ALBERT

Description: Alexander Russell , Anthony Yeates and Jonathan Eastwood review the state of the art and interesting future directions in this developing field, drawing on the RAS discussion meeting held on 12 December 2014.

Description: Perinatal distress and depression can have significant impacts on both the mother and baby. The present study investigated psychosocial and obstetric factors associated with perinatal distress and depressive symptoms among culturally and linguistically diverse (CALD) Australian women in Sydney, New South Wales. The study used retrospectively linked maternal and child health data from two Local Health Districts in Australia (N = 25,407). Perinatal distress was measured using the Edinburgh Postnatal Depression Scale (EPDS, scores of 10–12) and depressive symptoms, with EPDS scores of 13 or more. Multivariate multinomial logistic regression models were used to investigate the association between psychosocial and obstetric factors with perinatal distress and depressive symptoms. The prevalence of perinatal distress and depressive symptoms among CALD Australian women was 10.1% for antenatal distress; 7.3% for antenatal depressive symptoms; 6.2% for postnatal distress and 3.7% for postnatal depressive symptoms. Antenatal distress and depressive symptoms were associated with a lack of partner support, intimate partner violence, maternal history of childhood abuse and being known to child protection services. Antenatal distress and depressive symptoms were strongly associated with postnatal distress and depressive symptoms. Higher socioeconomic status had a protective effect on antenatal and postnatal depressive symptoms. Our study suggests that current perinatal mental health screening and referral for clinical assessment is essential, and also supports a re-examination of perinatal mental health policy to ensure access to culturally responsive mental health care that meets patients’ needs.

Description: We describe advanced spectral and radiometric calibration techniques developed for NASA’s Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). By employing both statistically rigorous analysis and utilizing in situ data to inform calibration procedures and parameter estimation, we can dramatically reduce undesirable artifacts and minimize uncertainties of calibration parameters notoriously difficult to characterize in the laboratory. We describe a novel approach for destriping imaging spectrometer data through minimizing a Markov Random Field model. We then detail statistical methodology for bad pixel correction of the instrument, followed by the laboratory and field protocols involved in the corrections and evaluate their effectiveness on historical data. Finally, we review the geometric processing procedure used in production of the radiometrically calibrated image data.

Description: Ice cream is a complex multi-phase colloidal soft-solid and its three-dimensional microstructure plays a critical role in determining the oral sensory experience or mouthfeel. Using in-line phase contrast synchrotron X-ray tomography, we capture the rapid evolution of the ice cream microstructure during heat shock conditions in situ and operando, on a time scale of minutes. The further evolution of the ice cream microstructure during storage and abuse was captured using ex situ tomography on a time scale of days. The morphology of the ice crystals and unfrozen matrix during these thermal cycles was quantified as an indicator for the texture and oral sensory perception. Our results reveal that the coarsening is due to both Ostwald ripening and physical agglomeration, enhancing our understanding of the microstructural evolution of ice cream during both manufacturing and storage. The microstructural evolution of this complex material was quantified, providing new insights into the behavior of soft-solids and semi-solids, including many foodstuffs, and invaluable data to both inform and validate models of their processing.

Description: The Large-aperture Experiment to Detect the Dark Age (LEDA) was designed to detect the predicted O(100) mK sky-averaged absorption of the cosmic microwave background by hydrogen in the neutral pre- and intergalactic medium just after the cosmological Dark Age. The spectral signature would be associated with emergence of a diffuse Lyα background from starlight during ‘Cosmic Dawn’. Recently, Bowman et al. have reported detection of this predicted absorption feature, with an unexpectedly large amplitude of 530 mK, centred at 78 MHz. Verification of this result by an independent experiment, such as LEDA, is pressing. In this paper, we detail design and characterization of the LEDA radiometer systems, and a first-generation pipeline that instantiates a signal path model. Sited at the Owens Valley Radio Observatory Long Wavelength Array, LEDA systems include the station correlator, five well-separated redundant dual polarization radiometers and back-end electronics. The radiometers deliver a 30–85 MHz band (16 〈z 〈 34) and operate as part of the larger interferometric array, for purposes ultimately of in situ calibration. Here, we report on the LEDA system design, calibration approach, and progress in characterization as of 2016 January. The LEDA systems are currently being modified to improve performance near 78 MHz in order to verify the purported absorption feature.

Description: Summary We present software to characterize and rank potential therapeutic (drug) targets with data from public databases and present it in a user-friendly format. By understanding potential obstacles to drug development through the gathering and understanding of this information, combined with robust approaches to target validation to generate therapeutic hypotheses, this approach may provide high quality targets, leading the process of drug development to become more efficient and cost-effective. Availability and implementation The information we gather on potential targets concerns small-molecule druggability (ligandability), suitability for large-molecule approaches (e.g. antibodies) or new modalities (e.g. antisense oligonucleotides, siRNA or PROTAC), feasibility (availability of resources such as assays and biological knowledge) and potential safety risks (adverse tissue-wise expression, deleterious phenotypes). This information can be termed ‘tractability’. We provide visualization tools to understand its components. TractaViewer is available from https://github.com/NeilPearson-Lilly/TractaViewer Supplementary information Supplementary data are available at Bioinformatics online.

Description: Fugitive emissions from waste disposal sites are important anthropogenic sources of the greenhouse gas methane (CH4). As a result of the growing world population and the recognition of the need to control greenhouse gas emissions, this anthropogenic source of CH4 has received much recent attention. However, the accurate assessment of the CH4 emissions from landfills by modeling and existing measurement techniques is challenging. This is because of inaccurate knowledge of the model parameters and the extent of and limited accessibility to landfill sites. This results in a large uncertainty in our knowledge of the emissions of CH4 from landfills and waste management. In this study, we present results derived from data collected during the research campaign COMEX (CO2 and MEthane eXperiment) in late summer 2014 in the Los Angeles (LA) Basin. One objective of COMEX, which comprised aircraft observations of methane by the remote sensing Methane Airborne MAPper (MAMAP) instrument and a Picarro greenhouse gas in situ analyzer, was the quantitative investigation of CH4 emissions. Enhanced CH4 concentrations or CH4 plumes were detected downwind of landfills by remote sensing aircraft surveys. Subsequent to each remote sensing survey, the detected plume was sampled within the atmospheric boundary layer by in situ measurements of atmospheric parameters such as wind information and dry gas mixing ratios of CH4 and carbon dioxide (CO2) from the same aircraft. This was undertaken to facilitate the independent estimation of the surface fluxes for the validation of the remote sensing estimates. During the COMEX campaign, four landfills in the LA Basin were surveyed. One landfill repeatedly showed a clear emission plume. This landfill, the Olinda Alpha Landfill, was investigated on 4 days during the last week of August and first days of September 2014. Emissions were estimated for all days using a mass balance approach. The derived emissions vary between 11.6 and 17.8 kt CH4 yr−1 with related uncertainties in the range of 14 to 45 %. The comparison of the remote sensing and in situ based CH4 emission rate estimates reveals good agreement within the error bars with an average of the absolute differences of around 2.4 kt CH4 yr−1 (±2. 8 kt CH4 yr−1). The US Environmental Protection Agency (EPA) reported inventory value is 11.5 kt CH4 yr−1 for 2014, on average 2.8 kt CH4 yr−1 (±1. 6 kt CH4 yr−1) lower than our estimates acquired in the afternoon in late summer 2014. This difference may in part be explained by a possible leak located on the southwestern slope of the landfill, which we identified in the observations of the Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) instrument, flown contemporaneously aboard a second aircraft on 1 day.

Description: Visible–shortwave infrared imaging spectroscopy provides valuable remote measurements of Earth's surface and atmospheric properties. These measurements generally rely on inversions of computationally intensive radiative transfer models (RTMs). RTMs' computational expense makes them difficult to use with high-volume imaging spectrometers, and forces approximations such as lookup table interpolation and surface–atmosphere decoupling. These compromises limit the accuracy and flexibility of the remote retrieval; dramatic speed improvements in radiative transfer models could significantly improve the utility and interpretability of remote spectroscopy for Earth science. This study demonstrates that nonparametric function approximation with neural networks can replicate radiative transfer calculations and generate accurate radiance spectra at multiple wavelengths over a diverse range of surface and atmosphere state parameters. We also demonstrate such models can act as surrogate forward models for atmospheric correction procedures. Incorporating physical knowledge into the network structure provides improved interpretability and model efficiency. We evaluate the approach in atmospheric correction of data from the PRISM airborne imaging spectrometer, and demonstrate accurate emulation of radiative transfer calculations, which run several orders of magnitude faster than first-principles models. These results are particularly amenable to iterative spectrum fitting approaches, providing analytical benefits including statistically rigorous treatment of uncertainty and the potential to recover information on spectrally broad signals.

Description: An integrated workflow to estimate the hydrocarbon-in-place and recovery factor is applied in the Bakken-Three Forks petroleum system. Evaluating factors that control the generation and storage of hydrocarbon, such as the total organic carbon, maturity of shale, thickness, porosity, and permeability is a challenge in any shale play study. In addition, the hybrid nature of the Bakken petroleum system, where the source and reservoir rock are present within a short depth interval, adds complexity to the production interpretation and outlook of the play. One complexity is the contribution from Upper and Lower Bakken organic-rich shales to the production of horizontal wells completed in the Middle Bakken low-permeability laminated sandstone/siltstone and Upper Three Forks sandy/silty dolostone. We have performed geologic and petrophysical studies and calculate and map the hydrocarbon pore volume. For fluid characterization, we use three models to accurately cover a range of American Petroleum Institute gravity and gas/oil ratio. We evaluate the contribution of Upper and Lower Bakken to production by constructing simulation models and used that knowledge to estimate the recovery factor of the horizontal wells. Production depletes the Middle Bakken, creating a pressure difference between the Middle Bakken and the Upper/Lower Bakken, which in turn depletes the Upper/Lower Bakken. Vertical permeability controls production from the Upper and Lower Bakken, and higher vertical permeability increases the contribution of the two shale members. An understanding of the maturity and trap mechanism can help to explain the water-saturation distribution, and understanding these factors is crucial to any future development of the play.

Description: An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation.