DeepPrecip: A deep neural network for precipitation retrievals

Remotely-sensed precipitation retrievals are critical for advancing our understanding of global energy and hydrologic cycles in remote regions. Radar reflectivity profiles of the lower atmosphere are commonly linked to precipitation through empirical power laws, but these relationships are tightly coupled to particle microphysical assumptions that do not generalize well to different regional climates. Here, we develop a robust, highly generalized precipitation retrieval from a deep convolutional neural network (DeepPrecip) to estimate 20-minute average surface precipitation accumulation using near-surface radar data inputs. DeepPrecip displays high retrieval skill and can accurately model total precipitation accumulation, with a mean square error (MSE) 99 % lower, on average, than current methods. DeepPrecip also outperforms a less complex machine learning retrieval algorithm, demonstrating the value of deep learning when applied to precipitation retrievals. Predictor importance analyses suggest that a combination of both near-surface (below 1 km) and higher-altitude (1.5 &ndash; 2 km) radar measurements are the primary features contributing to retrieval accuracy. Further, DeepPrecip closely captures total precipitation accumulation magnitudes and variability across nine distinct locations without requiring any explicit descriptions of particle microphysics or geospatial covariates. This research reveals the important role for deep learning in extracting relevant information about precipitation from atmospheric radar retrievals.</p

Simulation of Cross Section for the Production of Copper-64

The radionuclide 64Cu (T1/2 = 12.7 h) is an important positron emitter, suitable for combining PET imaging and therapy. We evaluated four reactions, namely 64Ni( p, n)64Cu, 64Ni(d, 2n)64Cu, 68Zn( p, αn)64Cu and 64Zn(d, 2 p)64Cu.  Data analysis was generally limited up to about 30MeV using the nuclear model code TALYS-1.6. The result compared favourably with experimental as well as other theoretical works in literature. The integral yields calculated from those data are also given.  A critical comparison of the various production routes of 64Cu is presented. The   64Ni (p, n) 64Cu reaction, utilizing a highly enriched target, is the method of choice. Keywords: 6464Cu Production, Excitation Functions, Calculate Thick Target Yiel

Chronic adaptation of atrial structure and function in elite male athletes

Aims The aim of this study was to establish the degree of structural and functional adaptations in the left (LA) and right atria (RA) in elite male athletes engaged in ‘high dynamic : high static’ (HDHS) and ‘low dynamic : high static’ (LDHS) sporting disciplines compared with sedentary controls. Methods and results Eighteen male, elite HDHS athletes (13 boxers and 7 triathletes), 18 male, elite LDHS athletes (8 weightlifters and 10 Akido), and 20 male, age-matched sedentary controls were assessed using conventional 2D and myocardial speckle tracking (MST) echocardiography. Absolute LA and RA volumes [end systole (VOLes), pre A (VOLpreA), and end diastole (VOLed)] as well as the functional indices of reservoir (RESvol), conduit (CONvol), and booster volumes (BOOvol) were defined. MST allowed the assessment of atrial strain (ε) during the reservoir (RESε), conduit (CONε), and booster (BOOε) phases of the cardiac cycle. Both LA and RA sizes were significantly larger in HDHS compared with LDHS and controls (P 1 in all groups due to a comparatively larger RA volume (RAVOLes : LAVOLes 1.05 ± 0.26, 1.12 ± 0.55, and 1.04 ± 0.28 for HDHS, LDHS, and controls, respectively, P > 0.05). There was no significant between group differences for any ε parameter. Conclusion Bi-atrial hypertrophy is demonstrated in HDHS athletes and not in LDHS athletes, suggesting that the dynamic component to training is the primary driver for both LA and RA adaptation. Although functional data derived from volume shifts suggest augmented function in HDHS athletes, MST imaging demonstrated no difference in intrinsic atrial ε in any of the groups

Magnetic Field Tomography in Nearby Galaxies with the Square Kilometre Array

Magnetic fields play an important role in shaping the structure and evolution of the interstellar medium (ISM) of galaxies, but the details of this relationship remain unclear. With SKA1, the 3D structure of galactic magnetic fields and its connection to star formation will be revealed. A highly sensitive probe of the internal structure of the magnetoionized ISM is the partial depolarization of synchrotron radiation from inside the volume. Different configurations of magnetic field and ionized gas within the resolution element of the telescope lead to frequency-dependent changes in the observed degree of polarization. The results of spectro-polarimetric observations are tied to physical structure in the ISM through comparison with detailed modeling, supplemented with the use of new analysis techniques that are being actively developed and studied within the community such as Rotation Measure Synthesis. The SKA will enable this field to come into its own and begin the study of the detailed structure of the magnetized ISM in a sample of nearby galaxies, thanks to its extraordinary wideband capabilities coupled with the combination of excellent surface brightness sensitivity and angular resolution.Comment: 11 pages, 1 figure; to appear as part of 'Cosmic Magnetism' in Proceedings 'Advancing Astrophysics with the SKA (AASKA14)', PoS(AASKA14)10

An Extensible Framework for Query Optimization on TripleT-Based RDF Stores

ABSTRACT The RDF data model is a key technology in the Linked Data vision. Given its graph structure, even relatively simple RDF queries often involve a large number of joins. Join evaluation poses a significant performance challenge on all state-of-the-art RDF engines. TripleT is a novel RDF index data structure, demonstrated to be competitive with the current state-of-the-art for join processing. Query optimization on TripleT, however, has not been systematically studied up to this point. In this paper we investigate how the use of (i) heuristics and (ii) data statistics can contribute towards a more intelligent way of generating query plans over TripleT-based RDF stores. We propose a generic framework for query optimization, and show through an extensive empirical study that our framework consistently produces efficient query evaluation plans

The impact of chronic endurance and resistance training upon the right ventricular phenotype in male athletes

Objectives The traditional view of differential left ventricular adaptation to training type has been questioned. Right ventricular (RV) data in athletes are emerging but whether training type mediates this is not clear. The primary aim of this study was to evaluate the RV phenotype in endurance- vs. resistance-trained male athletes. Secondary aims included comparison of RV function in all groups using myocardial speckle tracking, and the impact of allometric scaling on RV data interpretation. Methods A prospective cross-sectional design assessed RV structure and function in 19 endurance-trained (ET), 21 resistance-trained (RT) and 21 sedentary control subjects (CT). Standard 2D tissue Doppler imaging and speckle tracking echocardiography assessed RV structure and function. Indexing of RV structural parameters to body surface area (BSA) was undertaken using allometric scaling. Results A higher absolute RV diastolic area was observed in ET (mean ± SD: 27 ± 4 cm2) compared to CT (22 ± 4 cm2; P < 0.05) that was maintained after scaling. Whilst absolute RV longitudinal dimension was greater in ET (88 ± 9 mm) than CT (81 ± 10 mm; P < 0.05), this difference was removed after scaling. Wall thickness was not different between ET and RT and there were no between group differences in global or regional RV function. Conclusion We present some evidence of RV adaptation to chronic ET in male athletes but limited structural characteristics of an athletic heart were observed in RT. Global and regional RV functions were comparable between groups. Allometric scaling altered data interpretation in some variables

Banks' risk assessment of Swedish SMEs

Building on the literatures on asymmetric information and risk taking, this paper applies conjoint experiments to investigate lending officers' probabilities of supporting credit to established or existing SMEs. Using a sample of 114 Swedish lending officers, we test hypotheses concerning how information on the borrower's ability to repay the loan; alignment of risk preferences; and risk sharing affect their willingness to grant credit. Results suggest that features that reduce the risk to the bank and shift the risk to the borrower have the largest impact. The paper highlights the interaction between factors that influence the credit decision. Implications for SMEs, banks and research are discussed

Ursinus College Alumni Journal, August 1966

Departure day • Guidance • Counseling Ursinus students • Guiding high school students • Bertolt Brecht in America and East Berlin • From the President • The other side of the desk • Ursinus grizzly leaps the first Alumni Centennial Fund hurdle • A debate on war livens Alumni Day • Ups & downs of progress • Sporting scene: Lacrosse; Top athlete graduates; Wrestling; Tennis; Baseball; Track • Regionals: Each spring meeting has a style of its own • Campus clippings • Class notebook • Weddings • Births • In memoriamhttps://digitalcommons.ursinus.edu/alumnijournal/1086/thumbnail.jp

NASA's Earth Science Use of Commercially Availiable Remote Sensing Datasets: Cover Image

The cover image incorporates high resolution stereo pairs acquired from the DigitalGlobe(R) QuickBird sensor. It shows a digital elevation model of Meteor Crater, Arizona at approximately 1.3 meter point-spacing. Image analysts used the Leica Photogrammetry Suite to produce the DEM. The outside portion was computed from two QuickBird panchromatic scenes acquired October 2006, while an Optech laser scan dataset was used for the crater s interior elevations. The crater s terrain model and image drape were created in a NASA Constellation Program project focused on simulating lunar surface environments for prototyping and testing lunar surface mission analysis and planning tools. This work exemplifies NASA s Scientific Data Purchase legacy and commercial high resolution imagery applications, as scientists use commercial high resolution data to examine lunar analog Earth landscapes for advanced planning and trade studies for future lunar surface activities. Other applications include landscape dynamics related to volcanism, hydrologic events, climate change, and ice movement