378 research outputs found

    Social Media Behaviour Analysis in Disaster-Response Messages of Floods and Heat Waves via Artificial Intelligence

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    This paper analyses social media data in multiple disaster-related collections of floods and heat waves in the UK. The proposed method uses machine learning classifiers based on deep bidirectional neural networks trained on benchmark datasets of disaster responses and extreme events. The resulting models are applied to perform a qualitative analysis via topic inference in text data. We further analyse a set of behavioural indicators and match them with climate variables via decoding synoptical records to analyse thermal comfort. We highlight the advantages of aligning behavioural indicators along with climate variables to provide with 7 additional valuable information to be considered especially in different phases of a disaster and applicable to extreme weather periods. The positiveness of messages is around 8% for disaster, 1% for disaster and medical response, 7% for disaster and humanitarian related messages. This shows the reliability of such data for our case studies. We show the transferability of this approach to be applied to any social media data collection

    CaloriNet: From silhouettes to calorie estimation in private environments

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    We propose a novel deep fusion architecture, CaloriNet, for the online estimation of energy expenditure for free living monitoring in private environments, where RGB data is discarded and replaced by silhouettes. Our fused convolutional neural network architecture is trainable end-to-end, to estimate calorie expenditure, using temporal foreground silhouettes alongside accelerometer data. The network is trained and cross-validated on a publicly available dataset, SPHERE_RGBD + Inertial_calorie. Results show state-of-the-art minimum error on the estimation of energy expenditure (calories per minute), outperforming alternative, standard and single-modal techniques.Comment: 11 pages, 7 figure

    Evaluación y requerimientos nutricionales en pacientes hospitalizados por COVID-19

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    La COVID-19 desencadena un cuadro clínico que puede impactar negativamente en el estado nutricional y en el pronóstico de los pacientes. La respuesta inflamatoria exacerbada en casos críticos, puede traer consigo una serie de alteraciones metabólicas y catabólicas que afectan directamente el estado nutricional, generando pérdida de masa muscular esquelética y desnutrición, lo que se asocia a peores desenlaces y mayores complicaciones. La valoración del estado nutricional, mediante el tamizaje y la evaluación nutricional en pacientes con COVID-19, nos permite preservar el estado nutricional y/o prevenir o tratar la desnutrición asociada y así, reducir las complicaciones asociadas a la misma. Actualmente no existe tratamiento nutricional específico frente al COVID-19, sin embargo, las diversas sociedades científicas del mundo han establecido una serie de recomendaciones para confrontar la situación nutricional. Así, en el presente trabajo se exponen los requerimientos nutricionales en pacientes con COVID-19 no ventilados en hospitalización general y en la Unidad de Cuidados Intensivos (UCI) en base al aporte de energía, carbohidratos, proteínas, lípidos y micronutrientes (vitaminas y minerales) necesarios para mejorar su pronóstico durante la estancia hospitalaria. Palabras claves: Evaluación Nutricional, Necesidades Nutricionales, Infección por Coronavirus 2019-nCoV. (fuente: DeCS)   DOI: http://dx.doi.org/10.17268/rmt.2021.v16i03.1

    Deep sequencing of the Mexican avocado transcriptome, an ancient angiosperm with a high content of fatty acids

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    Background: Avocado (Persea americana) is an economically important tropical fruit considered to be a good source of fatty acids. Despite its importance, the molecular and cellular characterization of biochemical and developmental processes in avocado is limited due to the lack of transcriptome and genomic information. Results: The transcriptomes of seeds, roots, stems, leaves, aerial buds and flowers were determined using different sequencing platforms. Additionally, the transcriptomes of three different stages of fruit ripening (pre-climacteric, climacteric and post-climacteric) were also analyzed. The analysis of the RNAseqatlas presented here reveals strong differences in gene expression patterns between different organs, especially between root and flower, but also reveals similarities among the gene expression patterns in other organs, such as stem, leaves and aerial buds (vegetative organs) or seed and fruit (storage organs). Important regulators, functional categories, and differentially expressed genes involved in avocado fruit ripening were identified. Additionally, to demonstrate the utility of the avocado gene expression atlas, we investigated the expression patterns of genes implicated in fatty acid metabolism and fruit ripening. Conclusions: A description of transcriptomic changes occurring during fruit ripening was obtained in Mexican avocado, contributing to a dynamic view of the expression patterns of genes involved in fatty acid biosynthesis and the fruit ripening process

    Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

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    Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a ZZ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 <pT<100< p_{\textrm{T}} < 100 GeV and in the pseudorapidity range 2.5<η<42.5 < \eta < 4. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb1^{-1}. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

    Notas Breves

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    Study of the BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

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    The decay BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} is studied in proton-proton collisions at a center-of-mass energy of s=13\sqrt{s}=13 TeV using data corresponding to an integrated luminosity of 5 fb1\mathrm{fb}^{-1} collected by the LHCb experiment. In the Λc+K\Lambda_{c}^+ K^{-} system, the Ξc(2930)0\Xi_{c}(2930)^{0} state observed at the BaBar and Belle experiments is resolved into two narrower states, Ξc(2923)0\Xi_{c}(2923)^{0} and Ξc(2939)0\Xi_{c}(2939)^{0}, whose masses and widths are measured to be m(Ξc(2923)0)=2924.5±0.4±1.1MeV,m(Ξc(2939)0)=2938.5±0.9±2.3MeV,Γ(Ξc(2923)0)=0004.8±0.9±1.5MeV,Γ(Ξc(2939)0)=0011.0±1.9±7.5MeV, m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV}, where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt Λc+K\Lambda_{c}^{+} K^{-} sample. Evidence of a new Ξc(2880)0\Xi_{c}(2880)^{0} state is found with a local significance of 3.8σ3.8\,\sigma, whose mass and width are measured to be 2881.8±3.1±8.5MeV2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV} and 12.4±5.3±5.8MeV12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}, respectively. In addition, evidence of a new decay mode Ξc(2790)0Λc+K\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-} is found with a significance of 3.7σ3.7\,\sigma. The relative branching fraction of BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} with respect to the BD+DKB^{-} \to D^{+} D^{-} K^{-} decay is measured to be 2.36±0.11±0.22±0.252.36 \pm 0.11 \pm 0.22 \pm 0.25, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

    Measurement of the ratios of branching fractions R(D)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

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    The ratios of branching fractions R(D)B(BˉDτνˉτ)/B(BˉDμνˉμ)\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu}) and R(D0)B(BD0τνˉτ)/B(BD0μνˉμ)\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu}) are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb1{ }^{-1} of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode τμντνˉμ\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}. The measured values are R(D)=0.281±0.018±0.024\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024 and R(D0)=0.441±0.060±0.066\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is ρ=0.43\rho=-0.43. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

    Abstracts from the Food Allergy and Anaphylaxis Meeting 2016

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