ePix is a novel class of ASIC architectures, based on a common platform, optimized to build modular scalable detectors for LCLS. The platform architecture is composed of a random access analog matrix ...of pixel with global shutter, fast parallel column readout, and dedicated sigma-delta analog-to-digital converters per column. It also implements a dedicated control interface and all the required support electronics to perform configuration, calibration and readout of the matrix. Based on this platform a class of front-end ASICs and several camera modules, meeting different requirements, can be developed by designing specific pixel architectures. This approach reduces development time and expands the possibility of integration of detector modules with different size, shape or functionality in the same camera. The ePix platform is currently under development together with the first two integrating pixel architectures: ePix100 dedicated to ultra low noise applications and ePix10k for high dynamic range applications.
Maia X-ray Microprobe Detector Array System Siddons, D P; Kirkham, R; Ryan, C G ...
Journal of physics. Conference series,
01/2014, Letnik:
499, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Maia is an advanced system designed specifically for scanning x-ray fluorescence microprobe applications. It consists of a large array of photodiode detectors and associated signal processing, ...closely coupled to an FPGA-based control and analysis system. In this paper we will describe the architecture and construction of the system.
Silicon drift detectors (SDDs) revolutionized spectroscopy in fields as diverse as geology and dentistry. For a subset of experiments at ultrafast, X-ray free-electron lasers (FELs), SDDs can make ...substantial contributions. Often the unknown spectrum is interesting, carrying science data, or the background measurement is useful to identify unexpected signals. Many measurements involve only several discrete photon energies known a priori, allowing single-event decomposition of pile-up and spectroscopic photon counting. We designed a pulse function and demonstrated that the signal amplitude (i.e., proportional to the detected energy and obtained from fitting with the pulse function), rise time, and pulse height are interrelated, and at short peaking times, the pulse height and pulse area are not optimal estimators for detected energy; instead, the signal amplitude and rise time are obtained for each pulse by fitting, thus removing the need for pulse shaping. By avoiding pulse shaping, rise times of tens of nanoseconds resulted in reduced pulse pile-up and allowed decomposition of remaining pulse pile-up at photon separation times down to hundreds of nanoseconds while yielding time-of-arrival information with the precision of 10 ns. Waveform fitting yields simultaneously high energy resolution and high counting rates (two orders of magnitude higher than current digital pulse processors). At pulsed sources or high photon rates, photon pile-up still occurs. We showed that pile-up spectrum fitting is relatively simple and preferable to pile-up spectrum deconvolution. We developed a photon pile-up statistical model for constant intensity sources, extended it to variable intensity sources (typical for FELs), and used it to fit a complex pileup spectrum. We subsequently developed a Bayesian pile-up decomposition method that allows decomposing pile-up of single events with up to six photons from six monochromatic lines with 99% accuracy. The usefulness of SDDs will continue into the X-ray FEL era of science. Their successors, the ePixS hybrid pixel detectors, already offer hundreds of pixels, each with a similar performance to an SDD, in a compact, robust and affordable package.
Resumo O objetivo do presente artigo é estimar impactos da queda da arrecadação tributária para o financiamento da educação básica em virtude dos efeitos econômicos adversos da pandemia da COVID-19. ...Para tanto, são analisados três cenários hipotéticos de queda da arrecadação e seus efeitos para as receitas da educação nos estados e municípios, por meio de um modelo de previsão que combinou dados de receitas de impostos com receitas vinculadas a educação e matrículas. No cenário mais otimista, a redução da receita líquida de impostos de 7% implicaria um decréscimo dos recursos para educação básica de R$ 16,6 bilhões por ano. A receita aluno-mês, que, em 2018, foi de R$ 460,00 em média, poderia cair em proporções que variam entre 4,1% e 26,9%, a depender do cenário de redução e do contexto de cada município. Diante da previsível diminuição de recursos, são propostas medidas urgentes para atenuar o aprofundamento das desigualdades na educação, as quais convergem para a transferência de recursos da União aos governos subnacionais. Finalmente ressalta-se o papel virtuoso do investimento na educação, dada a capilaridade desta e o seu caráter intensivo em pessoal.
Abstract This article aims to estimate the impact of lower tax revenues on the funding of basic education, in the context of the economic impact of the COVID-19 pandemic. Three hypothetical scenarios of lowering tax revenues are estimated and analyzed, along with their effects on the investment in education in the states and municipalities, per-pupil and overall, using a methodology that combines data on tax revenues, mandatory allocation in education, and enrollment numbers. In the most optimistic scenario, the reduction of 7% in the net tax revenues would lead to a decrease in investment in basic education of more than R$ 16.6 billion. The monthly per-pupil expenditure, which in 2018 was R$ 460 on average, could drop between 4.1% and 26.9% depending on which scenario is considered. This probable reduction in revenues requires urgent measures to attenuate the deepening of educational inequalities, converging to the transference of federal funds to sub-national governments. Finally, we highlight the economic virtue of investing in education, when considering the capillarity of education, and its character of intensive investment in personnel.
Resumen El objetivo del artículo es estimar los impactos de la caída de la recaudación tributaria en el financiamiento de la educación básica frente a los efectos económicos adversos de la pandemia de COVID-19. Para ello, se analizan tres escenarios hipotéticos de caída de la recaudación y sus efectos sobre el presupuesto educativo y por alumno en los estados y municipios, por medio de una metodología que combinó datos de ingresos tributarios, recursos impositivos vinculados a la educación y matrículas. En el escenario más optimista, la reducción del 7% de los ingresos tributarios líquidos implicaría una disminución de los recursos para la educación básica de R$ 16,6 mil millones. Los recursos mensuales por alumno que en 2018 fueron de R$ 460,00 en promedio, podrían caer de 4,1% a 26,9%, dependiendo del escenario de reducción. Frente a la previsible disminución de recursos, se proponen medidas urgentes para atenuar la profundización de las desigualdades en la educación, las cuales convergen en la transferencia de recursos federales a los gobiernos subnacionales. Finalmente se resalta el papel virtuoso de la inversión educativa en la economía, dada la capilaridad de la educación y su carácter intensivo en personal.
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