A New Distance Correlation Metric and Bagging Method for NARX Model Estimation

System identification is a challenging and interesting engineering problem that has been studied for decades. In particular, the NARMAX methodology has been extensively used with interesting results. Such methodology identifies a deterministic parsimonious model by ranking a set of candidate terms using a linear dependency metric with respect to the output. Other metrics have been used that identify nonlinear dependencies, like the mutual information, but they are hard to interpret. In this work, the distance correlation metric is implemented together with the bagging method. These two implementations enhance the performance of the NARMAX methodology providing interpretability of nonlinear dependencies and uncertainty measures in the model identified. A comparison of the new BOFR-dCor (Bagging Orthogonal Forward Regression using distance Correlation) algorithm is done with respect to the traditional OFR (Orthogonal Forward Regression) algorithm and the OFR-MI (Orthogonal Forward Regression using Mutual Information) algorithm showing interesting results that improve interpretability and uncertainty analysis

GUIDELINES TO SIMULATE LINEAR VISCOELASTIC MATERIALS WITH AN ARBITRARY NUMBER OF CHARACTERISTIC TIMES IN THE CONTEXT OF ATOMIC FORCE MISCROSCOPY

We provide guidelines for modeling linear viscoelastic materials containing an arbitrary number of characteristic times, under atomic force microscopy (AFM) characterization. Instructions are provided to set up the governing equations that rule the deformation of the material by the AFM tip. Procedures are described in detail in the spirit of providing a simple handbook, which is accompanied by open-access code and workbook (Excel) sheets. These guidelines seek to complement the existing literature and reach out to a larger audience in the awareness of the interdisciplinary nature of science. Examples are given in the context of force-distance curves characterization within AFM, but they can be easily extrapolated to other types of contact characterization techniques at different length scales. Despite the simplified approach of this document, the algorithms described herein are built upon rigorous classical linear viscoelastic theory

Near-infrared colors of minor planets recovered from VISTA - VHS survey (MOVIS)

The Sloan Digital Sky Survey (SDSS) and Wide-field Infrared Survey Explorer (WISE) provide information about the surface composition of about 100,000 minor planets. The resulting visible colors and albedos enabled us to group them in several major classes, which are a simplified view of the diversity shown by the few existing spectra. We performed a serendipitous search in VISTA-VHS observations using a pipeline developed to retrieve and process the data that corresponds to solar system objects (SSo). The colors and the magnitudes of the minor planets observed by the VISTA survey are compiled into three catalogs that are available online: the detections catalog (MOVIS-D), the magnitudes catalog (MOVIS-M), and the colors catalog (MOVIS-C). They were built using the third data release of the survey (VISTA VHS-DR3). A total of 39,947 objects were detected, including 52 NEAs, 325 Mars Crossers, 515 Hungaria asteroids, 38,428 main-belt asteroids, 146 Cybele asteroids, 147 Hilda asteroids, 270 Trojans, 13 comets, 12 Kuiper Belt objects and Neptune with its four satellites. The colors found for asteroids with known spectral properties reveal well-defined patterns corresponding to different mineralogies. The distributions of MOVIS-C data in color-color plots shows clusters identified with different taxonomic types. All the diagrams that use (Y-J) color separate the spectral classes more effectively than the (J-H) and (H-Ks) plots used until now: even for large color errors (<0.1), the plots (Y-J) vs (Y-Ks) and (Y-J) vs (J-Ks) provide the separation between S-complex and C-complex. The end members A, D, R, and V-types occupy well-defined regions.Comment: 19 pages, 16 figure

An analysis of the variables that provide a supply chain with sustainable competitiveness

Objeto: Una cadena de suministro (CS) ágil, adaptable y alineada (Triple A) parece clave para la obtención de ventajas competitivas sostenibles. Sin embargo, hay escasa investigación previa sobre el tema, observándose incluso discrepancias a nivel conceptual. Por ello, el objetivo del presente trabajo es proponer un marco de referencia que determine las dimensiones y factores que definen la agilidad, adaptabilidad y alineación en la CS y facilite a los gestores e investigadores la evaluación del estado de la misma en lo que respecta a estas variables, así como el desarrollo de investigaciones empíricas que determinen su impacto en el rendimiento. Diseño/metodología/enfoque: Se realiza una revisión sistemática de bibliografía en revistas especializadas en Dirección de Operaciones, Logística, Administración y Gestión de la Cadena de Suministro utilizando la base de datos ABI/Inform. Los artículos obtenidos fueron revisados, seleccionándose los relevantes para este estudio. Con ellos se realizó un análisis cualitativo que nos llevó a la consecución del objetivo planteado. Aportaciones y resultados: En la presente investigación se establecen y agrupan, por primera vez, las definiciones, dimensiones y factores de la triple A en la CS, ofreciendo un marco conceptual que apoyará a investigadores y gestores a evaluar el desempeño de la CS. Aunque los artículos que analizan alguna de estas variables van en aumento, siguen siendo escasos. La agilidad es la variable más estudiada, siendo la adaptabilidad la menos analizada. Limitaciones / implicaciones: Se propone un marco de referencia teórico para la triple A en la CS construido a partir de estudios previos que no evalúan de manera conjunta las tres variables. El modelo será analizado empíricamente en futuras investigaciones. Originalidad / Valor añadido: La escasez de trabajos sobre agilidad, adaptabilidad y alineación en la CS, así como la falta de consenso respecto a las dimensiones y factores que las definen, hacen necesarios estudios como el que se presenta.Purpose: An agile, adaptable and aligned (Triple A) supply chain (SC) would seem to be key to obtaining sustainable competitive advantages. Little previous research has been done into the topic, however, and there are even discrepancies on the conceptual level. For this reason this study aims to propose a reference framework to determine the dimensions and factors that define agility, adaptability and alignment in the SC and to facilitate both the evaluation of its state by managers and researchers with respect to these variables and also the development of empirical research that determines its impact on performance. Design/methodology: A systematic literature review was carried out of specialist Operations Management, Logistics, Management and Supply Chain Management journals using the ProQuest (Abi/Inform Global) database. The articles retrieved were examined and those that were relevant for this study were selected. Using these, a qualitative analysis was done that led to the proposed goal being achieved. Findings: This study sets out the definitions, dimensions and factors of the three variables and groups them together for the first time, thus providing a solid conceptual frame. Although the number of articles that analyse one or other of the variables is growing, it is still low. Agility is the variable on which most research has been done, while adaptability is the least analysed. Research limitations/implications: A theoretical reference framework is proposed for the Triple A in the SC based on earlier studies which do not discuss the joint effect of three variables, as a result of which there is no tested theoretical base. The model will be analysed empirically in future research. Originality/value: The lack of papers on agility, adaptability and alignment in the supply chain and the lack of a consensus regarding the dimensions and factors to define them reveal a need for studies such as this.Peer Reviewe