Set Of Hubs Research Articles

Regional centrality and tax competition for FDI

We examine a trade model where three countries compete for an exogenous number of firms. In our hub-and-spoke framework, one country is the hub through which all trade with and between spokes takes place. We establish the distribution of industrial activity in the absence of taxes and compare it to the equilibrium when countries compete to attract firms. Even when all countries have the same size, the centrality of the hub sets it apart. We determine how this trading pattern matters, comparing it to a structure with direct trade between all countries. The implications of international tax competition are also examined.

Towards network substrates of brain disorders.

This scientific commentary refers to ‘The hubs of the human connectome are generally implicated in the anatomy of brain disorders’, by Crossley et al. (doi:10.1093/brain/awu132). A growing number of studies approach brain anatomy and function from the perspective of complex networks, with an explicit focus on the distributed layout of neural elements and their interconnections in the healthy, as well as diseased brain (Sporns, 2014). Network analysis has revealed a number of characteristic features of brain network organization, such as the presence of densely connected clusters or modules of brain regions, and of highly connected network hubs. In this issue of Brain , Nicolas Crossley and colleagues report the results of an extensive meta-analysis of MRI data, including a large set of observations of grey matter lesions in various brain disorders. They reveal that the disorders are associated with damage to distinct sets of hubs, and propose that disruption of network hubs may be a common factor contributing to brain dysfunction (Crossley et al. , 2014). Network approaches to brain function capitalize on the advances that have been made across a broad range of social, technological and biological systems using the concepts and computational tools of network science. Brain networks consist of nodes and connections; these are derived from brain imaging data by first applying a parcellation to derive node boundaries, and then estimating the presence and strength of connections between pairs of nodes. Structural networks capture network anatomy, based on data obtained via techniques such as diffusion imaging and tractography. In contrast, functional networks are built from estimates of statistical dependencies between time series of neuronal activity, as recorded for example with functional MRI. The complete set of structural connections is defined as the brain’s connectome (Sporns et al. , 2005), a whole-brain structural network that …

RNA-Seq and Microarrays Analyses Reveal Global Differential Transcriptomes of Mesorhizobium huakuii 7653R between Bacteroids and Free-Living Cells

Mesorhizobium huakuii 7653R occurs either in nitrogen-fixing symbiosis with its host plant, Astragalus sinicus, or free-living in the soil. The M. huakuii 7653R genome has recently been sequenced. To better understand the complex biochemical and developmental changes that occur in 7653R during bacteroid development, RNA-Seq and Microarrays were used to investigate the differential transcriptomes of 7653R bacteroids and free-living cells. The two approaches identified several thousand differentially expressed genes. The most prominent up-regulation occurred in the symbiosis plasmids, meanwhile gene expression is concentrated to a set of genes (clusters) in bacteroids to fulfill corresponding functional requirements. The results suggested that the main energy metabolism is active while fatty acid metabolism is inactive in bacteroid and that most of genes relevant to cell cycle are down-regulated accordingly. For a global analysis, we reconstructed a protein-protein interaction (PPI) network for 7653R and integrated gene expression data into the network using Cytoscape. A highly inter-connected subnetwork, with function enrichment for nitrogen fixation, was found, and a set of hubs and previously uncharacterized genes participating in nitrogen fixation were identified. The results described here provide a broader biological landscape and novel insights that elucidate rhizobial bacteroid differentiation, nitrogen fixation and related novel gene functions.

Capacitated Centralized Carrier Collaboration Multihub Location Problem

This study proposes a capacitated centralized carrier collaboration multihub location problem (CAP-CCCMLP) for the small- to medium-sized less-than-truckload industry, with a central entity (e.g., a third-party logistics firm) seeking a set of hybrid collaborative consolidation transshipment hubs to help establish a collaborative hybrid hub-and-spoke network that minimizes the total collaborative costs for the set of collaborating carriers in the system. A mathematical programming formulation is provided for the CAP-CCCMLP and shown to be NP-hard. The model was solved with two-phase tabu search heuristics. Computational runs were conducted to study the efficiency of the tabu search heuristic versus the CPLEX-based solution and the savings obtained through collaboration for different network sizes and maximum number of consolidation hubs. The tabu search heuristic was found to deliver significant computational savings over CPLEX and the optimality gap between the true optimal solution and the tabu search solution was found to be low for most cases. As the expected cost reduction at the shipment level needed to incentivize collaboration decreases, the likelihood that carriers will enter into collaboration increases. If the carriers expect significant cost reductions to enter into a collaborative strategy, the potential savings from the collaboration will decrease.

Chapter Four - Coexpression and Cosplicing Network Approaches for the Study of Mammalian Brain Transcriptomes

Next-generation sequencing experiments have demonstrated great potential for transcriptome profiling. While transcriptome sequencing greatly increases the level of biological detail, system-level analysis of these high-dimensional datasets is becoming essential. We illustrate gene network approaches to the analysis of transcriptional data, with particular focus on the advantage of RNA-Seq technology compared to microarray platforms. We introduce a novel methodology for constructing cosplicing networks, based on distance measures combined with matrix correlations. We find that the cosplicing network is distinct and complementary to the coexpression network, although it shares the scale-free properties. In the cosplicing network, we find a set of novel hubs that have unique characteristics distinguishing them from coexpression hubs: they are heavily represented in neurobiological functional pathways and have strong overlap with markers of neurons and neuroglia, long-coding lengths, and high number of both exons and annotated transcripts. We also find that gene networks are plastic in the face of genetic and environmental pressures.

Revealing Long-Range Interconnected Hubs in Human Chromatin Interaction Data Using Graph Theory

We use graph theory to analyze chromatin interaction (Hi-C) data in the human genome. We show that a key functional feature of the genome--"master" replication origins--corresponds to DNA loci of maximal network centrality. These loci form a set of interconnected hubs both within chromosomes and between different chromosomes. Our results open the way to a fruitful use of graph theory concepts to decipher DNA structural organization in relation to genome functions such as replication and transcription. This quantitative information should prove useful to discriminate between possible polymer models of nuclear organization.

London biomedical hub sets its research agenda

London biomedical hub sets its research agenda

Solving the p-hub Median Problem Under Intentional Disruptions Using Simulated Annealing

Hubs are special facilities designed to act as switching, transshipment and sorting points in various distribution systems. Since hub facilities concentrate and consolidate flows, disruptions at hubs could have large effects on the performance of a hub network. In this paper, we have formulated the multiple allocation p-hub median problem under intentional disruptions as a bi-level game model. In this model, the follower’s objective is to identify those hubs the loss of which would most diminish service efficiency. Moreover, the leader’s objective is to identify the set of hubs to locate in order to minimize expected transportation cost while taking normal and failure conditions into account. We have applied two algorithms based on simulated annealing to solve the defined problem. In addition, the algorithms have been calibrated using the Taguchi method. Computational experiments on different instances indicate that the proposed algorithms would be efficient in practice.

Piggybacking on social networks

The popularity of social-networking sites has increased rapidly over the last decade. A basic functionalities of social-networking sites is to present users with streams of events shared by their friends. At a systems level, materialized per-user views are a common way to assemble and deliver such event streams on-line and with low latency. Access to the data stores, which keep the user views, is a major bottleneck of social-networking systems. We propose to improve the throughput of these systems by using social piggybacking, which consists of processing the requests of two friends by querying and updating the view of a third common friend. By using one such hub view, the system can serve requests of the first friend without querying or updating the view of the second. We show that, given a social graph, social piggybacking can minimize the overall number of requests, but computing the optimal set of hubs is an NP-hard problem. We propose anO(logn) approximation algorithm and a heuristic to solve the problem, and evaluate them using the full Twitter and Flickr social graphs, which have up to billions of edges. Compared to existing approaches, using social piggybacking results in similar throughput in systems with few servers, but enables substantial throughput improvements as the size of the system grows, reaching up to a 2-factor increase. We also evaluate our algorithms on a real social networking system prototype and we show that the actual increase in throughput corresponds nicely to the gain anticipated by our cost function.

Centralized Carrier Collaboration Multihub Location Problem for Less-Than-Truckload Industry

A centralized carrier collaboration multihub location problem (CCCMLP) for the small to medium-sized less-than-truckload industry is addressed. In the CCCMLP, a central entity (e.g., a third-party logistics firm) seeks a set of collaborative consolidation transshipment hubs to establish a hybrid collaborative hub-and-spoke system that minimizes the total collaborative costs for the set of collaborating carriers. Previous studies focused on addressing the exchange of capacity without considering the location of transfer hubs and the routes that connect them. A carrier has the option either to collaborate or to ship its demand directly without collaborating. The decision depends on the expected profit margin over shipping directly while following a revenue-generating, rate-setting behavior. The CCCMLP was formulated as a variant of the P-hub location problem, which is NP-hard and solved with Lagrangian relaxation. Numerical experiments were conducted to gain insight into the performance of the CCCMLP formulation under various network sizes and numbers of hubs. The results indicate that larger expected profit margins from collaborative carriers applying revenue-generating behavior would increase the likelihood of collaboration by carriers. As the network size increases, the effect of hybrid hub location costs drops.

Hub covering location problems with different coverage types

The hub location problem is used for many applications, including cargo delivery systems, airline systems, telecommunication network design and so on. Each area has its own characteristics in hub location. In this paper, we study the hub covering problem with different coverage type over complete hub networks. Furthermore, hub set and maximal covering are expressed with single and multiple allocation strategies. First, a quadratic formulation is proposed for single allocation hub set covering problem. Then a linearization idea is considered for it and applied for multiple allocation hub set, single and multiple allocation hub maximal covering problems. The aim of these models is to find the location of hubs and allocate non-hub nodes to the located hub nodes subject to the travel time (cost or distance) between two nodes in origin-destination doesn’t exceed a given bound. The formulations with this coverage constraint have not been remarked in the literature. Two heuristic procedures are proposed to handle these models in an agreeable solution quality and computational time. The computational experience of Turkish dataset was presented for better illustration of proposed model. And a special application on Iranian hub airports location is discussed.

The capacitated p-hub median problem with integral constraints: An application to a Chinese air cargo network

Consolidation at hubs in a pure hub-and-spoke network eliminates partial center-to-center direct loads, resulting in savings in transportation costs. In this research, we propose a general capacitated p-hub median model, with economies of scale and integral constraints on the paths. This model requires the selection of a specific p among a set of candidate hubs so that the total cost on the resulting pure capacitated hub-and-spoke network is minimized while simultaneously meeting origin–destination demands, operational capacity and singular path constraints. We explored the problem structure and developed a genetic algorithm using the path for encoding. This algorithm is capable of determining local optimality within less than 0.1% of the Lagrangian relaxation lower bounds on our Chinese air cargo network testing case and has reasonable computational times. The study showed that designating airports with high pickups or deliveries as hubs resulted in a high percentage of origin–destination pairs (ODs) in direct deliveries. Furthermore, the more hubs there are, the higher the direct share and the less likely for double rehandles. Sensitivity analysis on the discount rate showed that the economies of scale on trunk lines of hub-and-spoke networks may have a substantial impact on both the operating costs and the route patterns.

Gapped Spectral Dictionaries and Their Applications for Database Searches of Tandem Mass Spectra

Generating all plausible de novo interpretations of a peptide tandem mass (MS/MS) spectrum (Spectral Dictionary) and quickly matching them against the database represent a recently emerged alternative approach to peptide identification. However, the sizes of the Spectral Dictionaries quickly grow with the peptide length making their generation impractical for long peptides. We introduce Gapped Spectral Dictionaries (all plausible de novo interpretations with gaps) that can be easily generated for any peptide length thus addressing the limitation of the Spectral Dictionary approach. We show that Gapped Spectral Dictionaries are small thus opening a possibility of using them to speed-up MS/MS searches. Our MS-Gapped-Dictionary algorithm (based on Gapped Spectral Dictionaries) enables proteogenomics applications (such as searches in the six-frame translation of the human genome) that are prohibitively time consuming with existing approaches. MS-Gapped-Dictionary generates gapped peptides that occupy a niche between accurate but short peptide sequence tags and long but inaccurate full length peptide reconstructions. We show that, contrary to conventional wisdom, some high-quality spectra do not have good peptide sequence tags and introduce gapped tags that have advantages over the conventional peptide sequence tags in MS/MS database searches.

Connectedness of PPI network neighborhoods identifies regulatory hub proteins.

With the growing availability of high-throughput protein-protein interaction (PPI) data, it has become possible to consider how a protein's local or global network characteristics predict its function. We introduce a graph-theoretic approach that identifies key regulatory proteins in an organism by analyzing proteins' local PPI network structure. We apply the method to the yeast genome and describe several properties of the resulting set of regulatory hubs. Finally, we demonstrate how the identified hubs and putative target gene sets can be used to identify causative, functional regulators of differential gene expression linked to human disease. Code is available at http://bcb.cs.tufts.edu/hubcomps. fox.andrew.d@gmail.com; slonim@cs.tufts.edu Supplementary data are available at Bioinformatics online.

The Hub Number of Sierpiński-Like Graphs

A set Q⊆V is a hub set of a graph G=(V,E) if, for every pair of vertices u,v∈V∖Q, there exists a path from u to v such that all intermediate vertices are in Q. The hub number of G is the minimum size of a hub set in G. This paper derives the hub numbers of Sierpinski-like graphs including: Sierpinski graphs, extended Sierpinski graphs, and Sierpinski gasket graphs. Meanwhile, the corresponding minimum hub sets are also obtained.

Uncapacitated single and multiple allocation p-hub center problems

The hub median problem is to locate hub facilities in a network and to allocate non-hub nodes to hub nodes such that the total transportation cost is minimized. In the hub center problem, the main objective is one of minimizing the maximum distance/cost between origin destination pairs. In this paper, we study uncapacitated hub center problems with either single or multiple allocation. Both problems are proved to be NP-hard. We even show that the problem of finding an optimal single allocation with respect to a given set of hubs is already NP-hard. We present integer programming formulations for both problems and propose a branch-and-bound approach for solving the multiple allocation case. Numerical results are reported which show that the new formulations are superior to previous ones.

The hub number of a graph

A hub set in a graph G is a set U ⊆ V ( G ) such that any two vertices outside U are connected by a path whose internal vertices lie in U. We prove that h ( G ) ⩽ h c ( G ) ⩽ γ c ( G ) ⩽ h ( G ) + 1 , where h ( G ) , h c ( G ) , and γ c ( G ) , respectively, are the minimum sizes of a hub set in G, a hub set inducing a connected subgraph, and a connected dominating set. Furthermore, all graphs with γ c ( G ) > h c ( G ) ⩾ 4 are obtained by substituting graphs into three consecutive vertices of a cycle; this yields a polynomial-time algorithm to check whether h c ( G ) = γ c ( G ) .

The Take Part Learning Framework and Networks

Networking is at the core of the Take Part learning framework and its principles inspired the Active Learning for Active Citizenship programme (ALAC). ALAC was organised as a set of regional hubs, which were constituted by local groups working on issues of active learning in civil society. Dialogue, reflection and networking were inherent in these hubs' activities at all levels of the programme. This paper elaborates the role of networking in Take Part, in particular, its contribution to increase social capital and community empowerment.

Web Communities: Models and Algorithms

In the last few years, a lot of research has been devoted to developing new techniques for improving the recall and the precision of current web search engines. Few works deal with the interesting problem of identifying the communities to which pages belong. Most of the previous approaches try to cluster data by means of spectral techniques or by means of traditional hierarchical algorithms. The main problem with these techniques is that they ignore the relevant fact that web communities are social networks with distinctive statistical properties. In this paper we analyze web communities on the basis of the evolution of an initial set of hubs and authoritative pages. The evolution law captures the behaviour of page authors with respect to the popularity of existing pages for the topics of interest. Assuming such a model, we have found interesting properties of web communities. On the basis of these properties we have proposed a technique for computing relevant properties for specific topics. Several experiments confirmed the validity of both the model and identification method.

Enumeration and Search Procedures for a Hub Location Problem with Economies of Scale

Within a communications or transportation network, in which a number of locations exchange material or information, hubs can be used as intermediate switching points. In this way, traffic can be consolidated on inter-hub links and, thus, achieve economies of scale in transport costs. Recently, O'Kelly and Brian in 1998 proposed a model (termed the FLOWLOC model) that treats these economies of scale by means of piecewise-linear concave cost functions on the interhub arcs. We show that, for a fixed set of hubs, the FLOWLOC model can be solved using the classic Uncapacitated Facility Location Problem (UFLP). This observation then motivates an optimal enumeration procedure for the FLOWLOC model, as well as some search heuristics that are based upon tabu search and greedy random adaptive search procedures (GRASP). These search procedures would be especially applicable for large-sized problems. Some computational experience is described.