Two-speed deflection system for electron micropattern generator

Development of dual speed deflection system for electron beam micropattern generator system is discussed. Factors affecting application of electron beam lithography are analyzed. Procedure for using two speed deflection system is described

Dual field alignment display and control for electron micropattern generator

Application of electron beam lithography to replace photolithography process in fabrication of integrated circuits is discussed. Procedure for using electron beam lithography equipment is described. Diagram of electron micropattern generator is provided

EMon : embodied monitorization

Serie : Lecture Notes in Computer Science, vol. 5859The amount of seniors in need of constant care is rapidly rising: an evident consequence of population ageing. There are already some monitorization environments which aim to monitor these persons while they remain at home. This, however, although better than delocalizing the elder to some kind of institution, may not still be the ideal solution, as it forces them to stay inside the home more than they wished, as going out means lack of accompaniment and a consequent sensation of fear. In this paper we propose EMon: a monitorization device small enough to be worn by its users, although powerful enough to provide the higher level monitorization systems with vital information about the user and the environment around him. We hope to allow the representation of an intelligent environment to move with its users, instead of being static, mandatorily associated to a single physical location. The first prototype of EMon, as presented in this paper, provides environmental data as well as GPS coordinates and pictures that are useful to describe the context of its user

A Method to Polarize Stored Antiprotons to a High Degree

Polarized antiprotons can be produced in a storage ring by spin--dependent interaction in a purely electron--polarized hydrogen gas target. The polarizing process is based on spin transfer from the polarized electrons of the target atoms to the orbiting antiprotons. After spin filtering for about two beam lifetimes at energies $T\approx 40-170$ MeV using a dedicated large acceptance ring, the antiproton beam polarization would reach $P=0.2-0.4$. Polarized antiprotons would open new and unique research opportunities for spin--physics experiments in $\bar{p}p$ interactions

Measurement of bronchial hyperreactivity : comparison of three Nordic dosimetric methods

Clinical testing of bronchial hyperreactivity (BHR) provides valuable information in asthma diagnostics. Nevertheless, the test results depend to a great extent on the testing procedure: test substance, apparatus and protocol. In Nordic countries, three protocols predominate in the testing field: Per Malmberg, Nieminen and Sovijarvi methods. However, knowledge of their equivalence is limited. We aimed to find equivalent provocative doses (PD) to obtain similar bronchoconstrictive responses for the three protocols. We recruited 31 patients with suspected asthma and health care workers and performed BHR testing with methacholine according to Malmberg and Nieminen methods, and with histamine according to Sovijarvi. We obtained the individual response-dose slopes for each method and predicted equivalent PD values. Applying a mixed-model, we found significant differences in the mean (standard error of mean) response-dose (forced expiratory volume in one second (FEV1)%/mg): Sovijarvi 7.2 (1.5), Nieminen 13.8 (4.2) and Malmberg 26 (7.3). We found that the earlier reported cut-point values for moderate BHR and marked BHR between the Sovijarvi (PD15) and Nieminen (PD20) methods were similar, but with the Malmberg method a significant bronchoconstrictive reaction was measured with lower PD20 values. We obtained a relationship between slope values and PD (mg) between different methods, useful in epidemiological research and clinical practice.Peer reviewe

Is our Sun a Singleton?

Most stars are formed in a cluster or association, where the number density of stars can be high. This means that a large fraction of initially-single stars will undergo close encounters with other stars and/or exchange into binaries. We describe how such close encounters and exchange encounters can affect the properties of a planetary system around a single star. We define a singleton as a single star which has never suffered close encounters with other stars or spent time within a binary system. It may be that planetary systems similar to our own solar system can only survive around singletons. Close encounters or the presence of a stellar companion will perturb the planetary system, often leaving planets on tighter and more eccentric orbits. Thus planetary systems which initially resembled our own solar system may later more closely resemble some of the observed exoplanet systems.Comment: 2 pages, 1 figure. To be published in the proceedings of IAUS246 "Dynamical Evolution of Dense Stellar Systems". Editors: E. Vesperini (Chief Editor), M. Giersz, A. Sill

Validity of the Central Sensitization Inventory to Address Human Assumed Central Sensitization:Newly Proposed Clinically Relevant Values and Associations

Central sensitization cannot be directly demonstrated in humans and thus a gold standard is missing. Therefore, we used human assumed central sensitization (HACS) when associated with humans. The central sensitization inventory (CSI) is a screening questionnaire for addressing symptoms that are associated with HACS. This cross-sectional study compared patients with chronic pain and at least one central sensitivity syndrome with healthy, pain-free controls via ROC analyses. Analyses were performed for all participants together and for each sex separately. Regression analyses were performed on patients with chronic pain with and without central sensitivity syndromes. Based on 1730 patients and 250 healthy controls, cutoff values for the CSI for the total group were established at 30 points: women: 33 points; men: 25 points. Univariate and multivariate regression analyses were used to identify possible predictors for the CSI score in 2890 patients with chronic pain. The CSI score is associated with all independent factors and has a low association with pain severity in women and a low association with pain severity, age, and body mass index in men. The newly established CSI cutoff values are lower than in previous studies and different per sex, which might be of clinical relevance in daily practice and importance in research.</p

Universal Rights and Wrongs

This paper argues for the important role of customers as a source of competitive advantage and firm growth, an issue which has been largely neglected in the resource-based view of the firm. It conceptualizes Penrose’s (1959) notion of an ‘inside track’ and illustrates how in-depth knowledge about established customers combines with joint problem-solving activities and the rapid assimilation of new and previously unexploited skills and resources. It is suggested that the inside track represents a distinct and perhaps underestimated way of generating rents and securing long-term growth. This also implies that the sources of sustainable competitive advantage in important respects can be sought in idiosyncratic interfirm relationships rather than within the firm itself

Against all odds? Forming the planet of the HD196885 binary

HD196885Ab is the most "extreme" planet-in-a-binary discovered to date, whose orbit places it at the limit for orbital stability. The presence of a planet in such a highly perturbed region poses a clear challenge to planet-formation scenarios. We investigate this issue by focusing on the planet-formation stage that is arguably the most sensitive to binary perturbations: the mutual accretion of kilometre-sized planetesimals. To this effect we numerically estimate the impact velocities $dv$ amongst a population of circumprimary planetesimals. We find that most of the circumprimary disc is strongly hostile to planetesimal accretion, especially the region around 2.6AU (the planet's location) where binary perturbations induce planetesimal-shattering $dv$ of more than 1km/s. Possible solutions to the paradox of having a planet in such accretion-hostile regions are 1) that initial planetesimals were very big, at least 250km, 2) that the binary had an initial orbit at least twice the present one, and was later compacted due to early stellar encounters, 3) that planetesimals did not grow by mutual impacts but by sweeping of dust (the "snowball" growth mode identified by Xie et al., 2010b), or 4) that HD196885Ab was formed not by core-accretion but by the concurent disc instability mechanism. All of these 4 scenarios remain however highly conjectural.Comment: accepted for publication by Celestial Mechanics and Dynamical Astronomy (Special issue on EXOPLANETS

The causes of epistasis

[EN] Since Bateson's discovery that genes can suppress the phenotypic effects of other genes, gene interactions-called epistasis-have been the topic of a vast research effort. Systems and developmental biologists study epistasis to understand the genotype-phenotype map, whereas evolutionary biologists recognize the fundamental importance of epistasis for evolution. Depending on its form, epistasis may lead to divergence and speciation, provide evolutionary benefits to sex and affect the robustness and evolvability of organisms. That epistasis can itself be shaped by evolution has only recently been realized. Here, we review the empirical pattern of epistasis, and some of the factors that may affect the form and extent of epistasis. Based on their divergent consequences, we distinguish between interactions with or without mean effect, and those affecting the magnitude of fitness effects or their sign. Empirical work has begun to quantify epistasis in multiple dimensions in the context of metabolic and fitness landscape models. We discuss possible proximate causes (such as protein function and metabolic networks) and ultimate factors (including mutation, recombination, and the importance of natural selection and genetic drift). We conclude that, in general, pleiotropy is an important prerequisite for epistasis, and that epistasis may evolve as an adaptive or intrinsic consequence of changes in genetic robustness and evolvability.We thank Fons Debets, Ryszard Korona, Alexey Kondrashov, Joachim Krug, Sijmen Schoustra and an anonymous reviewer for constructive comments, and funds from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 225167 (eFLUX), a visitor grant from Research School Production Ecology and Resource Conservation for S.F.E., and NSF grant DEB-0844355 for T.F.C.De Visser, JAGM.; Cooper, TF.; Elena Fito, SF. (2011). The causes of epistasis. Proceedings of the Royal Society B: Biological Sciences. 278(1725):3617-3624. https://doi.org/10.1098/rspb.2011.1537S361736242781725Costanzo, M., Baryshnikova, A., Bellay, J., Kim, Y., Spear, E. D., Sevier, C. S., … Mostafavi, S. (2010). The Genetic Landscape of a Cell. Science, 327(5964), 425-431. doi:10.1126/science.1180823Moore, J. H., & Williams, S. M. (2005). Traversing the conceptual divide between biological and statistical epistasis: systems biology and a more modern synthesis. BioEssays, 27(6), 637-646. doi:10.1002/bies.20236Phillips, P. C. (2008). Epistasis — the essential role of gene interactions in the structure and evolution of genetic systems. Nature Reviews Genetics, 9(11), 855-867. doi:10.1038/nrg2452Azevedo, R. B. R., Lohaus, R., Srinivasan, S., Dang, K. K., & Burch, C. L. (2006). Sexual reproduction selects for robustness and negative epistasis in artificial gene networks. Nature, 440(7080), 87-90. doi:10.1038/nature04488Desai, M. M., Weissman, D., & Feldman, M. W. (2007). Evolution Can Favor Antagonistic Epistasis. Genetics, 177(2), 1001-1010. doi:10.1534/genetics.107.075812Gros, P.-A., Le Nagard, H., & Tenaillon, O. (2009). The Evolution of Epistasis and Its Links With Genetic Robustness, Complexity and Drift in a Phenotypic Model of Adaptation. Genetics, 182(1), 277-293. doi:10.1534/genetics.108.099127Liberman, U., & Feldman, M. (2008). On the evolution of epistasis III: The haploid case with mutation. Theoretical Population Biology, 73(2), 307-316. doi:10.1016/j.tpb.2007.11.010Liberman, U., & Feldman, M. W. (2005). On the evolution of epistasis I: diploids under selection. Theoretical Population Biology, 67(3), 141-160. doi:10.1016/j.tpb.2004.11.001Liberman, U., Puniyani, A., & Feldman, M. W. (2007). On the evolution of epistasis II: A generalized Wright–Kimura framework. Theoretical Population Biology, 71(2), 230-238. doi:10.1016/j.tpb.2006.10.002Martin, O. C., & Wagner, A. (2009). Effects of Recombination on Complex Regulatory Circuits. Genetics, 183(2), 673-684. doi:10.1534/genetics.109.104174Misevic, D., Ofria, C., & Lenski, R. E. (2005). Sexual reproduction reshapes the genetic architecture of digital organisms. Proceedings of the Royal Society B: Biological Sciences, 273(1585), 457-464. doi:10.1098/rspb.2005.3338Bateson W. Saunders E. R. Punnett R. C.& Hurst C. C.. 1905 Reports to the Evolution Committee of the Royal Society Report II. London UK: Harrison and Sons.Fisher, R. A. (1919). XV.—The Correlation between Relatives on the Supposition of Mendelian Inheritance. Transactions of the Royal Society of Edinburgh, 52(2), 399-433. doi:10.1017/s0080456800012163Kondrashov, F. A., & Kondrashov, A. S. (2001). Multidimensional epistasis and the disadvantage of sex. Proceedings of the National Academy of Sciences, 98(21), 12089-12092. doi:10.1073/pnas.211214298Barton, N. H. (1995). A general model for the evolution of recombination. Genetical Research, 65(2), 123-144. doi:10.1017/s0016672300033140Kondrashov, A. S. (1988). Deleterious mutations and the evolution of sexual reproduction. Nature, 336(6198), 435-440. doi:10.1038/336435a0De Visser, J. A. G. M., & Elena, S. F. (2007). The evolution of sex: empirical insights into the roles of epistasis and drift. Nature Reviews Genetics, 8(2), 139-149. doi:10.1038/nrg1985Kouyos, R. D., Silander, O. K., & Bonhoeffer, S. (2007). Epistasis between deleterious mutations and the evolution of recombination. Trends in Ecology & Evolution, 22(6), 308-315. doi:10.1016/j.tree.2007.02.014The effect of sex and deleterious mutations on fitness in Chlamydomonas. (1996). Proceedings of the Royal Society of London. Series B: Biological Sciences, 263(1367), 193-200. doi:10.1098/rspb.1996.0031Salathe, P., & Ebert, D. (2003). The effects of parasitism and inbreeding on the competitive ability in Daphnia magna: evidence for synergistic epistasis. Journal of Evolutionary Biology, 16(5), 976-985. doi:10.1046/j.1420-9101.2003.00582.xJasnos, L., & Korona, R. (2007). Epistatic buffering of fitness loss in yeast double deletion strains. Nature Genetics, 39(4), 550-554. doi:10.1038/ng1986Lenski, R. E., Ofria, C., Collier, T. C., & Adami, C. (1999). Genome complexity, robustness and genetic interactions in digital organisms. Nature, 400(6745), 661-664. doi:10.1038/23245Maisnier-Patin, S., Roth, J. R., Fredriksson, Å., Nyström, T., Berg, O. G., & Andersson, D. I. (2005). Genomic buffering mitigates the effects of deleterious mutations in bacteria. Nature Genetics, 37(12), 1376-1379. doi:10.1038/ng1676Sanjuan, R., Moya, A., & Elena, S. F. (2004). The contribution of epistasis to the architecture of fitness in an RNA virus. Proceedings of the National Academy of Sciences, 101(43), 15376-15379. doi:10.1073/pnas.0404125101Zeyl, C. (2005). The Number of Mutations Selected During Adaptation in a Laboratory Population of Saccharomyces cerevisiae. Genetics, 169(4), 1825-1831. doi:10.1534/genetics.104.027102Peña, M. de la, Elena, S. F., & Moya, A. (2000). EFFECT OF DELETERIOUS MUTATION-ACCUMULATION ON THE FITNESS OF RNA BACTERIOPHAGE MS2. Evolution, 54(2), 686. doi:10.1554/0014-3820(2000)054[0686:eodmao]2.0.co;2De Visser, J. A. G. M., Hoekstra, R. F., & van den Ende, H. (1997). Test of Interaction Between Genetic Markers That Affect Fitness in Aspergillus niger. Evolution, 51(5), 1499. doi:10.2307/2411202Elena, S. F. (1999). Little Evidence for Synergism Among Deleterious Mutations in a Nonsegmented RNA Virus. Journal of Molecular Evolution, 49(5), 703-707. doi:10.1007/pl00000082Elena, S. F., & Lenski, R. E. (1997). Test of synergistic interactions among deleterious mutations in bacteria. Nature, 390(6658), 395-398. doi:10.1038/37108Hall, D. W., Agan, M., & Pope, S. C. (2010). Fitness Epistasis among 6 Biosynthetic Loci in the Budding Yeast Saccharomyces cerevisiae. Journal of Heredity, 101(Supplement 1), S75-S84. doi:10.1093/jhered/esq007Kelly, J. K. (2005). Epistasis in Monkeyflowers. Genetics, 171(4), 1917-1931. doi:10.1534/genetics.105.041525Segrè, D., DeLuna, A., Church, G. M., & Kishony, R. (2004). Modular epistasis in yeast metabolism. Nature Genetics, 37(1), 77-83. doi:10.1038/ng1489He, X., Qian, W., Wang, Z., Li, Y., & Zhang, J. (2010). Prevalent positive epistasis in Escherichia coli and Saccharomyces cerevisiae metabolic networks. Nature Genetics, 42(3), 272-276. doi:10.1038/ng.524Carneiro, M., & Hartl, D. L. (2009). Adaptive landscapes and protein evolution. Proceedings of the National Academy of Sciences, 107(suppl_1), 1747-1751. doi:10.1073/pnas.0906192106Franke, J., Klözer, A., de Visser, J. A. G. M., & Krug, J. (2011). Evolutionary Accessibility of Mutational Pathways. PLoS Computational Biology, 7(8), e1002134. doi:10.1371/journal.pcbi.1002134Weinreich, D. M. (2006). Darwinian Evolution Can Follow Only Very Few Mutational Paths to Fitter Proteins. Science, 312(5770), 111-114. doi:10.1126/science.1123539Lunzer, M. (2005). The Biochemical Architecture of an Ancient Adaptive Landscape. Science, 310(5747), 499-501. doi:10.1126/science.1115649O’Maille, P. E., Malone, A., Dellas, N., Andes Hess, B., Smentek, L., Sheehan, I., … Noel, J. P. (2008). Quantitative exploration of the catalytic landscape separating divergent plant sesquiterpene synthases. Nature Chemical Biology, 4(10), 617-623. doi:10.1038/nchembio.113Lozovsky, E. R., Chookajorn, T., Brown, K. M., Imwong, M., Shaw, P. J., Kamchonwongpaisan, S., … Hartl, D. L. (2009). Stepwise acquisition of pyrimethamine resistance in the malaria parasite. Proceedings of the National Academy of Sciences, 106(29), 12025-12030. doi:10.1073/pnas.0905922106De Visser, J. A. G. M., Park, S., & Krug, J. (2009). Exploring the Effect of Sex on Empirical Fitness Landscapes. The American Naturalist, 174(S1), S15-S30. doi:10.1086/599081Khan, A. I., Dinh, D. M., Schneider, D., Lenski, R. E., & Cooper, T. F. (2011). Negative Epistasis Between Beneficial Mutations in an Evolving Bacterial Population. Science, 332(6034), 1193-1196. doi:10.1126/science.1203801Chou, H.-H., Chiu, H.-C., Delaney, N. F., Segre, D., & Marx, C. J. (2011). Diminishing Returns Epistasis Among Beneficial Mutations Decelerates Adaptation. Science, 332(6034), 1190-1192. doi:10.1126/science.1203799Da Silva, J., Coetzer, M., Nedellec, R., Pastore, C., & Mosier, D. E. (2010). Fitness Epistasis and Constraints on Adaptation in a Human Immunodeficiency Virus Type 1 Protein Region. Genetics, 185(1), 293-303. doi:10.1534/genetics.109.112458Hinkley, T., Martins, J., Chappey, C., Haddad, M., Stawiski, E., Whitcomb, J. M., … Bonhoeffer, S. (2011). A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase. Nature Genetics, 43(5), 487-489. doi:10.1038/ng.795Kvitek, D. J., & Sherlock, G. (2011). Reciprocal Sign Epistasis between Frequently Experimentally Evolved Adaptive Mutations Causes a Rugged Fitness Landscape. PLoS Genetics, 7(4), e1002056. doi:10.1371/journal.pgen.1002056MacLean, R. C., Perron, G. G., & Gardner, A. (2010). Diminishing Returns From Beneficial Mutations and Pervasive Epistasis Shape the Fitness Landscape for Rifampicin Resistance in Pseudomonas aeruginosa. Genetics, 186(4), 1345-1354. doi:10.1534/genetics.110.123083Rokyta, D. R., Joyce, P., Caudle, S. B., Miller, C., Beisel, C. J., & Wichman, H. A. (2011). Epistasis between Beneficial Mutations and the Phenotype-to-Fitness Map for a ssDNA Virus. PLoS Genetics, 7(6), e1002075. doi:10.1371/journal.pgen.1002075Salverda, M. L. M., Dellus, E., Gorter, F. A., Debets, A. J. M., van der Oost, J., Hoekstra, R. F., … de Visser, J. A. G. M. (2011). Initial Mutations Direct Alternative Pathways of Protein Evolution. PLoS Genetics, 7(3), e1001321. doi:10.1371/journal.pgen.1001321Hayashi, Y., Aita, T., Toyota, H., Husimi, Y., Urabe, I., & Yomo, T. (2006). Experimental Rugged Fitness Landscape in Protein Sequence Space. PLoS ONE, 1(1), e96. doi:10.1371/journal.pone.0000096De Visser, J. A. G., & Lenski, R. E. (2002). BMC Evolutionary Biology, 2(1), 19. doi:10.1186/1471-2148-2-19Kryazhimskiy, S., Tkacik, G., & Plotkin, J. B. (2009). The dynamics of adaptation on correlated fitness landscapes. Proceedings of the National Academy of Sciences, 106(44), 18638-18643. doi:10.1073/pnas.0905497106Lehner, B. (2011). Molecular mechanisms of epistasis within and between genes. Trends in Genetics, 27(8), 323-331. doi:10.1016/j.tig.2011.05.007Feist, A. M., Henry, C. S., Reed, J. L., Krummenacker, M., Joyce, A. R., Karp, P. D., … Palsson, B. Ø. (2007). A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Molecular Systems Biology, 3(1), 121. doi:10.1038/msb4100155Szappanos, B., Kovács, K., Szamecz, B., Honti, F., Costanzo, M., Baryshnikova, A., … Papp, B. (2011). An integrated approach to characterize genetic interaction networks in yeast metabolism. Nature Genetics, 43(7), 656-662. doi:10.1038/ng.846Dean, A. M., Dykhuizen, D. E., & Hartl, D. L. (1986). Fitness as a function of β-galactosidase activity in Escherichia coli. Genetical Research, 48(1), 1-8. doi:10.1017/s0016672300024587Trindade, S., Sousa, A., Xavier, K. B., Dionisio, F., Ferreira, M. G., & Gordo, I. (2009). Positive Epistasis Drives the Acquisition of Multidrug Resistance. PLoS Genetics, 5(7), e1000578. doi:10.1371/journal.pgen.1000578Agrawal, A. F., & Whitlock, M. C. (2010). Environmental duress and epistasis: how does stress affect the strength of selection on new mutations? Trends in Ecology & Evolution, 25(8), 450-458. doi:10.1016/j.tree.2010.05.003Bonhoeffer, S. (2004). Evidence for Positive Epistasis in HIV-1. Science, 306(5701), 1547-1550. doi:10.1126/science.1101786Burch, C. L., & Chao, L. (2004). Epistasis and Its Relationship to Canalization in the RNA Virus φ6. Genetics, 167(2), 559-567. doi:10.1534/genetics.103.021196Martin, G., Elena, S. F., & Lenormand, T. (2007). Distributions of epistasis in microbes fit predictions from a fitness landscape model. Nature Genetics, 39(4), 555-560. doi:10.1038/ng1998DePristo, M. A., Weinreich, D. M., & Hartl, D. L. (2005). Missense meanderings in sequence space: a biophysical view of protein evolution. Nature Reviews Genetics, 6(9), 678-687. doi:10.1038/nrg1672Wang, X., Minasov, G., & Shoichet, B. K. (2002). Evolution of an Antibiotic Resistance Enzyme Constrained by Stability and Activity Trade-offs. Journal of Molecular Biology, 320(1), 85-95. doi:10.1016/s0022-2836(02)00400-xBj&ouml;rkman, J. (2000). Effects of Environment on Compensatory Mutations to Ameliorate Costs of Antibiotic Resistance. Science, 287(5457), 1479-1482. doi:10.1126/science.287.5457.1479Lenski, R. E. (1988). Experimental Studies of Pleiotropy and Epistasis in Escherichia coli. II. Compensation for Maldaptive Effects Associated with Resistance to Virus T4. Evolution, 42(3), 433. doi:10.2307/2409029Schoustra, S. E., Debets, A. J. M., Slakhorst, M., & Hoekstra, R. F. (2007). Mitotic Recombination Accelerates Adaptation in the Fungus Aspergillus nidulans. PLoS Genetics, 3(4), e68. doi:10.1371/journal.pgen.0030068MacLean, R. C., Bell, G., & Rainey, P. B. (2004). The evolution of a pleiotropic fitness tradeoff in Pseudomonas fluorescens. Proceedings of the National Academy of Sciences, 101(21), 8072-8077. doi:10.1073/pnas.0307195101Cooper, T. F., Ostrowski, E. A., & Travisano, M. (2007). A NEGATIVE RELATIONSHIP BETWEEN MUTATION PLEIOTROPY AND FITNESS EFFECT IN YEAST. Evolution, 61(6), 1495-1499. doi:10.1111/j.1558-5646.2007.00109.xPoon, A., & Chao, L. (2005). The Rate of Compensatory Mutation in the DNA Bacteriophage φX174. Genetics, 170(3), 989-999. doi:10.1534/genetics.104.039438Remold, S. K., & Lenski, R. E. (2004). Pervasive joint influence of epistasis and plasticity on mutational effects in Escherichia coli. Nature Genetics, 36(4), 423-426. doi:10.1038/ng1324Crow, J. F., & Kimura, M. (1979). Efficiency of truncation selection. Proceedings of the National Academy of Sciences, 76(1), 396-399. doi:10.1073/pnas.76.1.396Hamilton, W. D., Axelrod, R., & Tanese, R. (1990). Sexual reproduction as an adaptation to resist parasites (a review). Proceedings of the National Academy of Sciences, 87(9), 3566-3573. doi:10.1073/pnas.87.9.3566Jasnos, L., Tomala, K., Paczesniak, D., & Korona, R. (2008). Interactions Between Stressful Environment and Gene Deletions Alleviate the Expected Average Loss of Fitness in Yeast. Genetics, 178(4), 2105-2111. doi:10.1534/genetics.107.084533Kishony, R., & Leibler, S. (2003). Journal of Biology, 2(2), 14. doi:10.1186/1475-4924-2-14Yeh, P. J., Hegreness, M. J., Aiden, A. P., & Kishony, R. (2009). Drug interactions and the evolution of antibiotic resistance. Nature Reviews Microbiology, 7(6), 460-466. doi:10.1038/nrmicro2133Cooper, T. F., & Lenski, R. E. (2010). Experimental evolution with E. coli in diverse resource environments. I. Fluctuating environments promote divergence of replicate populations. BMC Evolutionary Biology, 10(1), 11. doi:10.1186/1471-2148-10-11Korona, R., Nakatsu, C. H., Forney, L. J., & Lenski, R. E. (1994). Evidence for multiple adaptive peaks from populations of bacteria evolving in a structured habitat. Proceedings of the National Academy of Sciences, 91(19), 9037-9041. doi:10.1073/pnas.91.19.9037Rozen, D. E., Habets, M. G. J. L., Handel, A., & de Visser, J. A. G. M. (2008). Heterogeneous Adaptive Trajectories of Small Populations on Complex Fitness Landscapes. PLoS ONE, 3(3), e1715. doi:10.1371/journal.pone.0001715Kashtan, N., & Alon, U. (2005). Spontaneous evolution of modularity and network motifs. Proceedings of the National Academy of Sciences, 102(39), 13773-13778. doi:10.1073/pnas.0503610102De Visser, J. A. G. M., Hermisson, J., Wagner, G. P., Meyers, L. A., Bagheri-Chaichian, H., Blanchard, J. L., … Whitlock, M. C. (2003). PERSPECTIVE:EVOLUTION AND DETECTION OF GENETIC ROBUSTNESS. Evolution, 57(9), 1959. doi:10.1554/02-750rWilke, C. O., & Christoph, A. (2001). Interaction between directional epistasis and average mutational effects. Proceedings of the Royal Society of London. Series B: Biological Sciences, 268(1475), 1469-1474. doi:10.1098/rspb.2001.1690Sanjuan, R., & Elena, S. F. (2006). Epistasis correlates to genomic complexity. Proceedings of the National Academy of Sciences, 103(39), 14402-14405. doi:10.1073/pnas.0604543103Sanjuán, R., & Nebot, M. R. (2008). A Network Model for the Correlation between Epistasis and Genomic Complexity. PLoS ONE, 3(7), e2663. doi:10.1371/journal.pone.0002663Lynch, M., & Conery, J. S. (2003). The Origins of Genome Complexity. Science, 302(5649), 1401-1404. doi:10.1126/science.1089370Wilke, C. O., Wang, J. L., Ofria, C., Lenski, R. E., & Adami, C. (2001). Evolution of digital organisms at high mutation rates leads to survival of the flattest. Nature, 412(6844), 331-333. doi:10.1038/35085569Weinreich, D. M., & Chao, L. (2005). RAPID EVOLUTIONARY ESCAPE BY LARGE POPULATIONS FROM LOCAL FITNESS PEAKS IS LIKELY IN NATURE. Evolution, 59(6), 1175-1182. doi:10.1111/j.0014-3820.2005.tb01769.xWagner, G. P., Pavlicev, M., & Cheverud, J. M. (2007). The road to modularity. Nature Reviews Genetics, 8(12), 921-931. doi:10.1038/nrg2267Watson, R. A., Weinreich, D. M., & Wakeley, J. (2010). GENOME STRUCTURE AND THE BENEFIT OF SEX. Evolution, 65(2), 523-536. doi:10.1111/j.1558-5646.2010.01144.xHayden, E. J., Ferrada, E., & Wagner, A. (2011). Cryptic genetic variation promotes rapid evolutionary adaptation in an RNA enzyme. Nature, 474(7349), 92-95. doi:10.1038/nature1008