n this paper, we present MDSHEET, a framework for the embedding, evolution and inference of spreadsheet models. This framework offers a model-driven software development mechanism for spreadsheet users.

Although spreadsheets can be seen as a flexible programming environment, they lack some of the concepts of regular programming languages, such as structured data types. This can lead the user to edit the spreadsheet in a wrong way and perhaps cause corrupt or redundant data. We devised a method for extraction of a relational model from a spreadsheet and the subsequent embedding of the model back into the spreadsheet to create a model-based spreadsheet programming environment. The extraction algorithm is specific for spreadsheets since it considers particularities such as layout and column arrangement. The extracted model is used to generate formulas and visual elements that are then embedded in the spreadsheet helping the user to edit data in a correct way. We present preliminary experimental results from applying our approach to a sample of spreadsheets from the EUSES Spreadsheet Corpus.

Spreadsheets can be viewed as programming languages for non-professional programmers. These so-called ``end-user'' programmers vastly outnumber professional programmers creating millions of new spreadsheets every year. As a programming language, spreadsheets lack support for abstraction, testing, encapsulation, or structured programming. As a result, and as numerous studies have shown, the high rate of production is accompanied by an alarming high rate of errors. Some studies report that up to 90% of real-world spreadsheets contain errors. After their initial creation, many spreadsheets turn out to be used for storing and processing increasing amounts of data and supporting increasing numbers of users over long periods of time, making them complicated systems. An emerging solution to handle the complex and evolving software systems is Model-driven Engineering (MDE). To consider models as first class entities and any software artifact as a model or a model element is one of the basic principles of MDE. We adopted some techniques from MDE to solve spreadsheet problems. Most spreadsheets (if not all) lack a proper specification or a model. Using reverse engineering techniques we are able to derive various models from legacy spreadsheets. We use functional dependencies (a formalism that allow us to define how some column values depend on other column values) as building blocks for these models. Models can be used for several spreadsheet improvements, namely refactoring, safe evolution, migration or even generation of edit assistance. The techniques presented in this work are available under the framework HAEXCEL that we developed. It is composed of online and batch tools, reusable HASKELL libraries and OpenOffice.org extensions. A study with several end-users was organized to survey the impact of the techniques we designed. The results of this study indicate that the models can bring great benefits to spreadsheet engineering helping users to commit fewer errors and to work faster.

Inductive superconducting fault current limiters have already demonstrated their technical viability in electrical networks. Its architecture and robustness make them potentially adequate for distribution networks, and this type of devices is considered as an enabling technology for the advent of embedded generation with renewable energy sources. In order to promote the growth and maturity of these superconducting technologies, fast design tools must be developed, allowing simulating devices with different materials in grids with diverse characteristics. This work presents advances in the development of such tool, which, at present stage, is an effective alternative to software simulations by finite elements methods, reducing dramatically computation time. The algorithms are now compared with experimental results from a laboratory scale prototype, showing the need to refine them.

Following our previous study on spin–rotation and shielding constants of the SF6 molecule, the rotational g factor and the magnetic susceptibility are calculated here, using ab initio methods to evaluate the electronic contribution to the nuclear hyperfine constants, and compared with experimental results. It is shown, for the first time, that the electronic component of the rotational g factor is proportional to a constant, which is given by a sum over electronic states. We also evaluate for the SF6 molecule the indirect, or electron-coupled spin–spin interaction, theoretically described by Ramsey, and show that it gives non-negligible corrections to direct coupling constants d1 and d2. The contributions of the terms included in this interaction (DSO, PSO, SD and FC) are also analysed.

This paper introduces a variability-aware methodology for the design of LC-VCOs in Nano-CMOS technologies. The complexity of the design as well as the necessity for having an environment offering the possibility for exploring design trade-offs has led to the development of design methodologies based multi-objective optimization procedures yielding the generation of Pareto-optimal surfaces. The efficiency of the process is granted by using analytical models for both passive and active devices. Although physics-based analytical expressions have been proposed for the evaluation of the lumped elements, the variability of the process parameters is usually ignored due to the difficulty to formalize it into an optimization performance index. The usually adopted methodology of considering only optimum solutions for the Pareto surface, may lead to pruning quasi-optimal solutions that may prove to be better, should their sensitivity to process parameter variation be accounted for. In this work we propose starting by generating an extended Pareto surface where both optimum and quasi-optimum solutions are considered. Finally information on the sensitivity to process parameter variations, is used for electing the best design solution.

To focus on processes of scientific and technological design and on how newly designed objects are used in different ways than initially intended (“displaced”), the organizers (the Society for Social Studies on Science-4S and the European Association of Studies on Science and Technology-EASST) chose the conference theme “Design and Displacement”. The concept of design here referred to innovative processes in forming new ideas and material objects. This general idea was reflected in a multitude of sub-topics.

The function of prion-like protein Doppel was suggested to be related to male fertility. In this study, the importance of ovine Doppel polypeptide on spermatozoa capacitation and fertilization was evaluated. After refolding, recombinant Doppel (rDpl) was supplemented with different concentrations (40, 80 or 190 ng/ml) to ovine spermatozoa during the capacitation process. In experiment 1, post-thawed ovine spermatozoa were incubated with different concentrations of rDpl during 1 h for swim-up, and changes in sperm motility, concentration, vigour, viability and capacitation were monitored (10 replicates). In experiment 2, the fertilization ability of post-swim-up spermatozoa incubated as above was tested through heterologous fertilization of bovine in vitro matured oocytes (n = 423, three replicates). Regardless of dosage, rDpl improved (p = 0.03) spermatozoa viability. Sperm individual motility and vigour were the highest (p = 0.04) for the group receiving 190 ng/ml rDpl. Sperm supplemented with the highest doses of rDpl achieved higher (p = 0.02) fertilization rates (56.0 +/- 3.0%) than control (39.1 +/- 2.2%) and 40 ng/ml rDpl (39.8 +/- 2.7%). Preliminary data suggest that Doppel protein may enhance in vitro spermatozoa fertilizing ability.

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This paper addresses an optimization-based approach for the design of RF integrated inductors. The methodology presented deals with the complexity of the design problem by formulating it as a multi-objective optimization. The multi-modal nature of the underlying functions combined with the need to be able to explore design trade-offs leads to the use of niching methods. This allows exploring not only the best trade-off solutions lying on the Pareto-optimum surface but also the quasi-optimum solutions that would be otherwise discarded. In this paper we take advantage of the niching properties of lbest PSO algorithm using ring topology to devise a simple optimizer able to find the local-optima. For the efficiency of the process analytical models are used for the passive/active devices. In spite the use of physics-based analytical expressions for the evaluation of the lumped elements, the variability of the process parameters is ignored in the optimization stage due to the significant computational burden it involves. Thus in the final stage both the Pareto-optimum solutions and the quasi-optimum solutions are evaluated with respect to the sensitivity to process parameter variations.

In this paper we present a quality model for spreadsheets, based on the ISO/IEC 9126 standard that defines a generic quality model for software. To each of the software characteristics defined in the ISO/IEC 9126, we associate an equivalent spreadsheet characteristic. Then, we propose a set of spreadsheet specific metrics to assess the quality of a spreadsheet in each of the defined characteristics. In order to obtain the normal distribution of expected values for a spreadsheet in each of the metrics that we propose, we have executed them against all spreadsheets in the large and widely used EUSES spreadsheet corpus. Then, we quantify each characteristic of our quality model after computing the values of our metrics, and we define quality scores for the different ranges of values. Finally, to automate the atribution of a quality score to a given spreadsheet, according to our quality model, we have integrated the computation of the metrics it includes in both a batch and a web-based tool.

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This tool demo paper presents SmellSheet Detective: a tool for automatically detecting bad smells in spreadsheets. We have defined a catalog of bad smells in spreadsheet data which was fully implemented in a reusable library for the manipulation of spreadsheets. This library is the building block of the SmellSheet Detective tool, that has been used to detect smells in large, real-world spreadsheet within the EUSES corpus, in order to validate and evolve our bad smells catalog.

Native agars from Gracilaria vermiculophylla produced in sustainable aquaculture systems (IMTA) were extracted under conventional (TWE) and microwave (MAE) heating. The optimal extracts from both processes were compared in terms of their properties. The agars’ structure was further investigated through Fourier transform infrared and NMR spectroscopy. Both samples showed a regular structure with an identical backbone, β-D-galactose (G) and 3,6-anhydro-α-L-galactose (LA) units; a considerable degree of methylation was found at C6 of the G units and, to a lesser extent, at C2 of the LA residues. The methylation degree in the G units was lower for MAEopt agar; the sulfate content was also reduced. MAE led to higher agar recoveries with drastic extraction time and solvent volume reductions. Two times lower values of [η] and Mv obtained for the MAEopt sample indicate substantial depolymerization of the polysaccharide backbone; this was reflected in its gelling properties; yet it was clearly appropriate for commercial application in soft-texture food products.

The accumulation of lead in several bones of Wistar rats with time was determined and compared Q3 for the different types of bones. Two groups were studied: a control group (n = 20), not exposed to lead and a contaminated group (n = 30), exposed to lead from birth, first indirectly through
mother’s milk, and then directly through a diet containing lead acetate in drinking water (0.2%). Rats age ranged from 1 to 11 months, with approximately 1 month intervals and each of the collections had 3 contaminated rats and 2 control rats. Iliac, femur, tibia–fibula and skull have been analysed by energy dispersive X-ray fluorescence technique (EDXRF). Samples of formaldehyde used to preserve the bone tissues were also analysed by Electrothermal Atomic Absorption (ETAAS), showing that there was no significant loss of lead from the tissue to the preservative. The bones mean lead concentration of exposed rats range from 100 to 300 mg g 1 while control rats never exceeded 10 mg g 1. Mean bone lead concentrations were compared and
the concentrations were higher in iliac, femur and tibia–fibula and after that skull. However, of all the concentrations in the different collections, only those in the skull were statistically Q4 significantly different (p o 0.05) from the other types of bones. Analysis of a radar chart also allowed us to say that these differences tend to diminish with age. The Spearman correlation test applied to mean lead concentrations showed strong and very strong positive correlations between
all different types of bones. This test also showed that mean lead concentrations in bones are negatively correlated with the age of the animals. This correlation is strong in iliac and femur and very strong in tibia–fibula and skull. It was also shown that the decrease of lead accumulation with age is made by three plateaus of accumulation,

This work reports a novel strategy to prepare affinity composite membranes using supercritical fluid technology. By blending molecularly imprinted polymeric particles with PMMA, a porous hybrid structure with affinity to the template molecule, bisphenol A, was prepared using a supercritical carbon dioxide (scCO2)-assisted method. Membranes were characterized in terms of morphology, mechanical performance and transport properties. The ability of the polymers and hybrid membranes to adsorb bisphenol A was tested in aqueous solutions and fitted to a linearized Langmuir equation, showing that adsorption takes place at homogeneous affinity binding sites within the imprinted surface. Filtration experiments showed that the imprinted hybrid membrane was able to adsorb higher amounts of template even in non-equilibrium dynamic binding conditions. The hybridization of the PMMA membrane herein reported conveys two important improvements over neat PMMA membrane: it introduced molecular affinity towards the template molecule and significantly increased the permeability of the porous structures, which are key parameters in processes that involve membranes. This technique could expand the applications of polymeric beads powders and enhance the efficiency of the membrane's transport properties. Our work presents a new method to confer affinity to a porous structure by immobilization of imprinted polymers, combining polymer synthesis and membrane formation using supercritical fluid technology.

Molecularly imprinted polymeric particles with molecular recognition towards Bisphenol A (BPA) were synthesized for the first time using the semi-covalent imprinting approach in supercritical carbon dioxide (scCO2). The material{'}s affinity to BPA was achieved by co-polymerizing ethylene glycol dimethacrylate (EGDMA) with a template-containing monomer{,} Bisphenol A dimethacrylate (BPADM) in scCO2. Bisphenol A is then cleaved from the polymeric matrix by hydrolysis with tetrabutylammonium hydroxide (n-Bu4OH) also in a supercritical environment{,} taking advantage of the high diffusivity of scCO2. The selectivity of the molecular imprinted polymer (MIP) was assessed by evaluating its capability to bind BPA in comparison with progesterone and [small alpha]-ethinylestradiol. In addition{,} the cross-linked particles were used to prepare a PMMA-based hybrid imprinted membrane by a scCO2-assisted phase inversion method. Results show that the incorporation of MIP particles was able to confer molecular affinity to BPA to the membrane and that at dynamic conditions of filtration{,} this imprinted porous structure was able to adsorb a higher amount of BPA than the corresponding non-imprinted hybrid membrane. Our work represents a valuable greener alternative to conventional methods{,} for the synthesis of affinity materials which are able to maintain molecular recognition properties in water.