The Deep Blue Color of HD 189733b: Albedo Measurements with Hubble Space Telescope/Space Telescope Imaging Spectrograph at Visible Wavelengths

We present a secondary eclipse observation for the hot Jupiter HD 189733b across the wavelength range 290-570 nm made using the Space Telescope Imaging Spectrograph on the Hubble Space Telescope. We measure geometric albedos of Ag = 0.40 ± 0.12 across 290-450 nm and Ag < 0.12 across 450-570 nm at 1σ confidence. The albedo decrease toward longer wavelengths is also apparent when using six wavelength bins over the same wavelength range. This can be interpreted as evidence for optically thick reflective clouds on the dayside hemisphere with sodium absorption suppressing the scattered light signal beyond ~450 nm. Our best-fit albedo values imply that HD 189733b would appear a deep blue color at visible wavelengths.

Validation of targeting the ventrointermediate thalamic nucleus using Q-ball calculation in deep brain stimulation for tremor

Objective: Identification of the ventrointermediate thalamic nucleus (Vim) in modern 3T high-field MRI for image-based targeting in deep brain stimulation (DBS) is still challenging. To evaluate the usefulness and reliability of analyzing the connectivity with the cerebellum using Q-ball-calculation we performed a retrospective analysis. Method: 5 patients who underwent bilateral implantation of electrodes in the Vim for treatment of Essential Tremor between 2011 and 2012 received additional preoperative Q-ball imaging. Targeting was performed according to atlas coordinates and standard MRI. Additionally we performed a retrospective identification of the Vim by analyzing the connectivity of the thalamus with the dentate nucleus. The exact position of the active stimulation contact in the postoperative CT was correlated with the Vim as it was identified by Q-ball calculation. Results: Localization of the Vim by analysis of the connectivity between thalamus and cerebellum was successful in all 5 patients on both sides. The average position of the active contacts was 14.6 mm (SD 1.24) lateral, 5.37 mm (SD 0.094 posterior and 2.21 mm (SD 0.69) cranial of MC. The cranial portion of the dentato-rubro-thalamic tract was localized an average of 3.38 mm (SD 1.57) lateral and 1.5 mm (SD 1.22) posterior of the active contact. Conclusions: Connectivity analysis by Q-ball calculation provided direct visualization of the Vim in all cases. Our preliminary results suggest, that the target determined by connectivity analysis is valid and could possibly be used in addition to or even instead of atlas based targeting. Larger prospective calculations are needed to determine the robustness of this method in providing refined information useful for neurosurgical treatment of tremor.

Earth gravity field recovery using GPS, GLONASS, and SLR satellites

The time variable Earth’s gravity field provides the information about mass transport within the system Earth, i.e., the relationship of mass transport between atmosphere, oceans, and land hydrology. We recover the low-degree parameters of the time variable gravity field using microwave observations from GPS and GLONASS satellites and from SLR data to five geodetic satellites, namely LAGEOS-1/2, Starlette, Stella, and AJISAI. GPS satellites are particularly sensitive to specific coefficients of the Earth's gravity field, because of the deep 2:1 orbital resonance with Earth rotation (two revolutions of the GPS satellites per sidereal day). The resonant coefficients cause, among other, a “secular” drift (actually periodic variations of very long periods) of the semi-major axes of up to 5.3 m/day of GPS satellites. We processed 10 years of GPS and GLONASS data using the standard orbit models from the Center of Orbit Determination in Europe (CODE) with a simultaneous estimation of the Earth gravity field coefficients and other parameters, e.g., satellite orbit parameters, station coordinates, Earth rotation parameters, troposphere delays, etc. The weekly GNSS gravity solutions up to degree and order 4/4 are compared to the weekly SLR gravity field solutions. The SLR-derived geopotential coefficients are compared to monthly GRACE and CHAMP results.

Groundwater age distributions at a public drinking water supply well field derived from multiple age tracers (⁸⁵Kr, ³H/³He, and ³⁹Ar)

Groundwater age is a key aspect of production well vulnerability. Public drinking water supply wells typically have long screens and are expected to produce a mixture of groundwater ages. The groundwater age distributions of seven production wells of the Holten well field (Netherlands) were estimated from tritium-helium (3H/3He), krypton-85 (85Kr), and argon-39 (39Ar), using a new application of a discrete age distribution model and existing mathematical models, by minimizing the uncertainty-weighted squared differences of modeled and measured tracer concentrations. The observed tracer concentrations fitted well to a 4-bin discrete age distribution model or a dispersion model with a fraction of old groundwater. Our results show that more than 75 of the water pumped by four shallow production wells has a groundwater age of less than 20 years and these wells are very vulnerable to recent surface contamination. More than 50 of the water pumped by three deep production wells is older than 60 years. 3H/3He samples from short screened monitoring wells surrounding the well field constrained the age stratification in the aquifer. The discrepancy between the age stratification with depth and the groundwater age distribution of the production wells showed that the well field preferentially pumps from the shallow part of the aquifer. The discrete groundwater age distribution model appears to be a suitable approach in settings where the shape of the age distribution cannot be assumed to follow a simple mathematical model, such as a production well field where wells compete for capture area.

Into the abyss of Lake Geneva: the elemo interdisciplinary field investigation using the MIR submersibles

In summer 2011, the two Russian MIR sub- mersibles were brought to Switzerland to perform deep water dives in Lake Geneva. Research teams from several environmental science institutes, both national and inter- national, participated in this interdisciplinary effort to investigate the deeper parts of Lake Geneva. Using the MIRs allowed the scientists to see and precisely select the sites where they could extract specific sediment cores and carry out detailed in situ measurements at the sediment– water boundary. One focus site was the surrounding of the outlet of the wastewater treatment plant of the City of Lausanne, which discharges into the Vidy Bay. The investigations concentrated on the pollution of the local sediments, pollution-related ecotoxicological risks, micro- bial activity and spreading and removal of the effluents from the bay to the open waters of the lake. The other focus site was the Rhoˆne River delta and its subaquatic canyons, which formed as a result of the long-term interplay of the deposition of river-borne sediments and flood-triggered canyon erosion events.

Novel radiotherapy techniques for involved-field and involved-node treatment of mediastinal Hodgkin lymphoma: when should they be considered and which questions remain open?

PURPOSE Hodgkin lymphoma (HL) is a highly curable disease. Reducing late complications and second malignancies has become increasingly important. Radiotherapy target paradigms are currently changing and radiotherapy techniques are evolving rapidly. DESIGN This overview reports to what extent target volume reduction in involved-node (IN) and advanced radiotherapy techniques, such as intensity-modulated radiotherapy (IMRT) and proton therapy-compared with involved-field (IF) and 3D radiotherapy (3D-RT)- can reduce high doses to organs at risk (OAR) and examines the issues that still remain open. RESULTS Although no comparison of all available techniques on identical patient datasets exists, clear patterns emerge. Advanced dose-calculation algorithms (e.g., convolution-superposition/Monte Carlo) should be used in mediastinal HL. INRT consistently reduces treated volumes when compared with IFRT with the exact amount depending on the INRT definition. The number of patients that might significantly benefit from highly conformal techniques such as IMRT over 3D-RT regarding high-dose exposure to organs at risk (OAR) is smaller with INRT. The impact of larger volumes treated with low doses in advanced techniques is unclear. The type of IMRT used (static/rotational) is of minor importance. All advanced photon techniques result in similar potential benefits and disadvantages, therefore only the degree-of-modulation should be chosen based on individual treatment goals. Treatment in deep inspiration breath hold is being evaluated. Protons theoretically provide both excellent high-dose conformality and reduced integral dose. CONCLUSION Further reduction of treated volumes most effectively reduces OAR dose, most likely without disadvantages if the excellent control rates achieved currently are maintained. For both IFRT and INRT, the benefits of advanced radiotherapy techniques depend on the individual patient/target geometry. Their use should therefore be decided case by case with comparative treatment planning.

Time-lapse pressure tomography for characterizing CO2 plume evolution in a deep saline aquifer

A time-lapse pressure tomography inversion approach is applied to characterize the CO2 plume development in a virtual deep saline aquifer. Deep CO2 injection leads to flow properties of the mixed-phase, which vary depending on the CO2 saturation. Analogous to the crossed ray paths of a seismic tomographic experiment, pressure tomography creates streamline patterns by injecting brine prior to CO2 injection or by injecting small amounts of CO2 into the two-phase (brine and CO2) system at different depths. In a first step, the introduced pressure responses at observation locations are utilized for a computationally rapid and efficient eikonal equation based inversion to reconstruct the heterogeneity of the subsurface with diffusivity (D) tomograms. Information about the plume shape can be derived by comparing D-tomograms of the aquifer at different times. In a second step, the aquifer is subdivided into two zones of constant values of hydraulic conductivity (K) and specific storage (Ss) through a clustering approach. For the CO2 plume, mixed-phase K and Ss values are estimated by minimizing the difference between calculated and “true” pressure responses using a single-phase flow simulator to reduce the computing complexity. Finally, the estimated flow property is converted to gas saturation by a single-phase proxy, which represents an integrated value of the plume. This novel approach is tested first with a doublet well configuration, and it reveals a great potential of pressure tomography based concepts for characterizing and monitoring deep aquifers, as well as the evolution of a CO2 plume. Still, field-testing will be required for better assessing the applicability of this approach.

Isotopic effects of nitrate photochemistry in snow: a field study at Dome C, Antarctica

Stable isotope ratios of nitrate preserved in deep ice cores are expected to provide unique and valuable information regarding paleoatmospheric processes. However, due to the post-depositional loss of nitrate in snow, this information may be erased or significantly modified by physical or photochemical processes before preservation in ice. We investigated the role of solar UV photolysis in the post-depositional modification of nitrate mass and stable isotoperatios at Dome C, Antarctica, during the austral summer of 2011/2012. Two 30 cm snow pits were filled with homogenized drifted snow from the vicinity of the base. One of these pits was covered with a plexiglass plate that transmits solar UV radiation, while the other was covered with a different plexiglass plate having a low UV transmittance. Samples were then collected from each pit at a 2–5 cm depth resolution and a 10-day frequency. At the end of the season, acomparable nitrate mass loss was observed in both pits for the top-level samples (0–7 cm) attributed to mixing with the surrounding snow. After excluding samples impacted by the mixing process, we derived an average apparent nitrogen isotopic fractionation (15" app/of role in driving the isotopic fractionation of nitrate in snow.We have estimated a purely photolytic nitrogen isotopic fractionation (15"photo) of -55.8 12.0 ‰ from the difference in the derived apparent isotopic ractionations of the two experimental fields, as both pits were exposed to similar physical processes except exposure to solar UV. This value is in close agreement with the 15" photo value of -47.9 6.8 ‰ derived in a laboratory experiment simulated for Dome C conditions (Berhanu et al., 2014). We have also observed an insensitivity of 15" with depth in the snowpack under the given experimental setup. This is due to the uniform attenuation of incoming solar UV by snow, as 15" is strongly dependent on the spectral distribution of the incoming light flux. Together with earlier work, the results presented here represent a strong body of evidence that solar UV photolysis is the most relevant post-depositional process modifying the stable isotope ratios of snow nitrate at low-accumulation sites, where many deep ice cores are drilled. Nevertheless, modeling the loss of nitrate in snow is still required before a robust interpretation of ice core records can be provided.

Doppler Orbit Determination of Deep Space Probes by the Bernese GNSS Software: First Results of the Combined Orbit Determination from DSN and Inter-Satellite Ka-Band Data from the Grail Mission

Navigation of deep space probes is most commonly operated using the spacecraft Doppler tracking technique. Orbital parameters are determined from a series of repeated measurements of the frequency shift of a microwave carrier over a given integration time. Currently, both ESA and NASA operate antennas at several sites around the world to ensure the tracking of deep space probes. Just a small number of software packages are nowadays used to process Doppler observations. The Astronomical Institute of the University of Bern (AIUB) has recently started the development of Doppler data processing capabilities within the Bernese GNSS Software. This software has been extensively used for Precise Orbit Determination of Earth orbiting satellites using GPS data collected by on-board receivers and for subsequent determination of the Earth gravity field. In this paper, we present the currently achieved status of the Doppler data modeling and orbit determination capabilities in the Bernese GNSS Software using GRAIL data. In particular we will focus on the implemented orbit determination procedure used for the combined analysis of Doppler and intersatellite Ka-band data. We show that even at this earlier stage of the development we can achieve an accuracy of few mHz on two-way S-band Doppler observation and of 2 µm/s on KBRR data from the GRAIL primary mission phase.

Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network

Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied in other domains, such as medical image analysis. In this paper, we propose and evaluate a convolutional neural network (CNN), designed for the classification of ILD patterns. The proposed network consists of 5 convolutional layers with 2×2 kernels and LeakyReLU activations, followed by average pooling with size equal to the size of the final feature maps and three dense layers. The last dense layer has 7 outputs, equivalent to the classes considered: healthy, ground glass opacity (GGO), micronodules, consolidation, reticulation, honeycombing and a combination of GGO/reticulation. To train and evaluate the CNN, we used a dataset of 14696 image patches, derived by 120 CT scans from different scanners and hospitals. To the best of our knowledge, this is the first deep CNN designed for the specific problem. A comparative analysis proved the effectiveness of the proposed CNN against previous methods in a challenging dataset. The classification performance (~85.5%) demonstrated the potential of CNNs in analyzing lung patterns. Future work includes, extending the CNN to three-dimensional data provided by CT volume scans and integrating the proposed method into a CAD system that aims to provide differential diagnosis for ILDs as a supportive tool for radiologists.