Graph Theory Methods Research Articles

Disrupted Brain Functional Status in Patients with Reversible Cerebral Vasoconstriction Syndrome.

The aim of this study was to investigate the functional networks in subjects with reversible cerebral vasoconstriction syndrome (RCVS) using resting-state functional magnetic resonance imaging (rs-fMRI). We prospectively recruited patients with RCVS and healthy controls (HCs) between February 2017 and April 2021. The rs-fMRI data were analyzed using graph theory methods. We compared node-based global and regional topological metrics (Bundle 1) and network-based intranetwork and internetwork connectivity (Bundle 2) between RCVS patients and HCs. We also explored the associations of clinical and vascular (ie, the Lindegaard index, LI) parameters with significant rs-fMRI metrics. A total of 104 RCVS patients and 93 HCs were included in the final analysis. We identified significantly decreased local efficiency of the left dorsal anterior insula (dAI; p = 0.0005) in RCVS patients within 30 days after disease onset as compared to HCs, which improved 1 month later. RCVS patients also had increased global efficiency (p = 0.009) and decreased average degree centrality (p = 0.045), clustering coefficient (p = 0.033), and assortativity values (p = 0.003) in node-based analysis. In addition, patients with RCVS had increased internetwork connectivity of the default mode network (DMN) with the salience (p = 0.027) and dorsal attention (p = 0.016) networks. Significant correlations between LI and regional local efficiency in left dAI (rs = -0.418, p = 0.042) was demonstrated. The significantly lower local efficiency of the left dAI, suggestive of impaired central autonomic modulation, was negatively correlated with vasoconstriction severity, which is highly plausible for the pathogenesis of RCVS. ANN NEUROL 2023;94:772-784.

Bipartite synchronization of stochastic Markov jump coupled systems via completely aperiodically intermittent discrete-time state observation control

This paper investigates the bipartite synchronization of stochastic Markov jump coupled systems (SMJCSs) on signed graphs via completely aperiodically intermittent discrete-time state observation control (CAIDC). It is the first time that CAIDC, as a new hybrid control, is designed. And it removes the constraints of quasi-periodicity compared with intermittent discrete-time state observation control. A structurally balanced signed network model is constructed where agents can be separated into two subgroups to describe signed networks mathematically and present the competing relationship. Based on the assumption of structural balance, the main results are obtained for bipartite synchronization of SMJCSs utilizing graph theory and Lyapunov method. As an application, coupled Chua’s circuits with Markov jump are elaborated and several numerical simulations are presented to verify the feasibility and effectiveness of the proposed results.

Fixed-time synchronization of large-scale systems via aperiodically intermittent control

This paper studies the fixed-time synchronization of large-scale systems. An aperiodically intermittent control (AIC) based on the average control rate is introduced to achieve fixed-time synchronization for the first time. Compared with previous work, the AIC based on the average control rate reduces the limitation of control width and rest width, thus, the conservativeness is reduced. Moreover, the designed control uses the hyperbolic sine function instead of the sign function, which can avoid the chattering phenomena. A concession is made between rest and control intervals by constructing the auxiliary timers, such that the derivative of Lyapunov function (ignoring the exogenous disturbance) built is always non-positive. Then by combining the graph theory and Lyapunov method, some sufficient conditions are given. Finally, a numerical example is presented to verify the effectiveness of the results developed.

Investigation of the Effectiveness of Usage of Graph Databases for Big Data Analysis

The purpose of research. The purpose of this work is to study graph models of databases and develop a methodology for comparative analysis of database models. The theoretical and methodological basis of the study was the fundamental scientific works of domestic and foreign authors in the field of basic problems of database theory, algorithm theory, graph theory, data processing structures and methods.Methods. The paper uses methods of structural, comparative and content analysis, as well as statistical methods of information processing and methods of graph theory. As a result of the conducted research, the authors justified the features, advantages and disadvantages of using a graph data model.Results. The relevance of this study is due to the intensive development of information technologies intended for the economic development of the country, the pandemic and the geopolitical situation in the world. These prerequisites orient researchers to use new methods of data processing and analysis. However, it is possible to optimize big data processing processes not only with the help of powerful new algorithms, but also with the use of fundamentally different data structures and models other than relational.The paper presents applied examples of using the graph model of databases in various subject areas. A method of comparative analysis of data models in relation to big data analysis has been developed. The main points of data model design are highlighted: system scaling, compliance with requirements and standards, the ability to change data model structures, language complexity, performance and data processing speed. The proposed technique made it possible to numerically evaluate the effectiveness of graph models. Conclusion. The theoretical significance of the research consists in the development of methodological and technological approaches to the analysis of big data and the formation of structures and databases. The practical results of the study can be useful to large IT companies, as well as to the financial, logistics and commercial sectors, where the problem of big data analysis and research is most acute.

Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns

The number of published scientific paper grows rapidly each year, totaling more than 2.9 million annually. New methodologies and systems have been developed to analyze scientific production and performance indicators from large quantities of data available from the scientific databases, such as Web of Science or Scopus. In this paper, we analyzed the international scientific production and co-authorship patterns for the most productive authors from Serbia based on the obtained Web of Science dataset in the period 2006–2013. We performed bibliometric and scientometric analyses together with statistical and collaboration network analysis, to reveal the causes of extraordinary publishing performance of some authors. For such authors, we found significant inequality in distribution of papers over journals and countries of co-authors, using Gini coefficient and Lorenz curves. Most of the papers belong to multidisciplinary, interdisciplinary, and the field of applied sciences. We have discovered three specific collaboration patterns that lead to high productivity in international collaboration. First pattern corresponds to mega-authorship papers with hundreds of co-authors gathered in specific research groups. The other two collaboration patterns were found in mathematics and multidisciplinary science, mainly application of graph theory and computational methods in physical chemistry. The former pattern results in a star-shaped collaboration network with mostly individual collaborators. The latter pattern includes multiple actors with high betweenness centrality measure and identified brokerage roles. The results are compared with the later period 2014–2023, where high scientific production has been observed in some other fields, such as biology and food science and technology.

Interconnected Systems Modelling in Food Industry: General Solution Scheme and Stability Conditions for Linear Time-Invariant Systems

The problem of simulating complex systems, such as production lines, industrial plants, food processing, etc., today represents an opportunity that brings with it the great advantage of limiting design costs. However, nowadays the designer, after defining and implementing the mathematical models of the studied process, may need to rebuild the whole simulation framework because he needs to modify the model of even just one subsystem. It is for this reason that in this paper, a new framework for the use of Individual Subsystem Models (ISM) for the modelling and simulation of interconnected systems has been studied and implemented. Furthermore, the study of the state of the art has revealed the lack of efficient and sufficiently general numerical algorithms, but, at the same time, it is simple to use to solve the algebraic-differential equations deriving from the ISM simulation. The proposed new approach follows the paradigm of co-simulation methods, including graph theory methods, to solve the general ISM simply and efficiently. In this approach, each subsystem is required to have its own representation independently of the other subsystems. In this way, it is always possible to replace any subsystem whenever an updated representation becomes available, making maintenance and evolution of the entire ISM flexible. Our framework calls each subsystem separately in an optimal (suboptimal) order based on the structure of the graph. Each calculated output is transferred to the input of the next subsystem in the chosen. The general procedure has been validated in the context of Linear and Time-Invariant ISMs: in these hypotheses, the stability conditions have been calculated and numerical tests have been performed which show the effectiveness of the proposed approach.

Modulation of Brain Network Topological Properties in Knee Osteoarthritis by Electroacupuncture in Rats.

Osteoarthritis is a chronic, ongoing disease that affects patients, and pain is considered a key factor affecting patients, but the brain changes during the development of osteoarthritis pain are currently unclear. In this study, we used electroacupuncture (EA) to intervene the rat model of knee osteoarthritis and analyzed the changes in topological properties of brain networks using graph theory. Sixteen SD rat models of right-knee osteoarthritis with anterior cruciate ligament transection (ACLT) were randomly divided into electroacupuncture intervention group and control group. The electroacupuncture group was intervened on Zusanli (ST36) and Futu (ST32) for 20 min each time, five times a week for 3 weeks, while the control group was applied sham stimulation. Both groups were measured for pain threshold. The small-world properties and node properties of the brain network between the two groups after the intervention were statistically analyzed by graph theory methods. The differences are mainly in the changes in node attributes between the two groups, such as degree centrality, betweenness centrality, and so on in different brain regions (P<0.05). Both groups showed no small-world characteristics in the brain networks of the two groups. The mechanical thresholds and thermal pain thresholds were significantly higher in the EA group than in the control group (P<0.05). The study demonstrated that electroacupuncture intervention enhanced the activity of nodes related to pain circuit and relieved pain in osteoarthritis, which provides a complementary basis for explaining the effect of electroacupuncture intervention on pain through graphical analysis of changes in brain network topological properties and helps to develop an imaging model for pain affected by electroacupuncture.

The Presence or Absence of Hippocampal Atrophy Differently Disrupts Graph Theory Properties of Cerebral Functional Connectivity in Temporal Lobe Epilepsy. (S30.004)

<h3>Objective:</h3> To investigate brain connectivity and network properties with graph theory methods in TLE patients according to the presence or absence of HA. <h3>Background:</h3> Although temporal lobe epilepsy (TLE) with unilateral hippocampal atrophy (HA) has been extensively investigated, the impact of bilateral HA and the absence of HA on brain connectivity and networks’ efficiency remains unknown. <h3>Design/Methods:</h3> We analyzed 216 3T-MRI resting-state images of TLE patients (median age: 48 years; 122 women): 92 LEFT-HA, 70 RIGHT-HA, 25 BILATERAL-HA, 29 NEGATIVE-TLE, and 216 healthy controls. We used the CONN connectivity_toolbox/MATLAB2019 to extract graph theory measures (global efficiency (Global-eff), average path length (PATH), degree/cost (DEGREE), betweenness centrality (BC), local efficiency (Local-eff), and clustering coefficient (CC). We considered a cost of 0.15 (including only the 15% more statistically significant results) and reported p-values&lt;0.05. <h3>Results:</h3> The LEFT-HA and RIGHT-HA presented a trend to higher measures of global connectivity (Global-Con), local connectivity (Local-Con), and centrality in the brain (higher Global-eff, DEGREE, BC, Local-eff, CC, and lower PATH) and a trend to lower Global-Con, Local-Con, and centrality in the cerebellum. The LEFT-HA and RIGHT-HA presented higher DEGREE in the ipsilateral hippocampus and higher Local-eff /CC in the contralateral hippocampus. The NEGATIVE-TLE group showed a trend to lower Global-eff and higher average PATH, DEGREE and CC in the brain. The BILATERAL-HA presented a trend to higher Local-eff /CC in the brain. <h3>Conclusions:</h3> Overall, there was a trend for higher local connectivity to the detriment of the Global-eff. Our data indicate more severe alterations in the unilateral groups, as the presence of unilateral HA disturbs hemispheric connectivity, which may disrupt global connections. While the unilateral groups showed higher connectivity levels in the brain (with higher ipsilateral hippocampal Global-Con and probable compensatory higher contralateral hippocampal Local-Con), the NEGATIVE-TLE presented concordantly higher Local-Con and lower Global-Con in the brain. <b>Disclosure:</b> Lucas Silva has nothing to disclose. Dr. Karmann Aventurato has received research support from Coordenadoria de Aperfeiçoamento de Pessoal de Ensino Superior (CAPES). Raphael Casseb has nothing to disclose. The institution of Brunno de Campos has received research support from São Paulo Research Fundation. Dr. Cendes has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for UCB Pharma. Dr. Cendes has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for UCB Biopharma. Dr. Cendes has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for United Medical – Brazil. Dr. Cendes has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Zodiac Pharma . Dr. Cendes has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Eurofarma – Brazil . Dr. Cendes has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Epilepsia. Dr. Cendes has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Frontiers in Neurology - Epilepsy. The institution of Dr. Cendes has received research support from São Paulo Research Foundation - FAPESP. The institution of Dr. Cendes has received research support from Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brazil . The institution of Dr. Cendes has received research support from NIH. Clarissa Yasuda has nothing to disclose.

Algorithms for Сonstructing Matrixes of Routes of Pipeline Networks by Using the Method of Graph Theory

Использование средств информационных технологий и уровня автоматизации процессов управления значительно повышают роль технического прогресса и решают поставленные задачи Республикой Узбекистан по обеспечению целевым продуктом населению. Вместе с тем возможности современных компьютерных систем и развитие математических методов моделирования используются далеко не полностью из-за неформализации многих задач, а также несовершенства или отсутствия ряда алгоритмов, обеспечивающих возможность произвести анализ функционирования объекта, обработать поступающую информацию и принять соответствующие решения по оптимальному управлению многосвязных систем. В связи с этим разработка и исследование компьютерных моделей, вычислительных алгоритмов и на их основе создание объектно-ориентированных программных средств в этом направлении представляется актуальной проблемой дальнейшего развития автоматизации научных исследований для различных предметных областей, в частности трубопроводных систем. Всякая реальная энергетическая сеть, в том числе и газовая, по своей топологической структуре эквивалентна некоторому графу. Провести расчет и анализ несогласованности исходной информации сетей с более одним кольцом затруднительно. В этих случаях необходимо обратиться к законам Кирхгофа и соответствующим замыкающим соотношениям. Тем не менее, топология сети отличается разнообразием, чему свидетельствуют, в частности, схемы городских сетей теплоснабжения. В таких условиях основная тяжесть гидравлического или экономического расчета должна концентрироваться на стадии формирования топологии сети, для чего используются теории графов. В данной статье рассматриваются алгоритмы построения и оптимизации функционирования газопроводных многоконтурных сетей методом теории графов и программное обеспечение для оптимального управления, анализа и синтеза трубопроводных систем. Таким образом, разработанные вычислительные алгоритмы и компьютерная программа расчета можно применять для оптимизации функционирования газопроводных сетей, когда сеть имеет сложную лучистую и многокольцевую структуру. The use of information technology tools and the level of automation of management processes significantly increase the role of technical progress and solve the tasks set by the Republic of Uzbekistan to provide the population with the target product. At the same time, the capabilities of modern computer systems and the development of mathematical modeling methods are far from being fully used due to the informalization of many tasks, as well as the imperfection or absence of a number of algorithms that make it possible to analyze the functioning of an object, process incoming information and make appropriate decisions on the optimal control of multiply connected systems. . In this regard, the development and research of computer models, computational algorithms and, on their basis, the creation of object-oriented software in this direction seems to be an urgent problem for the further development of automation of scientific research for various subject areas, in particular pipeline systems. Any real energy network, including a gas network, is equivalent in its topological structure to a certain graph. It is difficult to calculate and analyze the inconsistency of the initial information of networks with more than one ring. In these cases, it is necessary to turn to Kirchhoff’s laws and the corresponding closing relations. However, the network topology is diverse, as evidenced, in particular, by the schemes of urban heating networks. In such conditions, the main burden of hydraulic or economic calculation should be concentrated on the stage of network topology formation, for which graph theories are used. This article discusses algorithms for constructing and optimizing the functioning of gas pipeline multiloop networks using the graph theory method and software for optimal control, analysis and synthesis of pipeline systems. Thus, the developed computational algorithms and a computer calculation program can be used to optimize the operation of gas pipeline networks when the network has a complex radiant and multi-ring structure.

Research on schedling optimization of four-way shuttle-based storage and retrieval systems

In this paper, we take the four-way shuttle system as the research object and establish the mathematical model of scheduling optimization based on the minimum time for the in/out operation optimization and path optimization scheduling problems of the four-way shuttle system. An improved genetic algorithm is used to solve the task planning, and an improved A* algorithm is used to solve the path optimization within the shelf level. The conflicts generated by the parallel operation of the four-way shuttle system are classified, and the improved A* algorithm based on the time window method is constructed for path optimization through the dynamic graph theory method to seek safe conflict-free paths. Through simulation example analysis, it is verified that the improved A* algorithm proposed in this paper has obvious optimization effect on the model of this paper.

Diffusion Alignment Coefficient (DAC): A Novel Similarity Metric for Protein-Protein Interaction Network.

Interaction networks can be used to predict the functions of unknown proteins using known interactions and proteins with known functions. Many graph theory or diffusion-based methods have been proposed, using the assumption that the topological properties of a protein in a network are related to its biological function. Here we seek to improve function prediction by finding more similar neighbors with a new diffusion-based alignment technique to overcome the topological information loss of the node. In this study, we introduce the Diffusion Alignment Coefficient (DAC) algorithm, which combines diffusion, longest common subsequence, and longest common substring techniques to measure the similarity of two nodes in protein interaction networks. As a proof of concept, our experiments, conducted on a real PPI networks S.cerevisiae and Homo Sapiens, demonstrated that our method obtained better results than competitors for MIPS and MSigDB Collections hallmark gene set functional categories. This is the first study to develop a measure of node function similarity using alignment to consider the positions of nodes in protein-protein interaction networks. According to the experimental results, the use of spatial information belonging to the nodes in the network has a positive effect on the detection of more functionally similar neighboring nodes.

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain.

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

Distributed cooperative dual closed loop velocity-attitude consensus controller for rendezvous of the underactuated AUV swarm in 3-dimensional space

This paper addresses a distributed cooperative dual closed loop controller for the rendezvous process of the crowded underactuated AUV swarm recovery system in 3-dimensional space. Inspired by biological behaviors, the rendezvous process of the AUV swarm transforms into a flocking problem. Different from the traditional flocking problem, it is difficult to obtain the accurate position information of AUV in underwater environment. In the outer loop, the proposed velocity-attitude consensus protocol only uses the velocity and attitude information of neighbors in the communication range of AUV to handle the flocking issue of the AUV swarm. Moreover, the protocol guarantees the AUV swarm separation, cohesion, velocity matching and attitude synchronization, if no collision and the dynamically switch topology connectedness are preserved at the initial position. In the inner loop, the proposed fractional integral terminal sliding mode controller provides practical available control input for the actuator. In addition, the exponential consensus of velocity and attitude and the locally asymptotic stability of the system are rigorously proved by max-min, graph theory and Lyapunov method. Finally, straightforward simulation results confirm the feasibility of the distributed cooperative controller.

Network Reconfiguration for Searching Maximum Loading Capacity Radial Network: An Efficient Graph Theory-Based Machine Learning Approach

This study presents a unique method for network reconfiguration for Searching Maximum Loading Capacity Radial Network from an interconnected meshed network using continuation power flow. The network reconfiguration outcomes are also evaluated for various graph theory approaches presented in the literature. The combined graph theory and machine learning methods are used to determine the best sectional switch position. The system’s radiality is verified using graph theory. The recommended technique is tested on a 30-node mesh network with 41 sectional switches. The results demonstrate that the distribution system can manage a higher connected load using the suggested Bayesian-Ridge approach while lowering total active and reactive power losses.

Model of Threats to the Integrity and Availability of Information Processed in Cyberspace

Depending on their motivation, offenders have different goals, and disclosure of information is not always such a goal. It often happens that the purpose of the offender is to disrupt the normal operation of the system. This can be achieved both by acting directly on the information and by acting on the elements of the system. Actions of this kind lead to a violation of integrity and availability, but not confidentiality. It follows that the process of forming a threat model for the integrity and availability of information differs from a similar process for confidentiality threats. The purpose of this study is to develop an information integrity threat model that focuses on threats disrupting the normal operation of the system. The research methodology is based on the methods of system analysis, graph theory, discrete mathematics, and automata theory. As a result of the research, we proposed a model of threats to the integrity and availability of information. The proposed threat model differs from analogues by a high level of abstraction without reference to the subject area and identification of threats to the availability of information as a subset of threats to the integrity of the information transmission channel.

Lineages as Network: A Study of Chan Genealogy in the Zutang ji 祖堂集 Using Social Network Analysis

This paper attempts to examine the genealogical framework of “lamp records” (denglu 燈錄) of the Chan Buddhist tradition using analytical tools and methods of Historical Social Network Analysis (HSNA) and graph theory. As an exploratory study, the primary objectives are to investigate the possibilities offered by HSNA and visualization tools for research on Chan genealogy in lamp records, explore the benefits of this approach over traditional lineage charts, and reflect on its limitations. The essay focuses on the Chan community portrayed in the Goryeo 高麗 edition of the Zutang ji 祖堂集 (Collection of the Patriarchal Hall; K.1503). It shows that the lineage reportedly stemming from Qingyuan Xingsi 青原行思 (d. ca. 740) and Shitou Xiqian 石頭希遷 (701–791), as well as the branch descending from Tianhuang Daowu 天皇道悟 (748–807) to Xuefeng Yicun 雪峰義存 (822–908) and his successors, play a crucial role within the structure of the Zutang ji’s genealogical network. The study further highlights possible irregularities in lineage claims by contrasting metrics of degree and betweenness centrality with features of the text (e.g., number of hagiographic entries, length of the entries).

Topology Identification of Low-Voltage Power Lines Based on IEC 61850 and the Clustering Method

The large-scale access of distributed power puts forward higher requirements for the monitoring of the distribution networks, and the topology identification of low-voltage power lines can effectively promote the integration of monitoring data and the distribution network information, effectively realizing the rapid identification of faults and ensuring the safety of users. In this paper, the method of graph theory was used to simplify the analysis of low-voltage lines, and the full topology identification strategy was proposed. Based on IEC 61850 SCL topology configuration information, line topology identification within the region was realized, and the correlation between regions was determined by the injection method. According to the configuration information, regional association information, and user’s collection information, the low-voltage station area line topology was divided into known regional topology and unknown regional topology. Aiming for the identification of line topology in the unknown region, according to the similarity of voltage fluctuations over short electrical distances, clustering analysis of user’s voltage data in the unknown region was carried out based on the k-means clustering algorithm. The test results showed that this scheme can realize the identification of topology in the region.

ЕВОЛЮЦІЯ ФУНКЦІОНАЛЬНО-ТЕРИТОРІАЛЬНОЇ СТРУКТУРИ РЕЙКОВОГО ГРОМАДСЬКОГО ТРАНСПОРТУ КИЄВА

Urban transport systems require increased attention as connecting elements that affect the efficiency of the functioning of cities as a whole and individual districts. Public passenger transport of a large city, which is the capital of the state – Kyiv, is one of the branches of its life support, on the functioning of which both the development of the economic complex and the lifestyle of the population depend. The problem of the rational functioning of public transport and its territorial organization become one of the main ones for our capital during the martial law and will become critical after the Victory. The development of rail transport is a priority for any European city: it has the highest carrying capacity, it is environmentally friendly and comfortable for passengers, and most importantly, it does not depend on the amount of traffic jams. In Kyiv, there are four types of rail public transport - metro, tram (including high-speed tram), city electric train and funicular. The analysis of the evolution of the territorial structure of the urban rail public transport system, carried out using the methods of graph theory and historical-geographic sections, shows that this structure developed dynamically along with the development of Kyiv. It is substantiated that the priority directions of the development of Kyiv's transport system are aimed at the formation of a highly efficient transport complex capable of meeting the needs of the population in relevant services and minimizing the negative impact on the environment. To achieve this goal, the main directions of the development of Kyiv's rail public transport system have been determined: the priority of public passenger transport in the performance of city transportation; development of high-speed off-street types of public rail transport (metropolitan, high-speed tram, city railway); provision of fast, comfortable and safe transport connections between all functional zones of the capital on the basis of increasing the density of the street network, creating a system of complex transfer nodes at the stations of the metro and city railway lines.

基于MSPA分析的福建省生态网络构建

PDF HTML阅读 XML下载 导出引用 引用提醒 基于MSPA分析的福建省生态网络构建 DOI: 10.5846/stxb202107101863 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（31971639）；福建省自然科学基金项目（2019J01406） Construction of ecological network in Fujian Province based on Morphological Spatial Pattern Analysis Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:快速城镇化进程导致森林景观破碎化、连通性下降，严重威胁区域可持续发展、生物多样性保护和生态服务能力的维持。生态网络构建是提高景观连接度，维持物种扩散过程，保护生物多样性的有效手段。以福建省为例，借助形态学空间格局分析（MSPA）探讨2000、2010和2020年的森林景观结构动态变化，并在利用组分数（NC）与整体连通性指数（IIC）确定适宜距离阈值的基础上，根据可能连通性指数（PC）筛选生态源地；从人-地关系角度选择路网分布、建设用地分布、土地覆盖类型、坡度四种评价因子构建阻力面，采用最小阻力模型（MCR）提取生态廊道形成初步生态网络，进一步计算PC指数对生态廊道进行重要性分级；最后基于图论法，利用闭合度α、线点率β、网络连接度γ对所构建的生态网络进行定量评价。结果表明：（1）近20年来福建省森林景观结构较为稳定，其中核心区占比高达76.27%，但仍存在一定程度的破碎化趋势；（2）根据NC与IIC的计算结果，以500m为合适的距离阈值计算了PC，据此识别出15处生态源地，多位于闽西及闽北地区；（3）采用MCR模型提取了105条生态廊道，其中重要生态廊道27条，分布均匀且连通四方；（4）生态廊道穿过的土地利用类型中受人类干扰小的林草地占比超过85%，耕地占比12.33%，受人类干扰强烈的建设用地及未利用土地占比不足1%；（5）识别出生态节点62个，生态网络结构指数α=0.37，β=1.69，γ=0.58，表明网络结构较为合理，连通性较好。研究结果可从整体角度出发指导福建省生态安全格局构建，以期为土地资源有限背景下，省域尺度复合种群保护工作提供科学依据。 Abstract:The rapid urbanization process has led to the fragmentation and the declining in the connectivity of forest landscapes, which seriously threatened the sustainable development of regions, including the maintenance of biodiversity and ecological service. The construction of ecological network is an effective means to improve the connectivity of landscape, maintain the spread of species, and thus protect biodiversity. Taking Fujian Province as a case, the Morphological Spatial Pattern Analysis (MSPA) was employed to explore the dynamic changes of forest landscape structure in 2000, 2010 and 2020. Then, the appropriate distance threshold of patch connectivity was determined according to the number of components (NC) and the integral index of connectivity (IIC). On this basis, the probability connectivity index (PC) was calculated to identify the ecological sources. Then, from the perspective of human-land relationship, the factors including the distance from road network, distance from construction land, land cover type, and slope, were selected to construct the comprehensive resistance surface, which reflects the degree of obstruction for the species travelling between the ecological sources (i.e., core forest patches). To this end, the minimum cumulative resistance (MCR) model was adopted to extract the preliminary ecological corridors, which was ranked and filtered subsequently by the PC values. Finally, based on the graph theory method, the quantitative evaluation of the ecological network α, β, and γ index were carried out. The results show that:(1) the forest landscape structure in Fujian Province has been relatively stable in the past 20 years, of which the core area accounted for 76.27% of the total landscape area, but it still tended to fragmentation to a certain degree; (2) According to the results of NC and IIC, the PC value was calculated with a distance threshold of 500 meters, and 15 ecological sources were identified, which were mostly in the western and northern regions of Fujian; (3) 105 ecological corridors were extracted by MCR model, of which 27 were important corridors, which were evenly distributed and extended in all directions across the study area; (4) The ecological corridors and land use were superimposed to obtain the proportion of the corridors passing through each landscape type, of which the forests and grasslands less disturbed by humans accounted for more than 85%, the cultivated land accounted for 12%, while the construction land and unused land strongly disturbed by humans accounted for less than 1%; (5) Totally, 62 ecological nodes were identified, and the ecological network structure index α, β and γ were 0.37, 1.69 and 0.58, respectively, indicating that the reasonability of the network structure and the goodness in the network connectivity. The results can shed a light on the construction of the ecological security pattern in Fujian Province from a holistic perspective, and provide a scientific basis for biodiversity conservation at the provincial scale with the limited land resources. 参考文献 相似文献 引证文献

Altered whole-brain resting-state functional connectivity and brain network topology in typhoon-related post-traumatic stress disorder.

Altered resting-state functional connectivity has been found in patients with post-traumatic stress disorder (PTSD). However, the alteration of resting-state functional connectivity at whole-brain level in typhoon-traumatized individuals with PTSD remains largely unknown. To investigate changes in whole-brain resting-state functional connectivity and brain network topology in typhoon-traumatized subjects with and without PTSD. Cross-sectional study. Twenty-seven patients with typhoon-related PTSD, 33 trauma-exposed controls (TEC), and 30 healthy controls (HC) underwent resting-state functional MRI scanning. The whole brain resting-state functional connectivity network was constructed based on the automated anatomical labeling atlas. The graph theory method was used to analyze the topological properties of the large-scale resting-state functional connectivity network. Whole-brain resting-state functional connectivity and the topological network property were compared by analyzing the variance. There was no significant difference in the area under the curve of γ, λ, σ, global efficiency, and local efficiency among the three groups. The PTSD group showed increased dorsal cingulate cortex (dACC) resting-state functional connectivity with the postcentral gyrus (PoCG) and paracentral lobe and increased nodal betweenness centrality in the precuneus relative to both control groups. Compared with the PTSD and HC groups, the TEC group showed increased resting-state functional connectivity between the hippocampus and PoCG and increased connectivity strength in the putamen. In addition, compared with the HC group, both the PTSD and TEC groups showed increased connectivity strength and nodal efficiency in the insula. Aberrant resting-state functional connectivity and topology were found in all trauma-exposed individuals. These findings broaden our knowledge of the neuropathological mechanisms of PTSD.