Trend Of Movement Research Articles

Challenges to Ukraine's Demographics: Analysing the Exodus of Economically Active Citizens

Introduction: The relevance of this established research topic relies on the increasing dangers of the population dynamics owing to the end of the Russia – Ukraine conflict and the movement of working-age citizens. Objective: The research intends to evaluate the effects of migration on the rate of Ukraine's population and suggest favourable demography. Factors considered include assessment of the existing population situation, movement trends, forecasting and possible interventions to maintain stability. Methods: The methodologies for evaluating the decade risks of demographic transition impact on Ukraine's economy consist of stages of justification of measures: comprising the collection and estimation of demographic statistics; analysing migration trends; developing scenarios. Results: The study results show the patterns and trends in population increase attributed to the displacement of people. A key aspect of the research is evaluating how population movements and displacement affect the Ukrainian economy, society and international relations. The tasks include getting acquainted with the structure of the Taras Shevchenko National University of Kyiv and formulating recommendations to the government on demographic matters during the war and post-war reconstruction periods. The study seeks to evaluate measures aimed at encouraging the return of migrants, encouraging birth rates and enhancing social amenities. The supportive results will enable a strategic plan to restore the Ukrainian demographic potential. Conclusions: Given the currently prevailing circumstances, specific measures are suggested to reinforce demographic resilience and the effectiveness of such measures. Further directions for enhancing the state policy to attain sustainable population growth and the state's economic advancement are given.

The study of social capital as a mechanism of consolidation in a multiethnic society

In the context of modern challenges and "external" threats, the identification of mechanisms for the consolidation of society is becoming one of the critically important areas of scientific research. In turn, this initiates the study of such an object as social capital. Because it is its nature and structural elements that greatly contribute to the unification processes and the maintenance of order in society. The purpose of the study is to identify the theoretical and methodological foundations and the relevant structure of elements for assessing social capital at the macro level, taking into account the ethnic diversity of the regions and the current conditions of Russia. The basic theories and their leading positions, which are of fundamental importance in relation to the study of social capital at the macro level, are highlighted. Considerable attention is devoted to highlighting the traditions and main provisions of Russian research on social capital, which have theoretical and methodological potential for its research in regional societies, taking into account the peculiarities of functioning in relation to the conditions of Russia. The work is based on the application of general scientific methods, including synthesis and generalization, as well as on a structural approach, methods of systematic and comparative analysis. The paper reflects the results of a theoretical and empirical study of the social capital of multiethnic societies. The work concludes the operationalization of the concept of social capital of a multiethnic society, which allows us to describe and assess the current state of its structural elements such as: the level of generalized, interpersonal and institutional trust, the level of tolerance between peoples, the level of tolerance towards migrants, civil and national identity, the level of civic participation. Also, as an example of the practical implementation of the presented methodology, the work contains a fragment of the results of a sociological study conducted with the participation of the author in one of the multiethnic regions of Russia – the Republic of Bashkortostan. The research conducted according to the methodology described in the work allowed us to conclude that the pressure of external threats really contributes to social unity and cohesion of regional communities as components of Russian society, as evidenced by the received trend of movement of indicators of social capital towards a positive orientation.

Challenges in Training Human Resource of Vietnam in the 4.0 Industrial Revolution

The rapid and strong development of the Industrial Revolution 4.0 has placed significant responsibilities on the education sector, forcing educators to proactively develop forward-looking visions and innovate strategies, while university lecturers must adopt new teaching methods to cultivate a workforce that meets the demands of society in this transformative era. In this context, higher education institutions, as the primary drivers of training activities, play a pivotal role in producing high-quality human resources. This article examined labor movement trends, human resource training needs, and higher education training methodologies within the framework of the Industrial Revolution 4.0. By assessing the current state of Vietnam’s higher education, the study identified key challenges arising from the autonomy of higher education institutions, including challenges arise from the demand for international labor migration with increasingly higher requirements for the global workforce; challenges from the potential replacement of human labor by technology in many jobs; challenges from the need for new skills of labor force; and challenges from blended learning methods. At the results, the study proposed several recommendations for universities in training human resources, regarding innovations in training programs, in teaching methods and technological application, and in the role of lecturers.

Market Dynamics of Short Covering: The Price Rebound Phenomenon and Double Peak Model in China’s Futures

The present study examines the behavior of futures markets in the wake of widespread short selling and subsequent short covering, which frequently lead to notable price increases. Known as the "Double Peak Model," this study provides a thorough analysis by synthesizing empirical data and recent literature. Data on futures contracts for different financial indices and commodities during periods of notable short interest and subsequent short covering are gathered for the study. Using statistical and econometric methods, the research examines trends in price movements and volatility. Key findings show that while short covering can result in sudden and sharp price increases, short selling can improve market efficiency and transparency by improving information flow. The study also emphasizes how crucial institutional involvement, legal frameworks, and market dynamics are in determining these price fluctuations. The Double Peak Model provides a deeper understanding of the mechanisms underlying market behaviors related to short selling and covering, which is useful information for traders, investors, and policymakers. These understandings are essential for creating sensible regulatory policies, enhancing risk management, and creating successful trading strategies.

Creating a repository of archival of documents on the sanitary and epidemiological situation in Kaluga region contaminated with radionuclides as a result of the Chernobyl accident (1987-1994)

The study is relevant due to the need to preserve unique experience of the emergency response to the Chernobyl accident and ensure radiation safety of the population living in radioactively contaminated areas. The study of the impact of consequences of the Chernobyl accident on the health of people living in the areas of radioactive contamination aims to assess the effectiveness of measures to protect the inhabitants of the areas contaminated with radionuclides. The study uses archival information on the elimination of the consequences of the Chernobyl accident which is available on electronic resources. The study aims to create an electronic archive of documents on the sanitary and epidemiological condition in Kaluga region radioactively contaminated as a result of the Chernobyl accident. Information collected from scientific publications is presented. The documents on medical consequences of the Chernobyl accident for the population of Kaluga region derived from the State Archive of Kaluga region are studied. Results. The study analyzed documents from the State Archive of Kaluga region (GAKO): R-2275 “Federal State healthcare institution “Center for hygiene and epidemiology of Kaluga region”; R-3237 “Department of health and drug supply of Kaluga region”. A repository of archival documents containing information on the sanitary and epidemiological situation in the territories of the Kaluga region radioactively contaminated as a result of the Chernobyl accident (for the period of 1987-1994) has been created. Conclusion. Relying on the documents from the R-2275 and R-3237 funds, a repository containing data on the medical consequences for the population of Kaluga region living in radioactively contaminated areas was created (1987-1994). The repository contains the following information: laboratory data from food laboratory studies (including data on the maximum levels of cesium-137 contamination in food); information on the medical examination of the child population and women; data on specialized medical and dosimetric examinations of children and adolescents of the districts of Kaluga region most affected by the Chernobyl accident. The collected information may be used in the analysis of the key trends in the natural movement of the population and the dynamics of morbidity in the districts of Kaluga region most affected by the Chernobyl accident, in order to identify possible changes associated with radioactive contamination of the territories.

Insights on the multiple ions distribution in concrete under stray current: From experiments to multi-field simulation

Stray current can not only corrode steel bars but also cause the movement and accumulation of ions inside concrete. To investigate the distribution law and change mechanism of ions under the effect of stray current, a stray current corrosion experiment lasting 120 hours is carried out on a reinforced concrete beam. The pH value and concentrations of sodium, calcium and chloride ions of solution in the beam are measured at intervals. And the ion concentration distribution is simulated using DuCOM numerical platform. Results show that the ion concentration distribution is basically stable after three days of electrification. The alkalinity at the negative electrode increases, and the acidity at the positive electrode increases significantly. Sodium ion. The daughter and calcium ions gather at the negative electrode under the action of stray current and are far away from the positive electrode. The chloride ion concentration is at the positive electrode. Increase, decrease at the negative pole. The simulation by DuCOM can well reflect the directional movement trend of ions under the action of external current, with prediction error lower than 15%.

Geoeconomic modelling: southwestern trend of vegetable growing in Russia

Relevance. Modern globalization, internationalization, regional competitive differentiation actualize geoeconomic modeling methods for geopolitical planning, management and control. The novelty of the proposed solutions is the proposed concept, based on the translation of the ideas of theoretical mechanics into economics.Methodology. Considering the annual values of statistical indicators of territorial concentrates as a system of geographically distributed objects (subjects of the Russian Federation), it is possible to determine the geographic barycenter. Knowing the values of the geocoordinates of the barycenter, it is possible to determine the tendencies and trend of the barycenter movement as an indicator of the dynamics of the system under consideration through the analysis of the dynamics of these coordinates. Based on Russtat data on the annual gross harvest of agricultural crops (vegetables), population by constituent entities of the Russian Federation for the period 1991-2021, data on the coordinates of the administrative centers of the constituent entities of the Russian Federation, the values of the geographic coordinates of the barycenter of vegetable growing in Russia were calculated.Results. For 2021, the geographic coordinates of the barycenter of vegetable growing in Russia are 50.30° N and 49.49° E with an average regional value with an average regional annual vegetable har-vest of 1722.52 million centners/year and fluctuations in the coordinates of the barycenter in the zone of 3-4 geographic degrees or three hundred territorial kilometers with a pronounced south-west trend Analysis of the dynamics of the barycenter for the period 1991-2021. will allow to reveal a slight shift of the vegetable growing barycenter to the south by 3.5 degrees with an increase in the average regional vegetable harvest by 124.11 million centners per year for each degree (or the all-Russian by more than 9,500 million centners per year for each degree to the south), a slight shift of the vegetable growing barycenter to the west by 4.5 degrees with an increase in the average regional vegetable har-vest by 86.5 million centners per year per degree (or the All-Russian by more than 6,660 million cent-ners per year for each degree to the west). For the period 1991-2021, two opposite trends in the devel-opment of vegetable growing are distinguished. In the period from 1991 to 2000, the movement of the coordinate of the vegetable growing barycenter went in the direction of the northeast of Russia, in the period 2000 to 2021 -- on the contrary, to the southwest.The conclusion is made about the existence of a relationship between the development of vegetable growing and the geopolitics of Russia in the period under review. The obtained method and results can be used in strategic state management of agricultural production in Russia.

The Approaches to Predict Stock Prices by Random Forest

Abstract. People are always curious about how to predict the stock prices, various type of prediction tools are introduced to help people explore the trend of the stock price movement. With the development of the machine learning, there are more and more models and methods that we can use to predict the stock prices, while Random Forest, a typical machine learning algorithm, will be discussed in this article to examine its performance in the stock market. The data utilized in this study is sourced from Yahoo Finance, with several additional indicators computed and incorporated into feature set of the Random Forest model. To evaluate its performance, a comparison between the Random Forest model and the simple linear regression model is going to be conducted, which is a considerably basic model and serves as a benchmark for the minimum returns individuals can expect. The RMSE and MAPE will be compared firstly, which can help us assess which model demonstrates superior predictive accuracy, while the ROI derived from the strategy based on these models predictions will serve as a measure of their practical performance in the stock market. Collectively, this data will substantiate that Random Forest is indeed an effective model that is capable of assisting individuals in achieving greater profits.

LABOR MIGRATION: GLOBAL AND REGIONAL CHARACTERISTICS IN THE CONTEXT OF REMITTANCES

This article discusses aspects and integration characteristics of international migration in the world and regions. Based on statistical information, the main trends of the migration movement and prospects for the development of the labor market are determined. The author analyzed the data on priority country directions of labor migration from Uzbekistan and the state of money transfers on a global, regional and national scale. Information on domestic legal policy and ratified international agreements is summarized. He proposed possible solutions to improve research tools in the study of migration processes.

Prediction of the Relative Resource Abundance of the Argentine Shortfin Squid Illex argentinus in the High Sea in the Southwest Atlantic Based on a Deep Learning Model.

To analyze the impact of the marine environment on the relative abundance of Illex argentinus (high and low categories) in the southwest Atlantic, this study collected logbook data from Chinese pelagic trawlers from December 2014 to June 2024, including vessel position data and oceanographic variables such as sea surface temperature, 50 m and 100 m water temperature, sea surface salinity, sea surface height, chlorophyll-a concentration, and mixed layer depth. Vessel positions were used to enhance the logbook data quality, allowing an analysis of the annual trends in the resource center of this squid at a spatial resolution of 0.1° × 0.1° and a temporal resolution of ten days. The findings showed that the resource center is primarily located around 42° S in the north and between 45° S and 47° S in the south, with a trend of northward movement during the study period. Additionally, we constructed two ensemble learning models based on decision trees-AdaBoost and PSO-RF-aiming to identify the most critical environmental factors that affect its resource abundance; we found that the optimal model was the PSO-RF model with max_depth of 5 and n_estimators of 46. The importance analysis revealed that sea surface temperature, mixed layer depth, sea surface height, sea surface salinity, and 50 m water temperature are critical environmental factors affecting this species' resources. Given that deep learning models generally have shorter running times and higher accuracy than other models, we developed a CNN-Attention model based on the five most important input factors. This model achieved an accuracy of 73.6% in forecasting this squid for 2024, predicting that the population would first appear near the Argentine exclusive economic zone around mid-December 2023 and gradually move east and south thereafter. The predictions of the model, validated through log data, maintained over 70% accuracy during most periods at a time scale of ten days. The successful construction of the resource abundance forecasting model and its accuracy improvements can help enterprises save fuel and time costs associated with blind searches for target species. Moreover, this research contributes to improving resource utilization efficiency and reducing fishing duration, thereby aiding in lowering carbon emissions from pelagic trawling activities, offering valuable insights for the sustainable development of this species' resources.

Multiscale study of interfacial properties of carbon fiber reinforced polyphthalazine ether sulfone ketone resin matrix composites

In view of the limitations of traditional research tools on interfacial failure mechanisms in fiber/PPESK composites, this work proposes a multiscale research tool to carry out an in-depth study of the interfacial behavior between fibers and matrix. Based on microdroplet debonding tests, at the mesoscopic scale, the influence of residual thermal stress on the interface damage mode is explored through finite element (FEM) simulations. The evolution mechanism of composite material interfaces in spatial and temporal dimensions is examined based on changes in interfacial stress distribution, energy dissipation, and damage morphology during the debonding process, which can be summarized as follows: accompanied by elastic-plastic deformation and friction effects, the progressive process from localized to complete failure presents a dominant Type II damage mode at the interface. To further explore the interface failure mechanism at the molecular level, an interface model of CF/PPESK composite materials was established using molecular dynamics (MD) method. By monitoring the atom movement trend, the “fiber-matrix displacement synergistic effect" in the interfacial shear damage process was revealed, thereby establishing a multiscale mapping relationship of composite material interface. Based on this, the combination of FEM and MD was utilized to investigate the interface damage process of composite materials under different service conditions and to reasonably predict the initiation and expansion of microcracks. This study provides a pioneering perspective on interface damage research in composite materials with a “top-down” multiscale approach.

A Study on the Effect of Urban Form on the Street Interface Rhythm Based on Multisource Data and Waveform Classification

Good-quality urban street space is crucial for improving walkability. Frequency and amplitude are the main spatial characteristics of the street interface rhythm, known as a “virtual–real” relation. Exploring the mechanism influencing the urban street interface rhythm can help grasp the movement trend. In this study, the correlation between frequency and urban form is explored through a Pearson correlation analysis with multisource data, and the factors influencing the urban street interface rhythm are presented. The results indicate that frequency has a moderate negative correlation with the block scale and a moderate positive correlation with the number of pedestrian access entrances (PAE-n); the PAE-n also has a strong negative correlation with the block scale. Some spatial characteristics of outstanding streets from different countries are analyzed and discussed based on waveform classification. The regularities of interface rhythm that exist within multiple streets are found: multiple gaps on the street interface exist, acting as a “beat”, which regularly integrates or separates the street interface rhythm. The frequency and amplitude of the “beat” significantly affect streets’ walkability, and the amplitude is generally low and uniform, with good visual accessibility in all directions. A “Small Block and Dense Grid” becomes a key factor in improving walkability. Basic knowledge of the street interface rhythm in urban walking space research is supplemented by this study. Furthermore, theoretical guidance and parametric evidence are provided to improve walkability and promote the continuation of the traditional context.

STAFGCN:A spatial-temporal attention-based fusion graph convolution network for pedestrian trajectory prediction

Pedestrian trajectory prediction provides crucial data support for the development of smart cities. Existing pedestrian trajectory prediction methods often overlook the different types of pedestrian interactions and the micro-level spatial-temporal relationships when handling the interaction information in spatial dimension and temporal dimension. The model employs a spatial-temporal attention-based fusion graph convolutional framework to predict future pedestrian trajectories. For the different types of local and global relationships between pedestrians, it first employs spatial-temporal attention mechanisms to capture dependencies in pedestrian sequence data, obtaining the social interactions of pedestrians in spatial contexts and the movement trends of pedestrians over time. Subsequently, a fusion graph convolutional module merges the temporal weight matrix and the spatial weight matrix into a spatial-temporal fusion feature map. Finally, a decoder section utilizes TimeStacked Convolutional Neural Networks to predict future trajectories. The final validation on the ETH and UCY datasets yielded experimental results with an Average Displacement Error(ADE) of 0.34 and an Final Displacement Error(FDE) of 0.55. The visualization results further demonstrated the rationality of the model.

THE IMPULSES OF MODERNJADIDISM AND THE ROLEOF PRINTING

Jadidism, a reform movement among Muslims of the Russian Empire in the late 19th and early 20th centuries, played a key role in cultural and educational evolution. One of the main factors that contributed to its development began to be distributed in the form of newspapers, magazines, fiction books, scientific manuals, etc. The purpose of this study is to analyze the role of the press in the development and spread of Jadidism.The scientific originality of the work lies in deepening the understanding of the processes of the cultural revolution among the Turkic-Muslim peoples living on the territory of the Russia n Empire, and the role of the press in these processes. Practical originality lies in the possibility of using the data obtained to develop modern traditions of cultural and educational development of the Turkic peoples.The article uses historical analysis as well as descriptive and sociocultural methods to determine the relationships between technological advances in printing and ideological changes in Jadidism, using print methods such as a literacy measurement tool, the promotion of secular education, and the formation of modern Turkic identity.The study showed that print media are a central mechanism in disseminating Jadidist idea s and establishing the positions of reformers. The analysis found that the use of printed materials significantly accelerated economic development and led to profound changes in socia l development.The results of the study can be used to develop strategies for supporting and developing cultural and educational initiatives , as well as to study contemporary media in the field of socia l movement and progressive trends in other cultural contexts.

Study on water entry impact characteristics and parameter influence analysis of the vehicle passing through the thin crushed ice zone in a polar environment

The problem of water entry in polar environments holds significant research value for polar resource exploration and military applications. This study uses computational fluid dynamics and the discrete element method (CFD-DEM) to investigate the complex process of a vehicle entering water through a thin crushed ice zone. Experimental data validates the efficiency of the coupling algorithm. The primary focus of this study is to investigate the influence of crushed ice shapes, arrangement patterns, coverage densities, and sizes within thin crushed ice zones on the process of water entry. A comprehensive analysis is carried out to assess how the characteristic parameters of different thin crushed ice zones affect the dynamic behavior of the vehicle during water entry and the movements of the crushed ice. Concurrently, the influence of different velocities of the vehicle on the water entry process through a specific thin crushed ice zone is analyzed. The results show that when the crushed ice is in a regular arrangement, it exhibits a circular immersion phenomenon and a cross-shaped passive movement trend. The arrangement patterns, coverage densities, and sizes of the crushed ice have different effects on the water entry process. Of these factors, the complexity of the influence of crushed ice sizes on the water entry process stands out. Meanwhile, the water entry velocity plays a crucial role in determining the relative significance of the hydrodynamic force and the collision force of crushed ice on the total resistance of the vehicle during water entry. These insights provide valuable guidance for the planning and execution of missions in polar regions.

A framework for spatial-temporal cluster evolution representation and analysis based on graphs

Analysis on spatial-temporal data has several benefits that range from an improved traffic network in a city to increased earnings for drivers and ridesharing companies. A common analysis technique is clustering. However, most clustering techniques consider a constrained representation of clusters that is limited to a single timestamp. Evolving clusters exist through several timestamps and interact with other spatial-temporal objects or clusters, having cluster relationships. When many evolving clusters exist for analysis, a graph can be used to represent cluster evolution. In this article, we propose a framework for graph-based cluster evolution representation and analysis. The framework represents cluster structure and relationships as well as provides a graph representation of cluster evolution for analysis. Evaluation is done in three case studies with spatial-temporal data about taxis that can identify important phenomena or trends in movements in a city for traffic improvement.

Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors.

Wearable monitors continue to play a critical role in scientific assessments of physical activity. Recently, research-grade monitors have begun providing raw data from photoplethysmography (PPG) alongside standard raw data from inertial sensors (accelerometers and gyroscopes). Raw PPG enables granular and transparent estimation of cardiovascular parameters such as heart rate, thus presenting a valuable alternative to standard PPG methodologies (most of which rely on consumer-grade monitors that provide only coarse output from proprietary algorithms). The implications for physical activity assessment are tremendous, since it is now feasible to monitor granular and concurrent trends in both movement and cardiovascular physiology using a single noninvasive device. However, new users must also be aware of challenges and limitations that accompany the use of raw PPG data. This viewpoint paper therefore orients new users to the opportunities and challenges of raw PPG data by presenting its mechanics, pitfalls, and availability, as well as its parallels and synergies with inertial sensors. This includes discussion of specific applications to the prediction of energy expenditure, activity type, and 24-hour movement behaviors, with an emphasis on areas in which raw PPG data may help resolve known issues with inertial sensing (eg, measurement during cycling activities). We also discuss how the impact of raw PPG data can be maximized through the use of open-source tools when developing and disseminating new methods, similar to current standards for raw accelerometer and gyroscope data. Collectively, our comments show the strong potential of raw PPG data to enhance the use of research-grade wearable activity monitors in science over the coming years.

Networks of risk: international tourists as a biosecurity pathway into national parks

International tourists are recognised as vectors of alien microbes, plants, and animals into protected areas worldwide, either by introducing species from overseas or redistributing alien species within a region. Quantitative estimates of the risk from this introduction pathway have relied on surveys of invasive alien species associated with tourist clothing or transport vectors. In contrast, the large-scale movement of tourists across multiple protected areas within a region has rarely been examined. The New Zealand International Visitor Survey was used to estimate the frequency with which several thousand international travellers visited the nation’s 13 national parks. Trends in international visitor movements were compared immediately prior to the closure of international borders due to the SARS-CoV-2 pandemic and again once the border had reopened. Approximately one-third of international visitors only visited a single national park but over 20% visited five or more. The long tail in the frequency of national parks visited highlights that a small number of tourists pose a greater risk of introducing or moving invasive alien species among different protected areas. European tourists visited more national parks and were more likely to camp or stay in mountain huts while in New Zealand, potentially posing a greater biosecurity risk than other nationalities. The largely montane nature of most national parks imposes a strong bioclimatic filter on alien species establishment and combined with border controls, suggests international tourists pose a greater risk by disseminating already established alien species more widely among and within national parks. Network analyses highlighted geographic clustering of national parks based on tourist movements that might facilitate regional spread of alien species. Greater investment in the education of international tourists about the biosecurity risks they pose through spreading alien species into national parks is needed to address Target 6 of the Global Biodiversity Framework.

Monocular visual obstacle avoidance method for autonomous vehicles based on YOLOv5 in multi lane scenes

This study explores a more effective obstacle avoidance method for autonomous driving based on the monocular vision system of YOLOv5. The study utilizes the YOLOv5 model to detect obstacles and road signs in the environment in real-time, including vehicles, pedestrians, traffic signals, etc., identifying objects of different sizes and angles, providing accurate obstacle avoidance decision inputs. Then, we use a path planning algorithm based on deep reinforcement learning to combine the detected obstacle information with the current state of the vehicle, dynamically generating safe and efficient driving paths. In order to further improve the obstacle avoidance effect, a monocular visual autonomous driving obstacle avoidance aggregation network was introduced in the study, and the MMA (Multi lane monocular visual autonomous driving) obstacle avoidance method was established. The future movement trend of obstacles was predicted by setting an improved monocular obstacle avoidance loss function to sense historical data and the environment. The experimental results show that MMA has significantly enhanced obstacle avoidance and driving efficiency. The accuracy of the MMA obstacle avoidance method fluctuates between 78.76 % and 88.26 %, showing the best overall performance. The accuracy also shows an upward trend with the increase of the data sample size.

Wetting and Dewetting Behaviors of Droplets on the Nanoring Surface

AbstractThis study uses molecular dynamics simulations to investigate the wetting behavior of water droplets on a gold substrate with annular grooves. The research finds that droplet size and substrate hydrophilicity similarly affect wetting behavior. Enhanced hydrophilicity changes the velocity trend of droplet contact line movement, while droplet size impacts the magnitude of velocity change. Contact angle fluctuations are observed and analyzed theoretically based on Young's equation. The results provide insights into the relationship between droplet dynamics and surface structure, contributing to a better understanding of wetting processes at the microscopic level.