Inference and Optimization of Real Edges on Sparse Graphs - A Statistical Physics Perspective

Inference and optimization of real-value edge variables in sparse graphs are studied using the Bethe approximation and replica method of statistical physics. Equilibrium states of general energy functions involving a large set of real edge-variables that interact at the network nodes are obtained in various cases. When applied to the representative problem of network resource allocation, efficient distributed algorithms are also devised. Scaling properties with respect to the network connectivity and the resource availability are found, and links to probabilistic Bayesian approximation methods are established. Different cost measures are considered and algorithmic solutions in the various cases are devised and examined numerically. Simulation results are in full agreement with the theory.Comment: 21 pages, 10 figures, major changes: Sections IV to VII updated, Figs. 1 to 3 replace

Optimal Resource Allocation in Random Networks with Transportation Bandwidths

We apply statistical physics to study the task of resource allocation in random sparse networks with limited bandwidths for the transportation of resources along the links. Useful algorithms are obtained from recursive relations. Bottlenecks emerge when the bandwidths are small, causing an increase in the fraction of idle links. For a given total bandwidth per node, the efficiency of allocation increases with the network connectivity. In the high connectivity limit, we find a phase transition at a critical bandwidth, above which clusters of balanced nodes appear, characterised by a profile of homogenized resource allocation similar to the Maxwell's construction.Comment: 28 pages, 11 figure

Multicriteria ranking using weights which minimize the score range

Various schemes have been proposed for generating a set of non-subjective weights when aggregating multiple criteria for the purposes of ranking or selecting alternatives. The maximin approach chooses the weights which maximise the lowest score (assuming there is an upper bound to scores). This is equivalent to finding the weights which minimize the maximum deviation, or range, between the worst and best scores (minimax). At first glance this seems to be an equitable way of apportioning weight, and the Rawlsian theory of justice has been cited in its support.We draw a distinction between using the maximin rule for the purpose of assessing performance, and using it for allocating resources amongst the alternatives. We demonstrate that it has a number of drawbacks which make it inappropriate for the assessment of performance. Specifically, it is tantamount to allowing the worst performers to decide the worth of the criteria so as to maximise their overall score. Furthermore, when making a selection from a list of alternatives, the final choice is highly sensitive to the removal or inclusion of alternatives whose performance is so poor that they are clearly irrelevant to the choice at hand

Optimal Location of Sources in Transportation Networks

We consider the problem of optimizing the locations of source nodes in transportation networks. A reduction of the fraction of surplus nodes induces a glassy transition. In contrast to most constraint satisfaction problems involving discrete variables, our problem involves continuous variables which lead to cavity fields in the form of functions. The one-step replica symmetry breaking (1RSB) solution involves solving a stable distribution of functionals, which is in general infeasible. In this paper, we obtain small closed sets of functional cavity fields and demonstrate how functional recursions are converted to simple recursions of probabilities, which make the 1RSB solution feasible. The physical results in the replica symmetric (RS) and the 1RSB frameworks are thus derived and the stability of the RS and 1RSB solutions are examined.Comment: 38 pages, 18 figure

Research & Action Report, Fall/Winter 2015

In this issue: Commentary with Andrew Levack, M.P.H. Global Connections: Kerr, Stein, Cape Verde, and SEED New Findings & Publications Q&A with April Pattavina, Ph.D. and Linda M. Williams, Ph.D. Recent & Upcoming Presentations Short Takes: Acceptances, Appointments & Recognition Spotlight on New Funding & Projectshttps://repository.wellesley.edu/researchandactionreport/1027/thumbnail.jp

A heuristic approach for the allocation of resources in large-scale computing infrastructures

An increasing number of enterprise applications are intensive in their consumption of IT, but are infrequently used. Consequently, organizations either host an oversized IT infrastructure or they are incapable of realizing the benefits of new applications. A solution to the challenge is provided by the large-scale computing infrastructures of Clouds and Grids which allow resources to be shared. A major challenge is the development of mechanisms that allow efficient sharing of IT resources. Market mechanisms are promising, but there is a lack of research in scalable market mechanisms. We extend the Multi-Attribute Combinatorial Exchange mechanism with greedy heuristics to address the scalability challenge. The evaluation shows a trade-off between efficiency and scalability. There is no statistical evidence for an influence on the incentive properties of the market mechanism. This is an encouraging result as theory predicts heuristics to ruin the mechanism’s incentive properties. Copyright © 2015 John Wiley & Sons, Ltd

Sources to Seafood: Mercury Pollution in the Marine Environment

In 2010, the Toxic Metals Superfund Research Program at Dartmouth College brought together a group of 50 scientists and policy stakeholders to form C-MERC, the Coastal and Marine Mercury Ecosystem Research Collaborative. The goal was to review current knowledge—and knowledge gaps—relating to a global environmental health problem, mercury contamination of the world’s marine fish. C-MERC participants attended two workshops over a two-year period, and in 2012 C-MERC authors published a series of peer-reviewed papers in the journals Environmental Health Perspectives and Environmental Research that elucidated key processes related to the inputs, cycling, and uptake of mercury in marine ecosystems, effects on human health, and policy implications. This report synthesizes the knowledge from these papers in an effort to summarize the science relevant to policies being considered at regional, national, and global levels. The Dartmouth Toxic Metals Superfund Research Program uses an interdisciplinary approach to investigate the ways that arsenic and mercury in the environment affect ecosystems and human health. Arsenic and mercury are commonly found in Superfund sites around the U.S. as well as other areas that result in exposures to certain communities. The Research Translation Core of the program communicates program science to government partners, non-governmental organizations, health care providers and associations, universities and the lay community, and facilitates the use of its research for the protection of public health. The Research Translation Core organized the C-MERC effort. The Superfund Research Program of the National Institute of Environmental Health Sciences supports a network of university programs that investigate the complex health and environmental issues associated with contaminants found at the nation’s hazardous waste sites. The Program coordinates with the Environmental Protection Agency and the Agency for Toxic Substances and Disease Registry of the Centers for Disease Control and Prevention, federal entities charged with management of environmental and human health hazards associated with toxic substances

A computational analysis of lower bounds for big bucket production planning problems

In this paper, we analyze a variety of approaches to obtain lower bounds for multi-level production planning problems with big bucket capacities, i.e., problems in which multiple items compete for the same resources. We give an extensive survey of both known and new methods, and also establish relationships between some of these methods that, to our knowledge, have not been presented before. As will be highlighted, understanding the substructures of difficult problems provide crucial insights on why these problems are hard to solve, and this is addressed by a thorough analysis in the paper. We conclude with computational results on a variety of widely used test sets, and a discussion of future research

The type III effector EspF coordinates membrane trafficking by the spatiotemporal activation of two eukaryotic signaling pathways

Bacterial toxins and effector proteins hijack eukaryotic enzymes that are spatially localized and display rapid signaling kinetics. However, the molecular mechanisms by which virulence factors engage highly dynamic substrates in the host cell environment are poorly understood. Here, we demonstrate that the enteropathogenic Escherichia coli (EPEC) type III effector protein EspF nucleates a multiprotein signaling complex composed of eukaryotic sorting nexin 9 (SNX9) and neuronal Wiskott-Aldrich syndrome protein (N-WASP). We demonstrate that a specific and high affinity association between EspF and SNX9 induces membrane remodeling in host cells. These membrane-remodeling events are directly coupled to N-WASP/Arp2/3–mediated actin nucleation. In addition to providing a biochemical mechanism of EspF function, we find that EspF dynamically localizes to membrane-trafficking organelles in a spatiotemporal pattern that correlates with SNX9 and N-WASP activity in living cells. Thus, our findings suggest that the EspF-dependent assembly of SNX9 and N-WASP represents a novel form of signaling mimicry used to promote EPEC pathogenesis and gastrointestinal disease