Detection of Voigt Spectral Line Profiles of Hydrogen Radio Recombination Lines toward Sagittarius B2(N)

We report the detection of Voigt spectral line profiles of radio recombination lines (RRLs) toward Sagittarius B2(N) with the 100 m Green Bank Telescope (GBT). At radio wavelengths, astronomical spectra are highly populated with RRLs, which serve as ideal probes of the physical conditions in molecular cloud complexes. An analysis of the Hn alpha lines presented herein shows that RRLs of higher principal quantum number (n > 90) are generally divergent from their expected Gaussian profiles and, moreover, are well described by their respective Voigt profiles. This is in agreement with the theory that spectral lines experience pressure broadening as a result of electron collisions at lower radio frequencies. Given the inherent technical difficulties regarding the detection and profiling of true RRL wing spans and shapes, it is crucial that the observing instrumentation produce flat baselines as well as high-sensitivity, high-resolution data. The GBT has demonstrated its capabilities regarding all of these aspects, and we believe that future observations of RRL emission via the GBT will be crucial toward advancing our knowledge of the larger-scale extended structures of ionized gas in the interstellar medium (ISM).

Image processing chip for small object detection

A new, front-end image processing chip is presented for real-time small object detection. It has been implemented using a 0.6 µ, 3.3 V CMOS technology and operates on 10-bit input data at 54 megasamples per second. It occupies an area of 12.9 mm×13.6 mm (including pads), dissipates 1.5 W, has 92 I/O pins and is to be housed in a 160-pin ceramic quarter flat-pack. It performs both one- and two-dimensional FIR filtering and a multilayer perceptron (MLP) neural network function using a reconfigurable array of 21 multiplication-accumulation cells which corresponds to a window size of 7×3. The chip can cope with images of 2047 pixels per line and can be cascaded to cope with larger window sizes. The chip performs two billion fixed point multiplications and additions per second.

The WR content of IC10 - first detection of WC9 stars in a low metallicity environment?

We present deep, narrow-hand photometry of the Local Group starburst galaxy IC10. Our dedicated photometric system provides detection of 13 new Wolf-Rayet (WR) stars and allows spectral subtypes to be assigned. Three of these new stars appear to be WC9 subtypes. If confirmed, these would be the very first WC9 stars ever detected in a low metallicity environment, hence putting strong new constraints on the formation and evolution models of massive stars. Eight of the new WR stars are of the WC subtype, which does not significantly modify the anomalously high WC/WN ratio in IC10. However it is likely that a number of Wolf-Rayet stars of the WNE and WC spectral subtypes are still to be discovered in the heart of the galaxy.

Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

Hydrobiogeochemical Interactions along “Flow Tubes” Controls: Watershed Scale Contaminant Flow and Transformation at the Oak Ridge IFRC

Geochemical,spectrographic, microbiological and hydrogeologic studies at the ORIFRC site indicate that groundwater transport in structured media may behave as a system of parallel flow tubes. These tubes are preferred flowpaths that enable contaminant transport parallel to bedding planes (strike) over distances of 1000s of meters. A significant flux of groundwater is focused within an interval defined by the interface between the competent bedrock and overlying highly-weathered saprolite, commonly referred to as the"transition zone." Characteristics of this transition zone are dense fractures and the relative absence of weathering products (e.g. clays)results in a significantly higher permeability compared to both the overlying clay-saprolite and underlying bedrock. Several stratabound low seismic velocity zones located below the transition zone were identified during geophysics studies and were also determined to be fractured high permeability preferred contaminant transport pathways during subsequent drilling activities. XANES analysis of precipitates collected from these deeper flow zones indicate 95% or more of the U deposited is U(VI). Linear combination fitting of the EXAFS data shows that precipitates are ~51±5% U(VI)-carbonate-like phase (e.g., liebigite) and ~49±5% U(VI) associated with an iron oxide phase; inclusion of a third component in the fit suggests that up to 15% of the U(VI) may be associated with a phosphate phase or OH- phase (e.g.,schoepite). Although precipitates with similar U(VI)-carbonate and/or phosphate associations were identified in the transition zone pathways,there were also U(VI) complexes adsorbed to mineral surfaces that would tend to be more readily mobilized. Groundwater in the different flow tubes has been determined to consist of different water quality types that vary with the solid phase encountered (e.g., clays, carbonates, clastics) as contaminants migrate along the flow paths. This lateral and vertical variability in geochemistry, particularly pH, has a significant impact on microbiological community composition and activity. Ribosomal RNA gene analyses coupled with physiological and genomic analyses suggest that bacteria from the genus Rhodanobacter(a diverse population of denitrifiers that are moderately acid tolerant) have a high relative abundance in the acidic source zone at the ORIFRC site.Watershed-scale analysis across different flow paths/tubes revealed strong negative correlation between pH and the absolute and relative abundance of Rhodanobacter. Recent studies also confirmed that the ORIFRC site hosts a diverse fungal community, with significant differences observed between acidic (pH <5) and circumneutral (>5) wells. The lack of nitrous oxide reduction capability in fungi, and the detection of denitrification potential in slurry microcosms suggest that fungi may have aheretofore under appreciated role in biogeochemical transformations, with implications forsite remediation and greenhouse gas emissions. Further research is needed to determine if these organisms can influence U(VI) mobility either directly through immobilization or indirectly through the depletion of nitrate.In conclusion, additional studies are required to quantify the processes (e.g., solid phase reactions, recharge, diffusion, microbial interactions) that are occurring along the groundwater flow tubes identified at the ORIFRC so predictive models can be parameterized and used to assess long-term contaminant fate and transport and remedial options.

A J-band detection of the sub-stellar mass donor in SDSS J1433+1011

We present time-resolved J-band spectroscopy of the short-period cataclysmic variable SDSS J143317.78+101123.3. We detect absorption lines from the sub-stellar donor star in this system, which contributes 38 +/- 5 per cent to the J-band light. From the relative strengths of the absorption lines in the J band, we estimate the spectral type of the donor star to be L2 +/- 1. These data are the first spectroscopic detection of a donor with a confirmed sub-stellar mass in a cataclysmic variable, and the spectral type is consistent with that expected from semi-empirical evolutionary models.

Using skew mapping, we have been able to derive an estimate for the radial velocity of the donor of K-d = 520 +/- 60 km/s. This value is consistent with, though much less precise than, predictions from mass determinations found via photometric fitting of the eclipse light curves.

Detection of Protein-Protein Interactions Using Protein-Fragment Complementation Assays (PCA)

Protein-protein interactions play a central role in many cellular processes. Their characterisation is necessary in order to analyse these processes and for the functional identification of unknown proteins. Existing detection methods such as the yeast two-hybrid (Y2H) and tandem affinity purification (TAP) method provide a means to answer rapidly questions regarding protein-protein interactions, but have limitations which restrict their use to certain interaction networks; furthermore they provide little information regarding interaction localisation at the subcellular level. The development of protein-fragment complementation assays (PCA) employing a fluorescent reporter such as a member of the green fluorescent protein (GFP) family has led to a new method of interaction detection termed Bimolecular Fluorescent Complementation (BiFC). These assays have become important tools for understanding protein interactions and the development of whole genome interaction maps. BiFC assays have the advantages of very low background signal coupled with rapid detection of protein-protein interactions in vivo while also providing information regarding interaction compartmentalisation. Modified forms of the assay such as the use of combinations of spectral variants of GFP have allowed simultaneous visualisation of multiple competing interactions in vivo. Advantages and disadvantages of the method are discussed in the context of other fluorescence-based interaction monitoring techniques.

The progenitor mass of the Type IIP supernova SN 2004et from late-time spectral modeling

SN 2004et is one of the nearest and best-observed Type IIP supernovae, with a progenitor detection as well as good photometric and spectroscopic observational coverage well into the nebular phase. Based on nucleosynthesis from stellar evolution/explosion models we apply spectral modeling to analyze its 140-700 day evolution from ultraviolet to mid-infrared. We find a M_ZAMS= 15 Msun progenitor star (with an oxygen mass of 0.8 Msun) to satisfactorily reproduce [O I] 6300, 6364 {\AA} and other emission lines of carbon, sodium, magnesium, and silicon, while 12 Msun and 19 Msun models under- and overproduce most of these lines, respectively. This result is in fair agreement with the mass derived from the progenitor detection, but in disagreement with hydrodynamical modeling of the early-time light curve. From modeling of the mid-infrared iron-group emission lines, we determine the density of the "Ni-bubble" to rho(t) = 7E-14*(t/100d)^-3 g cm^-3, corresponding to a filling factor of f = 0.15 in the metal core region (V = 1800 km/s). We also confirm that silicate dust, CO, and SiO emission are all present in the spectra.

A quality-scalable and energy-efficient approach for spectral analysis of heart rate variability

Today there is a growing interest in the integration of health monitoring applications in portable devices necessitating the development of methods that improve the energy efficiency of such systems. In this paper, we present a systematic approach that enables energy-quality trade-offs in spectral analysis systems for bio-signals, which are useful in monitoring various health conditions as those associated with the heart-rate. To enable such trade-offs, the processed signals are expressed initially in a basis in which significant components that carry most of the relevant information can be easily distinguished from the parts that influence the output to a lesser extent. Such a classification allows the pruning of operations associated with the less significant signal components leading to power savings with minor quality loss since only less useful parts are pruned under the given requirements. To exploit the attributes of the modified spectral analysis system, thresholding rules are determined and adopted at design- and run-time, allowing the static or dynamic pruning of less-useful operations based on the accuracy and energy requirements. The proposed algorithm is implemented on a typical sensor node simulator and results show up-to 82% energy savings when static pruning is combined with voltage and frequency scaling, compared to the conventional algorithm in which such trade-offs were not available. In addition, experiments with numerous cardiac samples of various patients show that such energy savings come with a 4.9% average accuracy loss, which does not affect the system detection capability of sinus-arrhythmia which was used as a test case. 

Heterogeneous error-resilient scheme for spectral analysis in ultra-low power wearable electrocardiogram devices

Wearable devices performing advanced bio-signal analysis algorithms are aimed to foster a revolution in healthcare provision of chronic cardiac diseases. In this context, energy efficiency is of paramount importance, as long-term monitoring must be ensured while relying on a tiny power source. Operating at a scaled supply voltage, just above the threshold voltage, effectively helps in saving substantial energy, but it makes circuits, and especially memories, more prone to errors, threatening the correct execution of algorithms. The use of error detection and correction codes may help to protect the entire memory content, however it incurs in large area and energy overheads which may not be compatible with the tight energy budgets of wearable systems. To cope with this challenge, in this paper we propose to limit the overhead of traditional schemes by selectively detecting and correcting errors only in data highly impacting the end-to-end quality of service of ultra-low power wearable electrocardiogram (ECG) devices. This partition adopts the protection of either significant words or significant bits of each data element, according to the application characteristics (statistical properties of the data in the application buffers), and its impact in determining the output. The proposed heterogeneous error protection scheme in real ECG signals allows substantial energy savings (11% in wearable devices) compared to state-of-the-art approaches, like ECC, in which the whole memory is protected against errors. At the same time, it also results in negligible output quality degradation in the evaluated power spectrum analysis application of ECG signals.