Automatic classification system of Raman spectra applied to pigments analysis

Raman spectroscopy is one of the few non-destructive techniques capable of identifying pigments in art works. Raman spectra contain powerful information that can be used to identify unknown compounds and their chemical structures. However, the analysis of spectral data comes with some difficulties, and therefore the spectral interpretation is not straightforward. Sometimes, there are very little differences in the spectral data concerning to specific identification objectives, for instance, in polymorphic discrimination or in the discrimination of natural and synthetic forms of certain pigments. Moreover, this discrimination is often performed manually so that the process can be repetitive, subjective and particularly time-consuming. The result is an increasing motivation to automate the identification process involved in the classification of pigments in paint. In this paper, we propose a system to automatically classify the spectral data into specific and well-known classes, i.e. reference classes. The proposal is based on a combination of chemometric techniques, which provides a powerful way to achieve spectral separability so that it is possible to discriminate between very similar spectra in an automatic way. In this regard, a decision-making algorithm was specifically developed to select the corresponding reference class with no user input, which was successfully validated using simulated spectra. The implemented methodology was used to classify Raman spectra of pigments commonly present in artist's paints in experimental cases, providing reliable and consistent results. Therefore, the presented system can play a good auxiliary role in the analysts' endpoint classification.Peer ReviewedPostprint (author's final draft

Multivariate approach-based system for the automated interpretation of spectra : application to pigments identification through Raman spectroscopy in art analysis

The application of spectroscopic techniques is crucial for art historians and conservators who require knowledge of materials used in works of art (pigments, dyes, binders, additives, ...) in particular instances. In this sense, the knowledge of pigments which were in use on the ancient artists' palettes is fundamental to preserve the art works. In addition, this knowledge is important to determine correct conservation approaches, to study degradation processes or authenticity-related issues. For instance, the proper interpretation of molecular signatures from a vibrational spectroscopy gives valuable information about the materials used by the artists. In this regard, the spectral identification is one of the essential interpretations to be performed, which is generally carried out by visual comparison between the unknown spectra with an appropriate database of reference spectra. This identification approach while being simple and intuitive may turn out a complex task which usually requires an experienced analyst and inevitably introduces an element of subjectivity linked to the intervention of the investigator. Besides, these analyses can be limited due to interferences from other phenomena like noises or admixtures. This task is further complicated when the spectra are to be interpreted by a software system. Hence, the noise impact must be reduced to have an effective identification and a robust strategy for processing multi-component spectra needs to be implemented. Clearly, a fully-automated data processing system for a reliable spectral interpretation is of practical interest. Several automated methodologies were designed, developed and analysed in this Ph.D. Thesis for the purposes of art works analysis through Raman spectroscopy. In this sense, the usage of mathematical morphology together with p-spline fitting demonstrated to be a consistent combination in the application of data enhancement Raman spectra from artistic pigments. Besides, a generalised identification methodology to identify single- and multi- component spectra was developed. This identification method relies on automated spectral matching based on principal component analysis (PCA) and independent components analysis (ICA), being computationally efficient and conceptually simple. Moreover, a supervised classification methodology to automatically distinguish between Raman spectra showing small differences was developed. According to predefined reference training sets, the classification method is able to classify unknown Raman spectra relying on PCA and multiple discriminant analysis (MDA). Both the identification and classification methodologies successfully work using a single spectral observation for the unknown Raman spectra, with no user intervention or previous knowledge of the analysed sample. The designed, developed and analysed automated methodologies for noise filtering and identification and classification of artistic pigments are integrated in a global system for the automated data interpretation of spectra from art works analysis implemented in this Ph.D. Thesis, namely PigmentsLab. This software platform together with the integrated methodologies can play a good auxiliary role in the analysts' endpoint interpretation, providing insight from the raw spectral measurements into pigments. The system implementation provides an easy-to-use software platform and straightforward to update when new spectral data become available. The robust, reliable and consistent results obtained on Raman spectra demonstrated the competitiveness of the implemented data processing solutions. The system has great potential as an accurate and practical method for the automated interpretation of Raman spectra for not only pigment analysis, but essentially for any material group.La aplicación de técnicas espectroscópicas es crucial para los conservadores de arte que requieren el conocimiento de los materiales utilizados en obras de arte (pigmentos, aglutinantes, aditivos, ...) en casos particulares. En este sentido, el conocimiento del uso de los diferentes pigmentos en las paletas de los artistas es fundamental para preservar las obras de arte. Este conocimiento es importante para determinar las estrategias de conservación correctas, para estudiar los procesos de degradación o problemas relacionados con la autenticidad de las obras de arte. Por ejemplo, la interpretación adecuada de las firmas moleculares de una espectroscopia vibracional proporciona información valiosa sobre los materiales utilizados por los artistas. La identificación espectral es una de las interpretaciones esenciales a realizar, y generalmente se lleva a cabo mediante la comparación visual entre los espectros desconocidos con una base de datos adecuada de los espectros de referencia. Esta estrategia de identificación, a pesar de ser sencilla e intuitiva, puede resultar una tarea compleja que requiere generalmente de un analista experimentado e inevitablemente introduce un elemento de subjetividad vinculado a la intervención del investigador. Además, estos análisis pueden verse limitados debido a interferencias de otros fenómenos como ruido o mezclas de pigmentos. Esta tarea se complica aún más cuando los espectros deben ser interpretados por un computador. Por tanto, el impacto del ruido debe ser reducido para tener una identificación eficaz, y se debe implementar una estrategia robusta para el procesado de espectros de múltiples componentes. El desarrollo de un sistema de procesado de datos totalmente automatizado para una interpretación espectral fiable es de evidente interés práctico. Varias metodologías automatizadas han sido diseñadas y desarrolladas en esta tesis doctoral, focalizadas en el análisis de arte mediante espectroscopia Raman. En este sentido, el uso de morfología matemática junto con el ajuste basado en p-splines demostró ser una combinación consistente en la aplicación de mejora de la calidad de espectros Raman de pigmentos artísticos. Además, se ha desarrollado una metodología de identificación generalizada para identificar los espectros Raman compuestos tanto de un solo pigmento como de múltiples pigmentos. Este método de identificación se basa en la búsqueda de coincidencia espectral automatizada basada en el análisis por componentes principales (PCA) y el análisis por componentes independientes (ICA), siendo un método computacionalmente eficiente y conceptualmente simple. Por otra parte, se ha desarrollado una metodología de clasificación supervisada para distinguir entre espectros Raman que muestran pequeñas diferencias entre ellos. A partir de conjuntos de referencia predefinidos de datos de entrenamiento, el método de clasificación es capaz de clasificar los espectros Raman desconocidos mediante PCA y el análisis discriminante múltiple (MDA). Tanto la metodología de identificación como la de clasificación funcionan correctamente utilizando una sola observación espectral para los espectros Raman desconocidos, sin intervención del usuario ni el conocimiento previo de la muestra analizada. Las metodologías automatizadas diseñadas y desarrolladas para el filtrado de ruido y la identificación y clasificación de pigmentos artísticos están integradas en un sistema global para la interpretación automatizada de datos a partir de espectros medidos en obras de arte que ha sido implementado en esta tesis doctoral, llamado PigmentsLab. Esta plataforma software puede representar un buen papel auxiliar en la interpretación de punto final de los analistas, proporcionando valor a partir de las medidas espectrales en bruto de pigmentos artísticos. Los resultados obtenidos en los espectros Raman analizados, siendo robustos y consistentes, demuestran la competitividad de las soluciones de tratamiento de señal implementadas

A case study of corporate diversification and vertical integration in Africa

Africa is home to some of the world’s most original, resilient, and remarkable companies. The singular challenges and opportunities of the continent’s economic environment have given rise to idiosyncratic strategies and business models. However, there is a notable absence of studies on African companies. While there are numerous noteworthy companies in Africa, there are few as relevant, successful, and influential as the Dangote Group. This paper aims to add to the limited literature in the area by analyzing the business model and strategic choices of Dangote Cement, the Group’s flagship business and one of Africa’s industrial giants. In particular, it explores its corporate diversification and vertical integration strategies, which are at the core of its success. This article is based on 7 interviews with internal and external Dangote stakeholders and a detailed questionnaire completed by the Strategy Department of the firm, together with public data of the company. While the topics of diversification and integration have been studied in multiple contexts, this article provides an original perspective by applying existing research and management thinking to the specific business environment of Africa. This paper explores how and why Dangote Cement diversifies and how it identifies and integrates the advantages and disadvantages of its strategic choices. We believe it provides an original perspective that furthers our limited collective understanding of and research on strategic practices in Africa, the world’s last business academic frontier

Aplicación de comités de expertos en el modelado del comportamiento humano en situaciones de distorsión visuo-motora

En este trabajo se presenta una aplicación de las arquitecturas neuronales basadas en comités de expertos en donde dan una buena solución en un problema de modelado del comportamiento visuomotor humano. La intención de este artículo ha sido la de mostrar la validez de las redes en comités sobre una aplicación de modelado de sistemas biológicos. Se trata por tanto de mostrar un modelo del comportamiento psicofísico humano, es decir, del comportamiento de las arquitecturas neuronales biológicas mediante redes neuronales artificiales en donde las redes en comité de expertos forman parte de la arquitectura global del modelo

La evaluación inicial de la competencia digital del alumnado de primer curso de educación secundaria obligatoria en el proyecto 1x1

La implementación de las Tecnologías de la Información y la Comunicación (TIC) en un instituto público de Educación Secundaria Obligatoria (ESO) entraña necesariamente una reflexión sobre las competencias digitales que deberá asumir el alumnado y, con ello, el cambio metodológico necesario para su completa impregnación. Un primer paso es el cuestionario que aquí se presenta, en el contexto de la implementación del plan Escuela 2.0 en Cataluña, el innovador «Educat 1 x 1». Con él se pretende concoer el punto de partida respecto a la competencia TIC del alumnado de primero de ESO para estar en mejores condiciones al planificar la inclusión de las TIC en el proceso de enseñanza aprendizaje.The implementation of Information Technology and Communication (ICT) in a public institute of Secondary Education (ESO) must be preceded by a reflection about the digital skills students should assume, and thus the desirable methodological change for their full utilization. A first step is a questionnaire we present here within the context of the implementation of the School 2.0 plan in Catalonia, called «Educat 1 x 1». It aims to offer an initial assessment of our students’ ICT competence when they arrive to High Schools: only then we will do our best for planning the teachinglearning process of this competence

Analysis of Immunotherapy in hepatocellular carcinoma

One reason immunotherapy is important for Hepatocellular carcinoma, it’s because there are many immune cells in that organ. Because HCC is very aggressive, immunotherapy must be applied correctly. There are a lot of immunotherapies for all cancers, nevertheless, some has been tested for specific organs or tissues, and probably in the future, this organ-specific treatments can be applied in other tumor tissues.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Spectroelectrochemical studies of CTAB adsorbed on gold surfaces in perchloric acid

Acknowledgments. This research was funded by Ministerio de Ciencia e Innovación (Spain) grant number PID2019-105653GB-I00), Generalitat Valenciana (Spain) grant number PROMETEO/2020/063. A.C. gratefully acknowledges the support of the University of Aberdeen.Peer reviewedPublisher PD

Construction of a novel Pichia pastoris strain for production of xanthophylls

In this study, we used the yeast carotenogenic producer Pichia pastoris Pp-EBIL strain, which has been metabolically engineered, by heterologously expressing β-carotene-pathway enzymes to produce β-carotene, as a vessel for recombinant astaxanthin expression. For this purpose, we designed new P. pastoris recombinant-strains harboring astaxanthin-encoding genes from carotenogenic microorganism, and thus capable of producing xanthophyllic compounds. We designed and constructed a plasmid (pGAPZA-WZ) containing both the β-carotene ketolase (crtW) and β-carotene hydroxylase (crtZ) genes from Agrobacterium aurantiacum, under the control of the GAP promoter and containing an AOX-1 terminator. The plasmid was then integrated into the P. pastoris Pp-EBIL strain genomic DNA, producing clone Pp-EBILWZ. The recombinant P. pastoris (Pp-EBILWZ) cells exhibited a strong reddish carotenoid coloration and were confirmed, by HPLC, to produce not only the previous described carotenoids lycopene and β-carotene, but also de novo synthesized astaxanthin.J. M. A-G. is the recipient of an AECID scholarship from the Spanish Foreign Affairs MinistryS