Changes In Network Patterns Research Articles

Analysis on Ecological Network Pattern Changes in the Pearl River Delta Forest Urban Agglomeration from 2000 to 2020

The advancement of urbanization has led to a decline in the ecological function and environmental quality of cities, seriously reducing the services and sustainable development capacity of urban ecosystems. The construction of the National Forest Urban Agglomeration of China is conducive to alleviating the ecological and environmental problems brought about by rapid urbanization and promoting sustainable urban development. A time series analysis of ecological network changes can quickly and effectively explore the development and changes of ecological spatial patterns over time. Identifying ecological protection and restoration areas in urban agglomerations is an important way to promote ecosystem restoration and optimize ecological networks. This paper takes the Pearl River Delta forest urban agglomeration as the research area, uses multi-source remote sensing data from 2000 to 2020 (every 5 years), identifies ecological sources based on the morphological spatial pattern analysis (MSPA) method, generates ecological corridors based on the minimum cumulative resistance (MCR) model, constructs a time series ecological network pattern in the Pearl River Delta region, and analyzes the evolution process of the ecological network pattern over time. The results indicate that over time, the core green area in the ecological network pattern of the Pearl River Delta first decreased and then increased, and the complexity of ecological corridors first decreased and then increased. The main reason is that the urbanization process in the early 21st century led to severe ecological fragmentation. Under the promotion of the national forest urban agglomeration construction, the ecological network pattern of the Pearl River Delta was restored in 2015 and 2020. The time series analysis of the ecological network pattern in the Pearl River Delta region of this research confirms the effectiveness of the construction of forest urban agglomerations, providing a scientific reference for the identification of ecological networks and optimization of spatial patterns in forest urban agglomerations.

Analyzing ML-Based IDS over Real-Traffic

The rapid growth of computer networks has caused a significant increase in malicious traffic, promoting the use of Intrusion Detection Systems (IDSs) to protect against this ever-growing attack traffic. A great number of IDS have been developed with some sort of weaknesses and strengths. Most of the development and research of IDS is purely based on simulated and non-updated datasets due to the unavailability of real datasets, for instance, KDD '99, and CIC-IDS-18 which are widely used datasets by researchers are not sufficient to represent real-traffic scenarios. Moreover, these one-time generated static datasets cannot survive the rapid changes in network patterns. To overcome these problems, we have proposed a framework to generate a full feature, unbiased, real-traffic-based, updated custom dataset to deal with the limitations of existing datasets. In this paper, the complete methodology of network testbed, data acquisition and attack scenarios are discussed. The generated dataset contains more than 70 features and covers different types of attacks, namely DoS, DDoS, Portscan, Brute-Force and Web attacks. Later, the custom-generated dataset is compared to various available datasets based on seven different factors, such as updates, practical-to-generate, realness, attack diversity, flexibility, availability, and interoperability. Additionally, we have trained different ML-based classifiers on our custom-generated dataset and then tested/analyzed it based on performance metrics. The generated dataset is publicly available and accessible by all users. Moreover, the following research is anticipated to allow researchers to develop effective IDSs and real traffic-based updated datasets.

Handover between Vehicular Network Providers Using Bioinspired Attractor Selection Technique

This study looks at how to describe vehicular network connectivity using MATLAB simulation of an E. coli biological system. The model takes advantage of E. coli’s ability to adapt to environmental changes and variations by having stable states, which allows E. coli to continue surviving and developing, and uses this property to improve vehicular network connectivity to network service providers. As a result, an adaptive response to network pattern changes in terms of signal quality and stability can be obtained, as well as acceptable levels of connectivity in a changing environment via a handover mechanism. After applying it to four distinct networks, this probability-based technique was shown to work through simulation. The four networks used successfully completed the handover and maintained connectivity at various threshold levels. The impact of signal threshold variations and network sensitivity in reaction to surroundings on the handover process is also discussed in the study. By introducing two new physiologically based metrics (threshold and sensitivity), the goal of delivering Quality of Service (QoS) is realized. The used adaptive biological model allows for the selection probability λ to change according to the number of participating networks under certain environmental conditions. Noise effect is also discussed in the presented work as it affects network signals but does not affect the adaptive handover process, due to the built intelligence of the bio-inspired model.

Problem-solving by total productive maintenance swift teams: communication network structure, media choice and team effectiveness

PurposeThis study aims to look at the performance, communication structure and media choice for swift teams (STs) formed with the purpose of recovering from operational emergencies in manufacturing. The problem-solving process associated with these ad hoc teams include an early stage, where the main goal is to restore the process to working conditions, and a later stage, longer in duration, where the root cause of the problem is found and eliminated.Design/methodology/approachBased on field data from an industrial manufacturing operation, the authors test hypotheses by means of regression models.FindingsIt was found that in the evolution from early to later stage, media usage shifts from highly synchronous to asynchronous and the structural characteristics of the teams' collaboration networks mutate as well. These effects are different when comparing high- vs low-performing teams.Research limitations/implicationsThe study contains data for only one company, limiting the external validity of the conclusions. The sample was predominantly male. Participant attrition and other potential covariates not included in the study can be additional limitations.Practical implicationsMore successful teams adapt their communication patterns more rapidly, going from an initially decentralized organization to a more centralized one. These changes in network patterns open a new view of ST’s success, based on network characteristics rather than on aggregate measures. The conclusions yield insights for interventions that may increase the success rates of these teams and reduce production line downtime.Originality/valueThe two stages in the operational emergency problem-solving process have to the authors’ knowledge not been addressed simultaneously in previous research, which is attempted in this paper as its main theoretical contribution. Moreover, previous studies dealing with ST’s success have only looked at aggregated measures impacting effectiveness and never to how their communication networks evolve along the path to problem resolution. The network view of the evolution of the ST from a relatively disorganized impromptu agglomeration of individuals to an effective problem-solving organization is to the authors’ knowledge first presented.

Evolution of the network pattern of posttraumatic stress symptoms among children and adolescents exposed to a disaster

Growing network approach analyses of posttraumatic stress disorder (PTSD) have enhanced the knowledge of PTSD symptomatology. This study aims to explore changes in network patterns of PTSD symptoms among youth survivors following the Zhouqu debris flow through a network approach. A two-year longitudinal study was conducted to follow 1460 children and adolescents at 3, 15, and 27 months after the disaster. Symptoms with high centrality varied at different time points. Sleep problems and nightmares exhibited high centrality at 3 months, and their centrality decreased over time, while the centrality of physiological cue reactivity and flashbacks increased over time and reached a high level at 27 months. The global connectivity of the network was stronger at 27 months than at 3 and 15 months. These findings provide novel insights into youths’ PTSD symptom evolution. Temporal differences in PTSD symptoms merit more attention from researchers. Different core symptoms in acute and chronic PTSD structures should be treated as targets at different stages following trauma in clinical practice.

Understanding Allogrooming Through a Dynamic Social Network Approach: An Example in a Group of Dairy Cows.

For gregarious species such as domestic cattle, the social environment is a very important determinant of their welfare and fitness. Understanding the complexity of cows' relationships can assist the development of management practices that are more integrated with the cows' social behavioral processes. The two aims of this study were: (1) to determine the dynamics of affiliative relationships, as indicated by allogrooming, by means of stochastic actor-oriented modeling, in dairy cows during early lactation; (2) to explore the underlying processes and the individual attributes, such as age, social rank and reproductive state, that could shape network pattern changes in grooming contacts between individual. We observed the allogrooming behavior of a dynamic group of 38 dairy cows for 4 h per day for 30 days. Using stochastic actor-oriented models, we modeled the dynamics of weekly contacts and studied how structural processes (e.g., reciprocity, transitivity, or popularity) and individual attributes (i.e., age, social rank, and reproductive state) influence network changes. We found that cows tended to groom individuals that had previously groomed them, implying a possible cooperation. Cows that groomed more actively did not appear to have a preference for specific individuals in the herd, and in return, tended to be groomed by fewer cows over time. Older individuals groomed more cows than younger ones, indicating that allogrooming could be related to seniority. Cows groomed mainly individuals of similar age, suggesting that familiarity and growing up together enhanced social grooming. Over time, cows with higher social rank were groomed by fewer cows and individuals recently reintroduced to the group groomed more herdmates. The study of social network dynamics can be used to better understand the complexity and non-linearity of cow relationships. Our findings, along with further research, can complement and strengthen the design of improved management practices that are more in line with the natural social behavior of cows.

Effect of Joint Geometrical Parameters on Hydraulic Fracture Network Propagation in Naturally Jointed Shale Reservoirs

The presence of a significant amount of discontinuous joints results in the inhomogeneous nature of the shale reservoirs. The geometrical parameters of these joints exert effects on the propagation of a hydraulic fracture network in the hydraulic fracturing process. Therefore, mechanisms of fluid injection-induced fracture initiation and propagation in jointed reservoirs should be well understood to unleash the full potential of hydraulic fracturing. In this paper, a coupled hydromechanical model based on the discrete element method is developed to explore the effect of the geometrical parameters of the joints on the breakdown pressure, the number and proportion of hydraulic fractures, and the hydraulic fracture network pattern generated in shale reservoirs. The microparameters of the matrix and joint used in the shale reservoir model are calibrated through the physical experiment. The hydraulic parameters used in the model are validated through comparing the breakdown pressure derived from numerical modeling against that calculated from the theoretical equation. Sensitivity analysis is performed on the geometrical parameters of the joints. Results demonstrate that the HFN pattern resulting from hydraulic fracturing can be roughly divided into four types, i.e., crossing mode, tip-to-tip mode, step path mode, and opening mode. As β (joint orientation with respect to horizontal principal stress in plane) increases from 0° to 15° or 30°, the hydraulic fracture network pattern changes from tip-to-tip mode to crossing mode, followed by a gradual decrease in the breakdown pressure and the number of cracks. In this case, the hydraulic fracture network pattern is controlled by both γ (joint step angle) and β. When β is 45° or 60°, the crossing mode gains dominance, and the breakdown pressure and the number of cracks reach the lowest level. In this case, the HFN pattern is essentially dependent on β and d (joint spacing). As β reaches 75° or 90°, the step path mode is ubiquitous in all shale reservoirs, and the breakdown pressure and the number of the cracks both increase. In this case, β has a direct effect on the HFN pattern. In shale reservoirs with the same β, either decrease in k (joint persistency) and e (joint aperture) or increase in d leads to the increase in the breakdown pressure and the number of cracks. It is also found that changes in d and e result in the variation in the proportion of different types of hydraulic fractures. The opening mode of the hydraulic fracture network pattern is observed when e increases to 1.2 × 10−2 m.

Optical coherence tomography angiography at the acute phase of optic disc edema

BackgroundThe differential diagnosis of optic disc edema at the acute phase can be challenging. OCT angiography (OCTA) is a new technology allowing the visualization of the peripapillary vascular network and optic disc capillaries. The peripapillary network alterations of glaucoma and chronic non-arteritic anterior ischemic optic neuropathy (NAION) were reported. However, no OCTA studies on acute optic disc edema from various causes. The aim of this project was to use OCTA to demonstrate the vascular changes the optic nerve head of various types of optic disc edema at the acute phase.MethodsIn this retrospective study, patients with non-arteritic anterior ischemic optic neuropathy (NAION), papillitis or papilledema were recruited. Each patient was imaged using the AngioPlex™ CIRRUS™ HD-OCT device(model 5000, Carl Zeiss Meditec, Inc., Dublin, USA) with a scanning area of 6 × 6 mm2 centered on the optic disc. A morphological analysis of the peripapillary network was performed. For some patients with unilateral optic disc edema, a quantitative analysis was performed using a swept-source OCT-A system (PLEX® Elite 9000, Carl Zeiss Meditec, Inc., Dublin, USA). Vessel perfusion density and flux index of the peripapillary area were calculated.ResultsEight eyes with NAION (4 patients), 12 eyes with papillitis (6 patients) and 25 eyes with papilledema (13 patients) were imaged. The apparent disappearance or moderate pattern alteration of the peripapillary capillary vessels were observed in patients with NAION or papillitis, respectively. For papilledema, the capillaries at the surface of the optic disc were dilated and tortuous, but no peripapillary network pattern changes were observed. The quantitative analysis did not show any difference of peripapillary network between NAION and healthy eyes. For papillitis, the flux index was higher in inflammatory eyes compared to the healthy eyes in average (p = 0.03).ConclusionAt the acute phase, the morphological analysis of OCT-A appeared to be more useful than the quantification analysis, facilitating the differentiation between the three kinds of ONH edema: ischemic, inflammatory and papilledema.

Fibrin network pattern changes of platelet-rich fibrin in young versus old age group of individuals: A cell block cytology study.

Background:To evaluate variations in fibrin network patterns of the platelet-rich fibrin (PRF) in different age groups.Materials and Methods:Ninety-five patients were divided into three age groups: Group 1: (20–39 years); Group 2: (40–59 years); and Group 3: (60 years and above). PRF was prepared from blood samples of all patients and were subjected to cell block cytology method of histological analysis and slides were prepared to histologically assess the age-related changes in (i) fibrin network patterns in terms of density and (ii) entrapment of platelets and white blood cells (WBCs) within fibrin meshwork.Results:Two types of fibrin network pattern arrangements noticed: Dense and loose types in three age groups. However, there was a noticeable decrease in the dense type of fibrin network with progressing age and increase in the loose type of fibrin arrangement. Furthermore, variation in a number of platelets and WBCs entrapped within fibrin network in relation to age was noticed.Conclusion:From the current study it can be concluded that age can be considered as one of the influencing factors on quality of PRF in terms of fibrin network patterns and hence, platelet and WBCs entrapment within these fibrin networks.

Non-monotonic reorganization of brain networks with Alzheimer's disease progression.

Background: Identification of stage-specific changes in brain network of patients with Alzheimer's disease (AD) is critical for rationally designed therapeutics that delays the progression of the disease. However, pathological neural processes and their resulting changes in brain network topology with disease progression are not clearly known.Methods: The current study was designed to investigate the alterations in network topology of resting state fMRI among patients in three different clinical dementia rating (CDR) groups (i.e., CDR = 0.5, 1, 2) and amnestic mild cognitive impairment (aMCI) and age-matched healthy subject groups. We constructed density networks from these 5 groups and analyzed their network properties using graph theoretical measures.Results: The topological properties of AD brain networks differed in a non-monotonic, stage-specific manner. Interestingly, local and global efficiency and betweenness of the network were rather higher in the aMCI and AD (CDR 1) groups than those of prior stage groups. The number, location, and structure of rich-clubs changed dynamically as the disease progressed.Conclusions: The alterations in network topology of the brain are quite dynamic with AD progression, and these dynamic changes in network patterns should be considered meticulously for efficient therapeutic interventions of AD.

Aggregate-related changes in network patterns of nematodes and ammonia oxidizers in an acidic soil

Nitrification plays a central role in global nitrogen cycle, which is affected by biological interaction between soil microfauna and microorganisms. However, the complexity of soil biotic communities made it difficult to reveal organizational principles of the community and the interactions among species. Here, we used the network analysis to decipher the interactions between nematodes and ammonia oxidizers within aggregate fractions under 10-year manure application, and examine their associations with soil variables and potential nitrification activity (PNA). Three aggregate fractions included large macroaggregates (>2000 μm, LA), small macroaggregates (250–2000 μm, SA), and inter-aggregate soil and space (<250 μm, IA). Aggregate factions showed a remarkable effect on association networks of nematodes and ammonia oxidizers. The average connectivity (avgK) and the number of edges in overall networks increased with increasing aggregate sizes, while the average geodesic distance (GD) followed the opposite trend. The LA network could be viewed as a better organized or a better operational soil food web with more functional interrelated members than the SA and IA networks. The modules related to PNA were significantly correlated and clustered together as meta-modules in networks of aggregate fractions. The role-shifts prevailed among the network members such as significant module memberships (MMs) and generalist/specialist operational taxonomic units (OTUs). A half of shared nodes were further identified as shared MMs, dominated by ammonia-oxidizing bacteria (AOB) especially for Nitrosospira cluster 3a and 10. Soil pH could explain partly the shift of module hubs in different networks, while grazing by bacterivores might account for three exclusively connecters related to Nitrososphaera clusters 1.1. The strongly coupled modules correlated positively to pH and total carbon (TC), regardless of aggregate fractions. The network analysis approach provided new insights into potential importance of network interactions between nematodes and ammonia oxidizers in soil nitrogen cycling.

Integrating network ecology with applied conservation: a synthesis and guide to implementation.

Ecological networks are a useful tool to study the complexity of biotic interactions at a community level. Advances in the understanding of network patterns encourage the application of a network approach in other disciplines than theoretical ecology, such as biodiversity conservation. So far, however, practical applications have been meagre. Here we present a framework for network analysis to be harnessed to advance conservation management by using plant-pollinator networks and islands as model systems. Conservation practitioners require indicators to monitor and assess management effectiveness and validate overall conservation goals. By distinguishing between two network attributes, the 'diversity' and 'distribution' of interactions, on three hierarchical levels (species, guild/group and network) we identify seven quantitative metrics to describe changes in network patterns that have implications for conservation. Diversity metrics are partner diversity, vulnerability/generality, interaction diversity and interaction evenness, and distribution metrics are the specialization indices d' and [Formula: see text] and modularity. Distribution metrics account for sampling bias and may therefore be suitable indicators to detect human-induced changes to plant-pollinator communities, thus indirectly assessing the structural and functional robustness and integrity of ecosystems. We propose an implementation pathway that outlines the stages that are required to successfully embed a network approach in biodiversity conservation. Most importantly, only if conservation action and study design are aligned by practitioners and ecologists through joint experiments, are the findings of a conservation network approach equally beneficial for advancing adaptive management and ecological network theory. We list potential obstacles to the framework, highlight the shortfall in empirical, mostly experimental, network data and discuss possible solutions.

Local cattle movements in response to ongoing bovine tuberculosis zonation and regulations in Michigan, USA

Bovine tuberculosis (Mycobacterium bovis) is an ongoing management issue in the state of Michigan with eradication from livestock as the ultimate goal. Eradication has been a challenge owing to the presence of a wildlife reservoir; competing interests in managing the livestock and wildlife hosts; and many uncertainties in transmission dynamics of M. bovis. One of the cornerstones of the eradication effort has been to stop movement of infected cattle among farms by imposing strict pre-movement testing on cattle being moved within, into and out of the Modified Accredited Zone (MAZ) in northeastern Michigan. In addition to pre-movement tuberculosis testing, detailed information about the origin and destination premises of all movements within the MAZ has been recorded in Michigan. The aim of this study was to describe the farm-to-farm movements of cattle within the MAZ, report changes in the network of movements during a 6-year period when the MAZ was a constant size (2004–2009), and examine changes in cattle movement patterns when the MAZ was reduced from 11 to 5 counties in 2010. Non-slaughter cattle movement within the MAZ was characterized by predominantly local movements at a sub-county scale. Premises that shipped cattle were primarily senders or receivers, but rarely both. From 2004 to 2009, the number of cattle shipped, size of shipments, number of shipments and distance of shipments decreased; there was little change in the network patterns of interaction among individual premises; and interactions among all premises became more disconnected. After accounting for MAZ size, there were also no changes in cattle movement network patterns following the reduction of the MAZ in 2010. The movement of cattle was likely not a key risk factor in bTB spread among premises in the MAZ during the study period and the effect of zonation and movement regulations appeared to further reduce the risk of tuberculosis spread via cattle movements among farms in Michigan's MAZ.