Multivariate statistical process control of an industrial-scale fed-batch simulator

This article presents an improved batch-to-batch optimisation technique that is shown to be able to bring the yield closer to its set-point from one batch to the next. In addition, an innovative Model Predictive Control technique is proposed that over multiple batches, reduces the variability in yield that occurs as a result of random variations in raw material properties and in-batch process fluctuations. The proposed controller uses validity constraints to restrict the decisional space to that described by the identification dataset that was used to develop an adaptive multi-way partial least squares model of the process. A further contribution of this article is the formulation of a bootstrap calculation to determine confidence intervals within the hard constraints imposed on model validity. The proposed control strategy was applied to a realistic industrial-scale fed-batch penicillin simulator, where its performance was demonstrated to provide improved consistency and yield when compared with nominal operation

Public Management in Political Institutions: Explaining Perceptions of White House Chief of Staff Influence

The notion that public managers influence organizational performance is common in public administration research. However, less is known about why some managers are better at influencing organizational performance than others. Furthermore, relatively few studies have systematically examined managerial influence and scholars have yet to investigate either quantitatively or systematically managerial influence in the White House. Utilizing original survey data collected from former White House officials who served in the Reagan, George H.W. Bush, and Clinton administrations, this study applies empirical public management theory to examine for the first time the key determinants that shape perceptions of chief of staff managerial influence. The findings demonstrate how several core concepts in public management theory help explain the dynamics that drive perceptions of managerial influence, thereby providing a new contribution to the literature on public management

Revisión de los Gordiacea (Nematomorpha) de la colección de la Academia de Ciencias de California con descripción de una nueva especie

The Gordiacea of the California Academy of Sciences collection are studied. The specimens are included in the known species Gordius robustus Leidy, Pseudochordodes bedriagae (Camerano) and a new species, Neochordodes californensis n. sp. is proposed. Morphological, morphometric and geographical data are provided for these species.En este trabajo se estudian los Gordiacea de la colección de la California Academy of Sciences. Los ejemplares se incluyen en dos especies conocidas, Gordius robustus Leidy y Pseudochordodes bedriagae (Camerano), y una especie nueva: Neochordodes californensis n. sp. Se proporcionan datos morfológicos, morfométricos y geográficos para cada una de las especies

Multivariate statistical data analysis of cell-free protein synthesis toward monitoring and control

The optimization and control of cell free protein synthesis (CFPS) presents an ongoing challenge due to the complex synergies and nonlinearities that cannot be fully explained in first principle models. This article explores the use of multivariate statistical tools for analyzing data sets collected from the CFPS of Cereulide monoclonal antibodies. During the collection of these data sets, several of the process parameters were modified to investigate their effect on the end‐point product (yield). Through the application of principal component analysis and partial least squares (PLS), important correlations in the process could be identified. For example, yield had a positive correlation with pH and NH3 and a negative correlation with CO2 and dissolved oxygen. It was also found that PLS was able to provide a long‐term prediction of product yield. The presented work illustrates that multivariate statistical techniques provide important insights that can help support the operation and control of CFPS processes

The use of Instagram on education at the university level: a case study on the business management subject belonging to the industrial engineering degree

[EN] With one billion monthly active users, Instagram is one of the most popular social networks worldwide. A review on the role of Instagram in education has led to identify different purposes on Instagram use in different knowledge areas of teaching, and in different levels of education. This article presents the use Instagram application as an educational resource in the teaching-learning process, within the university environment. The objective is to improve this process through self-learning, developing posts with content related to the business management subject, specifically in the research area of industrial engineering. The purpose is threefold: (i) theoretical learning, the student uses Instagram posts published by the teacher to learn pills of concepts; (ii) practical learning, the student uses the teacher's posts related with industry professionals, showing the application of theoretical concepts in real life; (iii) autonomous teaching-learning, the student develops the content and posts of the Instagram account, with the supervision of the teacher.Andres, B.; Sempere-Ripoll, F.; Rodríguez Villalobos, A.; Mengual Recuerda, A. (2021). The use of Instagram on education at the university level: a case study on the business management subject belonging to the industrial engineering degree. ICERI Proceedings. 7986-7992. https://doi.org/10.21125/iceri.2021.18047986799

Evaluación de cultivares locales e introducidos de (RICINUS COMMUNIS L) higuerilla para condiciones de selva del Peru Región Ucayali 2011.

El experimento se instalo en el anexo experimental “Los Incas” de la Estación Experimental Agraria Pucallpa, departamento de Ucayali, provincia de Coronel Portillo, distrito de campo verde, el suelo donde se instalo el experimento es de altura o Ultisols. El diseño empleado fue de block completo randomizado con 04 tratamientos y 04 repeticiones, teniendo un total de 16 unidades experimentales, en un área de 1,881 m2. , los tratamientos evaluados fueron: T1 = Higuerilla BRS Nordestina, T2 = Higuerilla L1-003, T3 = Higuerilla L2-004 y T4 = Higuerilla L3-007. Se obtuvo como resultado que en las evaluaciones fenológicas en los cuatro cultivares donde para los parámetros agronómicos Higuerilla L3 – 007 e Higuerilla L 2-004, obtuvieron menor altura de planta al final del ciclo con 90 y 105 cm respectivamente siendo menor también en lo que corresponde a la altura de planta a la emisión del primer racimo que fue de 27.5 y 41 cm; asimismo el ecotipo Higuerilla L1 – 003 obtuvo 84 días a la emisión del primer racimo y 124 días a la cosecha del primer racimo siendo el más precoz con respecto a Higuerilla BRS Nordestina que obtuvo 147 días a la cosecha del primer racimo. Sin embargo en el parámetro de rendimiento de grano los ecotipos Higuerilla BRS Nordestina e Higuerilla L 2-004, rindieron un total de 602 y 524.8 kilos/ha respectivamente pero no superaron los 1,500 kg/ha

El Quijote del guineo de la Mancha

Una noche soñé que el Quijote era yo. Y mi hermano José el corpulento don Sancho. Y que aprisa salimos, en nuestras bestias montados, a perseguir a unos gringos que se hicieron los dueños de nuestros propios bananos

Modern day monitoring and control challenges outlined on an industrial-scale benchmark fermentation process

This paper outlines real-world control challenges faced by modern-day biopharmaceutical facilities through the extension of a previously developed industrial-scale penicillin fermentation simulation (IndPenSim). The extensions include the addition of a simulated Raman spectroscopy device for the purpose of developing, evaluating and implementation of advanced and innovative control solutions applicable to biotechnology facilities. IndPenSim can be operated in fixed or operator controlled mode and generates all the available on-line, off-line and Raman spectra for each batch. The capabilities of IndPenSim were initially demonstrated through the implementation of a QbD methodology utilising the three stages of the PAT framework. Furthermore, IndPenSim evaluated a fault detection algorithm to detect process faults occurring on different batches recorded throughout a yearly campaign. The simulator and all data presented here are available to download at www.industrialpenicillinsimulation.com and acts as a benchmark for researchers to analyse, improve and optimise the current control strategy implemented on this facility. Additionally, a highly valuable data resource containing 100 batches with all available process and Raman spectroscopy measurements is freely available to download. This data is highly suitable for the development of big data analytics, machine learning (ML) or artificial intelligence (AI) algorithms applicable to the biopharmaceutical industry