2,335 research outputs found

    Quantitative parameters for the examination of InGaN QW multilayers by low-loss EELS

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    We present a detailed examination of a multiple InxGa1-xN quantum well (QW) structure for optoelectronic applications. The characterization is carried out using scanning transmission electron microscopy (STEM), combining high-angle annular dark field (HAADF) imaging and electron energy loss spectroscopy (EELS). Fluctuations in the QW thickness and composition are observed in atomic resolution images. The impact of these small changes on the electronic properties of the semiconductor material is measured through spatially localized low-loss EELS, obtaining band gap and plasmon energy values. Because of the small size of the InGaN QW layers additional effects hinder the analysis. Hence, additional parameters were explored, which can be assessed using the same EELS data and give further information. For instance, plasmon width was studied using a model-based fit approach to the plasmon peak; observing a broadening of this peak can be related to the chemical and structural inhomogeneity in the InGaN QW layers. Additionally, Kramers-Kronig analysis (KKA) was used to calculate the complex dielectric function (CDF) from the EELS spectrum images (SIs). After this analysis, the electron effective mass and the sample absolute thickness were obtained, and an alternative method for the assessment of plasmon energy was demonstrated. Also after KKA, the normalization of the energy-loss spectrum allows us to analyze the Ga 3d transition, which provides additional chemical information at great spatial resolution. Each one of these methods is presented in this work together with a critical discussion of their advantages and drawbacks

    Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data.

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    This paper presents an innovative multisensor, multitemporal machine-learning approach using remote sensing big data for the detection of archaeological mounds in Cholistan (Pakistan). The Cholistan Desert presents one of the largest concentrations of Indus Civilization sites (from ca 3300 to 1500 BC). Cholistan has figured prominently in theories about changes in water availability, the rise and decline of the Indus Civilization, and the transformation of fertile monsoonal alluvial plains into an extremely arid margin. This paper implements a multisensor, multitemporal machine-learning approach for the remote detection of archaeological mounds. A classifier algorithm that employs a large-scale collection of synthetic-aperture radar and multispectral images has been implemented in Google Earth Engine, resulting in an accurate probability map for mound-like signatures across an area that covers ca 36,000 km2 The results show that the area presents many more archaeological mounds than previously recorded, extending south and east into the desert, which has major implications for understanding the archaeological significance of the region. The detection of small (30 ha) suggests that there were continuous shifts in settlement location. These shifts are likely to reflect responses to a dynamic and changing hydrological network and the influence of the progressive northward advance of the desert in a long-term process that culminated in the abandonment of much of the settled area during the Late Harappan period.ER

    Role of cis-zeatin in root responses to phosphate starvation

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    Phosphate (Pi) is an essential nutrient for all organisms. Root are underground organs, but the majority of the root biology studies have been done growing the root system in presence of light.Root illumination alters the Pi starvation response (PSR) at different levels. Thus, we have analyzed morphological, transcriptional and physiological responses to Pi starvation in dark‐grown roots.We have identified new genes and pathways regulated by Pi starvation that were not described previously. We also show that Pi‐starved plants increase the cis‐zeatin (cZ)/trans‐zeatin (tZ) ratio. Transcriptomic analyses show that tZ preferentially represses cell cycle and PSR genes while cZ induces genes involved in cell and root hair elongation and differentiation. In fact, cZ‐treated seedlings show longer root system as well as longer root hairs than tZ‐treated, increasing the total absorbing surface. Mutants with low cZ levels do not allocate free Pi in roots during Pi starvation.We propose that Pi‐starved plants increase the cZ/tZ ratio to maintain basal CK responses and allocate Pi in the root system to sustain its growth. Therefore, cZ acts as a Pi‐starvation response hormone that stimulates root and root hair elongation to enlarge root absorbing surface and to increase Pi levels in roots

    Heavy-flavour and quarkonium production in the LHC era: from proton-proton to heavy-ion collisions

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    This report reviews the study of open heavy-flavour and quarkonium production in high-energy hadronic collisions, as tools to investigate fundamental aspects of Quantum Chromodynamics, from the proton and nucleus structure at high energy to deconfinement and the properties of the Quark-Gluon Plasma. Emphasis is given to the lessons learnt from LHC Run 1 results, which are reviewed in a global picture with the results from SPS and RHIC at lower energies, as well as to the questions to be addressed in the future. The report covers heavy flavour and quarkonium production in proton-proton, proton-nucleus and nucleus-nucleus collisions. This includes discussion of the effects of hot and cold strongly interacting matter, quarkonium photo-production in nucleus-nucleus collisions and perspectives on the study of heavy flavour and quarkonium with upgrades of existing experiments and new experiments. The report results from the activity of the SaporeGravis network of the I3 Hadron Physics programme of the European Union 7th Framework Programme

    First month prednisone dose predicts prednisone burden during the following 11 months: An observational study from the RELES cohort

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    Aim: To study the influence of prednisone dose during the first month after systemic lupus erythematosus (SLE) diagnosis (prednisone-1) on glucocorticoid burden during the subsequent 11 months (prednisone-2–12). Methods: 223 patients from the Registro Español de Lupus Eritematoso Sistémico inception cohort were studied. The cumulative dose of prednisone-1 and prednisone-2–12 were calculated and recoded into a four-level categorical variable: no prednisone, low dose (up to 7.5 mg/day), medium dose (up to 30 mg/day) and high dose (over 30 mg/day). The association between the cumulative prednisone-1 and prednisone-2–12 doses was tested. We analysed whether the four-level prednisone-1 categorical variable was an independent predictor of an average dose >7.5 mg/day of prednisone-2–12. Adjusting variables included age, immunosuppressives, antimalarials, methyl-prednisolone pulses, lupus nephritis and baseline SLE Disease Activity Index (SLEDAI). Results: Within the first month, 113 patients (51%) did not receive any prednisone, 24 patients (11%) received average low doses, 46 patients (21%) received medium doses and 40 patients (18%) received high doses. There was a strong association between prednisone-1 and prednisone-2–12 dose categories (p7.5 mg/day, while patients receiving low-dose prednisone-1 were not (adjusted OR 1.4, 95% CI 0. 0.38 to 5.2). If the analysis was restricted to the 158 patients with a baseline SLEDAI of =6, the model did not change. Conclusion: The dose of prednisone during the first month after the diagnosis of SLE is an independent predictor of prednisone burden during the following 11 months

    Continuous flexibility analysis of SARS-CoV-2 spike prefusion structures

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    Using a new consensus-based image-processing approach together with principal component analysis, the flexibility and conformational dynamics of the SARS-CoV-2 spike in the prefusion state have been analysed. These studies revealed concerted motions involving the receptor-binding domain (RBD), N-terminal domain, and subdomains 1 and 2 around the previously characterized 1-RBD-up state, which have been modeled as elastic deformations. It is shown that in this data set there are not well defined, stable spike conformations, but virtually a continuum of states. An ensemble map was obtained with minimum bias, from which the extremes of the change along the direction of maximal variance were modeled by flexible fitting. The results provide a warning of the potential image-processing classification instability of these complicated data sets, which has a direct impact on the interpretability of the results.The authors would like to acknowledge financial support from CSIC (PIE/COVID-19 No. 202020E079), the Comunidad de Madrid through grant CAM (S2017/BMD-3817), the Spanish Ministry of Science and Innovation through projects SEV 2017-0712, FPU-2015/264 and PID2019-104757RB-I00/AEI/ FEDER, the Instituto de Salud Carlos III [PT17/0009/0010 (ISCIII-SGEFI/ERDF)], and the European Union and Horizon 2020 through grants INSTRUCT–ULTRA (INFRADEV-03-2016-2017, Proposal 731005), EOSC Life (INFRAEOSC-04-2018, Proposal 824087), HighResCells (ERC-2018-SyG, Proposal 810057), IMpaCT (WIDESPREAD- 03-2018, Proposal 857203), CORBEL (INFRADEV-1-2014-1, Proposal 654248) and EOSC–Synergy (EINFRA-EOSC-5, Proposal 857647). HDT and BF were supported by NIH grant GM125769 and JSM was supported by NIH grant R01-AI12752

    Inclusive photon production at forward rapidities in proton-proton collisions at s\sqrt{s} = 0.9, 2.76 and 7 TeV

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    See paper for full list of authors – 24 pages, 10 captioned figures, 4 tables, authors from page 19, figures at http://aliceinfo.cern.ch/ArtSubmission/node/1024International audienceThe multiplicity and pseudorapidity distributions of inclusive photons have been measured at forward rapidities (2.3<η<3.92.3 < \eta < 3.9) in proton-proton collisions at three center-of-mass energies, s=0.9\sqrt{s}=0.9, 2.76 and 7 TeV using the ALICE detector. It is observed that the increase in the average photon multiplicity as a function of beam energy is compatible with both a logarithmic and a power-law dependence. The relative increase in average photon multiplicity produced in inelastic pp collisions at 2.76 and 7 TeV center-of-mass energies with respect to 0.9 TeV are 37.2% ±\pm 0.3% (stat) ±\pm 8.8% (sys) and 61.2% ±\pm 0.3% (stat) ±\pm 7.6% (sys), respectively. The photon multiplicity distributions for all center-of-mass energies are well described by negative binomial distributions. The multiplicity distributions are also presented in terms of KNO variables. The results are compared to model predictions, which are found in general to underestimate the data at large photon multiplicities, in particular at the highest center-of-mass energy. Limiting fragmentation behavior of photons has been explored with the data, but is not observed in the measured pseudorapidity range

    A systematic review and meta-analysis of the effects of flavanol-containing tea, cocoa and apple products on body composition and blood lipids: exploring the factors responsible for variability in their efficacy

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    Several randomized controlled trials (RCTs) and meta-analyses support the benefits of flavanols on cardiometabolic health, but the factors affecting variability in the responses to these compounds have not been properly assessed. The objectives of this meta-analysis were to systematically collect the RCTs-based-evidence of the effects of flavanol-containing tea, cocoa and apple products on selected biomarkers of cardiometabolic risk and to explore the influence of various factors on the variability in the responses to the consumption of these products. A total of 120 RCTs were selected. Despite a high heterogeneity, the intake of the flavanol-containing products was associated using a random model with changes (reported as standardized difference in means (SDM)) in body mass index (−0.15, p < 0.001), waist circumference (−0.29, p < 0.001), total-cholesterol (−0.21, p < 0.001), LDL-cholesterol (−0.23, p < 0.001), and triacylglycerides (−0.11, p = 0.027), and with an increase of HDL-cholesterol (0.15, p = 0.005). Through subgroup analyses, we showed the influence of baseline-BMI, sex, source/form of administration, medication and country of investigation on some of the outcome measures and suggest that flavanols may be more effective in specific subgroups such as those with a BMI ≥ 25.0 kg/m2, non-medicated individuals or by specifically using tea products. This meta-analysis provides the first robust evidence of the effects induced by the consumption of flavanol-containing tea, cocoa and apple products on weight and lipid biomarkers and shows the influence of various factors that can affect their bioefficacy in humans. Of note, some of these effects are quantitatively comparable to those produced by drugs, life-style changes or other natural products. Further, RCTs in well-characterized populations are required to fully comprehend the factors affecting inter-individual responses to flavanol and thereby improve flavanols efficacy in the prevention of cardiometabolic disordersinfo:eu-repo/semantics/publishedVersio
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