Worldsheet Instanton Corrections to the Kaluza-Klein Monopole

The Kaluza-Klein monopole is a well known object in both gravity and string theory, related by T-duality to a "smeared" NS5-brane which retains the isometry around the duality circle. As the true NS5-brane solution is localized at a point on the circle, duality implies that the Kaluza-Klein monopole should show some corresponding behavior. In this paper, we express the Kaluza-Klein monopole as a gauged linear sigma model in two dimensions and show that worldsheet instantons give corrections to its geometry. These corrections can be understood as a localization in "winding space" which could be probed by strings with winding charge around the circle.Comment: 20 pages, REVTeX, v2: minor equation correctio

The Influence of Federal Laboratory R&D on Industrial Research

Over the past 60 years the United States has created the world's largest system of government laboratories. The impact of the laboratories on the private economy has been little studied though their research accounts for 14% of total U.S. R&D, more than the R&D of all colleges and universities combined. In this paper we study the influence of federal laboratory R&D on industrial research using a sample of industrial laboratories. In head-to-head comparisons with alternative measures, we find that Cooperative Research and Development Agreements or CRADAs, are the primary channel by which federal laboratories increase the patenting and R&D of industrial laboratories. With a CRADA industrial laboratories patent more, spend more on company-financed R&D and spend more of their own money on federal laboratories. Without a CRADA patenting stays about the same and only federally funded R&D increases, mostly because of direct subsidies by government. These results are consistent with the literature on endogenous R&D spillovers, which emphasizes that knowledge spills over when recipients work at making it spill over. CRADAs are legal agreements between federal laboratories and firms to work together on joint research. They are backed by real budgets and accompanied by cost sharing that could bind the parties together in joint research. Moreover, the CRADA instrument is the main form of such agreements. Thus, both in theory and in fact CRADAs may be more beneficial to firms than other public- private interactions, precisely because of the mutual effort that they require of firms and government laboratories.

The Influence of Federal Laboratory R&D on Industrial Research

This paper studies the influence of R&D in the federal laboratory system, the world's largest, on firm research. Our results are based on a sample of 220 industrial research laboratories that work with a variety of federal laboratories and agencies and are owned by 115 firms in the chemicals, machinery, electrical equipment, and motor vehicles industries. Using an indicator of their importance to R&D managers, we find that Cooperative Research and Development Agreements or CRADAs dominate other channels of technology transfer from federal laboratories to firms. With a CRADA industry laboratories patent more, spend more on company-financed R&D, and devote more resources to their federal counterparts. Without this influence patenting stays about the same, and only federally funded R&D increases, mostly because of government support. The Stevenson-Wydler Act and amendments during the 1980s introduced CRADAs, which legally bind federal laboratories and firms together in joint research. In theory the agreements could capitalize on complementarities between public and private research. Our results support this perspective and suggest that CRADAs may be more beneficial to firms than other interactions with federal laboratories, precisely because of the mutual effort that they demand from both parties.

How can we resolve Lewontin's Paradox?

We discuss the genetic, demographic, and selective forces that are likely to be at play in restricting observed levels of DNA sequence variation in natural populations to a much smaller range of values than would be expected from the distribution of census population sizes alone—Lewontin’s Paradox. While several processes that have previously been strongly emphasized must be involved, including the effects of direct selection and genetic hitchhiking, it seems unlikely that they are sufficient to explain this observation without contributions from other factors. We highlight a potentially important role for the less-appreciated contribution of population size change; specifically, the likelihood that many species and populations may be quite far from reaching the relatively high equilibrium diversity values that would be expected given their current census sizes

Evaluating the ability of the pairwise joint site frequency spectrum to co-estimate selection and demography

The ability to infer the parameters of positive selection from genomic data has many important implications, from identifying drug-resistance mutations in viruses to increasing crop yield by genetically integrating favorable alleles. Although it has been well-described that selection and demography may result in similar patterns of diversity, the ability to jointly estimate these two processes has remained elusive. Here we use simulation to explore the utility of the joint site frequency spectrum to estimate selection and demography simultaneously, including developing an extension of the previously proposed Jaatha program (Mathew et al., 2013). We evaluate both complete and incomplete selective sweeps under an isolation-with-migration model with and without population size change (both population growth and bottlenecks). Results suggest that while it may not be possible to precisely estimate the strength of selection, it is possible to infer the presence of selection while estimating accurate demographic parameters. We further demonstrate that the common assumption of selective neutrality when estimating demographic models may lead to severe biases. Finally, we apply the approach we have developed to better characterize the within-host demographic and selective history of human cytomegalovirus (HCMV) infection using published next generation sequencing data

WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data

With novel developments in sequencing technologies, time-sampled data are becoming more available and accessible. Naturally, there have been efforts in parallel to infer population genetic parameters from these datasets. Here, we compare and analyze four recent approaches based on the Wright-Fisher model for inferring selection coefficients (s) given effective population size (Ne), with simulated temporal datasets. Furthermore, we demonstrate the advantage of a recently proposed ABC-based method that is able to correctly infer genome-wide average Ne from time-serial data, which is then set as a prior for inferring per-site selection coefficients accurately and precisely. We implement this ABC method in a new software and apply it to a classical time-serial dataset of the medionigra genotype in the moth Panaxia dominula. We show that a recessive lethal model is the best explanation for the observed variation in allele frequency by implementing an estimator of the dominance ratio (h)

On Detecting Selective Sweeps Using Single Genomes

Identifying the genetic basis of human adaptation has remained a central focal point of modern population genetics. One major area of interest has been the use of polymorphism data to detect so-called “footprints” of selective sweeps – patterns produced as a beneficial mutation arises and rapidly fixes in the population. Based on numerous simulation studies and power analyses, the necessary sample size for achieving appreciable power has been shown to vary from a few individuals to a few dozen, depending on the test statistic. And yet, the sequencing of multiple copies of a single region, or of multiple genomes as is now often the case, incurs considerable cost. Enard et al. (2010) have recently proposed a method to identify patterns of selective sweeps using a single genome – and apply this approach to human and non-human primates (chimpanzee, orangutan, and macaque). They employ essentially a modification of the Hudson, Kreitman, and Aguade test – using heterozygous single nucleotide polymorphisms from single individuals, and divergence data from two closely related species (human–chimpanzee, human–orangutan, and human–macaque). Given the potential importance of this finding, we here investigate the properties of this statistic. We demonstrate through simulation that this approach is neither robust to demography nor background selection; nor is it robust to variable recombination rates