Corn Hybrids for Texas.

12 p

Traumatic Urethral Injury without Pelvic Fracture in an Adult Female

A 23-year-old female was involved in a motor vehicle collision with multiple injuries, including a right acetabular fracture, but no pelvic fracture. Urology consultation was obtained due to difficulty placing a urethral catheter. Examination revealed a longitudinal urethral tear with vaginal laceration extending 2 cm from the urethral meatus proximally toward the bladder neck. The longitudinal urethral tear was repaired primarily. Traumatic female urethral injury in the absence of a pelvic fracture is an exceedingly rare occurrence

Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining

Deep Learning for Neuroimaging: a Validation Study

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager’s toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data

The Heidelberg-Moscow double beta decay experiment with enriched 76Ge. First results

Abstract The status of the Heidelberg-Moscow ββ-experiment using isotopically enriched 76Ge is reported. The results of 14.8 mol yr (or 1.29 kg yr) of operation are presented. From these data a new half life time for the ββ0v-decay of 76Ge to the ground state of 76Se of T 1 2 1.4 (2.5) X 10 24 yr with 90% (68%) CL can be deduced. For a possible neutrinoless decay to the first excited state a half life of 4.3(8.2)X1023 yr can be excluded with 90% (68%) CL

New experimental limits for electron decay and charge conservation

Abstract New experimental limits for the decay e− → γ + νe are reported. The lower limit for the half-life of this decay mode is T e 1 2 > 1.63 × 10 25 yr (68% CL). The data were collected for 3199 h by using one of the enriched germanium detectors of the Heidelberg-Moscow ββ Collaboration. This detector has an active volume of 591 cm3. This value is up to now the most stringent laboratory limit for this decay mode. Also charge nonconservation in nuclei is shortly discussed in the GaGe system using the data of gallium solar neutrino experiments