Efficient Implementation of a Synchronous Parallel Push-Relabel Algorithm

Motivated by the observation that FIFO-based push-relabel algorithms are able to outperform highest label-based variants on modern, large maximum flow problem instances, we introduce an efficient implementation of the algorithm that uses coarse-grained parallelism to avoid the problems of existing parallel approaches. We demonstrate good relative and absolute speedups of our algorithm on a set of large graph instances taken from real-world applications. On a modern 40-core machine, our parallel implementation outperforms existing sequential implementations by up to a factor of 12 and other parallel implementations by factors of up to 3

The Wild Turkey in South Dakota

This bulletin provides an extensive look at the wild turkey in South Dakota

Finding community structure in very large networks

The discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community, but most methods proposed so far are unsuitable for very large networks because of their computational cost. Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O(m d log n) where d is the depth of the dendrogram describing the community structure. Many real-world networks are sparse and hierarchical, with m ~ n and d ~ log n, in which case our algorithm runs in essentially linear time, O(n log^2 n). As an example of the application of this algorithm we use it to analyze a network of items for sale on the web-site of a large online retailer, items in the network being linked if they are frequently purchased by the same buyer. The network has more than 400,000 vertices and 2 million edges. We show that our algorithm can extract meaningful communities from this network, revealing large-scale patterns present in the purchasing habits of customers

Mallard Use of Elevated Nesting Structures: Fifteen Years of Management in Eastern South Dakota

Studies of mallard use and nesting success on elevated structures have generally been of a short-term nature. In this report we evaluated 15 consecutive years of mallard nesting on elevated structures (baskets, cylinders, and culverts) located over standing water in wetland basins in eastern South Dakota. Our objectives were to: 1) determine long-term trends in mallard occupancy and nest success in nesting baskets, cylinders, and culverts, 2) evaluate the effects of various nest structure adaptations for enhancing mallard use and maintaining high nest success rates, and 3) provide managers with various enhancement techniques for mallard nesting structures that have proven productive in this long-term management effort

Identifying network communities with a high resolution

Community structure is an important property of complex networks. An automatic discovery of such structure is a fundamental task in many disciplines, including sociology, biology, engineering, and computer science. Recently, several community discovery algorithms have been proposed based on the optimization of a quantity called modularity (Q). However, the problem of modularity optimization is NP-hard, and the existing approaches often suffer from prohibitively long running time or poor quality. Furthermore, it has been recently pointed out that algorithms based on optimizing Q will have a resolution limit, i.e., communities below a certain scale may not be detected. In this research, we first propose an efficient heuristic algorithm, Qcut, which combines spectral graph partitioning and local search to optimize Q. Using both synthetic and real networks, we show that Qcut can find higher modularities and is more scalable than the existing algorithms. Furthermore, using Qcut as an essential component, we propose a recursive algorithm, HQcut, to solve the resolution limit problem. We show that HQcut can successfully detect communities at a much finer scale and with a higher accuracy than the existing algorithms. Finally, we apply Qcut and HQcut to study a protein-protein interaction network, and show that the combination of the two algorithms can reveal interesting biological results that may be otherwise undetectable.Comment: 14 pages, 5 figures. 1 supplemental file at http://cic.cs.wustl.edu/qcut/supplemental.pd

Australia matters for America / America matters for Australia

For more about the East-West Center, see http://www.eastwestcenter.org/This publication covers the close ties that bind the United States and Australia and is a collaboration between the United States Studies Centre at the University of Sydney, the Perth US-Asia Centre at the University of Western Australia, and the East-West Center. Click here to see a full map of all congressional district exports to Australia

Community Structure of the Physical Review Citation Network

We investigate the community structure of physics subfields in the citation network of all Physical Review publications between 1893 and August 2007. We focus on well-cited publications (those receiving more than 100 citations), and apply modularity maximization to uncover major communities that correspond to clearly-identifiable subfields of physics. While most of the links between communities connect those with obvious intellectual overlap, there sometimes exist unexpected connections between disparate fields due to the development of a widely-applicable theoretical technique or by cross fertilization between theory and experiment. We also examine communities decade by decade and also uncover a small number of significant links between communities that are widely separated in time.Comment: 14 pages, 7 figures, 8 tables. Version 2: various small additions in response to referee comment

Upper and lower treeline biogeographic patterns in semi-arid pinyon-juniper woodlands

none7siAim: Upper and lower treelines are particularly exposed to a changing climate. It has been hypothesized that upper treelines are constrained by growing season temperature, whereas lower tree lines are water limited. We expect different causal mechanisms of upper versus lower tree line formation to generate distinct patterns of spatial heterogeneity. Here, we compare dynamics, spatial patterns and shape complexity of upper and lower tree lines of semi‐arid pinyon‐juniper woodlands. Location: Toiyabe Range of the Nevada Great Basin (western US). Taxon: Pinus monophylla Torr. & Frém. and Juniperus osteosperma (Torr.). Methods: Within 20 sample plots (10 along the upper and 10 along the lower tree line), we mapped tree canopies through photointerpretation of high‐resolution imagery. We performed point pattern analyses to compare the spatial arrangement of trees and used LANDSAT 30‐year time series and NDVI to understand the vegetation dynamics of these ecotones. We adopted the surface roughness method to measure tree line shape complexity. Results: Lower tree lines were denser and showed a stronger trend of increasing NDVI change over the 1984–2015 period. Trees at the lower tree line were more strongly aggregated than at the upper tree line at spatial scales ranging from 15 to 65 meters. Shape complexity was higher at upper tree lines, expressed by a higher mean surface roughness; however, the spatial structures of upper and lower tree lines were similar. Main conclusions: Upper tree line expansion of pinyon‐juniper woodlands in the study area has been limited and highly variable, but lower tree line downslope expansion into adjacent shrub steppe vegetation was evident. The expected difference between energy‐ and water‐limited tree lines did not manifest in the observed spatial structures. Differences in tree line shape complexity were not significant, although lower tree lines exhibited less complex shapes, likely because they have been more strongly influenced by anthropogenic factors.The datasets generated and analysed during the current study are available in the Figshare repository, https://doi.org/10.6084/m9.figshare.11836284mixedGarbarino, Matteo; Malandra, Francesco; Dilts, Thomas; Flake, Sam; Montalto, Luigi; Spinsante, Susanna; Weisberg, Peter J.Garbarino, Matteo; Malandra, Francesco; Dilts, Thomas; Flake, Sam; Montalto, Luigi; Spinsante, Susanna; Weisberg, Peter J