Nonlinear Effects Research Articles

Nonlinear amplification of nano bowl surface concavity on the critical response threshold to biosignals

Polymer nanoparticles that can sharply sense and detect biological signals in cells are promising candidates for biomedical and theranostic nanomaterials. However, the response ability of current polymer assemblies poorly matches the requirement of trace concentration level (10−6 ~ 10−9 mol/L) of cellular biosignals due to their linear signal input-to-function output mode, which impedes their practical applications in vivo. Here we report a kind of nanobowl system with pH-tunable invaginated morphology that can nonlinearly amplify the response abilities toward biosignals by modulating the surface concavity. Compared to conventional spherical nanoparticles, nonspherical nanobowls with a specific concave structure reduce the critical response threshold of polymers by up to 5 orders of magnitude, from millimole to nanomole level, covering most of biosignal concentration windows. Moreover, we find that this nonlinear signal gain effect is originated from the collective impact of a single signal on transitioning the polymer chain aggregation state of individual assemblies, rather than just altering a certain unit or chain. This nonlinear signal-to-response mechanism is potential to solve the tricky problems of probing and sensing endogenous signals with trace physiological concentration.

Non-linear relationship between relative fat mass and diabetes risk in Japanese adults: a retrospective cohort study

Background: Relative fat mass (RFM) represents a newly developed sex-specific anthropometric formula to estimate total body fat percentage. Nonetheless, research examining the correlation between RFM and the risk of diabetes remains scarce. This research assessed the link between RFM and DM risk within the Japanese demographic. Methods: From 2004 to 2015, 15,462 Japanese individuals without diabetes underwent physical evaluations at Murakami Memorial Hospital. The relationship between RFM and the onset of diabetes was analyzed separately using Cox proportional-hazards regression models. This study employed Cox proportional hazards regression incorporating cubic spline functions and smooth curve fitting to detect non-linear associations between RFM and new cases of diabetes, categorized by sex. Sensitivity analyses were performed to confirm the robustness of the link between RFM and incident diabetes. Results: After controlling for confounding factors, a significant positive correlation between RFM and diabetes risk was found in women (HR: 1.13, 95%CI: 1.04–1.24, P = 0.0061), while the association in men was not statistically significant (HR: 1.05, 95%CI: 0.98–1.13, P = 0.1511). Additionally, a non-linear relationship between RFM and the incidence of diabetes was detected in both genders. The RFM threshold was identified at 39.23 for women and 23.08 for men. For women, HR was 1.11 (95%CI: 1.01–1.21) below the threshold and 1.39 (95%CI: 1.17–1.65) above it. In men, an RFM above 23.08 was positively related to diabetes risk (HR: 1.16, 95%CI: 1.06–1.28, P = 0.0012), whereas an RFM below this point did not show a significant association (HR: 0.98, 95%CI: 0.91–1.06, P = 0.5899). Conclusion: Our findings suggest a non-linear relationship and threshold effect between RFM and the risk of diabetes. These findings imply that maintaining RFM at lower levels may be beneficial in mitigating the onset of DM.

Pharmacokinetics of intramuscular L-carvone in sheep.

To measure and model concentrations of the analgesic L-carvone, a natural component of spearmint, over time when administered IM to sheep and to characterize L-carvone's effects on CBCs and clinical biochemistry panels. L-carvone formulated as a 50% solution (v/v) in ethanol and propylene glycol was administered at 71.6 mg/kg IM, split between each semitendinosus muscle in 6 sheep. Venous blood was sampled over 24 hours, and plasma was separated by centrifugation. Additional blood was collected for CBC and serum biochemical analysis, and tissues were sampled after euthanasia. L-carvone concentrations in plasma and tissue homogenates were measured using HPLC-MS-MS. Plasma pharmacokinetic data were described using a nonlinear mixed effects model. Complete blood count and biochemistry data were compared to baseline values using repeated-measures ANOVA and Holm-Šidák tests (P < .05). Maximum plasma concentrations ranged from 0.28 to 1.93 µg/mL and occurred within 9 to 15 minutes after injection. Pharmacokinetics were best described using 2 compartments. Elimination half-life was 33.7 minutes and 390.2 minutes in the central and peripheral compartments, respectively. Mild increases in neutrophil count and significant increases in creatinine kinase and aspartate aminotransferase were associated with injection site myonecrosis. No physical examination, behavioral, or other clinically significant laboratory changes were noted. Intramuscular L-carvone exhibits rapid time to peak concentration, relatively slow plasma elimination, and low tissue concentrations after 24 hours. L-carvone exhibits a favorable pharmacokinetic profile for an analgesic drug. A new L-carvone formulation or administration route is needed to reduce inflammation and necrosis at the injection site.

How Socialized Services Affect Agricultural Economic Resilience—Empirical Evidence from China

Socialized services are crucial for addressing the issue of “who will farm the land” and subsequently enhancing agricultural economic resilience (AER). However, few studies have examined the mechanisms and effects of socialized services on AER. Consequently, this study aims to elucidate the impact and mechanisms of socialized services on AER, with the objective of providing new policy recommendations for enhancing AER and ensuring food security. Based on provincial panel data from China spanning 2009 to 2021, this paper examines the impact and mechanisms of socialized services on AER using a two-way fixed effects model, a mediated effects model, and a panel threshold model. The findings reveal that socialized services significantly enhance AER. Mechanism analysis indicates that socialized services enhance AER by accelerating the substitution of machinery for manpower and promoting the efficiency of labor division. Heterogeneity analysis indicates that in regions with high grain cropping ratios and high internet penetration rates, the enhancement effect of socialized services on AER is stronger. Further analysis uncovers a significant nonlinear threshold effect of socialized services on AER. The impact becomes more pronounced when AER surpasses 0.4689. Consequently, this study argues that in the process of constructing a modern agricultural business system, it is essential to focus on improving the differentiated socialized service system and accelerating the development of rural digital infrastructure.

Effects of climate variability on the spatio-temporal distribution of Dengue in Valle del Cauca, Colombia, from 2001 to 2019.

Dengue is a vector-borne disease that has increased over the past two decades, becoming a global public health emergency. The transmission of dengue is contingent upon various factors, among which climate variability plays a significant role. However, there remains substantial uncertainty regarding the underlying mechanisms. This study aims to investigate the spatial and temporal patterns of dengue risk and to quantify the associated risk factors in Valle del Cauca, Colombia, from 2001 to 2019. To achieve this, a spatio-temporal Bayesian hierarchical model was developed, integrating delayed and non-linear effects of climate variables, socio-economic factors, along with spatio-temporal random effects to account for unexplained variability. The results indicate that average temperature is positively associated with dengue risk 0-2 months later, showing a 35% increase in the risk. Similarly, high precipitation levels lead to increased risk approximately 2-3 months later, while relative humidity showed a constant risk within a 6 months-lag. These findings could be valuable for local health authorities interested in developing early warning systems to predict future risks in advance.

Second harmonic generation based on graphene hyperstructure for higher resolution and performance on top of achieving fundamental wave detection in theory

In this paper, an innovative one-dimensional graphene hyperstructure (GHS) is proposed, allowing for the concurrent detection of multiple physical parameters in both the fundamental and second harmonic generation. The sensing characteristics of GHS pertaining to magnetic field strength (B), incident electromagnetic wave angle (θ), and graphene thickness (dgt) are systematically investigated. Moreover, through the incorporation of second harmonic generation alongside fundamental detection, higher resolution and performance are achieved. The findings indicate an expansion of the measurement range for B, θ, and dgt, from 0.3∼0.5 T, 35∼55°, and 1∼6 layers to 0.3∼1 T, 35∼65°, and 1∼10 layers, providing increased flexibility and adjustability. Additionally, by leveraging nonlinear effects and widening the Fabry-Perot cavity width, this structure effectively enhances the quality factor (Q) from 2.94 × 102 to 1.95 × 105, resulting in a substantial improvement in sensing performance. This development holds tremendous promise in surpassing the diffraction limit and addressing high-Q value sensing requirements. In comparison to conventional detectors, the GHS not only enhances detection efficiency but also harbors the potential for multiple physical quantities detection. This forward-looking research is pivotal in its successful resolution of detector performance limitations, ushering in novel possibilities across diverse domains.

Oblique propagation of dust acoustic solitary waves in a magnetized plasma in the presence of cairns-tsallis distributed ions

We investigate the effects of non-extensivity (q), non-thermality (α), obliqueness (l z ), the strength of the magnetic field (ω c ), and dust grain temperature (σ d ) on the basic features (viz., amplitude, width, velocity, and soliton energy) of obliquely propagating dust-acoustic solitary waves (DASWs) in a magnetized dusty plasma, which consists of highly negatively charged dust grains, Boltzmann-distributed electrons, and nonthermal non-extensive Cairns-Tsallis(C-T)-distributed ions. First, we derived the expression of the C-T polarization force and analyzed the combined effects of the ions’ non-extensivity (q) and non-thermality (α) parameters on the magnitude (R) of this polarization force. Our results show that R strongly depends on both the q-parameter and the α-parameter. Specifically, for q < 1, the ions’ non-extensivity and non-thermality weaken the polarization force, whereas for q > 1, R shifts toward higher values. Thus, the obliquely propagating DASWs are more likely to form in a magnetized non-extensive plasma rather than in a magnetized extensive plasma q = 1. Subsequent key findings are as follows: The wave phase velocity increases linearly as the obliquity (l z ) decreases. This implies that a reduced obliqueness results in faster soliton motion and spikier solitary structures. Moreover, the amplitude (width) of DASWs decreases (increases) with increasing l z . An increase in the magnetic field magnitude (ω c ) affects only the width of the DASWs. The amplitude (width) of DASWs decreases (increases) with higher dust grain temperature (σ d ). This indicates that dust temperature significantly affects wave excitation. Specifically, at higher dust temperatures, dispersion dominates over nonlinear effects, resulting in smoother solitary structures. The soliton’s energy increases with α and becomes more pronounced as q decreases (from 1 to 0.75). It increases also with higher ω c and dust temperature (σ d ), especially in the presence of nonthermal energetic particles. This investigation provides valuable insights into the propagation mechanisms of nonlinear DASWs in both space and laboratory plasmas containing non-extensive, nonthermal C-T-distributed ions and dust grains.

All-optical reconfigurable optical neural network chip based on wavelength division multiplexing

Optical computing has become an important way to achieve low power consumption and high computation speed. Optical neural network (ONN) is one of the key branches of optical computing due to its wide range of applications. However, the integrated ONN schemes proposed in previous works have some disadvantages, such as fixed network structure, complex matrix-vector multiplication (MVM) unit, and few all-optical nonlinear activation function (NAF) methods. Moreover, for the most compact MVM schemes based on wavelength division multiplexing (WDM), it is infeasible to employ intrinsic nonlinear effects to implement NAF, which brings frequent O-E-O conversion in ONN chips. Besides, it is also hard to realize a reconfigurable ONN with coherent MVMs, while it is much easier to implement in WDM schemes. We propose for the first time an all-optical silicon-based ONN chip based on WDM by adopting a new adjustment mechanism: optical gradient force (OGF). The proposed scheme is reconfigurable with tunable layers, variable neurons per layer, and adjustable NAF curves. In the task of classification of the MNIST dataset, our chip can realize an accuracy of 85.13% with 4 full-connected layers and only 50 neurons in total. In addition, we analyze the influence of the OGF-based NAF under fabrication errors and propose a calibration method. Compared to the previous works, our scheme has the two-fold advantages of compactness and reconfiguration, and it paves the way for the all-optical ONN based on WDM and opens the path to unblocking the bottleneck of integrated large-dimension ONNs.

Adaptive visual servoing control for uncalibrated robot manipulator with uncertain dead-zone constraint

This paper addresses the adaptive visual tracking control problem of an uncalibrated camera robot system with unknown dead-zone inputs. The uncertainties include camera extrinsic and intrinsic parameters, robot dynamic parameters, and feature depth parameters. The control achieves a better performance by establishing a smooth inverse model of the dead-zone input, which eliminates the nonlinear effect of the actuator constraint. A novel adaptive control scheme is presented which does not require a priori knowledge of the parameter intervals of dead-zone model, to update the parameter values online. Furthermore, adaptive laws are provided to estimate the uncertainties that exist both in robot and in camera models. Meanwhile, in order to avoid the singularity of the image Jacobian matrix, a projection algorithm is also introduced. Subsequently, a novel robust adaptive controller together with dead-zone compensation is established so that the tracking error image space converges to the origin. Simulations and experimental studies are conducted to verify the effectiveness of the proposed method.

Closed-form formula for unequal channel allocation to reduce FWM crosstalk in DWDM long-haul networks

Dense wavelength division multiplexing (DWDM) is considered as a mainstream solution for 5G optical transmission networks to confront increasing bandwidth demand. In such a dense multiwavelength system, the four wave mixing (FWM) non-linear effect limits the achievable transmission distance and channel capacity. For this reason, and to the best of our knowledge, a new unequal channel allocation (UCA) has been introduced in this paper based on new closed-form equations to reduce the FWM crosstalk in the DWDM optical long-haul network. The proposed channel allocation has been investigated based on several design parameters that affect FWM nonlinear crosstalk, such as total transmission distance, channel frequency spacing, the number of WDM channels, and the input power per channel. The suggested technique has further been compared with a previous model proposed by other authors to prove the effectiveness of this work. The simulation results have been examined and validated by analysing the optical spectrum analyser and the power of the FWM spectral products. Results demonstrate the reliability and the efficiency of the developed method.

A revised double diffusion Cattaneo–Christov bioconvective model for unsteady Williamson nanofluid due to Riga surface with additional nonlinear thermal sources

AbstractCurrent analysis presents the unsteady two‐dimensional flow of Williamson nanofluid with suspension of microorganisms due to stretched Riga surface with porous medium. The applications of external heat source/sink with non‐uniform relations are suggested. Furthermore, activation energy and nonlinear radiative effects are encountered. The extension in energy equation is subject to the implications of famous Cattaneo–Christov model. The problem is simplified with help of dimensionless quantities. The analytical simulations of formulated problem have been performed with help of built‐in bvp4c numerical scheme. The physical aspects of problem are presented for various flow parameters. It is claimed that velocity profile boosted due to modified Hartmann parameter while declining change in velocity profile is noted for Williamson fluid constant. The temperature field enhances for non‐uniform heat source constants. Current results convey applications in heat transfer enhancement, solar energy, extrusion processes, automobile industries, fertilizers, and so forth.

Too many friends, too little care: an exploration of the relational benefits and costs of friendship for academic self-efficacy, depression and anxiety in adolescence

ABSTRACT Our paper explores in a large Romanian sample (2168 adolescents) the relational costs and benefits of the number of friends at school. Using the MEDCURVE procedure to test the non-linear mediation effects, our results show that psychological safety, bullying and negative relations mediate the association between the number of friends and depression and anxiety, while social acceptance and bullying mediate the association between the number of friends and academic self-efficacy. In general, our results show that the relational benefits of friendship tend to diminish as the number of friends increase, in general over 9 friends (depending on the relational state) and parents, teachers and school counselors should help adolescents manage their number of friends in order to prevent the relational costs associated with engaging in too many (superficial) friendships.

Variability Effects of Meteorological Factors on Reported Malaria Cases in Kano and Lagos States of Nigeria

Abstract: Malaria is one of life’s threatening disease that contributed significantly to morbidity and mortality in Nigeria. The variability effects of meteorological factors between the Northern and Southern region of Nigeria on malaria transmission remain unclear and not well researched. This research was aimed at comparing the non-linear effects of seasonal, trend and meteorological variables on monthly malaria cases in Kano and Lagos State of Nigeria. The monthly malaria cases for age group above 5-year for Kano and Lagos State were obtained from DHIS for the period of January, 2016 to December, 2022. Also, the predictors/meteorological variables (Rainfall, Relative Humidity, Minimum Temperature and Maximum Temperature) were obtained from Nigeria Meteorological Agent. Generalized Additive Model was fitted using Negative Binomial to apply smooth function to estimate and compare the effects of the selected predictors on the malaria transmission in Kano and Lagos States. Rainfall and Maximum temperature were found not significant in explaining the effect of malaria transmission. Malaria transmission was found to be seasonal and varying in Kano State with highest transmission between September and October while the seasonal effect was reduced to linear in Lagos State. The long term trend had a significant increasing effect on malaria transmission in Kano Sate compared to non-significant effect in Lagos State. The effect of Relative Humidity was reduced to linear and increasing in the both State. Paying attention to the variability in the influence of season, trend and meteorological variables on malaria transmission will enhance respective State Government to develop an early warning and awareness that will help in controlling the malaria outbreak in their State.

Unraveling nonlinear and spatial non-stationary effects of urban form on surface urban heat islands using explainable spatial machine learning

Under global warming, surface urban heat islands (SUHI) threaten human health and urban ecosystems. However, scant research focused on exploring the complex associations between urban form factors and SUHI at the county scale, compared with rich studies at the city scale. Therefore, this study simultaneously examined the nonlinear and spatial non-stationary association between SUHI and urban form factors (e.g., landscape structure, built environment, and industrial pattern) across 2321 Chinese counties. An explainable spatial machine learning method, combining the Geographically Weighted Regression, Random Forest, and Shapley Additive Explanation model, was employed to deal with nonlinearity, spatial non-stationary, and interpretability of modeling. The results indicate the remarkable spatial disparities in the relationship between urban form factors and SUHI. Landscape structure contributes the most in southern counties, while the built environment is more important in northeastern counties. The impact of building density and building height increases with the county size and becomes the main driver of urban heat in mega counties. Most urban form factors exhibit nonlinear impacts on SUHI. For example, urban contiguity significantly affects SUHI beyond a threshold of 0.93, while building density does so at 0.17. By comparison, the influence of shape complexity remains stable above a value of 7. Factors such as industrial density and diversity have a varied influence on SUHI between daytime and nighttime. The results of local explanations and nonlinear effects provide targeted regional mitigation strategies for urban heat.

Lorentz attractor excitation-based structural damage identification using state space curvature reconstruction- enhanced transformer

Abstract Vibration-based structural damage identification has been widely investigated. Different from previous studies that analyze vibrational responses in time and frequency domains, a new Lorentz attractor excitation-based damage identification is becoming a novel strategy with the advantage of capturing the structure’s nonlinear dynamic effects. In this study, Lorentz attractor-based chaotic signals were employed as excitation signals for the structural damage identification of a frame structure. Nonlinear responses were recorded and damages of bolt looseness at different locations were considered. The structural damages could be revealed in the state-space plot of the responses. A state space curvature reconstruction method was introduced to enhance the key features of the nonlinear responses. A small-sample damage identification is performed using a deep learning algorithm – a Transformer with an accuracy of 92.38%. The advantages of the proposed method over conventional deep learning algorithms were validated. The proposed method can be applied to health conditions identification of buildings, bridges, and trusses.&amp;#xD;

Ferroelectric Semimetals with α-Bi/SnSe van der Waals Heterostructures and Their Topological Currents.

We show that proximity effects can be utilized to engineer van der Waals heterostructures (vdWHs) displaying semimetallic spin-ferroelectricity locking, where ferroelectricity and semimetallic spin states are confined to different layers, but are correlated by means of proximity effects. Our findings are supported by first principles calculations involving α-Bi/SnSe bilayers. We show that such systems support ferroelectrically switchable nonlinear anomalous Hall effect originating from large Berry curvature dipoles as well as direct and inverse spin Hall effects with giant bulk spin-charge interconversion efficiencies. The giant efficiencies are consequences of the proximity-induced semimetallic nature of low energy electron states, which are shown to behave as two-dimensional pseudo-Weyl fermions by means of symmetry analysis and first principles calculations as well as direct angle-resolved photoemission spectroscopy measurements.

Pulse component extraction and its application in simulation of pulse-like ground motions

A procedure for simulating new pulse-like ground motion based on natural pulse-like ground motion record is proposed. Firstly, an extraction method of pulse waveform based on Modified Ensemble Empirical Mode Decomposition is proposed, which reveals the relationship between half-wavelength width and pulse time-frequency information. Secondly, according to the response spectrum of the extracted non-pulse time-history, a triangular series is used to generate a stationary time-history, and then the extracted pulse component is added to the time-history, and the intensity envelope is adjusted to obtain the simulated pulse-like ground motion. Finally, the seismic response results of the Bouc-Wen-Baber-Noori model and the three-dimensional finite element model of the high-rise building are validated. It shows that the nonlinear effect of the simulated pulse-like ground motion by this method is close to that of the original natural pulse-like ground motion. The simulated pulse-like ground motion by this method can be used to analyze the inelastic response of various structures.

Identification of the Payne effect in a viscoelastic material coupling Bayesian identification and digital twin

The Payne or Fletcher-Gent effect is a particular behavior occurring in viscoelastic materials containing fillers. It induces a nonlinear dependency of the viscoelastic storage modulus on the amplitude of the applied strain. This amplitude dependency must be taken into account in engineering applications as it does change the elastodynamic behavior of the overall structure integrating the material. A methodology is developed in the proposed work to identify this nonlinear effect. The approach first starts with the identification by Bayesian inference of the frequency and damping properties of a viscoelastic sample. The input data are obtained from a modified Oberst test, conducted for different displacement load amplitudes. A digital twin of the experimental set-up is then used to evaluate the stiffness behavior, and in particular the Young's modulus of the material, at the measured frequencies, and to deduce the strain level within the sample. This work shows that the Payne effect, which leads to the decrease with the amplitude of the Young's modulus, can thus be estimated in terms of mean and standard deviation by combining experiments and numerical simulations.

High sound pressure level sound absorption in acoustic resonant metamaterials: adapting a mass-spring model for nonlinear effects

In aerospace, conventional materials as micro-perforated panels backed by cavities are used to absorb sound at high sound pressure levels. These solutions are not optimal at low frequencies compared to resonant acoustic metamaterials, which present an acoustic absorption peak with a wavelength-to-thickness ratio greater than conventional materials, i.e., a ratio&gt;&gt;5. Acoustic resonant metamaterials are mainly studied at low sound pressure levels (&lt;100dB). However, they are sensitive to increasing the amplitude of acoustic excitation. The studied metamaterial is composed of a compact array of thin single-perforation panels spaced by thin cylindrical air cavities. In a previous study, a mass-spring model was developed for low sound pressure levels. The perforations are modeled by equivalent masses, whereas cavities by equivalent springs. In the perforations, high values of the acoustic velocity lead to an increase in the acoustic resistance of the material. This effect is considered by the Forchheimer parameter in the mass-spring model. To determine this parameter and to study how it is impacted by the metamaterial geometry, the computational fluid dynamic method is used. The mass-spring model is adapted with a nonlinear term. The adapted model agrees well with simulations by finite element method at sound pressure levels up to 140dB.

Computing the dynamic response of a periodic structure coupled with a nonlinear junction using the harmonic balance method and Floquet-Bloch modelling

Structures constituted of assembled sub-components are often subject to nonlinear effects due to the presence of joints or contacts, which can induce higher-order harmonics of the source excitation. In the context of periodic structures, these nonlinearities cannot be tackled using the Floquet-Bloch theory in its usual harmonic formulation. This study hence presents an adaptation of the classical Floquet-Bloch theory to address multi-harmonic systems arising from a finite number of localized nonlinearities in periodic waveguides. We adopt the Harmonic Balance Method to recast the governing equations into a nonlinear algebraic system, which can then be solved using numerical continuation algorithms. To demonstrate the validity and benefit of this approach, the predictions derived from the proposed methodology are compared to results obtained through conventional Finite Element analysis. Excellent agreement and a notable reduction in computational cost are observed. This efficient procedure for analysing the nonlinear dynamic response of periodic waveguides opens up new possibilities in the study of damaged composite structures.