Fate of Calcium Chloride Dissolved in Concrete Mix Water

The extent to which chloride ion incorporated in portland cement concrete as calcium chloride accelerator at the usual treatment levels remains dissolved in the pore solution was investigated. This was examined by direct analysis of pore solutions expressed from cement pastes. The chloride ion concentration of the pore solution remains high during the first day of hydration and only gradually declines. It appears that appreciable concentrations of chloride ion likely remain in solution indefinitely .     

Experimental methods in chemical engineering: X‐ray photoelectron spectroscopy‐XPS

X‐ray photoelectron spectroscopy (XPS) is a quantitative surface analysis technique used to identify the elemental composition, empirical formula, chemical state, and electronic state of an element. The kinetic energy of the electrons escaping from the material surface irradiated by an x‐ray beam produces a spectrum. XPS identifies chemical species and quantifies their content and the interactions between surface species. It is minimally destructive and is sensitive to a depth between 1–10nm. The elemental sensitivity is in the order of 0.1 atomic %. It requires ultra high vacuum ( Pa) in the analysis chamber and measurement time varies from minutes to hours per sample depending on the analyte. XPS dates back 50 years ago. New spectrometers, detectors, and variable size photon beams, reduce analysis time and increase spatial resolution. An XPS bibliometric map of the 10 000 articles indexed by Web of Science^[1] identifies five research clusters: (i) nanoparticles, thin films, and surfaces; (ii) catalysis, oxidation, reduction, stability, and oxides; (iii) nanocomposites, graphene, graphite, and electro‐chemistry; (iv) photocatalysis, water, visible light, and ; and (v) adsorption, aqueous solutions, and waste water.     

Modulating drug release from poly(lactic-co-glycolic) acid microparticles by the addition of alginate and pectin

The aim of the present work is the characterization of PLGA microparticles including biopolymers for the controlled release of tilmicosin, a broad-spectrum antibiotic. Microparticles were prepared using the double-emulsion solvent evaporation technique. The effect of alginate and pectin incorporation over particle size and porosity, encapsulation efficiency (EE) and pH-responsive drug release was evaluated. Formulations presented a mean particle size of 5.5 μm approximately and a drug EE ranged from 22%–57%. PLGA-Alginate particles showed an increased porosity. Tilmicosin release profiles from PLGA and PLGA-biopolymer microparticles were affected by the particular combination of polymers and the pH of the release medium. The experimental data was simulated using a mathematical model, which takes into account the autocatalytic polymer degradation and the different mechanisms of drug transport. The combination of PLGA and biopolymers strongly influenced the morphology of the particles, offering the possibility of controlling the drug release profiles according to the therapy.     

Use of scanning probe microscopy to study the evolution of nanometer sized liquid structures

The evolution of the profile of nanometer sized water drops on a mica surface has been studied through hydration scanning probe microscopy. A time range from a few seconds down to a fraction of millisecond after the formation of the drop has been explored. This high time resolution has been obtained by sampling a series of statistically equivalent drops. This approach also avoids any probe interference during the drop evolution process.     

Re-examining the causal structure of information technology impact research

About 20 years ago, Markus and Robey noted that most research on IT impacts had been guided by deterministic perspectives and had neglected to use an emergent perspective, which could account for contradictory findings. They further observed that most research in this area had been carried out using variance theories at the expense of process theories. Finally, they suggested that more emphasis on multilevel theory building would likely improve empirical reliability. In this paper, we reiterate the observations and suggestions made by Markus and Robey on the causal structure of IT impact theories and carry out an analysis of empirical research published in four major IS journals, Management Information Systems Quarterly (MISQ), Information Systems Research (ISR), the European Journal of Information Systems (EJIS), and Information and Organization (I&O), to assess compliance with those recommendations. Our final sample consisted of 161 theory-driven articles, accounting for approximately 21% of all the empirical articles published in these journals. Our results first reveal that 91% of the studies in MISQ, ISR, and EJIS focused on deterministic theories, while 63% of those in I&O adopted an emergent perspective. Furthermore, 91% of the articles in MISQ, ISR, and EJIS adopted a variance model; this compares with 71% from I&O that applied a process model. Lastly, mixed levels of analysis were found in 14% of all the surveyed articles. Implications of these findings for future research are discussed.     

The Influence of the Internet on European Journalism

This study investigates how European journalists evaluate the changes that have occurred in their profession since the Internet has been integrated in newsrooms. How do journalists perceive the features and innovations associated with the Internet? What are the principal changes in the profession? Do practitioners believe that the quality of journalism has been raised or lowered? To answer to these research questions, we carried out a survey across 11 European countries–Cyprus, Estonia, Finland, Greece, Ireland, Italy, Lithuania, United Kingdom, Slovenia, Spain, Sweden–of 239 journalists, working for 40 of the most‐read print/online news outlets in these countries. The survey shows that the opportunity to use the Internet to reinforce the social functions of journalism has not been fully recognised.     

Optimal sampling for the estimation of dispersion parameters in soil columns using an Iterative Genetic Algorithm

In groundwater modelling, an appropriate soil characterization is strongly recommended to evaluate both the fate and transport of solutes and the performance of groundwater remediation criterion, though parameter estimation techniques are often blocked by several inherent difficulties (i.e. ill-posedness and insufficient quantity and quality of observation data). In this paper, an iterative decision model is built and tested in order to locate the position of a fixed number of sample points in a soil column experiment to obtain optimal parameter estimation (OPE), minimizing the parametric uncertainty and the overall cost of the experimental campaign. Starting from an initial guess of chosen points (given by a fraction of the total disposable ones), an Iterative Genetic Algorithm (IGA) is capable of finding the best points able to minimize a first-order approximation of the parameter covariance matrix. The parameter estimates are updated under a Bayesian scheme, using exclusively the observations collected after the earlier run of minimization, and the iterative process stops when the imposed convergence criterion based on the parameter values is reached. An important contribution of this work is the development of an effective direct search algorithm (IGA) for solving the sampling network optimization problem at a laboratory scale.     

Reducing false positives in anomaly detectors through fuzzy alert aggregation

In this paper we focus on the aggregation of IDS alerts, an important component of the alert fusion process. We exploit fuzzy measures and fuzzy sets to design simple and robust alert aggregation algorithms. Exploiting fuzzy sets, we are able to robustly state whether or not two alerts are “close in time”, dealing with noisy and delayed detections. A performance metric for the evaluation of fusion systems is also proposed. Finally, we evaluate the fusion method with alert streams from anomaly-based IDS.