415 research outputs found

    Non-Commutative (Softly Broken) Supersymmetric Yang-Mills-Chern-Simons

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    We study d=2+1 non-commutative U(1) YMCS, concentrating on the one-loop corrections to the propagator and to the dispersion relations. Unlike its commutative counterpart, this model presents divergences and hence an IR/UV mechanism, which we regularize by adding a Majorana gaugino of mass m_f, that provides (softly broken) supersymmetry. The perturbative vacuum becomes stable for a wide range of coupling and mass values, and tachyonic modes are generated only in two regions of the parameters space. One such region corresponds to removing the supersymmetric regulator (m_f >> m_g), restoring the well-known IR/UV mixing phenomenon. The other one (for m_f ~ m_g/2 and large \theta) is novel and peculiar of this model. The two tachyonic regions turn out to be very different in nature. We conclude with some remarks on the theory's off-shell unitarity.Comment: 42 pages, 11 figures, uses Axodraw. Bibliography revise

    A predicative and decidable characterization of the polynomial classes of languages

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    Characterizations of PTIME, PSPACE, the polynomial hierarchy and its elements are given, which are decidable (membership can be decided by syntactic inspection to the constructions), predicative (according to points of view by Leivant and others), and are obtained by means of increasing restrictions to course-of-values recursion on trees (represented in a dialect of Lisp). (C) 2001 Elsevier Science B.V. All rights reserved

    Application of calibrations to hyperspectral images of food grains: example for wheat falling number

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    The presence of a few kernels with sprouting problems in a batch of wheat can result in enzymatic activity sufficient to compromise flour functionality and bread quality. This is commonly assessed using the Hagberg Falling Number (HFN) method, which is a batch analysis. Hyperspectral imaging (HSI) can provide analysis at the single grain level with potential for improved performance. The present paper deals with the development and application of calibrations obtained using an HSI system working in the near infrared (NIR) region (~900–2500 nm) and reference measurements of HFN. A partial least squares regression calibration has been built using 425 wheat samples with a HFN range of 62–318 s, including field and laboratory pre-germinated samples placed under wet conditions. Two different approaches were tested to apply calibrations: i) application of the calibration to each pixel, followed by calculation of the average of the resulting values for each object (kernel); ii) calculation of the average spectrum for each object, followed by application of the calibration to the mean spectrum. The calibration performance achieved for HFN (R2 = 0.6; RMSEC ~ 50 s; RMSEP ~ 63 s) compares favourably with other studies using NIR spectroscopy. Linear spectral pre-treatments lead to similar results when applying the two methods, while non-linear treatments such as standard normal variant showed obvious differences between these approaches. A classification model based on linear discriminant analysis (LDA) was also applied to segregate wheat kernels into low (250 s) HFN groups. LDA correctly classified 86.4% of the samples, with a classification accuracy of 97.9% when using HFN threshold of 150 s. These results are promising in terms of wheat quality assessment using a rapid and non-destructive technique which is able to analyse wheat properties on a single-kernel basis, and to classify samples as acceptable or unacceptable for flour production

    NIR hyperspectral imaging for predicting the composition of granular food commodities

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    Hyperspectral imaging (HSI) in the Near-Infrared (NIR) spectral range was applied for non- destructive characterisation of three staple food commodities: wheat, cocoa and coffee. Industrially-relevant properties such as moisture, fat and proteins were explored on a single seed basis. Prediction models were built for whole wheat kernels, cocoa seeds (de-shelled i.e., cotyledons or nibs) and green coffee beans. Major constituents were successfully predicted in the three commodities with performance allowing quantitative prediction for screening purposes and quality control. In addition, chemical compounds found at lower concentrations were analysed. This comprised indirect methods for enzymatic activity in wheat, polyphenols and antioxidant activity in cocoa, and sucrose, caffeine and trigonelline in green coffee beans. Calibration models built from HSI scanning of green and roasted coffee beans demonstrated the potential to predict generated volatile compounds upon roasting. This approach has been also performed to demonstrate the potential to understand variability at single kernel/seed basis, which can be used for quality improvement of food grains/seeds. HSI-based quantification for single seeds (as well as single pixel level) could be used as a selection tool to create different streams, e.g. for specific product characteristics or to obtain a more consistent composition of the final food product or segregating materials into different process streams with different commercial values. This research work is of strong practical interest, due to the potential applications

    Hyperspectral imaging for non-destructive prediction of fermentation index, polyphenol content and antioxidant activity in single cocoa beans

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    The aim of the current work was to use hyperspectral imaging (HSI) in the spectral range 1000-2500 nm to quantitatively predict fermentation index (FI), total polyphenols (TP) and antioxidant activity (AA) of individual dry fermented cocoa beans scanned on a single seed basis. Seventeen cocoa bean batches were obtained and 10 cocoa beans were used from each batch. PLS regression models were built on 170 samples. The developed HSI predictive models were able to quantify three quality-related parameters with sufficient performance for screening purposes, with external validation R2 of 0.50 (RMSEP=0.27, RPD=1.40), 0.70 (RMSEP=34.1 mg ferulic acid g-1, RPD=1.77) and 0.74 (60.0 mmol Trolog kg-1, RPD=1.91) for FI, TP and AA, respectively. The calibrations were subsequently applied at a single bean and pixel level, so that the distribution was visualised within and between single seeds. HSI is thus suggested as a promising approach to estimate cocoa bean composition rapidly and non-destructively, thus offering a valid tool for food inspection and quality control

    Physical and Oxidative Stability of Functional olive Oil-in-Water Emulsions Formulated Using Olive Mill Wastewater and Whey Proteins

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    The present paper reports on the use of phenolic extracts from olive mill wastewater (OMW) in model olive oil-in-water (O/W) emulsions to study their effect on their physical and chemical stability. Spray-dried OMW polyphenols were added to a model 20% olive O/W emulsion stabilized with whey protein isolate (WPI) and xanthan gum, in phosphate buffer solution at pH 7. The emulsions were characterised under accelerated storage conditions (40 °C) up to 30 days. Physical stability was evaluated by analysing the creaming rate, mean particle size distribution and mean droplet size, viscosity and rheological properties, while chemical stability was assessed through the measurement of primary and secondary oxidation products. The rheological behaviour and creaming stability of the emulsions were dramatically improved by using xanthan gum, whereas the concentration of WPI and the addition of encapsulated OMW phenolics did not result in a significant improvement of physical stability. The formation of oxidation products was higher when higher concentrations of encapsulated polyphenols were used, indicating a possible binding with the WPI added in the system as a natural emulsifier. This paper might help in solving the issue of using the olive mill wastewater from olive processing in formulating functional food products with high antioxidant activity and improved health properties

    Skeletal muscle myopenia in mice model of bile duct ligation and carbon tetrachloride-induced liver cirrhosis

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    Skeletal muscle myopathy is universal in cirrhotic patients, however, little is known about the main mechanisms involved. The study aims to investigate skeletal muscle morphological, histological, and functional modifications in experimental models of cirrhosis and the principal molecular pathways responsible for skeletal muscle myopathy. Cirrhosis was induced by bile duct ligation (BDL) and carbon tetrachloride (CCl4) administration in mice. Control animals (CTR) underwent bile duct exposure or vehicle administration only. At sacrifice, peripheral muscles were dissected and weighed. Contractile properties of extensor digitorum longus (EDL) were studied in vitro. Muscle samples were used for histological and molecular analysis. Quadriceps muscle histology revealed a significant reduction in cross-sectional area of muscle and muscle fibers in cirrhotic mice with respect to CTR. Kinetic properties of EDL in both BDL and CCl4 were reduced with respect to CTR; BDL mice also showed a reduction in muscle force and a decrease in the resistance to fatigue. Increase in myostatin expression associated with a decrease in AKT-mTOR expressions was observed in BDL mice, together with an increase in LC3 protein levels. Upregulation of the proinflammatory citochines TNF-a and IL6 and an increased expression of NF-kB and MuRF-1 were observed in CCl4 mice. In conclusion, skeletal muscle myopenia was present in experimental models of BDL and CCl4-induced cirrhosis. Moreover, reduction in protein synthesis and activation of protein degradation were the main mechanisms responsible for myopenia in BDL mice, while activation of ubiquitin-pathway through inflammatory cytokines seems to be the main potential mechanism involved in CCl4 mice

    Phase transitions, double-scaling limit, and topological strings

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    Topological strings on Calabi--Yau manifolds are known to undergo phase transitions at small distances. We study this issue in the case of perturbative topological strings on local Calabi--Yau threefolds given by a bundle over a two-sphere. This theory can be regarded as a q--deformation of Hurwitz theory, and it has a conjectural nonperturbative description in terms of q--deformed 2d Yang--Mills theory. We solve the planar model and find a phase transition at small radius in the universality class of 2d gravity. We give strong evidence that there is a double--scaled theory at the critical point whose all genus free energy is governed by the Painlev\'e I equation. We compare the critical behavior of the perturbative theory to the critical behavior of its nonperturbative description, which belongs to the universality class of 2d supergravity. We also give evidence for a new open/closed duality relating these Calabi--Yau backgrounds to open strings with framing.Comment: 49 pages, 3 eps figures; section added on non-perturbative proposal and 2d gravity; minor typos correcte

    Prediction of coffee aroma from single roasted coffee beans by hyperspectral imaging

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    Coffee aroma is critical for consumer liking and enables price differentiation of coffee. This study applied hyperspectral imaging (1000–2500 nm) to predict volatile compounds in single roasted coffee beans, as measured by Solid Phase Micro Extraction-Gas Chromatography-Mass Spectrometry and Gas Chromatography-Olfactometry. Partial least square (PLS) regression models were built for individual volatile compounds and chemical classes. Selected key aroma compounds were predicted well enough to allow rapid screening (R2 greater than 0.7, Ratio to Performance Deviation (RPD) greater than 1.5), and improved predictions were achieved for classes of compounds - e.g. aldehydes and pyrazines (R2 ∼ 0.8, RPD ∼ 1.9). To demonstrate the approach, beans were successfully segregated by HSI into prototype batches with different levels of pyrazines (smoky) or aldehydes (sweet). This is industrially relevant as it will provide new rapid tools for quality evaluation, opportunities to understand and minimise heterogeneity during production and roasting and ultimately provide the tools to define and achieve new coffee flavour profiles
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