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Hub-and-spoke networks play a critical role in reducing cost and enhancing service levels in various infrastructural sectors since hubs act as the consolidation and transshipment points of the flows. The failure of hubs in such a network can cause severe disruptions. While disruptions can be natural or man-made, a disruption by a rational individual or entity can be significantly detrimental to the network and is often studied as an interdiction problem. It is important to take interdiction effects at the design stage; therefore, we study the three-level capacitated hub-and-spoke network design problem from the perspective of a defender who considers the risk of interdiction by a rational attacker. Within the three levels, the upper level represents the network design level, and the lower two levels represent the bi-level hub interdiction problem. The introduction of capacity constraints within an interdiction model dramatically increases the complexity of the problem, as there can be some unfulfilled flows post-interdiction. Moreover, a flow may or may not be fulfilled through the least-cost route using the nearest hubs. This work makes two major contributions: the first contribution is on the efficient handling of the bi-level hub interdiction problem using the Dual-based approach and the Penalty-based approach, and the second contribution is on solving the overall three-level problem using a super valid inequality. These two contributions allow us to solve large-scale versions of the capacitated multiple allocation p-median hub location problem under the risk of interdiction, which is otherwise mathematically intractable and can be handled only using complete enumeration techniques.

Accurate DNA replication and transcription elongation are crucial for preventing the accumulation of unreplicated DNA and genomic instability. Cells have evolved multiple mechanisms to deal with impaired replication fork progression, challenged by both intrinsic and extrinsic impediments. The bacterium Bacillus subtilis, which adopts multiple forms of differentiation and development, serves as an excellent model system for studying the pathways required to cope with replication stress to preserve genomic stability. This review focuses on the genetics, single molecule choreography, and biochemical properties of the proteins that act to circumvent the replicative arrest allowing the resumption of DNA synthesis. The RecA recombinase, its mediators (RecO, RecR, and RadA/Sms) and modulators (RecF, RecX, RarA, RecU, RecD2, and PcrA), repair licensing (DisA), fork remodelers (RuvAB, RecG, RecD2, RadA/Sms, and PriA), Holliday junction resolvase (RecU), nucleases (RnhC and DinG), and translesion synthesis DNA polymerases (PolY1 and PolY2) are key functions required to overcome a replication stress, provided that the fork does not collapse. Different stresses interfering with DNA replication, collectively termed replication stress, pose a threat to genomic stability in Bacillus subtilis cells.

This paper contributes to the integrated design issue of urban and rural logistics networks under demand uncertainty. A hierarchical hub location model is proposed, which minimizes the expected total system cost by optimizing the locations, number and capacities of “urban-town‒village” hierarchical logistics hubs. The interactions among the logistics hubs and among the hub‒and‒spoke connections, as well as the hub capacity constraints are explicitly considered in the presence of logistics demand uncertainty. A demand scenario‒based branch‒and‒Benders‒cut algorithm is developed to solve the proposed model. A case study of Jiangling urban‒rural region in Hubei province of China is conducted for the illustration of the model and solution algorithm. The results generated by the proposed algorithm are benchmarked against those obtained by GUROBI solver and the practical scheme being currently implemented in the region. The results showed that the proposed methodology can greatly improve the efficiency of the urban‒rural logistics system in terms of expected total system cost. It is important to explicitly model the demand uncertainty, otherwise a significant decision bias may emerge. The proposed algorithm outperforms the GUROBI solver in terms of problem size solved and computational time.

Last year was the 25th anniversary of two seminal transportation hub location publications, which appeared in 1986 in Transportation Science and Geographical Analysis . Though there are related hub location and network design articles that predate these works, the 1986 publications provided a key impetus for the growth of hub location as a distinct research area. This paper is not intended as a comprehensive review of hub location literature; rather, our goal is to reflect on the origins of hub location research, especially in transportation, and provide some commentary on the present status of the field. We provide insight into early motivations for analyzing hub location problems and describe linkages to problems in location analysis and network design. We also highlight some of the most recent research, discuss some shortcomings of hub location research and suggest promising directions for future effort.

Calcium is an essential structural, metabolic and signalling element. The physiological functions of Ca2+ are enabled by its orchestrated transport across cell membranes, mediated by Ca2+-permeable ion channels,Ca2+-ATPases andCa2+/H+ exchangers. Bioinformatics analysis has not determined any Ca2+-selective filters in plant ion channels, but electrophysiological tests do reveal Ca2+ conductances in plant membranes. The biophysical characteristics of plant Ca2+ conductances have been studied in detail and were recently complemented by molecular genetic approaches. Plant Ca2+ conductances are mediated by several families of ion channels, including cyclic nucleotide-gated channels (CNGCs), ionotropic glutamate receptors, two-pore channel 1 (TPC1), annexins and several types of mechanosensitive channels. Key Ca2+-mediated reactions (e.g. sensing of temperature, gravity, touch and hormones, and cell elongation and guard cell closure) have now been associated with the activities of specific subunits from these families. Structural studies have demonstrated a unique selectivity filter in TPC1, which is passable for hydrated divalent cations. The hypothesis of a ROS-Ca2+ hub is discussed, linking Ca2+ transport to ROS generation. CNGC inactivation by cytosolic Ca2+, leading to the termination of Ca2+ signals, is now mechanistically explained. The structure–function relationships of Ca2+-ATPases and Ca2+/H+ exchangers, and their regulation and physiological roles are analysed.

Proteins and glycans play a role in selecting and guiding sperm on their journey to the egg.

The air transport systems can be represented as a network where airports serve as nodes and flight paths as links. The degree of connections between airports is defined as connectivity in air transport. With the increasing competition environment after liberalization in the air transport sector, the connectivity of airports is becoming an increasingly important issue. Thanks to Türkiye’s advantageous geographical situation, and the hub and spoke system applied to the network structures of the airline companies operating, the city of Istanbul has become a major transfer point. However, considering the increasing demand for air transport, population growth, tourism and trade volume, capacity constraints of airports, and existing and ongoing transport infrastructure investments, it is considered that the establishment of a polycentric network structure in Türkiye will increase the connectivity in air transport. In this study, in order to contribute to the development of the multi-center air transport model; a hub location selection model has been developed considering the factors affecting the connectivity of airports. GAMS software was used for model solution. In order to measure high-speed train accessibility, green airport applications and the effects of the Covid-19 pandemic, different scenarios were produced, and the solution results were evaluated.

To explore the hub gene closely related to the progression of gastric cancer (GC), so as to provide a theoretical basis for revealing the therapeutic mechanism of GC. The gene expression profile and clinical data of GSE15459 in Gene Expression Omnibus (GEO) database were downloaded. The weighted gene co-expression network analysis (WGCNA) was used to screen the key modules related to GC progression. Survival analysis was used to assess the influence of hub genes on patients' outcomes. CIBERSORT analysis was used to predict the tissue infiltrating immune cells in patients. Immunohistochemical staining was conducted to further verify the expression of hub genes. Through WGCNA, a total of 26 co-expression modules were constructed, in which salmon module and royalblue module had strong correlation with GC progression. The results of enrichment analysis showed that genes in the two modules were mainly involved in toll-like receptor signaling pathway, cholesterol metabolism and neuroactive ligand-receptor interaction. Six hub genes ( , , , , and ) related to GC progression were screened. Survival analysis showed overall survival in the high expression group was significantly lower than that in the low expression group. CIBERSORT analysis revealed that immune characteristics difference between patients in early stage and advanced stage. Immunohistochemical results confirmed that , , and were significantly associated with disease progression in GC. Our study identified that , , and played important roles in the progression of GC, and their specific mechanisms are worth further study.

•Novel method MQGA enhances quantitative analysis of brain network hubs.•MQGA uses betweenness centrality, degree centrality, and participation coefficient to comprehensively characterize provincial nodes and connector nodes.•Optimal hub node index found at 4 % sparsity, improving hub identification accuracy.•Removing connector hubs impacts network integrity more than removing provincial hubs.•Higher hub stability observed in healthy controls compared to disease groups. Recent advancements in large-scale network studies have shown that connector hubs and provincial hubs are vital for coordinating complex cognitive tasks by facilitating information transfer between and within specialized modules. However, current methods for identifying these hubs often lack standardized measurement criteria, hindering quantitative analysis. This study proposes a novel computational method utilizing multi-graph theoretical index calculations to quantitatively analyze hub attributes in brain networks. Using benchmark network, random simulation network (N = 100), resting fMRI data from the ADHD-200 NYU dataset (HC = 110, ADHD = 146), and the Peking dataset (HC = 120, ADHD = 83), we introduce the Multi-criteria Quantitative Graph Analysis (MQGA) method, which employs betweenness centrality, degree centrality, and participation coefficient to determine the connector (con) hub index and provincial (pro) hub index. The method's accuracy, reliability, and stability were validated through correlation analysis of hub indices and labels, vulnerability tests, and consistency analysis across subjects. Results indicate that as network sparsity increases, the con hub index increases while the pro hub index decreases, with the optimal hub node index at 4 % sparsity. Vulnerability tests revealed that removing con nodes had a greater impact on network integrity than removing pro nodes. Both con and pro exhibited stability in consistency analyses, but con was more stable. The stability of hub scores in disease groups was significantly lower than in the healthy control group. High con values were found in the precuneus, postcentral gyrus, and precentral gyrus, whereas high pro values were identified in the precentral gyrus, postcentral gyrus, superior parietal lobule, precuneus, and superior temporal gyrus. This approach enhances the accuracy and sensitivity of hub node identification, facilitating precise comparisons and producing consistent, replicable results, advancing our understanding of brain network hub nodes, their roles in cognitive processes, and their implications for brain disease research.

Purpose: The overstocked goods flow in the hub of hub-and-spoke logistics network should be disposed of in time, to reduce delay loss and improve the utilization rate of logistics network resources. The problem we need to solve is to let logistics network cooperate by sharing network resources to shunt goods from one hub-and-spoke network to another hub-and-spoke network. Design/methodology/approach: This paper proposes the hub shunting cooperation between two hub-and-spoke networks. Firstly, a hybrid integer programming model was established to describe the problem, and then a multi-layer genetic algorithm was designed to solve it and two hub-and-spoke networks are expressed by different gene segments encoded by genes. The network data of two third-party logistics companies in southern and northern China are used for example analysis at the last step. Findings: The hub-and-spoke networks of the two companies were constructed simultaneously. The transfer cost coefficient between two networks and the volume of cargo flow in the network have an impact on the computation of hubs that needed to be shunt and the corresponding cooperation hubs in the other network. Originality/value: Previous researches on hub-and-spoke logistics network focus on one logistics network, while we study the cooperation and interaction between two hub-and-spoke networks. It shows that two hub-and-spoke network can cooperate across the network to shunt the goods in the hub and improve the operation efficiency of the logistics network.