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Cannabis retailer locations used to investigate geographic cannabis access are frequently ascertained from two sources: 1) webservices which provide locations of cannabis retailers (e.g., Yelp) or 2) government-maintained registries. Characterizing the operating status and location information accuracy of cannabis retailer data sources on a state-by-state level can inform research examining the health implications of cannabis legalization policies. This study ascertained cannabis retailer name and location from webservices and government-maintained registries for 26 states and the District of Columbia legalizing cannabis sales in 2019. Validation subsamples were created using state-level sequential sampling. Phone surveys were conducted by trained researchers for webservice samples (n=790, November 2019 - May 2020) and government-maintained registry (n=859, February - June 2020) to ascertain information about operating status and location. Accuracy was calculated as the percent agreement among subsample and phone survey data. For operating status and location, webservice derived data was 78% (614/790) and 79% (484/611) accurate, whereas government-maintained registry derived data was 76% (657/859) and 95% (622/655) accurate, respectively. Fifty-nine percent (15/27) of states and the District of Columbia had over 80% accuracy for operating status and 48% (13/27) states had over 80% accuracy for location information with both data sources. However, government-maintained registry derived information was more accurate in 33% (9/27) states for operating status and 41% (11/27) states for location information. Both data sources had similar operating status accuracy. Research using spatial analysis may prefer government-maintained registry derived data due to high location information accuracy, whereas studies looking at broad trends across states may prefer webservice derived. State level COVID-19 restrictions had minimal impact on ascertainment of cannabis retailer operating status and location information via phone survey derived from webservices and government-maintained registries.

Subgraph matching is a fundamental task in many applications which identifies all the embeddings of a query pattern in an input graph. Compilation-based subgraph matching systems generate specialized implementations for the provided patterns and often substantially outperform other systems. However, the generated code causes significant computation redundancy and the compilation process incurs too much overhead to be used online, both due to the inherent symmetry in the structure of the query pattern. In this paper, we propose an optimizing query compiler, named GraphZero, to completely address these limitations through symmetry breaking based on group theory. GraphZero implements three novel techniques. First, its schedule explorer efficiently prunes the schedule space without missing any high-performance schedule. Second, it automatically generates and enforces a set of restrictions to eliminate computation redundancy. Third, it generalizes orientation, a surprisingly effective optimization that was only used for clique patterns, to apply to arbitrary patterns. Evaluation on multiple query patterns shows that GraphZero outperforms two state-of-the-art compilation and non-compilation based systems by up to 40X and 2654X, respectively.

Background: Invasive streptococcus pyogenes infections are rarely seen in healthy children. The multifocal nature of the following case is unusual and presents a diagnostic and therapeutic challenge for the treating physician. Case presentation: In this case report, we discuss an otherwise healthy 11-year-old boy with a multifocal invasive streptococcus pyogenes infection presenting with a myriad of musculoskeletal complications at distant sites. He suffered from multiple abscesses, septic arthritis of sternoclavicular joint and multiple sites of osteomyelitis, osteitis and tenosynovitis in the neck hand and foot. A significant course of intravenous antibiotic therapy was required for resolution of disease.Conclusions: Streptococcus pyogenes is a common culprit in head and neck infections. This case is unique because of the multifocal nature of our patient’s infection. The Otolaryngologist – Head and Neck Surgeon should acknowledge the potential for rare and diffuse complications from invasive streptococcus pyogenes infection.

A common approach to localize a mobile robot is by measuring distances to points of known positions, called anchors. Locating a device from distance measurements is typically posed as a non-convex optimization problem, stemming from the nonlinearity of the measurement model. Non-convex optimization problems may yield suboptimal solutions when local iterative solvers such as Gauss-Newton are employed. In this paper, we design an optimality certificate for continuous-time range-only localization. Our formulation allows for the integration of a motion prior, which ensures smoothness of the solution and is crucial for localizing from only a few distance measurements. The proposed certificate comes at little additional cost since it has the same complexity as the sparse local solver itself: linear in the number of positions. We show, both in simulation and on real-world datasets, that the efficient local solver often finds the globally optimal solution (confirmed by our certificate), but it may converge to local solutions with high errors, which our certificate correctly detects., Comment: 10 pages, 7 figures, accepted to IEEE Robotics and Automation Letters (this arXiv version contains supplementary appendix)

Graph pattern matching searches a data graph for all instances of one or more query patterns. Since it is one of the most fundamental problems in graph analytics, many graph pattern matching systems have been proposed with distinct features to provide a mix of flexibility and performance, and it is generally accepted that distinct use cases may necessitate the use of different systems. In this paper, we propose Dryadic, a system which integrates comprehensive flexibility features, yet can still outperform four state-of-the-art graph pattern matching systems on the primary use cases they target. Unlike existing systems that employ a case-by-case design strategy, all functionalities of Dryadic are centered around a powerful intermediate representation, the computation tree structure, which encodes the matching algorithms for arbitrary patterns. Dryadic implements novel techniques to optimize the computation tree and maps it to different backends to perform compiled, interpreted, or distributed graph pattern matching. Extensive experiments on nine real-world graphs of different scales show that Dryadic, despite its all-in-one nature, is often one to three orders of magnitude faster than other systems in three common usage scenarios.

Andrew Chang,1 John Stokes,2,3 Lindy Priestman,4 Connor Holmes,4 Peter Said5 1Sydney Retina Clinic, Sydney Institute of Vision Science, Save Sight Institute, University of Sydney, Sydney, New South Wales, Australia; 2Inservio, Sydney, New South Wales, Australia; 3Department of Biomedical Sciences, Charles Sturt University, Orange, New South Wales, Australia; 4Atlantis Healthcare Pty Ltd, Sydney, New South Wales, Australia; 5Medical Affairs, Bayer Australia Ltd, Sydney, New South Wales, AustraliaCorrespondence: Andrew ChangSydney Retina Clinic, 187 Macquarie Street, Sydney, New South Wales, 2000, AustraliaTel + 61 2 92213755Fax + 61 2 92211637Email achang@sydneyretina.com.auPurpose: This study aimed to compare persistence between patients prescribed intravitreal aflibercept (IVT-AFL) for neovascular age-related macular degeneration (nAMD) in Australia enrolled on a patient support program (PSP) with that of a sample of patients from the Australian Pharmaceutical Benefits Scheme (PBS) dataset (10% PBS sample); explore predictors of persistence; describe changes in patient beliefs over the course of their enrollment in a PSP for patients treated with IVT-AFL for nAMD; and assess patient satisfaction.Participants and Methods: Participants prescribed IVT-AFL for the treatment of nAMD were invited to participate in the PSP. The PSP provided tailored support to patients through provision of a welcome pack, structured telephone calls, and information booklets. Persistence was defined in the PSP as the time from the start date in the program, until discontinuation from the program; and as the time from initial prescription until 6-months after the date of last prescription in the 10% PBS set. Persistence on the program and risk of discontinuation were modeled using Kaplan-Meier methods and Cox proportional hazards. In addition, persistence was compared between patients on the PSP and a 10% PBS sample of patients prescribed IVT-AFL for nAMD.Results: Persistence on treatment at 24 months was significantly higher in patients enrolled on the PSP compared to the PBS cohort (88% vs 64%, p< 0.05). The risk of discontinuation in patients enrolled on the PSP was higher in patients identified at screening as “high-risk”, those who were younger, or those with significant distance to travel for treatment. During the PSP, patients reported significant increase in their belief that they had control over their condition (6.1 ± 3.5 to 6.8 ± 3.7; p=0.0034) and a reduction in concerns about treatment. Satisfaction with the PSP was high.Conclusion: Patients provided with access to a PSP showed better persistence on treatment and improved beliefs about nAMD disease and its treatment compared to those in the PBS sample. Improved persistence rates may translate into better outcomes for the patient and the healthcare system, however, further research is required to determine which elements of the program are most beneficial, particularly to those at high risk of discontinuation.Keywords: intravitreal aflibercept, patient satisfaction, illness perceptions, medication beliefs, neovascular macular degeneration, persistence