Sparse Array Design via Fractal Geometries

Sparse sensor arrays have attracted considerable attention in various fields such as radar, array processing, ultrasound imaging and communications. In the context of correlation-based processing, such arrays enable to resolve more uncorrelated sources than physical sensors. This property of sparse arrays stems from the size of their difference coarrays, defined as the differences of element locations. Thus, the design of sparse arrays with large difference coarrays is of great interest. In addition, other array properties such as symmetry, robustness and array economy are important in different applications. Numerous studies have proposed diverse sparse geometries, focusing on certain properties while lacking others. Incorporating multiple properties into the design task leads to combinatorial problems which are generally NP-hard. For small arrays these optimization problems can be solved by brute force, however, in large scale they become intractable. In this paper, we propose a scalable systematic way to design large sparse arrays considering multiple properties. To that end, we introduce a fractal array design in which a generator array is recursively expanded according to its difference coarray. Our main result states that for an appropriate choice of the generator such fractal arrays exhibit large difference coarrays. Furthermore, we show that the fractal arrays inherit their properties from their generators. Thus, a small generator can be optimized according to desired requirements and then expanded to create a fractal array which meets the same criteria. This approach paves the way to efficient design of large arrays of hundreds or thousands of elements with specific properties.Comment: 16 pages, 9 figures, 1 Tabl

What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems

Estimating uncertainty in image-to-image networks is an important task, particularly as such networks are being increasingly deployed in the biological and medical imaging realms. In this paper, we introduce a new approach to this problem based on masking. Given an existing image-to-image network, our approach computes a mask such that the distance between the masked reconstructed image and the masked true image is guaranteed to be less than a specified threshold, with high probability. The mask thus identifies the more certain regions of the reconstructed image. Our approach is agnostic to the underlying image-to-image network, and only requires triples of the input (degraded), reconstructed and true images for training. Furthermore, our method is agnostic to the distance metric used. As a result, one can use $L_p$-style distances or perceptual distances like LPIPS, which contrasts with interval-based approaches to uncertainty. Our theoretical guarantees derive from a conformal calibration procedure. We evaluate our mask-based approach to uncertainty on image colorization, image completion, and super-resolution tasks, demonstrating high quality performance on each

Weakly-Supervised Surgical Phase Recognition

A key element of computer-assisted surgery systems is phase recognition of surgical videos. Existing phase recognition algorithms require frame-wise annotation of a large number of videos, which is time and money consuming. In this work we join concepts of graph segmentation with self-supervised learning to derive a random-walk solution for per-frame phase prediction. Furthermore, we utilize within our method two forms of weak supervision: sparse timestamps or few-shot learning. The proposed algorithm enjoys low complexity and can operate in lowdata regimes. We validate our method by running experiments with the public Cholec80 dataset of laparoscopic cholecystectomy videos, demonstrating promising performance in multiple setups

Migrated maxillary implant removed via semilunar hiatus by transnasal endoscope.

Endoscopic surgery via nasal approach to remove the implant body from the semilunar hiatus is presented with the images of the computed tomography and the intraoperative endoscopic findings

Changing trends in β-hemolytic streptococcal bacteremia in Manitoba, Canada:2007-2012

OBJECTIVES: European surveillance studies have reported an increasing incidence of β-hemolytic group G streptococcal bacteremia, but no studies have evaluated trends in β-hemolytic streptococcal bacteremia in North America. METHODS: We reviewed bacteremic episodes and positive throat swab cultures from two tertiary care centers in Manitoba, Canada, from January 2007 to December 2012. RESULTS: During the study period, 19 864 bacteremic episodes, and 9948 positive throat swabs were identified. There were 1025 (5.16%) bacteremic episodes attributable to β-hemolytic streptococci: 425 (2.03%), 339 (1.71%), 62 (0.31%), and 199 (0.95%) to β-hemolytic groups A, B, C, and G streptococci, respectively. From 2007 to 2012, there were significant increases in the proportion of bacteremia attributable to β-hemolytic streptococci in general (6.32% vs. 4.02%; p<0.0001; linear trend test, p<0.0001), and to groups G (1.49% vs. 0.43%; p<0.0001; linear trend test, p<0.0001) and C (0.58% vs. 0.13%; p=0.0068; linear trend test, p=0.0105) β-hemolytic streptococci in particular. Bacteremia attributable to groups A and B β-hemolytic streptococci and Streptococcus pneumoniae were unchanged. There were no changes in the distribution of β-hemolytic streptococcal groups among throat swabs. CONCLUSIONS: Bacteremia attributable to β-hemolytic groups G and C streptococci increased in Manitoba, Canada. Further study of the factors underlying these changes is required

Effect of Seven-Valent Pneumococcal Conjugate Vaccine on Staphylococcus aureus Colonisation in a Randomised Controlled Trial

Background: Heptavalent pneumococcal conjugate vaccine (PCV7) shifts nasopharyngeal colonisation with vaccine serotype pneumococci towards nonvaccine serotypes. Because of the reported negative association of vaccine serotype pneumococci and Staphylococcus aureus in the nasopharynx, we explored the effect of PCV7 on nasopharyngeal colonisation with S. aureus in children and parents. Methodology/Principal Findings: This study was part of a randomised controlled trial on the effect of PCV7 on pneumococcal carriage, enrolling healthy newborns who were randomly assigned (1: 1: 1) to receive PCV7 (1) at 2 and 4 months of age (2) at 2, 4 and 11 months or (3) no PCV7 (controls). Nasopharyngeal colonisation of S. aureus was a planned secondary outcome. Nasopharyngeal swabs were obtained from all children over a 2-year period with 6-months interval and from one parent at the child's age of 12 and 24 months and cultured for Streptococcus pneumoniae and S. aureus. Between July 2005 and February 2006, 1005 children were enrolled and received either 2-doses of PCV7 (n = 336), 2+1-doses (336) or no dose (n = 333) before PCV7 implementation in the Dutch national immunization program. S. aureus colonisation had doubled in children in the 2+1-dose group at 12 months of age compared with unvaccinated controls (10.1% versus 5.0%; p = 0.019). A negative association for co-colonisation of S. pneumoniae and S. aureus was observed for both vaccine serotype (adjusted odds ratio (aOR) 0.53, 95% confidence interval (CI) 0.38-0.74) and nonvaccine serotype pneumococci (aOR 0.67, 95% CI 0.52-0.88). Conclusions/Significance: PCV7 induces a temporary increase in S. aureus colonisation in children around 12 months of age after a 2+1-dose PCV7 schedule. The potential clinical consequences are unknown and monitoring is warranted