Effects of hydrocarbon spills on the temperature and moisture regimes of Cryosols in the Ross Sea region

Hydrocarbon spills have occurred on Antarctic soils where fuel oils are utilized, moved or stored. We investigated the effects of hydrocarbon spills on soil temperature and moisture regimes by comparing the properties of existing oil contaminated sites with those of nearby, uncontaminated, control sites at Scott Base, the old Marble Point camp, and Bull Pass in the Wright Valley. Hydrocarbon levels were elevated in fuel-contaminated samples. Climate stations were installed at all three locations in both contaminated and control sites. In summer at Scott Base and Marble Point the mean weekly maximum near surface (2 cm and 5 cm depth) soil temperatures were warmer (P<0.05), sometimes by more than 10°C, at the contaminated site than the control sites. At Bull Pass there were no statistically significant differences in near-surface soil temperatures between contaminated and control soils. At the Scott Base and Marble Point sites soil albedo was lower, and hydrophobicity was higher, in the contaminated soils than the controls. The higher temperatures at the Scott Base and Marble Point hydrocarbon contaminated sites are attributed to the decreased surface albedo due to soil surface darkening by hydrocarbons. There were no noteworthy differences in moisture retention between contaminated and control sites

Do investors care about impact?

We assess how investors’ willingness-to-pay (WTP) for sustainable investments responds to the social impact of those investments, using a framed field experiment. While investors have a substantial WTP for sustainable investments, they do not pay significantly more for more impact. This also holds for dedicated impact investors. When investors compare several sustainable investments, their WTP responds to relative, but not to absolute, levels of impact. Regardless of investments’ impact, investors experience positive emotions when choosing sustainable investments. Our findings suggest that the WTP for sustainable investments is primarily driven by an emotional, rather than a calculative, valuation of impact

SRflow: Deep learning based super-resolution of 4D-flow MRI data

Exploiting 4D-flow magnetic resonance imaging (MRI) data to quantify hemodynamics requires an adequate spatio-temporal vector field resolution at a low noise level. To address this challenge, we provide a learned solution to super-resolve in vivo 4D-flow MRI data at a post-processing level. We propose a deep convolutional neural network (CNN) that learns the inter-scale relationship of the velocity vector map and leverages an efficient residual learning scheme to make it computationally feasible. A novel, direction-sensitive, and robust loss function is crucial to learning vector-field data. We present a detailed comparative study between the proposed super-resolution and the conventional cubic B-spline based vector-field super-resolution. Our method improves the peak-velocity to noise ratio of the flow field by 10 and 30% for in vivo cardiovascular and cerebrovascular data, respectively, for 4 × super-resolution over the state-of-the-art cubic B-spline. Significantly, our method offers 10x faster inference over the cubic B-spline. The proposed approach for super-resolution of 4D-flow data would potentially improve the subsequent calculation of hemodynamic quantities

Analytical Study of Solution-Processed Tin Oxide as Electron Transport Layer in Printed Perovskite Solar Cells

Solution‐processed tin oxide (SnO$_{x}$ ) electron transport layers demonstrate excellent performance in various optoelectronic devices and offer the ease of facile and low cost deposition by various printing techniques. The most common precursor solution for the preparation of SnO$_{x}$ thin films is SnCl$_{2}$ dissolved in ethanol. In order to elucidate the mechanism of the precursor conversion at different annealing temperatures and the optoelectronic performance of the SnO$_{x}$ electron transport layer, phonon and vibrational infrared and photoelectron spectroscopies as well as atomic force microscopy are used to probe the chemical, physical, and morphological properties of the SnO$_{x}$ thin films. The influence of two different solvents on the layer morphology of SnO$_{x}$ thin films is investigated. In both cases, an increasing annealing temperature not only improves the structural and chemical properties of solution‐processed SnO$_{x}$, but also reduces the concentration of tin hydroxide species in the bulk and on the surface of these thin films. As a prototypical example for the high potential of printed SnO$_{x}$ layers for solar cells, high performance perovskite solar cells with a stabilized power conversion efficiency of over 15% are presented

Proton radiotherapy for chest wall and regional lymphatic radiation; dose comparisons and treatment delivery

Purpose The delivery of post-mastectomy radiation therapy (PMRT) can be challenging for patients with left sided breast cancer that have undergone mastectomy. This study investigates the use of protons for PMRT in selected patients with unfavorable cardiac anatomy. We also report the first clinical application of protons for these patients. Methods and materials Eleven patients were planned with protons, partially wide tangent photon fields (PWTF), and photon/electron (P/E) fields. Plans were generated with the goal of achieving 95% coverage of target volumes while maximally sparing cardiac and pulmonary structures. In addition, we report on two patients with unfavorable cardiac anatomy and IMN involvement that were treated with a mix of proton and standard radiation. Results: PWTF, P/E, and proton plans were generated and compared. Reasonable target volume coverage was achieved with PWTF and P/E fields, but proton therapy achieved superior coverage with a more homogeneous plan. Substantial cardiac and pulmonary sparing was achieved with proton therapy as compared to PWTF and P/E. In the two clinical cases, the delivery of proton radiation with a 7.2 to 9 Gy photon and electron component was feasible and well tolerated. Akimbo positioning was necessary for gantry clearance for one patient; the other was treated on a breast board with standard positioning (arms above her head). LAO field arrangement was used for both patients. Erythema and fatigue were the only noted side effects. Conclusions: Proton RT enables delivery of radiation to the chest wall and regional lymphatics, including the IMN, without compromise of coverage and with improved sparing of surrounding normal structures. This treatment is feasible, however, optimal patient set up may vary and field size is limited without multiple fields/matching

How challenging RADseq data turned out to favor coalescent-based species tree inference. A case study in Aichryson (Crassulaceae)

Analysing multiple genomic regions while incorporating detection and qualification of discordance among regions has become standard for understanding phylogenetic relationships. In plants, which usually have comparatively large genomes, this is feasible by the combination of reduced-representation library (RRL) methods and high-throughput sequencing enabling the cost effective acquisition of genomic data for thousands of loci from hundreds of samples. One popular RRL method is RADseq. A major disadvantage of established RADseq approaches is the rather short fragment and sequencing range, leading to loci of little individual phylogenetic information. This issue hampers the application of coalescent-based species tree inference. The modified RADseq protocol presented here targets ca. 5,000 loci of 300-600nt length, sequenced with the latest short-read-sequencing (SRS) technology, has the potential to overcome this drawback. To illustrate the advantages of this approach we use the study group Aichryson Webb & Berthelott (Crassulaceae), a plant genus that diversified on the Canary Islands. The data analysis approach used here aims at a careful quality control of the long loci dataset. It involves an informed selection of thresholds for accurate clustering, a thorough exploration of locus properties, such as locus length, coverage and variability, to identify potential biased data and a comparative phylogenetic inference of filtered datasets, accompanied by an evaluation of resulting BS support, gene and site concordance factor values, to improve overall resolution of the resulting phylogenetic trees. The final dataset contains variable loci with an average length of 373nt and facilitates species tree estimation using a coalescent-based summary approach. Additional improvements brought by the approach are critically discussed

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling

Solving the inverse problem is the key step in evaluating the capacity of a physical model to describe real phenomena. In medical image computing, it aligns with the classical theme of image-based model personalization. Traditionally, a solution to the problem is obtained by performing either sampling or variational inference based methods. Both approaches aim to identify a set of free physical model parameters that results in a simulation best matching an empirical observation. When applied to brain tumor modeling, one of the instances of image-based model personalization in medical image computing, the overarching drawback of the methods is the time complexity of finding such a set. In a clinical setting with limited time between imaging and diagnosis or even intervention, this time complexity may prove critical. As the history of quantitative science is the history of compression (Schmidhuber and Fridman, 2018), we align in this paper with the historical tendency and propose a method compressing complex traditional strategies for solving an inverse problem into a simple database query task. We evaluated different ways of performing the database query task assessing the trade-off between accuracy and execution time. On the exemplary task of brain tumor growth modeling, we prove that the proposed method achieves one order speed-up compared to existing approaches for solving the inverse problem. The resulting compute time offers critical means for relying on more complex and, hence, realistic models, for integrating image preprocessing and inverse modeling even deeper, or for implementing the current model into a clinical workflow. The code is available at https://github.com/IvanEz/for-loop-tumor

CoRoT-22 b: a validated 4.9 RE exoplanet in 10-day orbit

The CoRoT satellite has provided high-precision photometric light curves for more than 163,000 stars and found several hundreds of transiting systems compatible with a planetary scenario. If ground-based velocimetric observations are the best way to identify the actual planets among many possible configurations of eclipsing binary systems, recent transit surveys have shown that it is not always within reach of the radial-velocity detection limits. In this paper, we present a transiting exoplanet candidate discovered by CoRoT whose nature cannot be established from ground-based observations, and where extensive analyses are used to validate the planet scenario. They are based on observing constraints from radial-velocity spectroscopy, adaptive optics imaging and the CoRoT transit shape, as well as from priors on stellar populations, planet and multiple stellar systems frequency. We use the fully Bayesian approach developed in the PASTIS analysis software, and conclude that the planet scenario is at least 1400 times more probable than any other false positive scenario. The primary star is a metallic solar-like dwarf, with Ms = 1.099+-0.049 Msun and Rs = 1.136 (+0.038,-0.090) Rsun . The validated planet has a radius of Rp = 4.88 (+0.17,-0.39) RE and mass less than 49 ME. Its mean density is smaller than 2.56 g/cm^3 and orbital period is 9.7566+-0.0012 days. This object, called CoRoT-22 b, adds to a large number of validated Kepler planets. These planets do not have a proper measurement of the mass but allow statistical characterization of the exoplanet population