110 resultados para Spectroscopic parameters


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The method of distributing the outdoor air in classrooms has a major impact on indoor air quality and thermal comfort of pupils. In a previous study, ([11] Karimipanah T, Sandberg M, Awbi HB. A comparative study of different air distribution systems in a classroom. In: Proceedings of Roomvent 2000, vol. II, Reading, UK, 2000. p. 1013-18; [13] Karimipanah T, Sandberg M, Awbi HB, Blomqvist C. Effectiveness of confluent jets ventilation system for classrooms. In: Idoor Air 2005, Beijing, China, 2005 (to be presented).) presented results for four and two types of air distribution systems tested in a purpose built classroom with simulated occupancy as well as computational fluid dynamics (CFD) modelling. In this paper, the same experimental setup has been used to investigate the indoor environment in the classroom using confluent jet ventilation, see also ([12]Cho YJ, Awbi HB, Karimipanah T. The characteristics of wall confluent jets for ventilated enclosures. In: Proceedings of Roomvent 2004, Coimbra, Portugal, 2004.) Measurements of air speed, air temperature and tracer gas concentrations have been carried out for different thermal conditions. In addition, 56 cases of CFD simulations have been carried to provide additional information on the indoor air quality and comfort conditions throughout the classroom, such as ventilation effectiveness, air exchange effectiveness, effect of flow rate, effect of radiation, effect of supply temperature, etc., and these are compared with measured data.

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Until recently, there has been little investigation concerning the poor indoor air quality (IAQ) in classrooms. Despite the evidence that the educational building systems in many of the UK institutions have significant defects that may degrade IAQ, systematic assessments of IAQ measurements has been rarely undertaken. When undertaking IAQ measurement, there is a difficult task of representing and characterizing the environment parameters. Although technologies exist to measure these parameters, direct measurements especially in a naturally ventilated spaces are often difficult. This paper presents a methodology for developing a method to characterize indoor environment flow parameters as well as the Carbon Dioxide (CO2) concentrations. Thus, CO2 concentration level can be influenced by the differences in the selection of sampling points and heights. However, because this research focuses on natural ventilation in classrooms, air exchange is provided mainly by air infiltration. It is hoped that the methodology developed and evaluated in this research can effectively simplify the process of estimating the parameters for a systematic assessment of IAQ measurements in a naturally ventilated classrooms.

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The temperature-time profiles of 22 Australian industrial ultra-high-temperature (UHT) plants and 3 pilot plants, using both indirect and direct heating, were surveyed. From these data, the operating parameters of each plant, the chemical index C*, the bacteriological index B* and the predicted changes in the levels of beta-lactoglobulin, alpha-lactalbumin, lactulose, furosine and browning were determined using a simulation program based on published formulae and reaction kinetics data. There was a wide spread of heating conditions used, some of which resulted in a large margin of bacteriological safety and high chemical indices. However, no conditions were severe enough to cause browning during processing. The data showed a clear distinction between the indirect and direct heating plants. They also indicated that degree of denaturation of alpha-lactalbumin varied over a wide range and may be a useful discriminatory index of heat treatment. Application of the program to pilot plants illustrated its value in determining processing conditions in these plants to simulate the conditions in industrial UHT plants. (C) 2008 Elsevier Ltd. All rights reserved.

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A combined mathematical model for predicting heat penetration and microbial inactivation in a solid body heated by conduction was tested experimentally by inoculating agar cylinders with Salmonella typhimurium or Enterococcus faecium and heating in a water bath. Regions of growth where bacteria had survived after heating were measured by image analysis and compared with model predictions. Visualisation of the regions of growth was improved by incorporating chromogenic metabolic indicators into the agar. Preliminary tests established that the model performed satisfactorily with both test organisms and with cylinders of different diameter. The model was then used in simulation studies in which the parameters D, z, inoculum size, cylinder diameter and heating temperature were systematically varied. These simulations showed that the biological variables D, z and inoculum size had a relatively small effect on the time needed to eliminate bacteria at the cylinder axis in comparison with the physical variables heating temperature and cylinder diameter, which had a much greater relative effect. (c) 2005 Elsevier B.V All rights reserved.

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An atoxigenic strain of Penicillium camemberti was superficially inoculated on fermented sausages in an attempt to improve their sensory properties. The growth of this mould on the surface of the sausages resulted in an intense proteolysis and lipolysis, which caused an increase in the concentration of free amino acids, free fatty acids (FFA) and volatile compounds. Many of these were derived from amino acid catabolism and were responsible for the "ripened flavour", i.e. branched aldehydes and the corresponding alcohols, acids and esters. The development of the fungal mycelia on the surface of the sausages also protected lipids from oxidation, resulting in both lower 2-thiobarbituric acid (TBARS) values and lipid oxidation-derived compounds, such as aliphatic aldehydes and alcohols. The sensory analysis of superficially inoculated sausages showed clear improvements in odour and flavour and, as a consequence, in the overall quality of the sausages. Therefore, this strain is proposed as a potential starter culture for dry fermented sausage production. (C) 2002 Elsevier Science B.V All rights reserved.

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In this paper new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with regularised orthogonal least squares algorithm respectively. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalisation scheme in orthogonal least squares or regularised orthogonal least squares has been extended such that the new algorithms are computationally efficient. A numerical example is included to demonstrate effectiveness of the algorithms. Copyright (C) 2003 IFAC.

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Hidden Markov Models (HMMs) have been successfully applied to different modelling and classification problems from different areas over the recent years. An important step in using HMMs is the initialisation of the parameters of the model as the subsequent learning of HMM’s parameters will be dependent on these values. This initialisation should take into account the knowledge about the addressed problem and also optimisation techniques to estimate the best initial parameters given a cost function, and consequently, to estimate the best log-likelihood. This paper proposes the initialisation of Hidden Markov Models parameters using the optimisation algorithm Differential Evolution with the aim to obtain the best log-likelihood.

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We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class classifiers in terms of performance and computational efficiency.

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The alignment of model amyloid peptide YYKLVFFC is investigated in bulk and at a solid surface using a range of spectroscopic methods employing polarized radiation. The peptide is based on a core sequence of the amyloid beta (A beta) peptide, KLVFF. The attached tyrosine and cysteine units are exploited to yield information on alignment and possible formation of disulfide or dityrosine links. Polarized Raman spectroscopy on aligned stalks provides information on tyrosine orientation, which complements data from linear dichroism (LD) on aqueous solutions subjected to shear in a Couette cell. LD provides a detailed picture of alignment of peptide strands and aromatic residues and was also used to probe the kinetics of self-assembly. This suggests initial association of phenylalanine residues, followed by subsequent registry of strands and orientation of tyrosine residues. X-ray diffraction (XRD) data from aligned stalks is used to extract orientational order parameters from the 0.48 nm reflection in the cross-beta pattern, from which an orientational distribution function is obtained. X-ray diffraction on solutions subject to capillary flow confirmed orientation in situ at the level of the cross-beta pattern. The information on fibril and tyrosine orientation from polarized Raman spectroscopy is compared with results from NEXAFS experiments on samples prepared as films on silicon. This indicates fibrils are aligned parallel to the surface, with phenyl ring normals perpendicular to the surface. Possible disulfide bridging leading to peptide dimer formation was excluded by Raman spectroscopy, whereas dityrosine formation was probed by fluorescence experiments and was found not to occur except under alkaline conditions. Congo red binding was found not to influence the cross-beta XRD pattern.

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Pine beauty moth (Panolis flammea D&S, Lepidoptera: Noctuidae) were reared individually from egg hatch to pupation on one of three host plants, Pinus sylvestris (native host plant), Pinus contorta (Central Interior seed origin - good quality introduced host) and P. contorta (Alaskan seed origin - poor quality introduced host). After emerging from the pupae the adult moths were confined to a Skeena River seed origin of P. contorta. Female pupal weight and adult life span were significantly higher on P. sylvestris than on the two lodgepole pine seed origins. Development time was, however, not significantly different between treatments, but larval mean relative growth rate was found to be negatively correlated with birth weight and positively correlated with pupal weight. The time to emerge from the pupa was also not significantly different between treatments. However, there were marked differences between the genders. Male moths lost a significantly greater proportion of their weight over the pupal stage but lived significantly longer as adults than the females. Female moths emerged from the pupal stage significantly sooner than male moths. There was no apparent advantage of lai-ge birth size when looked at in terms of subsequent performance. These results are discussed in light of current life history theory.

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A series of half-sandwich bis(phosphine) ruthenium acetylide complexes [Ru(C CAr)(L-2)Cp'] (Ar = phenyl, p-tolyl, 1-naphthyl, 9-anthryl; L2 = (PPh3)(2), Cp' = Cp; L-2 = dppe; Cp' = Cp*) have been examined using electrochemical and spectroelectrochemical methods. One-electron oxidation of these complexes gave the corresponding radical cations [Ru(C CAr)(L2)Cp'](+). Those cations based on Ru(dppe)Cp*, or which feature a para-tolyl acetylide substituent, are more chemically robust than examples featuring the Ru(PPh3)(2)Cp moiety, permitting good quality UV-Vis-NIR and IR spectroscopic data to be obtained using spectroelectrochemical methods. On the basis of TD DFT calculations, the low energy (NIR) absorption bands in the experimental electronic spectra for most of these radical cations are assigned to transitions between the beta-HOSO and beta-LUSO, both of which have appreciable metal d and ethynyl pi character. However, the large contribution from the anthryl moiety to the frontier orbitals of [Ru(C CC14H9)(L2)CP'](+) suggests compounds containing this moiety should be described as metal-stabilised anthryl radical cations.

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The lowest allowed electronic transition of fac-[Re(Cl)(CO)(3)(bopy)(2)] (bopy = 4-benzoylpyridine) has a Re --> bopy MLCT character, as revealed by UV-vis and stationary resonance Raman spectroscopy. Accordingly, the lowest-lying, long-lived, excited state is Re --> bopy (MLCT)-M-3. Electronic depopulation of the Re(CO)(3) unit and population of a bopy pi* orbital upon excitation are evident by the upward shift of v(Cequivalent toO) vibrations and a downward shift of the ketone v(C=O) vibration, respectively, seen in picosecond time-resolved IR spectra. Moreover, reduction of a single bopy ligand in the (MLCT)-M-3 excited state is indicated by time-resolved visible and resonance Raman (TR3) spectra that show features typical of bopy(.-). In contrast, the lowest allowed electronic transition and lowest-lying excited state of a new complex fac-[Re(bopy)(CO)(3)(bpy)](+) (bpy = 2,2'-bipyridine) have been identified as Re --> bpy MLCT with no involvement of the bopy ligand, despite the fact that the first reduction of this complex is bopy-localized, as was proven spectroelectrochemically. This is a rare case in which the localizations of the lowest MLCT excitation and the first reduction are different. (MLCT)-M-3 excited states of both fac-[Re(Cl)(CO)(3)(bopy)(2)] and fac-[Re(bopy)(CO)(3)(bpy)](+) are initially formed vibrationally hot. Their relaxation is manifested by picosecond dynamic shifts of v(Cequivalent toO) IR bands. The X-ray structure of fac-[Re(bopy)(CO)(3)(bpy)](PF6CH3CN)-C-. has been determined.

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Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.