Statistical Quality Control with the qcr Package

[Abstract] The R package qcr for Statistical Quality Control (SQC) is introduced and described. It includes a comprehensive set of univariate and multivariate SQC tools that completes and increases the SQC techniques available in R. Apart from integrating different R packages devoted to SQC (qcc, MSQC), qcr provides nonparametric tools that are highly useful when Gaussian assumption is not met. This package computes standard univariate control charts for individual measurements, (Formula presented), S, R, p, np, c, u, EWMA, and CUSUM. In addition, it includes functions to perform multivariate control charts such as Hotelling T2, MEWMA and MCUSUM. As representative features, multivariate nonparametric alternatives based on data depth are implemented in this package: r, Q and S control charts. The qcr library also estimates the most complete set of capability indices from first to the fourth generation, covering the nonparametric alternatives, and performing the corresponding capability analysis graphical outputs, including the process capability plots. Moreover, Phase I and II control charts for functional data are included.The work of Salvador Naya, Javier Tarrío-Saavedra, Miguel Flores and Rubén Fernández-Casal has been supported by MINECO grant MTM2017-82724-R, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema universitario de Galicia ED431G 2019/01), all of them through the ERDF. The research of Miguel Flores has been partially supported by Grant PII-DM-002-2016 of Escuela Politécnica Nacional of Ecuador. In addition, the research of Javier Tarrío-Saavedra has been also founded by the eCOAR project (PC18/03) of CITICXunta de Galicia; ED431C-2020-14Xunta de Galicia; ED431G 2019/01Escuela Politécnica Nacional de Ecuador; PII-DM-002-201

A computational validation for nonparametric assessment of spatial trends

Versión final aceptada de: https://doi.org/10.1007/s00180-021-01108-0This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00180-021-01108-0The analysis of continuously spatially varying processes usually considers two sources of variation, namely, the large-scale variation collected by the trend of the process, and the small-scale variation. Parametric trend models on latitude and longitude are easy to fit and to interpret. However, the use of parametric models for characterizing spatially varying processes may lead to misspecification problems if the model is not appropriate. Recently, Meilán-Vila et al. (TEST 29:728–749, 2020) proposed a goodness-of-fit test based on an -distance for assessing a parametric trend model with correlated errors, under random design, comparing parametric and nonparametric trend estimates. The present work aims to provide a detailed computational analysis of the behavior of this approach using different bootstrap algorithms for calibration, one of them including a procedure that corrects the bias introduced by the direct use of the residuals in the variogram estimation, under a fixed design geostatistical framework. Asymptotic results for the test are provided and an extensive simulation study, considering complexities that usually arise in geostatistics, is carried out to illustrate the performance of the proposal. Specifically, we analyze the impact of the sample size, the spatial dependence range and the nugget effect on the empirical calibration and power of the test.The authors acknowledge the support from the Xunta de Galicia grant ED481A- 2017/361 and the European Union (European Social Fund - ESF). This research has been partially supported by MINECO grants MTM2016-76969-P and MTM2017-82724-R, and by the Xunta de Galicia (Grupo de Referencia Competitiva ED431C-2016-015, ED431C-2017-38 and ED431C-2020-14, and Centro de Investigación del SUG ED431G 2019/01), all of them through the ERDF. The authors also thank two anonymous referees and the Associate Editor for their comments that significantly improved this article.Xunta de Galicia; ED481A- 2017/361Xunta de Galicia; ED431C-2016-015Xunta de Galicia; ED431C-2017-38Xunta de Galicia; ED431C-2020-14Xunta de Galicia; ED431G 2019/0

Constructing a Control Chart Using Functional Data

[Abstract] This study proposes a control chart based on functional data to detect anomalies and estimate the normal output of industrial processes and services such as those related to the energy efficiency domain. Companies providing statistical consultancy services in the fields of energy efficiency; heating, ventilation and air conditioning (HVAC); installation and control; and big data for buildings, have been striving to solve the problem of automatic anomaly detection in buildings controlled by sensors. Given the functional nature of the critical to quality (CTQ) variables, this study proposed a new functional data analysis (FDA) control chart method based on the concept of data depth. Specifically, it developed a control methodology, including the Phase I and II control charts. It is based on the calculation of the depth of functional data, the identification of outliers by smooth bootstrap resampling and the customization of nonparametric rank control charts. A comprehensive simulation study, comprising scenarios defined with different degrees of dependence between curves, was conducted to evaluate the control procedure. The proposed statistical process control procedure was also applied to detect energy efficiency anomalies in the stores of a textile company in the Panama City. In this case, energy consumption has been defined as the CTQ variable of the HVAC system. Briefly, the proposed methodology, which combines FDA and multivariate techniques, adapts the concept of the control chart based on a specific case of functional data and thereby presents a novel alternative for controlling facilities in which the data are obtained by continuous monitoring, as is the case with a great deal of process in the framework of Industry 4.0.This study has been funded by the eCOAR project (PC18/03) of CITIC. The work of Salvador Naya, Javier Tarrío-Saavedra, Miguel Flores and Rubén Fernández-Casal has been supported by MINECO grants MTM2014-52876-R, MTM2017-82724-R, the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2016-015, and Centro Singular de Investigación de Galicia ED431G/01 2016-19), through the ERDF. The research of Miguel Flores has been partially supported by Grant PII-DM-002-2016 of Escuela Politécnica Nacional of EcuadorXunta de Galicia; ED431C-2016-015Xunta de Galicia; ED431G/01 2016-19Escuela Politécnica Nacional de Ecuador; PII-DM-002-201

Proceedings of the 8th International Conference on Data Science, Technology and Applications (DATA 2019)

[Abstract] The aim of this work is to propose different statistical and machine learning methodologies for identifying anomalies and control the quality of energy efficiency and hygrothermal comfort in buildings. Companies focused on energy sector for buildings are interested on statistical and machine learning tools to automate the control of energy consumption and ensure quality of Heat Ventilation and Air Conditioning (HVAC) installations. Consequently, a methodology based on the application of the Local Correlation Integral (LOCI) anomaly detection technique has been proposed. In addition, the most critical variables for anomaly detection are identified by using ReliefF method. Once vectors of critical variables are obtained, multivariate and univariate control charts can be applied to control the quality of HVAC installations (consumption, thermal comfort). In order to test the proposed methodology, the companies involved in this project have provided the case study of a store of a clothing brand located in a shopping center in Panama. It is important to note that this is a controlled case study for which all the anomalies have been previously identified by maintenance personnel. Moreover, as an alternatively solution, in addition to machine learning and multivariate techniques, new nonparametric control charts for functional data based on data depth have been proposed and applied to curves of daily energy consumption in HVAC.Ministerio de Asuntos Económicos y Transformación Digital; MTM2014-52876-RMinisterio de Asuntos Económicos y Transformación Digital; MTM2017-82724-RXunta de Galicia; ED431C-2016-015Centro Singular de Investigación de Galicia; ED431G/01 2016-19Centro de Investigación en Tecnoloxías da Información e as Comunicacións da Universidade da Coruña; PC18/03Escuela Politécnica Nacional of Ecuador; PII-DM-002-201

Functional Proteomics Characterization of the Role of SPRYD7 in Colorectal Cancer Progression and Metastasis

SPRY domain-containing protein 7 (SPRYD7) is a barely known protein identified via spatial proteomics as being upregulated in highly metastatic-to-liver KM12SM colorectal cancer (CRC) cells in comparison to its isogenic poorly metastatic KM12C CRC cells. Here, we aimed to analyze SPRYD7’s role in CRC via functional proteomics. Through immunohistochemistry, the overexpression of SPRYD7 was observed to be associated with the poor survival of CRC patients and with an aggressive and metastatic phenotype. Stable SPRYD7 overexpression was performed in KM12C and SW480 poorly metastatic CRC cells and in their isogenic highly metastatic-to-liver-KM12SM-and-to-lymph-nodes SW620 CRC cells, respectively. Upon upregulation of SPRYD7, in vitro and in vivo functional assays confirmed a key role of SPRYD7 in the invasion and migration of CRC cells and in liver homing and tumor growth. Additionally, transient siRNA SPRYD7 silencing allowed us to confirm in vitro functional results. Furthermore, SPRYD7 was observed as an inductor of angiogenesis. In addition, the dysregulated SPRYD7-associated proteome and SPRYD7 interactors were elucidated via 10-plex TMT quantitative proteins, immunoproteomics, and bioinformatics. After WB validation, the biological pathways associated with the stable overexpression of SPRYD7 were visualized. In conclusion, it was demonstrated here that SPRYD7 is a novel protein associated with CRC progression and metastasis. Thus, SPRYD7 and its interactors might be of relevance in identifying novel therapeutic targets for advanced CRC

Colour assessment outcomes – a new approach to grading the severity of color vision loss

INTRODUCTION: Recent studies have shown that a significant percentage of subjects with anomalous, congenital trichromacy can perform the suprathreshold, colour-related tasks encountered in many occupations with the same accuracy as normal trichromats. In the absence of detailed, occupation-specific studies, an alternative approach is to make use of new findings and the statistical outcomes of past practices that have been considered safe to produce graded, justifiable categories of colour vision that can be enforced. METHODS: We analyzed traditional color assessment outcomes and measured severity of colour vision loss using the CAD test in 1363 subjects (336 normals, 705 deutan, 319 protan and 3 tritan). The severity of colour vision loss was measured in each subject and statistical, pass / fail outcomes established for each of the most commonly used, conventional colour assessment tests and protocols. RESULTS: The correlation between the number of Ishihara (IH) test plates subjects fail and the severity of RG colour vision loss was very poor. The 38 plates IH test has high sensitivity when no errors are allowed (i.e., only 0.71% deutans and 0.63% protans pass). Protocols based on zero errors are uncommon since 18.15% of normal trichromats fail. The most common protocols employ either the 24 or the 14 plates editions with two or less errors. These protocols pass almost all normal trichromats, but the deutans and some protans that also pass (when two or less errors are allowed) can be severely deficient. This is simply because the most challenging plates have not been included in the 24 and 14 plates editions. As a result, normals no longer fail, but the deutans and protans that pass have more severe loss of colour vision since they fail less challenging plates. The severity of colour vision loss was measured in each subject and statistical, pass / fail outcomes established for each of the most commonly used, conventional colour assessment tests and protocols. DISCUSSION: Historical evidence and new findings that relate severity of loss to the effective use of colour signals in a number of tasks provide the basis for a new colour grading system based on six categories. A single colour assessment test is needed to establish the applicant’s Colour Vision category which can range from ‘supernormal’ (CV0), for the most stringent, colour-demanding tasks, to ‘severe colour deficiency’, when red / green colour vision is either absent or extremely weak (CV5)

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients

Background: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation

Nonparametric geostatistical risk mapping

Versión final aceptada de: https://doi.org/10.1007/s00477-017-1407-yThis version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00477-017-1407-yIn this work, a fully nonparametric geostatistical approach to estimate threshold exceeding probabilities is proposed. To estimate the large-scale variability (spatial trend) of the process, the nonparametric local linear regression estimator, with the bandwidth selected by a method that takes the spatial dependence into account, is used. A bias-corrected nonparametric estimator of the variogram, obtained from the nonparametric residuals, is proposed to estimate the small-scale variability. Finally, a bootstrap algorithm is designed to estimate the unconditional probabilities of exceeding a threshold value at any location. The behavior of this approach is evaluated through simulation and with an application to a real data set.The research of Rubén Fernández-Casal and Mario Francisco-Fernández has been partially supported by the Consellería de Cultura, Educación e Ordenación Universitaria of the Xunta de Galicia through the agreement for the Singular Research Center CITIC, and by Grant MTM2014-52876-R. The research of Sergio Castillo has been partially supported by the Universidad de las Fuerzas Armadas ESPE, from Ecuador. The authors thank the associate editor and two referees for constructive comments that improved the presentation of this article

La organización territorial del comercio en la provincia de Cuencar: un estudio interdisciplinar

Una de las principales preocupaciones a la hora de aplicar instrumentos de ordenación territorial es evaluar, desde distintos puntos de vista, el grado de coherencia interna de un espacio dado. En este artículo, tomando como criterio la distribución en el espacio de la actividad comercial y empleando una sucesión de métodos estadísticos elementales, pretendemos justamente eso, compaginando el rigor estadístico con la claridad de la interpretación geográfica. El resultado de este proceso, de raíz plenamente cuantitativa, es la de reconocer en la provincia conquense un territorio excepcional y caracterizado por unos niveles de desarticulación territorial extraordinarios fruto de su aislamiento y marginación secular