Compositional specification of functionality and timing of manufacturing systems

In this paper, a formal modeling approach is introduced for compositional specification of both functionality and timing of manufacturing systems. Functionality aspects can be considered orthogonally to the timing. The functional aspects are specified using two abstraction levels; high-level activities and lower level actions. Design of a functionally correct controller is possible by looking only at the activity level, abstracting from the different execution orders of actions. Furthermore, the specific timing of actions is not needed. As a result, controller designcan be performed on a much smaller state space compared to an explicit model where timing and actions are present. The performance of the controller can be analyzed and optimizedby taking into account the timing characteristics. Since formal semantics are given in terms of a (max, +) state space, various existing performance analysis techniques can be used. Weillustrate the approach, including performance analysis, on an example manufacturing system

Identifying bottlenecks in manufacturing systems using stochastic criticality analysis

System design is a difficult process with many design-choices for which the impact may be difficult to foresee. Manufacturing system design is no exception to this. Increased use of flexible manufacturing systems which are able to perform different operations/use-cases further raises the design complexity. One important criterion to consider is the overall makespan and associated critical path for the different use-cases of the system. Stochastic critical path analysis plays a fundamental role in providing useful feedback for system designers to evaluate alternative specifications, which traditional fixed-time analysis cannot. In this paper, we extend our formal model-based framework, for the specification and design of manufacturing systems, with stochastic analysis abilities by associating a criticality index to each action performed by the system. This index can then be visualized and used within the framework such that a system designer can make better informed decisions. We propose a Monte-Carlo method as an estimation algorithm and we explicitly define and use confidence intervals to achieve an acceptable estimation error. We further demonstrate the use of the extended framework and stochastic analysis with an example manufacturing system

Necessidades de treinamento organizacional e motivação para trabalhar Training needs and work motivation: analysis of the relationship

Apesar de contribuir com a programação, a execução e a avaliação de resultados, a etapa de análise de necessidades tem sido constantemente negligenciada pela literatura científica e pela prática profissional de treinamento, cujos volumosos investimentos, portanto, tendem a ser desperdiçados. Os modelos que orientam este importante campo foram propostos há aproximadamente 50 anos, de forma que não são capazes, atualmente, de orientar teórica e metodologicamente estudiosos e praticantes da área. Nesse sentido, esta pesquisa objetivou, mediante execução de análise de covariância em amostra de 213 participantes, investigar a relação entre motivação para o trabalho e complexidade de necessidades de treinamento, com vistas a permitir a composição futura de modelos teóricos de análise de necessidades integrados, não apenas por componentes relacionados às tarefas, como prescrito na literatura, mas, também, por variáveis relativas aos níveis individual, grupal e organizacional de análise. Especificamente, quatro objetivos específicos, cada qual associado a procedimentos e técnicas de pesquisa particulares, foram determinados: (1) elaborar, por meio de pesquisa documental e grupo de foco, e validar, teórica e empiricamente, a partir de entrevista individual e realização de análises fatoriais exploratórias, instrumento para aferição das necessidades de treinamento; (2) adaptar e validar estatisticamente o instrumento de medida de motivação para trabalhar, também em função de análises fatoriais exploratórias; (3) com teste de diferença de médias entre amostras independentes, formar grupos de comparação em função do no nível de motivação para trabalhar dos respondentes; e (4) identificar variáveis de controle estatístico para composição do modelo final de investigação a partir de correlações bivariadas. Os resultados obtidos satisfizeram todos esses quatro objetivos intermediários de pesquisa: bons índices psicométricos de validação e confiabilidade dos instrumentos de necessidades e de motivação foram obtidos; dois grupos de comparação puderam ser estatisticamente formados em função dos níveis de motivação de seus integrantes; e o tempo de serviço pôde ser selecionado como variável de controle estatístico para a composição do modelo final de investigação. Apesar desses resultados positivos, a análise de covariância efetuada não evidenciou relação alguma entre motivação e necessidades de treinamento, contrariando parte da literatura, não diretamente relacionada à área de treinamento, que atesta esta relação direta. Este resultado torna necessária a ampliação e o aprofundamento de pesquisas nesse sentido, principalmente pelo fato de a motivação ser uma das principais variáveis individuais responsáveis pela explicação de medidas de desempenho pós-treinamento.<br>Although contributing to the planning, execution and results evaluation, the needs analysis subsystem has been consistently neglected by the training scientific literature and professional practice, whose bulky investments, therefore, tend to be wasted. The models that guide this important field have been proposed about 50 years ago, so they are not capable, today, of theoretical and methodological guide scholars and practitioners in the area. Thus, this study aimed, through implementation of analysis of covariance in a sample of 213 participants, to investigate the relationship between motivation to work and complexity of training needs, in order to allow the composition of future needs analysis theoretical models integrated not only for components related to the tasks, as prescribed in the literature, but also by variables related to the individual, group and organizational level of analysis. Specifically, four specific objectives, each one associated with particular procedures and research techniques were determined: (1) developing, through documental research and focus group, and validate, theoretically and empirically, from individual interviews and exploratory factor analysis, instrument for measuring training needs; (2) adapt and statistically validate the instrument to measure motivation to work, also through of exploratory factor analysis; (3) to test for mean differences between independent samples produce comparison groups depending on the level of respondents' motivation to work; and (4) identifying control variables for statistical composition of the final research, from bivariate correlations. The results satisfied all of these four intermediate goals: good psychometric indices of reliability and validity of the instruments of needs and motivation were obtained; two groups could be statistically formed according to level of motivation of its members; and the time service might be selected as a control variable for the statistical composition of the final investigation model. Despite these positive results, the covariance analysis performed did not show any relation between motivation and training needs, contrary to conventional wisdom, not directly related to the training area, which certifies this direct relationship. This result makes it necessary to expand and deepen research in this direction, mainly because the motivation is one of the main individual variables responsible for the explanation of post-performance training measures

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions. © Copyright