Dimension Estimation Using Random Connection Models

Information about intrinsic dimension is crucial to perform dimensionality reduction, compress information, design efficient algorithms, and do statistical adaptation. In this paper we propose an estimator for the intrinsic dimension of a data set. The estimator is based on binary neighbourhood information about the observations in the form of two adjacency matrices, and does not require any explicit distance information. The underlying graph is modelled according to a subset of a specific random connection model, sometimes referred to as the Poisson blob model. Computationally the estimator scales like n log n, and we specify its asymptotic distribution and rate of convergence. A simulation study on both real and simulated data shows that our approach compares favourably with some competing methods from the literature, including approaches that rely on distance information

Road traffic estimation and distribution-based route selection

In route selection problems, the driver's personal preferences will determine whether she prefers a route with a travel time that has a relatively low mean and high variance over one that has relatively high mean and low variance. In practice, however, such risk aversion issues are often ignored, in that a route is selected based on a single-criterion Dijkstra-type algorithm. In addition, the routing decision typically does not take into account the uncertainty in the estimates of the travel time's mean and variance. This paper aims at resolving both issues by setting up a framework for travel time estimation. In our framework, the underlying road network is represented as a graph. Each edge is subdivided into multiple smaller pieces, so as to naturally model the statistical similarity between road pieces that are spatially nearby. Relying on a Bayesian approach, we construct an estimator for the joint per-edge travel time distribution, thus also providing us with an uncertainty quantification of our estimates. Our machinery relies on establishing limit theorems, making the resulting estimation procedure robust in the sense that it effectively does not assume any distributional properties. We present an extensive set of numerical experiments that demonstrate the validity of the estimation procedure and the use of the distributional estimates in the context of data-driven route selection

Triagem de hidrocarbonetos em bactérias isoladas de amostras da Antártida

Anais do V Encontro de Iniciação Científica e I Encontro Anual de Iniciação ao Desenvolvimento Tecnológico e Inovação – EICTI 2016 - 05 e 07 de outubro de 2016 – Sessão BiológicasVive-se um momento em que se faz necessário o aumento da produção energética no globo. Este quadro leva à exploração dos recursos naturais. Diante disso, buscam-se fontes renováveis de energia. Uma dessas alternativas são os chamados micro-organismos psicrofílicos. Estes apresentam características singulares, sendo capazes de sobreviver às baixas temperaturas de biomas como o continente Antártico. Existem estudos que procuram obter células microbianas com o intuito de sintetizar hidrocarbonetos ou outros compostos que derivam de hidrocarbonetos no propósito de utilizá-los como biocombustíveis. Esta opção apresentaria uma possibilidade de produção de combustíveis tidos como ecologicamente corretos, uma substituição aos combustíveis derivados do petróleo – fato que torna essas fontes de energia a partir de sistemas microbianos alternativas emergentes. O presente trabalho utilizou micro-organismos psicrofílicos ou psicrotolerantes isolados de amostras do continente Antártico com o objetivo de realizar a prospecção de hidrocarbonetos com potencial de utilização em processos de produção de biocombustíveis

TOFtracker: combination of time-of-flight and high-accuracy bidimensional tracking in a single gaseous detector

A 5-gap timing RPC equipped with patterned electrodes coupled to both charge-sensitive and timing circuits yields a time accuracy of 77 ps along with a position accuracy of 38 μm. These results were obtained by calculating the straight-line fit residuals to the positions provided by a 3-layer telescope made out of identical detectors, detecting almost perpendicular cosmic-ray muons. The device may be useful for particle identification by time-of-flight, where simultaneous measurements of trajectory and time are necessary

A cross-sectional study on nurses' attitudes towards physical restraints use in nursing homes in Portugal

© 2021 The Authors. Nursing Open published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.Aim: To explore nurses' opinions regarding restraint measures and attitudes towards physical restraints use in nursing homes. Design: Cross-sectional study. Methods: Nursing staff of 33 Portuguese nursing homes was asked to complete the Portuguese version of the Maastricht Attitude Questionnaire (MAQ), an instrument on attitudes regarding physical restraints (reasons, consequences and appropriateness of restraint use) and opinions about restraint measures (restrictiveness and discomfort). Descriptive statistics and bivariate analysis were performed. Results: Data from 186 nurses were included in the analysis. Overall, nurses expressed neutral to moderately positive attitudes towards physical restraints usage. Nurses with longer professional experience reported a more positive attitude regarding the appropriateness of restraint use in their clinical practice. Wrist and ankle restraints were the measures that nurses reported feeling most uncomfortable using, and the most restrictive. Bilateral bedrails were globally assessed as a slightly restrictive measure and nurses reported not feeling uncomfortable using them.The first author has an individual doctoral scholarship funded by Fundação para a Ciência e Tecnologia FCT, grant reference SFRH/BD/130970/2017info:eu-repo/semantics/publishedVersio

ISCOM-like nanoparticles formulated with Quillaja brasiliensis Saponins are promising adjuvants for seasonal influenza vaccines

Vaccination is the most effective public health intervention to prevent influenza infections, which are responsible for an important burden of respiratory illnesses and deaths each year. Currently, licensed influenza vaccines are mostly split inactivated, although in order to achieve higher efficacy rates, some influenza vaccines contain adjuvants. Although split-inactivated vaccines induce mostly humoral responses, tailoring mucosal and cellular immune responses is crucial for preventing influenza infections. Quillaja brasiliensis saponin-based adjuvants, including ISCOM-like nanoparticles formulated with the QB-90 saponin fraction (IQB90), have been studied in preclinical models for more than a decade and have been demonstrated to induce strong humoral and cellular immune responses towards several viral antigens. Herein, we demonstrate that a split-inactivated IQB90 adjuvanted influenza vaccine triggered a protective immune response, stronger than that induced by a commercial unadjuvanted vaccine, when applied either by the subcutaneous or the intranasal route. Moreover, we reveal that this novel adjuvant confers up to a ten-fold dose-sparing effect, which could be crucial for pandemic preparedness. Last but not least, we assessed the role of caspase-1/11 in the generation of the immune response triggered by the IQB90 adjuvanted influenza vaccine in a mouse model and found that the cellular-mediated immune response triggered by the IQB90-Flu relies, at least in part, on a mechanism involving the casp-1/11 pathway but not the humoral response elicited by this formulation