A 1.2 Billion Pixel Human-Labeled Dataset for Data-Driven Classification of Coastal Environments.

The world's coastlines are spatially highly variable, coupled-human-natural systems that comprise a nested hierarchy of component landforms, ecosystems, and human interventions, each interacting over a range of space and time scales. Understanding and predicting coastline dynamics necessitates frequent observation from imaging sensors on remote sensing platforms. Machine Learning models that carry out supervised (i.e., human-guided) pixel-based classification, or image segmentation, have transformative applications in spatio-temporal mapping of dynamic environments, including transient coastal landforms, sediments, habitats, waterbodies, and water flows. However, these models require large and well-documented training and testing datasets consisting of labeled imagery. We describe "Coast Train," a multi-labeler dataset of orthomosaic and satellite images of coastal environments and corresponding labels. These data include imagery that are diverse in space and time, and contain 1.2 billion labeled pixels, representing over 3.6 million hectares. We use a human-in-the-loop tool especially designed for rapid and reproducible Earth surface image segmentation. Our approach permits image labeling by multiple labelers, in turn enabling quantification of pixel-level agreement over individual and collections of images.

A multi-modal approach towards mining social media data during natural disasters - a case study of Hurricane Irma.

Streaming social media provides a real-time glimpse of extreme weather impacts. However, the volume of streaming data makes mining information a challenge for emergency managers, policy makers, and disciplinary scientists. Here we explore the effectiveness of data learned approaches to mine and filter information from streaming social media data from Hurricane Irma's landfall in Florida, USA. We use 54,383 Twitter messages (out of 784K geolocated messages) from 16,598 users from Sept. 10 - 12, 2017 to develop 4 independent models to filter data for relevance: 1) a geospatial model based on forcing conditions at the place and time of each tweet, 2) an image classification model for tweets that include images, 3) a user model to predict the reliability of the tweeter, and 4) a text model to determine if the text is related to Hurricane Irma. All four models are independently tested, and can be combined to quickly filter and visualize tweets based on user-defined thresholds for each submodel. We envision that this type of filtering and visualization routine can be useful as a base model for data capture from noisy sources such as Twitter. The data can then be subsequently used by policy makers, environmental managers, emergency managers, and domain scientists interested in finding tweets with specific attributes to use during different stages of the disaster (e.g., preparedness, response, and recovery), or for detailed research.

Blind testing of shoreline evolution models.

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999-2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014-2017), both approaches showed a decrease in models' capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.

Critical care checklists, the Keystone Project, and the Office for Human Research Protections: a case for streamlining the approval process in quality-improvement research.

Checklists have been recently promulgated as a method to enhance patient safety and improve outcomes for critically ill patients. Specifically, recent work performed by researchers from the Johns Hopkins Medical Institutions has demonstrated that the addition of checklists to usual care in the intensive care unit is associated with a decrease in the incidence of catheter-related bloodstream infections. Initially evaluated at the institutional level, this effort has been successfully expanded to the state level as part of the Michigan Keystone Project. Although this work has recently received significant positive attention in the lay press, the Office for Human Research Protections--as they felt that this was a research project requiring Institutional Review Board approval and informed consent--put the data collection on hold for lack of approval by the Institutional Review Board at the participating hospitals in Michigan as well as for not having obtained informed consent from each patient and clinician involved in the project. This article documents the recent events surrounding the Keystone Project and the response to the actions taken by the Office for Human Research Protections in the lay press and the new media (Internet and blogs), articulates how a determination can be made if a project is quality-improvement, human-subjects research, or both, and proposes some solutions to create a structured approach to this kind of research in the future.

Literature-based latitudinal distribution and possible range shifts of two US east coast dune grass species (Uniola paniculata and Ammophila breviligulata).

Previous work on the US Atlantic coast has generally shown that coastal foredunes are dominated by two dune grass species, Ammophila breviligulata (American beachgrass) and Uniola paniculata (sea oats). From Virginia northward, A. breviligulata dominates, while U. paniculata is the dominant grass south of Virginia. Previous work suggests that these grasses influence the shape of coastal foredunes in species-specific ways, and that they respond differently to environmental stressors; thus, it is important to know which species dominates a given dune system. The range boundaries of these two species remains unclear given the lack of comprehensive surveys. In an attempt to determine these boundaries, we conducted a literature survey of 98 studies that either stated the range limits and/or included field-based studies/observations of the two grass species. We then produced an interactive map that summarizes the locations of the surveyed papers and books. The literature review suggests that the current southern range limit for A. breviligulata is Cape Fear, NC, and the northern range limit for U. paniculata is Assateague Island, on the Maryland and Virginia border. Our data suggest a northward expansion of U. paniculata, possibly associated with warming trends observed near the northern range limit in Painter, VA. In contrast, the data regarding a range shift for A. breviligulata remain inconclusive. We also compare our literature-based map with geolocated records from the Global Biodiversity Information Facility and iNaturalist research grade crowd-sourced observations. We intend for our literature-based map to aid coastal researchers who are interested in the dynamics of these two species and the potential for their ranges to shift as a result of climate change.

The iCritical care podcast: a novel medium for critical care communication and education.

Podcasting is a recent creation combining old and new technologies allowing rapid, inexpensive delivery of media content (primarily audio) to the end user, both via the desktop environment and personal media players. The authors' group (the Society of Critical Care Medicine) saw the educational and communication potential for the podcasting concept, and have successfully designed and implemented the first podcast of a national medical society. As of this writing, there are an average of (mean +/- SD) 664 +/- 290 total downloads per podcast, and their podcast feed has been hit over 68,000 times in its first seven months. In this manuscript, the authors provide documentation of their successful endeavor, as well as a structured framework for other organizations to create similar products.

Calcifying fibrous pseudotumor of the neck: diagnostic challenges of a rare benign lesion.

Neck masses, frequently encountered by physicians, comprise a vast range of diagnoses, with malignancy being the greatest concern. Calcifying fibrous pseudotumor (CFP) is a rare lesion with unknown pathogenesis, characterized pathologically by a predominance of abundant hyalinized collagenous tissue with focal lymphoplasmacytic infiltrate and psammomatous or dystrophic calcifications. We present the case of a 29-year-old woman who presented with a 4-cm left neck mass, accompanied by constitutional symptoms of vague weakness and lethargy. After the lesion failed to respond to a course of antibiotic therapy, fine-needle aspiration was performed, the pathology of which was indeterminate. The concern was that the lesion was a lymphoproliferative disorder-further workup was performed. CT of the chest, abdomen, and pelvis revealed no evidence of adenopathy or neoplasms. Subsequently, an incisional biopsy was performed, suggesting a diagnosis of CFP. Magnetic resonance imaging with contrast, performed to delineate the anatomy, revealed the lesion in the left neck, deep to the left clavicle, that extended superiorly into the supraclavicular fossa. Complete surgical removal of the lesion was successfully performed, with immunophenotyping confirming the initial diagnosis of CFP. We present a case report of cervical CFP, discuss the approach to neck masses, and review the recent literature on this rare, benign entity.

Successful treatment of Bouveret syndrome using holmium: YAG laser lithotripsy.

Although gallstone disease is highly prevalent, cholelithiasis causing gallstone ileus is uncommon. Consideration has been given for nonoperative strategies to resolve obstruction due to the significant age and comorbidities afflicting this population. A 94-year-old man presented with a 5-day history of abdominal distension and tenderness. CT scan revealed multiple large gallstones within the gallbladder, pneumobilia, and two ectopic gallstones (antrum of the stomach and distal ileum). The patient was taken to the operating room where an enterolithotomy and gastrotomy was performed with removal of gallstones and subsequent relief of obstruction. During the postoperative course, the patient developed symptoms of gastric outlet obstruction and underwent gastrointestinal endoscopy for diagnosis and treatment. Two large gallstones, present in the duodenum, were retracted into the stomach using a Roth net but could not be retrieved beyond the upper esophageal sphincter. A holmium: yttrium-aluminum-garnet (Holmium: YAG) laser was used for fragmentation of the stones, with subsequent successful removal. This is the first documented successful use of the holmium: YAG laser for the treatment of recurrent gallstone ileus. Physicians should remember that in a small but important subgroup of patients, endoscopy accompanied by laser lithotripsy may prove beneficial.

Extensive stage small cell lung cancer presenting as an acute perforated appendix: case report and review of the literature.

Malignancies of the appendix are uncommon; a small subset of these lesions are actually metastatic cancers. In some rare cases, these lesions can cause obstruction, appendicitis, and perforation. M.K. is a 54-year-old man who presented to our institution with a 1-day history of right lower quadrant pain and a past medical history significant only for a 75-pack-year smoking history. CT scan revealed a perforated appendix, and the patient was taken to the operating room where a gangrenous appendix was removed uneventfully. Two days post-procedure, the patient was found to have acute mental status changes, requiring intubation and transfer to the surgical intensive care unit. As part of a workup, a CT scan of the head revealed multiple lesions compatible with metastatic disease. At that point, the pathology from the appendix came back as small cell lung cancer. Chest CT revealed hilar adenopathy and a hilar mass. The patient received emergent whole-brain irradiation therapy with improvement in his mental status, allowing him to be extubated and discharged from the hospital within 10 days of admission. Surgeons should remember that an underlying oncologic process may be the etiology of appendicitis in a small but important subgroup of patients.

Use of text messaging to enhance compliance with the accreditation council for graduate medical education resident duty hour requirements.

PURPOSE: Recently, the Accreditation Council for Graduate Medical Education (ACGME) has developed and enforced a complex set of regulations limiting resident duty hours (RDHs). One potential method to comply with these stringent regulations and better document resident work hours would be to use text message (TM)/short message service (SMS), allowing rapid, inexpensive, and interactive 2-way delivery of information. The purpose of this study was to document the successful implementation of TM to enhance compliance with the ACGME RDH regulations. METHODS: Our TM system uses TSHEETS (TS; Meridian, Ohio), which is an online time- and labor-management service. After our general surgical residents were registered with the system, the documentation of entry into (texting "t start" to a predetermined number) and exit out of (texting "t stop" to the same number) the hospital could easily be accomplished. The goals of this pilot study were to determine (1) the feasibility of implementing a program such as this and (2) if use of such a program was associated with high resident satisfaction and improved compliance. RESULTS: We registered 39 residents with TS. Within 3 days, compliance rose from 76.9% to 96.2%. After implementation of TM reminders, compliance increased to 100%. A time-tracking resident satisfaction survey was distributed after 8 weeks of data collection. Twenty six of 39 (67%) residents participated in the survey, with 25 (96%) being more satisfied with the current application as compared with either of the previous (manual or swipe card) systems, specifically regarding ease of use and overall ACGME RDH compliance. Self-reported resident scores of their ability to be compliant with ACGME RDH before versus after implementation increased from 47% to 75% (p < 0.05). CONCLUSIONS: We were able to implement successfully a novel technique for ACGME RDH documentation and compliance in a general surgery residency program through the use of TM; this approach employed a state-of-the-art time-tracking method that was associated with high levels of resident work-hour compliance and overall satisfaction.