Identification of a minor component of the sex pheromone ofLeucoptera malifoliella (Lepidoptera,lyonetiidae)

A new minor component in the female volatile extract ofLeucoptera malifoliella (Costa) (Lepidoptera, Lyonetiidae) has been identified as 5,9-dimethyloctadecane (2). The amount detected of the minor compound2 ranged from 4 to 8% in comparison with the major component 5,9-dimethylheptadecane (1). Neither compound has been found in the male volatile extract. The identification has been based on its spectroscopic properties and Chromatographic behavior in comparison with an authentic synthetic sample. The synthesis has been carried out through a short route from 2,6-dimethylcyclohexanone (3). In field tests, compound2 appears to act as a Synergist of the major component1 when mixed with the latter in a 1000.1– 5 ratio.     

Hydrogen sorption sites in the gallium containing hybrid catalysts used for the aromatization of light alkanes

Gallium species which were incorporated initially in the oxide form, were all in the (+3) oxidation state in the hybrid catalyst and exhibited two types of hydrogen chemisorption sites, s_hw and s_hs. The stronger sorption sites shs which predominated at higher gallium dispersion, corresponded probably to the most effective surface configuration for gallium in the aromatization ofn-butane.     

Detecting similarities in virtual machine behavior for cloud monitoring using smoothed histograms

The growing size and complexity of cloud systems determine scalability issues for resource monitoring and management. While most existing solutions consider each Virtual Machine (VM) as a black box with independent characteristics, we embrace a new perspective where VMs with similar behaviors in terms of resource usage are clustered together. We argue that this new approach has the potential to address scalability issues in cloud monitoring and management. In this paper, we propose a technique to cluster VMs starting from the usage of multiple resources, assuming no knowledge of the services executed on them. This innovative technique models VMs behavior exploiting the probability histogram of their resources usage, and performs smoothing-based noise reduction and selection of the most relevant information to consider for the clustering process. Through extensive evaluation, we show that our proposal achieves high and stable performance in terms of automatic VM clustering, and can reduce the monitoring requirements of cloud systems.     

Comparative evaluation of platforms for parallel Ant Colony Optimization

The rapidly growing field of nature-inspired computing concerns the development and application of algorithms and methods based on biological or physical principles. This approach is particularly compelling for practitioners in high-performance computing, as natural algorithms are often inherently parallel in nature (for example, they may be based on a “swarm”-like model that uses a population of agents to optimize a function). Coupled with rising interest in nature-based algorithms is the growth in heterogenous computing; systems that use more than one kind of processor. We are therefore interested in the performance characteristics of nature-inspired algorithms on a number of different platforms. To this end, we present a new OpenCL-based implementation of the Ant Colony Optimization algorithm, and use it as the basis of extensive experimental tests. We benchmark the algorithm against existing implementations, on a wide variety of hardware platforms, and offer extensive analysis. This work provides rigorous foundations for future investigations of Ant Colony Optimization on high-performance platforms.     

Barocalorimetric technique for monitoring pressurized copolymer reactors

The problem of on‐line estimation of the conversion and composition evolutions in a pressurized batch copolymer reactor with temperature and pressure measurements was addressed. The estimation model consisted of mass and energy balances with a pressure equation built from phase‐equilibrium considerations. The application of a nonlinear geometric estimation approach yielded the underlying solvability condition with physical meaning, a straightforward estimator construction, and a conventional‐like tuning procedure. The resulting barocalorimetric estimator was an on‐line dynamic measurement processor with a model‐based predictor and a measurement‐driven corrector, and whose implementation did not require the polymerization rates and heat‐transfer coefficient function dependencies. The technique was tested with a representative laboratory styrene–butadiene system. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 475–482, 2005     

Comparing global land-cover products – implications for geoscience applications: an investigation for the trans-boundary Mekong Basin

In this article we present the results of a comparison of six globally available land-cover products for the Mekong Basin – an area that spans 795,000 km² and comprises parts of six riparian countries: China, Myanmar, Thailand, Laos, Cambodia, and Vietnam. The basin covers most climatic zones: from high-altitude, snow-covered mountainous regions in the north, to subtropical and tropical rainforest areas and agricultural land further south. The geopolitically important region not only is home to over 72,000,000 inhabitants, but also is a centre of attention of several environmental modelling experts, trying to assess future hydrologic dynamics, climate variability, as well probable land-use developments in the area.

We compare land-cover products of the University of Maryland, UMD 1992–1993, the GLC 2000 product, the GlobCover products of 2004–2006 and 2009, as well as the MODIS-derived land-cover products of 2001 and 2009. For harmonization of individual legends, the Land Cover Classification System, LCCS, has been employed. However, even after harmonization, cross-tabulation among the products reveals extreme differences, where the impact of differing classification algorithms weighs higher than the impact of temporal coincidence of products. Especially, differences within mixed-vegetation classes are large, strongly impacting the overall assessment of forested land, other vegetated land, and even cultivated land in the Mekong Basin. The findings presented here are of high relevance for the modelling community as well as Mekong-related environmental studies, which should consider global remote-sensing-derived products with caution and solid background knowledge.     

Spatio‐temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces

Multi‐view reconstruction aims at computing the geometry of a scene observed by a set of cameras. Accurate 3D reconstruction of dynamic scenes is a key component for a large variety of applications, ranging from special effects to telepresence and medical imaging. In this paper we propose a method based on Moving Least Squares surfaces which robustly and efficiently reconstructs dynamic scenes captured by a calibrated set of hybrid color+depth cameras. Our reconstruction provides spatio‐temporal consistency and seamlessly fuses color and geometric information. We illustrate our approach on a variety of real sequences and demonstrate that it favorably compares to state‐of‐the‐art methods.     

Coping with uncertainty: police strategies for resilient decision-making and action implementation

This study uses a hostage negotiation setting to demonstrate how a team of strategic police officers can utilize specific coping strategies to minimize uncertainty at different stages of their decision-making in order to foster resilient decision-making to effectively manage a high-risk critical incident. The presented model extends the existing research on coping with uncertainty by (1) applying the RAWFS heuristic (Lipshitz and Strauss in Organ Behav Human Decis Process 69:149–163, 1997) of individual decision-making under uncertainty to a team critical incident decision-making domain; (2) testing the use of various coping strategies during “in situ” team decision-making by using a live simulated hostage negotiation exercise; and (3) including an additional coping strategy (“reflection-in-action”; Schön in The reflective practitioner: how professionals think in action. Temple Smith, London, 1983) that aids naturalistic team decision-making. The data for this study were derived from a videoed strategic command meeting held within a simulated live hostage training event; these video data were coded along three themes: (1) decision phase; (2) uncertainty management strategy; and (3) decision implemented or omitted. Results illustrate that, when assessing dynamic and high-risk situations, teams of police officers cope with uncertainty by relying on “reduction” strategies to seek additional information and iteratively update these assessments using “reflection-in-action” (Schön 1983) based on previous experience. They subsequently progress to a plan formulation phase and use “assumption-based reasoning” techniques in order to mentally simulate their intended courses of action (Klein et al. 2007), and identify a preferred formulated strategy through “weighing the pros and cons” of each option. In the unlikely event that uncertainty persists to the plan execution phase, it is managed by “reduction” in the form of relying on plans and standard operating procedures or by “forestalling” and intentionally deferring the decision while contingency planning for worst-case scenarios.     

Science in the Cloud: Allocation and Execution of Data-Intensive Scientific Workflows

An important challenge for the adoption of cloud computing in the scientific community remains the efficient allocation and execution of data-intensive scientific workflows to reduce execution time and the size of transferred data. The transferred data overhead is becoming significant with emerging scientific workflows that have input/output files and intermediate data products ranging in the hundreds of gigabytes. The allocation of scientific workflows on public clouds can be described through a variety of perspectives and parameters, and has been proved to be NP-complete. This paper proposes an evolutionary approach for task allocation on public clouds considering data transfer and execution time. In our framework, a solution is represented using an allocation chromosome that encodes the allocation of tasks to nodes, and an ordering chromosome that defines the execution order according to the scientific workflow representation. We propose a multi-objective optimization that relies on a cloud cost model and employs tailored evolution operators. Starting from a population of possible solutions, we employ crossover and mutation operators on both chromosomes aiming at optimizing the data transferred between nodes as well as the total workflow runtime. The crossover operators combine parts of solutions to reduce data overhead, whereas the mutation operators swamp between parts of the same chromosome according to pre-defined rules. Our experimental study compares between the proposed approach and current state-of-the art approaches using synthetic and real-life workflows. Our algorithm performs similarly to existing heuristics for small workflows and shows up to 80 % improvements for larger synthetic workflows. To further validate our approach we compare between the allocation and scheduling obtained by our approach with that obtained by popular scientific workflow managers, when real workflows with hundreds of tasks are executed on a public cloud. The results show a 10 % improvement in runtime over existing schedulers, caused by a 80 % reduction in transferred data and optimized allocation and ordering of tasks. This improved data locality has greater impact as it can be employed to improve and study data provenance and facilitate data persistence for scientific workflows.     

Activation of Pozzolanic Reaction of Hydrated Portland Cement Fly Ash Pastes in Sulfate Solution

The activation of the pozzolanic reaction of fly ash in portland cement paste immersed in sulfate solution has been studied. Mixtures of two Spanish fly ashes (ASTM class F) with 0%, 15%, and 35% replacement of portland cement by fly ash were immersed in Na₂SO₄ solution, of 2880 ppm SO₄²⁻ concentration, for a period of 90 days. The resistance of the different mixtures to the sulfate attack was evaluated using the Koch-Steinegger test. The results showed that all of the mixtures were sulfate resistant, despite the high Al₂O₃ content of the fly ash. The diffusion of SO₄²⁻ and Na⁺ ions through the pore solution activated the pozzolanic reactivity of the fly ashes, causing microstructural changes, which were characterized by X-ray diffraction (XRD), mercury intrusion porosimetry (MIP), and scanning electron microscopy (SEM). As a result, the flexural strength of the mixtures increased, principally for the fly ash of a lower particle size and 35% of addition.