Scale-effects on mean and standard deviation of the mechanical properties of condensed matter: an energy-based unified approach

The size effects on the mean values of the mechanical properties of condensed matter and on the related variances are analysed by means of a unified approach based on the multiscale character of energy dissipation. In particular, the scaling law for fragmentation energy density is obtained taking into account the self-similarity of fragments. It is based on a generalization of the three classical comminution laws that has been performed to evaluate the energy dissipation, computing volume and surface area of the particles for one- two- and three-dimensional fragmented objects. The result is general and can be applied to different fractal energy dissipation mechanisms, e.g., plasticity. Based on this approach, the scaling laws for mean and standard deviation values of the main mechanical properties of materials can be derived, like Young's and shear elastic moduli, ultimate normal and shear stresses and strains, fracture energy and toughness.     

Scaling of energy dissipation in crushing and fragmentation: a fractal and statistical analysis based on particle size distribution

An extensive experimental investigation on concrete specimens under crushing and fragmentation over a large scale range (1:10) – exploring even very small specimen dimensions (1 cm) – was carried out to evaluate the influence of fragment size distribution on energy density dissipation and related size effect. To obtain a statistically significant fragment production as well as the total energy dissipated in a given specimen, the experimental procedure was unusually carried out up to a strain of approximately –95%, practically corresponding to the initial fragment compaction between the loading platens. The experimental fragment analysis suggests a fractal law for the distribution in particle size; this simply means that fragments derived from a given specimen appear geometrically self-similar at each observation scale. In addition, clear size effects on dissipated energy density are experimentally observed. Fractal concepts permit to quantify the correlation between fragment size distribution and size effect on dissipated energy density, the latter being governed by the total surface area of produced fragments. The experimental results agree with the proposed multi-scale interpretation satisfactorily.     

Identification of piecewise affine systems via mixed-integer programming

This paper addresses the problem of identification of hybrid dynamical systems, by focusing the attention on hinging hyperplanes and Wiener piecewise affine autoregressive exogenous models, in which the regressor space is partitioned into polyhedra with affine submodels for each polyhedron. In particular, we provide algorithms based on mixed-integer linear or quadratic programming which are guaranteed to converge to a global optimum. For the special case where the estimation data only seldom switches between the different submodels, we also suggest a way of trading off between optimality and complexity by using a change detection approach.     

Effect of geometry and green density on the anisotropic sintering shrinkage of axisymmetric iron parts

Sintering shrinkage of prior cold compacted iron rings with different geometry (height to wall thickness ratio) and green density in the 6.5–7.3?g/cm³ range was investigated. It displays a minimum at an intermediate green density. Axial, tangential and radial shrinkages are different, due to the gradients of green density along the axial and the radial directions. Therefore, the effect of height on shrinkage and its anisotropy is the result of their effect on the stress distribution in the green parts during cold compaction, and the resulting green density and deformation experienced by the powder. Anisotropy decreases on increasing shrinkage.     

Autonomous indoor ultrasonic positioning system based on a low-cost conditioning circuit

This work presents a low cost 3-D location system based on ultrasonics and implemented with low-cost FPGAs. The mobile nodes of the system use distance estimation to several anchor points in order to trilaterate their positions with an accuracy of few centimeters. The ultrasonic transducers are handled with an ad hoc conditioning circuit based on instrumental amplifiers which provides high amplification keeping low noise. The proposed system is autonomous so there is no need of an external PC or other devices. A prototype of the system has been attached to a mobile robot to check the viability of the location system in a real scenario.     

Discovery of an Allosteric Ligand Binding Site in SMYD3 Lysine Methyltransferase

SMYD3 is a multifunctional epigenetic enzyme with lysine methyltransferase activity and various interaction partners. It is implicated in the pathophysiology of cancers but with an unclear mechanism. To discover tool compounds for clarifying its biochemistry and potential as a therapeutic target, a set of drug-like compounds was screened in a biosensor-based competition assay. Diperodon was identified as an allosteric ligand; its R and S enantiomers were isolated, and their affinities to SMYD3 were determined (K_D=42 and 84 μM, respectively). Co-crystallization revealed that both enantiomers bind to a previously unidentified allosteric site in the C-terminal protein binding domain, consistent with its weak inhibitory effect. No competition between diperodon and HSP90 (a known SMYD3 interaction partner) was observed although SMYD3–HSP90 binding was confirmed (K_D=13 μM). Diperodon clearly represents a novel starting point for the design of tool compounds interacting with a druggable allosteric site, suitable for the exploration of noncatalytic SMYD3 functions and therapeutics with new mechanisms of action.     

iCanCloud: A Flexible and Scalable Cloud Infrastructure Simulator

Simulation techniques have become a powerful tool for deciding the best starting conditions on pay-as-you-go scenarios. This is the case of public cloud infrastructures, where a given number and type of virtual machines (in short VMs) are instantiated during a specified time, being this reflected in the final budget. With this in mind, this paper introduces and validates iCanCloud, a novel simulator of cloud infrastructures with remarkable features such as flexibility, scalability, performance and usability. Furthermore, the iCanCloud simulator has been built on the following design principles: (1) it’s targeted to conduct large experiments, as opposed to others simulators from literature; (2) it provides a flexible and fully customizable global hypervisor for integrating any cloud brokering policy; (3) it reproduces the instance types provided by a given cloud infrastructure; and finally, (4) it contains a user-friendly GUI for configuring and launching simulations, that goes from a single VM to large cloud computing systems composed of thousands of machines.     

Plasmon-induced photochemical synthesis of silver triangular prisms and pentagonal bipyramids by illumination with light emitting diodes

We have grown silver prisms and pentagonal bipyramids, induced by plasmon excitation on a colloidal solution under the irradiation of light emitting diodes of different colors. Two methods of synthesis of the seeds were tested and their growth evolution recorded, in order to analyze the effect of the chemical synthesis and the color of the irradiation on the morphology and size of the final product. We show that the conversion rate into anisotropic nanoparticles is determined by the chemical environment and the shift of the irradiation wavelength with respect to the plasmon resonance of the seeds. The conversion rate defines the final morphology of the nanoparticles, whereas the size of the nanoparticles is univocally determined by the wavelength of irradiation, irrespective of the method to prepare the seed solution.     

Metabolomics of Genetically Modified Crops

Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.