DBT-5: An Open-Source TPC-E Implementation for Global Performance Measurement of Computer Systems

TPC-E is the new benchmark approved by the TPC council. It is designed to exercise a brokerage firm workload, which is representative of current On-Line Transaction Processing workloads. In this paper we present DBT-5, a fair usage open-source implementation of the TPC-E benchmark. In addition to reporting about the design and implementation of the tool, experimental results from a system running database engine are also described. The significance of this work is that it provides an environment where recent innovations in the OLTP workload field can be evaluated

Performance Evaluation of CORBA Concurrency Control Service Using Stochastic Petri Nets

The interest in performance evaluation of middleware systems is increasing. Measurement techniques are still predominant among those used to carry out performance evaluation. However, performance models are currently being defined due to their flexibility, precision and facilities to carry out capacity planning activities. This paper presents stochastic Petri net models for performance evaluation of the CORBA Concurrency Control Service (CCS), which mediates concurrent access to objects. In order to validate the proposed models, CCS performance results obtained using those models are then compared against ones obtained through actual measurements.The interest in performance evaluation of middleware systems is increasing. Measurement techniques are still predominant among those used to carry out performance evaluation. However, performance models are currently being defined due to their flexibility, precision and facilities to carry out capacity planning activities. This paper presents stochastic Petri net models for performance evaluation of the CORBA Concurrency Control Service (CCS), which mediates concurrent access to objects. In order to validate the proposed models, CCS performance results obtained using those models are then compared against ones obtained through actual measurements

Is Chinese Competition Causing Deindustrialization in Brazil?

There has been a lively debate in Brazil in recent years, involving sectors of business, the labor movement, and academics, over deindustrialization and the future of the manufacturing sector. This is often linked to the growing relation between Brazil and China, which is now the country’s most significant trade partner. Brazil has experienced relative deindustrialization in the sense of a declining share of the manufacturing sector in gross domestic product that is mainly attributable to the changes in the country’s trade balance in manufactures. The direct and indirect impacts of China on Brazilian manufacturing have contributed to this relative deindustrialization

SARS-CoV-2 introductions and early dynamics of the epidemic in Portugal

Genomic surveillance of SARS-CoV-2 in Portugal was rapidly implemented by the National Institute of Health in the early stages of the COVID-19 epidemic, in collaboration with more than 50 laboratories distributed nationwide. Methods By applying recent phylodynamic models that allow integration of individual-based travel history, we reconstructed and characterized the spatio-temporal dynamics of SARSCoV-2 introductions and early dissemination in Portugal. Results We detected at least 277 independent SARS-CoV-2 introductions, mostly from European countries (namely the United Kingdom, Spain, France, Italy, and Switzerland), which were consistent with the countries with the highest connectivity with Portugal. Although most introductions were estimated to have occurred during early March 2020, it is likely that SARS-CoV-2 was silently circulating in Portugal throughout February, before the first cases were confirmed. Conclusions Here we conclude that the earlier implementation of measures could have minimized the number of introductions and subsequent virus expansion in Portugal. This study lays the foundation for genomic epidemiology of SARS-CoV-2 in Portugal, and highlights the need for systematic and geographically-representative genomic surveillance.We gratefully acknowledge to Sara Hill and Nuno Faria (University of Oxford) and Joshua Quick and Nick Loman (University of Birmingham) for kindly providing us with the initial sets of Artic Network primers for NGS; Rafael Mamede (MRamirez team, IMM, Lisbon) for developing and sharing a bioinformatics script for sequence curation (https://github.com/rfm-targa/BioinfUtils); Philippe Lemey (KU Leuven) for providing guidance on the implementation of the phylodynamic models; Joshua L. Cherry (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health) for providing guidance with the subsampling strategies; and all authors, originating and submitting laboratories who have contributed genome data on GISAID (https://www.gisaid.org/) on which part of this research is based. The opinions expressed in this article are those of the authors and do not reflect the view of the National Institutes of Health, the Department of Health and Human Services, or the United States government. This study is co-funded by Fundação para a Ciência e Tecnologia and Agência de Investigação Clínica e Inovação Biomédica (234_596874175) on behalf of the Research 4 COVID-19 call. Some infrastructural resources used in this study come from the GenomePT project (POCI-01-0145-FEDER-022184), supported by COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation (POCI), Lisboa Portugal Regional Operational Programme (Lisboa2020), Algarve Portugal Regional Operational Programme (CRESC Algarve2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), and by Fundação para a Ciência e a Tecnologia (FCT).info:eu-repo/semantics/publishedVersio