Dynamic Analysis Research Articles

Impact of climate risk on energy market risk spillover: Evidence from dynamic heterogeneous network analysis

Using meteorological monitoring data from eight climate disasters across the globe, the Climate Policy Uncertainty (CPU) Index, and the financial data of eight energy markets between 2010 and 2020, this study employs the fixed base extreme difference entropy method to construct a Climate Risk Index (CRI) and investigates the impact of climate risk on the risk spillover among energy markets based on dynamic heterogeneous network analysis. The results confirm that the CRI fluctuated periodically and exhibited an upward trend during the sample period. In terms of risk spillover, the oil, geothermal, and fuel cell markets act as risk receivers, whereas the gas, wind, and bioenergy markets functions as risk emitters. Climate risk significantly increases the network complexity between energy markets and the risk spillover of gas, solar, water, and wind markets but decreases the risk spillover of oil, bioenergy, fuel cells, and geothermal markets. Additionally, the fossil fuel market is more sensitive to climate risk than is the renewable energy market.

Single gene analysis in yeast suggests nonequilibrium regulatory dynamics for transcription

Fluctuations in the initiation rate of transcription, the first step in gene expression, ensue from the stochastic behavior of the molecular process that controls transcription. In steady state, the regulatory process is often assumed to operate reversibly, i.e., in equilibrium. However, reversibility imposes fundamental limits to information processing. For instance, the assumption of equilibrium is difficult to square with the precision with which the regulatory process executes its task in eukaryotes. Here we provide evidence — from microscopic analyses of the transcription dynamics at a single gene copy of yeast — that the regulatory process for transcription is cyclic and irreversible (out of equilibrium). The necessary coupling to reservoirs of free energy occurs via sequence-specific transcriptional activators and the recruitment, in part, of ATP-dependent chromatin remodelers. Our findings may help explain how eukaryotic cells reconcile the dual but opposing requirements for fast regulatory kinetics and high regulatory specificity.

Clustering Individuals Based on Similarity in Idiographic Factor Loading Patterns.

Idiographic measurement models such as p-technique and dynamic factor analysis (DFA) assess latent constructs at the individual level. These person-specific methods may provide more accurate models than models obtained from aggregated data when individuals are heterogeneous in their processes. Developing clustering methods for the grouping of individuals with similar measurement models would enable researchers to identify if measurement model subtypes exist across individuals as well as assess if the different models correspond to the same latent concept or not. In this paper, methods for clustering individuals based on similarity in measurement model loadings obtained from time series data are proposed. We review literature on idiographic factor modeling and measurement invariance, as well as clustering for time series analysis. Through two studies, we explore the utility and effectiveness of these measures. In Study 1, a simulation study is conducted, demonstrating the recovery of groups generated to have differing factor loadings using the proposed clustering method. In Study 2, an extension of Study 1 to DFA is presented with a simulation study. Overall, we found good recovery of simulated clusters and provide an example demonstrating the method with empirical data.

Dynamic functional connectivity correlates of trait mindfulness in early adolescence

BackgroundTrait mindfulness, the tendency to attend to present-moment experiences without judgement, is negatively correlated with adolescent anxiety and depression. Understanding the neural mechanisms underlying trait mindfulness may inform the neural basis of psychiatric disorders. However, few studies have identified brain connectivity states that correlate with trait mindfulness in adolescence, nor have they assessed the reliability of such states. MethodsTo address this gap in knowledge, we rigorously assessed the reliability of brain states across 2 functional magnetic resonance imaging (fMRI) scan from 106 adolescents aged 12 to 15 (50% female). We performed both static and dynamic functional connectivity analyses and evaluated the test-retest reliability of how much time adolescents spent in each state. For the reliable states, we assessed associations with self-reported trait mindfulness. ResultsHigher trait mindfulness correlated with lower anxiety and depression symptoms. Static functional connectivity (ICCs from 0.31-0.53) was unrelated to trait mindfulness. Among the dynamic brains states we identified, most were unreliable within individuals across scans. However, one state, an hyperconnected state of elevated positive connectivity between networks, showed good reliability (ICC=0.65). We found that the amount of time that adolescents spent in this hyperconnected state positively correlated with trait mindfulness. ConclusionsBy applying dynamic functional connectivity analysis on over 100 resting-state fMRI scans, we identified a highly reliable brain state that correlated with trait mindfulness. The brain state may reflect a state of mindfulness, or awareness and arousal more generally, which may be more pronounced in those who are higher in trait mindfulness.

Real-time IMU-Based Kinematics in the Presence of Wireless Data Drop.

Wireless inertial motion capture holds promise for real-time human-machine interfaces and home-based rehabilitation applications. However, wireless data drop can cause significant estimation errors deteriorating performance or even making the system unusable. It is currently unclear how to estimate non-periodic kinematics with wearable inertial measurement units (IMUs) in the presence of wireless data drop (packet loss). We thus propose a novel inference encoder-decoder network model for real-time kinematics during dynamic movement. Twenty-four healthy subjects performed yoga, golf, swimming, dance, and badminton movement activities while wearing IMUs and 10-90% of each IMU's data were randomly removed to determine the effects of data drop on estimation accuracy with and without the proposed model. Results demonstrated a reduction in RMSE of 45.2% to 51.5% in the upper limb kinematic estimation of the proposed model compared to the No Prediction strategy, and a reduction of 19.1% to 31.3% of the proposed model compared with an baseline LSTM model. In addition, the proposed model has significantly less error (p<0.05) than the No Prediction strategy and the baseline LSTM model for 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80% data drop. These results could enable wearable, wireless IMU dynamic motion analysis and assessment with reduced kinematic estimation error in the presence of varying amounts of wireless data drop and thus could further facilitate human-machine interaction and home-based medical assessment and treatment.

Dynamic bending analysis of metallized silicon nitride substrate during thermal cycling via digital image correlation

Dynamic bending analysis of metallized silicon nitride substrate during thermal cycling via digital image correlation

Research on emergency decision quality evaluation and optimization basing on public sentiment big data analysis

The increasingly frequent occurrence of emergencies has led to significant losses, both human and economic. It is of the utmost importance to scientifically and effectively formulate emergency decision to prevent and reduce these losses. In this study, an evaluation model is developed for evaluating emergency decision quality based on fuzzy comprehensive evaluation method. The proposed model takes into consideration of the impact of public sentiment appeals on emergency decision in emergencies with the purpose of improving emergency decision quality. The “3·21” major explosion accident in Xiangshui County, Jiangsu Province, China, in March of 2019, is selected as a typical case, and the public sentiment big data is obtained from Weibo. The Latent Dirichlet Allocation (LDA) model and the TF-IDF algorithm are utilized to develop an emergency decision quality evaluation index system, from which public sentiment appeals are extracted and quantified. Furthermore, this study explores the changes of public sentiment attitude towards emergency decision through static and dynamic public sentiment analysis. Based on this, the emergency decision quality for the case event is evaluated by the proposed model. The effectiveness of the proposed approach is demonstrated with in-depth discussion and validation through this real case. The results indicate that the emergency decision quality of the Chinese government in this case is fairly good, yet exhibit room for further improvement. Optimization advice for emergency decision in emergencies is proposed accordingly. Empirical evidence suggests that the model proposed in this study can provide theoretical and methodological support for emergency response and government decision-making in the era of big data.

Rigid-flexible coupling dynamic modelling and dynamic accuracy analysis of planar cam four-bar mechanism with multiple clearance joints

Rigid-flexible coupling dynamic modelling and dynamic accuracy analysis of planar cam four-bar mechanism with multiple clearance joints

Investigation of the Filling of a Spherical Pore Body with a Nonwetting Fluid: A Modeling Approach and Computational Fluid Dynamics analysis

Investigation of the Filling of a Spherical Pore Body with a Nonwetting Fluid: A Modeling Approach and Computational Fluid Dynamics analysis

Dynamic analysis of planetary gear transmission based on Lagrange interpolation polynomials

Dynamic analysis of planetary gear transmission based on Lagrange interpolation polynomials

Dynamics modeling and fault diagnosis of flexible thin-walled elliptical bearings in harmonic reducers

Harmonic reducers, crucial in industrial robots for their high load capacity and low friction, often rely on Flexible Thin-Walled Bearings (FTWBs). However, these bearings are particularly prone to failure due to the cyclic alternating stress loads they experience, stemming from their unique elliptical structure. This study presents a dynamic model for the Flexible Thin-Walled Bearing (FTWB) using a finite element approach. Stress distribution and motion characteristics were analyzed, revealing maximum stress at major and minor axis positions during operation. The model was tested under three conditions: normal, outer ring fault, and inner ring fault. A vibration test rig was constructed to gather real vibration signals, enabling model validation and analysis of vibration signal characteristics under different conditions. This research sheds light on the mechanisms of impact and fault signal generation in FTWBs, offering valuable insights for dynamic analysis and fault diagnosis in FTWBs and harmonic drives.

The impact of global uncertainties on the spillover among the European carbon market, the Chinese oil futures market, and the international oil futures market

This paper employs the TVP-VAR-DY model to investigate the spillover among the European carbon market (EUA), the Chinese oil futures market (INE), and the Brent oil futures market (Brent) and explores whether their spillovers affect their volatility. Furthermore, we explore the impact of global uncertainties about the economy, finance, and geopolitics on their spillovers. The static analysis shows INE as a spillover receiver and EUA and Brent as transmitters. Dynamic analysis reveals spillover peaks during the COVID-19 pandemic. Furthermore, volatilities are positively influenced by spillovers among them. Finally, economic and financial uncertainties increase spillovers, while geopolitical uncertainties decrease them.

Experimental and numerical investigation on seismic performance of novel cable-restraining composite rubber bearings for highway bridges

Introducing cable restrainers into isolation bearings is promising to enhance the seismic performance of highway bridges. However, limitations exist in cost, performance, and analysis models of current products typically composed of flat sliding bearings (FBs) and separated cables. Therefore, this study proposes a novel cable-restraining composite rubber bearing (CRCRB) comprising a composite rubber bearing (CRB) as the bearing body and continuous cables. Cyclic tests were conducted on 12 specimens, including cable-restraining FBs and CRCRBs. Then, restoring force models of the bearing bodies were developed via theoretical analysis. Those of the cables were obtained from numerical models based on derived cable profiles. Finally, incremental dynamic analysis (IDA) was performed to evaluate the effects of the CRCRBs and cable models on structural responses. The test results verify the feasibility of the new cable layout and the advantages of the CRBs as the bearing body in restoring force, damping capacity, and residual displacement. As both the radii of the curved segments and the inclination angle of the linear one in the cable profiles decreased, the cable stiffness kept rising during loading. Cable sliding at clamps enlarged the cable-free displacement and residual deformation, and was relieved by adding clamps. The proposed models fit the test data well. The IDA results illustrate the superiority of the CRCRBs in mitigating bridge damage and highlight the importance of using the precise multi-linear cable model instead of the simplified linear one to avoid overestimating responses.

Comparative Study on Mechanical Response in Rigid Pavement Structures of Static and Dynamic Finite Element Models

The safety of airport runways is important to guarantee aircraft taking-off, landing, and taxiing, and the comparison of the mechanical response of pavement structures under dynamic and static loading by LS-DYNA has rarely been studied. The purpose of this work is to separate two analysis methods to investigate the mechanical response of rigid airport pavements. Firstly, a tire–road coupling model of an airfield was established to evaluate the suitability of dynamic and static analyses. Then, the effects of landing pitch angles, sinking speeds, and tire pressures on the effective stress, effective strain, and z-displacement of the runway were investigated for both dynamic and static analysis. Finally, the significance of influence factors was analyzed by regression analysis in Statistical Product and Service Solutions (SPSS). The results indicated that the effective stress, effective strain, and z-displacement of the runway increased with a decrease in the landing pitch angle, which also increased with an increase in the sinking speed and tire pressure. It was demonstrated that the difference in pavement mechanical response between dynamic and static analyses progressively widened at high tire pressure and sinking speed. In other words, the static analysis method can be adopted to assess the dynamic mechanical behavior when the landing pitch angle is large and the tire pressure is small. Among the various factors of mechanical response, the effect of tire pressure was the most obvious, followed by sinking speed and landing pitch angle. The work proposes a new approach to understanding the mechanical behavior of runways under complicated and varied conditions, evaluates the applicability of the dynamic and static mechanical analysis methods, identifies key factors in the dynamic and static mechanical analysis of rigid runways, and provides technical support for improving and maintaining the impact resistance of pavement facilities.

Laplace-Logistic Unit Distribution with Application in Dynamic and Regression Analysis

This manuscript presents a new two-parameter unit stochastic distribution, obtained by transforming the Laplace distribution, using a generalized logistic map, into a unit interval. The distribution thus obtained is named the Laplace-logistic unit (abbreviated LLU) distribution, and its basic stochastic properties are examined in detail. Also, the procedure for estimating parameters based on quantiles is provided, along with the asymptotic properties of the obtained estimates and the appropriate numerical simulation study. Finally, the application of the LLU distribution in dynamic and regression analysis of real-world data with accentuated “peaks” and “fat” tails is also discussed.

Site response analysis by generating a new 3d mesh design with surface topography: a 3d site response analysis of northwest Turkey

AbstractPredicting soil behavior under dynamic load due to earthquakes is pivotal for engineering structures and human life. Due to various limitations, such as insufficient computers and difficulties in generating models, the third-dimension effect is generally neglected in many studies. Conversely, the third-dimension effect in regions with high topographic differences, deep basins, three-dimensional heterogeneous and anisotropic environments, and alluvium is at a level that cannot be neglected. This study created a three-dimensional model of the northwest of Turkey for the first time by including surface topography. Soil properties were added to this model, and dynamic analysis was performed. This new model aims to increase the accuracy of ground motion predictions in Northwest Turkey. The accuracy of this model was analyzed using real earthquake data recorded in the study area. In addition, a new software (SiteEffect3D) with various features has been developed to create a three-dimensional mesh with topography using digital elevation model data and to perform dynamic analysis more effectively. This software has been tested comparatively with “Plaxis 3D” software using synthetic terrain models. The importance of this study is that in addition to its contributions to site response analysis and seismic hazard assessment, new software has been developed that can be used in similar studies. The findings will provide valuable information for seismic design and construction practices and facilitate the development of more effective strategies to reduce the potential damage from earthquakes in the region.

Convex equilibrium‐free stability and performance analysis of discrete‐time nonlinear systems

AbstractThis paper considers the equilibrium‐free stability and performance analysis of discrete‐time nonlinear systems. Two types of equilibrium‐free notions are considered. Namely, the universal shifted concept, which considers stability and performance w.r.t. all equilibrium points of the system, and the incremental concept, which considers stability and performance between trajectories of the system. This paper shows how universal shifted stability and performance of discrete‐time systems can be analysed by making use of the time‐difference dynamics. Moreover, the existing results are extended for incremental dissipativity for discrete‐time systems based on dissipativity analysis of the differential dynamics to more general state‐dependent storage functions for less conservative results. Finally, it is shown how both these equilibrium‐free notions can be cast as a convex analysis problem by making use of the linear parameter‐varying framework, which is also demonstrated by means of an example.

Perturbing the Stable Accretion Disk in Kerr and 4D Einstein–Gauss–Bonnet Gravities: Comprehensive Analysis of Instabilities and Dynamics

The study of a disturbed accretion disk holds great significance in the realm of astrophysics, as such events play a crucial role in revealing the nature of disk structure, the release of energy, and the generation of shock waves. Consequently, they can help explain the causes of X-ray emissions observed in black hole accretion disk systems. In this paper, we perturb the stable disk formed by spherical accretion around Kerr and Einstein–Gauss–Bonnet (EGB) black holes. This perturbation reveals one- and two-armed spiral shock waves around the black hole. We find a strong connection between these waves and the black hole spin parameter (a/M) and the EGB coupling constant (α). Specifically, we find that as α increases in the negative direction, the dynamics of the disk and the waves become more chaotic. Additionally, we observe that the angular momentum of the perturbing matter significantly affects mass accretion and the oscillation of the arising shock waves. This allows us to observe changes in QPO frequencies, particularly, perturbations with angular momentum matching the observed C−type low-frequency QPOs of the GRS 1915+105 source. Thus, we conclude that the possibility of the occurrence of shock waves within the vicinity of GRS 1915+105 is substantial.

Study of effect of dibenzoylmethane on thermal stability of PVC films stabilized with magnesium and zinc pentaerythritates

Static and dynamic thermal analysis of the destruction of PVC fi lms, as well as isothermal and non-isothermal thermogravimetric analysis (TGA) of PVC films stabilized with magnesium and zinc pentaerythritates with the addition of dibenzoylmethane as a synergistic additive were carried out.

Repercussion of Fiber Content on the Mechanical, Thermal, and Thermomechanical Properties of Natural Fibers Reinforced Thermoplastic Composites for Automotive Application

Abstract Natural fibers are becoming very popular as a reinforcement in composite materials owing to their benefits, such as low-price, lightweight, availability, and environmental friendliness. In this study, abaca fiber-reinforced polypropylene (PP) and high-density polyethylene (HDPE) composites were created with the help of the injection molding method. Prior to composite fabrication, abaca fibers were chemically treated with a 5 wt.% caustic soda (NaOH) solution to improve the bonding between the abaca fibers and the matrix and to enhance their properties. Scanning electron microscopy (SEM) was utilized to assess the fiber surface microstructures before as well as after the chemical treatment, along with the fractured surfaces of tensile specimens. The mechanical properties, such as tensile, bending, and impact strength, of abaca/PP and abaca/HDPE composites were evaluated and compared. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) methods were utilized to investigate the thermal behaviour of composites. Also, the dynamic mechanical analysis (DMA) method was utilized to explore the thermomechanical properties of the fabricated composites. The outcomes of the experimental findings showed that abaca/PP composite with 10 and 20 wt.% fibers is the best choice of material to be used in the automobile industry.&amp;#xD;