Dynamic Characteristics Research Articles

Thumbnail-Preserving Encryption Based on Binary–Decimal Hybrid and a Generalized Coupled Logistic Map

Traditional image encryption methods typically make a trade-off between privacy protection and visual usability. To address this issue, a novel thumbnail-preserving encryption scheme is proposed based on a hybrid of decimal and binary pixel values in three pixel groups, utilizing the excellent dynamic characteristics of a generalized coupled logistic map. Theoretically, it is proved that the core algorithm of this scheme is sum-preserving. Experimentally, it is demonstrated that this scheme not only excels in efficiency and resistance to attacks, effectively safeguarding image privacy, but also retains high-quality thumbnails after encryption, achieving both objectives of image privacy protection and visual usability.

Molecular docking and molecular dynamics of hypoxia-inducible factor (HIF-1alpha): towards potential inhibitors

HIF-1α is a primary regulator in the adaptation of cancer cells to hypoxia. The aim was to find out new inhibitors of the HIF-1α. A molecular dynamic (MD) simulation performed on HIF-1α showed stable dynamic features. Virtual screening of 217 anticancer drugs was performed along with a positive control (2-Methoxyestradiolm, 2-ME2) on an optimized HIF-1α and dynamically simulated structure. Docking results produced two compounds namely pycnidione and nilotinib of high binding affinity −9.34 kcal/mol and −9.04 kcal/mol respectively, whereas 2-ME2 displayed a relatively lower affinity (-6.68 kcal/mol). For the three complexes, MD of 200 ns simulation was run. Data analysis showed that the three medications behaved similarly in the MD simulation. Nilotinib had a lower RMSD and higher SASA than the other complexes. In addition, the Nilotinib-HIF-1α combination had a lower RMSF value, a flatter Rg, and a number of hydrogen bonds similar to other complexes. MM-GBSA analysis revealed that nilotinib, pycnidione and 2-ME2 compounds had free binding energy of −23.77 ± 5.29, −21.85 ± 4.24 and −7.53 ± 6.62 kcal/mol respectively. Nilotinib and pycnidione bind competitively to HIF-1α, with nilotinib showing consistent molecular-dynamic properties. They relatively pass the blood-brain barrier, non-carcinogenic, and have IV-category acute oral toxicity. They have low CYP inhibitory characteristics. Further investigations are therefore warranted to elucidate their implications in hypoxia pathways, cell proliferation, apoptosis, survival, and metastatic potential.

Changes in the soil and vegetation cover of the Kochubey biosphere station under global warming in recent years

Objectives: The study and long-term observations of changes in the spatial structure of vegetation cover of pasture landscapes of the Kochubey Biosphere Station (KBS) due to global climate warming. Arid pasture landscapes, due to the peculiarities of their spatial structure (the presence of semi-desert vegetation groupings) are a good indicator of modern climatic changes. To achieve this goal, the spatial structure and the current state of the arid landscapes of the Northwestern Caspian Sea in the territory of the KBS have been studied. The analysis of the biological diversity of species was carried out. Also the characteristics of the common features of seasonal dynamics of landscapes were studied. Moreover, trends of climatic changes in the landscape structure of the territory and trends in anthropogenic transformation of arid landscapes of the region were identified. It has been revealed that the main reasons for the reduction of biodiversity are habitat fragmentation, the introduction of alien species, the settlement of native species outside the range, ecotonization and “islandization” of pasture ecosystems, and the displacement of range boundaries. Since the goal of preserving the components of vegetation biodiversity is to reduce the pressures caused by climate change, adaptation measures should be aimed at reducing the rate of fragmentation and degradation of pasture landscapes. Monitoring observations have shown that over the last 20-century period there have been rhythmically repeating changes in climate and soil and vegetation cover, which indicates high mobility of vegetation. It has been established that the contribution of anthropogenic land degradation to desertification is confirmed by a significant linear trend in interannual fluctuations in indicators of pasture digression in the region. It has been established that the contribution of anthropogenic land degradation to desertification is confirmed by a significant linear trend in interannual fluctuations in indicators of pasture digression in the region. Due to excessive pasture digression, “islands” of anthropogenic desertification are formed here, the lifespan of which is determined by human influence and precipitation fluctuations.

Dynamic response characteristics and linearization of liquid crystal cladding waveguide beam scanner

Dynamic response characteristics and linearization of liquid crystal cladding waveguide beam scanner

Backup subscription scheme for differential protection using IEC61850-9-2 sampled values

In IEC-61850-based digital substations, the protection IED’s performance is dependent on merging unit’s vendor implementation, communication networks, and measurement circuit’s health conditions. As the process bus Sampled Value(SV) enables the availability of all sensor data on a communication network, this paper proposes a Backup Subscription scheme (BSS) for a transformer differential protection (87T, PDIF) function. BSS utilizes sensor data in digital substations to achieve a flexible protection scheme using a dynamic subscription feature. Thus, in case of failure of one sensor, differential protection would be maintained. The paper presents the implementation and verification of a prototyped scheme using a Hardware-in-the-loop simulation test bed. The main result is that BSS integration into differential protection ensures its dependability and security. Moreover, delay compensation and seamless switching feature increases the availability of differential protection.

Dynamic Testing and Finite Element Model Adjustment of the Ancient Wooden Structure Under Traffic Excitation

In situ dynamic testing is conducted to study the dynamic characteristics of the wooden structure of the North House main hall. The velocity response signals on the measurement points are obtained and analyzed using the self-interaction spectral method and stochastic subspace method, yielding natural frequencies, mode shapes, and damping ratios. This study reveals that the natural frequencies and damping ratios are highly consistent between the two methods. Therefore, to eliminate errors, the average of the results from both modal identification methods is taken as the final measured modal parameters of the structure. The natural frequencies of the first and second order in the X direction were 2.097 Hz and 3.845 Hz and in the Y direction were 3.955 Hz and 5.701 Hz. The modal frequency in the Y direction of the structure exceeds that in the X direction. Concurrently, a three-dimensional finite element model was established using ANSYS 2021R1, considering the semi-rigid properties of mortise–tenon connections, and validated based on in situ dynamic testing. The sensitivity analysis indicates adjustments to parameters such as beam–column elastic modulus, tenon–mortise joint stiffness, and roof mass for finite element model refinement. Modal parameter calculations from the corrected finite element model closely approximate the measured modal results, with maximum errors of 9.41% for the first two frequencies, both within 10% of the measured resonant frequencies. The adjusted finite element model closely matches the experimental results, serving as a benchmark model for the wooden structure of North House main hall. The validation confirms the rationality of the benchmark finite element model, providing valuable insights into ancient timber structures along transportation routes.

Observing the dynamic community structure of urban travel networks based on navigation data

Dynamic community division is crucial for comprehending the interactive structure and mechanism between residents and space. Currently, there is insufficient research on dynamic community changes in travel networks regarding travel distance. This study utilizes residents’ travel trajectories to construct a multi-layer network based on travel purposes. The study establishes methods for identifying travel network communities and analyzing community evolution influence. Dynamic characteristics of travel network communities at different distances are extracted. Results show that within 3–7 km travel distance, different travel network communities exhibit continuous spatial aggregation, whereas beyond 11 km, heterogeneity is observed. Moreover, communities within 3-7 km experience drastic dynamic evolution, whereas beyond 7 km, they tend to stabilize, forming a large-scale and fixed travel mode. This study enriches the dynamic interaction research of functional space from the perspective of distance, and the experimental results provide an effective reference for urban planning and management.

Dynamic analysis and application of network structure control in risk conduction in the industrial chain

According to control theory, a dynamical system is controllable if, with a suitable choice of inputs, it can be driven from any initial state to any desired final state within a finite time. Most dynamic characteristics of real networks are nonlinear, so achieving target control is more practical and necessary. The network’s control energy is also a problem that must be considered. Whether and how to control the complex system of the industrial chain has high theoretical and practical significance. In this study, we use the GARCH model, DCC model, and network structure control theory comprehensively to study the price fluctuation risk of the mining stock market from the perspective of the industry chain and network control dynamics and obtain interesting results. (1) Risk conduction among stocks has a prominent industry-driving effect, and the risk conduction ability of upper and middle stocks is stronger. (2) The risk regulation cost, time cost, and node number cost of the whole-industry chain are all higher than those of the two-tier chain, which indicates that the correlation complexity of the network has a positive relationship with risk control. (3) Key risk nodes play an essential role in risk control, so monitoring key stocks from the industrial chain perspective is necessary to control risks in time. This work can provide valuable suggestions for market regulators and policy-makers in terms of risk management and control.

Fracture Mode and Thermal Damage Evolution of Sandstone Under the Coupling Effect of Thermal Treatment and Impact Load

The dynamic properties of high-temperature sandstone quickly deteriorate with different cooling methods, which leads to the instability of underground engineering rock structures. Therefore, it is of great significance to quantify the changes in the dynamic characteristics of high-temperature cooled sandstone under impact loads. Therefore, the sandstone is heated to different temperatures and cooled using three methods. A dynamic tensile test is performed using the Splitting Hopkinson Pressure Bar (SHPB) test set for high-temperature cooled sandstone. At the same time, the transient process of rock failure was examined using high-speed cameras. The influence of different temperatures and cooling methods on the thermal damage value of sandstone was analyzed, and the prediction equation was formed. The change in rock energy during rock failure under impact load was calculated.

Modeling of Static Stress Identification Using Electromechanical Impedance of Embedded Piezoelectric Plate.

Working stress is an important indicator reflecting the health status of structures. Passive-monitoring technology using the piezoelectric effect can effectively monitor the dynamic stress of structures. However, under static loads, the charge generated by the piezoelectric devices can only be preserved when the external circuit impedance is infinitely large, which means passive-monitoring techniques are unable to monitor static and quasi-static stress caused by slow-changing actions. In current studies, experimental observations have shown that the impedance characteristics of piezoelectric devices are affected by external static loads, yet the underlying mechanisms remain inadequately explained. This is because the impedance characteristics of piezoelectric devices are actually dynamic characteristics under alternating voltage. Most existing impedance analysis models are based on linear elastic dynamics. Within this framework, the impact of static stress on dynamic characteristics, including impedance characteristics, cannot be addressed. Accounting for static stress in impedance modeling is a challenging problem. In this study, the static stress applied on an embedded piezoelectric plate is abstracted as the initial stress of the piezoelectric plate. Based on nonlinear elastic dynamic governing equations, using the displacement method, an impedance analysis model of an embedded piezoelectric plate considering initial stress is established and verified through a fundamental experiment and a finite element analysis. Based on this, the explicit analytical relation between initial stress and impedance characterizations is provided, the mechanism of the effect of initial stress on the impedance characterizations is revealed, and procedures to identify static stress using impedance characterizations is proposed. Moreover, the sensitivities of the impedance characterizations in response to the initial stress are thoroughly discussed. This study mainly provides a theoretical basis for monitoring static stress using the electromechanical impedance of an embedded piezoelectric plate. And the results of the present study can help with the performance prediction and design optimization of piezoelectric-based static stress sensors.

Real-Time Accuracy Evaluation of Arterial Catheter Transducer Systems

IntroductionArterial pressure is currently monitored in ICU with a catheter–transducer fluid line. This fluid filled tubing line distorts the original waveform due to its dynamic characteristics (natural frequency, Fn, and damping coefficient, z), introducing potentially significant errors when calculating the cardiac output from pulse contour signal analysis. MethodsIn our study, we cross-compared Fn and z obtained with our new Fast External Pressure Test (FEPT) and with the Fast Flush Test (FFLT), to the reference technique (Sine wave variable Frequency Analysis Test - SFAT). It was carried on a testbench for 48 hours. Fn and z were measured using the three techniques with two fluid-filled tubing lines (standard, STD, and blood conserving device, BCD). ResultsFn measurements with FEPT and FFLT present similar biases (0.79 vs 0.83 Hz), but lower variability for FEPT, with limits of agreement (LOA) ranging from −3.35 to +4.99 Hz for FFLT vs −2.29 to +3.86 Hz (p<0.0001) for FEPT. For the measurement of z, FEPT has a bias of 0.047 and LOA of −0.063 to +0.157, much lower (p<0.0001) than those measured with the FFLT (bias 0.139 and LOA −0.028 to +0.306). ConclusionWhen automated, the FEPT method will detect potential situations of over/under estimations occurrences. This will prevent false alarms, alarm fatigue and therefore consequences on patient care. Eventually, FEPT turns to be more accurate than FFLT, less scattered, less time-consuming, less invasive and so well suited for use in clinical settings.

Heart Rate Estimation Algorithm Integrating Long and Short-Term Temporal Features

Non-contact heart rate monitoring from facial videos utilizing remote photoplethysmography (rPPG) has gained significant traction in remote health monitoring. Given that rPPG captures the dynamic blood flow within the human body and constitutes a time-series signal characterized by periodic properties, this study introduced a three-dimensional convolutional neural network (3D CNN) designed to simultaneously address long-term periodic and short-term temporal characteristics for effective rPPG signal extraction. Firstly, differential operations are employed to preprocess video data, enhancing the face’s dynamic features. Secondly, building upon the 3D CNN framework, multi-scale dilated convolutions and self-attention mechanisms were integrated to enhance the model’s temporal modeling capabilities further. Finally, interpolation techniques are applied to refine the heart rate calculation methodology. The experiments conducted on the UBFC-rPPG dataset indicate that, compared with the existing optimal algorithm, the average absolute error (MAE) and the root mean square error (RMSE) realized significant enhancements of approximately 28% and 35%. Additionally, through comprehensive analyses such as cross-dataset experiments and complexity analyses, the validity and stability of the proposed algorithm in the task of heart rate estimation were manifested.

Life Cycle Prediction of Airport Operation Based on System Dynamics

Traditional airport development planning often overlooks an in-depth consideration of the airport operation life cycle, which frequently causes deviations from planned objectives during operation. This paper presents a framework for predicting and segmenting the airport operation life cycle by integrating the dynamic characteristics of the System Dynamics (SD) model with the static properties of Logistic modeling to examine the development trajectory of airport operations. The influencing factors in this model are selected across three levels: airport, city, and macro-environment. A system dynamics model of airport operation is constructed using causal loop diagrams and system flow diagrams. Using Guangzhou Baiyun International Airport (CAN) as a case study, the airport’s operational capacity from 2005 to 2035 is predicted through SD simulation. Subsequently, the airport operation life cycle from 2005 to 2050 is forecasted and segmented using Logistic modeling. The results indicate that, under the standard scenario, CAN’s operational capacity experiences two declines in 2016 and 2020, attributed to airport construction and emergencies. Logistic modeling identifies three distinct life cycle phases in the airport’s operation. Furthermore, by comparing various airport operation scenarios, the analysis reveals that fluctuations in the city economy significantly impact the airport’s operational system without altering its overall development trajectory. In contrast, the occurrence of emergencies can substantially modify the airport operation life cycle.

Experimental Evaluation of Gas-Dynamic Conditions of Heat Exchange of Stationary Air Flows in Vertical Conical Diffuser

Conical diffusers are widely used in technical devices (gasifiers, turbines, combustion chambers) and technological processes (ejectors, mixers, renewable energy). The perfection of flow gas dynamics in a conical diffuser affects the intensity of heat and mass transfer processes, the quality of mixing/separation of working media and the flow characteristics of technical devices. These parameters largely determine the efficiency and productivity of the final product. This article presents an analysis of experimental data on the gas-dynamic characteristics of stationary air flows in a vertical, conical, flat diffuser under different initial boundary conditions. An experimental setup was created, measuring instruments were selected, and an automated data collection system was developed. Basic data on the gas dynamics of air flows were obtained using the thermal anemometry method. Experimental data on instantaneous values of air flow velocity in a diffuser for initial velocities from 0.4 m/s to 2.22 m/s are presented. These data were the basis for calculating and obtaining velocity fields and turbulence intensity fields of the air flow in a vertical diffuser. It is shown that the value of the initial flow velocity at the diffuser inlet has a significant effect on the gas-dynamic characteristics. In addition, a spectral analysis of the change in air flow velocity both by height and along the diffuser axis was performed. The obtained data may be useful for refining engineering calculations, verifying mathematical models, searching for technical solutions and deepening knowledge about the features of gas dynamics of air flows in vertical diffusers.

Experimental Evaluation of Under Slab Mats (USMs) Made from End-of-Life Tires for Ballastless Tram Track Applications.

The growing population of urban areas results in the need to deal with the noise pollution from the transportation system. This study presents experimental test results of static and dynamic elastic characteristics of under slab mats (USMs) according to the procedure of DIN 45673-7. Prototype USMs based on recycled elastomeric materials, i.e., SBR granules and fibres produced from waste car tires, are analysed. Vibration isolation mats with different thicknesses (10, 15, 20, 25, 30, and 40 mm), densities (500 and 600 kg/m3), and different degrees of space filling (no holes, medium holes, large holes) are considered. Moreover, a practical application of the laboratory test results of USMs in the design of ballastless track structures of two different types (with a concrete slab and longitudinal beams) is presented. Deflections of the rail and the floating slab system, as well as stresses acting on the mat, are determined according to EN 16432-2. The use of shredded rubber from recycled car tires as a material component of sustainable and environmentally friendly tram track structures may be one of the most effective ways to manage rubber waste within the current trend toward a circular economy, and this study intends to introduce methods for experimental identification and analytical selection of basic static and dynamic parameters of prototype USMs.

Machine Learning Applied to Lithium‐Ion Battery State Estimation for Electric Vehicles: Method Theoretical, Technological Status, and Future Development

ABSTRACTLithium‐ion batteries (LIBs) are extensively utilized in electric vehicles due to their high energy density and cost‐effectiveness. LIBs exhibit dynamic and nonlinear characteristics, which raise significant safety concerns for electric vehicles. Accurate and real‐time battery state estimation can enhance safety performance and prolong battery lifespan. With the rapid advancement of big data, machine learning (ML) holds substantial promise for state estimation. This paper systematically reviews several common ML algorithms, detailing the basic principles of each and illustrating their structures with flowcharts. We compare the advantages and disadvantages of various methods. Subsequently, we discuss feature extraction techniques employed in recent studies for estimating state of charge (SOC), state of health (SOH), state of power (SOP), and remaining useful life (RUL), as well as the application of these ML methods in state estimation. Finally, we discuss the challenges associated with using ML methods for state estimation and outline future development trends.

Traffic complexity assessment on the malacca strait with traffic zone matrix based on AIS data

This study proposes a novel and feasible framework for assessing maritime traffic complexity, utilising historical Automatic Identification System data to extract dynamic traffic characteristics of sea waters and quantify the corresponding maritime traffic complexity. The processed historical statistics are initially segmented into subsets according to different geographic traffic cells based on traffic zones. Subsequently, a Radial Basis Function regression model with a Gaussian kernel is employed to extract dynamic traffic parameters at the central coordinates of each geographic traffic zone based on subsets. The dynamic parameters derived from nonlinear regression and complexity sub-models are ultimately applied in maritime traffic complexity identification. The effectiveness of the proposed framework is validated through complexity assessments in selected areas of Malacca Strait. Empirical results are significant for maritime shipping research on data-driven traffic complexity monitoring and digitalised decision support.

Optimization of Dynamic Characteristics of Rubber-Based SMA Composite Dampers Using Multi-Body Dynamics and Response Surface Methodology

The suspension system of a commercial vehicle cab plays a crucial role in enhancing ride comfort by mitigating vibrations. However, conventional rubber suspension systems have relatively fixed stiffness and damping properties, rendering them inflexible to load variations and resulting in suboptimal ride comfort under extreme road conditions. Shape memory alloys (SMAs) represent an innovative class of intelligent materials characterized by superelasticity, shape memory effects, and high damping properties. Recent advancements in materials science and engineering technology have focused on rubber-based SMA composite dampers due to their adjustable stiffness and damping through temperature or strain rate. This paper investigates how various structural parameters affect the stiffness and damping characteristics of sleeve-type rubber-based SMA composite vibration dampers. We developed a six-degree-of-freedom vibration differential equation and an Adams multi-body dynamics model for the rubber-based SMA suspension system in commercial vehicle cabins. We validated the model’s reliability through theoretical analysis and simulation comparisons. To achieve a 45% increase in stiffness and a 64.5% increase in damping, we optimized the suspension system’s z-axis stiffness and damping parameters under different operating conditions. This optimization aimed to minimize the z-axis vibration acceleration at the driver’s seat. We employed response surface methodology to design the composite shock absorber structure and then conducted a comparative analysis of the vibration reduction performance of the optimized front and rear suspension systems. This study provides significant theoretical foundations and practical guidelines for enhancing the performance of commercial vehicle cab suspension systems.

Analysis of static and dynamic characteristics of membrane air springs for small passenger cars

Analysis of static and dynamic characteristics of membrane air springs for small passenger cars

Reconstruction of Typhoon-Induced Ocean Thermal Structures Using Deep Learning and Multi-Source Satellite Data with News Impact Analysis

Reconstructing the three-dimensional thermal structure of the ocean under typhoon conditions presents significant challenges due to the scarcity of observational data, particularly in subsurface regions, and the limitations of existing observation methods in terms of spatial and temporal resolution. Accurate reconstruction of these structures is crucial for understanding the energy exchange between the ocean and typhoons, as this exchange directly influences typhoon intensity and trajectory. To address these challenges, this study introduces a fully connected transformer network (FCT), which integrates fully connected layers with a transformer model. The FCT model leverages the attention mechanisms inherent in the transformer architecture to effectively extract and integrate multi-scale ocean dynamical features. Using data from Typhoon Lekima in 2019, this study reconstructs ocean thermal structures at various depths and achieves an RMSE of 1.03 °C and an MAE of 0.83 °C when validated against Argo data. Furthermore, the model’s robustness was demonstrated through five-fold cross-validation, with the validation loss exhibiting minor fluctuations across folds but remaining stable overall, with an average validation loss of 0.986 °C, indicating the model’s generalizability. Sensitivity analysis also revealed the model’s resilience to variations in key input variables, showing minimal impact on output even with perturbations of up to 10% in input data. In addition, the study incorporates content analysis of typhoon-related news reports from 2011 to 2020, revealing a predominance of political topics, which underscores the central role of government in disaster response, with economic and ecological topics following. This integrated approach not only enhances our understanding of the interactions between ocean thermal structures and typhoon dynamics but also provides valuable insights into the societal impacts of typhoons, as reflected in media coverage, contributing to improved disaster management strategies.