to understand the tumor at each slice. With color differentiation, every MRI slice is visualized in the X, Y, and Z-axis. A tumor specialist can identify the size of a tumor with every co-ordinate plotted. This paper gives the solution for almost every tumor and its organ visualization. The slight change in parameters of the image processing algorithm can detect a tumor in multi organs.

HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking

BackgroundChromatin conformation capture techniques have evolved rapidly over the last few years and have provided new insights into genome organization at an unprecedented resolution. Analysis of Hi-C data is complex and computationally intensive involving multiple tasks and requiring robust quality assessment. This has led to the development of several tools and methods for processing Hi-C data. However, most of the existing tools do not cover all aspects of the analysis and only offer few quality assessment options. Additionally, availability of a multitude of tools makes scientists wonder how these tools and associated parameters can be optimally used, and how potential discrepancies can be interpreted and resolved. Most importantly, investigators need to be ensured that slight changes in parameters and/or methods do not affect the conclusions of their studies.ResultsTo address these issues (compare, explore and reproduce), we introduce HiC-bench, a configurable computational platform for comprehensive and reproducible analysis of Hi-C sequencing data. HiC-bench performs all common Hi-C analysis tasks, such as alignment, filtering, contact matrix generation and normalization, identification of topological domains, scoring and annotation of specific interactions using both published tools and our own. We have also embedded various tasks that perform quality assessment and visualization. HiC-bench is implemented as a data flow platform with an emphasis on analysis reproducibility. Additionally, the user can readily perform parameter exploration and comparison of different tools in a combinatorial manner that takes into account all desired parameter settings in each pipeline task. This unique feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple tool/parameter choices in each step of the analysis. To demonstrate the usefulness of our platform, we performed a comprehensive benchmark of existing and new TAD callers exploring different matrix correction methods, parameter settings and sequencing depths. Users can extend our pipeline by adding more tools as they become available.ConclusionsHiC-bench consists an easy-to-use and extensible platform for comprehensive analysis of Hi-C datasets. We expect that it will facilitate current analyses and help scientists formulate and test new hypotheses in the field of three-dimensional genome organization.

On the Structure of Boolean Functions with Small Spectral Norm

In this paper we prove results regarding Boolean functions with small spectral norm (the spectral norm of f is $${\|\hat{f}\|_1 = \sum_{\alpha}|\hat{f}(\alpha)|}$$źf^ź1=źź|f^(ź)|). Specifically, we prove the following results for functions $${f : \{0, 1\}^n \to \{0, 1\}}$$f:{0,1}nź{0,1} with $${\|\hat{f}\|_1 = A}$$źf^ź1=A. 1.There is an affine subspace V of co-dimension at most A2 such that $${f|_V}$$f|V is constant.2.f can be computed by a parity decision tree of size at most $${2^{A^2} n^{2A}}$$2A2n2A. (A parity decision tree is a decision tree whose nodes are labeled with arbitrary linear functions.) 3.f can be computed by a De Morgan formula of size $${O(2^{A^2} n^{2A + 2})}$$O(2A2n2A+2) and by a De Morgan formula of depth $${O(A^2 + \log(n) \cdot A)}$$O(A2+log(n)·A).4.If in addition f has at most s nonzero Fourier coefficients, then f can be computed by a parity decision tree of depth at most $${A^2 \log s}$$A2logs.5.For every $${\epsilon > 0}$$∈>0 there is a parity decision tree of depth $${O(A^2 + \log(1/\epsilon))}$$O(A2+log(1/∈)) and size $${2^{O(A^2)} \cdot \min \{1/\epsilon^2, \log(1/\epsilon)^{2A}\}}$$2O(A2)·min{1/∈2,log(1/∈)2A} that $${\epsilon}$$∈-approximates f. Furthermore, this tree can be learned (in the uniform distribution model), with probability $${1 - \delta}$$1-ź, using $${{\tt poly}(n, {\rm exp}(A^2), 1/\epsilon, \log(1/\delta))}$$poly(n,exp(A2),1/∈,log(1/ź)) membership queries. All the results above (except 3) also hold (with a slight change in parameters) for functions $${f : \mathbb{Z}_p^n \to \{0, 1\}}$$f:Zpnź{0,1}.

Sunshine or Shield? Secret Voting Procedures and Legislative Accountability

How does the use of a secret vote affect the likelihood that legislators will punish their peers? Two contending arguments exist in the literature: some argue that secret voting may be prejudicial, while others argue that it may help accountability. We address this controversy by analyzing the case of the Brazilian Congress, which uses a sequential combination of open and secret voting procedures. We begin with a statistical analysis of the Congress that establishes some key parameters of variance. The results of this exercise are then used to populate an agent-based model of the Congress, which is used to simulate a variety of potential behaviors under diverse conditions. Agent-based modeling enables us to extend the discussion beyond the small-n of cases available in the real world, demonstrating that slight changes in parameters can lead to very large changes in the overall effect of voting procedure. Modeling voting behaviors under different conditions, we conclude that both arguments about secret voting may hold true, and that the effects of the type of vote – open or secret – will be contingent on factors such as the power of the accused politician, the composition of the voting body, and the publicity given to the accusations.

A conceptual ENSO model under realistic noise forcing

Abstract. We investigated the influence of atmospheric noise on the generation of interannual El Niño variability. Therefore, we perturbed a conceptual ENSO delay model with surrogate windstress data generated from tropical windspeed measurements. The effect of the additional stochastic forcing was studied for various parameter sets including periodic and chaotic regimes. The evaluation was based on a spectrum and amplitude-period relation comparison between model and measured sea surface temperature data. The additional forcing turned out to increase the variability of the model output in general. The noise-free model was unable to reproduce the observed spectral bandwidth for any choice of parameters. On the contrary, the stochastically forced model is capable of producing a realistic spectrum. The weakly nonlinear regimes of the model exhibit a proportional relation between amplitude and period matching the relation derived from measurement data. The chaotic regime, however, shows an inversely proportional relation. A stability analysis of the different regimes revealed that the spectra of the weakly nonlinear regimes are robust against slight parameter changes representing disregarded physical mechanisms, whereas the chaotic regime exhibits a very unstable realistic spectrum. We conclude that the model including stochastic forcing in a parameter range of moderate nonlinearity best matches the real conditions. This suggests that atmospheric noise plays an important role in the coupled tropical pacific ocean-atmosphere system.

Reconstruction of Pt(111) and domain patterns on close-packed metal surfaces

We have studied the reconstruction of Pt(111) theoretically using a two-dimensional Frenkel-Kontorova model for which all parameters have been obtained from ab initio calculations. We find that the unreconstructed surface lies right at the stability boundary, explaining why it is easy to induce the surface to reconstruct into a pattern of fcc and hcp domains. The experimentally observed ``rotors'' at intersections of domain walls are shown to arise from a slight rotation of the top layer relative to the substrate. The size and shape of domains are very sensitive to the density in the top layer, the angle of rotation, and the chemical potential, with smooth transformations between different patterns that include the honeycomb, wavy triangles, bright stars, and Moir\'e pattern. This shows that the same physics is operating in the various homoepitaxial and heteroepitaxial systems for which these different patterns have been reported, with the apparent differences arising from very slight changes in parameters.

Slight parameter changes detection in biological models: a multiresolution approach

This paper deals with the automatic detection of slight parameter changes from the analysis of signals generated by nonlinear biological systems. The interest is focused here on investigating particular aspects of the relation between signal analysis and systems dynamics, involving the automatic detection of changes in parameters of nonlinear systems. The continuous multiresolution entropies combine advantages stemming from both entropy (Shannon and parametric q-entropy) and wavelet analysis, have been shown that they are sensitive to dynamical complexity changes. Classical statistical approaches offer a new tool that enables the automatic detection of such changes. In this paper, multiresolution and standard tools for the automatic detection of slight parameter changes in nonlinear dynamical systems from the analysis of the corresponding time series are introduced and compared. The relevance of the multiresolution approach, together with its robustness in the presence of moderate noise, and their comparison are discussed in numerical simulations and they are applied to biological signals.

AUTOMATIC DETECTION OF SLIGHT CHANGES IN NONLINEAR DYNAMICAL SYSTEMS USING MULTIRESOLUTION ENTROPY TOOLS

The continuous multiresolution entropy, which combines advantages stemming from both classical entropy and wavelet analysis, has shown to be sensitive to dynamical complexity changes. The addition of classical statistical changes detection tools gives rise to a new tool that allows their automatic detection. In this paper, a new tool for the automatic detection of slight parameter changes in nonlinear dynamical systems from the analysis of the corresponding time series is proposed. The relevance of the approach, together with its robustness in the presence of moderate noise, is discussed in numerical simulations and it is applied to biological signals.

Time Variability and Simmons–Wallace–Branstator Instability in a Simple Nonlinear One-Layer Model

Using a global, one-layer shallow water model, the response of a westerly flow to a localized mountain is investigated. A steady, linear response at small mountain heights successively gives way first to a steady flow in which nonlinearities are important and then to unsteady, but periodic, flow at larger mountain heights. At first the unsteady behavior consists of a low-frequency oscillation of the entire Northern Hemisphere zonal flow. As the mountain height is increased further, however, the oscillatory behavior becomes localized in the diffluent jet exit region downstream of the mountain. The oscillation then takes the form of a relatively rapid vortex shedding event, followed by a gradual readjustment of the split jet structure in the diffluent region. Although relatively simple, the model exhibits a surprisingly high sensitivity to slight parameter changes. A linear stability analysis of the time-averaged flow is able to capture the transition from steady to time-dependent behavior, but fails to capture the transition between the two distinct regimes of time-dependent response. Moreover, the most unstable modes of the time-averaged flow are found to be stationary and fail to capture the salient features of the EOFs of the full time-dependent flow. These results therefore suggest that, even in the simplest cases, such as the one studied here, a linear analysis of the time-averaged flow can be highly inadequate in describing the full nonlinear behavior.

Threshold models of interpersonal effects in consumer demand

Whether one buys may be determined in part by how many others have. When the correlation is positive we refer to ‘bandwagon’ effects, and when negative, ‘reverse bandwagons’. We construct demand schedules in the presence of such effects and, with simple assumptions about supply, investigate the existence of and approach to equilibrium. Stable price-quantity equilibria exist, but for many plausible parameter values, equilibria are asymptotically unstable, and system trajectories consist of cycles that can move, with slight parameter changes, via successive bifurcations into what has been called ‘chaotic’ dynamics, essentially indistinguishable from random noise. These conditions occur despite assumptions of [erfect information, profit maximizing firms and utility maximizing individuals.

Cyclic AMP and growth of Ehrlich ascites tumor cells lack of cyclic AMP elevation in nutritionally deprived cells and mechanism of retardation of growth by dibutyryl cyclic AMP

Cyclic AMP levels in Ehrlich ascites tumor cells changed little after deprivation of cells of essential nutrients, serum, glucose and amino acids, deprival of each of which leads to marked inhibition of growth and protein synthesis. Cyclic AMP levels also changed little after the addition of these nutrients to deprived cells. Thus cyclic AMP is not likely to be the intracellular mediator for growth regulation by these three nutrients. Elevation of cyclic AMP levels for short periods by exposure of cells to choleratoxin or theophylline produced only slight changes in parameters of protein synthesis (polyribosome pattern and rate of [ 3H]leucine incorporation). An exposure for 1 day to dibutyryl cyclic AMP did not inhibit cell growth. However, prolonged exposure to dibutyryl cyclic AMP inhibited the multiplication of Ehrlich ascites cells both in suspension and in stationary cultures. No morphological effects were evident in the former; in the latter, cells attached firmly to the substratum and formed elongated cytoplasmic processes. Inhibition of cell multiplication by dibutyryl cyclic AMP was related to cell density and to serum concentration. Cells in dibutyryl cyclic AMP-containing media plated at low cell densities multiplied as rapidly as control cells. The final densities cells reached were determined by the serum concentration; in dibutyryl cyclic AMP-containing media these densities were about one-half those of respective control cells. Limitation of cell multiplication by dibutyryl cyclic was AMP reversed by the addition of serum, by resuspending cells at lower densities, or by resuspending cells in media without dibutyryl cyclic AMP. These findings suggested that dibutyryl cyclic AMP may affect the utilization of serum factors by cells. Dibutyryl cyclic AMP did not inactivate serum factors and did not change the rate at which cells depleted the growth medium of serum factors. Dibutyryl cyclic AMP may limit cell multiplication by increasing the cellular requirement for serum factors.