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The authors describe a tropical cyclone risk model for the Philippines using open-source methods that can be straightforwardly generalized to other countries. Wind fields derived from historical observations, as well as those from an environmentally forced tropical cyclone hazard model, are combined with data representing exposed value and vulnerability to determine asset losses. Exposed value is represented by the LitPop dataset, which assumes total asset value is distributed across a country following population density and night-lights data. Vulnerability is assumed to follow a functional form previously proposed by Emanuel, with free parameters chosen by a sensitivity analysis in which simulated and historical reported damages are compared for different parameter values and further constrained by information from household surveys about regional building characteristics. Use of different vulnerability parameters for the region around Manila, Philippines, yields much better agreement between simulated and actually reported losses than does a single set of parameters for the entire country. Despite the improvements from regionally refined vulnerability, the model predicts no losses for a substantial number of destructive historical storms, a difference the authors hypothesize is due to the use of wind speed as the sole metric of tropical cyclone hazard, omitting explicit representation of storm surge and/or rainfall. Bearing these limitations in mind, this model can be used to estimate return levels for tropical cyclone-caused wind hazards and asset losses for regions across the Philippines, relevant to some disaster risk reduction and management tasks; this model also provides a platform for further development of open-source tropical cyclone risk modeling.

The authors describe a tropical cyclone risk model for the Philippines, using methods that are open-source and can be straightfor-wardly generalized to other countries. Wind fields derived from historical observations, as well as those from an environmentally forced tropical cyclone hazard model (using environmental forcing from the recent historical period) are combined with data representing exposed value and vulnerability to determine asset losses. Exposed value is represented by the LitPop dataset, which assumes total asset value is distributed across a country following population density and nightlights data. Vulnerability is assumed to follow a functional form previously proposed by Emanuel, with free parameters chosen by a sensitivity analysis in which simulated and historical reported damages are compared for different parameter values. Use of different vulnerability parameters for the region around Manila yields much better agreement between simulated and actually reported losses than does a single set of parameters for the entire country. Even then, however, the model predicts no losses for a substantial number of historical storms which did in fact produce them, a difference the authors hypothesize is at least in part due to the use of wind speed as the sole metric of TC hazard, omitting explicit representation of flooding due to storm surge and/or rainfall.

The intrinsic temporal nature of magnetic reconnection at the magnetopause has been an active area of research. Both temporally steady and intermittent reconnection have been reported. We examine the steadiness of reconnection using space-ground conjunctions under quasi-steady solar wind driving. The spacecraft suggests that reconnection is first inactive, and then activates. The radar further suggests that after activation, reconnection proceeds continuously but unsteadily. The reconnection electric field shows variations at frequencies below 10 mHz with peaks at 3 and 5 mHz. The variation amplitudes are ∼10-30 mV/m in the ionosphere, and 0.3-0.8 mV/m at the equatorial magnetopause. Such amplitudes represent 30%-60% of the peak reconnection electric field. The unsteadiness of reconnection can be plausibly explained by the fluctuating magnetic field in the turbulent magnetosheath. A comparison with a previous global hybrid simulation suggests that it is the foreshock waves that drive the magnetosheath fluctuations, and hence modulate the reconnection.

Learning Objectives: Understand what residents perceive as obstacles to receiving feedback. Understand the areas in which residents want more feedback.Objective: Feedback is perhaps the most important part of the educational process and how residents learn the art and the practice of medicine. Because of its importance, residency programs and all faculty members should constantly strive to improve the process. We sought to analyze the areas our residents believed they could use more feedback and what they perceived as obstacles to obtaining productive feedback.Methods: Using an online, anonymous survey, all the residents in a 3-year emergency medicine residency program were asked about the feedback they receive. They were asked about the areas in which they receive the most feedback, the areas in which they would like more feedback, and what they perceive as the obstacles to getting good feedback.Results: 94% of residents said they would like more feedback (44% said “much more,” 50% said “a little more.”) When asked about the areas in which they get the most feedback, 67% of respondents said they get the most feedback about charting/documentation and 20% said they get the most feedback about clinical care. When asked about the areas in which they wish they had more feedback, 94% would like more feedback on clinical care with critically-ill patients, 81% wanted more feedback on clinical care in non-critically-ill patients, and 44% wanted more feedback with procedures. 38% wanted more feedback about interactions with consultants, while only 31% wanted more feedback about interactions with patients. When asked about the obstacles to getting constructive feedback, 94% identified the patient volume / workload, while 63% identified the system being used (New Innovations.)Conclusion: Despite the emphasis our program puts on feedback, residents still perceive that there is not enough, especially when it comes to clinical care. Surveys like this can be eye-opening and will hopefully lead to changes in faculty behavior to improve the teaching we provide.

Learning Objectives: Understand how residency programs track procedures. Understand how real-time procedure tracking can improve documentation. Understand how real-time procedure tracking can make SIM labs more efficient.Objective: Tracking of residency procedures is vital to the continued accreditation of Emergency Medicine (EM) residency programs. We sought to determine if a Procedural Achievement Count Evaluation (PACE) score utilization increases ACGME procedural reporting.Methods: A spreadsheet was created on Google Sheets, which contains the names of all the residents and the ACGME required procedures. The minimum procedural threshold is divided by the total months of residency (36) and then multiplied by each resident’s month in training. We termed the minimal monthly requirement the PACE score. Each resident’s tallied procedures are compared to the PACE value. Residents had open access to the Google Sheets PACE score, attendings were educated monthly, and residents additionally were educated at their semi-annual exams regarding their comparative score. Documented procedures were subdivided into “live” or “SIM”. The number of procedures reported by the third year classes one year before and one year after implementation were tallied. The number of procedures compared to the minimum ACGME requirement were calculated. A two-tailed Wilcoxon Signed-Rank test was utilized, with a p-value of less than 0.05 for statistically significant.Results: Of the fifteen core procedures reported to the ACGME, 87% (N=13) had increased totals following implementation (P=0.004). The only two procedures without increases were pericardiocentesis and central lines. The average percent increase of all procedures when compared to the minimum requirement was 37% (95% CI, 23,46). The number of live procedures increased in 60% (N=9) of procedures (p=0.06). Additionally, SIM procedures increased in 86% of those procedures that utilized SIM. (N=6 procedures, p=NS). The average percentage increase of SIM procedures was 24% (95% CI, 18,36).Conclusion: Utilization of a PACE score significantly improved ACGME procedural reporting numbers overall and specifically increased SIM utilization.

Learning Objective: Understand how residents’ living situations and support structure might affect their wellness.Background: EM residents are known to be high-risk for depression; in all likelihood the Covid-19 pandemic added to this risk. In addition to the understandable work stressors, social isolation caused by the lockdowns likely has affected their support structure.Objectives: Using validated psychometric testing, we sought to determine the levels of depression, anxiety, and stress in EM residents in a region severely impacted by the pandemic. We hypothesized that residents living alone would have more depression, anxiety and stress than those living with family or other roommates.Methods: Setting: An EM residency program in the state greatly affected by Covid-19. All EM residents were surveyed a year into the pandemic using the Depression, Anxiety, Stress Scales (DASS). This scale has been validated in the psychology literature across multiple settings. Surveys were anonymous to promote honesty. Residents were also surveyed about their living situations and then separated into two groups based on whether they lived alone or with other people. Levels of depression, anxiety, and stress were determined for each group and compared. Differences between the groups and 95% confidence intervals (CI) were calculated.Results: 26 of 27 residents (96%) completed the survey. 12 residents lived by themselves and 16 residents lived with others. In terms of depression, the incidence was 58% for those living alone vs. 23% for those living with others (Difference -29%, CI: -69,11). In terms of anxiety, the incidence was 33% for those living alone vs 29% for those living with others (Difference -4%, CI: -43,35). In terms of stress, the incidence was 50% vs. 43% for those living with others (Difference -7%, CI:-49,35).Conclusion: During the pandemic, the rates of depression, anxiety and stress in emergency residents as measured by the DASS are high overall, but with the small sample size no differences between those who live alone and those that live with others was shown.

Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced "verse"), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH).

The role a geospace plume in influencing the efficiency of magnetopause reconnection is an open question with two contrasting theories being debated. A local-control theory suggests that a plume decreases both local and global reconnection rates, whereas a global-control theory argues that the global reconnection rate is controlled by the solar wind rather than local physics. Observationally, limited numbers of point measurements from spacecraft cannot reveal whether a local change affects the global reconnection. A distributed observatory is hence needed to assess the validity of the two theories. We use THEMIS and Los Alamos National Laboratory spacecraft to identify the occurrence of a geospace plume and its contact with the magnetopause. Global evolution and morphology of the plume is traced using GPS measurements. SuperDARN is then used to monitor the distribution and the strength of dayside reconnection. Two storm-time geospace plume events are examined and show that as the plume contacts the magnetopause, the efficiency of reconnection decreases at the contact longitude. The amount of local decrease is 81% and 68% for the two events, and both values are consistent with the mass loading effect of the plume if the plume's atomic mass is ∼4 amu. Reconnection in the surrounding is enhanced, and when the solar wind driving is stable, little variation is seen in the cross polar cap potential. This study illuminates a pathway to resolve the role of cold dense plasma on solar wind-magnetosphere coupling, and the observations suggest that plumes redistribute magnetopause reconnection activity without changing the global strength substantially.

PurposeThe analysis of cancer biology data involves extremely heterogeneous data sets, including information from RNA sequencing, genome-wide copy number, DNA methylation data reporting on epigenetic regulation, somatic mutations from whole-exome or whole-genome analyses, pathology estimates from imaging sections or subtyping, drug response or other treatment outcomes, and various other clinical and phenotypic measurements. Bringing these different resources into a common framework, with a data model that allows for complex relationships as well as dense vectors of features, will unlock integrated data set analysis.MethodsWe introduce the BioMedical Evidence Graph (BMEG), a graph database and query engine for discovery and analysis of cancer biology. The BMEG is unique from other biologic data graphs in that sample-level molecular and clinical information is connected to reference knowledge bases. It combines gene expression and mutation data with drug-response experiments, pathway information databases, and literature-derived associations.ResultsThe construction of the BMEG has resulted in a graph containing > 41 million vertices and 57 million edges. The BMEG system provides a graph query-based application programming interface to enable analysis, with client code available for Python, Javascript, and R, and a server online at bmeg.io. Using this system, we have demonstrated several forms of cross-data set analysis to show the utility of the system.ConclusionThe BMEG is an evolving resource dedicated to enabling integrative analysis. We have demonstrated queries on the system that illustrate mutation significance analysis, drug-response machine learning, patient-level knowledge-base queries, and pathway level analysis. We have compared the resulting graph to other available integrated graph systems and demonstrated the former is unique in the scale of the graph and the type of data it makes available.