969 resultados para Near-infrared emission intensity
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Sensors for real-time monitoring of environmental contaminants are essential for protecting ecosystems and human health. Refractive index sensing is a non-selective technique that can be used to measure almost any analyte. Miniaturized refractive index sensors, such as silicon-on-insulator (SOI) microring resonators are one possible platform, but require coatings selective to the analytes of interest. A homemade prism refractometer is reported and used to characterize the interactions between polymer films and liquid or vapour-phase analytes. A camera was used to capture both Fresnel reflection and total internal reflection within the prism. For thin-films (d = 10 μm - 100 μm), interference fringes were also observed. Fourier analysis of the interferogram allowed for simultaneous extraction of the average refractive index and film thickness with accuracies of ∆n = 1-7 ×10-4 and ∆d < 3-5%. The refractive indices of 29 common organic solvents as well as aqueous solutions of sodium chloride, sucrose, ethylene glycol, glycerol, and dimethylsulfoxide were measured at λ = 1550 nm. These measurements will be useful for future calibrations of near-infrared refractive index sensors. A mathematical model is presented, where the concentration of analyte adsorbed in a film can be calculated from the refractive index and thickness changes during uptake. This model can be used with Fickian diffusion models to measure the diffusion coefficients through the bulk film and at the film-substrate interface. The diffusion of water and other organic solvents into SU-8 epoxy was explored using refractometry and the diffusion coefficient of water into SU-8 is presented. Exposure of soft baked SU-8 films to acetone, acetonitrile and methanol resulted in rapid delamination. The diffusion of volatile organic compound (VOC) vapours into polydimethylsiloxane and polydimethyl-co-polydiphenylsiloxane polymers was also studied using refractometry. Diffusion and partition coefficients are reported for several analytes. As a model system, polydimethyl-co-diphenylsiloxane films were coated onto SOI microring resonators. After the development of data acquisition software, coated devices were exposed to VOCs and the refractive index response was assessed. More studies with other polymers are required to test the viability of this platform for environmental sensing applications.
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We present a primary transit observation for the ultra-hot (T eq ~ 2400 K) gas giant expolanet WASP-121b, made using the Hubble Space Telescope Wide Field Camera 3 in spectroscopic mode across the 1.12–1.64 μm wavelength range. The 1.4 μm water absorption band is detected at high confidence (5.4σ) in the planetary atmosphere. We also reanalyze ground-based photometric light curves taken in the B, r', and z' filters. Significantly deeper transits are measured in these optical bandpasses relative to the near-infrared wavelengths. We conclude that scattering by high-altitude haze alone is unlikely to account for this difference and instead interpret it as evidence for titanium oxide and vanadium oxide absorption. Enhanced opacity is also inferred across the 1.12–1.3 μm wavelength range, possibly due to iron hydride absorption. If confirmed, WASP-121b will be the first exoplanet with titanium oxide, vanadium oxide, and iron hydride detected in transmission. The latter are important species in M/L dwarfs and their presence is likely to have a significant effect on the overall physics and chemistry of the atmosphere, including the production of a strong thermal inversion.
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The aim of this work was to perform a detailed investigation of the use of Selective Laser Melting (SLM) technology to process eutectic silver-copper alloy Ag 28 wt. % Cu (also called AgCu28). The processing occurred with a Realizer SLM 50 desktop machine. The powder analysis (SEM-topography, EDX, particle distribution) was reported as well as the absorption rates for the near-infrared (NIR) spectrum. Microscope imaging showed the surface topography of the manufactured parts. Furthermore, microsections were conducted for the analysis of porosity. The Design of Experiments approach used the response surface method in order to model the statistical relationship between laser power, spot distance and pulse time.
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L’estimation temporelle de l’ordre des secondes à quelques minutes requiert des ressources attentionnelles pour l’accumulation d’information temporelle pendant l’intervalle à estimer (Brown, 2006; Buhusi & Meck, 2009; Zakay & Block, 2004). Ceci est démontré dans le paradigme de double tâche, où l’exécution d’une tâche concurrente pendant l’estimation d’un intervalle mène à un effet d’interférence, soit une distorsion de la durée perçue se traduisant par des productions temporelles plus longues et plus variables que si l’estimation de l’intervalle était effectuée seule (voir Brown, 1997; 2010). Un effet d’interférence est également observé lorsqu’une interruption est attendue pendant l’intervalle à estimer, l’allongement étant proportionnel à la durée d’attente de l’interruption (Fortin & Massé, 2000). Cet effet a mené à l’hypothèse que la production avec interruption serait sous-tendue par un mécanisme de partage attentionnel similaire à la double tâche (Fortin, 2003). Afin d’étudier cette hypothèse, deux études empiriques ont été effectuées dans des contextes expérimentaux associés respectivement à une augmentation et à une diminution de l’effet d’interférence, soit le vieillissement (Chapitre II) et l’entraînement cognitif (Chapitre III). Dans le Chapitre II, la tâche de production avec interruption est étudiée chez des participants jeunes et âgés à l’aide de la spectroscopie proche infrarouge fonctionnelle (SPIRf). Les résultats montrent que l’attente de l’interruption est associée à des coûts comportementaux et fonctionnels similaires à la double tâche. Au niveau comportemental, un allongement des productions proportionnel à la durée d’attente de l’interruption est observé chez l’ensemble des participants, mais cet effet est plus prononcé chez les participants âgés que chez les jeunes. Ce résultat est compatible avec les observations réalisées dans le paradigme de double tâche (voir Verhaegen, 2011 pour une revue). Au niveau fonctionnel, la production avec et sans interruption est associée à l’activation du cortex préfrontal droit et des régions préfrontales dorsolatérales connues pour leur rôle au niveau de l’estimation temporelle explicite (production d’intervalle) et implicite (processus préparatoires). En outre, l’attente de l’interruption est associée à l’augmentation de l’activation corticale préfrontale dans les deux hémisphères chez l’ensemble des participants, incluant le cortex ventrolatéral préfrontal associé au contrôle attentionnel dans la double tâche. Finalement, les résultats montrent que les participants âgés se caractérisent par une activation corticale bilatérale lors de la production sans et avec interruption. Dans le cadre des théories du vieillissement cognitif (Park & Reuter-Lorenz, 2009), cela suggère que l’âge est associé à un recrutement inefficace des ressources attentionnelles pour la production d’intervalle, ceci nuisant au recrutement de ressources additionnelles pour faire face aux demandes liées à l’attente de l’interruption. Dans le Chapitre III, la tâche de production avec interruption est étudiée en comparant la performance de participants assignés à l’une ou l’autre de deux conditions d’exécution extensive (cinq sessions successives) de double tâche ou de production avec interruption. Des sessions pré et post-test sont aussi effectuées afin de tester le transfert entre les conditions. Les résultats montrent un effet d’interférence et de durée d’interférence tant en production avec double tâche qu’en production avec interruption. Ces effets sont toutefois plus prononcés lors de la production avec interruption et tendent à augmenter au fil des sessions, ce qui n’est pas observé en double tâche. Cela peut être expliqué par l’influence des processus préparatoires pendant la période pré-interruption et pendant l’interruption. Finalement, les résultats ne mettent pas en évidence d’effets de transfert substantiels entre les conditions puisque les effets de la pratique concernent principalement la préparation temporelle, un processus spécifique à la production avec interruption. Par la convergence que permet l’utilisation d’un même paradigme avec des méthodologies distinctes, ces travaux approfondissent la connaissance des mécanismes attentionnels associés à l’estimation temporelle et plus spécifiquement à la production avec interruption. Les résultats supportent l’hypothèse d’un partage attentionnel induit par l’attente de l’interruption. Les ressources seraient partagées entre les processus d’estimation temporelle explicite et implicite, une distinction importante récemment mise de l’avant dans la recherche sur l’estimation du temps (Coull, Davranche, Nazarian & Vidal, 2013). L’implication de processus dépendant des ressources attentionnelles communes pour le traitement de l’information temporelle peut rendre compte de l’effet d’interférence robuste et systématique observé dans la tâche de production avec interruption.
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Thesis (Master's)--University of Washington, 2016-08
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Thesis (Ph.D.)--University of Washington, 2016-08
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The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.
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Terrestrial remote sensing imagery involves the acquisition of information from the Earth's surface without physical contact with the area under study. Among the remote sensing modalities, hyperspectral imaging has recently emerged as a powerful passive technology. This technology has been widely used in the fields of urban and regional planning, water resource management, environmental monitoring, food safety, counterfeit drugs detection, oil spill and other types of chemical contamination detection, biological hazards prevention, and target detection for military and security purposes [2-9]. Hyperspectral sensors sample the reflected solar radiation from the Earth surface in the portion of the spectrum extending from the visible region through the near-infrared and mid-infrared (wavelengths between 0.3 and 2.5 µm) in hundreds of narrow (of the order of 10 nm) contiguous bands [10]. This high spectral resolution can be used for object detection and for discriminating between different objects based on their spectral xharacteristics [6]. However, this huge spectral resolution yields large amounts of data to be processed. For example, the Airbone Visible/Infrared Imaging Spectrometer (AVIRIS) [11] collects a 512 (along track) X 614 (across track) X 224 (bands) X 12 (bits) data cube in 5 s, corresponding to about 140 MBs. Similar data collection ratios are achieved by other spectrometers [12]. Such huge data volumes put stringent requirements on communications, storage, and processing. The problem of signal sbspace identification of hyperspectral data represents a crucial first step in many hypersctral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction (DR) yelding gains in data storage and retrieval and in computational time and complexity. Additionally, DR may also improve algorithms performance since it reduce data dimensionality without losses in the useful signal components. The computation of statistical estimates is a relevant example of the advantages of DR, since the number of samples required to obtain accurate estimates increases drastically with the dimmensionality of the data (Hughes phnomenon) [13].
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The red deer (Cervus elaphus) is currently one of the most widespread and abundant wild ungulates in the Iberian Peninsula and is extremely important both ecologically, as a key species for the functioning of the ecosystems, and economically, as a major game species. In Iberia, red deer populations are subjected to different management systems that may affect the physical condition of the individuals, with further consequences for population dynamics. Studies investigating the effects of management practices and environmental conditions on the performance of red deer are still rare regarding Mediterranean ecosystems. Much of the knowledge concerning the ecology of red deer and the impact of management on its physical condition is based on studies conducted in northern and central regions of Europe, where climatological features and management practices differ from those observed in the Mediterranean areas of Iberia. Studies on a biogeographical scale can provide important insights into the relationships between species and a particular environment and contribute to the development of more targeted and appropriate management practices. The optimisation of sampling procedures and the fine-tuning of pre-existing analytical techniques are also fundamental to a more cost-effective monitoring and, therefore, are of enormous value to wildlife managers. In this context, the main aims of this thesis were: 1) to optimise the procedures used to assess the physical condition of red deer; and 2) to identify relevant management and environmental factors affecting the nutritional condition and stress physiology of red deer in the Mediterranean ecosystems of Iberia, as well as any potential interactions between those factors. Two studies with a methodological focus, presented in the first part of the thesis, demonstrated that the physical condition of red deer can be evaluated more simply, using more cost- and time-effective procedures than those traditionally used: i) it was shown that only one kidney and its associated fat is enough to assess nutritional condition in red deer; and ii) the feasibility of using near infrared spectroscopy to predict the concentrations of stress hormone metabolites was demonstrated using faeces of red deer for the first time. Subsequently, two large-scale observational studies, conducted in representative red deer populations found in Mediterranean Iberia, highlighted the importance of considering seasonal environmental variations and variables related to hunting management practices to better understand the nutritional and physiological ecology of red deer. High population densities had adverse effects on the nutritional condition of the deer and were associated with increased stress levels in natural populations without supplementary feeding. Massive hunting events involving the use of hounds were also identified as a potential source of chronic stress in red deer. The research presented in this thesis has clear implications regarding the management and monitoring of red deer populations in Mediterranean environments and is intended to help wildlife managers to implement more effective monitoring programmes and sustainable management practices.
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Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change
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Eucalyptus pellita demonstrated good growth and wood quality traits in this study, with young plantation grown timber being suitable for both solid and pulp wood products. All traits examined were under moderate levels of genetic control with little genotype by environment interaction when grown on two contrasting sites in Vietnam. Eucalyptus pellita currently has a significant role in reforestation in the tropics. Research to support expanded of use of this species is needed: particularly, research to better understand the genetic control of key traits will facilitate the development of genetically improved planting stock. This study aimed to provide estimates of the heritability of diameter at breast height over bark, wood basic density, Kraft pulp yield, modulus of elasticity and microfibril angle, and the genetic correlations among these traits, and understand the importance of genotype by environment interactions in Vietnam. Data for diameter and wood properties were collected from two 10-year-old, open-pollinated progeny trials of E. pellita in Vietnam that evaluated 104 families from six native range and three orchard sources. Wood properties were estimated from wood samples using near-infrared (NIR) spectroscopy. Data were analysed using mixed linear models to estimate genetic parameters (heritability, proportion of variance between seed sources and genetic correlations). Variation among the nine sources was small compared to additive variance. Narrow-sense heritability and genetic correlation estimates indicated that simultaneous improvements in most traits could be achieved from selection among and within families as the genetic correlations among traits were either favourable or close to zero. Type B genetic correlations approached one for all traits suggesting that genotype by environment interactions were of little importance. These results support a breeding strategy utilizing a single breeding population advanced by selecting the best individuals across all seed sources. Both growth and wood properties have been evaluated. Multi-trait selection for growth and wood property traits will lead to more productive populations of E. pellita both with improved productivity and improved timber and pulp properties.
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The Rangeland Journal – Climate Clever Beef special issue examines options for the beef industry in northern Australia to contribute to the reduction in global greenhouse gas (GHG) emissions and to engage in the carbon economy. Relative to its gross value (A$5 billion), the northern beef industry is responsible for a sizable proportion of national reportable GHG emissions (8–10%) through enteric methane, savanna burning, vegetation clearing and land degradation. The industry occupies large areas of land and has the potential to impact the carbon cycle by sequestering carbon or reducing carbon loss. Furthermore, much of the industry is currently not achieving its productivity potential, which suggests that there are opportunities to improve the emissions intensity of beef production. Improving the industry’s GHG emissions performance is important for its environmental reputation and may benefit individual businesses through improved production efficiency and revenue from the carbon economy. The Climate Clever Beef initiative collaborated with beef businesses in six regions across northern Australia to better understand the links between GHG emissions and carbon stocks, land condition, herd productivity and profitability. The current performance of businesses was measured and alternate management options were identified and evaluated. Opportunities to participate in the carbon economy through the Australian Government’s Emissions Reduction Fund (ERF) were also assessed. The initiative achieved significant producer engagement and collaboration resulting in practice change by 78 people from 35 businesses, managing more than 1 272 000 ha and 132 000 cattle. Carbon farming opportunities were identified that could improve both business performance and emissions intensity. However, these opportunities were not without significant risks, trade-offs and limitations particularly in relation to business scale, and uncertainty in carbon price and the response of soil and vegetation carbon sequestration to management. This paper discusses opportunities for reducing emissions, improving emission intensity and carbon sequestration, and outlines the approach taken to achieve beef business engagement and practice change. The paper concludes with some considerations for policy makers.
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In 2014, the Australian Government implemented the Emissions Reduction Fund to offer incentives for businesses to reduce greenhouse gas (GHG) emissions by following approved methods. Beef cattle businesses in northern Australia can participate by applying the 'reducing GHG emissions by feeding nitrates to beef cattle' methodology and the 'beef cattle herd management' methods. The nitrate (NO3) method requires that each baseline area must demonstrate a history of urea use. Projects earn Australian carbon credit units (ACCU) for reducing enteric methane emissions by substituting NO3 for urea at the same amount of fed nitrogen. NO3 must be fed in the form of a lick block because most operations do not have labour or equipment to manage daily supplementation. NO3 concentrations, after a 2-week adaptation period, must not exceed 50 g NO3/adult animal equivalent per day or 7 g NO3/kg dry matter intake per day to reduce the risk of NO3 toxicity. There is also a 'beef cattle herd management' method, approved in 2015, that covers activities that improve the herd emission intensity (emissions per unit of product sold) through change in the diet or management. The present study was conducted to compare the required ACCU or supplement prices for a 2% return on capital when feeding a low or high supplement concentration to breeding stock of either (1) urea, (2) three different forms of NO3 or (3) cottonseed meal (CSM), at N concentrations equivalent to 25 or 50 g urea/animal equivalent, to fasten steer entry to a feedlot (backgrounding), in a typical breeder herd on the coastal speargrass land types in central Queensland. Monte Carlo simulations were run using the software @risk, with probability functions used for (1) urea, NO3 and CSM prices, (2) GHG mitigation, (3) livestock prices and (4) carbon price. Increasing the weight of steers at a set turnoff month by feeding CSM was found to be the most cost-effective option, with or without including the offset income. The required ACCU prices for a 2% return on capital were an order of magnitude higher than were indicative carbon prices in 2015 for the three forms of NO3. The likely costs of participating in ERF projects would reduce the return on capital for all mitigation options. © CSIRO 2016.
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The routine analysis for quantization of organic acids and sugars are generally slow methods that involve the use and preparation of several reagents, require trained professional, the availability of special equipment and is expensive. In this context, it has been increasing investment in research whose purpose is the development of substitutive methods to reference, which are faster, cheap and simple, and infrared spectroscopy have been highlighted in this regard. The present study developed multivariate calibration models for the simultaneous and quantitative determination of ascorbic acid, citric, malic and tartaric and sugars sucrose, glucose and fructose, and soluble solids in juices and fruit nectars and classification models for ACP. We used methods of spectroscopy in the near infrared (Near Infrared, NIR) in association with the method regression of partial least squares (PLS). Were used 42 samples between juices and fruit nectars commercially available in local shops. For the construction of the models were performed with reference analysis using high-performance liquid chromatography (HPLC) and refractometry for the analysis of soluble solids. Subsequently, the acquisition of the spectra was done in triplicate, in the spectral range 12500 to 4000 cm-1. The best models were applied to the quantification of analytes in study on natural juices and juice samples produced in the Paraná Southwest Region. The juices used in the application of the models also underwent physical and chemical analysis. Validation of chromatographic methodology has shown satisfactory results, since the external calibration curve obtained R-square value (R2) above 0.98 and coefficient of variation (%CV) for intermediate precision and repeatability below 8.83%. Through the Principal Component Analysis (PCA) was possible to separate samples of juices into two major groups, grape and apple and tangerine and orange, while for nectars groups separated guava and grape, and pineapple and apple. Different validation methods, and pre-processes that were used separately and in combination, were obtained with multivariate calibration models with average forecast square error (RMSEP) and cross validation (RMSECV) errors below 1.33 and 1.53 g.100 mL-1, respectively and R2 above 0.771, except for malic acid. The physicochemical analysis enabled the characterization of drinks, including the pH working range (variation of 2.83 to 5.79) and acidity within the parameters Regulation for each flavor. Regression models have demonstrated the possibility of determining both ascorbic acids, citric, malic and tartaric with successfully, besides sucrose, glucose and fructose by means of only a spectrum, suggesting that the models are economically viable for quality control and product standardization in the fruit juice and nectars processing industry.
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Solution-grown colloidal nanocrystal (NC) materials represent ideal candidates for optoelectronic devices, due to the flexibility with which they can be synthesized, the ease with which they can be processed for devicefabrication purposes and, foremost, for their excellent and size-dependent tunable optical properties, such as high photoluminescence (PL) quantum yield, color purity, and broad absorption spectra up to the near infrared. The advent of surfactant-assisted synthesis of thermodynamically stable colloidal solutions of NCs has led to peerless results in terms of uniform size distribution, composition, rational shape-design and the possibility of building heterostructured NCs (HNCs) comprising two or more different materials joined together. By tailoring the composition, shape and size of each component, HNCs with gradually higher levels of complexity have been conceived and realized, which are endowed with outstanding characteristics and optoelectronic properties. In this review, we discuss recent advances in the design of HNCs for efficient light-emitting diodes (LEDs) and photovoltaic (PV) solar cell devices. In particular, we will focus on the materials required to obtain superior optoelectronic quality and efficient devices, as well as their preparation and processing potential and limitations