960 resultados para Leaf gas exchange


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Premise of the study: Plant invasiveness can be promoted by higher values of adaptive traits (e.g., photosynthetic capacity, biomass accumulation), greater plasticity and coordination of these traits, and by higher and positive relative influence of these functionalities on fitness, such as increasing reproductive output. However, the dataset for this premise rarely include linkages between epidermal-stomatal traits, leaf internal anatomy, and physiological performance. Methods: Three ecological pairs of invasive vs non-invasive (native) woody vine species of South-East Queensland, Australia were investigated for trait differences in leaf morphology and anatomy under varying light intensity. The linkages of these traits with physiological performance (e.g. water use efficiency, photosynthesis, and leaf construction cost) and plant adaptive traits of specific leaf area, biomass, and relative growth rates were also explored. Key results: Mean leaf anatomical trait differed significantly between the two groups, except for stomatal size. Plasticity of traits, and to a very limited extent, their phenotypic integration were higher in the invasive relative to the native species. ANOVA, ordination, and analysis of similarity suggest that for leaf morphology and anatomy, the three functional strategies contribute to the differences between the two groups in the order phenotypic plasticity > trait means > phenotypic integration. Conclusions: The linkages demonstrated in the study between stomatal complex/gross anatomy and physiology are scarce in the ecological literature of plant invasiveness, but the findings suggest that leaf anatomical traits need to be considered routinely as part of weed species assessment and in the worldwide leaf economic spectrum.

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Health Information Exchange (HIE) is an interesting phenomenon. It is a patient centric health and/or medical information management scenario enhanced by integration of Information and Communication Technologies (ICT). While health information systems are repositioning complex system directives, in the wake of the ‘big data’ paradigm, extracting quality information is challenging. It is anticipated that in this talk, ICT enabled healthcare scenarios with big data analytics will be shared. In addition, research and development regarding big data analytics, such as current trends of using these technologies for health care services and critical research challenges when extracting quality of information to improve quality of life will be discussed.

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Few would disagree that the upstream oil & gas industry has become more technology-intensive over the years. But how does innovation happen in the industry? Specifically, what ideas and inputs flow from which parts of the sector׳s value network, and where do these inputs go? And how do firms and organizations from different countries contribute differently to this process? This paper puts forward the results of a survey designed to shed light on these questions. Carried out in collaboration with the Society of Petroleum Engineers (SPE), the survey was sent to 469 executives and senior managers who played a significant role with regard to R&D and/or technology deployment in their respective business units. A total of 199 responses were received from a broad range of organizations and countries around the world. Several interesting themes and trends emerge from the results, including: (1) service companies tend to file considerably more patents per innovation than other types of organization; (2) over 63% of the deployed innovations reported in the survey originated in service companies; (3) neither universities nor government-led research organizations were considered to be valuable sources of new information and knowledge in the industry׳s R&D initiatives, and; (4) despite the increasing degree of globalization in the marketplace, the USA still plays an extremely dominant role in the industry׳s overall R&D and technology deployment activities. By providing a detailed and objective snapshot of how innovation happens in the upstream oil & gas sector, this paper provides a valuable foundation for future investigations and discussions aimed at improving how R&D and technology deployment are managed within the industry. The methodology did result in a coverage bias within the survey, however, and the limitations arising from this are explored.

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Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

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The upstream oil & gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data”—that is, the ability to apply more sophisticated types of analytical tools to information in a way that extracts new insights or creates new forms of value—is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil & gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This paper examines existing data management practices in the upstream oil & gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the Big Data revolution. The comparison shows that, in companies that are leading the Big Data revolution, data is regarded as a valuable asset. The presented evidence also shows, however, that this is usually not true within the oil & gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how upstream oil & gas companies could potentially extract more value from data, and concludes with a series of specific technical and management-related recommendations to this end.

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J.W.Lindt’s Colonial man and Aborigine image from the GRAFTON ALBUM: “On chemistry and optics all does not depend, art must with these in triple union blend” (text from J.W. Lindt’s photographic backing card)...

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This study evaluated the complexity of calcium ion exchange with sodium exchanged weak acid cation resin (DOW MAC-3). Exchange equilibria recorded for a range of different solution normalities revealed profiles which were represented by conventional “L” or “H” type isotherms at low values of equilibrium concentration (Ce) of calcium ions, plus a superimposed region of increasing calcium uptake was observed at high Ce values. The loading of calcium ions was determined to be ca. 53.5 to 58.7 g/kg of resin when modelling only the sorption curve created at low Ce values,which exhibited a well-defined plateau. The calculated calcium ion loading capacity for DOWMAC-3 resin appeared to correlate with the manufacturer's recommendation. The phenomenon of super equivalent ion exchange (SEIX) was observed when the “driving force” for the exchange process was increased in excess of 2.25 mmol calcium ions per gram of resin in the starting solution. This latter event was explained in terms of displacement of sodium ions from sodium hydroxide solution which remained in the resin bead following the initial conversion of the as supplied “H+” exchanged resin sites to the “Na+” version required for softening studies. Evidence for hydrolysis of a small fraction of the sites on the sodium exchanged resin surface was noted. The importance of carefully choosing experimental parameters was discussed especially in relation to application of the Langmuir–Vageler expression. This latter model which compared the ratio of the initial calcium ion concentration in solution to resin mass, versus final equilibrium loading of the calcium ions on the resin; was discovered to be an excellent means of identifying the progress of the calcium–sodium ion exchange process. Moreover, the Langmuir–Vageler model facilitated standardization of various calcium–sodium ion exchange experiments which allowed systematic experimental design.

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The exchange of iron species from iron (III) chloride solutions with a strong acid cation resin has been investigated in relation to a variety of water and wastewater applications. A detailed equilibrium isotherm analysis was conducted wherein models such as Langmuir Vageler, Competitive Langmuir, Freundlich, Temkin, Dubinin Astakhov, Sips and Brouers-Sotolongo were applied to the experimental data. An important conclusion was that both the bottle-point method and solution normality used to generate the ion exchange equilibrium information influenced which sorption model fitted the isotherm profiles optimally. Invariably, the calculated value for the maximum loading of iron on strong acid cation resin was substantially higher than the value of 47.1 g/kg of resin which would occur if one Fe3+ ion exchanged for three “H+” sites on the resin surface. Consequently, it was suggested that above pH 1, various iron complexes sorbed to the resin in a manner which required less than 3 sites per iron moiety. Column trials suggested that the iron loading was 86.6 g/kg of resin when 1342 mg/L Fe (III) ions in water were flowed at 31.7 bed volumes per hour. Regeneration with 5 to 10 % HCl solutions reclaimed approximately 90 % of exchange sites.