Partial least squares (PLS) regression and its application to coal analysis

Instrumental chemical analysis methods use the relationships between a signal obtained and a property (generally a concentration) of the system under study. The study and applications of these relations is known as chemometrics, a discipline of intense development, with ample applications in chemical and process industry and in environmental studies. The method of partial least squares (PLS) is one of the most used in chemometrics. This method is closely related to principal components regression (PCR). PLS have theoretical and computational advantages that have led to a great number of applications. The numbers of Internet sites referring to PLS are hundreds of thousands. Here, we give the fundamentals and show an application to prediction of coal properties from mid-infrared data, with the purpose of developing fast, non-destructive methods of analysis for these materials

Determinación simultánea de algunos elementos formadores de hidruros (Sb, Sn y Pb) en aleaciones de soldaduras blandas, mediante un sistema acoplado de Análisis en Flujo- Generación de Hidruros - Espectrometría Infrarroja de transformada de Fourier utili

En el presente trabajo se propone la determinación simultánea de elementos formadores de hidruros (Sn, Sb y Pb) mediante un método basado en el acoplamiento de un sistema de análisis por inyección en flujo con generación de hidruros, utilizando la espectrometría infrarroja de transformada de Fourier como forma de detección y el algoritmo de Regresión Lineal Múltiple para la calibración de los analitos bajo estudio. Las características analíticas arrojadas por el sistema propuesto fueron adecuadas para la determinación de los hidruros en muestras de aleaciones utilizadas en soldaduras blandas.In this paper the simultaneous determination of hydride forming elements (Sn, Sb and Pb) is proposed by means of a method based on the coupling of a system of flow injection analysis with hydride generation, using infrared spectrometry Fourier transform as a means of detection and the Multiple Linear Regression algorithm for calibrating the analytes under study. The analytical characteristics thrown out by the proposed system were suitable for the determination of the hydrides in samples of alloys used in solders

DESARROLLO DE UN PROGRAMA PARA ESTUDIAR EL COMPORTAMIENTO DE UNA COLUMNA DE FRACCIONAMIENTO ETANO/ETILENO DE UNA PLANTA DE OLEFINAS

En este trabajo se presenta el desarrollo de programas para el estudio del comportamiento de una columna de fraccionamiento Etano/Etileno, perteneciente a una planta de Olefinas. Se utilizaron una red neuronal (RNA) del tipo multicapas con propagación hacia adelante y el algoritmo de mínimos cuadrados parciales (PLS) con este propósito. El entrenamiento de la red neuronal y la obtención del modelo PLS se realizaron con datos experimentales de la planta. Estos datos experimentales se dividieron en un conjunto de prueba y un conjunto de validación. Se demostró que la red neuronal fue muy superior al algoritmo PLS para la predicción de la producción de etileno a partir de parámetros de funcionamiento de la planta. Adicionalmente, estos resultados fueron comparados con los resultados de la simulación arrojados por un paquete comercial, resultando en una buena correspondencia entre las predicciones del modelo de red neuronal y las del paquete comercial.This paper presents the development of programs for the study of the behavior of a fractionating column of Ethane/Ethylene, which belongs to an olefin plant. We used a neural network (ANN) multilayer type with forward propagation algorithm and partial least squares (PLS) for this purpose. The training of the neural network and the PLS model obtaining were performed with experimental data of the plant. These experimental data were divided into a test set and a validation set. It was shown that the neural network was much higher than PLS algorithm for predicting the production of ethylene from operating parameters of the plant. Additionally, these results were compared with simulation results achieved by a commercial package, resulting in a good agreement between predictions of the neural network model and the commercial package ones

Environmental scanning electron microscopy analysis of Proteus mirabilis biofilms grown on chitin and stainless steel

Proteus mirabilis is a human pathogen able to form biofilms on the surface of urinary catheters. Little is known about P. mirabilis biofilms on natural or industrial surfaces and the potential consequences for these settings. The main aim of this work was to assess and compare the adhesion and biofilm formation of P. mirabilis strains from different origins on chitin and stainless steel surfaces within 4 to 96 h. Using environmental scanning electron microscopy, the biofilms of a clinical strain grown on chitin at 4 h showed greater adhesion, aggregation, thickness, and extracellular matrix production than those grown on stainless steel, whereas biofilms of an environmental strain had less aggregation on both surfaces. Biofilms of both P. mirabilis strains developed different structures on chitin, such as pillars, mushrooms, channels, and crystalline-like precipitates between 24 and 96 h, in contrast with flat-layer biofilms produced on stainless steel. Significant differences (p < 0.05) were found in the frequency of pillars and channels. Images of transmission electron microscopy demonstrated abundant fimbriae in 100 % of cells from both strains, which could be related to surface adherence and biofilm formation. This represents the first study of P. mirabilis showing adhesion, biofilm formation, and development of different structures on surfaces found outside the human host