Analyzing the effects of transient faults into applications

As computer chips implementation technologies evolve to obtain more performance, those computer chips are using smaller components, with bigger density of transistors and working with lower power voltages. All these factors turn the computer chips less robust and increase the probability of a transient fault. Transient faults may occur once and never more happen the same way in a computer system lifetime. There are distinct consequences when a transient fault occurs: the operating system might abort the execution if the change produced by the fault is detected by bad behavior of the application, but the biggest risk is that the fault produces an undetected data corruption that modifies the application final result without warnings (for example a bit flip in some crucial data). With the objective of researching transient faults in computer system’s processor registers and memory we have developed an extension of HP’s and AMD joint full system simulation environment, named COTSon. This extension allows the injection of faults that change a single bit in processor registers and memory of the simulated computer. The developed fault injection system makes it possible to: evaluate the effects of single bit flip transient faults in an application, analyze an application robustness against single bit flip transient faults and validate fault detection mechanism and strategies.

Analyzing aggregate real exchange rate persistence through the lens of sectoral data

In this paper we analyze the persistence of aggregate real exchange rates (RERs) for a group of EU-15 countries by using sectoral data. The tight relation between aggregate and sectoral persistence recently investigated by Mayoral (2008) allows us to decompose aggregate RER persistence into the persistence of its different subcomponents. We show that the distribution of sectoral persistence is highly heterogeneous and very skewed to the right, and that a limited number of sectors are responsible for the high levels of persistence observed at the aggregate level. We use quantile regression to investigate whether the traditional theories proposed to account for the slow reversion to parity (lack of arbitrage due to nontradibilities or imperfect competition and price stickiness) are able to explain the behavior of the upper quantiles of sectoral persistence. We conclude that pricing to market in the intermediate goods sector together with price stickiness have more explanatory power than variables related to the tradability of the goods or their inputs.

Analyzing complexity in foreign language monologic oral production in a CLIL context

The study tested three analytic tools applied in SLA research (T-unit, AS-unit and Idea-unit) against FL learner monologic oral data. The objective was to analyse their effectiveness for the assessment of complexity of learners' academic production in English. The data were learners' individual productions gathered during the implementation of a CLIL teaching sequence on Natural Sciences in a Catalan state secondary school. The analysis showed that only AS-unit was easily applicable and highly effective in segmenting the data and taking complexity measures

Profitability, uncertainty and multi-product firm product proliferation: The Spanish car industry

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market. Keywords: Product introduction, entry, uncertainty, multiproduct firms, automobile JEL codes: L11, L13

Analyzing shapes as compositions of distances

We propose to analyze shapes as “compositions” of distances in Aitchison geometry asan alternate and complementary tool to classical shape analysis, especially when sizeis non-informative.Shapes are typically described by the location of user-chosen landmarks. Howeverthe shape – considered as invariant under scaling, translation, mirroring and rotation– does not uniquely define the location of landmarks. A simple approach is to usedistances of landmarks instead of the locations of landmarks them self. Distances arepositive numbers defined up to joint scaling, a mathematical structure quite similar tocompositions. The shape fixes only ratios of distances. Perturbations correspond torelative changes of the size of subshapes and of aspect ratios. The power transformincreases the expression of the shape by increasing distance ratios. In analogy to thesubcompositional consistency, results should not depend too much on the choice ofdistances, because different subsets of the pairwise distances of landmarks uniquelydefine the shape.Various compositional analysis tools can be applied to sets of distances directly or afterminor modifications concerning the singularity of the covariance matrix and yield resultswith direct interpretations in terms of shape changes. The remaining problem isthat not all sets of distances correspond to a valid shape. Nevertheless interpolated orpredicted shapes can be backtransformated by multidimensional scaling (when all pairwisedistances are used) or free geodetic adjustment (when sufficiently many distancesare used)

Profitability, uncertainty and multi-product firm product proliferation: The Spanish car industry

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market

The relevance of the Laplacian of intracule and extracule density distributions for analyzing electron-electron interactions in molecules

A topological analysis of intracule and extracule densities and their Laplacians computed within the Hartree-Fock approximation is presented. The analysis of the density distributions reveals that among all possible electron-electron interactions in atoms and between atoms in molecules only very few are located rigorously as local maxima. In contrast, they are clearly identified as local minima in the topology of Laplacian maps. The conceptually different interpretation of intracule and extracule maps is also discussed in detail. An application example to the C2H2, C2H4, and C2H6 series of molecules is presented

How does ownership structure invfluence bank risk? Analyzing the role of managerial incentives

This paper analyzes how ownership concentration and managerial incentives influences bank risk for a large sample of US banks over the period 1997-2007. Using 2SLS simultaneous equations models, we show that ownership concentration has a positive total effect on bank risk. This is the result of a positive direct effect, which reflects monitoring and opportunistic behavior, and a negative indirect effect, which works through the design of managerial incentive contracts and reflects shareholder preferences toward risk. Large shareholders reduce bank risk by reducing the sensitivity of CEO wealth to stock volatility (Vega) and by increasing the CEO pay-performance sensitivity (Delta). In addition, we show that the direct and indirect effect of ownership concentration on bank risk depends on the type of the largest shareholder (a family, a bank, a corporation or an institutional investor), as well as, on the total shareholding held by each type as a group. Our results suggest that the positive relation between ownership concentration and risk is not the result of preferences towards more risk. Rather, they point at opportunistic behavior of large shareholders.

Biana: a software framework for compiling biological interactions and analyzing networks

Background: The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties.Results: We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php.Conclusions: BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

The effects of structural reforms on productivity and profitability enhancing reallocation: Evidence from Colombia

Estimates for the U.S. suggest that at least in some sectors productivity enhancing reallocationis the dominant factor in accounting for producitivity growth. An open question, particularlyrelevant for developing countries, is whether reallocation is always productivity enhancing. Itmay be that imperfect competition or other barriers to competitive environments imply that thereallocation process is not fully e?cient in these countries. Using a unique plant-levellongitudinal dataset for Colombia for the period 1982-1998, we explore these issues byexamining the interaction between market allocation, and productivity and profitability.Moreover, given the important trade, labor and financial market reforms in Colombia during theearly 1990's, we explore whether and how the contribution of reallocation changed over theperiod of study. Our data permit measurement of plant-level quantities and prices. Takingadvantage of the rich structure of our price data, we propose a sequential mehodology to estimateproductivity and demand shocks at the plant level. First, we estimate total factor productivity(TFP) with plant-level physical output data, where we use downstream demand to instrumentinputs. We then turn to estimating demand shocks and mark-ups with plant-level price data, usingTFP to instrument for output in the inversedemand equation. We examine the evolution of thedistributions of TFP and demand shocks in response to the market reforms in the 1990's. We findthat market reforms are associated with rising overall productivity that is largely driven byreallocation away from low- and towards highproductivity businesses. In addition, we find thatthe allocation of activity across businesses is less driven by demand factors after reforms. Wefind that the increase in aggregate productivity post-reform is entirely accounted for by theimproved allocation of activity.

A comparison of mean phase difference and generalized least squares for analyzing single-case data

The present study focuses on single-case data analysis and specifically on two procedures for quantifying differences between baseline and treatment measurements The first technique tested is based on generalized least squares regression analysis and is compared to a proposed non-regression technique, which allows obtaining similar information. The comparison is carried out in the context of generated data representing a variety of patterns (i.e., independent measurements, different serial dependence underlying processes, constant or phase-specific autocorrelation and data variability, different types of trend, and slope and level change). The results suggest that the two techniques perform adequately for a wide range of conditions and researchers can use both of them with certain guarantees. The regression-based procedure offers more efficient estimates, whereas the proposed non-regression procedure is more sensitive to intervention effects. Considering current and previous findings, some tentative recommendations are offered to applied researchers in order to help choosing among the plurality of single-case data analysis techniques.

Analyzing peptides and proteins by mass spectrometry: principles and applications in proteomics

The study of proteins has been a key element in biomedicine and biotechnology because of their important role in cell functions or enzymatic activity. Cells are the basic unit of living organisms, which are governed by a vast range of chemical reactions. These chemical reactions must be highly regulatedin order to achieve homeostasis. Proteins are polymeric molecules that havetaken on the evolutionary process the role, along with other factors, of controlthese chemical reactions. Learning how proteins interact and control their up anddown regulations can teach us how living cells regulate their functions, as well asthe cause of certain anomalies that occur in different diseases where proteins areinvolved. Mass spectrometry (MS) is an analytical widely used technique to studythe protein content inside the cells as a biomarker point, which describesdysfunctions in diseases and increases knowledge of how proteins are working.All the methodologies involved in these descriptions are integrated in the fieldcalled Proteomics.

Analyzing hidden semantics in social bookmarking of open educational resources

Web 2.0 services such as social bookmarking allow users to manage and share the links they find interesting, adding their own tags for describingthem. This is especially interesting in the field of open educational resources, asdelicious is a simple way to bridge the institutional point of view (i.e. learningobject repositories) with the individual one (i.e. personal collections), thuspromoting the discovering and sharing of such resources by other users. In this paper we propose a methodology for analyzing such tags in order to discover hidden semantics (i.e. taxonomies and vocabularies) that can be used toimprove descriptions of learning objects and make learning object repositories more visible and discoverable. We propose the use of a simple statistical analysis tool such as principal component analysis to discover which tags createclusters that can be semantically interpreted. We will compare the obtained results with a collection of resources related to open educational resources, in order to better understand the real needs of people searching for open educational resources.

Impact of quality and environmental investment on business competitiveness and profitability: The case of travel agencies

Few studies have examined the combined effect of implementing quality and environmental management within the service sector. This void is more evident if we focus on segments in which small businesses predominate and even more so if we look for highly competitive sectors that are very variable and that have high business mortality. After analysing 198 surveys of Spanish travel agency managers using structural equations, it can be concluded that practices of quality management have a significant direct impact on business competitiveness but not on this business's financial results, at least directly. However, there is a significant relationship between environmental management practices and economic benefits. This article suggests that commitment to quality and the environment can allow small businesses in the service sector to have a competitive advantage that will separate surviving and ceased operations, particularly in sectors that are rapidly evolving and highly competitive.

Univariate versus multivariate modeling of panel data

Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.