Insights on the Milky Way bulge formation from the correlations between kinematics and metallicity

Context. Two main scenarios for the formation of the Galactic bulge are invoked, the first one through gravitational collapse or hierarchical merging of subclumps, the second through secular evolution of the Galactic disc. Aims. We aim to constrain the formation of the Galactic bulge through studies of the correlation between kinematics and metallicities in Baade's Window (l = 1 degrees, b = -4 degrees) and two other fields along the bulge minor axis (l = 0 degrees, b = -6 degrees and b = -12 degrees). Methods. We combine the radial velocity and the [Fe/H] measurements obtained with FLAMES/GIRAFFE at the VLT with a spectral resolution of R = 20 000, plus for the Baade's Window field the OGLE-II proper motions, and compare these with published N-body simulations of the Galactic bulge. Results. We confirm the presence of two distinct populations in Baade's Window found in Hill et al. (2010, A&A, submitted): the metal-rich population presents bar-like kinematics while the metal-poor population shows kinematics corresponding to an old spheroid or a thick disc. In this context the metallicity gradient along the bulge minor axis observed by Zoccali et al. (2008, A&A, 486, 177), visible also in the kinematics, can be related to a varying mix of these two populations as one moves away from the Galactic plane, alleviating the apparent contradiction between the kinematic evidence of a bar and the existence of a metallicity gradient. Conclusions. We show evidence that the two main scenarios for the bulge formation co-exist within the Milky Way bulge.

Li-rich red giant branch stars in the Galactic bulge

Aims. We present lithium abundance determination for a sample of K giant stars in the Galactic bulge. The stars presented here are the only 13 stars with a detectable lithium line (6767.18 angstrom) among similar to 400 stars for which we have spectra in this wavelength range, half of them in Baade's Window (b = -4 degrees) and half in a field at b = -6 degrees. Methods. The stars were observed with the GIRAFFE spectrograph of FLAMES mounted on VLT, with a spectral resolution of R similar to 20 000. Abundances were derived from spectral synthesis and the results are compared with those of stars with similar parameters, but no detectable Li line. Results. We find 13 stars with a detectable Li line, among which 2 have abundances A(Li) > 2.7. No clear correlations were found between the Li abundance and those of other elements. With the exception of the two most Li rich stars, the others follow a fairly tight A(Li) - T(eff) correlation. Conclusions. There is strong indication of a Li production phase during the red giant branch (RGB), acting either on a very short timescale, or selectively only in some stars. That the proposed Li production phase is associated with the RGB bump cannot be excluded, although our targets are significantly brighter than the predicted RGB bump magnitude for a population at 8 kpc.

Simultaneous steady state and dynamic design of process systems using structural indicators

The simultaneous design of the steady-state and dynamic performance of a process has the ability to satisfy much more demanding dynamic performance criteria than the design of dynamics only by the connection of a control system. A method for designing process dynamics based on the use of a linearised systems' eigenvalues has been developed. The eigenvalues are associated with system states using the unit perturbation spectral resolution (UPSR), characterising the dynamics of each state. The design method uses a homotopy approach to determine a final design which satisfies both steady-state and dynamic performance criteria. A highly interacting single stage forced circulation evaporator system, including control loops, was designed by this method with the goal of reducing the time taken for the liquid composition to reach steady-state. Initially the system was successfully redesigned to speed up the eigenvalue associated with the liquid composition state, but this did not result in an improved startup performance. Further analysis showed that the integral action of the composition controller was the source of the limiting eigenvalue. Design changes made to speed up this eigenvalue did result in an improved startup performance. The proposed approach provides a structured way to address the design-control interface, giving significant insight into the dynamic behaviour of the system such that a systematic design or redesign of an existing system can be undertaken with confidence.

A methodology for current density calculations in high-frequency RF resonators

As nuclear magnetic resonance imaging and spectroscopy move inexorably toward higher field-strength magnets in search of improved signal-to-noise ratio, spectral resolution, and spatial resolution, the way in which radiofrequency (RF) probes are designed changes. At higher frequencies, resonant cavities become the favored RF ''coil'' type and may be built using streamline elements to reduce the inductance of the system. In modeling such systems, the quasi-static approach of assuming that current flows evenly in all conductor cross sections and that adjacent conductors do not affect each other becomes less reasonable. The proximity of RF conductors in resonators typically causes RF eddy currents to flow, whereby the current density in each rung is altered by the RF fields generated by nearby conductors. The proper understanding and prediction of how resonators will perform require a model of the current densities flowing in conducting sections, including all RF eddy current effects. Very few models of this type have been presented in the literature. This article presents an overview of one such model and of how it may be applied to a variety of resonators, both shielded and unshielded, circular, and elliptical, in cross section. Results are presented from a shielded head coil operating at 2 tesla. (C) 1997 John Wiley & Sons, Inc.

Implementação em hardware reconfigurável de método de separação de dados hiperespetrais

Relatório do Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

A first analysis of the atmospheric measurements from TANSO/GOSAT

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau em Mestre em Engenharia Física

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

System-on-chip field-programmable gate array design for onboard real-time hyperspectral unmixing

Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.

Biometric recognition system using low bandwidth ECG signals

Biometric recognition has recently emerged as part of applications where the privacy of the information is crucial, as in the health care field. This paper presents a biometric recognition system based on the Electrocardiographic signal (ECG). The proposed system is based on a state-of-the-art recognition method which extracts information from the frequency domain. In this paper we propose a new method to increase the spectral resolution of low bandwidth ECG signals due to the limited bandwidth of the acquisition sensor. Preliminary results show that the proposed scheme reveals a higher identification rate and lower equal error rate when compared to previous approaches.

Application of Continuous Wavelet Transform to the Analysis of the Modulus of the Fractional Fourier Transform Bands for Resolving Two Component Mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

Compartmentalized Cerebral Metabolism of [1,6-(13)C]Glucose Determined by in vivo (13)C NMR Spectroscopy at 14.1 T.

Cerebral metabolism is compartmentalized between neurons and glia. Although glial glycolysis is thought to largely sustain the energetic requirements of neurotransmission while oxidative metabolism takes place mainly in neurons, this hypothesis is matter of debate. The compartmentalization of cerebral metabolic fluxes can be determined by (13)C nuclear magnetic resonance (NMR) spectroscopy upon infusion of (13)C-enriched compounds, especially glucose. Rats under light α-chloralose anesthesia were infused with [1,6-(13)C]glucose and (13)C enrichment in the brain metabolites was measured by (13)C NMR spectroscopy with high sensitivity and spectral resolution at 14.1 T. This allowed determining (13)C enrichment curves of amino acid carbons with high reproducibility and to reliably estimate cerebral metabolic fluxes (mean error of 8%). We further found that TCA cycle intermediates are not required for flux determination in mathematical models of brain metabolism. Neuronal tricarboxylic acid cycle rate (V(TCA)) and neurotransmission rate (V(NT)) were 0.45 ± 0.01 and 0.11 ± 0.01 μmol/g/min, respectively. Glial V(TCA) was found to be 38 ± 3% of total cerebral oxidative metabolism, accounting for more than half of neuronal oxidative metabolism. Furthermore, glial anaplerotic pyruvate carboxylation rate (V(PC)) was 0.069 ± 0.004 μmol/g/min, i.e., 25 ± 1% of the glial TCA cycle rate. These results support a role of glial cells as active partners of neurons during synaptic transmission beyond glycolytic metabolism.

Which prior knowledge? Quantification of in vivo brain 13C MR spectra following 13C glucose infusion using AMARES.

The recent developments in high magnetic field 13C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of 13C in vivo spectra in the rodent brain, enabling the separation of several 13C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the 13C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to 13 C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13)C2 ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo 13C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo 13C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo 13C spectra. AMARES led to accurate and reliable 13C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different 13C isotopomers were included as prior knowledge in the analysis.

MR spectroscopy of the human brain with enhanced signal intensity at ultrashort echo times on a clinical platform at 3T and 7T.

Recently, the spin-echo full-intensity acquired localized (SPECIAL) spectroscopy technique was proposed to unite the advantages of short TEs on the order of milliseconds (ms) with full sensitivity and applied to in vivo rat brain. In the present study, SPECIAL was adapted and optimized for use on a clinical platform at 3T and 7T by combining interleaved water suppression (WS) and outer volume saturation (OVS), optimized sequence timing, and improved shimming using FASTMAP. High-quality single voxel spectra of human brain were acquired at TEs below or equal to 6 ms on a clinical 3T and 7T system for six volunteers. Narrow linewidths (6.6 +/- 0.6 Hz at 3T and 12.1 +/- 1.0 Hz at 7T for water) and the high signal-to-noise ratio (SNR) of the artifact-free spectra enabled the quantification of a neurochemical profile consisting of 18 metabolites with Cramér-Rao lower bounds (CRLBs) below 20% at both field strengths. The enhanced sensitivity and increased spectral resolution at 7T compared to 3T allowed a two-fold reduction in scan time, an increased precision of quantification for 12 metabolites, and the additional quantification of lactate with CRLB below 20%. Improved sensitivity at 7T was also demonstrated by a 1.7-fold increase in average SNR (= peak height/root mean square [RMS]-of-noise) per unit-time.