Análise preditiva na empresa : OLI – Sistemas Sanitários, S.A.

A previsão constitui um importante ativo para as empresas, uma vez que ajuda no seu processo operacional e estratégico. A previsão do futuro através de metodologias quantitativas caracteriza-se por ser bastante útil para a antecipação de tomadas de decisão, o que poderá levar a vantagem competitiva e sucesso no universo empresarial. O desenvolvimento das áreas de business intelligence e business analytics têm um forte impacto na implementação destes métodos, uma vez que apresentam importantes ferramentas que se mostram eficientes para a análise e previsão. Este trabalho centra-se em duas análises preditivas, uma referente às vendas totais da empresa “OLI – Sistemas Sanitários, S.A”, e a segunda referente à produção de energia do painel solar da “OLI Moldes, Lda”. No sentido de averiguar métodos preditivos mais eficazes e eficientes para os dois casos de estudo implementados, empregou-se alguns métodos quantitativos de previsão existentes. No primeiro caso, pode-se destacar a implementação do Método de Holt Winters Aditivo, o Método Holt Winters Multiplicativo e o Método ARIMA. No segundo caso foram utilizados métodos causais, como o Modelo de Modelo de Regressão Múltipla, o Modelo de Regressão de Ridge, o Modelo de Regressão de Lasso, o Modelo de Regressão de Elastic Net e o Modelo de Floresta Aleatória. Deste modo, este trabalho conduz a uma elucidação dos conceitos de business analytics e business intelligence, que fortalecem a compreensão dos métodos quantitativos de previsão aplicados.Forecasting is an important asset for companies, as it helps in their operational and strategic process. Predicting the future through quantitative methodologies is characterized by being very useful for anticipating the decision making, which can lead to competitive advantage and success in the business universe. The development of the business analytics and business intelligence areas has a strong impact on the implementation of these methods, since they present important tools that prove to be efficient for analysis and forecasting. This work focuses on two predictive analyses, one referring to the total sales of the company "OLI - Sistemas Sanitários, S.A", and the second one referring to the energy production of the solar panel of "OLI Moldes, Lda". To ascertain more effective and efficient predictive methods for the two case studies implemented, some existing quantitative forecasting methods were used. In the first case, we can highlight the implementation of the Additive Holt Winters Method, the Multiplicative Holt Winters Method and the ARIMA Method. In the second case, causal methods were used, such as the Multiple Regression Model, the Ridge Regression Model, the Lasso Regression Model, and the Random Forest Model. In this way, this work leads to an elucidation of the concepts of business analytics and business intelligence, which strengthen the understanding of the quantitative forecasting methods applied

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field