Dynamic Mechanism Research Articles

Performance of metal circular tube under different loading amplitudes and dynamic resistance-yielding mechanism

As coal mining depth increases, the characteristics of “high ground stress, high ground temperature, high osmotic pressure, and mining disturbance” become increasingly pronounced, posing new challenges to the stability of the surrounding rock roadway. Amplitude is a key parameter affecting disturbance strength. A cyclic loading and unloading experiment was conducted under different amplitudes to explore the effect of metal circular tubes, used as energy-absorbing components, on the protection performance of anchor bolt tails. This experiment further revealed the competitive protection mechanism of the metal circular tube, termed “resistance - yielding”. The research results indicate that the metal tube incurs damage and accumulates it with the increase of loading amplitude in the pre-peak stage, leading to a decrease in its peak load. The metal tube absorbs external energy robustly through its elastic-plastic deformation. In the platform stage, a high amplitude load causes the peak load displacement to increase and its stable energy-absorbing stroke to decrease. Plastic energy dominates the main position of energy absorption, and the metal circular tube forms a dynamic competitive relationship of “resistance-yielding” with external stresses. Throughout the entire energy absorption process, the total energy absorption decreases with the increase of amplitude. The research results investigate the effect of amplitude on the performance of metal circular tubes and demonstrate the feasibility of applying metal circular tubes as energy-absorbing members at the end of anchor rods, which can provide theoretical guidance for the prevention of disaster accidents in mines caused by disturbances.

How to restore ecological impacts from wind energy? An assessment of Zhongying Wind Farm through MSPA-MCR model and circuit theory

The wind energy industry is developing rapidly in China with a maximum capacity worldwide. Meanwhile, the stability of the ecological network is challenged by extensive renewable energy expansion. There are still research deficiencies in wind farm ecological impacts at project scale from an ecological restoration perspective. It is of great necessity to monitor the ecological impacts with time going and explore ecological restoration strategies for wind power development. The research case of Zhongying Wind Farm is selected based on investigation and interviews regarding its ecological impact in the prior study. It employs a comparative methodology by comparing the ecological quality before and after the construction of Zhongying Wind Farm. Raw data from Landsat 8, the Digital Elevation Model (DEM), the Normalized Difference Vegetation Index (NDVI), and wind turbine statistics originating from open data platforms are analyzed and visually represented with ArcGIS. This paper establishes an ecological network based on morphological spatial pattern analysis (MSPA) and the Minimum Cumulative Resistance (MCR) model to quantify wind farms’ impacts on ecological corridors. The circuit theory and Pajek software are used to identify and categorize the ecological nodes into weak and obstacle points. The results reveal that ecological impacts on ecological corridors decay with distance, reflecting changes in length, connection strength and cumulative values of corridors. While the impacts on ecological nodes depend on nodes’ attributes: the number of weak points increased by 18.5 %, and obstacle points increased by 350 %, with their locations shifting from the edges of urban construction sites to the edges of wind farm. Differentiated strategies are proposed according to the impact magnitude of each ecological corridor and node: such as dynamic inspection mechanism, construction prohibition for protection; corridor structure and function recovering, stepping stones addition for restoration; buffer belts, warning radar, and monetary schemes for compensation. This research fills the gap of ecological impact assessment under the challenges of wind energy expansion. It helps to balance wind energy development and ecological restoration at the regional level.

A device to device driven approach towards optimizing energy efficiency for 6G networks

Our study aims to develop more energy-efficient mobile communication systems through the exploration of the 6th generation (6G) technology that is expected to be implemented in 2033. We focus on the impact of device-to-device (D2D) communication on power efficiency, which is a crucial need in this domain. To achieve this, we conducted a pioneering experiment using an in-house testbed and K-means clustering to classify locations as D2D enabled or disabled. Our findings show that there is a dynamic clustering mechanism that enables certain nodes to sustain D2D functionality around temporary base stations, resulting in a remarkable 5% improvement in network lifetime per second. This research not only enhances our understanding of 6G networks but also provides a practical methodology for optimizing energy consumption, which holds significant implications for society in advancing sustainable and efficient communication.

Morphological evolution of nano-droplets impinging on cylindrical wall: A molecular dynamics study

The impact of droplets on solid walls is the primary behavior in spray cooling, seawater desalination, self-cleaning, and other technological processes. Based on the molecular dynamics (MD) method, the morphological evolution characteristics of nanodroplets impinging on the copper cylinder wall are studied. The effects of droplet size, initial velocity, impact position, and wall wettability on nanodroplet dynamics are analyzed. The results indicate that a single nanodroplet impacting on a nanocylinder exhibits four distinct impact modes: spread-partially wrapped-deposition (SPD), spread-completely wrapped-deposition (SCD), spread-completely wrapped-splitting-deposition (SCSD), and spreading-partially wrapped-splitting-deposition (SPSD). The trend of the influence of initial velocity and droplet size on the impact mode is similar. As the initial velocity and droplet size increase, the droplet’s kinetic energy and inertia force increase, successively exhibiting the SPD, SCD, and SCSD modes. The trend of the influence of impact position and wall wettability on the droplet impact mode is similar. When the impact eccentricity distance is small, and the wall is highly hydrophilic, it exhibits the SCD mode. With increasing impact eccentricity and enhanced wall hydrophobicity, the adhesion force between the droplet and the cylinder wall decreases, making the droplet less likely to be captured and more prone to splitting, exhibiting the SPSD mode. The change in droplet centroid height and mean square displacement could predict whether the droplet undergoes a splitting mode, and its influence is most significant at the impact position. Constrained by the cylindrical wall, the droplet impacts radially and spreads primarily in that direction. With the enhancement of wall hydrophilicity, the migration region of the three-phase contact line expands, and the droplet spreading transforms into synchronous development along the radial and axial directions. The research results can enrich the dynamic mechanism of micro-nano scale droplet impact and provide potential guidance for optimizing relevant technologies.

Exploring the dynamics of ISR signaling in maize upon seed priming with plant growth promoting actinobacteria isolated from tea rhizosphere of Darjeeling.

Plant growth-promoting rhizobacteria (PGPR) offer an eco-friendly alternative to agrochemicals for better plant growth and development. Here, we evaluated the plant growth promotion abilities of actinobacteria isolated from the tea (Camellia sinensis) rhizosphere of Darjeeling, India. 16S rRNA gene ribotyping of 28 isolates demonstrated the presence of nine different culturable actinobacterial genera. Assessment of the in vitro PGP traits revealed that Micrococcus sp. AB420 exhibited the highest level of phosphate solubilization (i.e., 445 ± 2.1µg/ml), whereas Kocuria sp. AB429 and Brachybacterium sp. AB440 showed the highest level of siderophore (25.8 ± 0.1%) and IAA production (101.4 ± 0.5µg/ml), respectively. Biopriming of maize seeds with the individual actinobacterial isolate revealed statistically significant growth in the treated plants compared to controls. Among them, treatment with Paenarthrobacter sp. AB416 and Brachybacterium sp. AB439 exhibited the highest shoot and root length. Biopriming has also triggered significant enzymatic and non-enzymatic antioxidative defense reactions in maize seedlings both locally and systematically, providing a critical insight into their possible role in the reduction of reactive oxygen species (ROS) burden. To better understand the role of actinobacterial isolates in the modulation of plant defense, three selected actinobacterial isolates, AB426 (Brevibacterium sp.), AB427 (Streptomyces sp.), and AB440 (Brachybacterium sp.) were employed to evaluate the dynamics of induced systemic resistance (ISR) in maize. The expression profile of five key genes involved in SA and JA pathways revealed that bio-priming with actinobacteria (Brevibacterium sp. AB426 and Brachybacterium sp. AB440) preferably modulates the JA pathway rather than the SA pathway. The infection studies in bio-primed maize plants resulted in a delay in disease progression by the biotrophic pathogen Ustilago maydis in infected maize plants, suggesting the positive efficacy of bio-priming in aiding plants to cope with biotic stress. Conclusively, this study unravels the intrinsic mechanisms of PGPR-mediated ISR dynamics in bio-primed plants, offering a futuristic application of these microorganisms in the agricultural fields as an eco-friendly alternative.

Hierarchical reinforcement learning for handling sparse rewards in multi-goal navigation

Reinforcement learning (RL) has achieved remarkable advancements in navigation tasks in recent years. However, tackling multi-goal navigation tasks with sparse rewards remains a complex and challenging problem due to the long-sequence decision-making involved. Such multi-goal navigation tasks inherently incorporate a hybrid action space, where the robot needs to select a navigation endpoint first before executing primitive actions. To address the problem of multi-goal navigation with sparse rewards, we introduce a novel hierarchical RL framework named Hierarchical RL with Multi-Goal (HRL-MG). The main idea of HRL-MG is to divide and conquer the hybrid action space, splitting long-sequence decisions into short-sequence decisions. The HRL-MG framework is composed of two main modules: a selector and an actuator. The selector employs a temporal abstraction hierarchical architecture designed to specify a desired end goal based on the discrete action space. Conversely, the actuator utilizes a continuous goal-oriented hierarchical architecture developed to enact continuous action sequences to reach the desired end goal specified by the selector. In addition, we incorporate a dynamic goal detection mechanism, grounded in hindsight experience replay, to mitigate the challenges posed by sparse reward landscapes. We validated the algorithm’s efficacy on both the discrete environment Maze_2D and the continuous robotic environment MuJoCo ‘Ant’. The results indicate that HRL-MG significantly outperforms other methods in multi-goal navigation tasks with sparse rewards.

An Observer-Based Topology Identification and Synchronization in Finite Time for Fractional Singularly Perturbed Complex Networks via Dynamic Event-Triggered Control

This paper investigates the topology identification and synchronization in finite time for fractional singularly perturbed complex networks (FSPCNs). Firstly, a convergence principle is developed for continuously differential functions. Secondly, a dynamic event-triggered mechanism (DETM) is designed to achieve the network synchronization, and a topology observer is developed to identify the network topology. Thirdly, under the designed DETM, by constructing a Lyapunov functional and applying the inequality analysis technique, the topology identification and synchronization condition in finite time is established in the forms of the matrix inequality. In addition, it is proved that the Zeno behavior can be effectively excluded. Finally, the effectiveness of the main results is verified by an application example.

Self-Supervised Image Denoising of Third Harmonic Generation Microscopic Images of Human Glioma Tissue by Transformer-based Blind Spot (TBS) Network.

Third harmonic generation (THG) microscopy shows great potential for instant pathology of brain tumor tissue during surgery. However, due to the maximal permitted exposure of laser intensity and inherent noise of the imaging system, the noise level of THG images is relatively high, which affects subsequent feature extraction analysis. Denoising THG images is challenging for modern deep-learning based methods because of the rich morphologies contained and the difficulty in obtaining the noise-free counterparts. To address this, in this work, we propose an unsupervised deep-learning network for denoising of THG images which combines a self-supervised blind spot method and a U-shape Transformer using a dynamic sparse attention mechanism. The experimental results on THG images of human glioma tissue show that our approach exhibits superior denoising performance qualitatively and quantitatively compared with previous methods. Our model achieves an improvement of 2.47-9.50 dB in SNR and 0.37-7.40 dB in CNR, compared to six recent state-of-the-art unsupervised learning models including Neighbor2Neighbor, Blind2Unblind, Self2Self+, ZS-N2N, Noise2Info and SDAP. To achieve an objective evaluation of our model, we also validate our model on public datasets including natural and microscopic images, and our model shows a better denoising performance than several recent unsupervised models such as Neighbor2Neighbor, Blind2Unblind and ZS-N2N. In addition, our model is nearly instant in denoising a THG image, which has the potential for real-time applications of THG microscopy.

Between Freedom and Order: Evolution logic of urban-rural population mobility Policy from the perspective of historical institutionalism

Urban-rural population flow is the key element and important driving force for urban-rural integration development and rural revitalization. The pattern of urban-rural population flow in China is restricted and guided by policies. From the perspective of historical institutionalism, this paper analyzes the evolution context, structural logic and dynamic mechanism of the change of urban and rural population mobility policy. The urban and rural population mobility policy has gone through five historical stages: the order reconstruction period at the beginning of the founding of New China, the political call period after the Great Leap Forward Movement, the free flow period after the reform and opening up, the period of making the best use of the situation under the economic system reform and the accelerated integration period under the background of the new era. The institutional choice under different paths, the institutional evolution under the key nodes and the institutional continuation under the path dependence constitute the structural logic of the policy change of urban-rural population mobility. The situation coupling under the action of exogenous variables, the value coupling promoted by the change of ideas, and the subject coupling under the interaction of actors’ game constitute the dynamic mechanism of policy change, which promotes the historical change and realistic development of policy.

Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip

By mimicking the neurons and synapses of the human brain and employing spiking neural networks on neuromorphic chips, neuromorphic computing offers a promising energy-efficient machine intelligence. How to borrow high-level brain dynamic mechanisms to help neuromorphic computing achieve energy advantages is a fundamental issue. This work presents an application-oriented algorithm-software-hardware co-designed neuromorphic system for this issue. First, we design and fabricate an asynchronous chip called “Speck”, a sensing-computing neuromorphic system on chip. With the low processor resting power of 0.42mW, Speck can satisfy the hardware requirements of dynamic computing: no-input consumes no energy. Second, we uncover the “dynamic imbalance” in spiking neural networks and develop an attention-based framework for achieving the algorithmic requirements of dynamic computing: varied inputs consume energy with large variance. Together, we demonstrate a neuromorphic system with real-time power as low as 0.70mW. This work exhibits the promising potentials of neuromorphic computing with its asynchronous event-driven, sparse, and dynamic nature.

Symbolic Computation on a (2+1)-Dimensional Generalized Nonlinear Evolution System in Fluid Dynamics, Plasma Physics, Nonlinear Optics and Quantum Mechanics

Symbolic Computation on a (2+1)-Dimensional Generalized Nonlinear Evolution System in Fluid Dynamics, Plasma Physics, Nonlinear Optics and Quantum Mechanics

Optimization of Lithium Metal Anode Performance: Investigating the Interfacial Dynamics and Reductive Mechanism of Asymmetric Sulfonylimide Salts

Asymmetric lithium salts, such as lithium (difluoromethanesulfonyl)(trifluoromethanesulfonyl)imide (LiDFTFSI), have been demonstrated to surpass traditional symmetric lithium salts with improved Li+ conductivity and the capacity to generate a stable solid electrolyte interphase (SEI) while maintaining compatibility with an aluminum (Al0) current collector. However, the intrinsic reductive mechanism through which LiDFTFSI influences battery performance remains unclear and under debate. Herein, detailed SEI reactions of LiDFTFSI–based electrolytes were investigated by combining density functional theory and molecular dynamics, aiming to clarify the formation process and atomic structure of the SEI. Our results show that asymmetric DFTFSI− weakens the interaction between carbonate solvents and Li+, and substantially alters the solvation structure, exhibiting a well-balanced coordination capacity compared to bis(trifluoromethanesulfonyl)imide (TFSI−). Nanosecond hybrid molecular dynamics simulation further reveals that preferential decomposition of LiDFTFSI produces sufficient LiF and Li2O to facilitate a robust SEI. Moreover, abundant F− generated from LiDFTFSI decomposition accumulates on the Al surface and subsequently combines with Al3+ from the current collector to form AlF3, potentially inhibiting corrosion of the current collector. Overall, these findings elucidate how LiDFTFSI regulates the solvation sheath and SEI structure, advancing the development of high-performance electrolytes compatible with current collectors.

Exploring the interplay between the TGF-βpathway and SLN-mediated transfection: implications for gene delivery efficiency in prostate cancer and non-cancer cells.

Solid lipid nanoparticles (SLN) are widely recognized for their biocompatibility, scalability, and long-term stability, making them versatile formulations for drug and gene delivery. Cellular interactions, governed by complex endocytic and signaling pathways, are pivotal for successfully applying SLN as a therapeutic agent. This study aims to enhance our understanding of the intricate interplay between SLN and cells by investigating the influence of specific endocytic and cell signaling pathways, with a focus on the impact of the TGF-βpathway on SLN-mediated cell transfection in both cancerous and non-cancerous prostate cells. Here, we systematically explored the intricate mechanisms governing the interactions between solid lipid nanoparticles and cells. By pharmacologically manipulating endocytic and signaling pathways, we analyzed alterations in SLNplex internalization, intracellular traffic, and cell transfection dynamics. Our findings highlight the significant role of macropinocytosis in the internalization and transfection processes of SLNplex in both cancer and non-cancer prostate cells. Moreover, we demonstrated that the TGF-βpathway is an important factor influencing endosomal release, potentially impacting gene expression and modulating cell transfection efficiency. This study provides novel insights into the dynamic mechanisms governing the interaction between cells and SLN, emphasizing the pivotal role of TGF-βsignaling in SLN-mediated transfection, affecting internalization, intracellular transport, and release of the genetic cargo. These findings provide valuable insight for the optimization of SLN-based therapeutic strategies in prostate-related applications.

Sensory synergy and energy dynamics: unveiling the performance drivers of Chinese hotel frontline employees

ABSTRACT This study explores the relationship between sensory experiences and the energy levels of Chinese hotel frontline employees, examining the pathways through which their resource energy is activated and the underlying mechanisms. Specifically, it looks at how frontline employees in Asian hotels promote work integration through relational and collective energy. Set within the Asian hospitality sector, this research highlights the Asian paradigms – service philosophies and management styles embedded in Asian culture and values – that have made an impact on the global hospitality industry. Interviews with 35 hotel employees resulted in 35 narrative structure maps, revealing that sensory synergy and compensation can activate an interactive dynamic mechanism, facilitating the ongoing activation of energy in their daily tasks. This process advances the five critical nodes of energy activation at work. The study significantly contributes by focusing on the individual and collective values of frontline employees as they navigate and adapt to shifts in the Asian paradigm. It reveals the internal mechanism that regulates the integration and optimisation of hotel frontline employees’ energy, providing insights into improving employee well-being and performance in the hospitality industry.

Gap in drop collision rate between diffusive and inertial regimes explains the stability of fogs and non-precipitating clouds

Rain drops form in clouds by collision of submillimetric droplets falling under gravity: larger drops fall faster than smaller ones and collect them on their path. The puzzling stability of fogs and non-precipitating warm clouds with respect to this avalanche mechanism has been a longstanding problem. How can droplets of diameter around 10 $\mathrm {\mu }$ m have a low collision probability, inhibiting the cascade towards larger and larger drops? Here we review the dynamical mechanisms that have been proposed in the literature and quantitatively investigate the frequency of drop collisions induced by Brownian diffusion, electrostatics and gravity, using an open-source Monte Carlo code taking all of them into account. Inertia dominates over aerodynamic forces for large drops, when the Stokes number is larger than $1$ . Thermal diffusion dominates over aerodynamic forces for small drops, when the Péclet number is smaller than $1$ . We show that there exists a range of size (typically 3–30 $\mathrm {\mu }$ m for water drops in air) where neither inertia nor Brownian diffusion are significant, leading to a gap in the collision rate. The effect is particularly important, due to the lubrication film forming between the drops immediately before collision, and secondarily to the long-range aerodynamic interaction. Two different mechanisms regularise the divergence of the lubrication force at vanishing separation: the transition to a non-continuum regime in the lubrication film, when the separation is comparable to the mean free path of air, and the induction of a flow inside the drops due to shear at their surfaces. In the gap between inertia-dominated and diffusion-dominated regimes, dipole–dipole electrostatic interactions becomes the major effect controlling the efficiency of drop collisions.

Evolutionary mechanism for diversity dynamics in technology using a phylogenetic tree approach: directional suggestions for photovoltaic technology

Abstract This study investigates the dynamics of diversity within photovoltaic technology by considering the spatial information of technological change. We introduce a phylogenetic tree methodology using an evolutionary perspective for validation at the level of technology genes and functional modules. Our findings show that the photovoltaic technology phylogenetic tree fully describes the technological and industrial histories of photovoltaics. Furthermore, the results imply that diversity is necessary for the evolutionary mechanism to operate and technology integration is the correct direction to pursue.

Pose detection and docking control for autonomous dynamic docking mechanism with non-cooperative targets

Purpose This study aims to address the issue of random movement and non coordination between docking mechanisms and locking mechanisms, and proposes a comprehensive dynamic docking control architecture that integrates perception, planning, and motion control. Design/methodology/approach Firstly, the proposed dynamic docking control architecture uses laser sensors and a charge-coupled device camera to perceive the pose of the target. The sensor data are mapped to a high-dimensional potential field space and fused to reduce interference caused by detection noise. Next, a new potential function based on multi-dimensional space is developed for docking path planning, which enables the docking mechanism based on Stewart platform to rapidly converge to the target axis of the locking mechanism, which improves the adaptability and terminal docking accuracy of the docking state. Finally, to achieve precise tracking and flexible docking in the final stage, the system combines a self-impedance controller and an impedance control algorithm based on the planned trajectory. Findings Extensive simulations and experiments have been conducted to validate the effectiveness of the dynamic docking system and its control architecture. The results indicate that even if the target moves randomly, the system can successfully achieve accurate, stable and flexible dynamic docking. Originality/value This research can provide technical guidance and reference for docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

Dynamic Behavior and Mechanism of Transient Fluid–Structure Interaction in Viscoelastic Pipes Based on Energy Analysis

Dynamic Behavior and Mechanism of Transient Fluid–Structure Interaction in Viscoelastic Pipes Based on Energy Analysis

Revealing the Role of Spacer Layer in Domain Dynamics of Hf0.5Zr0.5O2 Thin Films for Ferroelectrics

AbstractHfO2‐based ferroelectrics offer promises for next‐generation nonvolatile nanoscale devices owing to excellent CMOS compatibility and robust ferroelectricity at the nanoscale. However, fundamentally understanding the mechanism of polarization reversal and domain dynamics is challenging because the role of the spacer layer at the domain level in HfO2‐based ferroelectrics remains elusive. Here, it is realized that visualization of time‐resolved dynamics of nanoscale domain configurations in the epitaxial Hf0.5Zr0.5O2 thin films using phase‐field simulations. Scale‐free domain independent switchability (namely, irreducible stable polar domain down to 1 nm lateral size) and sharp domain walls that originate from weak interactions between adjacent domains characterized by the reduced gradient energy coefficient, which unravels the mesoscale mechanism of spacer layer in domain dynamics are demonstrated. Meanwhile, it is revealed that 180° polarization switching is dominated by the nucleation of a new domain with a high nucleation density, well described by the nucleation‐limited switching model. This study not only provides a fundamental mesoscale mechanism of the spacer layer, but also stimulates further studies on the manipulation of ultra‐scaled single domain state for designing high‐density and fast‐speed HfO2‐based ferroelectric memory.

Analysis of Grotowskis Body Action Method from the Perspective of Zhuangzi

Jerzy Grotowski (1933-1999, hereinafter referred to as Grotowski) was a renowned theater practitioner in the 20th century, dedicating his life to the study of theatrical performance. His theatrical works shook the world in the 20th century, and he was well-known in the theater communities of Europe and America. Unfortunately, he passed away prematurely, leaving behind profound and abstruse writings for future generations. His late-life creation, the Art of Vehicle in body action methods, holds profound significance for the study of states in various artistic performances. Based on this, researchers, drawing on Grotowskis lifelong learning and research background, interpret and analyze Grotowskis study of art of vehicle through the Zhuangzis concept of body in the philosophy of Swiss philosopher Jean Franois Billeters dynamic mechanism. This paper is based on the research theory of Professor Mingder Chung from Taipei National University of the Arts on Grotowskis MPA, aiming to elucidate Grotowskis interpretation of body through Zhuangzis body view, and further clarify the conceptual framework of MPA. The purpose is to contribute theoretical foundations to the study of Grotowskis Art of Vehicle.