This page has only limited features, please log in for full access.
In this paper, we extend the use of disjoint orthogonal components to three-way table analysis with the parallel factor analysis model. Traditional methods, such as scaling, orthogonality constraints, non-negativity constraints, and sparse techniques, do not guarantee that interpretable loading matrices are obtained in this model. We propose a novel heuristic algorithm that allows simple structure loading matrices to be obtained by calculating disjoint orthogonal components. This algorithm is also an alternative approach for solving the well-known degeneracy problem. We carry out computational experiments by utilizing simulated and real-world data to illustrate the benefits of the proposed algorithm.
Carlos Martin-Barreiro; John A. Ramirez-Figueroa; Xavier Cabezas; Victor Leiva; Ana Martin-Casado; M. Purificación Galindo-Villardón. A New Algorithm for Computing Disjoint Orthogonal Components in the Parallel Factor Analysis Model with Simulations and Applications to Real-World Data. Mathematics 2021, 9, 2058 .
AMA StyleCarlos Martin-Barreiro, John A. Ramirez-Figueroa, Xavier Cabezas, Victor Leiva, Ana Martin-Casado, M. Purificación Galindo-Villardón. A New Algorithm for Computing Disjoint Orthogonal Components in the Parallel Factor Analysis Model with Simulations and Applications to Real-World Data. Mathematics. 2021; 9 (17):2058.
Chicago/Turabian StyleCarlos Martin-Barreiro; John A. Ramirez-Figueroa; Xavier Cabezas; Victor Leiva; Ana Martin-Casado; M. Purificación Galindo-Villardón. 2021. "A New Algorithm for Computing Disjoint Orthogonal Components in the Parallel Factor Analysis Model with Simulations and Applications to Real-World Data." Mathematics 9, no. 17: 2058.
Background: Systematic screening for antibodies against SARS-CoV-2 is a crucial tool for surveillance of the COVID-19 pandemic. The University of Salamanca (USAL) in Spain designed a project called “DIANCUSAL” (Diagnosis of New Coronavirus, COVID-19, in University of Salamanca) to measure antibodies against SARS-CoV-2 among its ~34,000 students and academic staff, as the influence of the university community in the spread of the SARS-CoV-2 pandemic in the city of Salamanca and neighboring towns hosting USAL campuses could be substantial. Objective: The aim of this study was to estimate the prevalence of SARS-CoV-2 antibodies among USAL students, professors and staff and to evaluate the demographic, academic, clinical and lifestyle and behavioral factors related to seropositivity. Methodology: The DIANCUSAL study is an ongoing university population-based cross-sectional study, with the work described herein conducted from July–October 2020. All USAL students, professors and staff were invited to complete an anonymized questionnaire. Seroprevalence of anti-SARS-CoV-2 antibodies was detected and quantified by using chemiluminescent assays for IgG and IgM. Principal findings: A total of 8197 (24.71%) participants were included. The mean age was 31.4 (14.5 SD) years, and 66.0% of the participants were female. The seroprevalence was 8.25% overall and was highest for students from the education campus (12.5%) and professors from the biomedical campus (12.6%), with significant differences among faculties (p = 0.006). Based on the questionnaire, loss of smell and fever were the symptoms most strongly associated with seropositivity, and 22.6% of seropositive participants were asymptomatic. Social distancing was the most effective hygiene measure (p = 0.0007). There were significant differences in seroprevalence between participants with and without household exposure to SARS-CoV-2 (p = 0.0000), but not between students who lived in private homes and those who lived in dormitories. IgG antibodies decreased over time in the participants with confirmed self-reported COVID-19 diagnoses. Conclusions: The analysis revealed an overall 8.25% seroprevalence at the end of October 2020, with a higher seroprevalence in students than in staff. Thus, there is no need for tailored measures for the USAL community as the official average seroprevalence in the area was similar (7.8% at 22 June and 12.4 at 15 November of 2020). Instead, USAL members should comply with public health measures.
Antonio Muro; Moncef Belhassen-García; Juan Muñoz Bellido; Helena Lorenzo Juanes; Belén Vicente; Josué Pendones; José Adserias; Gonzalo Sánchez Hernández; Miguel Rodríguez Rosa; José Vicente Villardón; Javier Burguillo; Javier López Andaluz; Jose Martín Oterino; Francisco García Criado; Fausto Barbero; Ana Morales; Purificación Galindo Villardón; Rogelio González Sarmiento; on behalf of the DIANCUSAL Team. Seroprevalence of SARS-CoV-2 Antibodies and Factors Associated with Seropositivity at the University of Salamanca: The DIANCUSAL Study. Journal of Clinical Medicine 2021, 10, 3214 .
AMA StyleAntonio Muro, Moncef Belhassen-García, Juan Muñoz Bellido, Helena Lorenzo Juanes, Belén Vicente, Josué Pendones, José Adserias, Gonzalo Sánchez Hernández, Miguel Rodríguez Rosa, José Vicente Villardón, Javier Burguillo, Javier López Andaluz, Jose Martín Oterino, Francisco García Criado, Fausto Barbero, Ana Morales, Purificación Galindo Villardón, Rogelio González Sarmiento, on behalf of the DIANCUSAL Team. Seroprevalence of SARS-CoV-2 Antibodies and Factors Associated with Seropositivity at the University of Salamanca: The DIANCUSAL Study. Journal of Clinical Medicine. 2021; 10 (15):3214.
Chicago/Turabian StyleAntonio Muro; Moncef Belhassen-García; Juan Muñoz Bellido; Helena Lorenzo Juanes; Belén Vicente; Josué Pendones; José Adserias; Gonzalo Sánchez Hernández; Miguel Rodríguez Rosa; José Vicente Villardón; Javier Burguillo; Javier López Andaluz; Jose Martín Oterino; Francisco García Criado; Fausto Barbero; Ana Morales; Purificación Galindo Villardón; Rogelio González Sarmiento; on behalf of the DIANCUSAL Team. 2021. "Seroprevalence of SARS-CoV-2 Antibodies and Factors Associated with Seropositivity at the University of Salamanca: The DIANCUSAL Study." Journal of Clinical Medicine 10, no. 15: 3214.
Data of the commercial parameters of Pleurotus ostreatus and Pleurotus djamor were analyzed using the data mining technique: K-means clustering algorithm. The parameters evaluated were: biological efficiency, crop yield ratio, productivity rate, nutritional composition, antioxidant and antimicrobial activities in the production of fruit bodies of 50 strains of Pleurotus ostreatus and 50 strains of Pleurotus djamor, cultivated on the most representative agricultural wastes from the province of Guayas: 80% sugarcane bagasse and 20% wheat straw (M1), and 60% wheat straw and 40% sugarcane bagasse (M2). The database of the parameters obtained in experimental procedures was grouped into three clusters, providing a visualization of the strains with a higher relation to each parameter (vector) measured.
Fabricio Guevara-Viejó; Juan Valenzuela-Cobos; Purificación Vicente-Galindo; Purificación Galindo-Villardón. Application of K-Means Clustering Algorithm to Commercial Parameters of Pleurotus spp. Cultivated on Representative Agricultural Wastes from Province of Guayas. Journal of Fungi 2021, 7, 537 .
AMA StyleFabricio Guevara-Viejó, Juan Valenzuela-Cobos, Purificación Vicente-Galindo, Purificación Galindo-Villardón. Application of K-Means Clustering Algorithm to Commercial Parameters of Pleurotus spp. Cultivated on Representative Agricultural Wastes from Province of Guayas. Journal of Fungi. 2021; 7 (7):537.
Chicago/Turabian StyleFabricio Guevara-Viejó; Juan Valenzuela-Cobos; Purificación Vicente-Galindo; Purificación Galindo-Villardón. 2021. "Application of K-Means Clustering Algorithm to Commercial Parameters of Pleurotus spp. Cultivated on Representative Agricultural Wastes from Province of Guayas." Journal of Fungi 7, no. 7: 537.
In this paper, we group South American countries based on the number of infected cases and deaths due to COVID-19. The countries considered are: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Peru, Paraguay, Uruguay, and Venezuela. The data used are collected from a database of Johns Hopkins University, an institution that is dedicated to sensing and monitoring the evolution of the COVID-19 pandemic. A statistical analysis, based on principal components with modern and recent techniques, is conducted. Initially, utilizing the correlation matrix, standard components and varimax rotations are calculated. Then, by using disjoint components and functional components, the countries are grouped. An algorithm that allows us to keep the principal component analysis updated with a sensor in the data warehouse is designed. As reported in the conclusions, this grouping changes depending on the number of components considered, the type of principal component (standard, disjoint or functional) and the variable to be considered (infected cases or deaths). The results obtained are compared to the k-means technique. The COVID-19 cases and their deaths vary in the different countries due to diverse reasons, as reported in the conclusions.
Carlos Martin-Barreiro; John Ramirez-Figueroa; Xavier Cabezas; Víctor Leiva; M. Galindo-Villardón. Disjoint and Functional Principal Component Analysis for Infected Cases and Deaths Due to COVID-19 in South American Countries with Sensor-Related Data. Sensors 2021, 21, 4094 .
AMA StyleCarlos Martin-Barreiro, John Ramirez-Figueroa, Xavier Cabezas, Víctor Leiva, M. Galindo-Villardón. Disjoint and Functional Principal Component Analysis for Infected Cases and Deaths Due to COVID-19 in South American Countries with Sensor-Related Data. Sensors. 2021; 21 (12):4094.
Chicago/Turabian StyleCarlos Martin-Barreiro; John Ramirez-Figueroa; Xavier Cabezas; Víctor Leiva; M. Galindo-Villardón. 2021. "Disjoint and Functional Principal Component Analysis for Infected Cases and Deaths Due to COVID-19 in South American Countries with Sensor-Related Data." Sensors 21, no. 12: 4094.
Models implemented in statistical software for the precision analysis of diagnostic tests include random-effects modeling (bivariate model) and hierarchical regression (hierarchical summary receiver operating characteristic). However, these models do not provide an overall mean, but calculate the mean of a central study when the random effect is equal to zero; hence, it is difficult to calculate the covariance between sensitivity and specificity when the number of studies in the meta-analysis is small. Furthermore, the estimation of the correlation between specificity and sensitivity is affected by the number of studies included in the meta-analysis, or the variability among the analyzed studies. To model the relationship of diagnostic test results, a binary covariance matrix is assumed. Here we used copulas as an alternative to capture the dependence between sensitivity and specificity. The posterior values were estimated using methods that consider sampling algorithms from a probability distribution (Markov chain Monte Carlo), and estimates were compared with the results of the bivariate model, which assumes statistical independence in the test results. To illustrate the applicability of the models and their respective comparisons, data from 14 published studies reporting estimates of the accuracy of the Alcohol Use Disorder Identification Test were used. Using simulations, we investigated the performance of four copula models that incorporate scenarios designed to replicate realistic situations for meta-analyses of diagnostic accuracy of the tests. The models’ performances were evaluated based on p-values using the Cramér–von Mises goodness-of-fit test. Our results indicated that copula models are valid when the assumptions of the bivariate model are not fulfilled.
Johny Pambabay-Calero; Sergio Bauz-Olvera; Ana Nieto-Librero; Ana Sánchez-García; Puri Galindo-Villardón. Hierarchical Modeling for Diagnostic Test Accuracy Using Multivariate Probability Distribution Functions. Mathematics 2021, 9, 1310 .
AMA StyleJohny Pambabay-Calero, Sergio Bauz-Olvera, Ana Nieto-Librero, Ana Sánchez-García, Puri Galindo-Villardón. Hierarchical Modeling for Diagnostic Test Accuracy Using Multivariate Probability Distribution Functions. Mathematics. 2021; 9 (11):1310.
Chicago/Turabian StyleJohny Pambabay-Calero; Sergio Bauz-Olvera; Ana Nieto-Librero; Ana Sánchez-García; Puri Galindo-Villardón. 2021. "Hierarchical Modeling for Diagnostic Test Accuracy Using Multivariate Probability Distribution Functions." Mathematics 9, no. 11: 1310.
The HJ biplot is a multivariate analysis technique that allows us to represent both individuals and variables in a space of reduced dimensions. To adapt this approach to massive datasets, it is necessary to implement new techniques that are capable of reducing the dimensionality of the data and improving interpretation. Because of this, we propose a modern approach to obtaining the HJ biplot called the elastic net HJ biplot, which applies the elastic net penalty to improve the interpretation of the results. It is a novel algorithm in the sense that it is the first attempt within the biplot family in which regularisation methods are used to obtain modified loadings to optimise the results. As a complement to the proposed method, and to give practical support to it, a package has been developed in the R language called SparseBiplots. This package fills a gap that exists in the context of the HJ biplot through penalized techniques since in addition to the elastic net, it also includes the ridge and lasso to obtain the HJ biplot. To complete the study, a practical comparison is made with the standard HJ biplot and the disjoint biplot, and some results common to these methods are analysed.
Mitzi Cubilla-Montilla; Ana Nieto-Librero; M. Galindo-Villardón; Carlos Torres-Cubilla. Sparse HJ Biplot: A New Methodology via Elastic Net. Mathematics 2021, 9, 1298 .
AMA StyleMitzi Cubilla-Montilla, Ana Nieto-Librero, M. Galindo-Villardón, Carlos Torres-Cubilla. Sparse HJ Biplot: A New Methodology via Elastic Net. Mathematics. 2021; 9 (11):1298.
Chicago/Turabian StyleMitzi Cubilla-Montilla; Ana Nieto-Librero; M. Galindo-Villardón; Carlos Torres-Cubilla. 2021. "Sparse HJ Biplot: A New Methodology via Elastic Net." Mathematics 9, no. 11: 1298.
The study of biotic and abiotic factors and their interrelationships is essential in the preservation of sustainable marine ecosystems and for understanding the impact that climate change can have on different species. For instance, phytoplankton are extremely vulnerable to environmental changes and thus studying the factors involved is important for the species’ conservation. This work examines the relationship between phytoplankton and environmental parameters of the eastern equatorial Pacific, known as one of the most biologically rich regions in the world. For this purpose, a new multivariate method called MixSTATICO has been developed, allowing mixed-type data structured in two different groups (environment and species) to be related and measured on a space–time scale. The results obtained show how seasons have an impact on species–environment relations, with the most significant association occurring in November and the weakest during the month of May (change of season). The species Lauderia borealis, Chaetoceros didymus and Gyrodinium sp. were not observed in the coastal profiles during the dry season at most stations, while during the rainy season, the species Dactyliosolen antarcticus, Proboscia alata and Skeletonema costatum were not detected. Using MixSTATICO, species vulnerable to specific geographical locations and environmental variations were identified, making it possible to establish biological indicators for this region.
Mariela González-Narváez; María Fernández-Gómez; Susana Mendes; José-Luis Molina; Omar Ruiz-Barzola; Purificación Galindo-Villardón. Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO. Sustainability 2021, 13, 5924 .
AMA StyleMariela González-Narváez, María Fernández-Gómez, Susana Mendes, José-Luis Molina, Omar Ruiz-Barzola, Purificación Galindo-Villardón. Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO. Sustainability. 2021; 13 (11):5924.
Chicago/Turabian StyleMariela González-Narváez; María Fernández-Gómez; Susana Mendes; José-Luis Molina; Omar Ruiz-Barzola; Purificación Galindo-Villardón. 2021. "Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO." Sustainability 13, no. 11: 5924.
Today, a greater generation of information is produced as a consequence of the technological development of society. The Internet has facilitated the access and extraction of this information, thus pursuing the automatic discovery of the knowledge contained within. In this context, data mining aims to discover patterns, profiles and trends of a large volume of data, for which multiple learning techniques are available. The selection of which technique to use depends on the type of result desired to obtain and the data that are available, considering that the algorithms for these tasks date mostly from the early twentieth century and are now the basis of these new technologies. The aim of this study is to show the development of these techniques in the field of scientific research and to present the evolution of algorithms and software for data mining in recent years. To this end, the systematic literature review methodology was applied, as it is considered a systematic process that identifies, evaluates, and interprets the work of researchers in a chosen field. As a result, we present a comparative analysis of the most outstanding software: Alteryx, TIBCO Data Science, RapidMiner and WEKA, their capacities for data mining processes and a description of the algorithms and techniques of machine learning that are currently on the rise.
Gilda Taranto-Vera; Purificación Galindo-Villardón; Javier Merchán-Sánchez-Jara; Julio Salazar-Pozo; Alex Moreno-Salazar; Vanessa Salazar-Villalva. Algorithms and software for data mining and machine learning: a critical comparative view from a systematic review of the literature. The Journal of Supercomputing 2021, 1 -33.
AMA StyleGilda Taranto-Vera, Purificación Galindo-Villardón, Javier Merchán-Sánchez-Jara, Julio Salazar-Pozo, Alex Moreno-Salazar, Vanessa Salazar-Villalva. Algorithms and software for data mining and machine learning: a critical comparative view from a systematic review of the literature. The Journal of Supercomputing. 2021; ():1-33.
Chicago/Turabian StyleGilda Taranto-Vera; Purificación Galindo-Villardón; Javier Merchán-Sánchez-Jara; Julio Salazar-Pozo; Alex Moreno-Salazar; Vanessa Salazar-Villalva. 2021. "Algorithms and software for data mining and machine learning: a critical comparative view from a systematic review of the literature." The Journal of Supercomputing , no. : 1-33.
Global rankings help boost the international reputation of universities, which thus attempt to achieve good positions on them. These rankings attract great interest each year and are followed attentively by stakeholders in higher education. This paper investigates the trajectory of Spanish universities in the ARWU and THE rankings over the last 5 years using the dynamic biplot technique to study the relationship between a multivariate dataset obtained at more than one time point. The results demonstrate that Spanish universities achieve low positions on international rankings when analyzed using this multivariate and dynamic approach. Indeed, only a small percentage occupy good positions in both studied rankings and stand out in terms of some of the indicators, whereas most achieve weak scores in the global context. Spanish universities should attempt to improve this situation, since the prestige resulting from a good position on these lists will always be beneficial in terms of the visibility of both the universities themselves and the whole Spanish university system.
María-Teresa Gómez-Marcos; Marcelo Ruiz-Toledo; María-Purificación Vicente-Galindo; Helena Martín-Rodero; Claudio Ruff-Escobar; María-Purificación Galindo-Villardón. Multivariate dynamics of Spanish universities in international rankings. El Profesional de la información 2021, 30, 1 .
AMA StyleMaría-Teresa Gómez-Marcos, Marcelo Ruiz-Toledo, María-Purificación Vicente-Galindo, Helena Martín-Rodero, Claudio Ruff-Escobar, María-Purificación Galindo-Villardón. Multivariate dynamics of Spanish universities in international rankings. El Profesional de la información. 2021; 30 (2):1.
Chicago/Turabian StyleMaría-Teresa Gómez-Marcos; Marcelo Ruiz-Toledo; María-Purificación Vicente-Galindo; Helena Martín-Rodero; Claudio Ruff-Escobar; María-Purificación Galindo-Villardón. 2021. "Multivariate dynamics of Spanish universities in international rankings." El Profesional de la información 30, no. 2: 1.
El control estadístico multivariante de procesos para la producción por lotes generalmente toma en consideración características correlacionadas para la inspección del desempeño del proceso. En la literatura, los investigadores han utilizado varias técnicas estadísticas de forma individual para abordar esta inspección durante las fases de control y seguimiento. Nuevas estrategias han explorado la posibilidad de combinar dos técnicas con el fin de optimizar el control y el monitoreo del proceso por lotes, como el enfoque DS-PC. Este enfoque novedoso se refiere al uso de Statis Dual y Coordenadas Paralelas e implica una serie de varios pasos de protocolos y aplicaciones de fórmulas que son propensas a errores y consumen mucho tiempo. Utilizando la metodología que se encuentra en la literatura, el paquete DSPC para R se desarrolló con el objetivo de ofrecer una herramienta simple para realizar el cómputo de Statis Dual rápidamente para las fases de control y seguimiento. Las salidas del paquete ofrecen visualizaciones gráficas para detectar comportamientos inusuales durante la producción a través de gráficos de control IS (Interestructura) y CO (Intraestructura). La salida también incluye el gráfico de coordenadas paralelas. Este paquete será útil para los profesionales interesados en la aplicación del enfoque DS-PC a cualquier industria de proceso por lotes a través de la automatización sugerida por defecto o la opción personalizada. Para familiarizar a los usuarios con esta estrategia, el paquete proporciona un conjunto de datos simulado de fabricación de bolsas de plástico industriales.
José Ascencio Moreno; Miriam Vanessa Hinojosa Ramos; Francisco Vera Alcívar; Omar Ruiz Barzola; María Purificación Galindo Villardón; Miriam Ramos Barberán. Un paquete de R para control y monitoreo de procesos por lotes utilizando el enfoque Statis Dual-Coordenadas Paralelas. Revista Científica Ciencia y Tecnología 2021, 21, 1 .
AMA StyleJosé Ascencio Moreno, Miriam Vanessa Hinojosa Ramos, Francisco Vera Alcívar, Omar Ruiz Barzola, María Purificación Galindo Villardón, Miriam Ramos Barberán. Un paquete de R para control y monitoreo de procesos por lotes utilizando el enfoque Statis Dual-Coordenadas Paralelas. Revista Científica Ciencia y Tecnología. 2021; 21 (29):1.
Chicago/Turabian StyleJosé Ascencio Moreno; Miriam Vanessa Hinojosa Ramos; Francisco Vera Alcívar; Omar Ruiz Barzola; María Purificación Galindo Villardón; Miriam Ramos Barberán. 2021. "Un paquete de R para control y monitoreo de procesos por lotes utilizando el enfoque Statis Dual-Coordenadas Paralelas." Revista Científica Ciencia y Tecnología 21, no. 29: 1.
The aim of this study was to show a novel and accurate digital measurement protocol by analyzing the area and volume for interproximal tooth enamel surface reduction. In total, 14 lower teeth from all dental sectors were embedded into an epoxy resin and distributed as the lower dental arch, keeping the contact points. The experimental model was submitted to an intraoral digital impression before and after interproximal tooth enamel surface reduction using air-rotor strips and then re-contouring and polishing the interproximal enamel surfaces. These steps helped obtain standard tessellation language (STL) digital files. Furthermore, each tooth in the preoperative and postoperative full-arch STL digital files was segmented individually and aligned to analyze the area and volume of the interproximal tooth enamel surface reduction using engineering morphometry software. Descriptive analysis of the area and volume of the interproximal tooth enamel surface reduction was performed using a Student t-test. Higher enamel reduction area (3.53 ± 3.08 mm2) and volume (0.32 ± 0.22 mm3) values were shown on the distal surface compared with the area (2.97 ± 3.05 mm2) and volume (0.22 ± 0.16 mm3) of the enamel reduction on the mesial surface measured using the morphometric measurement digital protocol. The morphometric measurement protocol is an accurate digital measurement protocol for analyzing the area and volume of interproximal enamel surface reduction.
Martina Triduo; Álvaro Zubizarreta-Macho; Jorge Alonso Pérez-Barquero; Clara Guinot Barona; Alfonso Alvarado Lorenzo; Purificación Vicente-Galindo; Alberto Albaladejo Martínez. A Novel Digital Technique to Quantify the Area and Volume of Enamel Removal after Interproximal Enamel Reduction. Applied Sciences 2021, 11, 1274 .
AMA StyleMartina Triduo, Álvaro Zubizarreta-Macho, Jorge Alonso Pérez-Barquero, Clara Guinot Barona, Alfonso Alvarado Lorenzo, Purificación Vicente-Galindo, Alberto Albaladejo Martínez. A Novel Digital Technique to Quantify the Area and Volume of Enamel Removal after Interproximal Enamel Reduction. Applied Sciences. 2021; 11 (3):1274.
Chicago/Turabian StyleMartina Triduo; Álvaro Zubizarreta-Macho; Jorge Alonso Pérez-Barquero; Clara Guinot Barona; Alfonso Alvarado Lorenzo; Purificación Vicente-Galindo; Alberto Albaladejo Martínez. 2021. "A Novel Digital Technique to Quantify the Area and Volume of Enamel Removal after Interproximal Enamel Reduction." Applied Sciences 11, no. 3: 1274.
One of the main drawbacks of the traditional methods for computing components in the three-way Tucker model is the complex structure of the final loading matrices preventing an easy interpretation of the obtained results. In this paper, we propose a heuristic algorithm for computing disjoint orthogonal components facilitating the analysis of three-way data and the interpretation of results. We observe in the computational experiments carried out that our novel algorithm ameliorates this drawback, generating final loading matrices with a simple structure and then easier to interpret. Illustrations with real data are provided to show potential applications of the algorithm.
Carlos Martin-Barreiro; John A. Ramirez-Figueroa; Ana B. Nieto-Librero; Víctor Leiva; Ana Martin-Casado; M. Purificación Galindo-Villardón. A New Algorithm for Computing Disjoint Orthogonal Components in the Three-Way Tucker Model. Mathematics 2021, 9, 203 .
AMA StyleCarlos Martin-Barreiro, John A. Ramirez-Figueroa, Ana B. Nieto-Librero, Víctor Leiva, Ana Martin-Casado, M. Purificación Galindo-Villardón. A New Algorithm for Computing Disjoint Orthogonal Components in the Three-Way Tucker Model. Mathematics. 2021; 9 (3):203.
Chicago/Turabian StyleCarlos Martin-Barreiro; John A. Ramirez-Figueroa; Ana B. Nieto-Librero; Víctor Leiva; Ana Martin-Casado; M. Purificación Galindo-Villardón. 2021. "A New Algorithm for Computing Disjoint Orthogonal Components in the Three-Way Tucker Model." Mathematics 9, no. 3: 203.
Learning approaches are factors that contribute to sustainability education. Academic stress negatively affects students’ performances in the context of sustainability teaching. This study analyzed how deep and surface approaches could be related to coping with academic stress and gender. An online survey was completed by 1012 university students. The relationship between gender, sources of stress and learning approaches was examined through a multivariate canonical correspondence analysis. Results showed differences in stress-coping strategies depending on the learning approach used. In both female and male students, academic stress was handled with a deep learning approach. The findings provide implications for professors and highlight the importance of variables such as deep learning and gender in the teaching and learning sustainability process.
Zaira-Jazmín Zárate-Santana; María-Carmen Patino-Alonso; Ana-Belén Sánchez-García; Purificación Galindo-Villardón. Learning Approaches and Coping with Academic Stress for Sustainability Teaching: Connections through Canonical Correspondence Analysis. Sustainability 2021, 13, 852 .
AMA StyleZaira-Jazmín Zárate-Santana, María-Carmen Patino-Alonso, Ana-Belén Sánchez-García, Purificación Galindo-Villardón. Learning Approaches and Coping with Academic Stress for Sustainability Teaching: Connections through Canonical Correspondence Analysis. Sustainability. 2021; 13 (2):852.
Chicago/Turabian StyleZaira-Jazmín Zárate-Santana; María-Carmen Patino-Alonso; Ana-Belén Sánchez-García; Purificación Galindo-Villardón. 2021. "Learning Approaches and Coping with Academic Stress for Sustainability Teaching: Connections through Canonical Correspondence Analysis." Sustainability 13, no. 2: 852.
In this paper, we propose a new method for disjoint principal component analysis based on an intelligent search. The method consists of a principal component analysis with constraints, allowing us to determine components that are linear combinations of disjoint subsets of the original variables. The effectiveness of the proposed method contributes to solve one of the crucial problems of multivariate analysis, that is, the interpretation of the vectorial subspaces in the reduction of the dimensionality. The method selects the variables that contribute the most to each of the principal components in a clear and direct way. Numerical results are provided to confirm the quality of the solutions attained by the proposed method. This method avoids a local optimum and obtains a high success rate when reaching the best solution, which occurs in all the cases of our simulation study. An illustration with environmental real data shows the good performance of the method and its potential applications.
John A. Ramirez-Figueroa; Carlos Martin-Barreiro; Ana B. Nieto-Librero; Victor Leiva; M. Purificación Galindo-Villardón. A new principal component analysis by particle swarm optimization with an environmental application for data science. Stochastic Environmental Research and Risk Assessment 2021, 1 -16.
AMA StyleJohn A. Ramirez-Figueroa, Carlos Martin-Barreiro, Ana B. Nieto-Librero, Victor Leiva, M. Purificación Galindo-Villardón. A new principal component analysis by particle swarm optimization with an environmental application for data science. Stochastic Environmental Research and Risk Assessment. 2021; ():1-16.
Chicago/Turabian StyleJohn A. Ramirez-Figueroa; Carlos Martin-Barreiro; Ana B. Nieto-Librero; Victor Leiva; M. Purificación Galindo-Villardón. 2021. "A new principal component analysis by particle swarm optimization with an environmental application for data science." Stochastic Environmental Research and Risk Assessment , no. : 1-16.
In this paper, we highlight the basic techniques of multivariate statistical process control (MSPC) under the dimensionality criteria, such as Multiway Principal Component Analysis, Multiway Partial Squares, Structuration à Trois Indices de la Statistique, Tucker3, Parallel Factors, Multiway Independent Component Analysis, Multiset Canonical Correlation Analysis, Slow Features Analysis, and Parallel Coordinates. Furthermore, we summarize the procedures of each statistical technique and the usage of multivariate control charts. In addition, we review the most significant proposals and applications in practical cases. Finally, we compare and discuss the benefits and limitations within methods.
Miriam Ramos; José Ascencio; Miriam Vanessa Hinojosa; Francisco Vera; Omar Ruiz; María Isabel Jimenez-Feijoó; Purificación Galindo. Multivariate statistical process control methods for batch production: a review focused on applications. Production & Manufacturing Research 2021, 9, 33 -55.
AMA StyleMiriam Ramos, José Ascencio, Miriam Vanessa Hinojosa, Francisco Vera, Omar Ruiz, María Isabel Jimenez-Feijoó, Purificación Galindo. Multivariate statistical process control methods for batch production: a review focused on applications. Production & Manufacturing Research. 2021; 9 (1):33-55.
Chicago/Turabian StyleMiriam Ramos; José Ascencio; Miriam Vanessa Hinojosa; Francisco Vera; Omar Ruiz; María Isabel Jimenez-Feijoó; Purificación Galindo. 2021. "Multivariate statistical process control methods for batch production: a review focused on applications." Production & Manufacturing Research 9, no. 1: 33-55.
Sergio A. Bauz-Olvera; Johny J. Pambabay-Calero; Ana B. Nieto-Librero; Ma. Purificación Galindo-Villardón. Bivariate hierarchical model for the Meta-analysis of diagnostic tests in studies with binary responses: its application from SAS and R. Proyecciones (Antofagasta) 2020, 39, 1365 -1380.
AMA StyleSergio A. Bauz-Olvera, Johny J. Pambabay-Calero, Ana B. Nieto-Librero, Ma. Purificación Galindo-Villardón. Bivariate hierarchical model for the Meta-analysis of diagnostic tests in studies with binary responses: its application from SAS and R. Proyecciones (Antofagasta). 2020; 39 (5):1365-1380.
Chicago/Turabian StyleSergio A. Bauz-Olvera; Johny J. Pambabay-Calero; Ana B. Nieto-Librero; Ma. Purificación Galindo-Villardón. 2020. "Bivariate hierarchical model for the Meta-analysis of diagnostic tests in studies with binary responses: its application from SAS and R." Proyecciones (Antofagasta) 39, no. 5: 1365-1380.
Currently, the debate on corporate social responsibility (CSR) and the strategies implemented by organizations to disseminate their business actions, fuels the discussion on aspects that point to sustainable development. To show their CSR strategies, one of the mechanisms used by companies is the presentation of sustainability reports. In this work, we have modified the analysis approach traditionally used to demonstrate the characteristic factors of transparency in the field of CSR. Specifically, we focus on analyzing which indicators are the least disclosed by companies. Within this framework, the objective of this work is to analyse the practices of dissemination of environmental information based on the sustainability reports of the global reporting initiative produced by large companies, in order to establish differences and similarities in corporate social responsibility. The results obtained for a sample of 80 large companies and 67 multinational enterprises (MNEs) indicate a slight difference in the disclosure of environmental indicators. Concretely, the results reveal that 56.12% of environmental indicators are not disclosed by large companies; while, in MNEs, 51.23% of these indicators are not reported. In large companies, the greatest deficiencies in the disclosure of environmental information correspond to the categories of biodiversity, environmental grievance mechanisms, and effluents and waste. In the case of MNEs, the least disclosed categories are biodiversity, environmental grievance mechanisms, and environmental protection expenditures and investments (overall).
Cinthia Leonora Murillo‐Avalos; Mitzi Cubilla‐Montilla; Miguel Ángel Celestino Sánchez; Purificación Vicente‐Galindo. What environmental social responsibility practices do large companies manage for sustainable development? Corporate Social Responsibility and Environmental Management 2020, 28, 153 -168.
AMA StyleCinthia Leonora Murillo‐Avalos, Mitzi Cubilla‐Montilla, Miguel Ángel Celestino Sánchez, Purificación Vicente‐Galindo. What environmental social responsibility practices do large companies manage for sustainable development? Corporate Social Responsibility and Environmental Management. 2020; 28 (1):153-168.
Chicago/Turabian StyleCinthia Leonora Murillo‐Avalos; Mitzi Cubilla‐Montilla; Miguel Ángel Celestino Sánchez; Purificación Vicente‐Galindo. 2020. "What environmental social responsibility practices do large companies manage for sustainable development?" Corporate Social Responsibility and Environmental Management 28, no. 1: 153-168.
With the growth of cities, urban traffic has increased and traffic congestion has become a serious problem. Due to their characteristics, metro systems are one of the most used public transportation networks in big cities. So, optimization and planning of metro networks are challenges which governments must focus on. The objective of this study was to analyze Madrid metro network using graph theory. Through complex network theory, the main structural and topological properties of the network as well as robustness characteristics were obtained. Furthermore, to inspect these results, multivariate analysis techniques were employed, specifically HJ-Biplot. This analysis tool allowed us to explore relationships between centrality measures and to classify stations according to their centrality. Therefore, it is a multidisciplinary study that includes network analysis and multivariate analysis. The study found that closeness and eccentricity were strongly negatively correlated. In addition, the most central stations were those located in the city center, that is, there is a relationship between centrality and geographic location. In terms of robustness, a highly agglomerated community structure was found.
E. Frutos Bernal; A. Martín Del Rey; P. Galindo Villardón. Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective. Applied Sciences 2020, 10, 5689 .
AMA StyleE. Frutos Bernal, A. Martín Del Rey, P. Galindo Villardón. Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective. Applied Sciences. 2020; 10 (16):5689.
Chicago/Turabian StyleE. Frutos Bernal; A. Martín Del Rey; P. Galindo Villardón. 2020. "Analysis of Madrid Metro Network: From Structural to HJ-Biplot Perspective." Applied Sciences 10, no. 16: 5689.
Diagnosis and classification of gliomas mostly relies on histopathology and a few genetic markers. Here we interrogated microarray gene expression profiles (GEP) of 268 diffuse astrocytic gliomas—33 diffuse astrocytomas (DA), 52 anaplastic astrocytomas (AA) and 183 primary glioblastoma (GBM)—based on multivariate analysis, to identify discriminatory GEP that might support precise histopathological tumor stratification, particularly among inconclusive cases with II–III grade diagnosed, which have different prognosis and treatment strategies. Microarrays based GEP was analyzed on 155 diffuse astrocytic gliomas (discovery cohort) and validated in another 113 tumors (validation set) via sequential univariate analysis (pairwise comparison) for discriminatory gene selection, followed by nonnegative matrix factorization and canonical biplot for identification of discriminatory GEP among the distinct histological tumor subtypes. GEP data analysis identified a set of 27 genes capable of differentiating among distinct subtypes of gliomas that might support current histological classification. DA + AA showed similar molecular profiles with only a few discriminatory genes overexpressed (FSTL5 and SFRP2) and underexpressed (XIST, TOP2A and SHOX2) in DA vs AA and GBM. Compared to DA + AA, GBM displayed underexpression of ETNPPL, SH3GL2, GABRG2, SPX, DPP10, GABRB2 and CNTN3 and overexpression of CHI3L1, IGFBP3, COL1A1 and VEGFA, among other differentially expressed genes.
Nerea González-García; Ana B. Nieto-Librero; Ana Luisa Vital; Herminio José Tao; María González-Tablas; Álvaro Otero; Purificación Galindo-Villardón; Alberto Orfao; María Dolores Tabernero. Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications. Scientific Reports 2020, 10, 1 -12.
AMA StyleNerea González-García, Ana B. Nieto-Librero, Ana Luisa Vital, Herminio José Tao, María González-Tablas, Álvaro Otero, Purificación Galindo-Villardón, Alberto Orfao, María Dolores Tabernero. Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications. Scientific Reports. 2020; 10 (1):1-12.
Chicago/Turabian StyleNerea González-García; Ana B. Nieto-Librero; Ana Luisa Vital; Herminio José Tao; María González-Tablas; Álvaro Otero; Purificación Galindo-Villardón; Alberto Orfao; María Dolores Tabernero. 2020. "Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications." Scientific Reports 10, no. 1: 1-12.
The assessment of sustainability is of the utmost importance nowadays. Several approaches exist that measure sustainability at a national level and rank countries accordingly. Comparison of countries could be done numerically or pictorially. This paper introduces a novel clustering disjoint HJ-biplot approach, which is then applied to data from two well-known models: Sustainability Assessment by Fuzzy Evaluation (SAFE) and the United Nations Sustainable Development Goals Index (UN-SDGs). This approach performs a graphical ranking that makes the sustainability standing of countries very transparent. As expected, the pictorial model yielded similar rankings to those of SAFE and UN-SDGs, but it additionally grouped countries according to their most important indicators, thereby yielding a more global picture of sustainability. Our approach thus comprises a useful complement to existing mathematical sustainability ranking models.
José Fernando Romero Cañizares; Purificación Vicente Galindo; Yannis Phillis; Evangelos Grigoroudis. Graphical sustainability analysis using disjoint biplots. Operational Research 2020, 1 -22.
AMA StyleJosé Fernando Romero Cañizares, Purificación Vicente Galindo, Yannis Phillis, Evangelos Grigoroudis. Graphical sustainability analysis using disjoint biplots. Operational Research. 2020; ():1-22.
Chicago/Turabian StyleJosé Fernando Romero Cañizares; Purificación Vicente Galindo; Yannis Phillis; Evangelos Grigoroudis. 2020. "Graphical sustainability analysis using disjoint biplots." Operational Research , no. : 1-22.