Influence Of Dynamics Research Articles

Distinct mesenchymal cell states mediate prostate cancer progression

In the complex tumor microenvironment (TME), mesenchymal cells are key players, yet their specific roles in prostate cancer (PCa) progression remain to be fully deciphered. This study employs single-cell RNA sequencing to delineate molecular changes in tumor stroma that influence PCa progression and metastasis. Analyzing mesenchymal cells from four genetically engineered mouse models (GEMMs) and correlating these findings with human tumors, we identify eight stromal cell populations with distinct transcriptional identities consistent across both species. Notably, stromal signatures in advanced mouse disease reflect those in human bone metastases, highlighting periostin’s role in invasion and differentiation. From these insights, we derive a gene signature that predicts metastatic progression in localized disease beyond traditional Gleason scores. Our results illuminate the critical influence of stromal dynamics on PCa progression, suggesting new prognostic tools and therapeutic targets.

Exploiting dynamic social feedback for session-based recommendation

Since people with close relationships are easily influenced by each other, social friends usually have more preferences of higher similarities than others. For this reason, social recommendation methods are proposed to adopt social links to improve the degree of preference matching between users and recommended items. Although current social recommendation methods have captured the general preference similarities among social friends, it is still difficult to model the evolution of dynamic social influence among friends, especially in session-based scenarios. In reality, when users’ dynamic preferences are changing, social feedback from their friends is also changing over time. So that the dynamic social feedback is an important social influence, which has not been considered in current studies. To this end, we propose a social feedback-enhanced session-based recommendation (SFRec) method, which not only utilizes the similarity of general preferences among friends but also captures the friends’ influence which reflects people’s dynamic preferences. Specifically, we first coordinate similarity relations via information propagation on social graph, item transition graph and user–item interaction graph. To capture social feedback based on users’ dynamic preferences, we then construct a social feedback generation module that consists of preference extraction, feedback generation and feedback aggregation. Finally, we construct a preference fusion module to obtain the final preference representation and make personalized recommendation. We conduct comprehensive experiments on three datasets. Results demonstrate that SFRec surpasses the state-of-the-art models on recommendation performance.

Research on the New Power of Car Making Ideal Car

In response to the escalating depletion of fossil fuel reserves and the detrimental environmental impacts of conventional internal combustion engine vehicles, the global automotive industry is undergoing a transformative shift towards clean, sustainable, and energy-efficient new energy vehicles (NEVs). This article scrutinizes the remarkable ascent of Ideal Cars, a prominent player in the burgeoning Chinese NEV market. In light of these developments, this scholarly examination explores the multifaceted determinants underpinning Ideal Cars' remarkable trajectory, encompassing its foundational evolution, distinctive technological orientation, nuanced user-centric approach, financial performance, scene-based marketing strategies, and innovative organizational structure. This comprehensive analysis underscores the imperative nature of consumer-oriented product design, the psychological aspects of consumer satisfaction, and the paramount influence of market dynamics in shaping the success of high-end automotive ventures. Ideal Cars' unprecedented journey serves as an instructive case study for the prospective evolution of the NEV industry in China and globally.

Accelerated marine carbon cycling forced by tectonic degassing over the Miocene Climate Optimum

Global warming during the Miocene Climate Optimum (MCO, ∼17–14 million years ago) is associated with massive carbon emissions sourced from the flood basalt volcanism and ocean crustal production. However, the perturbation of tectonic carbon degassing on the interaction between climate change and carbon cycle remains unclear. Here, through time-evolutive phase analysis of new and published high-resolution benthic foraminiferal oxygen (δ18O) and carbon (δ13C) isotope records from the global ocean, we find that variations in the marine carbon cycle lead the climate-cryosphere system (δ13C-lead-δ18O) on 405,000-year eccentricity timescales during the MCO. This is in contrast to the previously reported climate-lead-carbon (δ18O-lead-δ13C) scenario during most of the Oligo-Miocene (∼34–6 million years ago). Further sensitivity analysis and model simulations suggest that the elevated atmospheric CO2 concentrations and the resulting greenhouse effect strengthened the low-latitude hydrological cycle during the MCO, accelerating the response of marine carbon cycle to eccentricity forcing. Tropical climate processes played a more important role in regulating carbon-cycle variations when Earth’s climate was in a warm regime, as opposed to the dominant influence of polar ice-sheet dynamics during the Plio-Pleistocene (after ∼6 million years ago).

Interdependence of the rural housing stock and the rural population: a scientific perspective

This scientific article addresses the pressing issue of providing decent housing for the rural population of the Kyrgyz Republic, which has arisen due to uneven development of demographic and housing trends in rural areas. The research aims to solve this regional problem by managing interdependent demographic and housing trends. The study employs a general scientific methodology to analyze the relationship between the rural population and the volume of rural housing stock. A methodological approach to solving the regional problem of housing provision is presented, including a statistical analysis of demographic and housing aspects in time and space. The main results of the study include data on the mutual influence of demographic and housing dynamics in rural areas and a comparative forecast of demographic and housing parameters of rural development until 2030. Recommendations are provided within the framework of the Republican housing program “My Home” for 2021-2026. This study is highly significant in terms of its practical applicability and relevance for the development of regional policy.

Periodic solution analysis of a population dynamics system model for pulsating organisms

Abstract Population dynamics has a wide range of applications in ecological theory, especially in the fields of plant and animal conservation and the management and development of ecological environments. Periodic solution analysis of a population dynamics model for pulsating organisms. The influence of impulsive dynamics on the periodic solution of the system is investigated in this paper, which considers several types of population dynamics systems with impulsive effects. First, the impulsive differential modeling of the model of a constantator in a polluted environment considering time-lagged growth response and impulsive inputs proves that only ̄t needs to be sufficiently large to have x(t) > m x, such that, the constantator seeks a unique periodic solution for microbial extinction and persistent survivability. Next, a model of integrated pest control is modeled to find, a periodic solution for pest extinction and the existence of (0, I* (t)) is globally stable. Then, a Lur’e system with impulsive biodynamics is explored, modeled with uncertain parameters, and simulated with Chua’s circuit system to determine that the state trajectory lines all eventually converge to 0 and have stable periodic solutions. Finally, the Beddington-DeAngelis predator-prey model with impulsive effects is used to argue, using correlation priming, for the existence of z i * ( t ) = exp { x i * ( t ) } z_i^*\left( t \right) = \exp \left\{ {x_i^*\left( t \right)} \right\} , i = 1, 2, such that z * ( t ) = ( z 1 * ( t ) , z 2 * ( t ) ) T {z^*}\left( t \right) = {\left( {z_1^*\left( t \right),\,z_2^*\left( t \right)} \right)^T} there is a positive ω − periodic solution for this system.

A product requirement influence analysis method based on multilayer dynamic heterogeneous networks

With the promotion of emerging technologies in the era of big data, there has been a diversification in user participation in product requirement development. This has resulted in many complex, diverse, and rapidly iterated user requirements, greatly reducing the applicability of traditional requirement development methods. In this paper, to address the complex and ever-changing relationships among users, requirements, products, and requirement development teams in the product development process, a multilayer dynamic heterogeneous network node influence analysis method is constructed for product requirement development. This method establishes a product requirement development framework based on a multilayer dynamic heterogeneous network consisting of a user layer, requirement layer, component layer, and expert layer in terms of three dimensions: requirement development, requirement evaluation, and time. Based on this framework, indicators such as comprehensive node significance, layer significance, and node influence are designed. To address the issues encountered in small sample data testing, three measurement models are further designed in this paper, effectively improving the sampling efficiency of the multilayer dynamic heterogeneous network. Additionally, calculation models for the comprehensive node influence and comprehensive node influence variation rate are improved and constructed, and corresponding algorithms are designed. This method is applied in an experimental study of product requirement development for new energy vehicles, providing high-quality recommendations for new energy vehicle requirement developers, including functional requirements and product components that need close and timely attention. Moreover, accuracy tests show that the proposed algorithm achieves an average accuracy rate of 0.8611, which is significantly higher than those of other network node centrality measurement methods. This demonstrates the advanced nature and applicability of the proposed method in the field of product requirement development, providing a new way for requirement developers to improve work efficiency.

The Influence of Midlevel Shear and Horizontal Rotors on Supercell Updraft Dynamics

Abstract Large midlevel (3–6 km AGL) shear is commonly observed in supercell environments. However, any possible influence of midlevel shear on an updraft has been relatively unexplored until now. To investigate, we ran 10 simulations of supercells in a range of environments with varying midlevel shear magnitudes. In most cases, larger midlevel shear results in a storm motion that is faster relative to the low-level hodograph, meaning that larger midlevel shear leads to stronger low-level storm-relative flow. Because they are physically connected, we present an analysis of the effects of both midlevel shear and low-level storm-relative flow on supercell updraft dynamics. Larger midlevel shear does not lead to an increase in cohesive updraft rotation. The tilting of midlevel environmental vorticity does lead to localized areas of larger vertical vorticity on the southern edge of the updraft, but any dynamical influence of this is overshadowed by that of much larger horizontal vorticity in the same area associated with rotor-like circulations. This storm-generated horizontal vorticity is the primary driver behind lower nonlinear dynamic pressure on the southern flank of the midlevel updraft when midlevel shear and low-level storm-relative flow are larger, which leads to a larger nonlinear dynamic pressure acceleration in those cases. Storm-generated horizontal vorticity is responsible for the lowest nonlinear dynamic pressure anywhere in the midlevel updraft, unless the mesocyclone becomes particularly intense. These results clarify the influence of midlevel shear on a supercell thunderstorm, and provide additional insight on the role of low-level storm-relative flow on updraft dynamics. Significance Statement Persistent rotation in supercell thunderstorms results from the tilting of horizontal spin into the vertical direction. This initially horizontal spin is the result of shear, which is a change in wind speed and/or direction with height. More shear in the layer 0–3 km above ground level is well understood to lead to stronger rotation within the storm, but the influence of shear in the 3–6-km layer is unclear and is investigated here. We find that horizontal spin originating in the 3–6-km layer has little impact on vertically oriented thunderstorm rotation. Instead, intense regions of horizontal spin that are generated by the storm itself (rather than having originated from the background environment) dominate storm dynamics at midlevels.

The dynamic relationship between foreign direct investment inflows and interest rate in Sri Lanka

Foreign direct investment acts as an engine of rapid growth and development of developing and emerging countries. It helps to promote the host nation’s economic growth, financial inflows and markets, technology, and skills. This study aims to identify the dynamic influence and relationship between Foreign Direct Investment (FDI) and interest rate in Sri Lanka over the period 1978 to 2020. Foreign direct investment inflow has been used as the dependent variable while gross domestic products, interest rate, inflation rate, trade openness and exchange rate are the independent variables. This study used the ARDL model for the analysis. According to the bound test, F statistics is greater than the upper bound value. Therefore, this study confirmed that there is a cointegration relationship between foreign direct investment inflows and other explanatory variables. A negative and significant error correction coefficient of FDI inflows reveals that 128% disequilibrium is corrected each year which implies that FDI moves downward towards long-run equilibrium. This study found that there is no substantial relationship between the interest rate and FDI inflows in the long run and a negative and substantial relationship in the short run. Therefore, this study suggests that the government of Sri Lanka has to reflect on developing a monetary policy and maintaining the balance of interest rate and exchange rate. Because of the currency depreciation, the exchange rate negatively influences FDI.

Marine microdebris pollution in sediments from three environmental coastal areas in the southwestern Argentine Atlantic

Microplastics (MPs) and antifouling paint particles (APPs) are important components of marine microdebris (MDs), which constitute a potential environmental risk. This study analyzed baseline contamination levels of MDs and mesodebris (MesDs) in intertidal sediments at different depths, exploring the geomorphological influence in three Argentine coastal environments: Bahía Blanca Estuary (BBE), Los Pocitos (LP) and Puerto Madryn (PM). The MDs and MesDs samples were characterized by μ-FTIR, SEM/EDX and XRD. The abundance of MPs and APPs in sediments, range between 19.78 and 1087.19 and between 0 and 172.93 items/kg d.w., respectively. Despite variations in population and industrial developments in these areas, MPs abundance shows no significant differences in low and high intertidal zones. However, mean MPs concentrations were higher in the surface layer (0–5 cm) compared to the deeper sediments (5–10 cm), indicating recent MPs deposition. Chemical characterization evidenced the presence of cellulose (CE) and denser polymers as acrylonitrile butadiene styrene (ABS) and polyacrylics (PAN), APPs, metallic and black MDs. Surface degradation and heavy metals (Zn, Cr, and Ba) were also detected in APPs and other MDs, either as additives or adhered to their surfaces. Changes in crystallinity were also observed on the MesDs due to weathering. The calculated polymer hazard index (PHI) and the presence of hazardous polymers such as ABS and PAN indicated an increased risk of MPs pollution on the BBE and PM coasts. The pollution load index (PLI) values (from 4.63 to 5.34) suggested unpolluted to moderately polluted levels. These findings offer insights into potential risks associated with MDs in Argentine intertidal sediments, underscoring the critical need to comprehend the geomorphology and the influence of coastal dynamics. This is crucial for effectively addressing challenges linked to MDs pollution guiding the development of robust management and mitigation strategies.

The Impact of Political Influence and Power on the Indian Judiciary

The growing influence and power of political entities have presented significant obstacles to the autonomy of India’s judiciary. The Principles on the Independence of the Judiciary emphasize the significance of impartiality in rendering judgments, wherein decisions are made only on the basis of factual evidence and legal principles, without any undue limitations or inappropriate influences. The principle of separation of powers, which ensures the independence of the judiciary, is particularly highlighted in terms of the judiciary’s role and its relationship with other branches of government. This research provides a critical analysis of the influence of political factors and power dynamics on the Indian Judiciary. It examines the complex connection between political forces and judicial rulings, investigating situations when the judiciary could be influenced by external pressures. Further, the research offers a comprehensive examination of how the legislative and executive branches of government utilize statutory provisions to reverse judicial rulings. It also explores the significance of the Separation of Powers concept within the Indian context. Moreover, it provides illustrations of cases in which such encroachment of authority has taken place inside the Judiciary, emphasizing the difficulties encountered by the Indian Judiciary in preserving its autonomy and probity. It emphasizes the need to protect the autonomy of the judiciary in a democratic society, while also highlighting the difficulties encountered while trying to act as a fair and unbiased judge. This research makes a valuable contribution to the wider academic discussion around the function of the Judiciary in democratic government and the vital responsibility of safeguarding its independence and integrity.

Simulation study on surface deformation of shallow buried coal seam mining in a gully area

Coal mining subsidence leads to frequent surface ecological and environmental problems. Due to the unique topographic conditions within gully areas, the deformation and damage characteristics, along with the evolution laws of the surface, have been difficult to analyze. To explore the surface movement and deformation law of shallow-buried coal seam mining in a gully area, this study designed a three-dimensional similar-material simulation test simulating the complete movement and deformation of the ground surface under real terrain conditions and proposed a complete data acquisition and processing scheme. Combined with the numerical simulation analysis, we utilized this scheme to analyze the dynamic influence law of coal seam mining in a gully area on the distribution of ground surface stress and displacement as well as on the dynamic characteristics of the ground surface damage. The results show that the existence of gully topography affects the stress distribution of the ground surface and the raw rock of the coal seams underneath and that there exists a stress concentration in the gully area of the ground surface. Furthermore, the mining activities of the coal seams lead to an increase in the degree of stress concentration in the gully area of the ground surface, and the slopes enter into the process of energy accumulation and sudden release, which makes the region prone to the occurrence of geological disasters such as landslides and collapses. In addition, the surface movement and deformation in the gully area are more intense, exceeding the plain area, and the surface movement is affected by the spatial location relationship between the mining area and the slope body, causing the center of the mining area to show obvious eccentricity characteristics. The results of this study provide a reference basis for the safe mining of coal mines in gully topography.

Socioecological factors influencing intraspecific variation in ranging dynamics of western lowland gorillas (Gorilla gorilla gorilla) in Ndoki Forest.

Ranging dynamics are physical and behavioral representations of how different socioecological factors affect an organism's spatial decisions and space use strategies. Western lowland gorillas (Gorilla gorilla gorilla) are a model species to investigate the drivers of spatial dynamics based on both the natural variation in socioecological factors within the species and compared with their mountain gorilla counterparts. In this study, we evaluate the influences of resource seasonality and social dynamics on variation in home range size, utilization, and intergroup overlap among multiple gorilla groups over an 8-year study period in the northern Republic of Congo. This study shows that western lowland gorillas can have small home ranges comparable to mountain gorillas, rather than universally larger home ranges as previously supposed, and that home ranges are stable through time. The largest source of variation in space use was the degree of intergroup home range overlap. The study groups did not demonstrate intraspecific variation in range size nor changes in intergroup overlap with respect to seasonality of fruit resources, but all groups demonstrated expansion of monthly range and core area with group size, matching predictions of intragroup feeding competition. These findings highlight the potential impact of intergroup relationships on space use and prompt further research on the role of social dynamics in ranging strategies. In this study, we reveal a greater degree of variability and flexibility in gorilla ranging behavior than previously realized which is relevant to improving comparative studies and informing conservation strategies on behalf of these endangered primates.

Navigating the green future: Unraveling the role of fintech, decentralization, natural resources, and monetary policy uncertainty in China

Improving environmental integrity is a crucial policy agenda in achieving sustainable development goals, and reliable carbon emission measure is imperative in devising an effective climate strategy. Increasing climate susceptibility instigates us to explore the factors of ecological sustainability. Therefore, we scrutinize the dynamic influence of monetary policy uncertainty, mineral resources dependency, Fintech, fiscal decentralization, and trade on consumption-based carbon emissions (CCE) in China using the quarterly data from Q1-2005 to Q4-2021. For estimation, the study employed the bootstrap autoregressive distributed lag (ARDL) method, and the overall findings exhibit that fiscal decentralization significantly decreases the CCE, while monetary policy uncertainty, Fintech, and natural resources dependency increase CCE. Imports are responsible for higher CCE, while exports report the opposite. Consistent findings are endorsed by the short-run estimates with lower magnitude, and the error correction term significantly adjusts towards the steady state equilibrium with 61.0% quarterly adjustment in case of any deviation from stready state equilibrium. The results also confirm a bi-directional causality among all variables except Fintech, policy uncertainty, and CCE. This study offers relevant policy recommendations.

Joint item recommendation and trust prediction with graph neural networks

Item recommendation and trust prediction are desired by users on social network platforms since they can help users find their favourite items or friends faster. Existing methods usually utilize users’ social relationships to facilitate the item recommendation task and leverage users’ preferences to assist the trust prediction task. While sociological researchers have shown that users’ preferences and users’ social relationships are not isolated but influenced by each other, there are a few studies that model these two tasks jointly. However, in these studies, the incorporation of distrust relations and the dynamic item-specific mutual influence between users’ preferences and users’ social relationships are ignored. In this paper, we propose a joint learning method using graph neural networks for item recommendation and trust prediction tasks, named JoRTGNN. First, users’ distrust relations are incorporated along with trust relations to extract more potential user social relationships, which can benefit both the item recommendation and trust prediction tasks. In addition, a dynamic item-specific mutual influence between users’ preferences and users’ social relationships is highlighted with attention mechanisms for the joint learning tasks. Experiments have been conducted on the Epinions datasets, and the experimental results show a superior performance of JoRTGNN over baselines in item recommendation and trust prediction tasks, which demonstrates that item recommendation and trust prediction can be effectively improved in the process of the mutual influence between users’ preferences and users’ social relationships.

Construction Of Drug Abuses (Case Study at Class 11-A Kupang Penitentiary)

Completers reported higher alcohol use than counterparts. Explores the model's subcategories: “life choices” (substance use, criminal and sexual behavior), static (background and disposition), and dynamic situational influences (occupation, psychological state, recent and past encounters).This research aims to determine the development of drug abuse in the Kupang Class II A Correctional Institution. The method used is an analytical descriptive approach . The data collection method is data from interviews and observations, the data analysis used is qualitative data analysis . The results of the research show that drug abuse guidance in Class IIA Kupang Prison has been achieved implemented in accordance with the Decree of the Minister of Justice of the Republic of Indonesia regarding the pattern of training prisoners/detainees of the Minister of Justice of the Republic of Indonesia, however, its implementation is still not perfect due to various obstacles. The training for narcotics prisoners has so far remained the same as the training for general prisoners . Drug abuse is a special case and should receive special guidance.

Institutional dynamics and road accidents in the road haulage sector: the moderating role of information communication technology

PurposeThe purpose of this study is to investigate the influence of institutional dynamics on road accidents and whether this relationship is moderated by information and communication technology (ICT).Design/methodology/approachThe study adopted a quantitative approach with 133 respondents. Research hypotheses were tested in AMOS version 21. In addition, moderated regression analysis was used to test the moderating role of ICT on the relationship between institutional dynamics and road accidents.FindingsThe results show that vehicle maintenance, policy enforcement, safety culture, driver training and driver management positively influence road accidents. Moreover, the study established that ICT moderates the relationship between institutional dynamics and road accidents.Practical implicationsThe results of this study serve as a practical guideline for policymakers in the road haulage sector. Managers may gain insights on how to design effective interventions to reduce road accidents.Originality/valueThis research contributes to the existing body of knowledge by exploring previously unexplored moderating paths in the relationship between institutional dynamics and road accidents. By highlighting the moderating role of ICT, the study sheds new light on the institutional dynamics that influence road accidents in the context of road haulage companies.

Dynamic Capabilities and Firm Performance: Moderating Effect of Environmental Dynamism

This paper, therefore, conducts much detail with regard to the moderating role of environmental dynamism between dynamic capabilities and firm performance, with special reference to Small and Medium Enterprises (SMEs) of Pakistan. The conceptual framework leans on the proposition by Teece, Pisano, and Shuen (1997) that dynamic capabilities allow reconfiguration of resources for the changing market demand and hence the source of competitive advantage to the firm. It is theoretically possible that empirical studies on the moderating effect of environmental dynamism are possible, and still scarce within this domain—an even more rare context in the case of Pakistani SMEs. Thereby, this research intends to fill that gap by empirically examining how the influence of environmental dynamism plays out at the dynamic capabilities-performance nexus in Pakistani SMEs—a sector pivotal for the economic growth of the nation but also challenged by a unique blend of local business conditions. Understanding how firms can benefit from their dynamic capabilities in relation to their performance in volatile markets has become important within this fast-changing business environment. This paper, therefore, through an intensive review of the literature, traces the development of the dynamic capability theory in highlighting its relevance for firm performance and the critical roles environmental dynamism has played as one of the most emphasized contextual factors in firm performance. Quantitative research design will be used for data collection from a broad base of industries under the SME sector of Pakistan, and it will be collected through cross-sectional surveys to explore the proposed relationships. Findings have revealed an environmental dynamism-relevant moderating effect on the relationship between dynamic capabilities and performance. That is to say, in the most volatile environments, SME performance will be more dependent on dynamic capabilities, and that dependence will imply that the strategic value of the capabilities would become contingent on the level of environmental dynamism. This is congruent with the resource-based view (RBV) theory of strategy: the strategic value of resources and capabilities depends on the fit that such resources will have with the external environment. Implications for managers and policymakers, therefore, could be said to be very pragmatic, since SMEs operating within such dynamic markets would have a crying need to develop and deploy dynamic capabilities in a strategic way to effectively steer through the environment. First, these findings contribute to theoretical development in that they draw and support from the dynamic capability view (DCV) and RBV literature in verifying the contingent value of the dynamic capability with respect to environmental dynamism. It not only adds some fertile insights into the dynamic capabilities framework within an emerging market context like Pakistan but also substantiates some interesting facets for SMEs to gain an edge on their competitive advantage within the fast-changing global business environment.

The diffusion of platform self-operation on reputation-based two-layer network

PurposeDue to the cross-network effect, two-sided users communicate with each other, producing a coupling network. To study the spread of platform self-operation in two-sided users' marketing and purchasing tactics, this paper considers the differences in reputation acquired by platform-owned and third-party operating channels.Design/methodology/approachThis study proposes a two-layer network with cross-network links: one layer represents the social network of consumers, while the other layer represents the competitive network of buyers. A closed system of differential equations, based on the binary dynamics of the stochastic network, is developed to study the trend and stability points of the platform self-operation dissemination. Then the overall benefits of platform are analyzed to unify the platform diffusion and pricing strategies.FindingsThe degree of difference in social influence and cross-network effects affect diffusion synergistically. Cross-network effects hinder diffusion when there is a significant difference of social influence between consumers and sellers but promote diffusion when there is little difference of social influence between consumers and sellers. Additionally, the network weights and reputation gap exhibit a nonlinear correlation with diffusion. For pricing strategy of the platform, it can achieve maximum profit when the pricing of self-operated goods and third-party-operated goods is equal.Originality/valueThis study considers the complex network architecture created by bilateral markets and the dynamic influence of group interactions on product. Additionally, this study takes reputation into account when considering the price and dissemination tactics of various operating channels, offering guidelines for platforms to control merchants and mediate disputes between various operating channels.

Numerical simulation of particle flow around the impulsive monopile

In order to explore the particle flow field characteristics around the impulsive monopile, the particle flow field and particle distribution around impulsive monopile were simulated based on the classical impulsive flow around a monopile at medium and low Reynolds number (Re = 550). The Large Eddy Simulation (LES) technique was harnessed to capture the dynamic flow field around the monopile and to facilitate in-depth analysis of vortex evolution. Concurrently, the Lagrangian approach was employed to track and characterize particle trajectories, shedding light on the patterns of particle diffusion and congregation in the vicinity of the monopile under varying Reynolds numbers. Additionally, this investigation unveils the distinctive behavior of particle flow during the impulsive starting and stopping phases adjacent to the monopile. Leveraging these insights, the study elucidates the intricate influence of the unsteady flow field dynamics around the monopile on the progression of particle flow.