Cooperative passing network features are associated with successful match outcomes in the Australian Football League

Collective behaviour is an important component of team performance in team sports. This study used a binomial generalised linear mixed effects regression model to investigate the relationship between cooperative passing network characteristics and match outcomes of professional Australian Football League competition games across four seasons between 2016 and 2019. It divided a sample of 1629 observations into a training and testing partition used to develop and assess the validity of the model used in this study, respectively. The results of this study reveal that a team's connectedness is associated with the probability of winning Australian Football League games (Akaike Information Criterion = 1637.3, residual df= 1297, deviance = 1625.3). When most players within a team are involved in the team's passing network bidirectionally (i.e. a well-connected network; odds ratio = 1.053; 95% confidence interval: 4.2–6.5%, p < 0.001), teams have a higher probability of winning. The centralisation of a team's passing network was not significantly related to match outcomes. The classification accuracy for the model associating network characteristics with match outcomes was 69%. Collectively, these findings suggest that Australian Football League-specific network features should be incorporated within existing performance analysis methods and can provide a useful, practical tool for coaches to measure collective performance during team practice.

15 2020 CaRMS Residency Match Confirms Popularity of Pediatrics

Primary Subject area Medical Education Background Longitudinal data about the interest in, and competitiveness of, pediatric postgraduate training in Canada has not been reported. Objectives 1. To describe the results of the 2020 CaRMS pediatric residency match with respect to application rates, first-choice discipline choices, and succesful match rates by gender. 2. To examine the trend of these indices over the past decade. Design/Methods Data from the 2020 Canadian Residency Matching Service (CaRMS) pediatric residency match was evaluated and compared over the past decade. Residency match data from other programs was also used for some comparison reporting. Results Of a total pool of 2998 Canadian medical graduate (CMG) applicants in 2020, 305 (10.2%) applied to pediatrics, and 17 of these latter applicants (5.6%) applied solely to pediatrics. In the first iteration CaRMS match, pediatrics was the first-choice discipline for 177 CMG applicants (6.0% of all first choices). Pediatrics has been consistent as a first-choice discipline over the years: 5.9% (2017), 5.5% (2015), and 6.1% (2013). Of the 155 first-year positions offered in pediatrics this year, all were filled. Of those CMGs who matched to pediatrics in 2020, the specialty was the first-choice discipline for 128 applicants (92.8%) and the second-choice discipline for 9 applicants (6.5%). There were clear gender differences noted. Pediatrics accounted for 8.3% of female and 3.2% of male first-choice disciplines. Of the 135 females whose first-choice discipline was pediatrics, 101 matched to that first choice (74.8%). Of the 41 males whose first-choice discipline was pediatrics, 26 matched to that first choice (63.4%). Since 1995 (at CaRMS’ inception), the rates of first-choice discipline choice by gender have been quite stable (Table 1), with females consistently higher than males, while the first-choice discipline matching rate by gender have varied (Figure 1). Forty CMG applicants whose first-choice discipline was pediatrics matched to an alternate discipline choice and nine went unmatched, suggesting that pediatrics continues to be a competitive discipline. The pediatric rate of first-choice discipline matching to another alternate choice of 22.6% (40/177) is comparable to Anesthesia (22.1%; 34/154), Ophthalmology (26.7%; 20/75), and Otolaryngology (20.9%; 9/43). Conclusion Pediatrics continues to be a top specialty choice for graduates of Canadian medical schools, according to data from the 2020 CaRMS match. There are gender differences noted in the choice of pediatrics as a first-choice discipline, and in the successful match rate to pediatrics programs. The rate of successful first-choice discipline matching by gender have varied over time, with the past two years showing significantly greater matching success for females. These trends in the CaRMS pediatric data have implications on discipline recruitment and the pediatric workforce in Canada, and merit further exploration.

Use of PhenoCam Measurements and Image Analysis to Inform the ALMANAC Process-based Simulation Model

Near-surface remote sensing has been used to document seasonal growth patterns (i.e. phenology) for plant communities in diverse habitats. Phenology from this source may only apply to the area within the images. Meanwhile ecosystem models can accommodate variable weather and landscape differences to plant growth, but accuracy is improved by adding ground-truthed inputs. The objective of this study was to use PhenoCam data, image analysis, and Beer’s law with established extinction coefficients to compare leaf area index (LAI) development in the ALMANAC model for diverse plant types and environments. Results indicate that PhenoCam time series imagery can be used to improve leaf area development in ALMANAC by adjusting parameter values to better match LAI derived values in new diverse environments. Soybeans, mesquite, and maize produced the most successful match between the model simulations and PhenoCam data out of the eight species simulated. This study represents, to our knowledge, the first independent evaluation of the ALMANAC process-based plant growth model with imagery in agroecosystems available from the PhenoCam network. The results show how PhenoCam data can make a valuable contribution to validate process-based models, making these models much more realistic and allows for expansion of PhenoCam influence.

Otolaryngology Applicant Characteristics and Trends: Comparing OTO-HNS with Peer Specialties

Purpose: To evaluate the recent Otolaryngology-Head and Neck Surgery (OTO-HNS) applicant characteristics, to identify which applicant characteristics are associated with successful match into OTO-HNS, and to compare OTO-HNS applicant trends and characteristics to that of peer surgical specialties (PS). Materials and Methods: Data were obtained from official reports by the National Residency Matching Program (NRMP) for OTO-HNS, plastic and reconstructive surgery, orthopedic surgery, neurosurgery, and dermatology from 2006 to 2019. Alpha Omega Alpha (AOA) membership, United States Medical Licensing Examination (USMLE) scores, research productivity, graduation from a top-40 NIH-funded U.S. medical school, and additional graduate degree were recorded. Odds ratios (OR) were calculated to evaluate the relationship between applicant qualifications and match success. Results: From 2014 to 2018, the OTO-HNS applicant pool shrunk from 443 to 333, representing the largest drop of all PS. Furthermore, OTO-HNS reported the most unfilled positions and highest match rates in 2017 (n = 14; 92.1%) and 2018 (n = 12; 94.6%) among any PS. Despite recent trends, 2019 NRMP data revealed a 38.74% increase in OTO-HNS applicant numbers compared to 2018. AOA membership (OR, 7.3; P = .030), USMLE Step 2 scores between 241 and 260 (OR, 6.5; P = .009), and research productivity (OR, 5.6; P = .005) significantly increased the odds of matching into OTO-HNS. Conclusions: Despite recent fluctuations in application trends, OTO-HNS continues to successfully match highly qualified applicants, including applicants with AOA membership, high Step 2 scores, and high research productivity. An understanding of the qualifications used to evaluate residency applicants may be helpful to both applicants and residency programs of OTO-HNS.

Comparisons of image-matching software when identifying pool frog (Pelophylax lessonae) individuals from a reintroduced population

Photographic identification of individual animals is a non-invasive and cost-effective method that can provide demographic information on wild populations. This study aims to compare two photo-matching algorithms (Wild- ID and I3S-Spot) using a reintroduced population of pool frogs (Pelophylax lessonae) in the UK as a case study. We compared the following parameters 1) sex and age, 2) image quality, 3) image collection size and 4) processing time to evaluate successful image match rates. There were no significant differences in successful match rates found between sex and age groups. Wild-ID was more sensitive to image quality than I3S-Spot. There was a significant negative relationship between image collection size and successful match rates for I3S-Spot, however, no such relationship for Wild-ID. The findings of our study can be used by conservation practitioners to reduce workload and improve accuracy during population monitoring activities.

Multimodal Multiobject Tracking by Fusing Deep Appearance Features and Motion Information

Multiobject Tracking (MOT) is one of the most important abilities of autonomous driving systems. However, most of the existing MOT methods only use a single sensor, such as a camera, which has the problem of insufficient reliability. In this paper, we propose a novel Multiobject Tracking method by fusing deep appearance features and motion information of objects. In this method, the locations of objects are first determined based on a 2D object detector and a 3D object detector. We use the Nonmaximum Suppression (NMS) algorithm to combine the detection results of the two detectors to ensure the detection accuracy in complex scenes. After that, we use Convolutional Neural Network (CNN) to learn the deep appearance features of objects and employ Kalman Filter to obtain the motion information of objects. Finally, the MOT task is achieved by associating the motion information and deep appearance features. A successful match indicates that the object was tracked successfully. A set of experiments on the KITTI Tracking Benchmark shows that the proposed MOT method can effectively perform the MOT task. The Multiobject Tracking Accuracy (MOTA) is up to 76.40% and the Multiobject Tracking Precision (MOTP) is up to 83.50%.

How Well Do Medical Students at the Regional Medical Campus Match?: A 6-year Analysis at a Single Medical School.

ABSTRACT Introduction: Anecdotally, some students and faculty members alike have at times expressed concern that medical students who train at Regional Medical Campuses (RMC) will be disadvantaged in the National Residency Matching Program (NRMP), and may not achieve the same level of success as their peers at the main academic medical center. This project was undertaken to examine the validity of these concerns at the RMC affiliated with the Penn State Hershey College of Medicine (PSCOM). Methods: Results from the annual NRMP process were analyzed over a 6-year period (2014-2019), for both the main Hershey Campus (HC) and University Park Regional Campus (UPRC). Comparisons included the types of residencies selected, percent of students matching instate, percent matching in primary care specialties, and number having to participate in the supplemental offer and acceptance process (SOAP). All results were expressed as simple percentages. Results: During the study period, 819 students graduated from PSCOM (723 - Hershey Campus, 96 - UPRC). In total, 28 of the 723 Hershey Campus graduates (3.9%) and 1 of the 96 UPRC graduates (1%) went through the SOAP process. UPRC students were more likely to match into primary care specialties (44.8% (UPRC) vs 33.2% (Hershey Campus), defined as Medicine, Pediatrics, Family Medicine and Obstetrics-Gynecology, as well as stay within the state of Pennsylvania for their residency (34.4% - UPRC vs 31.7% - Hershey Campus). While the UPRC students more frequently matched into primary care specialties, several matched into highly competitive specialties, including ophthalmology, orthopedic surgery, otolaryngology, diagnostic radiology, and neurosurgery. Conclusions: Concerns frequently expressed regarding a successful match for students studying at regional medical campuses are not supported by our findings. Compared to their main campus peers, the UPRC medical students have been equally successful in the NRMP match.

Primary Language in Relation to Knowledge of Diagnosis and Sun-Related Behaviors in Adults with Sun-Exacerbated Dermatoses

Objective: To evaluate how patients’ primary spoken language influences the understanding of their disorder and their subsequent sun-related behaviors. Methods: This was a cross-sectional study conducted between February 2015 and July 2016 in two outpatient dermatology clinics among 419 adults with a sun-exacerbated dermatosis. The primary outcome was a successful match between the patient-reported diagnosis on a survey and the dermatologist-determined diagnosis. Results: Of participants, 42% were native English speakers, and 68% did not know their diagnosis. Fewer non-native English speakers identified one risk factor for their condition (46% versus 54%, p < 0.01). A greater number of non-native English speakers were less familiar with medical terminology. Native English speakers were 2.5 times more likely to know their diagnosis compared to non-native speakers (adjusted odds (aOR) 2.5, 95% confidence interval, 1.32 to 4.5; p = 0.005). Additional factors associated with higher odds of knowing the diagnosis included: Higher education, sunscreen use, female gender, symptoms for 1–5 years, and diagnosis of melasma and postinflammatory hyperpigmentation (PIH). Conclusions: Knowledge of the diagnosis and understanding of factors that may influence skin disease may promote conscious sun behavior. Patients who knew that their diagnosis was sun-exacerbated had higher odds of wearing sunscreen.