954 resultados para Trissino, Giovanni Giorgio, 1478-1550.


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Background Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.

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Emerging from the challenge to reduce energy consumption in buildings is the need for energy simulation to be used more effectively to support integrated decision making in early design. As a critical response to a Green Star case study, we present DEEPA, a parametric modeling framework that enables architects and engineers to work at the same semantic level to generate shared models for energy simulation. A cloud-based toolkit provides web and data services for parametric design software that automate the process of simulating and tracking design alternatives, by linking building geometry more directly to analysis inputs. Data, semantics, models and simulation results can be shared on the fly. This allows the complex relationships between architecture, building services and energy consumption to be explored in an integrated manner, and decisions to be made collaboratively.

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Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.

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The use of Cellular Automata (CA) for musical purposes has a rich history. In general the mapping of CA states to note-level music representations has focused on pitch mapping and downplayed rhythm. This paper reports experiments in the application of one-dimensional cellular automata to the generation and evolution of rhythmic patterns. A selection of CA tendencies are identified that can be used as compositional tools to control the rhythmic coherence of monophonic passages and the polyphonic texture of musical works in broad-brush, rather than precisely deterministic, ways. This will provide the composer and researcher with a clearer understanding of the useful application of CAs for generative music.

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Surface coating with an organic self-assembled monolayer (SAM) can enhance surface reactions or the absorption of specific gases and hence improve the response of a metal oxide (MOx) sensor toward particular target gases in the environment. In this study the effect of an adsorbed organic layer on the dynamic response of zinc oxide nanowire gas sensors was investigated. The effect of ZnO surface functionalisation by two different organic molecules, tris(hydroxymethyl)aminomethane (THMA) and dodecanethiol (DT), was studied. The response towards ammonia, nitrous oxide and nitrogen dioxide was investigated for three sensor configurations, namely pure ZnO nanowires, organic-coated ZnO nanowires and ZnO nanowires covered with a sparse layer of organic-coated ZnO nanoparticles. Exposure of the nanowire sensors to the oxidising gas NO2 produced a significant and reproducible response. ZnO and THMA-coated ZnO nanowire sensors both readily detected NO2 down to a concentration in the very low ppm range. Notably, the THMA-coated nanowires consistently displayed a small, enhanced response to NO2 compared to uncoated ZnO nanowire sensors. At the lower concentration levels tested, ZnO nanowire sensors that were coated with THMA-capped ZnO nanoparticles were found to exhibit the greatest enhanced response. ΔR/R was two times greater than that for the as-prepared ZnO nanowire sensors. It is proposed that the ΔR/R enhancement in this case originates from the changes induced in the depletion-layer width of the ZnO nanoparticles that bridge ZnO nanowires resulting from THMA ligand binding to the surface of the particle coating. The heightened response and selectivity to the NO2 target are positive results arising from the coating of these ZnO nanowire sensors with organic-SAM-functionalised ZnO nanoparticles.

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Purpose – In the context of global knowledge economy, knowledge-based urban development (KBUD) is seen as an effective development strategy for city-regions to survive, flourish and become highly competitive urban agglomerations – i.e., a knowledge city-region. This paper aims to evaluate the KBUD dynamics, capacity and potentials of a rapidly emerging knowledge city-region of Finland – Tampere region. Design/methodology/approach – The paper undertakes a review of the literature on regional development in the knowledge economy era. It adopts a qualitative analysis technique to scrutinize the dynamics, capacity and potentials of Tampere region. The semi-structured interview process starts with the pre-determined key actors of the city-region with an aim of determining the other key players. Next, with the participation of all key players to the interviews, the research reveals the principal issues, assets and mechanisms that relate to KBUD, and portrays the strengths, weaknesses, opportunities and threats of the city-region. A critical analysis of the findings along with the previous studies is undertaken to provide a clear picture of the dynamics, capacity and potentials of the emerging knowledge city-region. Originality/value – This paper reports the findings of a pioneering study focusing on the investigation of the KBUD dynamics, capacity and potentials of Tampere region. The paper critically evaluates the city-region from the knowledge perspective with the lens of KBUD, and the lessons learned and the methodological approach of the paper shed light to other city-regions seeking such development. Practical implications – The paper discusses the findings of a study from Tampere region that critically scrutinizes the KBUD experience of the city-region. The research provides an invaluable opportunity to inform the regional decision-, policy- and plan-making mechanisms by determining key issues, actors, assets, processes and potential development directions for the KBUD of Tampere region.

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Exposure to ultrafine particles (diameter less than 100 nm) is an important topic in epidemiological and toxicological studies. This study used the average particle number size distribution data obtained from our measurement survey in major micro-environments, together with the people activity pattern data obtained from the Italian Human Activity Pattern Survey to estimate the tracheobronchial and alveolar dose of submicrometer particles for different population age groups in Italy. We developed a numerical methodology based on Monte Carlo method, in order to estimate the best combination from a probabilistic point of view. More than 106 different cases were analyzed according to a purpose built sub-routine and our results showed that the daily alveolar particle number and surface area deposited for all of the age groups considered was equal to 1.5 x 1011 particles and 2.5 x 1015 m2, respectively, varying slightly for males and females living in Northern or Southern Italy. In terms of tracheobronchial deposition, the corresponding values for daily particle number and surface area for all age groups was equal to 6.5 x 1010 particles and 9.9 x 1014 m2, respectively. Overall, the highest contributions were found to come from indoor cooking (female), working time (male) and transportation (i.e. traffic derived particles) (children).

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Crop simulation models have the potential to assess the risk associated with the selection of a specific N fertilizer rate, by integrating the effects of soil-crop interactions on crop growth under different pedo-climatic and management conditions. The objective of this study was to simulate the environmental and economic impact (nitrate leaching and N2O emissions) of a spatially variable N fertilizer application in an irrigated maize field in Italy. The validated SALUS model was run with 5 nitrogen rates scenarios, 50, 100, 150, 200, and 250 kg N ha−1, with the latter being the N fertilization adopted by the farmer. The long-term (25 years) simulations were performed on two previously identified spatially and temporally stable zones, a high yielding and low yielding zone. The simulation results showed that N fertilizer rate can be reduced without affecting yield and net return. The marginal net return was on average higher for the high yield zone, with values ranging from 1550 to 2650 € ha−1 for the 200 N and 1485 to 2875 € ha−1 for the 250 N. N leaching varied between 16.4 and 19.3 kg N ha−1 for the 200 N and the 250 N in the high yield zone. In the low yield zone, the 250 N had a significantly higher N leaching. N2O emissions varied between 0.28 kg N2O ha−1 for the 50 kg N ha−1 rate to a maximum of 1.41 kg N2O ha−1 for the 250 kg N ha−1 rate.