Supervised Random Walks: Predicting and Recommending Links in Social Networks

Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interactions among existing members are likely to occur in the near future or which existing interactions are we missing. Although this problem has been extensively studied, the challenge of how to effectively combine the information from the network structure with rich node and edge attribute data remains largely open. We develop an algorithm based on Supervised Random Walks that naturally combines the information from the network structure with node and edge level attributes. We achieve this by using these attributes to guide a random walk on the graph. We formulate a supervised learning task where the goal is to learn a function that assigns strengths to edges in the network such that a random walker is more likely to visit the nodes to which new links will be created in the future. We develop an efficient training algorithm to directly learn the edge strength estimation function. Our experiments on the Facebook social graph and large collaboration networks show that our approach outperforms state-of-the-art unsupervised approaches as well as approaches that are based on feature extraction

Electromagnetics from a quasistatic perspective

Quasistatics is introduced so that it fits smoothly into the standard textbook presentation of electrodynamics. The usual path from statics to general electrodynamics is rather short and surprisingly simple. A closer look reveals however that it is not without confusing issues as has been illustrated by many contributions to this Journal. Quasistatic theory is conceptually useful by providing an intermediate level in between statics and the full set of Maxwell's equations. Quasistatics is easier than general electrodynamics and in some ways more similar to statics. It is however, in terms of interesting physics and important applications, far richer than statics. Quasistatics is much used in electromagnetic modeling, an activity that today is possible on a PC and which also has great pedagogical potential. The use of electromagnetic simulations in teaching gives additional support for the importance of quasistatics. This activity may also motivate some change of focus in the presentation of basic electrodynamics

Flow graphs: interweaving dynamics and structure

The behavior of complex systems is determined not only by the topological organization of their interconnections but also by the dynamical processes taking place among their constituents. A faithful modeling of the dynamics is essential because different dynamical processes may be affected very differently by network topology. A full characterization of such systems thus requires a formalization that encompasses both aspects simultaneously, rather than relying only on the topological adjacency matrix. To achieve this, we introduce the concept of flow graphs, namely weighted networks where dynamical flows are embedded into the link weights. Flow graphs provide an integrated representation of the structure and dynamics of the system, which can then be analyzed with standard tools from network theory. Conversely, a structural network feature of our choice can also be used as the basis for the construction of a flow graph that will then encompass a dynamics biased by such a feature. We illustrate the ideas by focusing on the mathematical properties of generic linear processes on complex networks that can be represented as biased random walks and also explore their dual consensus dynamics.Comment: 4 pages, 1 figur

Economic Impact of a Ban on the Use of Over-the-Counter Antibiotics

Because antibiotic drugs are widely used in starter, grower, finishing, and sow feeds, a ban on their use would impact pork production processes and practices, and therefore would have an economic impact on the U.S. pork industry and pork market. This study considers the economic effects of a ban in pork production, with no change of regulation on other meats. The authors examine the evidence from a range of cases from Sweden to describe what is most likely to occur if a ban on antibiotic drugs in pork production were to be implemented in the United States

Comparative Raman Studies of Sr2RuO4, Sr3Ru2O7 and Sr4Ru3O10

The polarized Raman spectra of layered ruthenates of the Srn+1RunO3n+1 (n=1,2,3) Ruddlesden-Popper series were measured between 10 and 300 K. The phonon spectra of Sr3Ru2O7 and Sr4Ru3O10 confirmed earlier reports for correlated rotations of neighboring RuO6 octahedra within double or triple perovskite blocks. The observed Raman lines of Ag or B1g symmetry were assigned to particular atomic vibrations by considering the Raman modes in simplified structures with only one double or triple RuO6 layer per unit cell and by comparison to the predictions of lattice dynamical calculations for the real Pban and Pbam structures. Along with discrete phonon lines, a continuum scattering, presumably of electronic origin, is present in the zz, xx and xy, but not in the x'y' and zx spectra. Its interference with phonons results in Fano shape for some of the lines in the xx and xy spectra. The temperature dependencies of phonon parameters of Sr3Ru2O7 exhibit no anomaly between 10 and 300 K where no magnetic transition occurs. In contrast, two B1g lines in the spectra of Sr4Ru3O10, corresponding to oxygen vibrations modulating the Ru-O-Ru bond angle, show noticeable hardening with ferromagnetic ordering at 105 K, thus indicating strong spin-phonon interaction.Comment: 9 pages, 12 figure

Analytical reasoning task reveals limits of social learning in networks

Social learning -by observing and copying others- is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is our ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of lab-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions, and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an 'unreflective copying bias,' which limits their social learning to the output, rather than the process, of their peers' reasoning -even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behavior through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning

Novel Approach to Mass Tort Class Actions: The Billion Dollar Settlement in the Sulzer Artificial Hip and Knee Litigation: A Symposium

This is a transcript of a two hour symposium which deals with the Sulzer knee and hip replacement class action. A copy of the settlement is included as an appendix. The settlement in the U.S. District Court for the N.D. Ohio was unique and creative approach to resolving a mass tort class action. In a novel move, Sulzer agreed to open its books to an independent review firm to determine how much the firm could pay without going bankrupt. The number was $1 billion. As negotiated by the parties and approved by the court, the final settlement provides compensation for each member of the class based on a variety of factors, such as whether the member has undergone - or is likely to undergo - a revision to replace the defective part. Professor Susan Becker made the introductory remarks. The panel members were all involved in the Sulzer knee and hip replacement class action. R. Eric Kennedy served as lead plaintiffs\u27 counsel. The Honorable Kathleen McDonald O\u27Malley of the U.S. District Court for the Northern District of Ohio presided over the Sulzer class action litigation and settlement. Sidney A. Backstrom and Richard F. Scruggs were the defense counsel. James J. McMonagle served as the Claims Administrator overseeing distribution of the Sulzer class action settlement funds

Novel Approach to Mass Tort Class Actions: The Billion Dollar Settlement in the Sulzer Artificial Hip and Knee Litigation: A Symposium

This is a transcript of a two hour symposium which deals with the Sulzer knee and hip replacement class action. A copy of the settlement is included as an appendix. The settlement in the U.S. District Court for the N.D. Ohio was unique and creative approach to resolving a mass tort class action. In a novel move, Sulzer agreed to open its books to an independent review firm to determine how much the firm could pay without going bankrupt. The number was $1 billion. As negotiated by the parties and approved by the court, the final settlement provides compensation for each member of the class based on a variety of factors, such as whether the member has undergone - or is likely to undergo - a revision to replace the defective part. Professor Susan Becker made the introductory remarks. The panel members were all involved in the Sulzer knee and hip replacement class action. R. Eric Kennedy served as lead plaintiffs\u27 counsel. The Honorable Kathleen McDonald O\u27Malley of the U.S. District Court for the Northern District of Ohio presided over the Sulzer class action litigation and settlement. Sidney A. Backstrom and Richard F. Scruggs were the defense counsel. James J. McMonagle served as the Claims Administrator overseeing distribution of the Sulzer class action settlement funds

An efficient and principled method for detecting communities in networks

A fundamental problem in the analysis of network data is the detection of network communities, groups of densely interconnected nodes, which may be overlapping or disjoint. Here we describe a method for finding overlapping communities based on a principled statistical approach using generative network models. We show how the method can be implemented using a fast, closed-form expectation-maximization algorithm that allows us to analyze networks of millions of nodes in reasonable running times. We test the method both on real-world networks and on synthetic benchmarks and find that it gives results competitive with previous methods. We also show that the same approach can be used to extract nonoverlapping community divisions via a relaxation method, and demonstrate that the algorithm is competitively fast and accurate for the nonoverlapping problem.Comment: 14 pages, 5 figures, 1 tabl

Out of Florida: mtDNA reveals patterns of migration and Pleistocene range expansion of the Green Anole lizard (Anolis carolinensis)

Anolis carolinensis is an emerging model species and the sole member of its genus native to the United States. Considerable morphological and physiological variation has been described in the species, and the recent sequencing of its genome makes it an attractive system for studies of genome variation. To inform future studies of molecular and phenotypic variation within A. carolinensis, a rigorous account of intraspecific population structure and relatedness is needed. Here, we present the most extensive phylogeographic study of this species to date. Phylogenetic analyses of mitochondrial DNA sequence data support the previous hypothesis of a western Cuban origin of the species. We found five well-supported, geographically distinct mitochondrial haplotype clades throughout the southeastern United States. Most Florida populations fall into one of three divergent clades, whereas the vast majority of populations outside Florida belong to a single, shallowly diverged clade. Genetic boundaries do not correspond to major rivers, but may reflect effects of Pleistocene glaciation events and the Appalachian Mountains on migration and expansion of the species. Phylogeographic signal should be examined using nuclear loci to complement these findings.Organismic and Evolutionary Biolog