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{Summary: We consider a new class of consistent semi-parametric estimators of a negative extreme value index, based on the set of the $k$ largest observations. This class of estimators depends on a control or tuning parameter, which enables us to have access to an estimator with a null second-order component of asymptotic bias, and with a rather interesting mean squared error, as a function of $k$. We study the consistency and asymptotic normality of the proposed estimators. Their finite sample behaviour is obtained through Monte Carlo simulation.}

Many errors in spreadsheet formulas can be avoided if spreadsheets are built automatically from higher-level models that can encode and enforce consistency constraints. However, designing such models is time consuming and requires expertise beyond the knowledge to work with spreadsheets. Legacy spreadsheets pose a particular challenge to the approach of controlling spreadsheet evolution through higher-level models, because the need for a model might be overshadowed by two problems: (A) The benefit of creating a spreadsheet is lacking since the legacy spreadsheet already exists, and (B) existing data must be transferred into the new model-generated spreadsheet. To address these problems and to support the model-driven spreadsheet engineering approach, we have developed a tool that can automatically infer ClassSheet models from spreadsheets. To this end, we have adapted a method to infer entity/relationship models from relational database to the spreadsheets/ClassSheets realm. We have implemented our techniques in the HAEXCEL framework and integrated it with the ViTSL/Gencel spreadsheet generator, which allows the automatic generation of refactored spreadsheets from the inferred ClassSheet model. The resulting spreadsheet guides further changes and provably safeguards the spreadsheet against a large class of formula errors. The developed tool is a significant contribution to spreadsheet (reverse) engineering, because it fills an important gap and allows a promising design method (ClassSheets) to be applied to a huge collection of legacy spreadsheets with minimal effort.

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This paper analyses and compares the dynamic behavior of superelastic shape memory alloy (SMA) systems based on two different constitutive models. The first model, although being able to describe the response of the material to complex uniaxial loading histories, is temperature and rate independent. The second model couples the mechanical and kinetic laws of the material with a balance equation considering the thermal effects. After numerical validation and calibration, the behavior of these two models is tested in single degree of freedom dynamic systems, with SMAs acting as restoring elements. Different dynamic loads are considered, including artificially generated seismic actions, in a numerical model of a railway viaduct. Finally, it is shown that, in spite of its simplicity, the temperature- and rate-independent model produces a set of very satisfying results. This, together with its robustness and straightforward computational implementation, yields a very appealing numerical tool to simulate superelastic passive control applications.

Transactional Memory allows programmers to reduce the number of synchronization errors introduced in concurrent programs, but does not ensures its complete elimination. This paper proposes a pattern matching based approach to the static detection of atomicity violation, based on a path-sensitive symbolic execution method to model four anomalies that may affect Transactional Memory programs. The proposed technique may be used to to bring to programmer's attention pairs of transactions that the programmer has mis-specified, and should have been combined into a single transaction. The algorithm first traverses the AST tree, removing all the non-transactional blocks and generating a trace tree in the path sensitive manner for each thread. The trace tree is a Trie like data structure, where each path from root to a leaf is a list of transactions. For each pair of threads, erroneous patterns involving two consecutive transactions are then checked in the trace tree. Results allow to conclude that the proposed technique, although triggering a moderate number of false positives, can be successfully applied to Java programs, correctly identifying the vast majority of the relevant erroneous patterns.

Dispersive liquid–liquid microextraction (DLLME) coupled with gas chromatography–mass spectrometry (GC–MS) was applied for the determination of 11 alkylphenols in eluates of chars produced in the co-pyrolysis of different wastes.

The optimized DLLME procedure, 4 mL of sample solution, 15 μL of trichloroethylene as extraction solvent, 1 mL of acetone as dispersion solvent and addition of 15% (w/v) of NaCl, was validated. Under the optimum conditions, the enrichment factors were in the range of 82–180. Calibration curves were constructed for each analyte in pure water in the concentration range of 0.5–8 μg/L with correlation coefficients higher than 0.999. The limits of detection were between 0.07 and 0.17 μg/L. The repeatability of the method was evaluated using water samples fortified with the analyte mixture at two concentration levels: the relative standard deviation (RSD) values were between 3.7% and 8.0% for a concentration of 0.5 μg/L, and between 4.2% and 6.4% for a concentration of 3 μg/L. The recoveries of the analytes evaluated by fortification of real eluate samples were in the range of 67.9–97.9% for eluate 1 (obtained from a decontaminated char) and in the range of 61.9–101.4% for eluate 2 (obtained from the untreated char). o-Methylphenol presented low recoveries for both eluates showing a possible matrix effect. The results obtained show that this method is adequate for the determination of alkylphenols in environmental aqueous samples and presents itself as a fast and inexpensive technique, using minor amounts of organic solvents.

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The traditional methodology used in civil engineering measurements requires a lot of equipment and a very complex procedure especially if the number of target points increase. Since the beginning of the current century, several studies have been conducted in the area of photogrametry using digital image
correlation associated with block motion algorithms to estimate displacements in reinforced concrete (RC) beams during a load test. Using image processing techniques it is possible to measure the whole area of interest and not only a few points of the tests materials. In this paper, block-matching algorithms are used in order to compare the results from photogrametry techniques and the data obtained with linear voltage displacement transducer (LVDT) sensors during the load tests of RC beams, which are very common to find in civil engineering laboratories.

Domain Specic Languages (DSLs) can contribute to increment productivity, while reducing the required maintenance and programming expertise. We hypothesize that Software Languages Engineering (SLE) developers consistently skip, or relax, Language Evaluation. Based on the experience of engineering other types of software products, we assume that this may potentially lead to the deployment of inadequate languages. The fact that the languages already deal with concepts from the problem domain, and not the solution domain, is not enough to validate several issues at stake, such as its expressiveness, usability,
effectiveness, maintainability, or even the domain expert's productivity while using them. We present a systematic review on articles published in top ranked venues, from 2001 to 2008, which report DSLs' construction, to characterize the common practice. This work conrms our initial hypothesis and lays the ground for the discussion on how to include a systematic approach to DSL evaluation in the SLE process.

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Spreadsheets are widely used by end users, and studies have shown that most end-user spreadsheets 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 systematic empirical study to assess the effectiveness and efficiency of this approach. A set of spreadsheet end users worked with two different model-based spreadsheets, and we present and analyze the results achieved.