Dynamic Applications Research Articles

Parking Assistant with the Simulation of Application

Smart Parking can be used for any city. It aims to improve the efficiency and sustainability of urban transportation systems by using technology to manage parking systems. This article provides an overview of the different components of smart parking systems. The increasing vehicular population in urban areas has led to significant challenges related to parking management, exacerbating traffic congestion, environmental impact, and user dissatisfaction. The app facilitates real- time information on available parking spaces, reservation capabilities, and payment integration, thereby enhancing user experience and operational efficiency. We summarize the methodologies applied in developing the app, which include sensor integration for dynamic parking space monitoring and mobile application development for user interaction. The article concludes with a consideration of the future of smart parking and its role in the overall development of smart cities. In conclusion, the findings serve as a basis for future advancements in intelligent parking systems, ensuring improved service delivery for urban commuters.

Human dignity and patient’s interests above all: assisted dying in Switzerland and the UK

Abstract This paper delves into the complex issue of the right to die with dignity, focusing on assisted dying practices within the legal frameworks of Switzerland and the United Kingdom. It examines the emerging challenges and contradictions that this right presents, especially in relation to the fundamental right to life. Highlighting the nuanced interplay between self-determination and the sanctity of life, the study delineates the ethical, medical, and cultural hurdles associated with euthanasia and assisted suicide. It underscores the necessity for legal systems to remain flexible and adaptable, bridging the gap between static legal texts and dynamic real-world applications. This paper seeks to provide a comprehensive analysis of how both countries manage the delicate balance between protecting human dignity and navigating the ethical complexities of assisted dying.

ZnO-Based Memristive Device for Temperature Sensing: Design, Modeling, and Performance Evaluation

This paper presents the design and modeling of a highly sensitive ZnO-based memristive temperature sensor, underpinned by the fundamental physics of memristive behavior. Utilizing a multi-physics simulation tool, the proposed model accurately maps temperature variation contours within the ZnO pyroelectric material, paving the way for its application in temperature sensing. An in-depth exploration of the sensor's electrical properties under varying temperature conditions reveals exceptional sensitivity (8.9 µV/K) and showcases the inherent non-volatile memory switching behavior of the memristor, making it ideally suited for dynamic applications. Moreover, this sensor operates inherently bias-free, functioning as a self-powered solution for emerging fields like the Internet of Things.

Coarse-grained polarizable soft solvent models, with applications in dissipative particle dynamics.

We critically examine a broad class of explicitly polarizable soft solvent models aimed at applications in dissipative particle dynamics. We obtain the dielectric permittivity using the fluctuating box dipole method in linear response theory and verify the models in relation to several test cases, including demonstrating ion desorption from an oil-water interface due to image charge effects. We additionally compute the Kirkwood factor and find that it uniformly lies in the range gK≃0.7-0.8, indicating that dipole-dipole correlations are not negligible in these models. This is supported by the measurements of dipole-dipole correlation functions. As a consequence, Onsager theory over-predicts the dielectric permittivity by 20%-30%. The mean square molecular dipole moment can be accurately estimated with a first-order Wertheim perturbation theory.

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.

Research on dynamic solution analysis and applications based on the Rydberg atom superheterodyne structure

This paper investigates the dynamic solution of the density matrix equation based on the Rydberg atom superheterodyne structure. Compared to the current analytical method relying on the steady-state solution, the dynamic solution is related to the Rabi frequency and the frequency of the signal to be measured. Therefore, it can comprehensively describe the instantaneous bandwidth and gain characteristics of the receiver and is in good agreement with experimental results. Additionally, we propose an atomic all-heterodyne receiver architecture that combines electric-field heterodyne and optical heterodyne techniques and demonstrates the reception and recovery of modulated signals under this architecture with linear frequency modulation (LFM) signals as an example. Our research offers interesting theoretical insights that can be applied to the performance analysis and system optimization of atomic receivers.

New methods and applications of structural dynamics modeling for railway freight liquid tank

As railway freight technology advances towards heavy-load, high-speed capabilities, the design of liquid tank products is evolving to prioritize high load capacity, lightweight, high-strength materials, low structural rigidity, and thin-walled construction. These changes result in pronounced nonlinear low-frequency vibrations during rail operation. Addressing these complex liquid-solid coupled vibrations requires accurate dynamic modeling of the structural system. This paper introduces a novel dynamic modeling method for liquid tank products based on acousto-elastic coupling. This approach considers the swaying of the free liquid surface and liquid-solid interactions, enabling precise characterization of these dynamics in a unified model. Specifically, it tackles the challenge of uneven node swaying forces caused by non-uniform liquid surface meshing, presenting a technique and program to adjust swaying recovery forces based on nodes’ actual coverage area. This method’s liquid sway frequency calculations showed a 10% precision increase over traditional methods, more accurately reflecting liquid vibration states. The paper applies these techniques to a single tank container and an LNG tank container on a flatbed trailer. Through theoretical, simulation, and experimental comparisons, the model’s accuracy and reasonableness were validated. This low-dimensionality, high-precision dynamic model is universally applicable, especially valuable in modeling complex engineering structures.

A Semantic Augmented Approach to FEMA P-58 based Dynamic Regional Seismic Loss Estimation Application

Regional seismic loss estimation (RSLE) is a crucial process in both immediate post-earthquake emergency response and long-term reconstruction endeavors. Over the years, significant progress has been made in RSLE: sensing approaches such as field investigation and remote sensing offers a comprehensive overview necessary for real-time disaster response, while simulation techniques such as the methodology proposed in Federal Emergency Management Agency (FEMA) P-58 series provide insights into the mechanism of disaster development and its potential long-term impacts on urban assets. Nonetheless, challenges persist in the realm of practical RSLE applications. Firstly, a dynamic understanding of a disaster event and its influence is deemed important for effective emergency responses while challenging to achieve in current approaches. Secondly, stakeholders with varying roles, including administrators, rescue teams and ordinary citizens have distinct information requirements for RSLE. Thirdly, the complexity of seismic loss estimation, involving diverse data sources such as building information models, performance models, fragility data and sensor observations, poses interoperability issue. To tackle these issues, this article introduces a dynamic, multi-granularity, ontological representation scheme tailored for RSLE decision-supporting systems. This scheme operates across various scales, from individual building components to broader regional scales by synergistically employing FEMA P-58 guidelines and Semantic Web technologies. Upon the corresponding semantics, a question-and-answer agent powered by large language model is further developed to facilitate interaction requirements within the RSLE process via FEMA P-58 pipeline. The practical efficacy of this approach is validated through a prototype deployed under a real earthquake event, demonstrating its value in real-world scenarios.

Acute effect of Dynamic Tape™ application to the gluteus medius muscle on lower limb kinetics in healthy women: A randomized controlled clinical trial

Acute effect of Dynamic Tape™ application to the gluteus medius muscle on lower limb kinetics in healthy women: A randomized controlled clinical trial

Ultrasound Evaluation of the Hip.

Non-arthritic hip pain is a common presentation among the general population, with many possible contributing etiologies. While radiographs, computed tomography, and magnetic resonance imaging are all within the standard diagnostic workup, ultrasonography has emerged as a facile tool given its low cost, lack of radiation, and dynamic application. This article reviews the utility of ultrasound (US) in evaluation of non-arthritic hip pain and its ability to detect pathology both statically and dynamically in comparison and as an adjunct to standard imaging modalities. Current research highlights applications of US to commonly treated hip pathologies including femoroacetabular impingement, labral tears, hip microinstability, and various other extra-articular phenomena. While static evaluation seems to add similar value to that of radiography, several novel protocols have been developed that allow for dynamic evaluation of joint biomechanics, including extent and onset of impingement and femoral head translation, that cannot be assessed with more standard imaging modalities.

Bioinspired skin-like in vitro model for investigating catheter-related bloodstream infections

Intravenous (IV) catheter-related bloodstream infections (CRBSIs) cause significant risks in healthcare, necessitating advancements in catheter design and materials. This study investigates the effectiveness of Ecoflex, a silicone-based material, in studying CRBSIs through the development of skin-like replicas that mimic human skin properties for use in wearable sensing devices. We characterized the replica’s bioinspired surface roughness, wettability, bacterial adhesion, and mechanical properties and validated its performance using in vitro IV simulation. The results demonstrated that the bioinspired model replicates human skin textures with less than 7.5% error for surface roughness ranging from 0.05 μm to 6.3 μm. Wettability tests revealed that the artificial sebum application significantly reduced the static contact angles for deionized water and artificial sweat. Comprehensive mechanical testing revealed material high elasticity and resilience, suitable for dynamic biomedical applications. Bacterial adhesion studies using Staphylococcus epidermidis showed varying adhesion patterns influenced by surface roughness, highlighting the potential for material texture to impact infection risk. In IV therapy simulations, we observed bacterial growth dynamics over the incubation period. Our findings suggest that Ecoflex-based skin-like replicas can serve as a valuable tool for developing and testing new catheters, while the potential for use in other medical innovation devices, including wearable sensing devices, ultimately contributes to improved patient outcomes and infection control strategies.

Flexible multifunctional composite films for adjustable EMI shielding behavior under self-fixed deformation

With the widespread application of electromagnetic technology, the significance of intelligent electronic devices in modern communication is increasingly prominent. Despite this, the public focuses more on the harm caused by electromagnetic pollution. However, traditional EMI shielding materials struggle to meet the diverse and dynamic application requirements. Hence, developing materials capable of adjusting EMI shielding has become imperative to satisfy various scenarios. This paper presents the composite film TAPU-MXene, which is capable of adjustable EMI SE under self-fixed deformation. Introducing tannic acid increases the innermolecular interactions of TAPU. This enhancement leads to remarkable improvements in mechanical performance, achieving a stress level of 36.6 MPa at a strain of 560 %. Furthermore, the catechol groups can establish non-covalent interactions with multiple substrates, endowing the TAPU film with remarkable adhesion and self-healing capabilities. By combining the highly conductive nano-filler MXene with TAPU, the EMI shielding composite film TAPU-MXene is obtained. The EMI SE of TAPU-MXene was up to 56.7 dB when MXene loading was 3 mg cm−2. Most importantly, TAPU-MXene exhibits the ability to adjust the EMI shielding effectiveness from 56.7 dB to 2.75 dB under self-fixing deformation through shape memory mechanism, demonstrating promising applications in the field of adjustable EMI shielding materials.

Solid, structured composite neutron detectors with high dynamic range capability

Neutron detectors are essential across disciplines such as fundamental science, nuclear security, safeguards, and civilian applications. While 3He-filled gas proportional counters have long been revered for their efficacy in detecting thermal neutrons and praised for their efficiency, neutron/gamma discrimination, and stability, the scarcity of 3He has spurred a search for alternatives. Here, we explore a solid structured scintillating particle composite (SPC) consisting of 6Li-containing scintillating glass particles within an acrylic matrix as a neutron detector for high dynamic range applications. We show for the first time that an SPC neutron detector can boast an intrinsic detection efficiency of 0.261% for pure 252Cf fission neutrons and an overall neutron detection efficiency of (0.546 ± 0.003)% at the Neutron Free-in-Air facility while being able to function in an intense gamma-ray environment. We also show that the SPC neutron detector supports fast neutron capture times and enables a dual-readout scheme that extends the detector dynamic range to high incident neutron fluxes. A scalable fabrication process allows for tailoring the SPC detector properties to the requirements of specific applications. Good agreement is found between the experimental results taken with a National Institute of Standards and Technology traceable 252Cf source and the coupled MCNP6 and optical-ray-tracing simulations.

Modeling of Carbon Footprint Emissions in Sugarcane Production Using System Dynamics

Objective: This study proposes a model aimed at estimating and reducing carbon emissions in sugarcane cultivation and juice extraction, designed for potential application in real-world systems. Method: The model grounded in a hypothetical case study of a 60-hectare sugarcane plantation in a warm climate with a 7-month growth cycle and a three-year simulation period, focuses on estimate and evaluate mitigation scenarios to decrease emissions from fuel and electricity usage in activities such as plowing, sowing, harvesting, and irrigation. Utilizing Vensim PLE, a System Dynamics model that combine event and dynamic simulation. Results and Discussion: Utilizing Vensim PLE, a System Dynamics model that combine event and dynamic simulation estimated a 3060.81 tons CO2 equivalent carbon footprint. Two scenarios aimed at footprint reduction were tested: substituting electrical energy with solar power reduced the footprint by 86% to 450.092 tons, demonstrating clean energy's efficacy. Conversely, replacing an industrial mill with the traditional trapiche technique for juice extraction yielded a mere 1% reduction, indicating its ineffectiveness for real-world application. Research Implications: This study emphasizes the development of a simulation model based on system dynamics to estimate the carbon footprint emissions in sugar cane production considering its cultivation and juice extraction. The results support that through simulations, it is possible to determine the factors that influence the generation of carbon dioxide, offering a broader vision to establish and implement mitigation measures such as adopting clean energies and reducing fuel consumption. Originality/Value: This research contributes to the understanding of the application of system dynamics by using software such as Vensim PLE to estimate the carbon footprint emissions in sugar cane production, considering its cultivation and juice extraction. The results found through simulations suggest the implementation of mitigation measures such as the adoption of clean energies and the reduction of fuel consumption.

Dynamics behaviours of N-kink solitons in conformable Fisher–Kolmogorov–Petrovskii–Piskunov equation

PurposeThis manuscript is related to compute $N$-kink soliton solutions for conformable Fisher–Kolmogorov equation (CFKE) by using the generalized extended direct algebraic method (EDAM). The considered problem has important applications in mathematical biology and reaction diffusion processes. Also, the mentioned problem has significant applications in population dynamics. The fractional order conformable derivative has many features as compared to the other fractional order differential operators. For instance, the chain, product and quotient procedures do not satisfy by other fractional differential operators, but conformable operators obey the mentioned rules. Hence, we compute the soliton solutions for the mentioned problem and present its various dynamical behaviours graphically.Design/methodology/approachThe generalized EDAM is used in this article to examine the calculation of N-kink soliton solutions for the CFKE. In mathematical biology and reaction-diffusion processes, the topic under consideration holds great significance, especially when considering population dynamics.FindingsThe results highlight the benefits of utilising conformable derivatives in mathematical modelling and further our understanding of fractional differential equations and their applications.Research limitations/implicationsThe work focuses primarily on N-kink soliton solutions, which may limit the examination of alternative types of solutions (e.g., multi-soliton or periodic solutions) that might give new insights into the dynamics of the CFKE.Practical implicationsThe generated N N-kink soliton solutions can enhance mathematical models in biological contexts, notably in modelling population dynamics, disease propagation and ecological interactions, leading to better forecasts and interventions.Social implicationsPublic health initiatives can benefit from the understanding of disease transmission and intervention efficacy that comes from modelling population dynamics and reaction-diffusion processes.Originality/valueThe use of the generalized EDAM to obtain solutions for N-kink soliton problems is an innovative method for solving the conformable Fisher–Kolmogorov equation, demonstrating the power of this mathematical tool.

Dynamical analysis and fault detection application of a time-delayed multi-stable stochastic resonance system driven by white correlated noises.

Bearing fault diagnosis is a crucial means to ensure the normal operation of machinery, reduce maintenance costs, enhance equipments safety and extend the service life of bearings. However, the noise interference in input signals often affects the effective extraction of bearing fault signals. In this paper, a time-delay multi-stable stochastic resonance (SR) system driven by white correlated noises is proposed. Firstly, the expressions of the steady-state probability density (SPD) function and the mean first passage time (MFPT) is derived. Simultaneously, we delve into the influences of various system parameters, including multiplicative noise intensity, additive noise intensity, noise correlated strength, time-delay, and time-delay feedback intensity, on the dynamical behavior exhibited by particles within the system. Then, according to the signal-to-noise ratio (SNR) formula, the paper investigates the impact of system parameters on the SNR. It is found that the ease of SR occurrence is directly related to the system parameters. Finally, the experimental results demonstrate that the proposed method exhibits superior performance in detecting faults compared with the classical bistable SR system and the quad-stable SR system.

Representing turbulent statistics with partitions of state space. Part 1. Theory and methodology

This is the first of a two-part paper. We formulate a data-driven method for constructing finite-volume discretizations of an arbitrary dynamical system's underlying Liouville/Fokker–Planck equation. A method is employed that allows for flexibility in partitioning state space, generalizes to function spaces, applies to arbitrarily long sequences of time-series data, is robust to noise and quantifies uncertainty with respect to finite sample effects. After applying the method, one is left with Markov states (cell centres) and a random matrix approximation to the generator. When used in tandem, they emulate the statistics of the underlying system. We illustrate the method on the Lorenz equations (a three-dimensional ordinary differential equation) saving a fluid dynamical application for Part 2 (Souza, J. Fluid Mech., vol. 997, 2024, A2).

Research on Non-Equilibrium Dynamics Theory in Chemical Thermodynamics

Non-equilibrium dynamics theory is an important branch of chemical thermodynamics, widely applied in describing complex chemical reaction systems far from equilibrium. With the advancement of modern science and technology, an increasing number of chemical reactions exhibit unique behaviors under non-equilibrium conditions, such as self-organization and periodic oscillations—nonlinear phenomena. This paper systematically explores the distinctions between non-equilibrium and equilibrium states, introduces the fundamental principles of non-equilibrium thermodynamics, and analyzes cutting-edge issues such as nonlinear phenomena and multi-scale dynamics. Additionally, it discusses the specific applications of non-equilibrium dynamics in far-from-equilibrium reactions, heterogeneous catalysis, and industrial chemical processes, addressing both theoretical and experimental challenges. Through the combination of theoretical analysis and practical application, this paper aims to provide new insights and methodologies for research on non-equilibrium dynamics in the field of chemistry.

Single-shot echo planar time-resolved imaging for multi-echo functional MRI and distortion-free diffusion imaging.

To develop a single-shot SNR-efficient distortion-free multi-echo imaging technique for dynamic imaging applications. Echo planar time-resolved imaging (EPTI) was first introduced as a multi-shot technique for distortion-free multi-echo imaging. This work aims to develop single-shot EPTI (ss-EPTI) to achieve improved robustness to motion/physiological noise, increased temporal resolution, and higher SNR efficiency. A new spatiotemporal encoding that enables reduced phase-encoding blips and minimized echo spacing under the single-shot regime was developed, which improves sampling efficiency and enhances spatiotemporal correlation in the k-TE space for improved reconstruction. A continuous readout with minimized deadtime was employed to optimize SNR efficiency. Moreover, k-TE partial Fourier and simultaneous multi-slice acquisition were integrated for further acceleration. ss-EPTI provided distortion-free imaging with densely sampled multi-echo images at standard resolutions (e.g., ˜1.25 to 3 mm) in a single-shot. Improved SNR efficiency was observed in ss-EPTI due to improved motion/physiological-noise robustness and efficient continuous readout. Its ability to eliminate dynamic distortions-geometric changes across dynamics due to field changes induced by physiological variations or eddy currents-further improved the data's temporal stability. For multi-echo fMRI, ss-EPTI's multi-echo images recovered signal dropout in short- regions and provided TE-dependent functional information to distinguish non-BOLD noise for further tSNR improvement. For diffusion MRI, it achieved shortened TEs for improved SNR and provided images free from both B0-induced and diffusion-encoding-dependent eddy-current-induced distortions with multi-TE diffusion metrics. ss-EPTI provides SNR-efficient distortion-free multi-echo imaging with comparable temporal resolutions to ss-EPI, offering a new acquisition tool for dynamic imaging.

Observation of quantum superposition of topological defects in a trapped-ion quantum simulator.

Topological defects are discontinuities of a system protected by global properties, with wide applications in mathematics and physics. While previous experimental studies mostly focused on their classical properties, it has been predicted that topological defects can exhibit quantum superposition. Despite the fundamental interest and potential applications in understanding symmetry-breaking dynamics of quantum phase transitions, its experimental realization still remains a challenge. Here, we report the observation of quantum superposition of topological defects in a trapped-ion quantum simulator. By engineering long-range spin-spin interactions, we observe a spin kink splitting into a superposition of kinks at different positions, creating a "Schrodinger kink" that manifests nonlocality and quantum interference. Furthermore, by preparing superposition states of neighboring kinks with different phases, we observe the propagation of the wave packet in different directions, thus unambiguously verifying the quantum coherence in the superposition states. Our work provides useful tools for nonequilibrium dynamics in quantum Kibble-Zurek physics.