Babesia Bovis Ligand-Receptor Interaction: AMA-1 Contains Small Regions Governing Bovine Erythrocyte Binding

Apical membrane antigen 1 is a microneme protein which plays an indispensable role during Apicomplexa parasite invasion. The detailed mechanism of AMA-1 molecular interaction with its receptor on bovine erythrocytes has not been completely defined in Babesia bovis. This study was focused on identifying the minimum B. bovis AMA-1-derived regions governing specific and high-affinity binding to its target cells. Different approaches were used for detecting ama-1 locus genetic variability and natural selection signatures. The binding properties of twelve highly conserved 20-residue-long peptides were evaluated using a sensitive and specific binding assay based on radio-iodination. B. bovis AMA-1 ectodomain structure was modelled and refined using molecular modelling software. NetMHCIIpan software was used for calculating B- and T-cell epitopes. The B. bovis ama-1 gene had regions under functional constraint, having the highest negative selective pressure intensity in the Domain I encoding region. Interestingly, B. bovis AMA-1-DI (¹⁰⁰YMQKFDIPRNHGSGIYVDLG¹¹⁹ and ¹²⁰GYESVGSKSYRMPVGKCPVV¹³⁹) and DII (³⁰²CPMHPVRDAIFGKWSGGSCV³²¹)-derived peptides had high specificity interaction with erythrocytes and bound to a chymotrypsin and neuraminidase-treatment sensitive receptor. DI-derived peptides appear to be exposed on the protein’s surface and contain predicted B- and T-cell epitopes. These findings provide data (for the first-time) concerning B. bovis AMA-1 functional subunits which are important for establishing receptor-ligand interactions which could be used in synthetic vaccine development.     

Extracting Low-Frequency Spatio-Temporal Patterns in Ambient Power System Data Using Blind Source Separation

Wide-area techniques provide a powerful tool to extract spatio-temporal patterns from high-dimensional datasets and can be used for event detection and visualization, data fusion, stability assessment, and coherency analysis. In this paper, a novel blind source separation-based approach for extracting low-frequency spatio-temporal patterns from measured ambient power system data is proposed and a spatio-temporal visualization index is also suggested. This methodology combines a nonlinear hierarchical neural network with a Blind Source Separation (BSS) technique. The neural network allows reducing noise and removing the nonlinear relations among data (preserve dynamic features of interest), while the BSS technique permits extracting spatial and temporal patterns. In addition, the proposed approach takes advantage of the latest techniques in nonlinear estimation of non-stationary time series. Finally, application examples of the proposed framework on real test cases recorded from an actual power system by Phasor Measurement Units (PMUs) are presented. The obtained results show that the temporal patterns can be used for extracting and identifying the low-frequency oscillation modes and the spatial patterns can be used for identifying modes with the most contribution in original data. Compared to other BSS approaches, the proposed method has shown to be better for the analysis of real ambient data.     

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.     

Spatial partially coherent imaging

We introduce the partial coherence response function for describing the behaviour of imaging systems under spatial partially coherent illumination in the centre and the diierence coordinates notation. It involves the impulse response of the system and the spatial coherence properties of the illumination. It is shown that this function is the image cross-spectral density for a Young's pair of pinholes attached at the object plane. Furthermore, the partial coherence response function and the partial coherence transfer function constitute a Fourier pair on which the Fourier representation of partially coherent imaging can be based.     

Multi‐criteria algorithm‐based methodology used to select suitable domes for compressed air energy storage

Storing energy allows both the efficiency and availability of renewable energy to be increased, thus dissociating actual from expected generation and from consumption demands. Compressed air energy storage (hereinafter ‘CAES’) enables the efficient and cost‐effective storage of large amounts of energy, achieving a capacity of over 100 MWh. There are several geological structures that can be used as CAES, among which the use and construction of salt domes are particularly noteworthy. However, there is a high exploration risk associated with subsurface exploration. To this end, it is advisable to establish a detailed schedule to select and characterize structures, with the purpose of minimizing the aforementioned risk. Multi‐criteria algorithms can be used to establish a hierarchy of the alternatives and to identify the structures with the greatest potential with an objective approach. The analytic hierarchy process method is used in this paper as the selection algorithm, which is based on identifying and assessing criteria and weighting each criterion. In accordance with the analytic hierarchy process method, the goal was divided into a series of different level criteria, defining a breakdown structure of the problem to select salt domes. This paper defines a structure hierarchization method that allows the objective establishment of the areas with the highest potential for CAES, considering both technical and socioeconomic factors. Therefore, a supporting decision‐making method may be established to reduce the exploration risk associated with underground structures. Copyright © 2017 John Wiley & Sons, Ltd.     

Creep and shrinkage of recycled aggregate concrete

This paper presents the results of experimental research into concrete produced by replacing the natural aggregates with recycled aggregates coming from construction waste and concrete work demolitions. The main aim of this work was to determine creep and shrinkage variations experienced in recycled concrete, made by replacing the main fraction of the natural aggregate with a recycled aggregate coming from waste concrete and comparing it to a control concrete. The substitution percentages were 20%, 50% and 100%. Fine natural aggregate was used in all cases and the amount of cement and water–cement ratio remained constant in the mixture. It was possible to state that the evolution of deformation by shrinkage and creep was similar to a conventional concrete, although the results after a period of 180 days showed the influence of the substitution percentage in the recycled aggregates present in the mixture. In the case when 100% coarse natural aggregate was replaced by recycled aggregate there was an increase in the deformations by creep of 51% and by shrinkage of 70% as compared to those experienced by the control concrete.