Some factors that may affect the physical-chemical properties of blueberries

The aim of the present study was to investigate the effect of different production and conservation factors on some properties of blueberries. Among the production factors considered were cultivar (Duke, Bluecrop and Ozarkblue) and production mode (organic or conventional). Regarding the conservation factors were evaluated temperature (ambient or refrigeration) and storage time (0, 7 and 14 days). The properties under study belong to three categories: physical properties (color and texture); chemical properties (moisture content, sugars and acidity) and phenolic and antioxidant properties (total phenols, anthocyanins, tannins, ABTS antioxidant activity, DPPH antioxidant activity). The results revealed that moisture content was only influenced by cultivar and that both acidity and sugar contents varied according to the production mode used. Also it was evidenced that the antioxidant activity was not statistically different between cultivars, production modes or conservation conditions. Regarding the phenolic compounds, the tannins were significantly higher for the blueberries produced in organic agriculture. Regarding color significant differences were also encountered and the most intense blue was found in blueberries from cv. Duke, produced in organic farming and stored under refrigeration. Textural attributes were also very significantly influenced by all factors at study: cultivar, production mode and conservation, and the berries from cv. Duke stored under refrigeration showed the highest firmness.

Automatic dynamic mask extraction for PIV images containing an unsteady interface, bubbles, and a moving structure

When performing Particle Image Velocimetry (PIV) measurements in complex fluid flows with moving interfaces and a two-phase flow, it is necessary to develop a mask to remove non-physical measurements. This is the case when studying, for example, the complex bubble sweep-down phenomenon observed in oceanographic research vessels. Indeed, in such a configuration, the presence of an unsteady free surface, of a solid–liquid interface and of bubbles in the PIV frame, leads to generate numerous laser reflections and therefore spurious velocity vectors. In this note, an image masking process is developed to successively identify the boundaries of the ship and the free surface interface. As the presence of the solid hull surface induces laser reflections, the hull edge contours are simply detected in the first PIV frame and dynamically estimated for consecutive ones. As for the unsteady surface determination, a specific process is implemented like the following: i) the edge detection of the gradient magnitude in the PIV frame, ii) the extraction of the particles by filtering high-intensity large areas related to the bubbles and/or hull reflections, iii) the extraction of the rough region containing these particles and their reflections, iv) the removal of these reflections. The unsteady surface is finally obtained with a fifth-order polynomial interpolation. The resulted free surface is successfully validated from the Fourier analysis and by visualizing selected PIV images containing numerous spurious high intensity areas. This paper demonstrates how this data analysis process leads to PIV images database without reflections and an automatic detection of both the free surface and the rigid body. An application of this new mask is finally detailed, allowing a preliminary analysis of the hydrodynamic flow.

Wind turbine indirect ice detection and operational analysis

Wind energy is one of the most promising and fast growing sector of energy production. Wind is ecologically friendly and relatively cheap energy resource available for development in practically all corners of the world (where only the wind blows). Today wind power gained broad development in the Scandinavian countries. Three important challenges concerning sustainable development, i.e. energy security, climate change and energy access make a compelling case for large-scale utilization of wind energy. In Finland, according to the climate and energy strategy, accepted in 2008, the total consumption of electricity generated by means of wind farms by 2020, should reach 6 - 7% of total consumption in the country [1]. The main challenges associated with wind energy production are harsh operational conditions that often accompany the turbine operation in the climatic conditions of the north and poor accessibility for maintenance and service. One of the major problems that require a solution is the icing of turbine structures. Icing reduces the performance of wind turbines, which in the conditions of a long cold period, can significantly affect the reliability of power supply. In order to predict and control power performance, the process of ice accretion has to be carefully tracked. There are two ways to detect icing – directly or indirectly. The first way applies to the special ice detection instruments. The second one is using indirect characteristics of turbine performance. One of such indirect methods for ice detection and power loss estimation has been proposed and used in this paper. The results were compared to the results directly gained from the ice sensors. The data used was measured in Muukko wind farm, southeast Finland during a project 'Wind power in cold climate and complex terrain'. The project was carried out in 9/2013 - 8/2015 with the partners Lappeenranta university of technology, Alstom renovables España S.L., TuuliMuukko, and TuuliSaimaa.

Statistical Analysis of Text Summarization Evaluation

This dissertation applies statistical methods to the evaluation of automatic summarization using data from the Text Analysis Conferences in 2008-2011. Several aspects of the evaluation framework itself are studied, including the statistical testing used to determine significant differences, the assessors, and the design of the experiment. In addition, a family of evaluation metrics is developed to predict the score an automatically generated summary would receive from a human judge and its results are demonstrated at the Text Analysis Conference. Finally, variations on the evaluation framework are studied and their relative merits considered. An over-arching theme of this dissertation is the application of standard statistical methods to data that does not conform to the usual testing assumptions.

Information Analysis and Databases

Means to automate the fact replace the man in their job functions for a man and machines automatic mechanism, ie documentary specialists in computer and computers are the cornerstone of any modern system of documentation and information. From this point of view immediately raises the problem of deciding what resources should be applied to solve the specific problem in each specific case. We will not let alone to propose quick fixes or recipes in order to decide what to do in any case. The solution depends on repeat for each particular problem. What we want is to move some points that can serve as a basis for reflection to help find the best solution possible, once the problem is defined correctly. The first thing to do before starting any automated system project is to define exactly the domain you want to cover and assess with greater precision possible importance.

A truncation in the Aryl Hydrocarbon Receptor of the CRL:WI(Han) rat does not affect the developmental toxicity of TCDD

The Aryl Hydrocarbon Receptor (AhR) is required for the toxicity of TCDD, and so the AhR of CRL:WI and CRL:WI(Han) rats was characterised. Western blot showed AhR proteins of ~110 and ~97 kDa in individual rats from both strains. The AhR cDNA from a CRL:WI(Han) rat with the ~110kDa protein revealed a sequence that was identical to that of the CRL:WI and SD rat. However, cloning of the AhR from a rat with the ~97kDa protein revealed a point mutation, and five variants encoding two C-terminally truncated variants of the AhR protein, arising from a point mutation in the intron/exon junction and consequent differential splicing. These C-terminally truncated variants were expressed and shown to give rise to a protein of ~97kDa; the recombinant AhR bound TCDD with an affinity that was not statistically different from the full-length protein. A single-nucleotide polymorphism (SNP) assay was developed, and showed that both alleles were represented in a Hardy-Weinberg equilibrium in samples of CRL:WI and CRL:WI(Han) populations; both alleles are abundant. Rats from two studies of TCDD developmental toxicity were genotyped, and the association with toxicity investigated using statistical analysis. There was no plausible evidence that the AhR allele had a significant effect on the toxic endpoints examined. These data show that the two AhR alleles are common in two strains of Wistar rat, and that the AhR alleles had no effect on TCDD-induced developmental toxicity in two independent studies.

Recombinant expression of Aryl Hydrocarbon Receptor for quantitative ligand-binding analysis

Recombinant expression of the Aryl Hydrocarbon Receptor (AhR) yields small amounts of ligand- binding competent AhR. Therefore, Spodoptera frugiperda (Sf9) cells and baculovirus have been evaluated for high level and functional expression of AhR. Rat and human AhR were expressed as soluble protein in significant amounts. Expression of ligand-binding competent AhR was sensitive to the protein concentration of Sf9 extract, and co-expression of the chaperone p23 failed to affect the yield of functional ligand-binding AhR. The expression system yielded high levels of functional protein, with the ligand-binding capacity (Bmax) typically 20- fold higher than that obtained with rat liver cytosol. Quantitative estimates of the ligand-binding affinity of human and rat AhR were obtained; the Kd for recombinant rat AhR was indistinguishable from that of native rat AhR, thereby validating the expression system as a faithful model for native AhR. The human AhR bound TCDD with significantly lower affinity than the rat AhR. These findings demonstrate high-level expression of ligand-binding competent AhR, and sufficient AhR for quantitative analysis of ligand-binding.

An Analysis of Colombian Power Market Price Behavior from an Industrial Organization Perspective

We analyze the behavior of spot prices in the Colombian wholesale power market, using a series of models derived from industrial organization theory -- We first create a Cournot-based model that simulates the strategic behavior of the market-leader power generators, which we use to estimate two industrial organization variables, the Index of Residual Demand and the Herfindahl-Hirschman Index (HHI) -- We use these variables to create VAR models that estimate spot prices and power market impulse-response relationships -- The results from these models show that hydroelectric generators can use their water storage capability strategically to affect off-peak prices primarily, while the thermal generators can manage their capacity strategically to affect on-peak prices -- In addition, shocks to the Index of Residual Capacity and to the HHI cause spot price fluctuations, which can be interpreted as the generators´ strategic response to these shocks

The transformed-stationary approach: a generic and simplified methodology for non-stationary extreme value analysis

Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result into a non-stationary extreme value distribution. As a transformation, we propose and discuss a simple time-varying normalization of the signal and show that it enables a comprehensive formulation of non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with a constant shape parameter. A validation of the methodology is carried out on time series of significant wave height, residual water level, and river discharge, which show varying degrees of long-term and seasonal variability. The results from the proposed approach are comparable with the results from (a) a stationary EVA on quasi-stationary slices of non-stationary series and (b) the established method for non-stationary EVA. However, the proposed technique comes with advantages in both cases. For example, in contrast to (a), the proposed technique uses the whole time horizon of the series for the estimation of the extremes, allowing for a more accurate estimation of large return levels. Furthermore, with respect to (b), it decouples the detection of non-stationary patterns from the fitting of the extreme value distribution. As a result, the steps of the analysis are simplified and intermediate diagnostics are possible. In particular, the transformation can be carried out by means of simple statistical techniques such as low-pass filters based on the running mean and the standard deviation, and the fitting procedure is a stationary one with a few degrees of freedom and is easy to implement and control. An open-source MAT-LAB toolbox has been developed to cover this methodology, which is available at https://github.com/menta78/tsEva/(Mentaschi et al., 2016).

Proteomic analysis of Rhizobium freirei PRF 81 responses to low pH.

Rhizobium freirei PRF 81 is employed in common bean commercial inoculants in Brazil, due to its outstanding efficiency in fixing nitrogen, competitiveness and tolerance to abiotic stresses. Among the environmental conditions faced by rhizobia in soils, acidity is perhaps the encountered most, especially in Brazil. So, we used proteomics based approaches to study the responses of PRF 81 to a low pH condition. R. freirei PRF 81 was grown in TY medium until exponential phase in two treatments: pH 6,8 and pH 4,8. Whole-cell proteins were extracted and separated by two-dimensional gel electrophoresis, using IPG-strips with pH range 4-7 and 12% polyacrilamide gels. The experiment was performed in triplicate. Protein spots were detected in the high-resolution digitized gel images and analyzed by Image Master 2D Platinum v 5.0 software. Relative volumes (%vol) of compared between the two conditions tested and were statistically evaluated (p ≤ 0.05). Even knowing that R. freirei PRF 81 can still grow in more acid conditions, pH 4.8 was chosen because didn´t affect significantly the bacterial growth kinetics, a factor that could compromise the analysis. Using a narrow pH range, the gel profiles displayed a better resolution and reprodutibility than using broader pH range. Spots were mostly concentrated between pH 5-7 and molecular masses between 17-95 kDa. From the six hundred well-defined spots analyzed, one hundred and sixty-three spots presented a significant change in % vol, indicating that the pH led to expressive changes in the proteome of R. freirei PRF 81. Of these, sixty-one were up-regulated and one hundred two was downregulated in pH 4.8 condition. Also, fourteen spots were only identified in the acid condition, while seven spots was exclusively detected in pH 6.8. Ninety-five differentially expressed spots and two exclusively detected in pH 4,8 were selected for Maldi-Tof identification. Together with the genome sequencing and the proteome analysis of heat stress, we will search for molecular determinants of PRF 81 related to capacity to adapt to stressful tropical conditions.

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

Political ideologies and attitudes towards income inequality in the US: a critical discourse analysis of CNN and Fox News opinion articles

The topic of the thesis is media discourse about current state if income inequality in the US, and political ideologies as influences behind the discourse. The data consists of four opinion articles, two from CNN and two from Fox News. The purpose of the study was to examine how media represents income inequality as an issue, and if the attitudes conveyed are concerned or indifferent. Previous studies have indicated that the level of income is often seen as a personal responsibility, and such perspective can be linked with Republican ideology. In contrast, the Democrats typically express more concern about the consequences of inequality. CNN has been previously considered to have a Democratic bias, and Fox News has been considered to have Republican bias, which is one reason why these two news channels were chosen as the sources of the data. The study is a critical discourse analysis, and the methods applied were sociocognitive approach, which analyzes the social and cognitive factors affecting the discourse, and appraisal framework, which was applied to scrutinize the expressed attitudes more closely by identifyind specific linguistic features. The appraisal framework includes studying such features as affect, judgment and appreciation, which offer a more detailed analysis on the attitudes present in the articles. The sociocognitive approach, additionally, offers a way of analyzing a more broad context affecting the articles. The findings were then compared, to see if there are differences between the articles, or between the news sites with alleged bias. The findings showed that CNN, with alleged Democratic bias, had a more symphatetic attitude towards income inequality, whereas Fox News, with more Republican views, showed clearly less concern towards the issue. Moreover, the Fox News articles had such dubious claims that the underlying ideology behind the articles could be even supporting of income inequality, as it allows the rich to pursue all the wealth they can without having to give anything away. The results, thus, suggest that the political ideologies may a significant effect on media discourse, which, in turn, may have a significant effect on the attitudes of the public towards great issues that could require prompt measures.

Automatic identification of whole-part relations in Portuguese

Dissertação de Mestrado, Ciências da Linguagem, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2014

Analysis of contributions of herpes simplex virus type 1 UL43 protein to induction of cell-cell fusion

Purpose: To investigate whether UL43 protein, which is highly conserved in alpha- and gamma herpes viruses, and a non-glycosylated transmembrane protein, is involved in virus entry and virus-induced cell fusion. Methods: Mutagenesis was accomplished by a markerless two-step Red recombination mutagenesis system implemented on the Herpes simplex virus 1 (HSV-1) bacterial artificial chromosome (BAC). Growth properties of HSV-1 UL43 mutants were analyzed using plaque morphology and one-step growth kinetics. SDS-PAGE and Western blot was employed to assay the synthesis of the viral glycoproteins. Virus-penetration was assayed to determine if UL43 protein is required for efficient virus entry. Results: Lack of UL43 expression resulted in significantly reduced plaque sizes of syncytial mutant viruses and inhibited cell fusion induced by gBΔ28 or gKsyn20 (p < 0.05). Deletion of UL43 did not affect overall expression levels of viral glycoproteins gB, gC, gD, and gH on HSV-1(F) BAC infected cell surfaces. Moreover, mutant viruses lacking UL43 gene exhibited slower kinetics of entry into Vero cells than the parental HSV-1(F) BAC. Conclusion: Thus, these results suggest an important role for UL43 protein in mediating virus-induced membrane fusion and efficient entry of virion into target cells.

Biological significance of dead biomass retention trait in Mediterranean Basin species: an analysis between different successional niches and regeneration strategies as functional groups

Standing dead biomass retention is considered one of the most relevant fuel structural traits to affect plant flammability. However, very little is known about the biological significance of this trait and its distribution between different functional groups. Our aim was to analyse how the proportion of dead biomass produced in Mediterranean species is related to the successional niche of species (early-, mid- and late-successional stages) and the regeneration strategy of species (seeders and resprouters). We evaluated biomass distribution by size classes and standing dead biomass retention in nine dominant species from the Mediterranean Basin in different development stages (5, 9, 14 and 26 years since the last fire). The results revealed significant differences in the standing dead biomass retention of species that presented a distinct successional niche or regeneration strategy. These differences were restricted to the oldest ages studied (>9 years). Tree and small tree resprouters, typical in late-successional stages, presented slight variations with age and a less marked trend to retain dead biomass, while seeder shrubs and dwarf shrubs, characteristic of early-successional stages, showed high dead biomass loads. Our results suggest that the species that tend to retain more dead branches are colonising species that may promote fire in early-successional stages.