Critical Nodes Research Articles

Greedy randomized adaptive search procedure for supply chain network resilience optimization considering risk diffusion

Supply disruption risks occurring at individual nodes in a supply chain network can propagate to other nodes through the links in the network affecting the overall performance of the supply chain. In this context, mitigation strategies are commonly implemented to respond to these disruptions and improve the resilience of the supply chain. This study proposes a mathematical model to optimize the resilience of the supply chain network by selecting critical nodes and identifying the appropriate type of mitigation strategies to be implemented under a limited budget. The resilience of the supply chain network is evaluated by the degree of propagation of risks from individual nodes to the entire supply chain network, using a risk diffusion model where a disruption risk decreases exponentially as it progresses downstream in the supply chain. A greedy randomized adaptive search procedure (GRASP)-based solution approach was developed to solve the proposed formulation and its performance was compared to other solution procedures for different scenarios showing it to be the most effective and robust. A summary of the insights developed from the solutions obtained for the different scenarios is presented along with directions for future research.

Complex network analysis for accident causes modelling to enhance process safety in chemical enterprises

AbstractHazardous chemicals often cause catastrophic accidents, and accidents often result from intricate interactions among various causes. Due to the varying risk factors in different areas of chemical enterprises, to achieve more precise prevention, a more detailed study of the accident risk factors in each area is necessary. Therefore, this study focuses on analyzing critical accident causes and their interrelationships in different functional areas of chemical enterprises to enhance process safety by using a complex network model. Based on 90 accident information, complex network models are constructed for hazardous chemical warehouse areas (HCWAs), tank farm areas (TFAs), and production areas (PAs). Subsequently, a topological analysis of the complex network models is conducted. Based on the PageRank algorithm, 13 critical nodes are identified for HCWAs, while 14 for TFAs and 13 for PAs. Node degree analysis with confidence quantifies mutual influences, forming critical accident causal links for each area. The research results offer decision support for precise accident risk control, aiding in reducing future accidents and improving process system safety in chemical enterprises.

Charging Scheduling Method for Wireless Rechargeable Sensor Networks Based on Energy Consumption Rate Prediction for Nodes.

With the development of the IoT, Wireless Rechargeable Sensor Networks (WRSNs) derive more and more application scenarios with diverse performance requirements. In scenarios where the energy consumption rate of sensor nodes changes dynamically, most existing charging scheduling methods are not applicable. The incorrect estimation of node energy requirement may lead to the death of critical nodes, resulting in missing events. To address this issue, we consider both the spatial imbalance and temporal dynamics of the energy consumption of the nodes, and minimize the Event Missing Rate (EMR) as the goal. Firstly, an Energy Consumption Balanced Tree (ECBT) construction method is proposed to prolong the lifetime of each node. Then, we transform the goal into Maximizing the value of the Evaluation function of each node's Energy Consumption Rate prediction (MEECR). Afterwards, the setting of the evaluation function is explored and the MEECR is further transformed into a variant of the knapsack problem, namely "the alternating backpack problem", and solved by dynamic programming. After predicting the energy consumption rate of the nodes, a charging scheduling scheme that meets the Dual Constraints of Nodes' energy requirements and MC's capability (DCNM) is developed. Simulations demonstrate the advantages of the proposed method. Compared to the baselines, the EMR was reduced by an average of 35.2% and 26.9%.

Which comes first? Comorbidity of depression and anxiety symptoms: A cross-lagged network analysis

Depression and anxiety significantly impact college students, leading to various negative outcomes. While numerous studies have investigated the relationship between these two conditions, their temporal sequence remains unresolved. Many previous studies have concentrated on broad latent variables, often neglecting the nuanced symptomatology perspective, which may offer deeper insight into the clinical characteristics of these disorders. In this study, we collected questionnaire data from a college in South China using a cluster random sampling method. Data collection occurred over two time points, with the first round completed in November 2022 and May 2023, with a six-month interval. A total of 689 participants successfully completed the questionnaires during both rounds. Employing cross-lagged network analysis from a symptom-focused perspective, this research examines the interactions and predictive relationships between symptoms of depression and anxiety. The findings identified key symptoms-specifically “Irritability”, “Guilty” and “Sad mood"- as critical bridging nodes of connection within the depression and anxiety symptom network. Our analysis revealed both bidirectional predictive relationships between certain symptoms nodes of depression and anxiety, as well as unidirectional ones. By highlighting these core nodes and their directional relationships, this study offers valuable insights that can inform targeted intervention and treatment strategies for enhancing mental health among college students.

Maritime transportation risk assessment: A multilevel node relationship-based fuzzy bayesian network

Maritime transportation safety has encountered unprecedented challenges arising from abrupt changes in various risk attributes in recent years, including natural weather and non-traditional security threats. This study presents a novel two-phase framework for assessing the maritime transportation risk. Firstly, a fuzzy Bayesian network considering multi-level node relationships was constructed to more accurately assess the transportation risk in various sea areas. In the second phase, RF-Shapley was developed to identify crucial risk nodes that exert substantial influence on transportation risk within individual sea areas. The results showed that transportation risk was the lowest in the South Asian and the highest in the Middle East waters. Critical risk nodes were different for each sea area, such as pirate attack node in Southeast Asian waters, extreme weather node in Northeast Asia, changing these nodes would be more helpful in improving transportation safety. Moreover, the contribution of critical risk nodes exhibited variations, such as combating terrorism and piracy were more conducive to reducing transportation risk in Middle Eastern waters, while ship accidents node be low contribution. These results offer valuable insights for evaluating transportation risk in uncertain environments and can serve as a reference for stakeholders to devise tailored policies and action plans.

Understanding the metabolic nodes in itaconic acid synthesis of an Aspergillus terreus mutant identified by high-throughput screening

Aspergillus terreus is the most important strain for the industrial production of itaconic acid. Few works have reported the critical metabolic nodes in the synthesis of itaconic acid in A. terreus. Herein a high-throughput screening method was established to screen an efficient mutant A. terreus 6–12#, which could produce 28.6 g/L itaconic acid with a productivity of 0.36 g/g glucose, about 66 % and 57 % higher than that of the parent strain. On this basis, the expression of the key enzymes was analyzed centering on the glycolytic pathway, the precursor synthesis pathway, the itaconic acid synthesis and degradation pathways, and the membrane transport system. It was proven that the expressions of enzymes favoring itaconic acid synthesis in each of these modules were significantly elevated in the mutant. But the enzymes CAD, MTT, MFS in the itaconic acid synthesis pathway and the membrane transport system displayed low elevation levels, while the degradation pathway was activated with the improvement of itaconic acid, which was considered the possible limited step in itaconic acid synthesis in A. terreus. These findings provided potential metabolic modification targets for further acquisition of excellent A. terreus cell factories and helped to facilitate the industrial production of itaconic acid.

Behavioral Transition Path and Pivotal Nodes Regulating Attack in Initial Encounters between Unfamiliar Pigs.

This study leverages the inherent curiosity of pigs and their competitive nature among conspecifics to explore behavioral transition paths and critical nodes that govern aggression during initial encounters between unfamiliar individuals. Two consecutive experiments were designed to investigate these dynamics under controlled conditions. In Experiment 1, unfamiliar pigs engaged in one-on-one fights with quick retreats, displaying a simple behavioral sequence of looking followed by attacking. In Experiment 2, the addition of new pigs to resident groups resulted in a more complex and structured behavioral sequence. Resident pigs exhibited a 'four-step' exploratory behavior pattern: looking, sniffing, touching, and attacking. Further analysis revealed distinct exploratory pathways. In Experiment 1, only short behavioral paths were observed, while Experiment 2 revealed both long and short paths. Specifically, Experiment 2 uncovered seven types of behavioral transition paths, four of which were long and three short, highlighting different combinations of the basic behaviors. The transition paths involving aggression were more varied in Experiment 2 compared to Experiment 1. Overall, the 15 most frequent and obvious behavioral transition paths were identified across both experiments. Eight types of paths were categorized based on the transitions between the basic behaviors. These findings enhance our understanding of the behavioral dynamics in unfamiliar pig encounters, emphasizing the complexity of social interactions and the conditions under which aggression occurs.

Determination of mining-induced stress based on mining face hydraulic support stress and micro-seismicity

Understanding dynamic visualization of mining-induced stress is of great significance to disaster prevention and control in coal mining activities. In this study, three theoretical models, including linear, polynomial, and exponential models, are proposed to inverse the mining-induced stress through the acquisition and analysis of hydraulic support stress and micro-seismicity in the coal mining face. The distribution of mining-induced stress in the coal seam are graphed by fitting two key stress parameters including hydraulic support stress and peak stress, and two key zones including goaf zone and in situ stress zone. These key stress parameters and zones are defined based on the critical nodes of the model curve. According to the geological background of Mataihao coal mine in Erdos, Inner Mongolia Autonomous Region, China, the contours of mining-induced stress are graphed through the stress calculation of these three inversion theoretical models. The multi-monitoring data of micro-seismicity, drilling chips, advanced borehole stress and bolts axial force are used to verify the key stress parameters and zones of the theoretical models. It shows that the monitoring data are in good agreement with the distribution of inversed results. It should be emphasized that, if the fault structure exists around the mining face, the mining-induced stress decreases obviously when the mining face is passing through the faults, and the location of the peak stress will be closer to the mining face. The results in this study could provide methods for early prevention of extreme mining-induced stress and disaster control in the mining activities.

The Pangsau Pass: Historical, Cultural, And Geopolitical Dimensions Of Border Construction Between Arunachal Pradesh And Myanmar

The Pangsau Pass, straddling the border between Arunachal Pradesh (India) and Myanmar, has historically functioned as a critical node for trade, cultural exchange, and geopolitical strategies. This paper delves into the pass’s historical importance, its role in cultural interactions, and the political dynamics that have shaped its significance. The study explores the pass's use as a trade route and cultural conduit prior to and following British colonial interventions. It further examines the impacts of colonial policies, including the Treaty of Yandabo and the Simla Convention, on regional socio-cultural landscapes. Additionally, the paper addresses the effects of modern border management and infrastructure developments, highlighting the resilience of indigenous communities and the continuing relevance of historical routes in current geopolitical contexts.

EtROP38 suppresses apoptosis of host cells infected with Eimeria tenella by inhibition of the p38MAPK pathway

Coccidiosis is an important parasitic disease that has serious adverse effects on the global poultry industry. The mechanism by which the pathogenic factors of Eimeria tenella damage host cells is unknown. Some kinases from the rhoptry compartment can regulate apoptosis of host cells. This study focused on revealing the role and critical nodes of E. tenella rhoptry protein (EtROP) 38 in controlling the apoptosis of host cells via the P38 mitogen-activated protein kinase (MAPK) signaling pathway. The cells were treated with EtROP38 protein, siRNA p38MAPK, or both. The rate of infection, apoptosis, and the dynamic changes in the expression and activation of key factor genes of the P38MAPK signaling pathway in host cells infected with E. tenella were measured. The results showed that the addition of EtROP38 and/or knockdown of the host cells p38 gene reduced the apoptosis rate of cecal epithelial cells (CECS), decreased the mRNA expressions of p38, p53, c-myc, c-fos, and c-jun and increased the expression of p65, decreased the protein expressions of c-myc, c-fos, and c-jun, decreased the p38 protein phosphorylation level, and increased the p65 protein phosphorylation level in CECS. When E. tenella was inoculated for 4–96 h, the addition of Et ROP38 and/or host cell p38 knockdown both increased the infection rate of host cells, and this effect was more pronounced with the addition of EtROP38 with the host cell p38 knockdown. These observations indicate that E. tenella can inhibits the activation of the p38MAPK signaling pathway in host cells via EtROP38, which suppresses apoptosis in host cells.

Efficiency Assessment of Urban Road Networks Connecting Critical Node Pairs under Seismic Hazard

Efficiency Assessment of Urban Road Networks Connecting Critical Node Pairs under Seismic Hazard

Distributions of exotic herbaceous species along a roadside on Chichijima, the Ogasawara Islands, and their relationship with human disturbance

AbstractOceanic islands are a major tourist destination, and the invasion of exotic plants on oceanic islands is a serious problem. To discuss how exotic herbaceous plant invasion is driven by human disturbance on an oceanic island, we assessed the distribution patterns of exotic herbaceous species along a metropolitan road, including parking lots, on the island of Chichijima in the Ogasawara Islands of Japan in the North Pacific Ocean. We observed 16 exotic herbaceous species representing seven families, and all the species have also been recorded in surveys 25 years ago. Species richness (number of species per plot) ranged from 0 to 9 with an average of 2.49. Distance from a parking lot was significantly negatively related to the distribution patterns of seven species and positively related to three species, pointing to parking lots being critical nodes along the dispersal pathways of exotic herbaceous species in Chichijima. Although roads are well known to play an important role as corridors for the invasion and seed dispersal of exotic plants, our results suggest that it would also be important to consider the location of parking lots to understand the distribution of exotic herbaceous species in road networks. We suggest that intensive weed management near parking lots and car wash protocols on Chichijima may be effective in halting exotic species spread.

Elevated plasma matrix metalloproteinase 9 in schizophrenia patients associated with poor antipsychotic treatment response and white matter density deficits

Oxidative stress and neuroinflammation contribute to schizophrenia (SCZ) pathology and may influence treatment efficacy. Matrix metalloproteinase 9 (MMP9) is a critical molecular node mediating the interaction between oxidative stress and inflammation, and so may influence treatment efficacy. Here we examined the associations of plasma MMP9 concentration with antipsychotic drug responses, clinical symptoms, and brain structure. A total of 129 healthy controls and 124 patients with SCZ were included in this study. Patients were monitored clinically during 8 weeks of antipsychotic treatment and classified as poor responders (n = 49) or good responders (n = 75). We then compared plasma MMP9 concentrations in healthy controls at baseline and both SCZ responder groups at baseline and after the 8-week antipsychotic treatment regimen. Cognitive function was also examined using the MATRICS Consensus Cognitive Battery. In addition, we extracted regional white matter density from magnetic resonance images of patients. Compared to healthy controls, plasma MMP9 levels were significantly elevated in poor responders at baseline and negatively correlated with both white matter density in the right superior temporal gyrus and the change in cognitive symptoms after treatment. Conversely, there was no significant difference in plasma MMP9 between good responders and healthy controls, and no associations of plasma MMP9 with cognitive symptoms or regional white matter density among good responders. Elevated plasma MMP9 is associated with poor antipsychotic drug efficacy and white matter deficits in SCZ patients, and so may be a useful biomarker to guide personalized treatment.

Disruption of glucose homeostasis by bacterial infection orchestrates host innate immunity through NAD+/NADH balance

Metabolic reprogramming is crucial for activating innate immunity in macrophages, and the accumulation of immunometabolites is essential for effective defense against infection. The NAD+/NADH (ratio of nicotinamide adenine dinucleotide and its reduced counterpart) redox couple serves as a critical node that integrates metabolic pathways and signaling events, but how this metabolite couple engages macrophage activation remains unclear. Here, we show that the NAD+/NADH ratio serves as a molecular signal that regulates proinflammatory responses and type I interferon (IFN) responses divergently. Salmonella Typhimurium infection leads to a decreased NAD+/NADH ratio by inducing the accumulation of NADH. Further investigation shows that an increased NAD+/NADH ratio correlates with attenuated proinflammatory responses and enhanced type I IFN responses. Conversely, a decreased NAD+/NADH ratio is linked to intensified proinflammatory responses and restrained type I IFN responses. These results show that the NAD+/NADH ratio is an essential cell-intrinsic factor that orchestrates innate immunity, which enhances our understanding of how metabolites fine-tune innate immunity.

The multi-stage plasticity in the aggression circuit underlying the winner effect.

Winning increases the readiness to attack and the probability of winning, a widespread phenomenon known as the "winner effect". Here, we reveal a transition from target-specific to generalized aggression enhancement over 10 days of winning in male mice, which is supported by three stages of plasticity in the ventrolateral part of the ventromedial hypothalamus (VMHvl), a critical node for aggression. Over 10-day winning, VMHvl cells experience monotonic potentiation of long-range excitatory inputs, a transient local connectivity strengthening, and a delayed excitability increase. These plasticity events are causally linked. Optogenetically coactivating the posterior amygdala (PA) terminals and VMHvl cells potentiates the PA-VMHvl pathway and triggers the cascade of plasticity events as those during repeated winning. Optogenetically blocking PA-VMHvl synaptic potentiation eliminates all winning-induced plasticity. These results reveal the complex Hebbian synaptic and excitability plasticity in the aggression circuit during winning that ultimately leads to an increase in "aggressiveness" in repeated winners.

A dynamic decision-making approach for cabin unlawful interference emergency disposal using dynamic Bayesian network

Disposal of unlawful interference incidents is essential for is crucial for the advancement of aviation security. Effective emergency disposal requires a comprehensive approach that includes the perspectives of airlines, airports, and passengers. In this context, each component of the disposal process can fail randomly. The objective of this research is to optimize emergency disposal decisions to enhance the efficiency of civil aviation operations, reduce accidents, and lower costs. Given the dynamic complexity of unlawful interference incidents, a dynamic fault tree consisting of 26 nodes was constructed to analyze the emergency disposal process. To explore the relationships and priorities of each event, the Dynamic Fault Tree is converted into a dynamic Bayesian network. Based on historical statistical data, simulation analysis is conducted in three aspects: posterior probability, sensitivity, and importance. Simulation results reveal that the top three critical nodes in cabin unlawful interference incidents are “structural damage to the cabin,” “inadequate training by airlines,” and “untimely airport police takeover of disruptive passengers.” Further analysis shows that (1) most of the critical nodes are associated with airlines. (2) The decision-making rationale and pathways of the critical nodes can be clearly observed and prioritized. (3) Besides airlines, other entities such as airports can implement targeted emergency disposal measures. Through quantitative analysis and simulation, this study provides decision-making guidance for participating groups on dynamic emergency disposal, thereby enhancing civil aviation security.

Spatial distribution characteristics of relationship network of Beijing-Hangzhou Grand Canal water engineering facilities based on Gephi

The Beijing-Hangzhou Grand Canal, China’s oldest and most crucial water transportation project, ensures smooth operation and efficient water transportation through interconnected water engineering facilities. Studying the connections among the water engineering facilities of the Beijing-Hangzhou Grand Canal is theoretically and practically significant for preserving and innovating canal heritage. Therefore, this study utilizes social network analysis to comprehensively examine the spatial connections and network status of water engineering facilities along the Beijing-Hangzhou Grand Canal across different channel structure. Gephi 0.10.1 was utilized in this study to construct a relational network of water engineering facilities along the Beijing-Hangzhou Grand Canal, with each facility considered as a network node. By applying network analysis indices such as degree, closeness centrality, and betweenness centrality, the correlation between water engineering facilities was thoroughly investigated. The study’s findings reveal that: (1) the Beijing-Hangzhou Grand Canal possesses numerous overall network nodes with extensive coverage; however, its overall network density is relatively low, and the inter-node connection is weak. (2) Across the entire network, the spatial distribution of degree and betweenness centrality exhibits a clustered pattern. Their distribution patterns are centered on the Lake region section where Hongze Lake is located and the segment from Liucheng to Zhenjiang in the Lake region, the River transport confluence section, and the Nature river section, respectively. The spatial distribution characteristics of closeness centrality show a dispersed shape, with stronger areas mainly concentrated in the canal’s tributaries, especially the Nature river section, which shows more prominence. (3) Analyzed from a channel structure perspective, water engineering facilities in different sections assume distinct linking roles within the network. Facilities in the Lake region section play the strongest overall linkage role, partly due to its highest node proportion. Conversely, in the Nature river section, facilities primarily serve transshipment and direct connection functions, whereas in the River transport confluence section, they act mainly as intermediaries or “bridges”. Notably, water control facilities in the Nature river section and river engineering facilities in the River transport confluence section play pivotal driving roles in their respective sections, warranting special attention and protection as critical canal nodes.

Response to the comment on “Identifying critical nodes in complex networks based on distance Laplacian energy”

The following is a point-by-point response to Wang and Sun's comment on “Identifying critical nodes in complex networks based on distance Laplacian energy”.

Improving resilience of cyber–physical power systems against cyber attacks through strategic energy storage deployment

The widespread integration of advanced technologies has increased the vulnerability of Cyber–Physical Power Systems (CPPS) against cyber attacks. In addition, the incorporation of renewable energy sources (RESs) poses extra uncertainty challenges in CPPS security. In this paper, focusing on resilience assessment and improvement, we first propose a comprehensive framework to reveal the whole process from attack initiation to performance recovery. Then, regarding the protection strategies before and after cyber attacks, we improve resilience performance by protecting critical nodes and deploying energy storage nodes. The effectiveness of our proposed methods is validated through testing on a simulated model, which couples the IEEE 39-bus power system with a scale-free communication network. The results demonstrate that the deployment of energy storage plays a significant role in suppressing the uncertainty of RESs and improving the resilience of CPPS against cyber attacks. In addition, we employ a heuristic algorithm to optimize the placement of energy storage nodes. Our work not only represents an overview of the resilience process but also provides system dispatchers with practical strategies for improving the resilience of renewable CPPS against the growing threat of cyber attacks.

A practically efficient algorithm for identifying critical control proteins in directed probabilistic biological networks

Network controllability is unifying the traditional control theory with the structural network information rooted in many large-scale biological systems of interest, from intracellular networks in molecular biology to brain neuronal networks. In controllability approaches, the set of minimum driver nodes is not unique, and critical nodes are the most important control elements because they appear in all possible solution sets. On the other hand, a common but largely unexplored feature in network control approaches is the probabilistic failure of edges or the uncertainty in the determination of interactions between molecules. This is particularly true when directed probabilistic interactions are considered. Until now, no efficient algorithm existed to determine critical nodes in probabilistic directed networks. Here we present a probabilistic control model based on a minimum dominating set framework that integrates the probabilistic nature of directed edges between molecules and determines the critical control nodes that drive the entire network functionality. The proposed algorithm, combined with the developed mathematical tools, offers practical efficiency in determining critical control nodes in large probabilistic networks. The method is then applied to the human intracellular signal transduction network revealing that critical control nodes are associated with important biological features and perturbed sets of genes in human diseases, including SARS-CoV-2 target proteins and rare disorders. We believe that the proposed methodology can be useful to investigate multiple biological systems in which directed edges are probabilistic in nature, both in natural systems or when determined with large uncertainties in-silico.