997 resultados para Hyperspectral systems


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Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r2 relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r2 = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg)1) in Horsham with an r2 = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.

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This paper provides a comprehensive review of the vision-based See and Avoid problem for unmanned aircraft. The unique problem environment and associated constraints are detailed, followed by an in-depth analysis of visual sensing limitations. In light of such detection and estimation constraints, relevant human, aircraft and robot collision avoidance concepts are then compared from a decision and control perspective. Remarks on system evaluation and certification are also included to provide a holistic review approach. The intention of this work is to clarify common misconceptions, realistically bound feasible design expectations and offer new research directions. It is hoped that this paper will help us to unify design efforts across the aerospace and robotics communities.

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The paper deals with the basic problem of adjusting a matrix gain in a discrete-time linear multivariable system. The object is to obtain a global convergence criterion, i.e. conditions under which a specified error signal asymptotically approaches zero and other signals in the system remain bounded for arbitrary initial conditions and for any bounded input to the system. It is shown that for a class of up-dating algorithms for the adjustable gain matrix, global convergence is crucially dependent on a transfer matrix G(z) which has a simple block diagram interpretation. When w(z)G(z) is strictly discrete positive real for a scalar w(z) such that w-1(z) is strictly proper with poles and zeros within the unit circle, an augmented error scheme is suggested and is proved to result in global convergence. The solution avoids feeding back a quadratic term as recommended in other schemes for single-input single-output systems.

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Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

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The monoterpene cyclic ether, cineole (l,8-cineole, I) also known as eucalyptol, is a component of many essential oils and is widely distributed in nature. It is extensively used in pharmaceutical preparations for external application and also as a nasal spray. It was reported earlier that cineole when administered to sheep may be largely oxidized in the system (Scheline 1978). However the mode of metabolism of cineole is not known. Hence the present study was undertaken to investigate the metabolic fate of this ubiquitous terpenoid following its administration to rats by gastric intubation.

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ErBa2Cu3O7 and Er0.5Y0.5Ba2Cu3O7 are both high-Tc superconductors attaining zero resistance above 80 K. Preliminary studies indicate that Yb1−xYxBa2Cu3O7 also exhibits zero resistance above 77 K.

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The Mycoplasma hyopneumoniae ribonucleotide reductase R2 subunit (NrdF) gene fragment was cloned into eukaryotic and prokaryotic expression vectors and its immunogenicity evaluated in mice immunized orally with attenuated Salmonella typhimurium aroA CS332 harboring either of the recombinant expression plasmids. We found that NrdF is highly conserved among M. hyopneumoniae strains. The immunogenicity of NrdF was examined by analyzing antibody responses in sera and lung washes, and the cell-mediated immune (CMI) response was assessed by determining the INF-[gamma] level produced by splenocytes upon in vitro stimulation with NrdF antigen. S. typhimurium expressing NrdF encoded by the prokaryotic expression plasmid (pTrcNrdF) failed to elicit an NrdF-specific serum or secretory antibody response, and IFN-[gamma] was not produced. Similarly, S. typhimurium carrying the eukaryotic recombinant plasmid encoding NrdF (pcNrdF) did not induce a serum or secretory antibody response, but did elicit significant NrdF-specific IFN-[gamma] production, indicating induction of a CMI response. However, analysis of immune responses against the live vector S. typhimurium aroA CS332 showed a serum IgG response but no mucosal IgA response in spite of its efficient invasiveness in vitro. In the present study we show that the DNA vaccine encoding the M. hyopneumoniae antigen delivered orally via a live attenuated S. typhimurium aroA can induce a cell-mediated immune response. We also indicate that different live bacterial vaccine carriers may have an influence on the type of the immune response induced.