No abstract

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This case represents successful assisted reproductive technology quintuplets with monochorionic quadruplets and a co-sibling. Higher-order monozygotic pregnancies with monochorionic quadruplets are exceedingly rare and a potential complication of IVF.

Computer vision relies on labeled datasets for training and evaluation in detecting and recognizing objects. The popular computer vision program, YOLO ("You Only Look Once"), has been shown to accurately detect objects in many major image datasets. However, the images found in those datasets, are independent of one another and cannot be used to test YOLO's consistency at detecting the same object as its environment (e.g. ambient lighting) changes. This paper describes a novel effort to evaluate YOLO's consistency for large-scale applications. It does so by working (a) at large scale and (b) by using consecutive images from a curated network of public video cameras deployed in a variety of real-world situations, including traffic intersections, national parks, shopping malls, university campuses, etc. We specifically examine YOLO's ability to detect objects in different scenarios (e.g., daytime vs. night), leveraging the cameras' ability to rapidly retrieve many successive images for evaluating detection consistency. Using our camera network and advanced computing resources (supercomputers), we analyzed more than 5 million images captured by 140 network cameras in 24 hours. Compared with labels marked by humans (considered as "ground truth"), YOLO struggles to consistently detect the same humans and cars as their positions change from one frame to the next; it also struggles to detect objects at night time. Our findings suggest that stateof-the art vision solutions should be trained by data from network camera with contextual information before they can be deployed in applications that demand high consistency on object detection.

Currently no recommendation exists to collect genital culture for Chlamydia trachomatis and Neisseria gonorrhoeae at diagnosis of spontaneous abortion. A retrospective cross sectional study was performed to identify first trimester abortions with concurrent genital culture collection in an emergency room setting. The results were compared to most current 2015 Center for Disease Control (CDC) statistics. Among women aged 15-24 the rate of C. trachomatis was increased to 20.0% and greater than CDC rate of 6.7% (RR 2.97, p<0.0001). No positive screens for C. trachomatis were found above age 30 and the study rate of N. gonorrhoeae was not significantly elevated. Younger women presenting for miscarriage have high prevalence of C. trachomatis in comparison to 2015 CDC statistics. Routine genital culture could be recommended at diagnosis of first trimester spontaneous abortion.