Explaining Aviation Safety Incidents Using Deep Temporal Multiple Instance Learning

Although aviation accidents are rare, safety incidents occur more frequently and require a careful analysis to detect and mitigate risks in a timely manner. Analyzing safety incidents using operational data and producing event-based explanations is invaluable to airline companies as well as to governing organizations such as the Federal Aviation Administration (FAA) in the United States. However, this task is challenging because of the complexity involved in mining multi-dimensional heterogeneous time series data, the lack of time-step-wise annotation of events in a flight, and the lack of scalable tools to perform analysis over a large number of events. In this work, we propose a precursor mining algorithm that identifies events in the multidimensional time series that are correlated with the safety incident. Precursors are valuable to systems health and safety monitoring and in explaining and forecasting safety incidents. Current methods suffer from poor scalability to high dimensional time series data and are inefficient in capturing temporal behavior. We propose an approach by combining multiple-instance learning (MIL) and deep recurrent neural networks (DRNN) to take advantage of MIL's ability to learn using weakly supervised data and DRNN's ability to model temporal behavior. We describe the algorithm, the data, the intuition behind taking a MIL approach, and a comparative analysis of the proposed algorithm with baseline models. We also discuss the application to a real-world aviation safety problem using data from a commercial airline company and discuss the model's abilities and shortcomings, with some final remarks about possible deployment directions

Interpreting forest and grassland biome productivity utilizing nested scales of image resolution and biogeographical analysis

Several hardware, software, and data collection problems encountered were conquered. The Geographic Information System (GIS) data from other systems were converted to ERDAS format for incorporation with the image data. Statistical analysis of the relationship between spectral values and productivity is being pursued. Several project sites, including Jackson, Pope, Boulder, Smokies, and Huntington Forest are evolving as the most intensively studied areas, primarily due to availability of data and time. Progress with data acquisition and quality checking, more details on experimental sites, and brief summarizations of research results and future plans are discussed. Material on personnel, collaborators, facilities, site background, and meetings and publications of the investigators are included

MetaLab and metalabR: Facilitating dynamic meta-analyses in developmental psychology

Background: Developmental psychologists often make statements of the form “babies learn to do X at age Y”. Yet summaries made on the basis of one or a few studies can misrepresent a messy and complex evidence base. True results may also not be generalizable outside of the specific testing context for theoretically important reasons including the language or age of the infants. Other factors that are typically considered "noise" might also impede generalizability, including the lab where testing takes place, the type of stimuli, or the methods that were used. Systematic reviews and meta-analyses help bring coherence to a complex evidence base, control for confounds, and increase confidence in results. However, meta-analyses are underused in developmental research. Objective: To facilitate developmental researchers’ access to current meta-analyses, we created MetaLab (metalab.stanford.edu), a platform for open, dynamic meta-analytic datasets. In 6 years, the site has grown to 30 meta-analyses with data from 45,000 infants and children. A key feature is the standardized data storage format, which allows a unified framework for analysis and visualization. This facilitates the addition of new data points, resulting in community-augmented meta-analyses (CAMAs; Tsuji, Bergmann, & Cristia, 2014), which provide the most up-to-date summary of the body of literature. Use of this standardized format is facilitated by tailored documentation and our metalabR package, as follows. Method: The MetaLab website hosts tutorials for conducting a systematic review and quantitative synthesis. In progress are tutorials for researchers who are planning on conducting, or who have conducted, a study on a topic where a MetaLab CAMA already exists. These tutorials will help researchers decide on their methodology and sample size, based on the collated body of evidence, and to add their results to the CAMA when their study is complete. Currently in development, our new R package, metalabR, facilitates and standardizes the process of conducting and integrating meta-analyses with the MetaLab platform. Existing key features focus on ensuring adherence to our data format by providing functions for reading, validating, and cleaning new datasets and added data points, and calculating standardized effect sizes. Multiple datasets can be read into one dataframe to allow for meta-meta-analysis across different topics. MetalabR helps one access existing MetaLab functionalities for quantitative analysis, building on metafor (Viechtbauer, 2007) to run inverse-variance weighted multivariate meta-analytic models with random effects. The package also includes functions for data visualization, building on ggplot2 (Wickham, 2016) to create scatter, forest, funnel and violin plots, all with a standardized theme and colour scheme. In progress is a function for generating a summary report of results of random effects models appropriate for meta-analyses in experimental developmental psychology. In addition to using the metalabR package in R, various shinyapps can be accessed from the MetaLab website, which have a user-friendly interface and require no knowledge of R or coding. These are tools for visualizing MetaLab data, conducting power analyses and power simulations, and data validation tools to ensure a reviewer’s planned meta-analysis fits the MetaLab structure and format, so their data can eventually be integrated into MetaLab. Outlook: MetaLab facilitates the adoption of transparent, reproducible, and dynamic meta-analyses in developmental psychology along multiple dimensions. It contains tools for conducting a new meta-analysis, planning a study, contributing to an existing meta-analysis, and conducting a meta-meta-analysis across multiple meta-analyses. Our functionalities and interfaces are also easily adaptable for use outside of the field of developmental psychology, with one spinoff having been created for evidence synthesis of vocal patterns in neuropsychiatric conditions (Nyholm Jensen & Dwenger, 2020, metavoice.au.dk). We will continue to develop MetaLab and metalabR to accommodate different types of data, and interface with standards such as Brain Imaging Data Structure (BIDS, Gorgolewski et al., 2016) for neuroimaging datasets, thereby further broadening the scope and utility of MetaLab

Principles And Practices Fostering Inclusive Excellence: Lessons From The Howard Hughes Medical Institute’s Capstone Institutions

Best-practices pedagogy in science, technology, engineering, and mathematics (STEM) aims for inclusive excellence that fosters student persistence. This paper describes principles of inclusivity across 11 primarily undergraduate institutions designated as Capstone Awardees in Howard Hughes Medical Institute’s (HHMI) 2012 competition. The Capstones represent a range of institutional missions, student profiles, and geographical locations. Each successfully directed activities toward persistence of STEM students, especially those from traditionally underrepresented groups, through a set of common elements: mentoring programs to build community; research experiences to strengthen scientific skill/identity; attention to quantitative skills; and outreach/bridge programs to broaden the student pool. This paper grounds these program elements in learning theory, emphasizing their essential principles with examples of how they were implemented within institutional contexts. We also describe common assessment approaches that in many cases informed programming and created traction for stakeholder buy-in. The lessons learned from our shared experiences in pursuit of inclusive excellence, including the resources housed on our companion website, can inform others’ efforts to increase access to and persistence in STEM in higher education

Effect of a Cold Margin on Ice Flow at the Terminus of Storglaciaren, Sweden: Implications for Sediment Transfer

The cold-based termini of polythermal glaciers are usually assumed to adhere strongly to an immobile substrate and thereby supply significant resistance to the flow of warm-based ice upglacier. This compressive environment is commonly thought to uplift basal sediment to the surface of the glacier by folding and thrust faulting. We present model and field evidence from the terminus of Storglaciaren, Sweden, showing that the cold margin provides limited resistance to flow from up-glacier. Ice temperatures indicate that basal freezing occurs in this zone at 10−1 –10−2 ma−1, but model results indicate that basal motion at rates greater than 1ma−1 must, nevertheless, persist there for surface and basal velocities to be consistent with measurements. Estimated longitudinal compressive stresses of 20– 25 kPa within the terminus further indicate that basal resistance offered by the cold-based terminus is small. These results indicate that where polythermal glaciers are underlain by unlithified sediments, ice-flow trajectories and sediment transport pathways may be affected by subglacial topography and hydrology more than by the basal thermal regime

Video analysis and verification of direct head impacts recorded by wearable sensors in junior rugby league players

Background: Rugby league is a high-intensity collision sport that carries a risk of concussion. Youth athletes are considered to be more vulnerable and take longer to recover from concussion than adult athletes. Purpose: To review head impact events in elite-level junior representative rugby league and to verify and describe characteristics of X-patchTM-recorded impacts via video analysis. Study Design: Observational case series. Methods: The X-patchTM was used on twenty-one adolescent players (thirteen forwards and eight backs) during a 2017 junior representative rugby league competition. Game-day footage, recorded by a trained videographer from a single camera, was synchronised with X-patchTM-recorded timestamped events. Impacts were double verified by video review. Impact rates, playing characteristics, and gameplay situations were described. Results: The X-patchTM-recorded 624 impacts ≥ 20g between game start and finish, of which 564 (90.4%) were verified on video. Upon video review, 413 (73.2%) of all verified impacts ≥ 20g where determined to be direct head impacts. Direct head impacts ≥ 20g occurred at a rate of 5.2 impacts per game hour; 7.6 for forwards and 3.0 for backs (range = 0–18.2). A defender’s arm directly impacting the head of the ball carrier was the most common event, accounting for 21.3% (n = 120) of all impacts, and 46.7% of all “hit-up” impacts. There were no medically diagnosed concussions during the competition. Conclusion: The majority (90.4%) of head impacts ≥ 20g recorded by the X-patchTM sensor were verified by video. Double verification of direct head impacts in addition to cross-verification of sensor-recorded impacts using a secondary source such as synchronised video review can be used to ensure accuracy and validation of data

Accreditation council for graduate medical education (ACGME) annual anesthesiology residency and fellowship program review: a "report card" model for continuous improvement

<p>Abstract</p> <p>Background</p> <p>The Accreditation Council for Graduate Medical Education (ACGME) requires an annual evaluation of all ACGME-accredited residency and fellowship programs to assess program quality. The results of this evaluation must be used to improve the program. This manuscript describes a metric to be used in conducting ACGME-mandated annual program review of ACGME-accredited anesthesiology residencies and fellowships.</p> <p>Methods</p> <p>A variety of metrics to assess anesthesiology residency and fellowship programs are identified by the authors through literature review and considered for use in constructing a program "report card."</p> <p>Results</p> <p>Metrics used to assess program quality include success in achieving American Board of Anesthesiology (ABA) certification, performance on the annual ABA/American Society of Anesthesiology In-Training Examination, performance on mock oral ABA certification examinations, trainee scholarly activities (publications and presentations), accreditation site visit and internal review results, ACGME and alumni survey results, National Resident Matching Program (NRMP) results, exit interview feedback, diversity data and extensive program/rotation/faculty/curriculum evaluations by trainees and faculty. The results are used to construct a "report card" that provides a high-level review of program performance and can be used in a continuous quality improvement process.</p> <p>Conclusions</p> <p>An annual program review is required to assess all ACGME-accredited residency and fellowship programs to monitor and improve program quality. We describe an annual review process based on metrics that can be used to focus attention on areas for improvement and track program performance year-to-year. A "report card" format is described as a high-level tool to track educational outcomes.</p

Verifying head impacts recorded by a wearable sensor using video footage in rugby league: A preliminary study

Background: Rugby league is a full-contact collision sport with an inherent risk of concussion. Wearable instrumented technology was used to observe and characterize the level of exposure to head impacts during game play. Purpose: To verify the impacts recorded by the x-patch™ with video analysis. Study design: Observational case series. Methods: The x-patch™ was used on eight men’s semi-professional rugby league players during the 2016 Newcastle Rugby League competition (five forwards and three backs). Game day footage was recorded by a trained videographer using a single camera located at the highest midfield location to verify the impact recorded by the x-patch™. Videographic and accelerometer data were time synchronized. Results: The x-patch™ sensors recorded a total of 779 impacts ≥ 20 g during the games, of which 732 (94.0%) were verified on video. In addition, 817 impacts were identified on video that did not record an impact on the sensors. The number of video-verified impacts ≥ 20 g, per playing hour, was 7.8 for forwards and 4.8 for backs (range = 3.9–19.0). Impacts resulting in a diagnosed concussion had much greater peak linear acceleration (M = 76.1 g, SD = 17.0) than impacts that did not result in a concussion (M = 34.2g, SD = 18.0; Cohen’s d = 2.4). Conclusions: The vast majority (94%) of impacts ≥ 20 g captured by the x-patch™ sensor were video verified in semi-professional rugby league games. The use of a secondary source of information to verify impact events recorded by wearable sensors is beneficial in clarifying game events and exposure levels

Interpreting forest and grassland biome productivity utilizing nested scales of image resolution and biogeographical analysis

Data acquisition, initial site characterization, image and geographic information methods available, and brief evaluations of first-year for NASA's Thematic Mapper (TM) working group are presented. The TM and other spectral data are examined in order to relate local, intensive ecosystem research findings to estimates of carbon cycling rates over wide geographic regions. The effort is to span environments ranging from dry to moist climates and from good to poor site quality using the TM capability, with and without the inclusion of geographic information system (GIS) data, and thus to interpret the local spatial pattern of factors conditioning biomass or productivity. Twenty-eight TM data sets were acquired, archived, and evaluated. The ERDAS image processing and GIS system were installed on the microcomputer (PC-AT) and its capabilities are being investigated. The TM coverage of seven study areas were exported via ELAS software on the Prime to the ERDAS system. Statistical analysis procedures to be used on the spectral data are being identified