Applied Physics Laboratory Research Articles

Prolonged Field Care Research Approach and Its Relevance to Civilian Medicine.

In early March 2020, Johns Hopkins University Applied Physics Lab hosted an Association of Military Surgeons of the United States regional conference to address medical demands of the future battlefield for which prolonged field care is expected. Arising from this conference, we propose here an approach to prolonged field care research-and also summarize the major concepts discussed at the conference. We draw parallels to prolonged field care investments and advancements that apply beyond the combat environment. The exceedingly daunting medical challenges of the future battlefield, on land and at sea, must be addressed to maintain an effective force able to compete with modern highly capable adversaries. Since the human element, and its health, will allow future mission success, we propose here an approach to making soldier health-related research most impactful.

Self-calibration dense bundle adjustment of multi-view Worldview-3 basic images

Very high-resolution satellite images (VHRSIs) with improved spatial resolution provide unprecedented opportunities to explore the geometric and semantic information of the world. Accordingly, to compensate for the bias of exterior orientation parameters, bundle adjustment of VHRSIs is required. Owing to the sparse points, the bundle adjustment of a few VHRSIs omits high-frequency errors and attitude jitters; therefore, the rational function model (RFM) can achieve an accuracy comparable to that of a rigorous sensor model (RSM), despite the significant difference between the RSM and RFM. In this study, we provide insight into the role of RSM in modeling attitude jitters for the Worldview-3 basic imagery product. Penalized splines were proposed to model the attitude jitters. After correcting the photogrammetric refraction using Saastamoinen’s model and light aberration, the RSM was built for agile satellites. The difference between RSM and RFM is consistent with attitude jitters, which is calculated using the penalized splines model and third-degree polyniomials. To fully explore the attitude jitters, a dense bundle adjustment was proposed to process 47 scenes of the Worldview-3 basic product imagery, which was provided by Johns Hopkins University Applied Physics Laboratory for the “Multi-View Stereo 3D Challenge.” Pairwise feature matching and feature tracking were adopted to generate over 16 000 tie-points (TPs), which were detected in an average of 9.38 images. The bundle adjustment residuals with RFM exhibited distortions similar to those of the attitude jitter. The experiments verified that the bundle adjustment with RFM introduced significant errors triggered by attitude jitters, with a maximum of over 5.0 pixels. The bundle adjustment with RSM could eliminate significant errors caused by attitude jitters and reduce the root mean square errors (RMSEs) from 1.12 pixels to 0.61 pixels. However, the basic product imagery of Worldview-3 exhibited errors in the interior orientation parameters. After analyzing the physical meanings of bias compensation, a self-calibration model was proposed. After comparing the shift compensation, affine compensation, self-calibration, temporal self-calibration, second-degree self-calibration, and second-degree polynomial models, the dense bundle adjustment with self-calibration was suggested because it could compensate for errors in the interior orientation parameters (IOPs) and obtain an accuracy similar to that of high-degree models. Thus, a self-calibration dense bundle adjustment with RSM compensates for the attitude jitters and errors in the IOPs, and achieves a remarkable accuracy of 0.49 pixels in the image coordinates.

Magnetic Field Line Random Walk and Solar Energetic Particle Path Lengths: Stochastic Theory and PSP/ISoIS Observation

We thank Junxiang Hu for useful discussions. This research is partially supported by the Parker Solar Probe mission and the IS IS project (contract NNN06AA01C) and a subcontract to University of Delaware from Princeton University (SUB0000165). Additional support is acknowledged from the NASA Living With a Star (LWS) program (NNX17AB79G) and HSR program (80NSSC18K1210 & 80NSSC18K1648) and Thailand Science Research and Innovation (RTA6280002). The IS IS data and visualization tools are available to the community at https://spacephysics.princeton.edu/missions-instruments/isois; data are also available via the NASA Space Physics Data Facility. PSP was designed, built, and is now operated by the Johns Hopkins Applied Physics Laboratory as part of NASA’s LWS program (contract NNN06AA01C). Support from the LWS management and technical team has played a critical role in the success of the PSP mission.

APL JANUS System Progress on Commercial Suborbital Launch Vehicles: Moving the Laboratory Environment to Near Space

Abstract Multiple private companies are building suborbital reusable launch vehicles possessing vastly different designs. Many of these companies originally focused on space tourism; however, revolutionary applications for scientific and engineering research as well as technology demonstrations and instrument development are emerging. The dramatic reduction in cost over traditional launch systems as well as a guaranteed (and rapid) safe payload return enable many new launch vehicle applications. These new capabilities will essentially move the laboratory environment up to the edge of space. To make use of these novel launch vehicles, the John Hopkins University Applied Physics Laboratory has established a Commercial Suborbital Program with a core system (JANUS) to support and enable many future suborbital missions. This program has already conducted six suborbital flight missions to establish vehicle interfaces and analyze the suitability and limits of each flight environment. Additionally, this program has also been selected by the NASA Flight Opportunities Program for five additional operational suborbital missions. Here we present the results of our completed missions as well as descriptions of future selected missions scheduled for 2021–2023.

Boundary Layer Transit Flight Experiment: Mission Overview, Launch Vehicle and Payload Subsystems

The objective of the Boundary Layer Transition (BOLT) flight experiment is to investigate the hypersonic boundary-layer transition mechanisms on a low-curvature concave surface with a swept leading edge at Mach numbers between five and seven. This shall be achieved during a captive-carry flight experiment on an S31/Improved Orion sounding rocket. The BOLT project is coordinated by the U.S. Air Force Research Laboratory U.S. Air Force Office of Scientific Research and will be carried out in collaboration with the U.S. Air Force Research Laboratory Aerospace Systems Directorate, the Johns Hopkins University Applied Physics Laboratory, and a multiorganization team of researchers. DLR, German Aerospace Center’s Mobile Rocket Base (DLR MORABA) is responsible for the development of the required mission and flight profile, layout and adaption of the launch vehicle, as well as the provision of payload subsystems for attitude control, time synchronization, data telemetry, despin, and separation. DLR MORABA will complete ground testing, coordinates, and conducts launch operations; and it will support postflight analysis. This paper presents these contributions in detail.

Flying beyond mach 5 is back, decades after the original need-for-speed arms race ended: Going Hypersonic

IT'S OBVIOUS WHY the militaries of the world want missiles that can follow erratic paths at low altitude while flying at five times the speed of sound, eluding any chance at detection or interception. • “Think of it as delivering a pizza, except it's not a pizza,” says Bradley Wheaton, a specialist in hypersonics at the Johns Hopkins University Applied Physics Laboratory (APL), in Maryland. “In the United States, just 15 minutes can cover the East Coast; a really fast missile takes 20 minutes to get to the West Coast. At these speeds, you have a factor of 50 increase in the area covered per unit of time.” • So the question isn't why the great powers are pursuing hypersonic arms, but why they are doing so now. Quick answer: They are once again locked in an arms race. • The wider world first heard of this type of weaponry in March 2018, when Russian president Vladimir Putin gave a speech describing his country's plans for a nuclear-powered cruise missile that could fly around the world at blinding speed, then snake around hills and dales to a target. His bold assertions have been questioned, particularly the part about nuclear power. Even so, a year later a nuclear accident killed seven people near a testing range off the northern coast of Russia, and U.S. intelligence officials speculated that it involved hypersonic experiments.

Fabrication of Microsensor for Detection of Low-Concentration Formaldehyde Gas in Formalin-Treated Fish

After nine years (the maximum three consecutive terms) on the Editorial Board of the IEEE Transactions on Electron Devices (TED), Prof. Richard Carter, Lancaster University, U.K. (Vacuum Electron Devices), Dr. Youichi Momiyama, Socionext, Japan (MOS Devices and Technology), Prof. Guofu Niu, Auburn University, USA (Bipolar Devices), and Prof. Rama Venkatasubramanian, Johns Hopkins Applied Physics Lab, USA (Thermal Management) have stepped down from their Editor positions in the respective fields.

The streamer blowout origin of a flux rope and energetic particle event observed by Parker Solar Probe at 0.5 AU

We acknowledge the NASA Parker Solar Probe mission team and the SWEAP team led by J. C. Kasper, the ISeIS team led by D. J. McComas, and the FIELDS team led by S. D. Bale, for the use of PSP data. The data used in this paper can be downloaded from spdf.gsfc.nasa.gov, www.srl.caltech.edu/ACE/ASC/, and stereo.gsfc.nasa.gov. Parker Solar Probe was designed, built, and is now operated by the Johns Hopkins Applied Physics Laboratory as part of NASA’s Living with a Star (LWS) program (contract NNN06AA01C). Support from the LWS management and technical team has played a critical role in the success of the Parker Solar Probe mission. Simulation results have been provided by the Community Coordinated Modeling Center at Goddard Space Flight Center through their public Runs on Request system (ccmc.gsfc.nasa. gov; run david_lario_012820_SH_1). The ENLIL-Cone Model was developed by D. Odstrcil of George Mason University. We thank the STEREO/SECCHI, STEREO/IMPACT, STEREO/ PLASTIC, SOHO/LASCO, and SDO/AIA teams and Predictive Science Inc. for providing the data used in this study. The STEREO SECCHI data are produced by a consortium of RAL (UK), NRL (USA), LMSAL (USA), GSFC (USA), MPS (Germany), CSL (Belgium), IOTA (France), and IAS (France). SOHO is a mission of international cooperation between ESA and NASA. The SDO/AIA data are provided by the Joint Science Operations Center (JSOC) Science Data Processing (SDP). We acknowledge all of the science instrument teams for making their data used in this paper available. This work utilizes data produced collaboratively between the Air Force Research Laboratory (AFRL) and the National Solar Observatory (NSO). The ADAPT model development is supported by AFRL. We appreciate the reviewer’s comprehensive reading of the article. This work was partially supported under NASA contract NNN06AA01C. D.L. was also supported by NASA-HGI grant NNX16AF73G and NASA/LWS grant NNX15AD03G. L.J. acknowledges support from the NASA Program NNH16ZDA001N-HSR and NNH17ZDA001-HSR. D.L., L.B., and I.R. acknowledge the support from the NASA Program NNH17ZDA001N-LWS.

A miniaturized XRF instrument for in situ planetary exploration: The Active X-Ray Spectrometer (AXRS)

The Active X-Ray Spectrometer (AXRS) was developed at Johns Hopkins Applied Physics Lab (APL) to be utilized in landed planetary exploration spacecraft seeking to better understand bulk rock geochemistry of lithophile materials. The AXRS sensor head has a mass of 360 ​g, fits within an envelope of 11 ​× ​6 ​× ​5 ​cm3, and consumes <5 ​W during operation. AXRS has an average relative uncertainty of 9% for deriving the abundances of major and minor elements, and measurement precision ≤10% for all elements. Measurements were made with powdered samples, analogous to high-processed regoliths as expected on the surfaces of airless planetary objects. These specifications are equal to or better than those published for other x-ray instruments used in landed planetary exploration missions. We explored several mission applications for AXRS via analysis of planetary materials under mission conditions. These include the ability to: 1) resolve sub-type of carbonaceous chondrite meteorite via measured abundances of various lithophile element ratios based on volatility, 2) identify low-Fe lunar anorthosite, from high-Fe lunar anorthosite, from lunar mare using bulk Ca, Al, Fe, Mg, and 3) resolve various Venus- and Mars-like volcanic rocks utilizing bulk Si, K, and Na.

Optimization of Charles Gay-Lussac’s law experiment with temperature correction at the capillary pipe and fixed volume to improve the accuracy of experimental data in Polban applied physics laboratory

The results of Charles Gay-Lussac’s law experimental tools at Politeknik Negeri Bandung (Polban) Applied Physics Laboratory show the pressure value of 1.027 x 105 Pa with relative uncertainty value of 11.1% and the number of moles in a flask of 12.47 mmole with relative uncertainty value of 24.3%. The experimental data has relatively low accuracy. In this study, Charles’s Law experimental tools were optimized by a measured temperature correction on the capillary pipe using the conduction concept. The heat distribution equation that occurs in capillary pipe was solved by numerical solutions using the finite difference method. The modification of Gay-Lussac’s Law experimental tools to get fixed volume was located on the manometer integrated with a glass flask. Data collection techniques were carried out in two different circumstances, namely when the system is experiencing heating and cooling, then compared. After temperature correction, it was obtained that pressure value 0.977 x 105 Pa with relative uncertainty of 5.7%. After using integrated manometer and data collection techniques when cooling, the number of moles in the flask was 21.5 mmole with relative uncertainty value of 6.2%. With the correction of temperature in the capillary pipe and the volume maintained provides more accurate experimental results.

The origin of patch cavitation

The initial form of partial cavitation on axisymmetric bodies in some water tunnel tests is a regular system of patches with the approximately constant azimuthal distance between them. The described numerical simulation shows that the origin of such three-dimensional system is in the relatively small non-axisymmetric regular perturbations of the inflow caused by the shapes of non-circular water tunnel cross sections (these sections were squares or hexagons). Computational prediction of cavitation inception number for patch cavitation is carried out by a viscous-inviscid interaction method that combines three-dimensional analysis of inviscid flows with quasi-two-dimensional analysis of viscous flows. Computational results are compared with the experimental data obtained in 1980s in water tunnels of Applied Physics Laboratory and David Taylor Research Center. The satisfactory agreement of computed and measured data is considered as the proof of the described explanation of the origin of patch cavitation.

Analytic Fusion for Essential Indicators of the Opioid Epidemic

Analytic Fusion for Essential Indicators of the Opioid Epidemic

What Can You Really Do with 35,000 Statistical Alerts a Week Anyways?

ObjectiveFind practical ways to sort through statistical noise in syndromic data and make use of alerts most likely to have public health importance.IntroductionThe National Syndromic Surveillance Program’s (NSSP) instance of ESSENCE* in the BioSense Platform generates about 35,000 statistical alerts each week. Local ESSENCE instances can generate as many as 5,000 statistical alerts each week. While some states have well-coordinated processes for delegating data and statistical alerts to local public health jurisdictions for review, many do not have adequate resources. By design, statistical alerts should indicate potential clusters that warrant a syndromic surveillance practitioner‘s time and focus. However, practitioners frequently ignore statistical alerts altogether because of the overwhelming volume of data and alerts. In 2008, staff in the Virginia Department of Health experimented with rules that could be used to rank the statistical output generated in ESSENCE alert lists. Results were shared with Johns Hopkins University Applied Physics Lab (JHU/APL), the developer of ESSENCE, and were early inputs into what is now known as “myAlerts,” an ESSENCE function that syndromic surveillance practitioners can use to customize alerting and sort through statistical noise. NSSP–ESSENCE produces a shared alert list by syndrome, county, and age-group strata, which generates an unwieldy but rich data set that can be studied to learn more about the importance of these statistical alerts. Ultimately, guidance can be developed to help syndromic surveillance practitioners set up meaningful ESSENCE myAlerts effective in identifying clusters with public health importance.MethodsThe region/syndrome alert list generated from NSSP’s instance of ESSENCE on the BioSense Platform was downloaded and ranked based on five criteria:1. Observed count causing the alert2. Expected count generated by ESSENCE3. Total number of alerts for that syndrome in that county and number of prior alerts during that week for the same syndrome, county, and age group4. Density of alerts during the prior week5. Recency of the latest alertAlerts were then ranked based on:1. Higher absolute counts (regardless of expected value)2. Higher partial chi-square, (Obs-Exp)2 / Exp3. Higher total alerts for a given county/syndrome4. Higher number of earlier alerts for same county/syndrome/age group5. Multiple alerts same day &gt; alerts on consecutive days &gt; alerts separated by days without alerts6. Alerts present on more recent daysThe top 20 alerts with the highest scores were then reviewed and if anything unusual was noticed (i.e. problems unrelated to recent data quality problems or onboardings, seasonal trends, etc.) then there was follow-up with the site. The alert list rankings were then evaluated for differences among factors available in the ESSENCE myAlert function. We compared the top 5% of ranked alerts to the remaining 95% to determine if there were significant differences in the following factors:1. Total number of alerts across six age groups (including all ages) within 8 days of each syndrome and county stratum;2. Average alert frequency across six age groups (including all ages) within 8 days for each stratum;3. Average count across the strata;4. Average expected value across the strata;5. Average of the difference between the count and expected values for each stratum; and6. Average Level across the strata.ResultsPreliminary interactions with sites revealed important clusters – some already known and some not. For example, a cluster of healthcare workers exposed to Neisseria meningitides, and kids exposed to a bat at summer camp and presenting for prophylaxis were among the clusters identified. Additionally there were differences seen in the adjustable myAlert parameters when comparing the top 5% to the lower 95% of ranked alerts.ConclusionsThe differences seen and preliminary feedback suggests that this ranking method may be effective in identifying alerts representing true clusters of public health importance. Testing designed to evaluate myAlert parameters based on the differences seen in the top 5% of ranked alerts is underway in sites where more detailed data access is available. More study is needed; however, there are indications that cutoff values for these parameters may be a valuable way for syndromic surveillance practitioners to reduce the review burden and focus on the most important statistical clusters identified by ESSENCE statistical algorithms.References*ESSENCE stands for the Electronic Surveillance System for the Early Notification of Community-based Epidemics and is designed by Johns Hopkins University Applied Physics Laboratory.

Streamlined Development of Analytic Fusion Capability for Health Surveillance

Streamlined Development of Analytic Fusion Capability for Health Surveillance

ESSENCE Features for 2019

ObjectiveThe objective of this presentation is to discuss the new features that are under development for ESSENCE in 2019. This is a chance to describe the features, the use cases for the features, and open a dialogue with the community on potential new enhancements that are available.IntroductionThe ESSENCE system is a community-driven disease surveillance system. Installed in over 25 jurisdictions across the US, the system is built on a single codebase that is shared across all instances. While each individual location can customize many of the settings, data sources, and configurations, the underlying code and functionality is shared. This means that when one jurisdiction works with the Johns Hopkins University Applied Physics Laboratory (JHU/APL) to create a new feature, it is available to all sites.MethodsThe roadmap for ESSENCE in 2019 is based upon ongoing and future projects between jurisdictions and JHU/APL. While specifics can change before features are deployed, the following list of new features have exceptional capabilities. These include:Social Elements to the User Experience: Ability for users to share what they are doing within ESSENCE with their peers. Ability for users to see what others are querying and find interesting. Support sharing both within a system and across jurisdictions.Text Analysis: Text analysis and visualizations to help support the user in building new free-text queries.Provide correlation, trend, and association analytics for words and phrases to help the user determine what should or should not be included in their queries.Site Monitoring: Back-end tools and checks to better monitor an ESSENCE system for issues and data irregularities. This administrative tool will help the system maintain its day-to-day availability and improve visibility of errors and issues that may develop over time.Longitudinal Surveillance: Visualizations and cohort clustering analytics to determine the types of patients who are using the healthcare systems that provide data to ESSENCE. These tools can show patient uses over time with trends to better inform utilization of healthcare resources in a community.Opioid Overdose Surveillance: Visualizations and analytics to better support the surveillance activities related to the opioid overdose crisis. Work with additional data sources (EMS, Poison Control, Death Records, etc.) to determine the benefit of fusing multiple pieces of information into a common picture for improved opioid surveillance.And other new features…ResultsThe presentation will describe the current roadmap, demonstrate features that are mature enough in the software development process, share mock-ups for features still in the early stages of development and provide use cases for each of the new features discussed.ConclusionsNo organization can build a successful system without the participation and buy-in from its stakeholder community. ESSENCE is an excellent example of a tool built on collective input whose ongoing enhancements benefit all its users. By seeing the roadmap and understanding the new features for 2019, the community can prepare for upcoming enhancements and begin discussions about other needs and use cases that will drive the development of the next round of ESSENCE features.

Building Electronic Disease Surveillance Capacity in the Peruvian Navy with SAGES

ObjectiveTo introduce SMS-based data collection into the Peruvian Navy’s public health surveillance system for increased reporting rates and timeliness, particularly from remote areas, as well as improve capabilities for analysis of surveillance data by decision makers.IntroductionIn the past 15 years, public health surveillance has undergone a revolution driven by advances in information technology (IT) with vast improvements in the collection, analysis, visualization, and reporting of health data. Mobile technologies and open source software have played a key role in advancing surveillance techniques, particularly in resource-limited settings. Johns Hopkins University Applied Physics Laboratory (JHU/APL) is an internationally recognized leader in the area of electronic disease surveillance. In addition to the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) used by several state and local jurisdictions and the CDC in the U.S., JHU/APL has also developed the Suite for Automated Global Electronic bioSurveillance (SAGES). SAGES is a collection of modular, open-source software tools designed to meet the challenges of electronic disease surveillance in resource-limited settings.JHU/APL is working with the Peruvian Navy health system to improve their electronic disease surveillance capabilities. The Peruvian Navy currently uses a SAGES-based system called Alerta DISAMAR that was implemented several years ago in an effort supported by the Armed Forces Health Surveillance Branch, and in collaboration with the Naval Medical Research Unit No. 6 (NAMRU-6). The system uses both web-based and IVR-based (interactive voice response) data collection from several Navy health facilities in Peru. For the present effort, JHU/APL is implementing a new SMS-based data collection capability for the Peruvian Navy.MethodsJHU/APL is engaged with the Peruvian Navy Health System to upgrade the existing SAGES-based Alerta DISAMAR surveillance system which relies on remote data collection using IVR (interactive voice recording) technology, with a SAGES-based system that uses SMS (short message service) text messages for remote data collection. Based on Peruvian Navy requirements, JHU/APL created mobile data entry forms for Android smartphones using the SAGES mCollect application. SAGES mCollect is built using Open Data Kit open source tools along with added features such as 128-bit encryption and quality checks.The JHU/APL team engages closely with end users and other stakeholders to determine system requirements and to deploy the system, as well as to train end users and the system administrators who will need to maintain the system once it is deployed. The JHU/APL team, consisting of both information technology and public health expertise, conduct a country-level capabilities and needs assessment to address design considerations and operational end user requirements. This assessment takes into account the requirements and objectives of the Peruvian Navy, while keeping in mind infrastructure, cost, and personnel constraints. A pilot test of SMS-based data collection is currently underway with 10 health clinics within the Navy.ResultsMany challenges exist when implementing electronic disease surveillance tools in resource-limited settings, but using a tailored approach to implementation in which specific needs, constraints, and expectations are identified with stakeholders helps increase the overall adoption and sustainment of the system. JHU/APL believes SMS-based data collection will be more sustainable than IVR-based data collection for the Peruvian Navy.ConclusionsJHU/APL is deploying a SAGES-based electronic disease surveillance system for the Peruvian Navy that has great potential to increase reporting rates from its health facilities as well as improve data quality and timeliness, thus resulting in greater awareness and enhanced public health decision making.

3-μm reflectance spectroscopy of carbonaceous chondrites under asteroid-like conditions

We measured 3-μm reflectance spectra of 21 meteorites that represent all carbonaceous chondrite types available in terrestrial meteorite collections. The measurements were conducted at the Laboratory for Spectroscopy under Planetary Environmental Conditions (LabSPEC) at the Johns Hopkins University Applied Physics Laboratory (JHU APL) under vacuum and thermally-desiccated conditions (asteroid-like conditions). This is the most comprehensive 3-μm dataset of carbonaceous chondrites ever acquired in environments similar to the ones experienced by asteroids. The 3-μm reflectance spectra are extremely important for direct comparisons with and appropriate interpretations of reflectance data from ground-based telescopic and spacecraft observations of asteroids. We found good agreement between 3-μm spectral characteristics of carbonaceous chondrites and carbonaceous chondrite classifications. The 3-μm band is diverse, indicative of varying composition, thus suggesting that these carbonaceous chondrites experienced distinct parent body aqueous alteration and metamorphism environments. The spectra of CI chondrites, from which significant amount of water adsorbed under ambient conditions was removed, are consistent with Mg-serpentine and clay minerals. The high abundances of organics in CI chondrites is also associated with the mineralogy of these chondrites, oxyhydroxides- and complex clay minerals-rich. CM chondrites, which are cronstedtite-rich, have shallower 3-μm band than CI chondrites, suggesting they experienced less aqueous alteration. CR chondrites showed moderate aqueous alteration relative to CI and CM chondrites. CV chondrites, except for Efremovka, have a very shallow 3-μm band, consistent with their lower phyllosilicate proportions. CO chondrites, like most CVs, have a very shallow 3-μm band that suggest they experienced minor aqueous alteration. The 3-μm band in CH/CBb is deep and broad centered ~3.11 μm, possibly due to the high abundance of FeNi metal and presence of heavily hydrated clasts in these chondrites. The 3-μm spectra of Essebi (C2-ung) and EET 83226 are more consistent with CM chondrites' spectra. The 3-μm spectra of Tagish lake (C2-ung), on the other hand, are consistent with CI chondrites. None of these spectral details could have been resolved without removing the adsorbed water before acquiring spectra.

Equine syndromic surveillance in Colorado using veterinary laboratory testing order data

IntroductionThe Risk Identification Unit (RIU) of the US Dept. of Agriculture’s Center for Epidemiology and Animal Health (CEAH) conducts weekly surveillance of national livestock health data and routine coordination with agricultural stakeholders. As part of an initiative to increase the number of species, health issues, and data sources monitored, CEAH epidemiologists are building a surveillance system based on weekly syndromic counts of laboratory test orders in consultation with Colorado State University laboratorians and statistical analysts from the Johns Hopkins University Applied Physics Laboratory. Initial efforts focused on 12 years of equine test records from three state labs. Trial syndrome groups were formed based on RIU experience and published literature. Exploratory analysis, stakeholder input, and laboratory workflow details were needed to modify these groups and filter the corresponding data to eliminate alerting bias. Customized statistical detection methods were sought for effective monitoring based on specialized laboratory information characteristics and on the likely presentation and animal health significance of diseases associated with each syndrome.MethodsData transformation and syndrome formation focused on test battery type, test name, submitter source organization, and specimen type. We analyzed time series of weekly counts of tests included in candidate syndrome groups and conducted an iterative process of data analysis and veterinary consultation for syndrome refinement and record filters. This process produced a rule set in which records were directly classified into syndromes using only test name when possible, and otherwise, the specimen type or related body system was used with test name to determine the syndrome. Test orders associated with government regulatory programs, veterinary teaching hospital testing protocols, or research projects, rather than clinical concerns, were excluded. We constructed a testbed for sets of 1000 statistical trials and applied a stochastic injection process assuming lognormally distributed incubation periods to choose an alerting algorithm with the syndrome-required sensitivity and an alert rate within the specified acceptable range for each resulting syndrome. Alerting performance of the EARS C3 algorithm traditionally used by CEAH was compared to modified C2, CuSUM, and EWMA methods, with and without outlier removal and adjustments for the total weekly number of non-mandatory tests.ResultsThe equine syndrome groups adopted for monitoring were abortion/reproductive, diarrhea/GI, necropsy, neurological, respiratory, systemic fungal, and tickborne. Data scales, seasonality, and variance differed widely among the weekly time series. Removal of mandatory and regulatory tests reduced weekly observed counts significantly—by >80% for diarrhea/GI syndrome. The RIU group studied outcomes associated with each syndrome and called for detection of single-week signals for most syndromes with expected false-alert intervals >8 and <52 weeks, 8-week signals for neurological and tickborne monitoring (requiring enhanced sensitivity), 6-week signals for respiratory, and 4-week signals for systemic fungal. From the test-bed trials, recommended methods, settings and thresholds were derived.ConclusionsUnderstanding of laboratory submission sources, laboratory workflow, and of syndrome-related outcomes are crucial to form syndrome groups for routine monitoring without artifactual alerting. Choices of methods, parameters, and thresholds varied by syndrome and depended strongly on veterinary epidemiologist-specified performance requirements.

Advances in planetary defense in the United States

The National Aeronautics and Space Administration (NASA) recently established an office to manage the Agency's planetary defense-related projects and coordinate activities across multiple U.S. agencies as well as with international efforts to plan appropriate responses to the potential asteroid impact hazard. The creation of the Planetary Defense Coordination Office (PDCO) is a logical and formal step forward with NASA's NEO Observations program which began nearly two decades ago. Since the program's inception in 1998, NASA-funded efforts have discovered more than 98% of the more than 16,000 NEOs currently known.As important as it is to mitigate a potential impact event, the essential first step is to find these near-Earth objects as early as possible. To that end, NASA's PDCO leads national and international efforts to:•detect any potential for significant impact of the Earth by natural objects;•appraise the range of potential effects by any possible object; and•develop strategies to mitigate impact effects on human welfare.Since commencing the program in 1998, NASA has provided funding to upgrade and operate existing 1-m class telescopes to conduct the search for NEOs. Today, NASA funds three primary ground-based survey capabilities: the Lincoln Near-Earth Asteroid Research (LINEAR) project, the Catalina Sky Survey (CSS), and the Panoramic Survey Telescope and Rapid Reporting System (Pan-STARRS). Recent enhancements to NASA's Near-Earth Object (NEO) Observations Program have led to ∼83% increase in the discovery rate of near-Earth asteroids (NEAs) over the past three years.These survey efforts are increasingly detecting close encounter events (i.e., <0.001 AU; recent examples include 2012 DA14, 2017 EA, and 2017 GM) and have enabled the prediction of some small object impact events (e.g., 2008 TC3 and 2014 AA). Such encounters provide opportunities for NASA's Infrared Telescope Facility (IRTF) to make spectral measurements; or observation by planetary radars at Arecibo and Goldstone to refine the orbit of the object with great precision and even “image” the small primitive body.Of critical importance is the Minor Planet Center (MPC), where automated systems process observations made by the search teams to determine orbits and what are NEOs. The Center for NEO Studies at the Jet Propulsion Laboratory (JPL) determines more precise orbits for the objects. Both JPL and the MPC utilize processes and procedures for NEO orbit determination and prediction that are sanctioned and monitored by the International Astronomical Union (IAU) and produce data catalogues on small bodies in the Solar System that are utilized world-wide by the astronomical community.The Wide-field Infrared Survey Explorer (WISE) was reactivated for the purpose detecting NEOs and will continue to operate well into 2018. It is in Sun-synchronous, near-polar inclination (97.5°) orbit around the Earth. The NEOWISE project uses WISE in ‘warm mode’ (at 3.4 and 4.6 μm), and in conjunction with ground-based follow-up, this unique dataset has set limits on population statistics, orbital parameters, approximate sizes, and initial compositional knowledge of the asteroid population.Further follow-up observations with visible and infrared telescopes (e.g., NASA's Infrared Telescope Facility, Spitzer Space Telescope, other NASA-funded NEO observer teams) refine the astrometric positions of an NEO, photometric observations obtain detailed light curve information [thereby constraining NEO shapes and spin state], and collect albedo and spectral data on basic physical properties and mineralogy.Planetary defense demonstration missions also fall within the purview of the PDCO. The Double Asteroid Redirection Test (DART) mission is directed by NASA to the Johns Hopkins University Applied Physics Laboratory (JHU/APL). The target is the binary near-Earth asteroid (65803) Didymos, which consists of a primary body ∼800 m across, and a secondary body (or “moonlet”) whose 150-m size is more typical of the size of asteroids that could pose a more common hazard to Earth.However, the first step in planetary defense is the overarching goal to complete the NEO survey down to a 100 m-sized objects. The asteroid hunter mission – NEOCam – is a single scientific instrument: 0.5-m aperture infrared telescope that would survey the solar system for NEOs from Sun-Earth L1 Lagrange point (SEL1). NEOCam is also in an extended Phase A study under the auspices of NASA's PDCO.

POINT CLOUD AND DIGITAL SURFACE MODEL GENERATION FROM HIGH RESOLUTION MULTIPLE VIEW STEREO SATELLITE IMAGERY

Abstract. Nowadays, multiple-view stereo satellite imagery has become a valuable data source for digital surface model generation and 3D reconstruction. In 2016, a well-organized multiple view stereo publicly benchmark for commercial satellite imagery has been released by the John Hopkins University Applied Physics Laboratory, USA. This benchmark motivates us to explore the method that can generate accurate digital surface models from a large number of high resolution satellite images. In this paper, we propose a pipeline for processing the benchmark data to digital surface models. As a pre-procedure, we filter all the possible image pairs according to the incidence angle and capture date. With the selected image pairs, the relative bias-compensated model is applied for relative orientation. After the epipolar image pairs’ generation, dense image matching and triangulation, the 3D point clouds and DSMs are acquired. The DSMs are aligned to a quasi-ground plane by the relative bias-compensated model. We apply the median filter to generate the fused point cloud and DSM. By comparing with the reference LiDAR DSM, the accuracy, the completeness and the robustness are evaluated. The results show, that the point cloud reconstructs the surface with small structures and the fused DSM generated by our pipeline is accurate and robust.