Spreadsheets are considered to be the most widely used programming language in the world, and reports have shown that 90% of real-world spreadsheets contain errors. In this work, we try to identify spreadsheet smells, a concept adapted from software, which consists of a surface indication that usually corresponds to a deeper problem. Our smells have been integrated in a tool, and were computed for a large spreadsheet repository. Finally, the analysis of the results we obtained led to the refinement of our initial catalog.

Spreadsheets are widely recognized as popular programming systems with a huge number of spreadsheets being created every day. Also, spreadsheets are often used in the decision processes of profit-oriented companies. While this illustrates their practical importance, studies have shown that up to 90% of real-world spreadsheets contain errors. In order to improve the productivity of spreadsheet end-users, the software engineering community has proposed to employ model-driven approaches to spreadsheet development. In this paper we describe the evaluation of a bidirectional model-driven spreadsheet environment. In this environment, models and data instances are kept in conformity, even after an update on any of these artifacts. We describe the issues of an empirical study we plan to conduct, based on our previous experience with end-user studies. Our goal is to assess if this model-driven spreadsheet development framework does in fact contribute to improve the productivity of spreadsheet users.

In this paper we address the problem of uncertainty in the design and planning of a multi-period, multi-product closed loop supply chain, where the recovered products are end-of-life products that are disassembled and recycled. Uncertainty is explicitly modelled by considering customers’ demands and returns to be stochastic. A two–stage model is developed where first stage decisions concern the facility location while second stage decisions are the production planning of the supply chain. The integer L- shaped method was adopted as the solution tool and computational tests were performed on multi-period and multi-commodity networks randomly generated based on a reference case. A comparison between the proposed solution method and the straight use of the CPLEX is performed.

A set of methods defining an API (Application Programming Interface) are to be made thread safe; thus running any subset of these methods in parallel should not create races or deadlocks. Originally, the set of methods were not designed to be thread safe, so races and deadlocks are expected when running them in parallel. The number of possible interleavings when running methods from this API in parallel is huge, and this work focuses on the identification of the high level data races introduced by such interleavings. We propose an analysis that avoids the exhaustive exploration of all possible interleavings. For a concurrent program P, the closure of P, clos(P), is defined. Roughly speaking, we can say that the clos(P) is obtained by adding threads to P in such a way that high level data races resulting from running P in parallel to other programs are exposed statically. A set of methods representing the API is then modeled as a set of concurrent programs and their closure is analysed to identify high level data races. These high level data races are then inspected and removed to make the API thread safe. We illustrate the application of this methodology with a simple use case.

In this paper, the solution of the asymmetric eigenvalue complementarity problem (EiCP) is investigated by means of a variational inequality formulation. This problem is then solved by finding a stationary point of the gap function and the regularized gap function. A nonlinear programming formulation of the EiCP results from the gap function. A hybrid algorithm combining a projection technique and a modified Josephy-Newton method is proposed to solve the EiCP by finding a stationary point of the regularized gap function. Numerical results show that the proposed method can in general solve EiCPs efficiently.

{Zinc alkyl cations supported by N,N-BIAN-type bidentate ligands were found to be highly active in the immortal ROP of epsilon-caprolactone to yield narrowly disperse and chain length-controlled poly(epsilon-caprolactone), whether in solution or bulk polymerization conditions.}

{{A series of Ar-BIAN-based copper(I) complexes (where Ar-BIAN = bis(aryl) acenaphthenequinonediimine) were synthesised and characterised by H-1 and C-13 NMR spectroscopies, FT-IR spectroscopy, MALDI-TOF-MS spectrometry, cyclic voltammetry and single crystal X-ray diffraction. The bis-chelated complexes of general formula {[}Cu(Ar-BIAN)(2)]BF4 (where Ar = C6H5 (1), 4-iPrC(6)H(4) (3), 2-iPrC(6)H(4) (4)) were prepared by reaction of {[}Cu(NCMe)(4)]BF4 with two equivalents of the corresponding Ar-BIAN ligands, in dichloromethane, while the mono-chelated complexes of the type {[}Cu(Ar-BIAN)L2]BF4 (where Ar = 2,6-iPr(2)C(6)H(3)

Cancer is one of the main causes of death in the world and its incidence increases every day. Current treatments are insufficient and present many breaches. Hyperthermia is an old concept and since early it was established as a cancer treatment option, mainly in superficial cancers. More recently the concept of intracellular hyperthermia emerged wherein magnetic particles are concentrated at the tumor site and remotely heated using an applied magnetic field to achieve hyperthermic temperatures (42-45 degrees C). Many patents have been registered in this area since the year 2000. This review presents the most relevant information, organizing them according to the hyperthermic method used: 1) external RadioFrequency devices; 2) hyperthermic perfusion; 3) frequency enhancers; 4) apply heating to the target site using a catheter; 5) injection of magnetic and ferroelectric particles; 6) injection of magnetic nanoparticles that may carry a pharmacological active drug. The use of magnetic nanoparticles is a very promising treatment approach since it may be used for diagnostic and treatment. An ideal magnetic nanoparticle would be able to detect and diagnose the tumor, carry a pharmacological active drug to be delivered in the tumor site, apply hyperthermia through an external magnetic field and allow treatment monitoring by magnetic resonance imaging.

A gene encoding Bfr (bacterioferritin) was identified and isolated from the genome of Desulfovibrio vulgaris cells, and overexpressed in Escherichia coli. In vitro, H2O2 oxidizes Fe2+ ions at much higher reaction rates than O-2. The H2O2 oxidation of two Fe2+ ions was proven by Mossbauer spectroscopy of rapid freeze-quenched samples. On the basis of the Mossbauer parameters of the intermediate species we propose that D. vulgaris Bfr follows a mineralization mechanism similar to the one reported for vertebrate H-type ferritins subunits, in which a diferrous centre at the ferroxidase site is oxidized to diferric intermediate species, that are subsequently translocated into the inner nanocavity. D. vulgaris recombinant Bfr oxidizes and stores up to 600 iron atoms per protein. This Bfr is able to bind DNA and protect it against hydroxyl radical and DNase deleterious effects. The use of H2O2 as an oxidant, combined with the DNA binding and protection activities, seems to indicate a DPS (DNA-binding protein from starved cells)-like role for D. vulgaris Bfr.