Active Processor Scheduling Using Evolution Algorithms

The allocation of processes to processors has long been of interest to engineers. The processor allocation problem considered here assigns multiple applications onto a computing system. With this algorithm researchers could more efficiently examine real-time sensor data like that used by United States Air Force digital signal processing efforts or real-time aerosol hazard detection as examined by the Department of Homeland Security. Different choices for the design of a load balancing algorithm are examined in both the problem and algorithm domains. Evolutionary algorithms are used to find near-optimal solutions. These algorithms incorporate multiobjective coevolutionary and parallel principles to create an effective and efficient algorithm for real-world allocation problems. Three evolutionary algorithms (EA) are developed. The primary algorithm generates a solution to the processor allocation problem. This allocation EA is capable of evaluating objectives in both an aggregate single objective and a Pareto multiobjective manner. The other two EAs are designed for fine turning returned allocation EA solutions. One coevolutionary algorithm is used to optimize the parameters of the allocation algorithm. This meta-EA is parallelized using a coarse-grain approach to improve performance. Experiments are conducted that validate the improved effectiveness of the parallelized algorithm. Pareto multiobjective approach is used to optimize both effectiveness and efficiency objectives. The other coevolutionary algorithm generates difficult allocation problems for testing the capabilities of the allocation EA. The effectiveness of both coevolutionary algorithms for optimizing the allocation EA is examined quantitatively using standard statistical methods. Also the allocation EAs objective tradeoffs are analyzed and compared

THE ROLE OF PRODUCT ATTRIBUTES IN THE AGRICULTURAL NEGOTIATIONS

Marketing, International Relations/Trade,

Rab-coupling protein coordinates recycling of α5β1 integrin and EGFR1 to promote cell migration in 3D microenvironments

Here we show that blocking the adhesive function of αvβ3 integrin with soluble RGD ligands, such as osteopontin or cilengitide, promoted association of Rab-coupling protein (RCP) with α5β1 integrin and drove RCP-dependent recycling of α5β1 to the plasma membrane and its mobilization to dynamic ruffling protrusions at the cell front. These RCP-driven changes in α5β1 trafficking led to acquisition of rapid/random movement on two-dimensional substrates and to a marked increase in fibronectin-dependent migration of tumor cells into three-dimensional matrices. Recycling of α5β1 integrin did not affect its regulation or ability to form adhesive bonds with substrate fibronectin. Instead, α5β1 controlled the association of EGFR1 with RCP to promote the coordinate recycling of these two receptors. This modified signaling downstream of EGFR1 to increase its autophosphorylation and activation of the proinvasive kinase PKB/Akt. We conclude that RCP provides a scaffold that promotes the physical association and coordinate trafficking of α5β1 and EGFR1 and that this drives migration of tumor cells into three-dimensional matrices

Autoregulation of the Escherichia coli melR promoter: repression involves four molecules of MelR

The Escherichia coli MelR protein is a transcription activator that autoregulates its own promoter by repressing transcription initiation. Optimal repression requires MelR binding to a site that overlaps the melR transcription start point and to upstream sites. In this work, we have investigated the different determinants needed for optimal repression and their spatial requirements. We show that repression requires a complex involving four DNA-bound MelR molecules, and that the global CRP regulator plays little or no role

Light Composite Vector Bosons

In gauge theories with slowly-running coupling constants, it may be possible for four-fermion operators to be nearly marginal. Such operators can possess asymptotically weak couplings, and can plausibly give rise to light composite vector mesons.Comment: 16 pages (TeX w/epsf), 4 figures (uuencoded) included, CERN-TH.6767/9

Discovery of a Candidate Central Compact Object in the Galactic Nonthermal SNR G330.2+1.0

We report on the discovery of a pointlike source (CXOU J160103.1$-$513353) at the center of a Galactic supernova remnant (SNR) G330.2+1.0 with {\it Chandra X-Ray Observatory}. The X-ray spectrum fits a black-body (BB) model with $kT$ $\sim$ 0.49 keV, implying a small emission region of $R$ $\sim$ 0.4 km at the distance of 5 kpc. The estimated X-ray luminosity is $L_X$ $\sim$ 1 $\times$ 10$^{33}$ ergs s$^{-1}$ in the 1 $-$ 10 keV band. A power law model may also fit the observed spectrum, but the fit results in a very large photon index, $\Gamma$ $\sim$ 5. We find no counterparts at other wavelengths. The X-ray emission was steady over the $\sim$13 hr observation period, showing no variability. While we find marginal evidence for X-ray pulsations ($P$ $\approx$ 7.5 s), the presence of a pulsar at the position of this object is not conclusive with the current data, requiring an independent confirmation. These results are generally consistent with an interpretation of this object as a Central Compact Object associated with SNR G330.2+1.0.Comment: 9 pages (AASTex preprint style) including 1 Table and 4 Figures. Accepted by ApJ Letter

(Borel) convergence of the variationally improved mass expansion and the O(N) Gross-Neveu model mass gap

We reconsider in some detail a construction allowing (Borel) convergence of an alternative perturbative expansion, for specific physical quantities of asymptotically free models. The usual perturbative expansions (with an explicit mass dependence) are transmuted into expansions in 1/F, where $F \sim 1/g(m)$ for $m \gg \Lambda$ while $F \sim (m/\Lambda)^\alpha$ for m \lsim \Lambda, $\Lambda$ being the basic scale and $\alpha$ given by renormalization group coefficients. (Borel) convergence holds in a range of $F$ which corresponds to reach unambiguously the strong coupling infrared regime near $m\to 0$, which can define certain "non-perturbative" quantities, such as the mass gap, from a resummation of this alternative expansion. Convergence properties can be further improved, when combined with $\delta$ expansion (variationally improved perturbation) methods. We illustrate these results by re-evaluating, from purely perturbative informations, the O(N) Gross-Neveu model mass gap, known for arbitrary $N$ from exact S matrix results. Comparing different levels of approximations that can be defined within our framework, we find reasonable agreement with the exact result.Comment: 33 pp., RevTeX4, 6 eps figures. Minor typos, notation and wording corrections, 2 references added. To appear in Phys. Rev.

Protecting Against Address Space Layout Randomization (ASLR) Compromises and Return-to-Libc Attacks Using Network Intrusion Detection Systems

Writable XOR eXecutable (W XOR X) and Address Space Layout Randomisation (ASLR), have elevated the understanding necessary to perpetrate buffer overflow exploits [1]. However, they have not proved to be a panacea [1] [2] [3] and so other mechanisms such as stack guards and prelinking have been introduced. In this paper we show that host based protection still does not offer a complete solution. To demonstrate, we perform an over the network brute force return-to-libc attack against a pre-forking concurrent server to gain remote access to W XOR X and ASLR. We then demonstrate that deploying a NIDS with appropriate signatures can detect this attack efficiently

Twenty Five Years of Asymptotic Freedom

On the occasion of the 25th anniversary of Asymptotic Freedom, celebrated at the QCD Euroconference 98 on Quantum Chromodynamics, Montpellier, July 1998, I described the discovery of Asymptotic Freedom and the emergence of QCD.Comment: 35 pages, LaTe

Inferring transient dynamics of human populations from matrix non-normality

This is the final version of the article. Available from Springer Verlag via the DOI in this record.In our increasingly unstable and unpredictable world, population dynamics rarely settle uniformly to long-term behaviour. However, projecting period-by-period through the preceding fluctuations is more data-intensive and analytically involved than evaluating at equilibrium. To efficiently model populations and best inform policy, we require pragmatic suggestions as to when it is necessary to incorporate short-term transient dynamics and their effect on eventual projected population size. To estimate this need for matrix population modelling, we adopt a linear algebraic quantity known as non-normality. Matrix non-normality is distinct from normality in the Gaussian sense, and indicates the amplificatory potential of the population projection matrix given a particular population vector. In this paper, we compare and contrast three well-regarded metrics of non-normality, which were calculated for over 1000 age-structured human population projection matrices from 42 European countries in the period 1960 to 2014. Non-normality increased over time, mirroring the indices of transient dynamics that peaked around the millennium. By standardising the matrices to focus on transient dynamics and not changes in the asymptotic growth rate, we show that the damping ratio is an uninformative predictor of whether a population is prone to transient booms or busts in its size. These analyses suggest that population ecology approaches to inferring transient dynamics have too often relied on suboptimal analytical tools focussed on an initial population vector rather than the capacity of the life cycle to amplify or dampen transient fluctuations. Finally, we introduce the engineering technique of pseudospectra analysis to population ecology, which, like matrix non-normality, provides a more complete description of the transient fluctuations than the damping ratio. Pseudospectra analysis could further support non-normality assessment to enable a greater understanding of when we might expect transient phases to impact eventual population dynamics.This work was funded by Wellcome Trust New Investigator 103780 to TE, who is also funded by NERC Fellowship NE/J018163/1. JB gratefully acknowledges the ESRC Centre for Population Change ES/K007394/1