Analysis Of Nonlinear Interaction Research Articles

Association between lipid accumulation products and gallstones: an analysis of the National Health and Nutrition Examination Survey 2017–2020

AimsThe aim of the research was to look into the connection between the occurrence of gallstones in adult US citizens and lipid accumulation products (LAP).MethodsWe conducted a cross-sectional study of 3,582 U.S. adults with relevant indicators collected from the 2017–2020 National Health and Nutrition Examination Survey (NHANES) database. Multifactorial logistic regression was used to investigate the linear relationship between LAP and gallstone incidence, while smoothed curve fitting was used to describe the nonlinear relationship, and subgroup and interaction analyses were used to evaluate the potential differences between groups.ResultsAmong the 3582 participants aged ≥ 20 years included, there was a positive association between LAP and gallstones. Following adjustments for all covariates, the likelihood of getting gallstones rose by 29% for each unit rise in log2-LAP (OR = 1.29, 95% CI: 1.13‒1.49). Compared to those in the lowest tertile, those in the highest LAP tertile had a significantly higher risk of developing gallstones (OR = 1.97, 95% CI: 1.31‒2.95). Subgroup analyses indicated that the association between LAP and gallstones was not affected by the stratification of the variables examined.ConclusionGallstones and LAP exhibited a positive association in our investigation, indicating that LAP may be utilized as a clinical indicator to determine the occurrence of gallstones.

Data-driven risk analysis of nonlinear factor interactions in road safety using Bayesian networks

This paper aims to demonstrate nonlinear risk factor interactions based on a data-driven approach using a Bayesian network model, providing a road safety use case. Road safety is a critical issue worldwide, with approximately 1.3 million road traffic deaths each year (WHO). Traditional road safety risk assessment methods often analyze individual factors separately; however, these assessments fail to capture the complex dynamics of real-world analysis, in which multiple factors interact through nonlinear relationships. In this study, a novel road safety risk assessment approach that uses a Bayesian network model to explore the nonlinear relationships among road safety risk factors is developed. Through the analysis of extensive crash reports from the state of Maryland, the complex interdependencies among various risk factors and their cumulative impact on road safety are investigated. Our findings show that two combined risk factors have different effects on risk level when considered individually. Two case studies related to human state risk factors and environmental risk factors, such as driving under the influence and snowy roads, as well as fatigue and snowy roads, have an amplified effect on the risk level. The findings highlight the importance of considering nonlinear interactions among risk factors when developing effective and targeted strategies for accident prevention and road safety improvement. This research contributes to the field of road safety by presenting a new methodology for understanding and mitigating road safety hazards.

Computational evaluation of flight performance of flapping-wing nano air vehicles using hierarchical coupling of nonlinear dynamic and fluid-structure interaction analyses

This study endeavours to introduce an inventive hierarchical coupling methodology for evaluating the flight capabilities of polymer micromachined flapping-wing nano air vehicles (FWNAVs) using advanced computational tools. Furthermore, our objective is to provide a practical demonstration of FWNAVs in both tethered and airborne scenarios. These dual objectives represent the distinctive and pioneering aspects of this research. Such FWNAVs, which are insect-inspired robots, have a 2.5-dimensional structure. An FWNAV comprises a micro piezoelectric drive system and a pair of micro thin flexible wings. The drive system includes a micro transmission and a piezoelectric bimorph actuator. The flight performance of the designed FWNAV is evaluated using a hierarchical coupling approach, where the whole system is decomposed into a micro wing and a micro piezoelectric drive system. The coupling between these parts is modelled as one-way coupling and that between the micro wings and the surrounding air is modelled as strong coupling. In the one-way coupling analysis, nonlinear structural dynamic analysis is conducted for the micro piezoelectric drive system, where the dynamic response is transmitted to the micro wings via the Dirichlet boundary condition. In the strong coupling analysis, strongly coupled fluid-structure interaction analysis is conducted for the micro wings and the surrounding air to consider their strong coupling. The optimisation of flight performance is conducted using fluid-structure interaction analysis to achieve sufficient lift force to support the weight of an FWNAV. The design of a tethered and flyable FWNAV with a size of 10 mm or smaller is demonstrated. This FWNAV can be easily fabricated using polymer micromachining.

Enhanced Vehicle Performance Through Nonlinear Finite Element Analysis of Tyre-Soil Interaction

Enhanced Vehicle Performance Through Nonlinear Finite Element Analysis of Tyre-Soil Interaction

Numerical analysis of nonlinear interaction between a gas bubble and free surface in a viscous compressible liquid

Liquid viscosity has a potential effect on bubble dynamics. This paper is concerned with bubble dynamics in a compressible viscous liquid near the free surface. The liquid–gas flow is modeled using the Eulerian finite element method coupled with the volume of fluid method. The numerical results have been shown to be in excellent agreement with those from the spherical bubble theory and experiment. Parametric studies are carried out regarding the Reynolds number Re and the stand-off parameter γd. It clearly demonstrated that the liquid viscosity inhibits bubble pulsation, jet flow, free surface jet, and bubble splitting. Quantitatively, as Reynolds number Re decreases, the maximum bubble volume, jet tip velocity, free surface spike, and crown height decrease, and the toroidal bubble splitting weakens. As the stand-off parameter γd increases, the maximum bubble volume, jet velocity, and bubble average pressure peak increase while the height of the free surface spike decreases. Close observation reveals that the free surface crown tends to disappear at small Re or large γd, further indicating the complex mechanism behind the crown spike evolution.

Analysis of nonlinear soil-structure interaction using partitioned method

For the current state-of-practice in soil-structure interaction (SSI) of nuclear facilities, the strain-dependent characteristics of soil are considered indirectly via equivalent linear methods in the frequency domain, typically represented by the SASSI program. SSI analysis in the time-domain, although directly involving material nonlinearity of the soil, is inefficient in practice up to now. Based on Partitioned Analysis of SSI (PASSI), a method for nonlinear soil-structure interaction analysis is developed in this paper, by applying implicit time-step integration and explicit one with different time steps to nuclear island and to soil, respectively. The incremental equilibrium equation and explicit decoupling method are used to analyze the soil nonlinearity described by the Davidenkov model with simplified loading-reloading rules, which avoids solving algebraic equations and iteration processes. An asynchronous parallel algorithm for nonlinear SSI analysis is given. A simple example is given to verify the partitioned approach with explicit-implicit co-computation against the full-explicit approach. Seismic response characteristics of nuclear power plants are investigated by comparing responses of nonlinear analysis with linear analysis. Different results address the importance of nonlinear SSI analysis for the seismic performance of nuclear structures.

Electrophysiological foundations of the human default-mode network revealed by intracranial-EEG recordings during resting-state and cognition

Investigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during resting-state and its modulation during a cognitive task involving episodic memory formation. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz), while DMN interactions with other brain networks was higher in the beta (12–30 Hz) and gamma (30–80 Hz) bands. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during both verbal memory encoding and recall. Compared to resting-state, slow-wave intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify frequency specific neurophysiological signatures of the DMN which allow it to maintain stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the electrophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.

Detection of Hermitian connections in wave equations with cubic non-linearity

We consider the geometric non-linear inverse problem of recovering a Hermitian connection A from the source-to-solution map of the cubic wave equation \Box_{A}\phi+\kappa |\phi|^{2}\phi=f , where \kappa\neq 0 and \Box_{A} is the connection wave operator in the Minkowski space \mathbb{R}^{1+3} . The equation arises naturally when considering the Yang–Mills–Higgs equations with Mexican hat type potentials. Our proof exploits the microlocal analysis of non-linear wave interactions, but instead of employing information contained in the geometry of the wave front sets as in previous literature, we study the principal symbols of waves generated by suitable interactions. Moreover, our approach relies on inversion of a novel non-abelian broken light ray transform, a result interesting in its own right.

Nonlinear Wave Interactions in a Macroscopic Production Model

In this article, we study the exhaustive analysis of nonlinear wave interactions for a 2 × 2 homogeneous system of quasilinear hyperbolic partial differential equations (PDEs) governing the macroscopic production. We use the hodograph transformation and differential constraints technique to obtain the exact solution of governing equations. Furthermore, we study the interaction between simple waves in detail through exact solution of general initial value problem. Finally, we discuss the all possible interaction of elementary waves using the solution of Riemann problem.

Seismic Performance of Deeply Embedded Conceptual Advanced Reactors: Three-Dimensional Nonlinear Soil-Structure Interaction Analyses

The U.S. Nuclear Regulatory Commission’s functional containment concept provides advanced nuclear power plant designers with more flexibility in terms of the civil/structural design if the appropriate set of barriers for prevention of radioactive material release exist. Some of the conceptual advanced reactor structures, without the traditional pressure boundaries of large containment structures, are proposed to be deeply embedded or buried into soil. This approach is expected to provide (1) lesser seismic demands on the structures and safety-critical structures, (2) eased regulatory efforts and overall design against other external hazards such as aircraft impact, and (3) overall cost savings. One of the important aspects of assessing the technical and economic viability of deeply embedding advanced reactor buildings is to assess the seismic performance with the understanding of effects with material and geometric nonlinearities. This study investigates the seismic response of deeply embedded or buried advanced reactors by conducting three-dimensional nonlinear soil-structure interaction analyses. Although the results indicate that there is a general trend of decreased seismic response with increased embedment depths, the change in the dynamic environment with different embedment depths and the nonlinear environment under high-intensity seismic inputs may result in increased peak response at increased embedment depths.

Nonlinear modal interaction analysis and vibration characteristics of a francis hydro-turbine generator unit

The Francis hydro-turbine generator unit (FHTGU) is a typical nonlinear system with the coupling hydraulic, mechanical and electric subsystems. It is a challenge to understand the reasons for its operational failures because the major reason for failures involves complex interactions of the three subsystems. Subsystems’ model interaction with the method of normal forms has been well developed and investigated, overcoming the linear methods used in the FHTGU’s stability analysis. However, these methods have not to quantify higher-order terms in a mathematically accurate type to capture dynamic modal interactions between subsystems. Due to the accelerating expansion of hydropower stations, stability of FHTGU shows singular nonlinear oscillations and new methods have to be upgraded to cope with this new situation. In this study, the nonlinear modal method is introduced to analyze the dynamic modal interactions between subsystems, and results given by the different methods are compared to verify the method’s feasibility. The effect of the second order modes is quantified to investigate its effect on the dynamic characteristics of FHTGU, and the vibration characteristics affected by the wind generation system are also investigated. The result shows that the intensity of modes can be effectively reduced to satisfy the stable requirements. All of these results provide a theoretical guidance for the stable operation of FHTGUs.

Bispectral analysis of nonlinear interaction, predictability and stochastic modelling with application to ENSO

Non-Gaussianity and nonlinearity have been shown to be ubiquitous characteristics of El Niño Southern Oscillation (ENSO) with implication on predictability, modelling, and assessment of extremes. These topics are investigated through the analysis of third-order statistics of El Niño 3.4 index in the period 1870–2018, namely bicovariance and bispectrum. Likewise, the spectral decomposition of variance, the bispectrum provides a spectral decomposition of skewness. Positive and negative bispectral contributions identify modes contributing respectively to La Niñas and El Niños, mostly in the period range 2–6 years. The ENSO bispectrum also shows statistically significant features associated with nonlinearity. The analysis of bicovariance reveals a nonlinear correlation between the Boreal Spring and following Winter, coming from an asymmetry of the persistence of El Niño, contributing hence to a reduction of Spring Predictability Barrier. The positive skewness and main features of the ENSO bicovariance and bispectrum are shown to be well reproduced by fitting a bilinear stochastic model. This model shows improved forecasts, with respect to benchmark linear models, especially of the amplitude of extreme El Niños. This study is relevant, particularly in a changing climate, to better characterize and predict ENSO extremes coming from non-Gaussianity and nonlinearity.

Feature prioritisation on big genomic data for analysing gene-gene interactions

Complex diseases are not caused by single genes but result from intricate non-linear interactions among them. There is a critical need to implement approaches that take into account non-linear gene-gene interactions in searching for markers that jointly cause diseases. Determining the interaction between more than two single nucleotide polymorphisms (SNP) within the whole genome data is computationally expensive and often infeasible. In this paper, we develop an approach to classify patients with Acute Lymphoblastic Leukaemia by analysing multiple SNP interactions. A novel feature prioritisation algorithm called interaction effect quantity (IEQ) selects SNPs with high potential of interaction by analysing their distribution throughout the genomic data and enables deeper analysis of non-linear interactions within large datasets. We show that IEQ enables analyses of interactions between up to four SNPs, with F-measure for classification greater than 89% obtained. Such an analysis is typically much more computationally challenging if IEQ is not implemented.

Assessing Coral Reef Condition Indicators for Local and Global Stressors Using Bayesian Networks.

Coral reefs are highly valued ecosystems currently threatened by both local and global stressors. Given the importance of coral reef ecosystems, a Bayesian network approach can benefit an evaluation of threats to reef condition. To this end, we used data to evaluate the overlap between local stressors (overfishing and destructive fishing, watershed-based pollution, marine-based pollution, and coastal development threats), global stressors (acidification and thermal stress), and management effectiveness with indicators of coral reef health (live coral index, live coral cover, population bleaching, colony bleaching, and recently killed corals). Each of the coral health indicators had Bayesian networks constructed globally and for Pacific, Atlantic, Australia, Middle East, Indian Ocean, and Southeast Asia coral reef locations. Sensitivity analysis helped evaluate the strength of the relationships between different stressors and reef condition indicators. The relationships between indicators and stressors were also evaluated with conditional analyses of linear and nonlinear interactions. In this process, a standardized direct effects analysis was emphasized with a target mean analysis to predict changes in the mean value of the reef indicator from individual changes to the distribution of the predictor variables. The standardized direct effects analysis identified higher risks in the Middle East for watershed-based pollution with population bleaching and in Australia for overfishing and destructive fishing with living coral. For thermal stress, colony bleaching and recently killed coral in the Indian Ocean were found to have the strongest direct associations along with living coral in the Middle East. For acidification threat, Australia had a relatively strong association with colony bleaching, and the Middle East had the strongest overall association with recently killed coral, although extrapolated spatial data were used for the acidification estimates. The Bayesian network approach helped to explore the relationships among existing databases used for policy development in coral reef management by examining the sensitivity of multiple indicators of reef condition to spatially distributed stress. Integr Environ Assess Manag 2021;17:165-187. Published 2020. This article is a US Government work and is in the public domain in the USA.

Numerical Investigation of Mechanisms Underlying Oceanic Internal Gravity Wave Power-Law Spectra

AbstractWe consider the power-law spectra of internal gravity waves in a rotating and stratified ocean. Field measurements have shown considerable variability of spectral slopes compared to the high-wavenumber, high-frequency portion of the Garrett–Munk (GM) spectrum. Theoretical explanations have been developed through wave turbulence theory (WTT), where different power-law solutions of the kinetic equation can be found depending on the mechanisms underlying the nonlinear interactions. Mathematically, these are reflected by the convergence properties of the so-called collision integral (CL) at low- and high-frequency limits. In this work, we study the mechanisms in the formation of the power-law spectra of internal gravity waves, utilizing numerical data from the high-resolution modeling of internal waves (HRMIW) in a region northwest of Hawaii. The model captures the power-law spectra in broad ranges of space and time scales, with scalings ω−2.05±0.2 in frequency and m−2.58±0.4 in vertical wavenumber. The latter clearly deviates from the GM76 spectrum but is closer to a family of induced-diffusion-dominated solutions predicted by WTT. Our analysis of nonlinear interactions is performed directly on these model outputs, which is fundamentally different from previous work assuming a GM76 spectrum. By applying a bicoherence analysis and evaluations of modal energy transfer, we show that the CL is dominated by nonlocal interactions between modes in the power-law range and low-frequency inertial motions. We further identify induced diffusion and the near-resonances at its spectral vicinity as dominating the formation of power-law spectrum.

Impact from ice floes and icebergs on ships and offshore structures in Polar Regions

The principles for ULS design and ALS design for offshore structures are discussed. The use of pressure-area curve versus force-area curves for analysis for estimation of ALS impacts is deliberated. Aspects of local and global shape of the ice feature are discussed in view of external mechanics (demand for energy dissipation) and internal mechanics (local damage). Simplified methods for structural damage assessment are reviewed for ice loads that may move both transverse to and along the shell plating. Material modelling of ice for nonlinear finite element analysis (NLFEA) of ice-structure interaction is reviewed. The material models must be calibrated against design curves and the sensitivity of the material parameters with respect to mesh size is investigated. Results from simulation of impacts of ice with different shapes on the column of a floating platform are presented, and the critical shape for penetration of the front plating for the present structural configuration is identified.

Analysis of Nonlinear Fiber Interactions for Finite-Length Constant-Composition Sequences

In order to realize probabilistically shaped signaling within the probabilistic amplitude shaping (PAS) framework, a shaping device outputs sequences that follow a certain nonuniform distribution. In case of constant-composition (CC) distribution matching (CCDM), the sequences differ only in the ordering of their constituent symbols, whereas the number of occurrences of each symbol is constant in every output block. Recent results by Amari \textit{et al.} have shown that the CCDM block length can have a considerable impact on the effective signal-to-noise ratio (SNR) after fiber transmission. So far, no explanation for this behavior has been presented. Furthermore, the block-length dependence of the SNR seems not to be fully aligned with previous results in the literature. This paper is devoted to a detailed analysis of the nonlinear fiber interactions for CC sequences. We confirm in fiber simulations the inverse proportionality of SNR with CCDM block length and present two explanations. The first one, which only holds in the short-length regime, is based on how two-dimensional symbols are generated from shaped amplitudes in the PAS framework. The second, more general explanation relates to an induced shuffling within a sequence, or equivalently a limited concentration of identical symbols, that is an inherent property for short CC blocks, yet not necessarily present for long blocks. This temporal property results in weaker nonlinear interactions, and thus higher SNR, for short CC sequences. For a typical multi-span fiber setup, the SNR difference is numerically demonstrated to be up to 0.7dB. Finally, we evaluate a heuristic figure of merit that captures the number of runs of identical symbols in a concatenation of several CC sequences. For moderate block lengths up to approximately 100 symbols, this metric suggests that limiting the number of identical-symbol runs can be beneficial.

Nonlinear Interaction Analysis of Cardiovascular-Respiratory Data by Means of Convergent Cross Mapping.

Appropriate analyses of directed complex interactions within the cardiovascular-respiratory system are of growing interest for a better understanding of physiological regulatory mechanisms in healthy subjects and diseased persons. There are various concepts to analyze such interactions. Convergent Cross Mapping (CCM) provides the possibility to define directed interactions in terms of nonlinear stability. A proof-of-principle approach is introduced to apply CCM to cardiovascular-respiratory data of healthy subjects during resting state period. Showing group results of time-invariant as well as single subject results of interval-based CCM, the introduced approach was able to quantify correct directionality and strength of interactions within the cardiovascular-respiratory system and to provide statistical thresholds for significant interactions. These results may serve as a methodological base to compare healthy subjects and diseased persons.

Partners in Debt: An Endogenous Nonlinear Analysis of Interaction of Public and Private Debt on Growth

This paper analyzes how the interaction of public and private debt influences economic growth. Both debt variables are treated as endogenous and subject to regime switch, with the interaction term being the threshold variable. We test whether this interaction variable causes a nonlinear relationship. We find strong evidence for a threshold effect. The threshold variable is endogenous, unlike its treatment in the previous literature. Using data from 29 OECD countries from 1995-2014, the thresh old effect of the interaction between the public and private debt variables and economic growth is found to be negative and significant when it reaches the level of 137%. We also decompose private debt into household and corporate debt. We find that the public and private debt interaction is likely to operate through the channels of household debt and public debt. For a robustness check, we examine the sensitivity of the threshold effects to banking crises, output volatility, and institutional quality, different time periods, and alternative models.

An experimental study and numerical modeling of laterally loaded regular and finned pile foundations in sandy soils

A significant objective in the design and implementation of capable and cost-effective pile foundations is the enhancement of their lateral capacity when lateral load is applied. This study offers a nonlinear 3D analysis of pile-soil interaction. The ways that piles behave are examined in this research, with a sequence of laboratory model tests conducted to develop p-y curves of laterally loaded finned and regular piles in multilayered sandy soil from Karbala city in Iraq. To clarify the effects of group interaction, pile type, pile group patterns, and spacing ratios were analyzed, and from the investigational tests, p-multipliers values were identified.