An asymptotic formula for integer points on Markoff-Hurwitz varieties

We establish an asymptotic formula for the number of integer solutions to the Markoff-Hurwitz equation x21+x22+⋯+x2n=ax1x2⋯xn+k. When n≥4, the previous best result is by Baragar (1998) that gives an exponential rate of growth with exponent β that is not in general an integer when n≥4. We give a new interpretation of this exponent of growth in terms of the unique parameter for which there exists a certain conformal measure on projective space

Failure of interpolation in the intuitionistic logic of constant domains

This paper shows that the interpolation theorem fails in the intuitionistic logic of constant domains. This result refutes two previously published claims that the interpolation property holds.Comment: 13 pages, 0 figures. Overlaps with arXiv 1202.1195 removed, the text thouroughly reworked in terms of notation and style, historical notes as well as some other minor details adde

Image analysis as an adjunct to manual HER-2 immunohistochemical review: a diagnostic tool to standardize interpretation

Dobson L, Conway C, Hanley A, Johnson A, Costello S, O’Grady A, Connolly Y, Magee H, O’Shea D, Jeffers M & Kay E (2010) Histopathology57, 27–38 Image analysis as an adjunct to manual HER-2 immunohistochemical review: a diagnostic tool to standardize interpretatio

Low Cost Gunshot Detection using Deep Learning on the Raspberry Pi

Many cities using gunshot detection technology depend on expensive systems that ultimately rely on humans differentiating between gunshots and non-gunshots, such as ShotSpotter. Thus, a scalable gunshot detection system that is low in cost and high in accuracy would be advantageous for a variety of cities across the globe, in that it would favorably promote the delegation of tasks typically worked by humans to machines. A repository of audio data was created from sound clips collected from online audio databases as well as from clips recorded using a USB microphone in residential areas and at a gun range. One-dimensional as well as two-dimensional convolutional neural networks were then trained on this sound data, and spectrograms created from this sound data, to recognize gunshots. These models were deployed to a Raspberry Pi 3 Model B+ with a short message service modem and a USB microphone attached, using a software pipeline to continuously analyze discrete two-second chunks of audio and alert a set of phone numbers if a gunshot is detected in that chunk. Testing found that a majority-rules ensemble of our one-dimensional and two-dimensional models fared best, with an accuracy above 99% on validation data as well as when distinguishing gunshots from fireworks. Besides increasing the safety standards for a city's residents, the findings generated by this research project expand the current state of knowledge regarding sound-based applications of convolutional neural networks

The GstLAL template bank for spinning compact binary mergers in the second observation run of Advanced LIGO and Virgo

We describe the methods used to construct the aligned-spin template bank of gravitational waveforms used by the GstLAL-based inspiral pipeline to analyze data from the second observing run of Advanced LIGO and Virgo. The bank expands upon the parameter space covered during the first observing run, including coverage for merging compact binary systems with total mass between 2 $\mathrm{M}_{\odot}$ and 400 $\mathrm{M}_{\odot}$ and mass ratios between 1 and 97.989. Thus the systems targeted include merging neutron star-neutron star systems, neutron star-black hole binaries, and black hole-black hole binaries expanding into the intermediate-mass range. Component masses less than 2 $\mathrm{M}_{\odot}$ have allowed (anti-)aligned spins between $\pm0.05$ while component masses greater than 2 $\mathrm{M}_{\odot}$ have allowed (anti-)aligned between $\pm0.999$. The bank placement technique combines a stochastic method with a new grid-bank method to better isolate noisy templates, resulting in a total of 677,000 templates.Comment: 9 pages, 13 figure

The Grizzly, December 6, 2007

Students: Fresh Produce on Sale Now • Relay for Life Kicks Off in Fanfare • Wings for Wishes Hosts Competitive Eating Contest • Balancing Act: Avoiding Weight Gain in College • Beer and the Bedroom • Soulja Boy to the Rescue • Trappe Tavern: It\u27s a Trap! • Hell is Other People • Ursinus Student Video Blogs in Japan • Opinions: Why Terrorists Do What They Do; New Homepage Long Overdue • Bears Off to a 1-0 Start in League • Fresh Faces on the Women\u27s Court • Preview of UC Winter Sportshttps://digitalcommons.ursinus.edu/grizzlynews/1752/thumbnail.jp

The Clicker Study

Purpose: A recent study in orthopedics showed that clicker-based learning was more effective than traditional feedback when teaching procedures. We sought to determine whether this principle is applicable to ultrasound skills. Methods: Our prospective randomized control trial used a population of new ultrasound learners. Exclusion criteria included previous ultrasound experience of more than one hour. Students were shown an instructional video on the Focused Assessment with Sonography in Trauma (FAST) exam and randomized to receive clicker or scripted feedback. Each student performed the FAST exam once without feedback, then with either scripted or clicker-based feedback. They were timed and scored on 18 microskills. Results and Conclusions: 45 students were enrolled in the study, with 6 excluded from analysis. This included 24 premedical and 15 medical students. No significant differences were observed between groups for time or accuracy on the FAST exam. Among medical students, there was a trend toward faster results in the clicker group (mean=83 seconds) than the script group (mean=103 seconds) (p=0.22). Among undergraduates, there was a trend toward higher accuracy in the script group (mean=100%) than the clicker group (mean=95%) (p=0.068) and towards faster performance (mean=103 seconds) than the clicker group (mean=121 seconds) (p=0.38). Although no significant differences were observed, there seemed to be a trend toward faster performance with clicker feedback among medical students and faster and more accurate performance with scripted feedback among premedical students. This may be an area for future study