Changes In Dynamic Behavior Research Articles

Dynamic behavioural changes in an agent-based econophysics tax compliance model: bomb crater versus target effects and efficient audit strategies

We investigate a heterogeneous Ising model in the context of tax evasion dynamics, where different types of agents are parameterised via local temperatures and magnetic fields. Our work focuses on the dynamic behavioural change of agents after an audit, which either corresponds to a temporal reduction or enhancement of compliance, also known under the terms of ‘bomb crater effect’ and ‘target effect’, respectively. We analyse this effect for different types of agents: endogenously non-compliant types; agents that have a tendency to copy (non-)compliant behaviour from their social environment; ethical agents with strong endogenous moral attitudes; and random types that show large fluctuations between compliant and non-compliant behaviour. Each type influences overall tax evasion differently and our model predicts that, interestingly, increasing the audit probability can have the counter-intuitive effect of increasing tax evasion under certain circumstances. We analyse audit strategies that can suppress this effect, and thus contribute to the burgeoning literature on the actual impact of tax audits.

Bridge Load Testing for Identifying Live Load Distribution, Load Rating, Serviceability and Dynamic Response

In this article, dynamic and static load tests of a concrete highway bridge, which is a deteriorated and repaired, are presented depending on displacement and strain data for engineering decision making about the operation of a critical bridge. Static load test was carried out to determine the live load distribution factor (DF) and load-rating (RF) as well as serviceability by means of deflection limits. Modal characteristics in terms of structural frequencies and mode shapes and impact factor (IM) were identified from the dynamic load test for different truck-load and speed cases, and FE model. The distribution factor (DF) and load rating factor (RF) were also compared with those calculated according to AASHTO standard and FE model. The results showed that the distribution factor (DF) calculated by AASHTO standard gave more conservative results when compared with the experimental and FEM approaches. Similarly, the load-rating factor (RF) calculated by AASHTO standard yielded to more conservative results comparing with the experimental FEM approaches using practical distribution factors. Maximum deflections in static cases and dynamic cases were found to be within the limit calculated by (L/800) given in the AASHTO code. Impact factors among all the cases were obtained much smaller than the one recommended by AASHTO standard (33%). The modal properties were obtained to track changes in dynamic behavior due to stiffness and boundary effects as well as for finite element model calibration. The calibrated FE model of the bridge also indicated that the load carrying capacity of the bridge is adequate after repair. Finally, the results from the current study reveal that use of experimental data can be utilized to obtain load rating with minimum interruption to bridge operations through computer vision technology and methods.

Cholesterol Transport in Wild-Type NPC1 and P691S: Molecular Dynamics Simulations Reveal Changes in Dynamical Behavior.

The Niemann–Pick C1 (NPC1) protein is the main protein involved in NPC disease, a fatal lysosomal lipid storage disease. NPC1, containing 1278 amino acids, is comprised of three lumenal domains (N-terminal, middle lumenal, C-terminal) and a transmembrane (TM) domain that contains a five helix bundle referred to as the sterol-sensing domain (SSD). The exact purpose of the SSD is not known, but it is believed that the SSD may bind cholesterol, either as a part of the lipid trafficking pathway or as part of a signaling mechanism. A recent cryo-EM structure has revealed an itraconazole binding site (IBS) in the SSD of human NPC1. Using this structural data, we constructed a model of cholesterol-bound wild-type (WT) and mutant P691S and performed molecular dynamics (MD) simulations of each cholesterol-bound protein. For WT NPC1, cholesterol migrates laterally, in the direction of the lipid bilayer. In the case of P691S, cholesterol is observed for the first time to migrate away from the SSD toward the N-terminal domain via a putative tunnel that connects the IBS with the lumenal domains. Structural features of the IBS are analyzed to identify the causes for different dynamical behavior between cholesterol-bound WT and cholesterol-bound P691S. The side chain of Ser691 in the P691S mutant introduces a hydrogen bond network that is not present in the WT protein. This change is likely responsible for the altered dynamical behavior observed in the P691S mutant and helps explain the disrupted cholesterol trafficking behavior observed in experiments.

Finite Element Analysis for Time Varying Mesh Stiffness behavior of different shapes of spalling

Time Varying gear mesh stiffness is the variation of stiffness for the one contact period of a gear pair. Spalling on gear tooth is one of the most common defects in gear transmission. The loss of surface materials due to tooth spall reduces the Time-Varying Mesh Stiffness (TVMS) of the gear pair. The time varying mesh stiffness is the change in mesh stiffness for a gear pair in one contact period. The evaluation of the TVMS of the pair of gear tooth under gear tooth spalling conditions may be useful in finding its dynamic behavior or instant change in TVMS behavior may be the signal of fault developed. The potential energy method is used for analytical calculation of time varying mesh stiffness of the gear. The tooth spall may be of any shape and in this paper we have assumed the spall to be circular, triangular and elliptical and conducted analytical calculation to find TVMS and compare with healthy gear pair. The same gear pair with three shape of spall and modelled and verified through finite element analysis. The data may be used for further analysis. Also a number of shape may be modelled in future.

Model of Bio-Colonisation on Mooring Lines: Updating Strategy Based on a Static Qualifying Sea State for Floating Wind Turbines

Bio-colonisation affects the ageing of materials and the behaviour of offshore structures. Mooring systems and umbilicals belong to the family of slender bodies which are components sensitive to bio-colonisation because of a change of dynamic behaviour due to shape, roughness and mass modifications. However, this stochastic process in time and space is hard to predict. The purpose is then twofold: first, to provide a stochastic spatial model of the bio-colonisation on a mooring line; second, to show that in some defined environmental conditions, such as low wave height, low wind and current velocities, the monitoring of mooring lines tension can help to assess and reduce uncertainty on this model. Therefore, a comprehensive stochastic modelling based on mussels colonisation was carried out using on-site videotapes, experimental campaigns and expert knowledge. We studied the efficiency of a virtual sensing network using this model and a conditional entropy metric. It is first shown that the spatial model fits well with experimental data, and second that a denser medium accuracy sensor network is to be preferred to a single high accuracy fairlead sensor to reduce the uncertainty on the model parameters. It is then worth updating bio-colonisation on mooring lines during the life-time of a floating wind turbine.

Adaptation of dynamical properties of time series data and its applications in deep brain stimulation

The chaotic nature of the brain can be observed by electroencephalogram signals. This chaotic behavior can be affected by the progressive nature of neurodegenerative disorders like Parkinson disease. The gradual changes in dynamical behavior of brain can be tracked to facilitate effective and timely treatment. Deep brain stimulation (DBS) is used in therapy when the medication stops working. We investigate the use of chaotic signal as stimulus in DBS. We stimulate a simulated model of isolated neuron with different types of stimuli to see if periodicity in neuronal spiking can be disrupted and show that neuron, when stimulated with chaotic signal, does fire up in non-periodic/chaotic manner. Furthermore, as a step toward the development of our system for estimation of chaotic behavior of brain, we investigate the use of recurrent neural networks to adapt the chaotic characteristics of a chaotic time series in this research work. We explore two different setups of long short-term memory (LSTM). In first setup, we define three unique topologies of LSTM network and analyze those for chaotic parameter estimation in seven different test cases for shallow and deep networks. We show that the deep LSTM networks are capable of modeling the chaotic behavior of a wide range of parameters and that the network performs the best when the architecture is driven by chaotic attributes of the time series data. In second setup, we use LSTM network in a traditional configuration to predict the chaotic time series data and demonstrate that the LSTM network can make prediction over a range of chaotic parameters with adequate accuracy. This provides the basis for the generation of chaotic stimulation signals when required.

On Making Factories Smarter through Actionable Predictions based on Time-Series Data

The emergence of the Industrial Internet of Things paves the way for enhancing the real-time monitoring capabilities of contemporary factories. This can be materialised through sensors collecting data which can be further analysed. This paradigm enables the detection of indicators concerning systems’ degradation and facilitates corrective actions to be performed ahead of time. In this paper, we propose a damage prediction framework exploiting data that are coming from the core IT system in a steel industry use case. The novelty of our approach lies in the exploitation of Deep Learning techniques over streaming operational sensor data. To evaluate the framework, real-life data are collected and analysed based on daily operational activities enriched with the Remaining Useful Life (RUL). The Remaining Useful Life is automatically computed. We also periodically align the damage attribute, which is recorded in the planned activities and is performed by the maintenance engineers. We demonstrate the framework’s potential by conducting a quantitative and qualitative analysis to timely identify rare events based on historical data and predict dynamic behavioural changes in the manufacturing settings.

Effects of delayed immune-activation in the dynamics of tumor-immune interactions

This article presents the impact of distributed and discrete delays that emerge in the formulation of a mathematical model of the human immunological system describing the interactions of effector cells (ECs), tumor cells (TCs) and helper T-cells (HTCs). We investigate the stability of equilibria and the commencement of sustained oscillations after Hopf-bifurcation. Moreover, based on the center manifold theorem and normal form theory, the expression for direction and stability of Hopf-bifurcation occurring at tumor presence equilibrium point of the system has been derived explicitly. The effect of distributed delay involved in immune-activation on the system dynamics of the tumor is demonstrated. Numerical simulations are also illustrated for elucidating the change of dynamic behavior by varying system parameters.

MAAT

As the Internet of Things (IoT) proliferates, the potential for its opportunistic interaction with traditional mobile apps becomes apparent. We argue that to fully take advantage of this potential, mobile apps must become things themselves, and interact in a smart space like their hardware counterparts. We present an extension to our Atlas thing architecture on smartphones, allowing mobile apps to behave as things and provide powerful services and functionalities. To this end, we also consider the role of the mobile app developer, and introduce actionable keywords (AKWs)---a dynamically programmable description---to enable potential thing to thing interactions. The AKWs empower the mobile app to dynamically react to services provided by other things, without being known a priori by the original app developer. In this paper, we present the mobile-apps-as-things (MAAT) concept along with its AKW concept and programming construct. For MAAT to be adopted by developers, changes to the existing development environments (IDE) should remain minimal to stay acceptable and practically usable, thus we also propose an IDE plugin to simplify the addition of this dynamic behavior. We present details of MAAT, along with the implementation of the IDE plugin, and give a detailed benchmarking evaluation to assess the responsiveness of our implementation to impromptu interactions and dynamic app behavioral changes. We also investigate another study, targeting Android developers, which evaluates the acceptability and usability of the MAAT IDE plugin.

Нейрофизиологические механизмы аддиктивного поведения и употребления психоактивных веществ в подростковом возрасте: возможности профилактики и терапии

Поведенческие аддикции подростков, включающие употребление психоактивных веществ, являются одними из основных проблем здравоохранения большинства стран мира, в том числе России. Подростковый возраст - это период динамичных физиологических, психологических, и поведенческих изменений. Данный период также связан с повышенным риском употребления психоактивных веществ, и формированием различных аддиктивных расстройств. В подростковом возрасте происходящие изменения в нейронных системах вознаграждения, мотивации, когнитивного контроля и сопротивления стрессовым воздействиям способствуют формированию повышенного риска употреблении различных психоактивных веществ, и нехимических вариантов аддиктивной патологии. Современные патофизиологические модели возникновения аддиктивной патологии в подростковом возрасте включают данные о аллостатических изменениях функций и структуры дофаминергической системы среднего мозга, нейропластичности, связанной со стрессом, и нарушениии баланса между когнитивным контролем и процессами в системе вознаграждения. Результаты генетических и эпигенетических исследований, изучение промежуточных фенотипов / эндофенотипов могут помочь в изучении детей и подростков, входящих в группу риска возникновения аддиктивных расстройств.The use of psychoactive substances as a part of behavioral addictions of adolescents is a medical issue in most of countries all over the world, including Russia. Adolescence is a period of dynamic physiological, psychological, and behavioral changes. This period is also associated with increased risk of substance abuse and formation of various addictive disorders. In adolescence, changes in neural systems of reward, motivation, cognitive control, and resistance to stress contribute to increased risk of using various psychoactive substances and of non-chemical variants of addictive pathology. Current pathophysiological models of addictive pathology in adolescence include data on allostatic changes in functions and structure of the mid-brain dopaminergic system, neuroplasticity related with stress, and imbalance between cognitive control and processes in the reward system. Results of genetic and epigenetic studies and investigation of intermediate phenotypes / endophenotypes can help to study children and adolescents at risk of addictive disorders.

Do Helpful Mothers Help? Effects of Maternal Scaffolding and Infant Engagement on Cognitive Performance.

Infants are highly social and much early learning takes place in a social context during interactions with caregivers. Previous research shows that social scaffolding – responsive parenting and joint attention – can confer benefits for infants’ long-term development and learning. However, little previous research has examined whether dynamic (moment-to-moment) adaptations in adults’ social scaffolding are able to produce immediate effects on infants’ performance. Here we ask whether infants’ success on an object search task is more strongly influenced by maternal behavior, including dynamic changes in response behavior, or by fluctuations in infants’ own engagement levels. Thirty-five mother-infant dyads (infants aged 10.8 months, on average) participated in an object search task that was delivered in a naturalistic manner by the child’s mother. Measures of maternal responsiveness (teaching duration; sensitivity) and infant engagement (engagement score; visual attention) were assessed. Mothers varied their task delivery trial by trial, but neither measure of maternal responsiveness significantly predicted infants’ success in performing the search task. Rather, infants’ own level of engagement was the sole significant predictor of accuracy. These results indicate that while parental scaffolding is offered spontaneously (and is undoubtedly crucial for development), in this context children’s endogenous engagement proved to be a more powerful determinant of task success. Future work should explore this interplay between parental and child-internal factors in other learning and social contexts.

Testing the limits of cardiac electrophysiology models through systematic variation of current

Mathematical models of the electrical response of cardiac cells are used to help develop an understanding of the electrophysiological properties of cardiac cells. Increasingly complex models are being developed in an effort to enhance the biological fidelity of the models and potentially increase their ability to predict electrical dynamics observed in vivo and in vitro. However, as the models increase in size, they have a tendency to become unstable and are highly sensitive to changes in established parameters. This means that such models might be unable to accurately predict person-to-person variability, dynamical changes due to disease pathologies that alter ionic currents, or the effect of treatment with antiarrhythmics. In this paper, we test the predictive limits of two mathematical models by altering the conductance of Ca2+, Na+, and K+ channels. We assess changes in action potential duration (APD), rate dependence, hysteresis, dynamical behavior, and restitution as conductance is varied. We find model predictions of abrupt changes in measured quantities and differences in the predictions of the two models that might be missed in a less systematic approach. These features can be compared to experimental observations to help assess the fidelity of the models.

Theoretical modeling and nonlinear analysis of piezoelectric energy harvesters with different stoppers

This study focuses on investigating the dynamic mechanism and nonlinear analysis of a piezoelectric energy harvester with different stoppers so as to determine optimal impact energy harvesting configurations. Based on the Hamilton's principle, a set of coupled nonlinear governing equations for the energy harvesting system is established, which is then discretized by the Galerkin method. It is indicated that the energy harvester without stoppers displays a softening characteristic and this softening becomes more obvious with increasing the base acceleration. This is due to the considered geometric and inertia nonlinearities. By introducing stoppers to the harvester, however, the dynamic behavior changes from softening to hardening characteristic, owing to the induced impact force nonlinearity. Then four kinds of stoppers are compared and better stopper configurations for energy harvesting performance are picked out, following by the consideration of parametric analysis on stopper's stiffness, placed position and spacing distance. It is noted that there exists optimal parameter regions where the energy harvester can strike a balance between bandwidth and generated average power depending on excitation frequencies in surroundings.

An investigation into spatial and temporal aspects of transient stability in power systems with increasing renewable generation

This paper investigates the impact of generator dispatch (dictated by cost) and locational aspects related to renewable generation connection and consequent disconnection of synchronous generation, on transient stability. As conventional synchronous generation (SG) is displaced by power electronic converter interfaced generation (PEC), the transient behaviour of the power system may change significantly due both to the changed power flows resulting from the different locations of renewables compared with thermal plant and the different dynamic characteristics of PEC. This paper uses an AC Optimal Power Flow (OPF) to determine credible, minimum cost dispatches of generation in a test network with increasing penetration of PEC in different locations. It is found that the critical locations of the system can vary significantly with respect to economic dispatch, location of disconnection of SG and location of PEC, highlighting the increasing temporal and spatial change in system dynamic behavior.

Dynamic friction behavior of ultrananocrystalline diamond films: A depth-resolved chemical phase analysis

Investigation of dynamic changes in friction behavior of ultrananocrystalline diamond (UNCD) films is a complex mainly because of the rapid change in chemical composition at the sliding interfaces. To address this issue, for the first time, we report chemical phase analysis of transferfilm using the depth-resolved X-ray photoelectron spectroscopy (XPS) technique. The friction coefficient of the UNCD films was high during the initial run-in regime, but it gradually decreased to an ultralow value after longer sliding cycles at the ambient atmospheric tribo-condition. Depth-resolved XPS analysis showed a higher sp3/sp2 carbon ratio during the initial run-in regime. This ratio decreased with increasing sliding cycles and consequently the friction coefficient decreased. However, a higher value of the friction coefficient throughout the run-in regime persisted at the high-vacuum tribo-condition. In this case, the sp3/sp2 carbon ratio inside the transferfilm was quite high and no considerable changes were observed in the depth-resolved XPS analysis. This investigation confirmed that the dynamic friction behavior in UNCD films was manipulated by the sp3/sp2 carbon ratio inside the transferfilm which showed tribo-atmospheric dependence.

Shooting a high-density electroencephalographic picture on sleep in children with attention-deficit/hyperactivity disorder.

Sleep-related slow-wave activity (SWA) has been recognized as a marker of synaptic plasticity. In children affected by attention deficit hyperactivity disorder (ADHD), SWA is mainly located in the central rather than frontal regions, reflecting a maturational delay. A detailed subjective and objective sleep investigation, including a full night video-polysomnography (PSG-HD-EEG), was performed on 30 consecutive drug naïve outpatients with a diagnosis of ADHD. They received a diagnosis of sleep disorders in 29/30 cases, and most of them had a past history of sleep problems. They had a higher apnea-hypopnea index at PSG, and slept less than 9 hr at actigraphy. We aimed to describe the SWA behavior in the same group of children with ADHD. The full-night PSG-HD EEG of children with ADHD was compared with the one of the 25 healthy controls. The scalp SWA mapping, the decrease of SWA during the night, and the EEG source of SWA were analyzed. At scalp topography, the focus of SWA was observed over the centro-parietal-occipital regions in participants with ADHD (p < 0.01), which remained significant in the subgroups divided between subgroups according to the sleep diagnosis (p < 0.01). The physiological decrease in SWA was more evident in control participants. The source analysis revealed a greater delta power over the posterior cingulate in participants with ADHD (p < 0.01). Our results confirm static and dynamic changes in SWA behavior in children with ADHD, which may reflect a maturational delay occurring at a vulnerable age, as a consequence of chronic sleep deprivation.

A Sequence-Based Damage Identification Method for Composite Rotors by Applying the Kullback–Leibler Divergence, a Two-Sample Kolmogorov–Smirnov Test and a Statistical Hidden Markov Model

Composite structures undergo a gradual damage evolution from initial inter-fibre cracks to extended damage up to failure. However, most composites could remain in service despite the existence of damage. Prerequisite for a service extension is a reliable and component-specific damage identification. Therefore, a vibration-based damage identification method is presented that takes into consideration the gradual damage behaviour and the resulting changes of the structural dynamic behaviour of composite rotors. These changes are transformed into a sequence of distinct states and used as an input database for three diagnostic models, based on the Kullback–Leibler divergence, the two-sample Kolmogorov–Smirnov test and a statistical hidden Markov model. To identify the present damage state based on the damage-dependent modal properties, a sequence-based diagnostic system has been developed, which estimates the similarity between the present unclassified sequence and obtained sequences of damage-dependent vibration responses. The diagnostic performance evaluation delivers promising results for the further development of the proposed diagnostic method.

Effect of inertia heterogeneity on frequency dynamics of low‐inertia power systems

Based on fundamental dynamic simulation principles and illustrative case studies, this study aims to identify key changes in the dynamic behaviour of the system due to the high penetration of renewable energy sources (RES) affecting frequency dynamics and provide guidelines for performing frequency stability analysis in low-inertia power systems with a large penetration of RES. First, a critical comparison of the frequency responses obtained using a system equivalent model and a detailed dynamic model following an active power disturbance are presented. It is then demonstrated, using detailed dynamic models of two multi-area systems, such that when the proportion of RES prevails over the share of synchronous generator (SG), the dynamic coupling among areas (even separated by short-medium length lines) reduces and the inertia of the system should be considered as heterogeneous instead of a global parameter. Following this, the study discusses how frequency dynamics may be strongly and complexly affected by the physical characteristics of converter-connected generation leading to increased frequency and voltage interactions when the proportion of converter connected RES becomes greater than SG. The resulting changes in the system's dynamic behaviour due to frequency and voltage interactions can increase the actual active power imbalance size following a credible contingency so that careful considerations to protect the system against an excessively high rate of change of frequency should be made. In order to evaluate the extent of this change in system dynamic behaviour, an appropriate dynamic model of the network should be used with adequate multi-area representation of RES and loads.

An investigation on Monod–Haldane immune response based tumor-effector–interleukin-2 interactions with treatments

In this article, a mathematical model with time delay describing tumor immune interaction with Monod–Haldane kinetic response is proposed to reveal the dynamics of related inter-cellular phenomena. Positivity of the solutions, boundedness and uniform persistence of the system are determined to ensure the well-posedness of the system. The local stability of equilibria is studied as well as the length of the delay to preserve the stability is estimated for providing the mechanism of action to control the oscillation in tumor growth. Transcritical bifurcation using Sotomayer’s theorem and Hopf bifurcation are investigated analytically and numerically. Global stability is examined before the commencement of sustained oscillations using a suitable Lyapunov function. To observe the influence of tumor growth due to uncertainty in input parameters, Latin hypercube sampling based uncertainty analysis is performed followed by sensitivity analysis. Computer simulation results are illustrated to elucidate the change of dynamical behavior due to the change of system parameters.

An investigation of hygrothermal aging effects on high strain rate behaviour of adhesively bonded composite joints

Composite materials have vast range of engineering applications because of their outstanding mechanical performance, low density and cost effectiveness. Marine industry and naval structures are one of the applications where composites are gaining importance rapidly however, there are confronted with extreme environmental conditions in addition mechanical behaviour. Therefore, it is important to comprehend the behaviour of these materials not only under mechanical loads but also under environmental effects. For that reason, the objective of this paper is to study the effects of hygrothermal aging phenomenon on the behaviour of adhesively bonded composite joints at high strain rates. Dynamic compressive properties and microstructural damage progression is analysed utilizing the Split Hopkinson Pressure Bars (SHPB) technique. The stress-strain behaviour of composite specimens subjected to severe hygrothermal conditions have been studied at high strain rates ranging from 445 to 1240 s−1. In addition, Keyence and scanning electron microscopic (SEM) is used to study the significant damage modes. The results indicated change in dynamic properties and damage behaviour because of the environmental effects.