Effect of the marine environment on reinforced concrete durability in Iberoamerican countries: DURACON project/CYTED

This work presents some of the results from the project: “Effect of the environment on reinforcement durability” (DURACON) in its first two-years period, which investigates the influence of urban and marine meteorochemical parameters on the performance of reinforced concrete structures. The results presented in this investigation are from 21 marine test sites only (no urban environments are included), distributed among 11 countries (Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Mexico, Spain, Uruguay, Portugal and Venezuela). The environment was evaluated using ISO Standard 9223 and the concrete was characterized by measuring compressive strength, elastic modulus, total and effective porosity, chloride permeability according to ASTM standards, as well as the effective porosity and resistance to water absorption using the Fagerlund method. To that effect, concrete specimens (with and without reinforcement) were prepared for electrochemical and physical/mechanical/chemical tests using the existing materials in each participating country, following strict procedures which enabled the preparation of similar concrete samples. Two water/cement (w/c) ratios (0.45 and 0.65) were selected, where the concrete with 0.45 w/c ratio had to have a minimum cement content of 400 kg/m³ and the one with 0.65 w/c ratio a compressive strength of 210 kg/cm². Type I Portland cement, siliceous sand, and crushed rock as coarse aggregates (13-mm maximum nominal size) were used. After a one-year exposure, the results of the corrosion potentiality and probability analysis of the reinforcement in the different test stations showed that, for marine atmospheres, the most aggressive environment to induce steel corrosion was at Portugal’s Cabo Raso station, and the least aggressive one was at Chile’s Valparaíso station. These results are comparable with the ones found using electrochemical measurements, after a two-year exposure.     

An analytical evaluation of the cutting forces in self-piloting drilling using the model of shear zone with parallel boundaries. Part 1: Theory

The performance of a self-piloting tool is affected by its design and geometry parameters. These parameters constitute the tool-force system which directly defines quality of the machined holes, tool life and required power. This paper presents an analytical approach to describe the cutting forces in self-piloting drilling. The approach is useful at the level of tool and process design. The subject has been covered in two parts. Part one deals with the analysis of the cutting mechanics employing the shear-zone model with parallel boundaries. The analysis of the continuity condition results in better understanding of the traditional cutting model's characteristics, such as the chip compression ratio and velocity diagram. Based on this analysis and using the thermomechanical model of the work-material resistance to cutting, a cutting-force model is proposed and has been verified experimentally.     

Are U.K. Citizens Satisfied With E-Government Services? Identifying and Testing Antecedents of Satisfaction

Citizens’ satisfaction is acknowledged as one of the most significant influences for e-government adoption and diffusion. This study examines the impact of information quality, system quality, trust, and cost on user satisfaction of e-government services. Using a survey, this study collected 1518 valid responses from e-government service adopters across the United Kingdom. Our empirical outcomes show the five factors identified in this study have a significant impact on U.K. citizens’ satisfaction with e-government services.     

Small‐signal and noise modeling of class of HEMTs using knowledge‐based artificial neural networks

In this article, the neural network approach is exploited for development of bias‐dependent small‐signal and noise models of a class of microwave field effect transistor (FETs) made in the same technology but differing in the gate width. The prior knowledge neural approach is applied. Introducing gate width at the input of proposed neural networks, as well as the S/noise parameters of a device that belongs to the same class as the modeled device representing the prior knowledge, leads to very accurate scattering and noise parameters' modeling, as exemplified by modeling of class of pseudomorphic high electron mobility transistor (pHEMT) devices. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet

We propose a new semantic relation for gradable adjectives in WordNet, which enriches the present, vague, similar relation with information on the degree or intensity with which different adjectives express a shared attribute. Using lexical-semantic patterns, we mine the Web for evidence of the relative strength of adjectives like “large”, “huge” and “gigantic” with respect to their attribute (“size”). The pairwise orderings we derive allow us to construct scales on which the adjectives are located. To represent the intensity relation among gradable adjectives in WordNet, we combine ordered scales with the current WordNet dumbbells based on the relation between a pair of central adjectives and a group of undifferentiated semantically similar adjectives. A new intensity relation links the adjectives in the dumbbells and their concurrent representation on scales. Besides capturing the semantics of gradable adjectives in a way that is both intuitively clear as well as consistent with corpus data, the introduction of an intensity relation would potentially result in several specific benefits for NLP.     

Privacy-enhanced architecture for smart metering

The recent deployment of smart grids promises to bring numerous advantages in terms of energy consumption reduction in both homes and businesses. A more transparent and instantaneous measurement of electricity consumption through smart meters utilization leads to an enhancement in the ability of monitoring, controlling and predicting energy usage. Nevertheless, it also has associated drawbacks related to the privacy of customers, since such management might reveal their personal habits, which electrical appliances they are using at each moment, whether they are at home or not, etc. In this work, we present a privacy-enhanced architecture for smart metering aimed at tackling this threat by means of encrypting individual measurements while allowing the electricity supplier to access the aggregation of the corresponding decrypted values.     

Hybrid Nanoscopy of Hybrid Nanomaterials

The combination of complementary techniques to characterize materials at the nanoscale is crucial to gain a more complete picture of their structure, a key step to design and fabricate new materials with improved properties and diverse functions. Here it is shown that correlative atomic force microscopy (AFM) and localization‐based super‐resolution microscopy is a useful tool that provides insight into the structure and emissive properties of fluorescent β‐lactoglobulin (βLG) amyloid‐like fibrils. These hybrid materials are made by functionalization of βLG with organic fluorophores and quantum dots, the latter being relevant for the production of 1D inorganic nanostructures templated by self‐assembling peptides. Simultaneous functionalization of βLG fibers by QD655 and QD525 allows for correlative AFM and two‐color super‐resolution fluorescence imaging of these hybrid materials. These experiments allow the combination of information about the topography and number of filaments that compose a fibril, as well as the emissive properties and nanoscale spatial distribution of the attached fluorophores. This study represents an important step forward in the characterization of multifunctionalized hybrid materials, a key challenge in nanoscience.     

Control Charts with Variable Dimension for Linear Combination of Poisson Variables

This article analyzes the simultaneous control of several correlated Poisson variables by using the Variable Dimension Linear Combination of Poisson Variables (VDLCP) control chart, which is a variable dimension version of the LCP chart. This control chart uses as test statistic, the linear combination of correlated Poisson variables in an adaptive way, i.e. it monitors either p₁ or p variables (p₁ < p) depending on the last statistic value. To analyze the performance of this chart, we have developed software that finds the best parameters, optimizing the out‐of‐control average run length (ARL) for a shift that the practitioner wishes to detect as quickly as possible, restricted to a fixed value for in‐control ARL. Markov chains and genetic algorithms were used in developing this software. The results show performance improvement compared to the LCP chart. Copyright © 2015 John Wiley & Sons, Ltd.