177 research outputs found

    Recovery of missing data in correlated smart grid datasets

    Get PDF
    We study the recovery of missing data from multiple smart grid datasets within a matrix completion framework. The datasets contain the electrical magnitudes required for monitoring and control of the electricity distribution system. Each dataset is described by a low rank matrix. Different datasets are correlated as a result of containing measurements of different physical magnitudes generated by the same distribution system. To assess the validity of matrix completion techniques in the recovery of missing data, we characterize the fundamental limits when two correlated datasets are jointly recovered. We then proceed to evaluate the performance of Singular Value Thresholding (SVT) and Bayesian SVT (BSVT) in this setting. We show that BSVT outperforms SVT by simulating the recovery for different correlated datasets. The performance of BSVT displays the tradeoff behaviour described by the fundamental limit, which suggests that BSVT exploits the correlation between the datasets in an efficient manner

    Distant Supervised Construction and Evaluation of a Novel Dataset of Emotion-Tagged Social Media Comments in Spanish

    Get PDF
    Tagged language resources are an essential requirement for developing machine-learning text-based classifiers. However, manual tagging is extremely time consuming and the resulting datasets are rather small, containing only a few thousand samples. Basic emotion datasets are particularly difficult to classify manually because categorization is prone to subjectivity, and thus, redundant classification is required to validate the assigned tag. Even though, in recent years, the amount of emotion-tagged text datasets in Spanish has been growing, it cannot be compared with the number, size, and quality of the datasets in English. Quality is a particularly concerning issue, as not many datasets in Spanish included a validation step in the construction process. In this article, a dataset of social media comments in Spanish is compiled, selected, filtered, and presented. A sample of the dataset is reclassified by a group of psychologists and validated using the Fleiss Kappa interrater agreement measure. Error analysis is performed by using the Sentic Computing tool BabelSenticNet. Results indicate that the agreement between the human raters and the automatically acquired tag is moderate, similar to other manually tagged datasets, with the advantages that the presented dataset contains several hundreds of thousands of tagged comments and it does not require extensive manual tagging. The agreement measured between human raters is very similar to the one between human raters and the original tag. Every measure presented is in the moderate agreement zone and, as such, suitable for training classification algorithms in sentiment analysis field

    Membrane-containing virus particles exhibit the mechanics of a composite material for genome protection

    Get PDF
    The protection of the viral genome during extracellular transport is an absolute requirement for virus survival and replication. In addition to the almost universal proteinaceous capsids, certain viruses add a membrane layer that encloses their double-stranded (ds) DNA genome within the protein shell. Using the membrane-containing enterobacterial virus PRD1 as a prototype, and a combination of nanoindentation assays by atomic force microscopy and finite element modelling, we show that PRD1 provides a greater stability against mechanical stress than that achieved by the majority of dsDNA icosahedral viruses that lack a membrane. We propose that the combination of a stiff and brittle proteinaceous shell coupled with a soft and compliant membrane vesicle yields a tough composite nanomaterial well-suited to protect the viral DNA during extracellular transport

    Why does Spain have smaller inequalities in mortality?

    Get PDF
    Background: While educational inequalities in mortality are substantial in most European countries, they are relatively small in Spain. A better understanding of the causes of these smaller inequalities in Spain may help to develop policies to reduce inequalities in mortality elsewhere. The aim of the present study was therefore to identify the specific causes of death and determinants contributing to these smaller inequalities. Methods: Data on mortality by education were obtained from longitudinal mortality studies in three Spanish populations (Barcelona, Madrid, the Basque Country), and six other Western European populations. Data on determinants by education were obtained from health interview surveys. Results: The Spanish populations have considerably smaller absolute inequalities in mortality than other Western European populations. This is due mainly to smaller inequalities in mortality from cardiovascular disease (men) and cancer (women). Inequalities in mortality from most other causes are not smaller in Spain than elsewhere. Spain also has smaller inequalities in smoking and sedentary lifestyle and this is due to more smoking and physical inactivity in higher educated groups. Conclusion: Overall, the situation with regard to health inequalities does not appear to be more favourable in Spain than in other Western European populations. Smaller inequalities in mortality from cardiovascular disease and cancer in Spain are likely to be related to its later socio-economic modernization. Although these smaller inequalities in mortality seem to be a historical coincidence rather than the outcome of deliberate policies, the Spanish example does suggest that large inequalities in total mortality are

    Synchrony-induced modes of oscillation of a neural field model

    Get PDF
    We investigate the modes of oscillation of heterogeneous ring-networks of quadratic integrate-and-fire (QIF) neurons with non-local, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogous to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network’s oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions. In the thermodynamic limit, an exact low-dimensional neural field model (QIF-NFM) describing the macroscopic dynamics of the network is derived. This allows us to obtain formulas for the Turing eigenvalues of the spatially-homogeneous state, and hence to obtain its stability boundary. We find that the frequency of each Turing mode depends on the corresponding Fourier coefficient of the synaptic pattern of connectivity. The decay rate instead, is identical for all oscillation modes as a consequence of the heterogeneity-induced desynchronization of the neurons. Finally, we numerically compute the spectrum of spatially-inhomogeneous solutions branching from the Turing bifurcation, showing that similar oscillatory modes operate in neural bump states, and are maintained away from onset

    Stable socioeconomic inequalities in ischaemic heart disease mortality during the economic crisis : A time trend analysis in 2 Spanish settings

    Get PDF
    Prior studies have identified a decrease in ischaemic heart disease mortality during the recent economic recession. The Spanish population was severely affected by the Great Recession, however, there is little evidence on its effects on socioeconomic inequalities in ischaemic heart disease mortality. This study examines trends in socioeconomic inequalities in mortality due to ischaemic heart disease (IHD). We used linked census records with mortality registers available from the Basque Country and Barcelona city for population above 25 years, between 2001 and 04, the accelerated economic growth period of 2005-08, and 2009-12, with the last period coinciding with the Great Recession. Applying Poisson models, we calculated relative and absolute indexes of inequalities by education level for each period, age group, gender, and site. We found moderate age-adjusted inequalities in IHD with a gradient of increasing rates through less educational level, but no significant evidence of increasing trends in socioeconomic inequalities in IHD mortality, rather an inverted U-shape time trend in some groups below 75 years in relative inequalities. Absolute inequalities decrease in the last period except for women from 50 to 64 years. This study shows that the economic crisis has not increased socioeconomic inequalities in IHD mortality in two geographical settings in Spain

    SwarmCom : an infra-red-based mobile ad-hoc network for severely constrained robots

    Get PDF
    Swarm robotics investigates groups of relatively simple robots that use decentralized control to achieve a common goal. While the robots of many swarm systems communicate via optical links, the underlying channels and their impact on swarm performance are poorly understood. This paper models the optical channel of a widely used robotic platform, the e-puck. It proposes SwarmCom, a mobile ad-hoc network for mobile robots. SwarmCom has a detector that, with the help of the channel model, was designed to adapt to the environment and nearby robots. Experiments with groups of up to 30 physical e-pucks show that (i) SwarmCom outperforms the state-of-the-art infra-red communication software—libIrcom—in range (up to 3 times further), bit error rate (between 50 and 63% lower), or throughput (up to 8 times higher) and that (ii) the maximum number of communication channels per robot is relatively low, which limits the load per robot even for high-density swarms. Using channel coding, the bit error rate can be further reduced at the expense of throughput. SwarmCom could have profound implications for swarm robotics, contributing to system understanding and reproducibility, while paving the way for novel applications

    Early prediction of clinical response to checkpoint inhibitor therapy in human solid tumors through mathematical modeling

    Get PDF
    Background:: Checkpoint inhibitor therapy of cancer has led to markedly improved survival of a subset of patients in multiple solid malignant tumor types, yet the factors driving these clinical responses or lack thereof are not known. We have developed a mechanistic mathematical model for better understanding these factors and their relations in order to predict treatment outcome and optimize personal treatment strategies. Methods:: Here, we present a translational mathematical model dependent on three key parameters for describing efficacy of checkpoint inhibitors in human cancer: tumor growth rate (α), tumor-immune infiltration (Λ), and immunotherapy-mediated amplification of anti-tumor response (µ). The model was calibrated by fitting it to a compiled clinical tumor response dataset (n = 189 patients) obtained from published anti-PD-1 and anti-PD-L1 clinical trials, and then validated on an additional validation cohort (n = 64 patients) obtained from our in-house clinical trials. Results:: The derived parameters Λ and µ were both significantly different between responding versus nonresponding patients. Of note, our model appropriately classified response in 81.4% of patients by using only tumor volume measurements and within 2 months of treatment initiation in a retrospective analysis. The model reliably predicted clinical response to the PD-1/PD-L1 class of checkpoint inhibitors across multiple solid malignant tumor types. Comparison of model parameters to immunohistochemical measurement of PD-L1 and CD8+ T cells confirmed robust relationships between model parameters and their underlying biology. Conclusions:: These results have demonstrated reliable methods to inform model parameters directly from biopsy samples, which are conveniently obtainable as early as the start of treatment. Together, these suggest that the model parameters may serve as early and robust biomarkers of the efficacy of checkpoint inhibitor therapy on an individualized per-patient basis. Funding:: We gratefully acknowledge support from the Andrew Sabin Family Fellowship, Center for Radiation Oncology Research, Sheikh Ahmed Center for Pancreatic Cancer Research, GE Healthcare, Philips Healthcare, and institutional funds from the University of Texas M.D. Anderson Cancer Center. We have also received Cancer Center Support Grants from the National Cancer Institute (P30CA016672 to the University of Texas M.D. Anderson Cancer Center and P30CA072720 the Rutgers Cancer Institute of New Jersey). This research has also been supported in part by grants from the National Science Foundation Grant DMS-1930583 (ZW, VC), the National Institutes of Health (NIH) 1R01CA253865 (ZW, VC), 1U01CA196403 (ZW, VC), 1U01CA213759 (ZW, VC), 1R01CA226537 (ZW, RP, WA, VC), 1R01CA222007 (ZW, VC), U54CA210181 (ZW, VC), and the University of Texas System STARS Award (VC). BC acknowledges support through the SER Cymru II Programme, funded by the European Commission through the Horizon 2020 Marie Skłodowska-Curie Actions (MSCA) COFUND scheme and the Welsh European Funding Office (WEFO) under the European Regional Development Fund (ERDF). EK has also received support from the Project Purple, NIH (U54CA210181, U01CA200468, and U01CA196403), and the Pancreatic Cancer Action Network (16-65-SING). MF was supported through NIH/NCI center grant U54CA210181, R01CA222959, DoD Breast Cancer Research Breakthrough Level IV Award W81XWH-17-1-0389, and the Ernest Cockrell Jr. Presidential Distinguished Chair at Houston Methodist Research Institute. RP and WA received serial research awards from AngelWorks, the Gillson-Longenbaugh Foundation, and the Marcus Foundation. This work was also supported in part by grants from the National Cancer Institute to SHC (R01CA109322, R01CA127483, R01CA208703, and U54CA210181 CITO pilot grant) and to PYP (R01CA140243, R01CA188610, and U54CA210181 CITO pilot grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    KIMA: Noise: A visual sound installation on urban noise

    Get PDF
    KIMA: Noise is a participatory art piece inviting audiences to explore impact of urban noises interactively. Using specific urban sound sources, the audience experiences noise as spatial soundscapes, responding to it, physically engaging and interacting with it. KIMA: Noise creates awareness for the phenomenon of noise pollution. The paper looks at preeminent research in the field, and draws conclusions of how sound affects us as individuals. The art project KIMA: Noise is introduced technically and conceptually
    corecore