914 resultados para FT-IR ATR


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In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1% - 78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R2 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R2 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain.

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FLOWERING LOCUS T (FT) and CENTRORADIALIS (CEN) homologs have been implicated in regulation of growth, determinacy and flowering. The roles of kiwifruit FT and CEN were explored using a combination of expression analysis, protein interactions, response to temperature in high-chill and low-chill kiwifruit cultivars and ectopic expression in Arabidopsis and Actinidia. The expression and activity of FT was opposite from that of CEN and incorporated an interaction with a FLOWERING LOCUS D (FD)-like bZIP transcription factor. Accumulation of FT transcript was associated with plant maturity and particular stages of leaf, flower and fruit development, but could be detected irrespective of the flowering process and failed to induce precocious flowering in transgenic kiwifruit. Instead, transgenic plants demonstrated reduced growth and survival rate. Accumulation of FT transcript was detected in dormant buds and stem in response to winter chilling. In contrast, FD in buds was reduced by exposure to cold. CEN transcript accumulated in developing latent buds, but declined before the onset of dormancy and delayed flowering when ectopically expressed in kiwifruit. Our results suggest roles for FT, CEN and FD in integration of developmental and environmental cues that affect dormancy, budbreak and flowering in kiwifruit.

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This study investigates if and why assessing relevance of clinical records for a clinical retrieval task is cognitively demanding. Previous research has highlighted the challenges and issues information retrieval systems are faced with when determining the relevance of documents in this domain, e.g., the vocabulary mismatch problem. Determining if this assessment imposes cognitive load on human assessors, and why this is the case, may shed lights on what are the (cognitive) processes that assessors use for determining document relevance (in this domain). High cognitive load may impair the ability of the user to make accurate relevance judgements and hence the design of IR mechanisms may need to take this into account in order to reduce the load.

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A common measure of the economic performance of different fleet segments in fisheries is the rate of return on capital. However, in the English Channel (UK), observed changes in the fleet structure are at odds with expectations given the observed rates of return on capital. This disjunction between expected and observed behaviour raises the question as to the appropriateness of rate of return on capital as a measure of economic performance for small boats whose main input is often non-wage labour. In this paper, an alternative performance indicator is developed based on returns on owner-operator labour. This indicator appears to be of more relevance to small scale boats than the traditional returns on capital, and a better indicator of the direction of adjustment in the fishery.

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The influence of graphene oxide (GO) and its surface oxidized debris (OD) on the cure chemistry of an amine cured epoxy resin has been investigated by Fourier Transform Infrared Emission Spectroscopy (FT-IES) and Differential Scanning Calorimetry (DSC). Spectral analysis of IR radiation emitted at the cure temperature from thin films of diglycidyl ether of bisphenol A epoxy resin (DGEBA) and 4,4'-diaminodiphenylmethane (DDM) curing agent with and without GO allowed the cure kinetics of the interphase between the bulk resin and GO to be monitored in real time, by measuring both the consumption of primary (1°) amine and epoxy groups, formation of ether groups as well as computing the profiles for formation of secondary (2°) and tertiary (3°) amines. OD was isolated from as-produced GO (aGO) by a simple autoclave method to give OD-free autoclaved GO (acGO). It has been found that the presence of OD on the GO prevents active sites on GO surfaces fully catalysing and participating in the reaction of DGEBA with DDM, which results in slower reaction and a lower crosslink density of the three-dimensional networks in the aGO-resin interphase compared to the acGO-resin interphase. We also determined that OD itself promoted DGEBA homopolymerization. A DSC study further confirmed that the aGO nanocomposite exhibited lower Tg while acGO nanocomposite showed higher Tg compared to neat resin because of the difference in crosslink densities of the matrix around the different GOs.

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An oxovanadium(IV) complex of dipyridophenazine, as a potent metal-based PDT agent, shows efficient DNA photocleavage activity at near-IR region and high photocytotoxicity in both UV-A and visible light in HeLa cells.

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BACKGROUND: The inability to consistently guarantee internal quality of horticulture produce is of major importance to the primary producer, marketers and ultimately the consumer. Currently, commercial avocado maturity estimation is based on the destructive assessment of percentage dry matter (%DM), and sometimes percentage oil, both of which are highly correlated with maturity. In this study the utility of Fourier transform (FT) near-infrared spectroscopy (NIRS) was investigated for the first time as a non-invasive technique for estimating %DM of whole intact 'Hass' avocado fruit. Partial least squares regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. RESULTS: It was found that combining three harvests (early, mid and late) from a single farm in the major production district of central Queensland yielded a predictive model for %DM with a coefficient of determination for the validation set of 0.76 and a root mean square error of prediction of 1.53% for DM in the range 19.4-34.2%. CONCLUSION: The results of the study indicate the potential of FT-NIRS in diffuse reflectance mode to non-invasively predict %DM of whole 'Hass' avocado fruit. When the FT-NIRS system was assessed on whole avocados, the results compared favourably against data from other NIRS systems identified in the literature that have been used in research applications on avocados.

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X-ray and IR studies on Nasicon solid solutions, Na1+xZr2SixP3−xO12, are carried out as a function of composition x. X-ray diffraction studies show that the unit cell volume increases as x increases and exhibits a maximum at x ≈ 2. On further increase in x the unit cell volume decreases. The infrared absorption peak positions and the splitting of these absorption peaks suggest a distortion of the PO4 and SiO4 tetrahedra. But the distortion is not large enough to change the local symmetry around the phosphorus or silicon ion from Td to C3v.

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Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The R-v(2) and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but <= 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of R-v(2) = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation. Crown Copyright (c) 2012 Published by Elsevier B.V. All rights reserved.

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Our present-day understanding of fundamental constituents of matter and their interactions is based on the Standard Model of particle physics, which relies on quantum gauge field theories. On the other hand, the large scale dynamical behaviour of spacetime is understood via the general theory of relativity of Einstein. The merging of these two complementary aspects of nature, quantum and gravity, is one of the greatest goals of modern fundamental physics, the achievement of which would help us understand the short-distance structure of spacetime, thus shedding light on the events in the singular states of general relativity, such as black holes and the Big Bang, where our current models of nature break down. The formulation of quantum field theories in noncommutative spacetime is an attempt to realize the idea of nonlocality at short distances, which our present understanding of these different aspects of Nature suggests, and consequently to find testable hints of the underlying quantum behaviour of spacetime. The formulation of noncommutative theories encounters various unprecedented problems, which derive from their peculiar inherent nonlocality. Arguably the most serious of these is the so-called UV/IR mixing, which makes the derivation of observable predictions especially hard by causing new tedious divergencies, to which our previous well-developed renormalization methods for quantum field theories do not apply. In the thesis I review the basic mathematical concepts of noncommutative spacetime, different formulations of quantum field theories in the context, and the theoretical understanding of UV/IR mixing. In particular, I put forward new results to be published, which show that also the theory of quantum electrodynamics in noncommutative spacetime defined via Seiberg-Witten map suffers from UV/IR mixing. Finally, I review some of the most promising ways to overcome the problem. The final solution remains a challenge for the future.

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Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

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High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.