The PreAmplifier ShAper for the ALICE TPC-Detector

In this paper the PreAmplifier ShAper (PASA) for the Time Projection Chamber (TPC) of the ALICE experiment at LHC is presented. The ALICE TPC PASA is an ASIC that integrates 16 identical channels, each consisting of Charge Sensitive Amplifiers (CSA) followed by a Pole-Zero network, self-adaptive bias network, two second-order bridged-T filters, two non-inverting level shifters and a start-up circuit. The circuit is optimized for a detector capacitance of 18-25 pF. For an input capacitance of 25 pF, the PASA features a conversion gain of 12.74 mV/fC, a peaking time of 160 ns, a FWHM of 190 ns, a power consumption of 11.65 mW/ch and an equivalent noise charge of 244e + 17e/pF. The circuit recovers smoothly to the baseline in about 600 ns. An integral non-linearity of 0.19% with an output swing of about 2.1 V is also achieved. The total area of the chip is 18 mm$^2$ and is implemented in AMS's C35B3C1 0.35 micron CMOS technology. Detailed characterization test were performed on about 48000 PASA circuits before mounting them on the ALICE TPC front-end cards. After more than two years of operation of the ALICE TPC with p-p and Pb-Pb collisions, the PASA has demonstrated to fulfill all requirements

A near infrared frequency comb for Y+J band astronomical spectroscopy

Radial velocity (RV) surveys supported by high precision wavelength references (notably ThAr lamps and I2 cells) have successfully identified hundreds of exoplanets; however, as the search for exoplanets moves to cooler, lower mass stars, the optimum wave band for observation for these objects moves into the near infrared (NIR) and new wavelength standards are required. To address this need we are following up our successful deployment of an H band(1.45-1.7{\mu}m) laser frequency comb based wavelength reference with a comb working in the Y and J bands (0.98-1.3{\mu}m). This comb will be optimized for use with a 50,000 resolution NIR spectrograph such as the Penn State Habitable Zone Planet Finder. We present design and performance details of the current Y+J band comb.Comment: Submitted to SPIE, conference proceedings 845

The spectral variability of FSRQs

The optical variability of 29 flat spectrum radio quasars in SDSS Stripe 82 region are investigated by using DR7 released multi-epoch data. All FSRQs show variations with overall amplitude ranging from 0.24 mag to 3.46 mag in different sources. About half of FSRQs show a bluer-when-brighter trend, which is commonly observed for blazars. However, only one source shows a redder-when-brighter trend, which implies it is rare in FSRQs. In this source, the thermal emission may likely be responsible for the spectral behavior.Comment: 4 pages, 1 figure, to be published in Journal of Astrophysics and Astronomy, as a proceeding paper of the conference "Multiwavelength Variability of Blazars", Guangzhou, China, September 22-24, 201

Validation of northern latitude Tropospheric Emission Spectrometer stare ozone profiles with ARC-IONS sondes during ARCTAS: sensitivity, bias and error analysis

We compare Tropospheric Emission Spectrometer (TES) versions 3 and 4, V003 and V004, respectively, nadir-stare ozone profiles with ozonesonde profiles from the Arctic Intensive Ozonesonde Network Study (ARCIONS, http://croc.gsfc.nasa.gov/arcions/ during the Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field mission. The ozonesonde data are from launches timed to match Aura's overpass, where 11 coincidences spanned 44° N to 71° N from April to July 2008. Using the TES "stare" observation mode, 32 observations are taken over each coincidental ozonesonde launch. By effectively sampling the same air mass 32 times, comparisons are made between the empirically-calculated random errors to the expected random errors from measurement noise, temperature and interfering species, such as water. This study represents the first validation of high latitude (>70°) TES ozone. We find that the calculated errors are consistent with the actual errors with a similar vertical distribution that varies between 5% and 20% for V003 and V004 TES data. In general, TES ozone profiles are positively biased (by less than 15%) from the surface to the upper-troposphere (~1000 to 100 hPa) and negatively biased (by less than 20%) from the upper-troposphere to the lower-stratosphere (100 to 30 hPa) when compared to the ozonesonde data. Lastly, for V003 and V004 TES data between 44° N and 71° N there is variability in the mean biases (from −14 to +15%), mean theoretical errors (from 6 to 13%), and mean random errors (from 9 to 19%)

Turning gender inside out: delivering higher education in women’s carceral spaces

This article is a critical reflection of the role of gender in the delivery of a higher education course based on the Inside-Out Prison Exchange Programme. Related concepts such as hegemonic masculinity, heteronormativity, and intersectionality are discussed within the prison education setting. This reflection primarily draws on critical incidents from the experiences of the first three authors facilitating a higher education course in a women’s prison in England. One major reflection is that learning in a group of ‘inside’ and ‘outside’ students, all self-identified women, who vary along the dimensions of age, class, ethnicity, nationality and sexual expression, presented unique dynamics. This included working with both collectiveness and difference, gender-aligned expectations about behaviour, and experiences of control, criminal justice and higher education. Additionally, all four authors' experiences of delivering various higher education courses under different prison-education partnership models in both men and women’s prisons allows for comparison and reflection on the institutional reproduction of gender norms. These reflections point to the conclusion that, despite the strong presence of intersectional divisions, gender can become a uniting force when working with an all-women student group, fostering critical thinking and engagement with challenging structural issues. However further reflection considers that being gender-conscious in the classroom should not be limited to all-women student cohorts, as this is exactly what may enable facilitators to tackle some of the issues produced by hegemonic masculinity in a mixed prison classroom

A method for colocating satellite X_(CO₂) data to ground-based data and its application to ACOS-GOSAT and TCCON

Satellite measurements are often compared with higher-precision ground-based measurements as part of validation efforts. The satellite soundings are rarely perfectly coincident in space and time with the ground-based measurements, so a colocation methodology is needed to aggregate "nearby" soundings into what the instrument would have seen at the location and time of interest. We are particularly interested in validation efforts for satellite-retrieved total column carbon dioxide (X_(CO₂)), where X_(CO₂) data from Greenhouse Gas Observing Satellite (GOSAT) retrievals (ACOS, NIES, RemoteC, PPDF, etc.) or SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) are often colocated and compared to ground-based column X_(CO₂) measurement from Total Carbon Column Observing Network (TCCON). Current colocation methodologies for comparing satellite measurements of total column dry-air mole fractions of CO₂ (X_(CO₂)) with ground-based measurements typically involve locating and averaging the satellite measurements within a latitudinal, longitudinal, and temporal window. We examine a geostatistical colocation methodology that takes a weighted average of satellite observations depending on the "distance" of each observation from a ground-based location of interest. The "distance" function that we use is a modified Euclidian distance with respect to latitude, longitude, time, and midtropospheric temperature at 700 hPa. We apply this methodology to X_(CO₂) retrieved from GOSAT spectra by the ACOS team, cross-validate the results to TCCON X_(CO₂) ground-based data, and present some comparisons between our methodology and standard existing colocation methods showing that, in general, geostatistical colocation produces smaller mean-squared error

A High-Resolution Atlas of Uranium-Neon in the H Band

We present a high-resolution (R ~ 50 000) atlas of a uranium-neon (U/Ne) hollow-cathode spectrum in the H-band (1454 nm to 1638 nm) for the calibration of near-infrared spectrographs. We obtained this U/Ne spectrum simultaneously with a laser-frequency comb spectrum, which we used to provide a first-order calibration to the U/Ne spectrum. We then calibrated the U/Ne spectrum using the recently-published uranium line list of Redman et al. (2011), which is derived from high-resolution Fourier transform spectrometer measurements. These two independent calibrations allowed us to easily identify emission lines in the hollow cathode lamp that do not correspond to known (classified) lines of either uranium or neon, and to compare the achievable precision of each source. Our frequency comb precision was limited by modal noise and detector effects, while the U/Ne precision was limited primarily by the signal-to-noise ratio (S/N) of the observed emission lines and our ability to model blended lines. The standard deviation in the dispersion solution residuals from the S/N-limited U/Ne hollow cathode lamp were 50% larger than the standard deviation of the dispersion solution residuals from the modal-noise-limited laser frequency comb. We advocate the use of U/Ne lamps for precision calibration of near-infrared spectrographs, and this H-band atlas makes these lamps significantly easier to use for wavelength calibration.Comment: 23 pages, 7 figures, submitted and accepted in ApJSS. Online-only material to be published online by ApJS

Predicting outcomes of steady-state 13C isotope tracing experiments using Monte Carlo sampling

<p>Abstract</p> <p>Background</p> <p>Carbon-13 (¹³C) analysis is a commonly used method for estimating reaction rates in biochemical networks. The choice of carbon labeling pattern is an important consideration when designing these experiments. We present a novel Monte Carlo algorithm for finding the optimal substrate input label for a particular experimental objective (flux or flux ratio). Unlike previous work, this method does not require assumption of the flux distribution beforehand.</p> <p>Results</p> <p>Using a large <it>E. coli </it>isotopomer model, different commercially available substrate labeling patterns were tested computationally for their ability to determine reaction fluxes. The choice of optimal labeled substrate was found to be dependent upon the desired experimental objective. Many commercially available labels are predicted to be outperformed by complex labeling patterns. Based on Monte Carlo Sampling, the dimensionality of experimental data was found to be considerably less than anticipated, suggesting that effectiveness of ¹³C experiments for determining reaction fluxes across a large-scale metabolic network is less than previously believed.</p> <p>Conclusions</p> <p>While ¹³C analysis is a useful tool in systems biology, high redundancy in measurements limits the information that can be obtained from each experiment. It is however possible to compute potential limitations before an experiment is run and predict whether, and to what degree, the rate of each reaction can be resolved.</p