SORs (superoxide reductases) are enzymes involved in bacterial resistance to reactive oxygen species, catalysing the reduction of superoxide anions to hydrogen peroxide. So far three structural classes have been identified. Class I enzymes have two ironcentre-containing domains. Most studies have focused on the catalytic iron site (centre II), yet the role of centre I is poorly understood. The possible roles of this iron site were approached by an integrated study using both classical and fast kinetic measurements, as well as direct electrochemistry. A new heterometallic form of the protein with a zinc-substituted centre I, maintaining the iron active-site centre II, was obtained, resulting in a stable derivative useful for comparison with the native all-iron from. Second-order rate constants for the electron transfer between reduced rubredoxin and the different SOR forms were determined to be 2.8 x 10(7) M(-1) . s(-1) and 1.3 x 10(6) M(-1) . s(-1) for SOR(Fe(IIII)-Fe(II)) and for SOR(Fe(IIII)-Fe(III)) forms respectively, and 3.2 x 10(6) M(-1) s(-1) for the SOR(Zn(II)-Fe(III)) form. The results obtained seem to indicate that centre I transfers electrons from the putative physiological donor rubredoxin to the catalytic active iron site (intramolecular process). In addition, electrochemical results show that conformational changes are associated with the redox state of centre I, which may enable a faster catalytic response towards superoxide anion. The apparent rate constants calculated for the SOR-mediated electron transfer also support this observation.

Toxic amides, such as acrylamide, are potentially harmful to Human health, so there is great interest in the fabrication of compact and economical devices to measure their concentration in food products and effluents. The CHEmically Modified Field Effect Transistor (CHEMFET) based on amorphous silicon technology is a candidate for this type of application due to its low fabrication cost. In this article we have used a semi-empirical model of the device to predict its performance in a solution of interfering ions. The actual semiconductor unit of the sensor was fabricated by the PECVD technique in the top gate configuration. The CHEMFET simulation was performed based on the experimental current voltage curves of the semiconductor unit and on an empirical model of the polymeric membrane. Results presented here are useful for selection and design of CHEMFET membranes and provide an idea of the limitations of the amorphous CHEMFET device. In addition to the economical advantage, the small size of this prototype means it is appropriate for in situ operation and integration in a sensor array.

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Two cyclen-derived Gd probes, [Gd-DOTAM](3+) and [Gd-DOTP](5-) (DOTAM = 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetamide; DOTP = 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetrakis(methylenephosphonate)), were assessed as paramagnetic relaxation enhancement (PRE)-inducing probes for characterization of protein-protein interactions. Two proteins, Desulfovibrio gigas rubredoxin and Desulfovibrio gigas cytochrome c(3), were used as model partners. In a (1)H NMR titration it was shown that [Gd-DOTP](5-) binds to cytochrome c(3) near heme IV, causing pronounced PREs, characterized by line width broadenings of the heme methyl resonances at ratios as low as 0.08. A K(d) of 23 +/- 1 muM was calculated based on chemical shift perturbation of selected heme methyl resonances belonging to three different heme groups, caused by allosteric effects upon [Gd-DOTP](5-) binding to cytochrome c(3) at a molar ratio of 2. The other probe, [Gd-DOTAM](3+), caused PREs on a well-defined patch near the metal center of rubredoxin (especially the patch constituted by residues D19-G23 and W37-S45, which broaden beyond detection). This effect was partially reversed for some resonances (C6-Y11, in particular) when cytochrome c(3) was added to this system. Both probes were successful in causing reversible PREs at the partner binding site, thus showing to be good probes to identify partners' binding sites and since the interaction is reversible to structurally characterize protein complexes by better defining the complex interface.

Chemical Physics Letters, 516 (2011) 149-153. doi:10.1016/j.cplett.2011.10.001

Respiratory nitric oxide reductase (NOR) was purified from membrane extract of Pseudomonas (Ps.) nautica cells to homogeneity as judged by polyacrylamide gel electrophoresis. The purified protein is a heterodimer with subunits of molecular masses of 54 and 18 kDa. The gene encoding both subunits was cloned and sequenced. The amino acid sequence shows strong homology with enzymes of the cNOR class. Iron/heme determinations show that one heme c is present in the small subunit (NORC) and that approximately two heme b and one non-heme iron are associated with the large subunit (NORB), in agreement with the available data for enzymes of the cNOR class. Mossbauer characterization of the as-purified, ascorbate-reduced, and dithionite-reduced enzyme confirms the presence of three heme groups (the catalytic heme b(3) and the electron transfer heme b and heme c) and one redox-active non-heme Fe (Fe(B)). Consistent with results obtained for other cNORs, heme c and heme b in Ps. nautica cNOR were found to be low-spin while Fe(B) was found to be high-spin. Unexpectedly, as opposed to the presumed high-spin state for heme b(3), the Mossbauer data demonstrate unambiguously that heme b(3) is, in fact, low-spin in both ferric and ferrous states, suggesting that heme b(3) is six-coordinated regardless of its oxidation state. EPR spectroscopic measurements of the as-purified enzyme show resonances at the g approximately 6 and g approximately 2-3 regions very similar to those reported previously for other cNORs. The signals at g = 3.60, 2.99, 2.26, and 1.43 are attributed to the two charge-transfer low-spin ferric heme c and heme b. Previously, resonances at the g approximately 6 region were assigned to a small quantity of uncoupled high-spin Fe(III) heme b(3). This assignment is now questionable because heme b(3) is low-spin. On the basis of our spectroscopic data, we argue that the g = 6.34 signal is likely arising from a spin-spin coupled binuclear center comprising the low-spin Fe(III) heme b(3) and the high-spin Fe(B)(III). Activity assays performed under various reducing conditions indicate that heme b(3) has to be reduced for the enzyme to be active. But, from an energetic point of view, the formation of a ferrous heme-NO as an initial reaction intermediate for NO reduction is disfavored because heme [FeNO](7) is a stable product. We suspect that the presence of a sixth ligand in the Fe(II)-heme b(3) may weaken its affinity for NO and thus promotes, in the first catalytic step, binding of NO at the Fe(B)(II) site. The function of heme b(3) would then be to orient the Fe(B)-bound NO molecules for the formation of the N-N bond and to provide reducing equivalents for NO reduction.

Concurrent programs may suffer from concurrency anomalies that may lead to erroneous and unpredictable program behaviors. To ensure program correctness, these anomalies must be diagnosed and corrected. This paper addresses the detection of both low- and high-level anomalies in the Transactional Memory setting. We propose a static analysis procedure and a framework to address Transactional Memory anomalies. We start by dealing with the classic case of low-level dataraces, identifying concurrent accesses to shared memory cells that are not protected within the scope of a memory transaction. Then, we address the case of high-level dataraces, bringing the programmer's attention to pairs of memory transactions that were misspecified and should have been combined into a single transaction. Our framework was applied to a set of programs, collected form different sources, containing well known low- and high-level anomalies. The framework demonstrated to be accurate, confirming the effectiveness of using static analysis techniques to precisely identify concurrency anomalies in Transactional Memory programs.

Purpose – This paper aims to explore the divergences and commitments between the lean, agile, resilient and green paradigms while investigating the effect of paradigms' practices within supply chain attributes.
Design/methodology/approach – A conceptual model with lean, agile, resilient and green practices and supply chain management attributes is proposed. Causal diagrams were used to represent the relationships between paradigm practices and supply chain attributes. The four diagrams were aggregated to build the conceptual model.
Findings – The conceptual model allows for the identification of synergies and divergences resulting from the paradigms practices implementation. The synergies between paradigms are related to “information frequency” and “integration level” increasing as well as reduction of “production lead time” and “transportation lead time”. However, other supply chain attributes such as “capacity surplus”, “inventory level” and “replenishment frequency” are affected in opposite directions by some paradigms creating divergences.
Research limitations/implications – The model relationships were established using an anecdotal approach derived from the literature review, reflecting only a partial view of supply chain dynamics. More research related to other supply chain attributes and/or paradigm practices, and validation of the proposed relationships is suggested.
Practical implications – The proposed model can be the basis for further research in lean, agile, resilient and green paradigms, contributing to a more sustainable and competitive lean supply chain with the necessary agility toward a quick response, resiliency to disruptions, and harmonization with the ecologic and environmental aspects. Originality/value – To the authors' knowledge this paper is the first to provide an understanding about the tradeoffs among lean, agile, resilient and green supply chain paradigms.

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 less errors and to work faster.

Spreadsheetsarewidelyusedandstudiesshowthatmostoftheexisting ones contain non-trivial errors. To improve end-users productivity, recent research proposes the use of a model-driven engineering approach to spreadsheets. In this paper we conduct the first empirical study to assess the effectiveness and efficiency of this approach. A set of spreadsheet end users worked with two different model-based spreadsheets. We present and analyze here the results achieved.

High temperature superconducting (HTS) machines are recognized to offer several advantageous features when comparing to conventional ones. Amongst these, highlights the decrease in weight and volume of the machines, due to increased current density in conductors or the absence of iron slots' teeth; or the decrease in AC losses and consequent higher efficiency of the machines, even accounting for cryogenics. These concepts have been already demonstrated and some machines have even achieved commercial stage. In this paper, several alternative approaches are applied to electrical motors employing HTS materials. The first one is an all superconducting linear motor, where copper conductors and permanent magnets are replaced by Bi-2223 windings and trapped flux magnets, taking advantage of stable levitation due to flux pinning, higher current densities and higher excitation field. The second is an induction disk motor with Bi-2223 armature, where iron, ironless and hybrid approaches are compared. Finally, an innovative command strategy, consisting of an electronically variable pole pairs' number approach, is applied to a superconducting hysteresis disk motor. All these concepts are being investigated and simulation and experimental results are presented.

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