Contact Network Research Articles

Socially-determined factors of positive transformation of the professional and labor self-concept of persons with musculosketal disorders

The article studies social factors that determine the features of transformation of professional-labor self-concept in students with musculoskeletal disabilities studying under inclusive conditions in organizations of secondary vocational and higher education. The study was carried out on a sample of 106 students with musculoskeletal disorders of final years of educational organizations, in whom positive, negative, and neutral forms of transformation were recorded during the study. It has been revealed that in the group of students characterized by positive changes in professional and personal development during education and professional training, the transition of maladaptive forms of professional and labor self-concept into adaptive ones that allow them to achieve success in professional development, the majority of them are those who have an extensive network of social contacts, including friends with disabilities, classmates, and other people without any disabilities, teachers, and professors who give them the opportunity to develop their professional self-concept. In this group, most students have high rates of satisfaction of basic psychological needs for autonomy, social contacts, and competence, whereas in the group of students characterized by negative transformation of professional and labor self-concept, many identify themselves only with the social group of disabled people, feel alienated from the outside world with excessively high rates of satisfaction of basic psychological needs, which demonstrates their helplessness and deprivation of conditions of their professional and personal development.

3d topological characterisation of aggregates contact network in asphalt mixture

Aggregates contact each other to form a complex network. 3D topological models are established to characterise the mesostructue of asphalt mixtures. Upon analysing the distribution of algebraic connectivity ( La ), it’s observed that topologies are dominated by the topologies corresponding to La = 1.000 and La = 2.000 . And 10 representative topologies are identified. Furthermore, Upon analysing the relationship between coordination number( K n ), clustering coefficient( C i ) and the maximum size, it’s observed that with the increase of the maximum size, the AC asphalt mixture skeleton is more compact, the compactness of the SMA asphalt mixture is not significantly affected and the fine-grained OGFC asphalt mixture has a more compact skeleton than medium-grained OGFC mixture. Moreover, the AC asphalt mixture skeleton is relatively loose, the SMA asphalt mixture skeleton is more compact and the OGFC asphalt mixture skeleton exhibits the highest degree of compactness.

How Does the Largest Cluster in the Strong Network Rule Granular Soil Mechanics? A DEM Study

ABSTRACTThe contact network of granular materials is often divided into strong and weak subnetworks, which play different roles in micromechanics. Within the strong contact network, there exists the largest connected component, that is, the largest cluster, which may connect system boundaries and could be the most important structure in force transmission of the whole system. This paper concerns the particular features of the largest cluster in the strong contact network of granular materials, by considering the combining effects of loading path and particle shape. A series of true triaxial tests with various intermediate principal stress ratios are conducted for granular assemblies of different shaped particles using the discrete element method (DEM). Both the macroscopic stress–strain responses and the microscopic topological changes of the contact network are investigated. It is found that both particle shape and loading path will influence the shear strength and the topological features of the strong network. The threshold (the ratio to the average force) is used to distinguish the strong and weak networks, and a critical threshold can be identified by comparing the network‐based metrics. The largest cluster within the strong network approaching the critical threshold can span the boundaries in each direction with minimum contacts, which occupies a small portion of particles and contacts but transmits a considerable portion of the applied stress. In addition, the similar contribution weight of the largest cluster to the deviatoric stress is identified for granular materials with different particle shapes.

ВПЛИВ КОНКУРСІВ НА РОЗВИТОК КАР’ЄРИ СКРИПАЛЯ

The article analyzes the impact of competitions on the development of a violinist’s career. Competitions play a significant role in the development of a violinist’s career. They provide musicians with the opportunity to show their talents, gain recognition, expand their network of professional contacts and increase their reputation. Preparation for the competition often requires intensive and detailed study of the repertoire, which improves the musician’s technical skills. Winning or participating in well-known competitions can draw attention to a musician from professional colleagues, conductors, agents and music critics. Successful contestants often get the opportunity to perform on prestigious stages and participate in various music festivals, which can greatly expand their audience. Many competitions offer significant cash prizes and scholarships that can help musicians financially support their education and further development. It has been proven that competitions are often a place to meet other musicians, teachers, producers and other professionals of the music industry, which can become an important factor in a future career. Participating in competitions helps musicians develop endurance, stress resistance and the ability to perform in front of an audience, which are essential skills for a professional career. Separately, competitions are an important stage in the professional formation of violinists, providing them with many opportunities for development and improvement. It is considered which technical, musical and personal qualities are the most important for achieving high results at competitions. Achieving these goals will help to better understand the importance and impact of competitions on the professional path of violinists, as well as to develop practical recommendations for improving this process. Studying the impact of competitions on the career development of violinist shows that they are an important tool for professional growth. It is important to support musicians at all stages of preparation and participation in competitions, including technical, psychological and financial assistance. Contest organizers should pay special attention to the objectivity of evaluation and ensuring equal opportunities for all participants.

Novel sampling strategy for regular nucleic acid testing in low risk areas during epidemics

Large-scale regular nucleic acid testing (NAT) such as Regular-1/7, played a crucial role in the successful and sustained containment of COVID-19 in China, enabling rapid case detection in low-risk areas. However, Regular-1/7 strategies are extremely costly and time-consuming. To address these challenges and facilitate the broader implementation of large-scale NAT during outbreaks of highly contagious diseases with long incubation periods, we propose a novel sampling strategy called Weighted Hub and Time Sampling (WHTS). This strategy considers the intensity of social activity, the degree of social overlap, and the time interval since the last NAT for each individual. Based on a scale-free contact network model, we simulated the spread of scenario in a community and compared the performance of the WHTS strategy to the Regular-1/7 strategy in terms of cost reduction and shorter alert time. The results show that WHTS-1/14 strategy can save half of the cost, and WHTS-1/7 strategy can alert 1.0 days in advance, compared to Regular-1/7 strategy. Additionally, The WHTS-1/14 strategy also achieves promising results under various scenarios, even though it samples half as many people as the Regular-1/7 strategy. Our study offers a valuable reference for large-scale testing in future efforts to manage emerging infectious diseases.

Discrete control model Q-learning for an energy storage system with a hydrogen unit of an autonomous hybrid power plant of a railway substation

The paper considers the prospects for creating autonomous hybrid power plants using renewable energy sources and hydrogen as energy storage systems, as well as storage batteries, for the railway power supply system. A comparative analysis of various energy storage systems is carried out. A simulation model has been created that takes into account the characteristics of electric rolling stock trains, a model of the contact network of the inter-station zone of the railway stage, and a model of the energy storage system. Managing the flow of electricity in an autonomous hybrid power plant requires considering forecasts of electricity consumption and generation and the level of charge of the energy storage device. To solve the problem of synthesizing a control algorithm, the use of matrix Q-learning is proposed. The novelty of the study lies in the proposed approach of applying Q-learning to the problem under consideration based on discretization of input and output parameters of the model and verification of the approach on a simulation model built for a real railway section between the Yaya and Izhmorskaya stations (Kemerovo region of the Russian Federation). It is shown that the use of the proposed system makes it possible to equalize the voltage in the network between traction substations and provide a significant increase in the capacity of the railway section, and the proposed method of matrix Q-learning makes it possible to synthesize an effective algorithm for controlling the energy storage system as part of an autonomous hybrid power plant.

Estimation of bearing capacity of bimsoils under shallow foundations

Bimsoils, consist of fine soil matrix and coarse rock aggregates, and are widespread as sedimentary soils. The bearing behavior of bimsoils are significantly affected by rock fraction. However, the mechanism governing the coarse fraction effect remains unclear. The traditional analysis methods are not effective in describing the rock fraction effect due to heterogeneous structure. To this end, 91 simulations have been performed to investigate the bearing capacity of bimsoils (mainly of two-dimensional, 2D) under shallow foundations using finite element method (FEM). It is found that the densified matrix bridge as well as the coarse aggregates forms a strong contact network which is responsible for the coarse fraction effect. A structure variable is introduced to quantify the reinforcing effect of rock aggregates. Then, a model incorporating the structural variable is proposed to evaluate the coarse fraction effect on the bearing capacity of bimsoils. Compared with the conventional method for pure soil matrix, only two additional parameters are required, and they can be readily calibrated by laboratory tests. The model is further validated by data available in literature, which can effectively estimate the bearing capacity of bimsoils under shallow foundations with a various of rock contents and rock characteristics.

Evolutionary dynamic of the coupled awareness-epidemic networks with higher-order structure

Mitigating epidemic spreading and outbreaks is crucial to reducing their significant impacts on people’s lives. Although research has begun to consider the impact of information networks on disease transmission in recent years, most studies have not fully considered the high-order characteristics in network structures. To better capture the dynamics of epidemic spreading and comprehensively understand and predict epidemic transmission patterns, a model of epidemic spreading in a coupled awareness-epidemic model, considering higher-order structures, is proposed. Extensive simulations on real and synthetic structured networks show that information networks influence the spread on physical contact networks by altering individual behaviors, leading to a transition from bistability to a single stable state induced by higher-order structures. Through theoretical analysis, it is proved that the corresponding conclusion is that as the information influence value (an indicator that measures the impact of information networks on physical contact networks) decreases, the impact of higher-order structures on the system’s dynamic behavior gradually weakens. This leads to the disappearance of the bistable phenomenon originally caused by the presence of higher-order structures, and the system transitions from a bistable state to a single stable state. This transition is accompanied by an increase in the threshold for epidemic outbreaks and a decrease in the stable infection density. This work contributes to a deeper understanding of the influence of information on epidemic dynamics, providing important theoretical guidance for the future development of more effective prevention and control strategies.

Genome-wide chromosome architecture prediction reveals biophysical principles underlying gene structure.

Classical observations suggest a connection between 3D gene structure and function, but testing this hypothesis has been challenging due to technical limitations. To explore this, we developed epigenetic highly predictive heteromorphic polymer (e-HiP-HoP), a model based on genome organization principles to predict the 3D structure of human chromatin. We defined a new 3D structural unit, a "topos," which represents the regulatory landscape around gene promoters. Using GM12878 cells, we predicted the 3D structure of over 10,000 active gene topoi and stored them in the 3DGene database. Data mining revealed folding motifs and their link to Gene Ontology features. We computed a structural diversity score and identified influential nodes-chromatin sites that frequently interact with gene promoters, acting as key regulators. These nodes drive structural diversity and are tied to gene function. e-HiP-HoP provides a framework for modeling high-resolution chromatin structure and a mechanistic basis for chromatin contact networks that link 3D gene structure with function.

From agent-based simulations of disease dynamics to expert support on public health interventions

Abstract Agent-based epidemiological simulators have long been used to predict the dynamics of infectious diseases. They allow to combine compartment approaches with representing contact networks derived from real or synthetic populations. Often, scenario techniques are applied to model the impact of public health interventions. During the COVID-19 pandemics the agent-based simulator COVASIM has been established for modelling the spreading of SARS-CoV-2. It includes four different contact networks related to homes, schools, workplaces and environment. During the pandemic it became obvious that the current simulation techniques were not sufficient to cover important needs in public health administrations and society. While most simulations were based on scenarios predicting expected numbers for the infected, hospitalized or critically ill, these studies could not provide easily strategic options on a variety of equivalent public health interventions, which are all suitable to keep disease dynamics within acceptable bounds, set e.g. by hospital capacity. Knowing about a variety of equivalent options, however, is of crucial importance to enable a fair burden sharing throughout all groups of society. Therefore, we applied machine learning techniques to create an inverse model for epidemiological simulations based on COVASIM. For given transmission rates it outputs a range of quantitative interventions which are equivalently suitable to keep epidemiological dynamics within predefined bounds. Currently, it covers interventions like school and workplace closings and other mobility restrictions. Future work will be directed to include other interventions, like vaccination campaigns, and we will work to make the approach more generalizable for other infectious diseases. The tool may turn out helpful fur public health administrations and stimulate the public debate on the best way a society may take in a pandemic event or other situations where public health action has to be imposed. Key messages • Machine Learning allows to invert agent based simulators. • Instead of disease dynamics simulations a set of equivalent public health interventions consistent with pre-defined constraints can be calculated.

Europol 25, Hungary 20

Aim: Europol has evolved over the last quarter of a century, as its legal framework has changed in line with EU requirements, and its tasks have expanded and its network of contacts has become more extensive. Methodology: Beyond the national offices of EU Member States, close cooperation is now possible across several continents through operational, strategic and working agreements with third countries. Findings: The unique use of a liaison officer system and participation in joint investigation teams helps to build trust-based relationships. Over the years, several specialised crime centres have been set up. Value: In Hungary, the design of the national unit has been developed in line with EU expectations and has adapted continuously over the last twenty years to the changes at Europol.

Europol 25, Magyarország 20

Aim: Europol has evolved over the last quarter of a century, as its legal framework has changed in line with EU requirements, and its tasks have expanded and its network of contacts has become more extensive. Methodology: Beyond the national offices of EU Member States, close cooperation is now possible across several continents through operational, strategic and working agreements with third countries. Findings: The unique use of a liaison officer system and participation in joint investigation teams helps to build trust-based relationships. Over the years, several specialised crime centres have been set up. Value: In Hungary, the design of the national unit has been developed in line with EU expectations and has adapted continuously over the last twenty years to the changes at Europol.

Finding patient zero in susceptible-infectious-susceptible epidemic processes.

Finding the source of an epidemic is important, because correct source identification can help to stop a budding epidemic or prevent new ones. We investigate the backward equationsof the N-intertwined mean-field approximation susceptible-infectious-susceptible (SIS) process. The backward equationsallow us to trace the epidemic back to its source on networks of sizes up to at least N=1500. Additionally, we show that the source of the "more realistic" Markovian SIS model cannot feasibly be found, even in a "best-case scenario," where the infinitesimal generator Q, which completely describes the epidemic process and the underlying contact network, is known. The Markovian initial condition s(0), which reveals the epidemic source, can be found analytically when the viral state vector s(t) is known at some time t as s(0)=s(t)e^{-Qt}. However, s(0) can hardly be computed, except for small times t. The numerical errors are largely due to the matrix exponential e^{-Qt}, which is severely ill-behaved.

Phylodynamic Structure in the Botswana HIV Epidemic.

Studying viral sequences can provide insights into the structure of host contact networks through which the virus is transmitted. Uncovering the population structure of the HIV-1 epidemic in Botswana will help optimise public health interventions and may identify hidden sub-epidemics. We sought to determine the phylodynamic structure of the Botswana HIV-1 epidemic from viral sequence genetic data. The Botswana Combination Prevention Project (BCPP) randomly sampled 20% of households in 30 villages in Botswana between 2013-2018 and tested for HIV-1. Extensive demographic data were collected from all participants and next-generation full-genome HIV-1 sequences were generated from HIV-1 positive participants (n = 4,164), 78% of whom were on antiretroviral treatment (ART). We inferred the stage of infection (< or > 1 year) among HIV-1 cases based on nucleotide diversity and clinical data using a previously trained machine learning model. We then reconstructed time-resolved gag and pol phylogenies from sequences, other Botswana cohorts and publicly available sequences that were genetically close to those from Botswana. We statistically explored phylogenies for partitions with diverging patterns of coalescence, indicating sub-epidemics, and estimated viral effective population size through time, a measure of viral incidence, for each partition. Finally, we compared the demographic makeup, clinical and geographic characteristics across partitions using χ2, ANOVA tests and Tukey analysis. We identified three partitions of time-resolved gag and pol phylogenies, revealing divergent patterns of coalescence and HIV-1 transmission. In both gag and pol phylogenies, partitions with persistent growth and transmission were characterised by lower treatment coverage and more recent infections when compared to other partitions. The Southern and South East regions of Botswana were over-represented in the fast-growing partitions. Our findings suggest that transmission is slowing in segments of the population that have high ART coverage. However, recent infections are over-represented in ongoing sub-epidemics. The phylodynamic structure suggests that there are districts with higher growth and prioritising these in the deployment of public health interventions might curb new infections. Nonetheless the high mobility of Botswana residents should be taken into consideration in implementing effective interventions to combat HIV-1.

DIGITIZATION DEVELOPMENT OPPORTUNITIES IN HUNTING MANAGEMENT IN HUNGARY

In the course of my scientific research so far, I have investigated many areas of professional administration from the point of view of how information communication devices (especially smartphones and drones) can improve and make the administration of the area more efficient. Of these, hunting management stands out for me and is particularly important, which is the main focus of this study. There are several reasons for this. On the one hand, I hunt myself, and as a senior official of the county's hunting civil organizations, I have a broader knowledge and network of contacts about the background of the area's administration and operating rules than the general citizen's perspective. On the other hand, in this area, I came to the formulation of a research result, which I hope will be able to be put into practice in the future, to convince the legislator of its raison d'etre. There are many opinions regarding what hunting can be considered: a leisure activity, a form of sport, or a way of life. I myself am a supporter of the latter definition, since we are talking about a complex activity that cannot be grasped solely from the aspect of one characteristic. Accordingly, the regulation of hunting is also a complex area of law covering several branches of law, which includes elements of civil law, criminal law and, of course, administrative law, but can also be approached from an environmental law point of view.[1] I believe that this fact also clearly shows that it is useful and by now even expected that the authorities can carry out better administrative processes in relation to the administration of the area with the help of the best possible technical support. In the following, I would like to support the applicability of drones and smartphones, especially by presenting the concept of the e-register of hunting

Structural properties and mechanical behavior of three-dimensional cylindrical particle-like systems under in situ loading

To investigate the mechanical behavior of granular systems and their impact on density uniformity during compression, a three-dimensional micro-CT in situ loading experiment was conducted on a cylindrical granular system. The granular system was subjected to tomographic scanning and reconstruction, and the variation patterns of structural parameters such as volume fraction, porosity, and intrinsic density during the in situ loading process were analyzed. Internal pores within the granular system were extracted to obtain changes in pore area at each layer, allowing for an analysis of the evolving patterns of layered pore areas across different regions of the granular system during loading. This characterization elucidated the dynamic evolution process of compaction within the granular system. A contact network model for the granular system was established using particle contact area as a representation of inter-particle contact forces, revealing inherent connections between particle contact networks and macroscopic mechanical behaviors within the granular system.

A guided twin delayed deep deterministic reinforcement learning for vaccine allocation in human contact networks

This manuscript introduces an innovative approach to optimizing the distribution of a limited vaccine resource within a population modeled as a contact network, aiming to mitigate the spread of infectious diseases. The study develops a novel methodology that combines reinforcement learning and graph neural networks. To understand the dynamics of disease propagation, the study constructs an analytical model that outlines conditions for disease eradication or endemic states. This model supports a series of simulation experiments across various scenarios, demonstrating the proposed method’s superiority over random and centrality-based approaches in reducing the average number of infections per individual during an outbreak. The adaptability of the proposed method is further emphasized by its robust performance across networks of diverse sizes and configurations, highlighting its real-world applicability. The findings of this study have significant implications for public health policy and resource allocation, offering a promising framework for managing infectious disease outbreaks in complex and dynamic environments.

IMPACTS OF INNOVATION EVENTS ON THE DEVELOPMENT OF ENTREPRENEURSHIP SKILLS: A CASE STUDY OF CAMPUS PARTY BRASIL

This study investigates the impact of student participation in innovation events on the development of entrepreneurial skills, using Campus Party Brasil 2023 as a case study. The research adopts a qualitative and quantitative approach, combining primary data obtained through questionnaires applied to 25 students, with secondary data extracted from a literature review. Data analysis was conducted using Bardin's (2004) content analysis method, with pre-analysis and coding stages. Triangulation between primary and secondary data ensured the validity of the findings. The results indicate that innovation events provide a favorable environment for the development of skills such as problem-solving, creativity, leadership, and teamwork. The study advances the literature by offering empirical evidence that reinforces the importance of integrating practical experiences, such as hackathons and entrepreneurship marathons, into the formal entrepreneurial education curriculum. In addition, it highlights the role of these events in forming contact networks and expanding internship and employment opportunities for students, which is not widely addressed in previous studies. By examining the interaction between theory and practice in the development of entrepreneurial skills, this work contributes to a deeper understanding of how innovation events can complement academic training, providing an interdisciplinary education and preparing students for market challenges. The study suggests that the systematic inclusion of events, such as Campus Party, in educational programs can be an effective strategy to strengthen experiential learning and foster an entrepreneurial mindset.

Modeling and analysis of COVID-19 spreading based on complex network theory

Complex networks can effectively describe interactions within real-world complex systems. In researches of epidemic spreading, scientists constructed various physical contact networks between individuals on the microscopic scale and the metapopulation networks on the macroscopic scale. These different types of network structures significantly impact the propagation dynamics of epidemic in human society. For instance, population flows in global airline networks influence the speed and arrival time of epidemics across large-scale space. In this paper we review the epidemic spreading models on various network structures, including fully mixed networks, three types of lower-order networks, three types of higher-order networks, metapopulation networks, and multiple strains competitive epidemic spreading models. We also provide an overview of the application of complex network theory in the COVID-19 pandemic, covering topics of prediction, prevention, and control of the epidemic. Finally, we discuss the strengths and limitations of these models and propose perspectives for future research.

Systems of autonomous running of urban electric transport

The autonomous running system (ARS) is crucial for urban electric transport, ensuring the movement of electric rolling stock even when access to the contact network is lost owing to emergencies or repair work. Thanks to the ARS, the vehicles can maintain their set speeds, providing passengers with comfortable and safe movements. The autonomous running allows vehicles to remain mobile and accessible to passengers, even without power supply from the contact network. ARS increases the reliability and efficiency of urban electric transport, ensuring a more stable operation of the transportation system in the city. This article aims to review the transport systems of urban electric transport and assess their development potential by integrating an ARS into the rolling stock.