Resistance spectra of six elite breeding lines of upland rice to Pyricularia grisea

The objective of this work was to evaluate the resistance spectra of six elite breeding lines of rice, developed for improved yield and grain quality, in inoculation tests in the greenhouse and in the field. Forty-six isolates of Pyricularia grisea collected from the cultivar Primavera, 31 from the cultivar Maravilha and 19 from six elite breeding lines, totaling 96 were utilized for inoculations. Out of 11 international and 15 Brazilian pathotypes, IC-1, IB-9, and BD-16, respectively, were identified as most frequent isolates collected from the cultivar Primavera. The isolates retrieved from Maravilha belong to four international and 11 Brazilian pathotypes, the predominant ones being IB-9 and IB-49 and BB-1 and BB-21, respectively. Lines CNAs 8711 and CNAs 8983 showed resistant reaction to all test isolates from Maravilha, while CNAs 8983 was susceptible to three isolates of Primavera pertaining to the pathotype IC-1. A majority of isolates exhibiting compatible reaction to Primavera were incompatible to Maravilha and vice-versa.Field assessment of rice blast utilizing the area under disease progress curve as a criterion for measuring disease severity showed significant differences among the six breeding lines. The isolates of P. grisea exhibiting differential reaction on breeding lines can be utilized in pyramiding resistance genes in new upland rice cultivars.

Detecting the oxidative reactivity of nanoparticles: a new protocol for reducing artifacts

Understanding the oxidative reactivity of nanoparticles (NPs; <100 nm) could substantially contribute to explaining their toxicity. We attempted to refine the use of 2′7-dichlorodihydrofluorescein (DCFH) to characterize NP generation of reactive oxygen species (ROS). Several fluorescent probes have been applied to testing oxidative reactivity, but despite DCFH being one of the most popular for the detection of ROS, when it has been applied to NPs there have been an unexplainably wide variability in results. Without a uniform methodology, validating even robust results is impossible. This study, therefore, identified sources of conflicting results and investigated ways of reducing occurrence of artificial results. Existing techniques were tested and combined (using their most desirable features) to form a more reliable method for the measurement of NP reactivity in aqueous dispersions. We also investigated suitable sample ranges necessary to determine generation of ROS. Specifically, ultrafiltration and time-resolved scan absorbance spectra were used to study possible optical interference when using high sample concentrations. Robust results were achieved at a 5 µM DCFH working solution with 0.5 unit/mL horseradish peroxidase (HRP) dissolved in ethanol. Sonication in DCFH-HRP working solution provided more stable data with a relatively clean background. Optimal particle concentration depends on the type of NP and in general was in the µg/mL range. Major reasons for previously reported conflicting results due to interference were different experimental approaches and NP sample concentrations. The protocol presented here could form the basis of a standardized method for applying DCFH to detect generation of ROS by NPs.

In vivo time-resolved spectroscopy of the human bronchial early cancer autofluorescence.

Time-resolved measurements of tissue autofluorescence (AF) excited at 405 nm were carried out with an optical-fiber-based spectrometer in the bronchi of 11 patients. The objectives consisted of assessing the lifetime as a new tumor/normal (T/N) tissue contrast parameter and trying to explain the origin of the contrasts observed when using AF-based cancer detection imaging systems. No significant change in the AF lifetimes was found. AF bronchoscopy performed in parallel with an imaging device revealed both intensity and spectral contrasts. Our results suggest that the spectral contrast might be due to an enhanced blood concentration just below the epithelial layers of the lesion. The intensity contrast probably results from the thickening of the epithelium in the lesions. The absence of T/N lifetime contrast indicates that the quenching is not at the origin of the fluorescence intensity and spectral contrasts. These lifetimes (6.9 ns, 2.0 ns, and 0.2 ns) were consistent for all the examined sites. The fact that these lifetimes are the same for different emission domains ranging between 430 and 680 nm indicates that there is probably only one dominant fluorophore involved. The measured lifetimes suggest that this fluorophore is elastin.

Wigner higher-order spectra: definition, properties, computation and application to transient signal analysis

The Wigner higher order moment spectra (WHOS)are defined as extensions of the Wigner-Ville distribution (WD)to higher order moment spectra domains. A general class oftime-frequency higher order moment spectra is also defined interms of arbitrary higher order moments of the signal as generalizations of the Cohen’s general class of time-frequency representations. The properties of the general class of time-frequency higher order moment spectra can be related to theproperties of WHOS which are, in fact, extensions of the properties of the WD. Discrete time and frequency Wigner higherorder moment spectra (DTF-WHOS) distributions are introduced for signal processing applications and are shown to beimplemented with two FFT-based algorithms. One applicationis presented where the Wigner bispectrum (WB), which is aWHOS in the third-order moment domain, is utilized for thedetection of transient signals embedded in noise. The WB iscompared with the WD in terms of simulation examples andanalysis of real sonar data. It is shown that better detectionschemes can be derived, in low signal-to-noise ratio, when theWB is applied.

Selecting Wavelet Filter for Compression of Spectra from Multispectral Images

The problem of selecting anappropriate wavelet filter is always present in signal compression based on thewavelet transform. In this report, we propose a method to select a wavelet filter from a predefined set of filters for the compression of spectra from a multispectral image. The wavelet filter selection is based on the Learning Vector Quantization (LVQ). In the training phase for the test images, the best wavelet filter for each spectrum has been found by a careful compression-decompression evaluation. Certain spectral features are used in characterizing the pixel spectra. The LVQ is used to form the best wavelet filter class for different types of spectra from multispectral images. When a new image is to be compressed, a set of spectra from that image is selected, the spectra are classified by the trained LVQand the filter associated to the largest class is selected for the compression of every spectrum from the multispectral image. The results show, that almost inevery case our method finds the most suitable wavelet filter from the pre-defined set for the compression.

Prediction of crude protein and classification of the growth stage of wheat plant samples from NIR spectra

Near-infrared spectroscopy (NIRS) was used to analyse the crude protein content of dried and milled samples of wheat and to discriminate samples according to their stage of growth. A calibration set of 72 samples from three growth stages of wheat (tillering, heading and harvest) and a validation set of 28 samples was collected for this purpose. Principal components analysis (PCA) of the calibration set discriminated groups of samples according to the growth stage of the wheat. Based on these differences, a classification procedure (SIMCA) showed a very accurate classification of the validation set samples : all of them were successfully classified in each group using this procedure when both the residual and the leverage were used in the classification criteria. Looking only at the residuals all the samples were also correctly classified except one of tillering stage that was assigned to both tillering and heading stages. Finally, the determination of the crude protein content of these samples was considered in two ways: building up a global model for all the growth stages, and building up local models for each stage, separately. The best prediction results for crude protein were obtained using a global model for samples in the two first growth stages (tillering and heading), and using a local model for the harvest stage samples.

Affinity distribution functions in multicomponent heterogeneous adsorption. Analytical inversion of isotherms to obtain affinity spectra

An analytical approach for the interpretation of multicomponent heterogeneous adsorption or complexation isotherms in terms of multidimensional affinity spectra is presented. Fourier transform, applied to analyze the corresponding integral equation, leads to an inversion formula which allows the computation of the multicomponent affinity spectrum underlying a given competitive isotherm. Although a different mathematical methodology is used, this procedure can be seen as the extension to multicomponent systems of the classical Sips’s work devoted to monocomponent systems. Furthermore, a methodology which yields analytical expressions for the main statistical properties (mean free energies of binding and covariance matrix) of multidimensional affinity spectra is reported. Thus, the level of binding correlation between the different components can be quantified. It has to be highlighted that the reported methodology does not require the knowledge of the affinity spectrum to calculate the means, variances, and covariance of the binding energies of the different components. Nonideal competitive consistent adsorption isotherm, widely used in metal/proton competitive complexation to environmental macromolecules, and Frumkin competitive isotherms are selected to illustrate the application of the reported results. Explicit analytical expressions for the affinity spectrum as well as for the matrix correlation are obtained for the NICCA case. © 2004 American Institute of Physics.

Investigation and data adaptive analysis of CARS spectra

In this diploma work advantages of coherent anti-Stokes Raman scattering spectrometry (CARS) and various methods of the quantitative analysis of substance structure with its help are considered. The basic methods and concepts of the adaptive analysis are adduced. On the basis of these methods the algorithm of automatic measurement of a scattering strip size of a target component in CARS spectrum is developed. The algorithm uses known full spectrum of target substance and compares it with a CARS spectrum. The form of a differential spectrum is used as a feedback to control the accuracy of matching. To exclude the influence of a background in CARS spectra the differential spectrum is analysed by means of its second derivative. The algorithm is checked up on the simulated simple spectra and on the spectra of organic compounds received experimentally.

Monte Carlo derivation of filtered tungsten anode X-ray spectra for dose computation in digital mammography

Abstract Objective: Derive filtered tungsten X-ray spectra used in digital mammography systems by means of Monte Carlo simulations. Materials and Methods: Filtered spectra for rhodium filter were obtained for tube potentials between 26 and 32 kV. The half-value layer (HVL) of simulated filtered spectra were compared with those obtained experimentally with a solid state detector Unfors model 8202031-H Xi R/F & MAM Detector Platinum and 8201023-C Xi Base unit Platinum Plus w mAs in a Hologic Selenia Dimensions system using a direct radiography mode. Results: Calculated HVL values showed good agreement as compared with those obtained experimentally. The greatest relative difference between the Monte Carlo calculated HVL values and experimental HVL values was 4%. Conclusion: The results show that the filtered tungsten anode X-ray spectra and the EGSnrc Monte Carlo code can be used for mean glandular dose determination in mammography.

Classifier combination for in vivo magnetic resonance spectra of brain tumours

Peer-reviewed

Classifier combination for in vivo magnetic resonance spectra of brain tumours

In this paper we present a multi-stage classifier for magnetic resonance spectra of human brain tumours which is being developed as part of a decision support system for radiologists. The basic idea is to decompose a complex classification scheme into a sequence of classifiers, each specialising in different classes of tumours and trying to reproducepart of the WHO classification hierarchy. Each stage uses a particular set of classification features, which are selected using a combination of classical statistical analysis, splitting performance and previous knowledge.Classifiers with different behaviour are combined using a simple voting scheme in order to extract different error patterns: LDA, decision trees and the k-NN classifier. A special label named "unknown¿ is used when the outcomes of the different classifiers disagree. Cascading is alsoused to incorporate class distances computed using LDA into decision trees. Both cascading and voting are effective tools to improve classification accuracy. Experiments also show that it is possible to extract useful information from the classification process itself in order to helpusers (clinicians and radiologists) to make more accurate predictions and reduce the number of possible classification mistakes.

Excitação eletrônica das moléculas de metacrilato de metila e estireno na região do ultravioleta de vácuo

Angle-resolved electron energy-loss spectra have been measured for the methyl methacrylate (MMA) and styrene molecules in the 0 - 50 eV energy range. The spectra have been obtained at 1 keV incident energy, with an energy resolution of 0.8 eV and covering an angular range of 2.0 to 7.0 degrees. Within our knowledge, this is the first gas-phase excitation spectrum for MMA and styrene in this energy range. The spectra of MMA at small scattering angles are dominated by an intense peak at 6.7 eV followed by a broad band centered at about 16 eV. In the case of styrene, six bands can be observed in the spectra. Based on the angular behaviour of the excitation spectra of these molecules, the low-lying peaks observed are considered to be associated predominantly with dipole-allowed processes. In both cases, new bands can be observed for excitation energies greater than 20 eV. This could be associated with dipole-forbidden transitions to shake-up and doubly-excited states.

Monte Carlo simulation of x-ray spectra generated by kilo-electron-volt electrons

We present a general algorithm for the simulation of x-ray spectra emitted from targets of arbitrary composition bombarded with kilovolt electron beams. Electron and photon transport is simulated by means of the general-purpose Monte Carlo code PENELOPE, using the standard, detailed simulation scheme. Bremsstrahlung emission is described by using a recently proposed algorithm, in which the energy of emitted photons is sampled from numerical cross-section tables, while the angular distribution of the photons is represented by an analytical expression with parameters determined by fitting benchmark shape functions obtained from partial-wave calculations. Ionization of K and L shells by electron impact is accounted for by means of ionization cross sections calculated from the distorted-wave Born approximation. The relaxation of the excited atoms following the ionization of an inner shell, which proceeds through emission of characteristic x rays and Auger electrons, is simulated until all vacancies have migrated to M and outer shells. For comparison, measurements of x-ray emission spectra generated by 20 keV electrons impinging normally on multiple bulk targets of pure elements, which span the periodic system, have been performed using an electron microprobe. Simulation results are shown to be in close agreement with these measurements.