Modular and Stackable Power Generators for Efficient Renewable Power Generation

Stackable power generators enable very compact electric machines with high power density. How to identify an effective way of stacking is necessary and requires new knowledge for future guidance. In this paper, both possibilities of stacking modules concentrically and axially are explored and compared. An axial flux generator based on our existing double claw pole design is used as a case study. The claw pole generator, which is modular and stackable, significantly benefits on-site installation due to its flexible small modules that can be easily transported. This is particularly important to the installation of offshore wind turbines. Superconducting field windings are applied instead of copper in such power generators, which greatly increases their power density. In order to further increase their power density and reduce mass, we improved the modularity of 5 MW generators and stacked them in both ways. Results show that the power density versus mass as well as volume can be improved through stacking the modules both concentrically and axially, while the former approach is much more effective. Stacking two modules of 5 MW concentrically results in a 12.1 MW power generator with a more compact structure and higher power density than the original 10 MW generator

Artificial intelligence for photovoltaic systems

Photovoltaic systems have gained an extraordinary popularity in the energy generation industry. Despite the benefits, photovoltaic systems still suffer from four main drawbacks, which include low conversion efficiency, intermittent power supply, high fabrication costs and the nonlinearity of the PV system output power. To overcome these issues, various optimization and control techniques have been proposed. However, many authors relied on classical techniques, which were based on intuitive, numerical or analytical methods. More efficient optimization strategies would enhance the performance of the PV systems and decrease the cost of the energy generated. In this chapter, we provide an overview of how Artificial Intelligence (AI) techniques can provide value to photovoltaic systems. Particular attention is devoted to three main areas: (1) Forecasting and modelling of meteorological data, (2) Basic modelling of solar cells and (3) Sizing of photovoltaic systems. This chapter will aim to provide a comparison between conventional techniques and the added benefits of using machine learning methods

Parâmetros biológicos e tabela de vida de Tetranychus urticae (Acari: Tetranychidae) em cultivares de mamão

Este trabalho foi realizado para avaliar o desenvolvimento e reprodução de Tetranychus urticae em cultivares comerciais de mamão Carica papaya. Foram utilizadas cultivares do grupo "Formosa" ("Tainung 01" e "Calimosa") e do grupo "Solo" ("Golden" e "Sunrise"). Para iniciar o bioensaio, foi transferida uma fêmea fertilizada por disco de folha (n=50 repetições) e retirado após um período de 12h, sendo avaliada a cada 12h, registrando-se o período de incubação, duração do estágio de imaturo, longevidade e fecundidade dos adultos e viabilidade desses estágios. Os resultados indicaram que as cultivares de mamão "Tainung 01", "Calimosa", "Sunrise" e "Golden" são bons hospedeiros para T. urticae. O parâmetro viabilidade não sofreu influência das cultivares em todas as fases de desenvolvimento avaliadas, apresentando valores superiores a 90%. Não houve diferença estatística entre as cultivares nos parâmetros: período de pre-oviposição e viabilidade dos ovos. A cultivar "Tainung 01" apresentou menor potencial hospedeiro, embora houvesse menor duração nos estágios de ovo, larva, protoninfa e ovo-adulto. Nos parâmetros de tabela de vida e fertilidade, apresentou menores valores de Ro, r m e λ e maior valor de Td. Entre as cultivares, o "Sunrise" apresentou um elevado potencial hospedeiro para T. urticae, pois essa cultivar proporcionou a maior produção de ovos por fêmea, maior longevidade das fêmeas, bem como a maior taxa de reprodução (maior Ro, r m e λ e menor valor de Td).The study was conducted to evaluate the Tetranichus urticae development and reproduction in commercial Carica papaya cultivars. The assayed cultivars belongs to the "Formosa" ("Tainung 01" and "Calimosa") and from the "Solo" ("Golden" and "Sunrise") groups. A fertilized female was transferred to a leaf dish (n=50 repetitions) and was removed after a period of 12 hours and evaluations were done every 12 hours recording the incubation period, length of immature stage, longevity and fecundity of adults and viability of these stages. The cultivars of papaya, "Tainung 01", "Calimosa", "Sunrise" and "Golden" are adequate hosts for T. urticae. The recorded viability above 90% was not influenced by the different cultivars during all the development phases. There was not statistic difference among the cultivars in the parameters: pre-ovopositional period, and egg viability. Mites assayed in "Tainung 01" cultivar showed a shorter duration of the egg, larva, protonymph and egg-adult. At life table parameters and fertility, presented smaller Ro, r m and λ, and larger Td. "Sunrise" is the cultivar most adequate for T. urticae development, considering that mites assayed in this cultivar showed a larger production of eggs per female, longer female longevity, and higher reproduction rate (larger Ro, r m and λ and smaller Td)

Application guide for omics approaches to cell signaling

Research in signal transduction aims to identify the functions of different signaling pathways in physiological and pathological states. Traditional techniques using biochemical, genetic or cell biological approaches have made important contributions to our understanding of cellular signaling. However, the single-gene approach does not take into account the full complexity of cell signaling. With the availability of omics techniques, great progress has been made in understanding signaling networks. Omics approaches can be classified into two categories: 'molecular profiling', including genomic, proteomic, post-translational modification and interactome profiling; and 'molecular perturbation', including genetic and functional perturbations