Differentiation of Staphylococci from Iberian dry fermented sausages by protein fingerprinting

The Staphylococci populations in different types of Iberian dry fermented sausages from central-west Spain were identified. A simple electrophoretic method of whole-cell proteins and extracellular protein profiling was evaluated for speed of identification. This study was correlated with a 16S rRNA gene sequence analysis and biochemical identification by API Staph. A total of 81 isolates were identified by SDS-PAGE of the whole-cell proteins. These showed stable profiles in the range 99-14kDa that were clearly different for the different species, and were grouped into clusters together with the profiles of the eight reference strains. SDS-PAGE of the extracellular protein extracts provided additional characteristic banding patterns for the characterization of the Staphylococcus species present. The whole-cell SDS-PAGE showed that the predominant species was Staphylococcus saprophyticus (61.7%) followed by Staphylococcus aureus (19.7%). The identifications were confirmed by the 16S rRNA gene sequencing and by a BLAST search of the GenBank database. However, the API Staph biochemical identifications were frequently erroneous at the species level. In sum, SDS-PAGE analysis showed itself to be rapid and accurate in identifying the most commonly encountered Staphylococcus isolates in dry fermented sausages.     

Effect of Trichoderma asperellum on Wheat Plants’ Biochemical and Molecular Responses,and Yield under Different Water Stress Conditions

Eight Trichoderma strains were evaluated for their potential to protect wheat seedlings against severe (no irrigation within two weeks) water stress (WS). Considering the plant fresh weight and phenotype, T. asperellum T140, which displays 1-aminocyclopropane-1-carboxylic acid deaminase activity and which is able to produce several phytohormones, was selected. The molecular and biochemical results obtained from 4-week-old wheat seedlings linked T140 application with a downregulation in the WS-response genes, a decrease in antioxidant activities, and a drop in the proline content, as well as low levels of hydrogen peroxide and malondialdehyde in response to severe WS. All of these responses are indicative of T140-primed seedlings having a higher tolerance to drought than those that are left untreated. A greenhouse assay performed under high nitrogen fertilization served to explore the long-term effects of T140 on wheat plants subjected to moderate (halved irrigation) WS. Even though all of the plants showed acclimation to moderate WS regardless of T140 application, there was a positive effect exerted by T. asperellum on the level of tolerance of the wheat plants to this stress. Strain T140 modulated the expression of a plant ABA-dependent WS marker and produced increased plant superoxide dismutase activity, which would explain the positive effect of Trichoderma on increasing crop yields under moderate WS conditions. The results demonstrate the effectiveness of T. asperellum T140 as a biostimulant for wheat plants under WS conditions, making them more tolerant to drought.     

Improving the training time of support vector regression algorithms through novel hyper-parameters search space reductions

The selection of hyper-parameters in support vector machines (SVM) is a key point in the training process of these models when applied to regression problems. Unfortunately, an exact method to obtain the optimal set of SVM hyper-parameters is unknown, and search algorithms are usually applied to obtain the best possible set of hyper-parameters. In general these search algorithms are implemented as grid searches, which are time consuming, so the computational cost of the SVM training process increases considerably. This paper presents a novel study of the effect of including reductions in the range of SVM hyper-parameters, in order to reduce the SVM training time, but with the minimum possible impact in its performance. The paper presents reduction in parameter C, by considering its relation with the rest of SVM hyper-parameters (γ and ε), through an approximation of the SVM model. On the other hand, we use some characteristics of the Gaussian kernel function and a previous result in the literature to obtain novel bounds for γ and ε hyper-parameters. The search space reductions proposed are evaluated in different regression problems from UCI and StatLib databases. All the experiments carried out applying the popular LIBSVM solver have shown that our approach reduces the SVM training time, maintaining the SVM performance similar to when the complete range in SVM parameters is considered.     

Brain fMRI reactivity to smoking-related images before and during extended smoking abstinence.

[Correction Notice: An erratum for this article was reported in Vol 18(3) of Experimental and Clinical Psychopharmacology (see record 2010-11933-011). In the article the authors find it necessary to redefine the thresholding procedure used for data analyses, due to problems in the Brain Voyager software. This does not affect the main findings of the paper.] Reactivity to smoking-related cues may play a role in the maintenance of smoking behavior and may change depending on smoking status. Whether smoking cue-related functional MRI (fMRI) reactivity differs between active smoking and extended smoking abstinence states currently is unknown. We used fMRI to measure brain reactivity in response to smoking-related versus neutral images in 13 tobacco-dependent subjects before a smoking cessation attempt and again during extended smoking abstinence (52 ± 11 days) aided by nicotine replacement therapy. Prequit smoking cue induced fMRI activity patterns paralleled those reported in prior smoking cue reactivity fMRI studies. Greater fMRI activity was detected during extended smoking abstinence than during the prequit assessment subcortically in the caudate nucleus and cortically in prefrontal (BA 6, 9, 44, 46), primary somatosensory (BA 1, 2, 3), temporal (BA 22, 41, 42), parietal (BA 7, 40) anterior cingulate (BA 24, 32), and posterior cingulate (BA 31) cortex. These data suggest that during extended smoking abstinence, fMRI reactivity to smoking versus neutral stimuli persists in brain areas involved in attention, somatosensory processing, motor planning, and conditioned cue responding. In some brain regions, fMRI smoking cue reactivity is increased during extended smoking abstinence in comparison to the prequit state, which may contribute to persisting relapse vulnerability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ranking of departments and researchers within a university using two different databases: Web of Science versus Scopus

In this work, we compare the difference in the number of citations compiled with Scopus as opposed to the Web of Science (WoS) with the aim of analysing the agreement among the citation rankings generated by these databases. For this, we analysed the area of Health Sciences of the University of Navarra (Spain), composed of a total of 50 departments and 864 researchers. The total number of published works reflected in the WoS during the period 1999–2005 was 2299. For each work, the number of citations in both databases was recorded. The results indicate that the works received 14.7% more citations in Scopus than in WoS. In the departments, the difference was greater in the clinical ones than in the basic ones. In the case of the rankings of citations, it was found that both databases generate similar results. The Spearman and Kendall-Tau coefficients were higher than 0.9. It was concluded that the difference in the number of citations found did not correspond to the difference of coverage of WoS and Scopus.     

Unsupervised neural models for country and political risk analysis

This interdisciplinary research project focuses on relevant applications of Knowledge Discovery and Artificial Neural Networks in order to identify and analyze levels of country, business and political risk. Its main goal is to help business decision-makers understand the dynamics within the emerging market countries in which they operate. Most of the neural models applied in this study are defined within the framework of unsupervised learning. They are based on Exploratory Projection Pursuit, Topology Preserving Maps and Curvilinear Component Analysis. Two interesting real data sets are analyzed to empirically probe the robustness of these models. The first case study describes information from a significant sample of Spanish multinational enterprises (MNEs). It analyses data pertaining to such aspects as decisions over the location of subsidiary enterprises in various regions across the world, the importance accorded to such decisions and the driving forces behind them. Through a projection-based analysis, this study reveals a range of different reasons underlying the internationalization strategies of Spanish MNEs and the different goals they pursue. It may be concluded that projection connectionist techniques are of immense assistance in the process of identifying the internationalization strategies of Spanish MNEs, their underlying motives and the goals they pursue. The second case study covers several risk categories that include task policy, security, and political stability among others, and it tracks the scores of different countries all over the world. Interesting conclusions are drawn from the application of several business intelligence solutions based on neural projection models, which support data analysis in the context of country and political risk analysis.     

High-Frequency Induction Hardening with Controlled Capacitors-Discharge Pulse-Operation Processes

Induction hardening processes with power pulses obtained by means of capacitors-discharge high-frequency generators are discussed. The process is characterized by high-power densities and heating times on the order of some tens or hundreds of milliseconds together with cooling rates obtained by self-quenching without the use of auxiliary means. The possibility of obtaining the most favorable transient temperature distribution in the workpieces by controlling the shape of the pulses and therefore the variable time rate energy supply is examined. The influence of shape of pulses and discharge circuit's electrical parameters on the heating and cooling transients has been analyzed by a thermal model which allows prediction of the depths of hardening. Measurements from hardening tests carried out on steel samples varying the pulse shapes are given in support of the calculation results.     

Interaction of isobutene and methacrolein with silica-supported uranium and molybdenum oxide catalysts

The adsorption of isobutene (in the temperature range 309–341K) and methacrolein (in the temperature range 296–336 K) on a Mo/(Mo+U)=0.89 catalyst were studied. The equilibrium data were analysed according to Freundlich's model. The high coverages observed at lower temperatures suggest some participation of physical adsorption in the reversible adsorption. Entropy calculations showed that these adsorbed species are best described by a mobile model which assumes bidimensional translation and two rotational degrees of freedom. Isobutene is weakly chemisorbed, producing reversible species which were identified as a π-complex formed by interaction with surface OH groups through π-electrons (infrared bands at 1655, 1615, 1470 and 1375 cm^?1), and only a small fraction of isobutene interacts strongly via lattice oxygen forming intermediate species in the oxidation reaction. However, in the presence of oxygen at 523 K a majority of the surface species are strongly held by the surface (infrared bands at 1775, 1723, 1610, 1460 and 1350 cm^?1 associated to a methacrylic complex and bands at 1590 and 1538 cm^?1 of carbonate-carboxylate species).