Do sophisticated evolutionary algorithms perform better than simple ones?

Evolutionary algorithms (EAs) come in all shapes and sizes. Theoretical investigations focus on simple, bare-bones EAs while applications often use more sophisticated EAs that perform well on the problem at hand. What is often unclear is whether a large degree of algorithm sophistication is necessary, and if so, how much performance is gained by adding complexity to an EA. We address this question by comparing the performance of a wide range of theory-driven EAs, from bare-bones algorithms like the (1+1) EA, a (2+1) GA and simple population-based algorithms to more sophisticated ones like the (1+(λ,λ)) GA and algorithms using fast (heavy-tailed) mutation operators, against sophisticated and highly effective EAs from specific applications. This includes a famous and highly cited Genetic Algorithm for the Multidimensional Knapsack Problem and the Parameterless Population Pyramid for Ising Spin Glasses and MaxSat. While for the Multidimensional Knapsack Problem the sophisticated algorithm performs best, surprisingly, for large Ising and MaxSat instances the simplest algorithm performs best. We also derive conclusions about the usefulness of populations, crossover and fast mutation operators. Empirical results are supported by statistical tests and contrasted against theoretical work in an attempt to link theoretical and empirical results on EAs

Aspects of Superembeddings

Some aspects of the geometry of superembeddings and its application to supersymmetric extended objects are discussed. In particular, the embeddings of (3|16) and (6|16) dimensional superspaces into (11|32) dimensional superspace, corresponding to supermembranes and superfivebranes in eleven dimensions, are treated in some detail.Comment: 13 pages, Latex, Contribution to Supersymmetry and Quantum Field Theory, International Seminar dedicated to the memory of D. V. Volkov (Kharkov, 1997), some clarifications are mad

The timing and location of glial cell line-derived neurotrophic factor expression determine enteric nervous system structure and function

Ret signaling is critical for formation of the enteric nervous system (ENS) because Ret activation promotes ENS precursor survival, proliferation, and migration and provides trophic support for mature enteric neurons. While these roles are well established, we now provide evidence that increasing levels of the Ret ligand GDNF in mice causes alterations in ENS structure and function that are critically dependent on the time and location of increased GDNF availability. This is demonstrated using two different strains of transgenic mice and by injecting newborn mice with GDNF. Furthermore, because different subclasses of ENS precursors withdraw from the cell cycle at different times during development, increases in GDNF at specific times alter the ratio of neuronal subclasses in the mature ENS. In addition, we confirm that esophageal neurons are GDNF responsive and demonstrate that the location of GDNF production influences neuronal process projection for NADPH diaphorase expressing, but not acetylcholinesterase, choline acetyltransferase, or tryptophan hydroxylase expressing small bowel myenteric neurons. We further demonstrate that changes in GDNF availability influence intestinal function in vitro and in vivo. Thus, changes in GDNF expression can create a wide variety of alterations in ENS structure and function and may in part contribute to human motility disorders

A multi-resolution, non-parametric, Bayesian framework for identification of spatially-varying model parameters

This paper proposes a hierarchical, multi-resolution framework for the identification of model parameters and their spatially variability from noisy measurements of the response or output. Such parameters are frequently encountered in PDE-based models and correspond to quantities such as density or pressure fields, elasto-plastic moduli and internal variables in solid mechanics, conductivity fields in heat diffusion problems, permeability fields in fluid flow through porous media etc. The proposed model has all the advantages of traditional Bayesian formulations such as the ability to produce measures of confidence for the inferences made and providing not only predictive estimates but also quantitative measures of the predictive uncertainty. In contrast to existing approaches it utilizes a parsimonious, non-parametric formulation that favors sparse representations and whose complexity can be determined from the data. The proposed framework in non-intrusive and makes use of a sequence of forward solvers operating at various resolutions. As a result, inexpensive, coarse solvers are used to identify the most salient features of the unknown field(s) which are subsequently enriched by invoking solvers operating at finer resolutions. This leads to significant computational savings particularly in problems involving computationally demanding forward models but also improvements in accuracy. It is based on a novel, adaptive scheme based on Sequential Monte Carlo sampling which is embarrassingly parallelizable and circumvents issues with slow mixing encountered in Markov Chain Monte Carlo schemes

Interleukin-6 and Associated Cytokine Responses to An Acute Bout of High-intensity Interval Exercise: the Effect of Exercise Intensity and Volume

Acute increases in interleukin (IL)-6 following prolonged exercise are associated with the induction of a transient anti-inflammatory state (e.g., increases in IL-10) that is partly responsible for the health benefits of regular exercise. The purposes of this study were to investigate the IL-6–related inflammatory response to high-intensity interval exercise (HIIE) and to determine the impact of exercise intensity and volume on this response. Ten participants (5 males and 5 females) completed 3 exercise bouts of contrasting intensity and volume (LOW, MOD, and HIGH). The HIGH protocol was based upon standard HIIE protocols, while the MOD and LOW protocols were designed to enable a comparison of exercise intensity and volume with a fixed duration. Inflammatory cytokine concentrations were measured in plasma (IL-6, IL-10) and also determined the level of gene expression (IL-6, IL-10, and IL-4R) in peripheral blood. The plasma IL-6 response to exercise (reported as fold changes) was significantly greater in HIGH (2.70 ± 1.51) than LOW (1.40 ± 0.32) (P = 0.04) and was also positively correlated to the mean exercise oxygen uptake (r = 0.54, P < 0.01). However, there was no change in anti-inflammatory IL-10 or IL-4R responses in plasma or at the level of gene expression. HIIE caused a significant increase in IL-6 and was greater than that seen in low-intensity exercise of the same duration. The increases in IL-6 were relatively small in magnitude, and appear to have been insufficient to induce the acute systemic anti-inflammatory effects, which are evident following longer duration exercise

Active region formation through the negative effective magnetic pressure instability

The negative effective magnetic pressure instability operates on scales encompassing many turbulent eddies and is here discussed in connection with the formation of active regions near the surface layers of the Sun. This instability is related to the negative contribution of turbulence to the mean magnetic pressure that causes the formation of large-scale magnetic structures. For an isothermal layer, direct numerical simulations and mean-field simulations of this phenomenon are shown to agree in many details in that their onset occurs at the same depth. This depth increases with increasing field strength, such that the maximum growth rate of this instability is independent of the field strength, provided the magnetic structures are fully contained within the domain. A linear stability analysis is shown to support this finding. The instability also leads to a redistribution of turbulent intensity and gas pressure that could provide direct observational signatures.Comment: 19 pages, 10 figures, submitted to Solar Physic

Super D-branes from BRST Symmetry

Recently a new formalism has been developed for the covariant quantization of superstrings. We study properties of Dp-branes and p-branes in this new framework, focusing on two different topics: effective actions and boundary states for Dp-branes. We present a derivation of the Wess-Zumino terms for super (D)p-branes using BRST symmetry. To achieve this we derive the BRST symmetry for superbranes, starting from the approach with/without pure spinors, and completely characterize the WZ terms as elements of the BRST cohomology. We also develope the boundary state description of Dp-branes by analyzing the boundary conditions for open strings in the completely covariant (i.e., without pure spinors) BRST formulation.Comment: 31 pp; journal version, expended discussion of D-brane pure spinor constraints in Section 2.

Constraints on Dark Matter Annihilation in Clusters of Galaxies with the Fermi Large Area Telescope

Nearby clusters and groups of galaxies are potentially bright sources of high-energy gamma-ray emission resulting from the pair-annihilation of dark matter particles. However, no significant gamma-ray emission has been detected so far from clusters in the first 11 months of observations with the Fermi Large Area Telescope. We interpret this non-detection in terms of constraints on dark matter particle properties. In particular for leptonic annihilation final states and particle masses greater than ~200 GeV, gamma-ray emission from inverse Compton scattering of CMB photons is expected to dominate the dark matter annihilation signal from clusters, and our gamma-ray limits exclude large regions of the parameter space that would give a good fit to the recent anomalous Pamela and Fermi-LAT electron-positron measurements. We also present constraints on the annihilation of more standard dark matter candidates, such as the lightest neutralino of supersymmetric models. The constraints are particularly strong when including the fact that clusters are known to contain substructure at least on galaxy scales, increasing the expected gamma-ray flux by a factor of ~5 over a smooth-halo assumption. We also explore the effect of uncertainties in cluster dark matter density profiles, finding a systematic uncertainty in the constraints of roughly a factor of two, but similar overall conclusions. In this work, we focus on deriving limits on dark matter models; a more general consideration of the Fermi-LAT data on clusters and clusters as gamma-ray sources is forthcoming.Comment: accepted to JCAP, Corresponding authors: T.E. Jeltema and S. Profumo, minor revisions to be consistent with accepted versio

Search for the glueball candidates f0(1500) and fJ(1710) in gamma gamma collisions

Data taken with the ALEPH detector at LEP1 have been used to search for gamma gamma production of the glueball candidates f0(1500) and fJ(1710) via their decay to pi+pi-. No signal is observed and upper limits to the product of gamma gamma width and pi+pi- branching ratio of the f0(1500) and the fJ(1710) have been measured to be Gamma_(gamma gamma -> f0(1500)). BR(f0(1500)->pi+pi-) < 0.31 keV and Gamma_(gamma gamma -> fJ(1710)). BR(fJ(1710)->pi+pi-) < 0.55 keV at 95% confidence level.Comment: 10 pages, 3 figure

Azimuthal anisotropy and correlations in p+p, d+Au and Au+Au collisions at 200 GeV

We present the first measurement of directed flow ($v_1$) at RHIC. $v_1$ is found to be consistent with zero at pseudorapidities $\eta$ from -1.2 to 1.2, then rises to the level of a couple of percent over the range $2.4 < |\eta| < 4$. The latter observation is similar to data from NA49 if the SPS rapidities are shifted by the difference in beam rapidity between RHIC and SPS. Back-to-back jets emitted out-of-plane are found to be suppressed more if compared to those emitted in-plane, which is consistent with {\it jet quenching}. Using the scalar product method, we systematically compared azimuthal correlations from p+p, d+Au and Au+Au collisions. Flow and non-flow from these three different collision systems are discussed.Comment: Quark Matter 2004 proceeding, 4 pages, 3 figure