6,731 research outputs found

    Probing Short Range Nucleon Correlations in High Energy Hard Quasielastic pd Reactions

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    We show that the strong dependence of the amplitude for NNNN hard scattering on the collision energy can be used to magnify the effects of short range nucleon correlations in quasielastic pdpd scattering. Under specific kinematical conditions the effect of initial and final state interactions can be accounted for by rescaling the cross section calculated within the plane wave impulse approximation. The feasibility to investigate the role of relativistic effects in the deuteron wave function is demonstrated by comparing the predictions of different formalisms. Binding effects due to short range correlations in deuteron are discussed as well.Comment: 18 pages (LaTex) + 10 postscript figs (available on request

    A model-based multithreshold method for subgroup identification

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    Thresholding variable plays a crucial role in subgroup identification for personalizedmedicine. Most existing partitioning methods split the sample basedon one predictor variable. In this paper, we consider setting the splitting rulefrom a combination of multivariate predictors, such as the latent factors, principlecomponents, and weighted sum of predictors. Such a subgrouping methodmay lead to more meaningful partitioning of the population than using a singlevariable. In addition, our method is based on a change point regression modeland thus yields straight forward model-based prediction results. After choosinga particular thresholding variable form, we apply a two-stage multiple changepoint detection method to determine the subgroups and estimate the regressionparameters. We show that our approach can produce two or more subgroupsfrom the multiple change points and identify the true grouping with high probability.In addition, our estimation results enjoy oracle properties. We design asimulation study to compare performances of our proposed and existing methodsand apply them to analyze data sets from a Scleroderma trial and a breastcancer study

    Exploring Food Detection using CNNs

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    One of the most common critical factors directly related to the cause of a chronic disease is unhealthy diet consumption. In this sense, building an automatic system for food analysis could allow a better understanding of the nutritional information with respect to the food eaten and thus it could help in taking corrective actions in order to consume a better diet. The Computer Vision community has focused its efforts on several areas involved in the visual food analysis such as: food detection, food recognition, food localization, portion estimation, among others. For food detection, the best results evidenced in the state of the art were obtained using Convolutional Neural Network. However, the results of all these different approaches were gotten on different datasets and therefore are not directly comparable. This article proposes an overview of the last advances on food detection and an optimal model based on GoogLeNet Convolutional Neural Network method, principal component analysis, and a support vector machine that outperforms the state of the art on two public food/non-food datasets

    Low-Symmetry Rhombohedral GeTe Thermoelectrics

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    High-symmetry thermoelectric materials usually have the advantage of very high band degeneracy, while low-symmetry thermoelectrics have the advantage of very low lattice thermal conductivity. If the symmetry breaking of band degeneracy is small, both effects may be realized simultaneously. Here we demonstrate this principle in rhombohedral GeTe alloys, having a slightly reduced symmetry from its cubic structure, to realize a record figure of merit (zT ∼ 2.4) at 600 K. This is enabled by the control of rhombohedral distortion in crystal structure for engineering the split low-symmetry bands to be converged and the resultant compositional complexity for simultaneously reducing the lattice thermal conductivity. Device ZT as high as 1.3 in the rhombohedral phase and 1.5 over the entire working temperature range of GeTe alloys make this material the most efficient thermoelectric to date. This work paves the way for exploring low-symmetry materials as efficient thermoelectrics. Thermoelectric materials enable a heat flow to be directly converted to a flow of charge carriers for generating electricity. The crystal structure symmetry is one of the most fundamental parameters determining the properties of a crystalline material including thermoelectrics. The common belief currently held is that high-symmetry materials are usually good for thermoelectrics, leading to great efforts having historically been focused on GeTe alloys in a high-symmetry cubic structure. Here we show a slight reduction of crystal structure symmetry of GeTe alloys from cubic to rhombohedral, enabling a rearrangement in electronic bands for more transporting channels of charge carriers and many imperfections for more blocking centers of heat-energy carriers (phonons). This leads to the discovery of rhombohedral GeTe alloys as the most efficient thermoelectric materials to date, opening new possibilities for low-symmetry thermoelectric materials. Cubic GeTe thermoelectrics have been historically focused on, while this work utilizes a slight symmetry-breaking strategy to converge the split valence bands, to reduce the lattice thermal conductivity and therefore realize a record thermoelectric performance, all enabled in GeTe in a rhombohedral structure. This not only promotes GeTe alloys as excellent materials for thermoelectric power generation below 800 K, but also expands low-symmetry materials as efficient thermoelectrics

    Clinical characteristics of children infected with SARS-CoV-2 in Italy

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    Cultural-based visual expression: Emotional analysis of human face via Peking Opera Painted Faces (POPF)

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    © 2015 The Author(s) Peking Opera as a branch of Chinese traditional cultures and arts has a very distinct colourful facial make-up for all actors in the stage performance. Such make-up is stylised in nonverbal symbolic semantics which all combined together to form the painted faces to describe and symbolise the background, the characteristic and the emotional status of specific roles. A study of Peking Opera Painted Faces (POPF) was taken as an example to see how information and meanings can be effectively expressed through the change of facial expressions based on the facial motion within natural and emotional aspects. The study found that POPF provides exaggerated features of facial motion through images, and the symbolic semantics of POPF provides a high-level expression of human facial information. The study has presented and proved a creative structure of information analysis and expression based on POPF to improve the understanding of human facial motion and emotion

    Olive fruits infested with olive fly larvae respond with an ethylene burst and the emission of specific volatiles

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    Olive fly (Bactrocera oleae R.) is the most harmful insect pest of olive (Olea europaea L.) which strongly affects fruits and oil production. Despite the expanding economic importance of olive cultivation, up to now, only limited information on plant responses to B. oleae is available. Here, we demonstrate that olive fruits respond to B. oleae attack by producing changes in an array of different defensive compounds including phytohormones, volatile organic compounds (VOCs), and defense proteins. Bactrocera oleae-infested fruits induced a strong ethylene burst and transcript levels of several putative ethylene-responsive transcription factors became significantly upregulated. Moreover, infested fruits induced significant changes in the levels of 12-oxo-phytodienoic acid and C12 derivatives of the hydroperoxide lyase. The emission of VOCs was also changed quantitatively and qualitatively in insect-damaged fruits, indicating that B. oleae larval feeding can specifically affect the volatile blend of fruits. Finally, we show that larval infestation maintained high levels of trypsin protease inhibitors in ripe fruits, probably by affecting post-transcriptional mechanisms. Our results provide novel and important information to understand the response of the olive fruit to B. oleae attack; information that can shed light onto potential new strategies to combat this pes

    Functional characterisation of substrate-binding proteins to address nutrient uptake in marine picocyanobacteria.

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    Marine cyanobacteria are key primary producers, contributing significantly to the microbial food web and biogeochemical cycles by releasing and importing many essential nutrients cycled through the environment. A subgroup of these, the picocyanobacteria (Synechococcus and Prochlorococcus), have colonised almost all marine ecosystems, covering a range of distinct light and temperature conditions, and nutrient profiles. The intra-clade diversities displayed by this monophyletic branch of cyanobacteria is indicative of their success across a broad range of environments. Part of this diversity is due to nutrient acquisition mechanisms, such as the use of high-affinity ATP-binding cassette (ABC) transporters to competitively acquire nutrients, particularly in oligotrophic (nutrient scarce) marine environments. The specificity of nutrient uptake in ABC transporters is primarily determined by the peripheral substrate-binding protein (SBP), a receptor protein that mediates ligand recognition and initiates translocation into the cell. The recent availability of large numbers of sequenced picocyanobacterial genomes indicates both Synechococcus and Prochlorococcus apportion >50% of their transport capacity to ABC transport systems. However, the low degree of sequence homology among the SBP family limits the reliability of functional assignments using sequence annotation and prediction tools. This review highlights the use of known SBP structural representatives for the uptake of key nutrient classes by cyanobacteria to compare with predicted SBP functionalities within sequenced marine picocyanobacteria genomes. This review shows the broad range of conserved biochemical functions of picocyanobacteria and the range of novel and hypothetical ABC transport systems that require further functional characterisation
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