Phenanthroimidazoles as fluorimetric and colourimetric chemosensors in aqueous solution

2,4,5-Triaryl-imidazoles are versatile compounds with application in medicine, due to their biological activity, and materials sciences, for their interesting optical properties. These properties can be tuned by careful selection of substituents at positions 2, 4 and 5: replacement of the aryl group by an heterocyclic group results in larger π-conjugated systems with improved optical properties for application in nonlinear optics, OLEDs, DNA intercalators, and chemosensors. Moreover, it is expected that introducing more conjugation and rigidity into the resulting system will further improve its properties. The development of chromo/fluorescent probes that are capable of detecting ions with high sensitivity and selectivity in aqueous media is currently a topic of strong interest and the design of heteroditopic receptors that contain two or more different binding sites for the simultaneous complexation of cationic and anionic guests is a emerging field of supramolecular chemistry. In this communication, we report the synthesis of new phenanthroimidazoles substituted at position 2 with arylthienyl or arylfuryl moieties possessing substituents of different electronic character, in order to tune the chromo/fluoro response in the presence of relevant anions and metal cations. Their photophysical properties and chemosensory ability were studied in acetonitrile and mixtures of acetonitrile and water, and selective detection of cyanide was achieved in aqueous mixtures for some of the derivatives.

From a NoSQL data source to a business intelligence solution: An experiment

We are living in the era of Big Data. A time which is characterized by the continuous creation of vast amounts of data, originated from different sources, and with different formats. First, with the rise of the social networks and, more recently, with the advent of the Internet of Things (IoT), in which everyone and (eventually) everything is linked to the Internet, data with enormous potential for organizations is being continuously generated. In order to be more competitive, organizations want to access and explore all the richness that is present in those data. Indeed, Big Data is only as valuable as the insights organizations gather from it to make better decisions, which is the main goal of Business Intelligence. In this paper we describe an experiment in which data obtained from a NoSQL data source (database technology explicitly developed to deal with the specificities of Big Data) is used to feed a Business Intelligence solution.

Step towards of a homemade business intelligence solution: A case study in textile industry

Nowadays, organizations are increasingly looking to invest in business intelligence solutions, mainly private companies in order to get advantage over its competitors, however they do not know what is necessary. Business intelligence allows an analysis of consolidated information in order to obtain more specific outlets and certain indications in order to support the decision making process. You can take the right decision based on the data collected from different information systems present in the organization and outside of them. The textile sector is a sector where concept of Business Intelligence it is not many explored yet. Actually there are few textile companies that have a BI platform. Thus, the article objective is present an architecture and show all the steps by which companies need to spend to implement a successful free homemade Business Intelligence system. As result the proposed approach it was validated using real data aiming assess the steps defined.

Comparison of different numerical methods for the solution of the time-fractional reaction-diffusion equation with variable diffusion coefficient

In this work we perform a comparison of two different numerical schemes for the solution of the time-fractional diffusion equation with variable diffusion coefficient and a nonlinear source term. The two methods are the implicit numerical scheme presented in [M.L. Morgado, M. Rebelo, Numerical approximation of distributed order reaction- diffusion equations, Journal of Computational and Applied Mathematics 275 (2015) 216-227] that is adapted to our type of equation, and a colocation method where Chebyshev polynomials are used to reduce the fractional differential equation to a system of ordinary differential equations

Project management under uncertainty: a study on solution methods

Project Management involves onetime endeavors that demand for getting it right the first time. On the other hand, project scheduling, being one of the most modeled project management process stages, still faces a wide gap from theory to practice. Demanding computational models and their consequent call for simplification, divert the implementation of such models in project management tools from the actual day to day project management process. Special focus is being made to the robustness of the generated project schedules facing the omnipresence of uncertainty. An "easy" way out is to add, more or less cleverly calculated, time buffers that always result in project duration increase and correspondingly, in cost. A better approach to deal with uncertainty seems to be to explore slack that might be present in a given project schedule, a fortiori when a non-optimal schedule is used. The combination of such approach to recent advances in modeling resource allocation and scheduling techniques to cope with the increasing flexibility in resources, as can be expressed in "Flexible Resource Constraint Project Scheduling Problem" (FRCPSP) formulations, should be a promising line of research to generate more adequate project management tools. In reality, this approach has been frequently used, by project managers in an ad-hoc way.

Local non-negative initial data scalar characterization of the Kerr solution

For any vacuum initial data set, we define a local, non-negative scalar quantity which vanishes at every point of the data hypersurface if and only if the data are Kerr initial data. Our scalar quantity only depends on the quantities used to construct the vacuum initial data set which are the Riemannian metric defined on the initial data hypersurface and a symmetric tensor which plays the role of the second fundamental form of the embedded initial data hypersurface. The dependency is algorithmic in the sense that given the initial data one can compute the scalar quantity by algebraic and differential manipulations, being thus suitable for an implementation in a numerical code. The scalar could also be useful in studies of the non-linear stability of the Kerr solution because it serves to measure the deviation of a vacuum initial data set from the Kerr initial data in a local and algorithmic way.

Hot-dip galvanized steel dip-coatedwith ureasilicate hybrid in simulated concrete pore solution: Assessment of coating morphology and corrosion protection efficiency

The barrier effect and the performance of an organic–inorganic hybrid (OIH) sol–gel coating are highlydependent on the coating deposition method as well as processing conditions. In this work, studies onthe influence of experimental parameters using the dip coating method were performed. Factors suchas residence time (Rt), a curing step between each dip step and the number of layers of sol–gel OIHfilms deposited on HDGS to prevent corrosion in highly alkaline environments were studied. These OIHcoatings were obtained using a functionalized siloxane, 3-isociantepropyltriethoxysilane that reactedwith a diamino-functionalized oligopolymer (Jeffamine®D-230). The barrier efficiency of OIH coatings insimulated concrete pore solutions (SCPS) was assessed in the first moments of contact, by electrochemicalimpedance spectroscopy and potentiodynamic methods. The durability and stability of the OIH coatings inSCPS was monitored during eight days by macrocell current density. The morphological characterizationof the surface was performed by scanning electronic microscopy before and after exposure to SCPS.Glow discharge optical emission spectroscopy was used to obtain quantitative composition profiles toinvestigate the thickness of the OIH coatings as a function of the number of layers deposited and theinfluence of the Rt in the coating thickness.

Ureasilicate hybrid coatings for corrosion protection of galvanized steel in chloride-contaminated simulated concrete pore solution

Organic-inorganic hybrid (OIH) sol-gel coatings based on ureasilicates (U(X)) have promising properties for use as eco-friendly coatings on hot dip galvanized steel (HDGS) and may be considered potential substitutes for pre-treatment systems containing Cr(VI). These OIH coatings reduce corrosion activity during the initial stages of contact of the HDGS samples with highly alkaline environments (cementitious media) and allow the mitigation of harmful effects of an initial excessive reaction between cement pastes and the zinc layer. However, the behavior of HDGS coated with U(X) in the presence of chloride ions has never been reported. In this paper, the performance of HDGS coated with five different U(X) coatings was assessed by electrochemical measurements in chloride-contaminated simulated concrete pore solution (SCPS). U(X) sol-gel coatings were produced and deposited on HDGS by a dip coating method. The coatings performance was evaluated by electrochemical impedance spectroscopy, potentiodynamic polarization curves measurements, macrocell current density and polarization resistance in contact with chloride-contaminated SCPS. The SEM/EDS analyses of the coatings before and after the tests were also performed. The results showed that the HDGS samples coated with the OIH coatings exhibited enhanced corrosion resistance to chloride ions when compared to uncoated galvanized steel.