Ancillary Information Research Articles

Enabling interoperability in planetary sciences and heliophysics: The case for an information model

The Planetary Data System has developed the PDS4 Information Model to enable interoperability across diverse science disciplines. The Information Model is based on an integration of International Organization for Standardization (ISO) level standards for trusted digital archives, information model development, and metadata registries. Where controlled vocabularies provides a basic level of interoperability by providing a common set of terms for communication between both machines and humans the Information Model improves interoperability by means of an ontology that provides semantic information or additional related context for the terms. The information model was defined by team of computer scientists and science experts from each of the diverse disciplines in the Planetary Science community, including Atmospheres, Geosciences, Cartography and Imaging Sciences, Navigational and Ancillary Information, Planetary Plasma Interactions, Ring-Moon Systems, and Small Bodies. The model was designed to be extensible beyond the Planetary Science community, for example there are overlaps between certain PDS disciplines and the Heliophysics and Astrophysics disciplines. “Interoperability” can apply to many aspects of both the developer and the end-user experience, for example agency-to-agency, semantic level, and application level interoperability. We define these types of interoperability and focus on semantic level interoperability, the type of interoperability most directly enabled by an information model.

Modeling induced polarization effects in helicopter time-domain electromagnetic data: Field case studies

Induced polarization (IP) effects are becoming more evident in time-domain helicopter airborne electromagnetic (AEM) data thanks to advances in instrumentation, mainly due to improvements in the signal-to-noise ratio and hence better data quality. Although the IP effects are often manifested as negative receiver voltage values, which are easy to detect, in some cases, IP effects can distort recovered transients in other ways so they may be less obvious and require careful data analysis and processing. These effects represent a challenge for modeling and inversion of the AEM data. For proper modeling of electromagnetic transients, the chargeability of the subsurface and other parameters describing the dispersion also need to be taken into consideration. We use the Cole-Cole model to characterize the dispersion and for modeling of the IP effects in field AEM data, collected by different airborne systems over different geologies and exploration targets, including examples from diamond, gold, and base metal exploration. We determined how multiparametric inversion techniques can simultaneously recover all four Cole-Cole parameters, including resistivity [Formula: see text], chargeability [Formula: see text], relaxation time [Formula: see text], and frequency parameter [Formula: see text]. The results obtained are in good agreement with the ancillary information available. Interpretation of the IP effects in AEM data is therefore seen by the authors as providing corrected electrical resistivity distributions, as well as additional information that could assist in mineral exploration.

A look towards the future in the handling of space science mission geometry

The “SPICE” system11Spacecraft, Planet, Instrument, Camera-matrix, Events has been widely used since the days of the Magellan mission to Venus as the method for scientists and engineers to access a variety of space mission geometry such as positions, velocities, directions, orientations, sizes and shapes, and field-of-view projections (Acton, 1996). While originally focused on supporting NASA’s planetary missions, the use of SPICE has slowly grown to include most worldwide planetary missions, and it has also been finding application in heliophysics and other space science disciplines. This paper peeks under the covers to see what new capabilities are being developed or planned at SPICE headquarters to better support the future of space science.The SPICE system is implemented and maintained by NASA’s Navigation and Ancillary Information Facility (NAIF) located at the Jet Propulsion Laboratory in Pasadena, California (http://naif.jpl.nasa.gov).

An emission processing system for air quality modelling in the Mexico City metropolitan area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions.

This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km2) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO2, O3, VOC and PM2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NOx and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA.

Using low-cost drones to map malaria vector habitats

BackgroundThere is a growing awareness that if we are to achieve the ambitious goal of malaria elimination, we must compliment indoor-based vector control interventions (such as bednets and indoor spraying) with outdoor-based interventions such as larval source management (LSM). The effectiveness of LSM is limited by our capacity to identify and map mosquito aquatic habitats. This study provides a proof of concept for the use of a low-cost (< $1000) drone (DJI Phantom) for mapping water bodies in seven sites across Zanzibar including natural water bodies, irrigated and non-irrigated rice paddies, peri-urban and urban locations.ResultsWith flying times of less than 30 min for each site, high-resolution (7 cm) georeferenced images were successfully generated for each of the seven sites, covering areas up to 30 ha. Water bodies were readily identifiable in the imagery, as well as ancillary information for planning LSM activities (access routes to water bodies by road and foot) and public health management (e.g. identification of drinking water sources, mapping individual households and the nature of their construction).ConclusionThe drone-based surveys carried out in this study provide a low-cost and flexible solution to mapping water bodies for operational dissemination of LSM initiatives in mosquito vector-borne disease elimination campaigns. Generated orthomosaics can also be used to provide vital information for other public health planning activities.

Buckeye Power &amp; Light Company Supplement (Excel Solver)

Power & Light (BP&L) has recently retained the services of a consulting firm to analyze aspects of its operations. This supplement contains the consultant's report, which includes an optimized linear-programming (LP) spreadsheet model using the Excel Solver. The supplement also provides a detailed explanation of the model, written for someone with no prior LP experience. See also the main case, Buckeye Power & Light Company (QA-0326). Excerpt UVA-QA-0490 BUCKEYE POWER & LIGHT COMPANY SUPPLEMENT (EXCEL SOLVER) Early in October, 1986, Don Peters, manager of the production fuels department of Power & Light (BP&L), received a preliminary report from a consultancy commissioned to analyze various aspects of its operations, including the coal-procurement process. The consultants had been given, among other items, the Offers Edit Report and the Plant Requirements Edit Report for the November coal-procurement decision. The section of the report dealing with the coal-procurement process, reproduced below, contained the consultants' recommendations with respect to the November purchase, as well as an explanation of their methodology. Peters was anxious to understand how this approach might help him more aggressively manage the procurement process and resolve the internal debates on long-term contracts and safety-stock levels. Section of the Consultants' Report Dealing with the Coal-Procurement Process Attached is a spreadsheet model (Exhibit 1) of the November coal-procurement decision. Based on the information contained in the model, linear programming (LP) can be used to identify the optimal (i.e., minimum-cost) procurement and shipping plan. In addition, LP provides valuable ancillary information on related questions of interest, such as how much you would be willing to pay for additional coal from certain vendors, how much your long-term contracts are costing you, and how much the quality restrictions imposed by the various plants are costing the company. . . .

P3.02b-098 Plasma T790M Mutation Associates with Extensive Progression in Non-small Cell Lung Cancer with Acquired Resistance to EGFR Inhibitors: Topic: EGFR RES

T790M mutation is a major mechanism for clinical failure in non-small cell lung cancer (NSCLC) patients with EGFR-TKI therapy. Acknowledgement of its frequency/abundance and its correlation with clinical characteristics will be of significant importance for the management of those patients in clinical practice and future trial design. Due to the difficulty of rebiopsy, plasma ctDNA is an ideal biopsy for detection of T790M mutation. 314 patients with advanced or recurrent NSCLC who had progressed during EGFR-TKIs treatment were enrolled prospectively. T790M mutation was determined in plasma samples by ARMS and ddPCR assay. Disease failure site was defined into three types of chest limited (CP), brain limited (BP) and extensive progression (EP). The T790M mutation status was analyzed for their correlations with failure site and clinical characteristics. T790M mutations were detected in 30.9% and 46.8% of the patients by ARMS and ddPCR. The concordance rate was 78.3% between two methods. Compared to patients with CP and BP, EP patients showed significant higher rate for T790M+ determined by both ARMS and ddPCR (73.8% and 54.7%, p<0.001). In T790M positive population, the median T790M abundance was 1.2% (range, 0.04%-70.3%), and the median abundance of CP, BP, and EP was 0.66%, 1.52%, and 2.61%, respectively (p＝0.062). When adjusting for TKI response, worse PFS was found correlated with the plasma T790M mutation by ddPCR. Plasma T790M status correlates the extensive progression in NSCLC patients with EGFR-TKI therapy, which may provide the important ancillary information for treatment decision-making.

Assessing population exposure for landslide risk analysis using dasymetric cartography

Abstract. Assessing the number and locations of exposed people is a crucial step in landslide risk management and emergency planning. The available population statistical data frequently have insufficient detail for an accurate assessment of potentially exposed people to hazardous events, mainly when they occur at the local scale, such as with landslides. The present study aims to apply dasymetric cartography to improving population spatial resolution and to assess the potentially exposed population. An additional objective is to compare the results with those obtained with a more common approach that uses, as spatial units, basic census units, which are the best spatial data disaggregation and detailed information available for regional studies in Portugal. Considering the Portuguese census data and a layer of residential building footprint, which was used as ancillary information, the number of exposed inhabitants differs significantly according to the approach used. When the census unit approach is used, considering the three highest landslide susceptible classes, the number of exposed inhabitants is in general overestimated. Despite the associated uncertainties of a general cost–benefit analysis, the presented methodology seems to be a reliable approach for gaining a first approximation of a more detailed estimation of exposed people. The approach based on dasymetric cartography allows the spatial resolution of population over large areas to be increased and enables the use of detailed landslide susceptibility maps, which are valuable for improving the exposed population assessment.

Formation of ionospheric irregularities over Southeast Asia during the 2015 St. Patrick's Day storm

AbstractWe investigate the geospace response to the 2015 St. Patrick's Day storm leveraging on instruments spread over Southeast Asia (SEA), covering a wide longitudinal sector of the low‐latitude ionosphere. A regional characterization of the storm is provided, identifying the peculiarities of ionospheric irregularity formation. The novelties of this work are the characterization in a broad longitudinal range and the methodology relying on the integration of data acquired by Global Navigation Satellite System (GNSS) receivers, magnetometers, ionosondes, and Swarm satellites. This work is a legacy of the project EquatoRial Ionosphere Characterization in Asia (ERICA). ERICA aimed to capture the features of both crests of the equatorial ionospheric anomaly (EIA) and trough (EIT) by means of a dedicated measurement campaign. The campaign lasted from March to October 2015 and was able to observe the ionospheric variability causing effects on radio systems, GNSS in particular. The multiinstrumental and multiparametric observations of the region enabled an in‐depth investigation of the response to the largest geomagnetic storm of the current solar cycle in a region scarcely reported in literature. Our work discusses the comparison between northern and southern crests of the EIA in the SEA region. The observations recorded positive and negative ionospheric storms, spread F conditions, scintillation enhancement and inhibition, and total electron content variability. The ancillary information on the local magnetic field highlights the variety of ionospheric perturbations during the different storm phases. The combined use of ionospheric bottomside, topside, and integrated information points out how the storm affects the F layer altitude and the consequent enhancement/suppression of scintillations.

Prevalence and Abundance of Cyamid “Whale Lice” (&lt;i&gt;Cyamus ceti&lt;/i&gt;) on Subsistence Harvested Bowhead Whales (&lt;i&gt;Balaena mysticetus&lt;/i&gt;)

We present findings on the prevalence and abundance of cyamid ectoparasites (Cyamus ceti) or “whale lice” on bowhead whales (Balaena mysticetus) harvested for subsistence in the Bering, Chukchi, and Beaufort Seas from 1973 to 2015. Cyamids were present on 20% of the 673 whales that were examined for cyamid ectoparasites. Logistic regression was used to determine factors associated with cyamid prevalence. The probability of cyamid presence increased with age, length, and improving body condition, but decreased over the past 35 years. Cyamid presence was also more probable on whales harvested in the spring than on those harvested in the fall. When present, cyamid abundance was typically low(&lt; 10 per whale). Case histories provide ancillary information about the relationships between abundance of cyamids and their bowhead hosts. Environmental change and increasing anthropogenic disturbances are expected to occur in the Arctic regions inhabited by bowheads. We recommend continued monitoring of subsistence harvested whales for cyamids, as well as further investigations into the roles of environmental and anthropogenic variables in cyamid prevalence and abundance, as part of a comprehensive program of Arctic ecosystem assessment.

Targeted next-generation sequencing enables reliable detection of HER2 (ERBB2) status in breast cancer and provides ancillary information of clinical relevance.

HER2-positive breast cancers are a heterogeneous group of tumors, which share amplification and overexpression of HER2. In routine diagnostics, the HER2 (ERBB2) status is currently assessed by immunohistochemistry (IHC) and in situ hybridization (ISH). Data on targeted next-generation sequencing (NGS) approaches that could be used to determine the HER2 status are sparse. Employing two breast cancer-related gene panels, we performed targeted NGS of 41 FFPE breast cancers for which full pathological work-up including ISH and IHC results was available. Selected cases were analyzed by qPCR. Of the 41 cases, the HER2 status of the 4 HER2-positive and 6 HER2-negative tumors was independently detected by our NGS approach achieving a concordance rate of 100%. The remaining 31 cases were equivocal HER2 cases by IHC of which 5 showed amplification of HER2 by ISH. Our NGS approach classified all non-amplified cases correctly as HER2 negative and corroborated all but one of the 5 cases with amplified HER2 as detected by ISH. For the overall cohort, concordance between the gold standard and NGS was 97.6% (sensitivity 88.9% and specificity 100%). Additionally, we observed mutations in PIK3CA (44%), HER2 (8%), and CDH1 (6%) among others. Amplifications were found in CCND1 (12%), followed by MYC (10%) and EGFR (2%) and deletions in CDKN2A (10%), MAP2K4 and PIK3R1 (2% each). We here show that targeted NGS data can be used to interrogate the HER2 status with high specificity and high concordance with gold standard methods. Moreover, this approach identifies additional genetic events that may be clinically exploitable. © 2016 Wiley Periodicals, Inc.

Putting the behavior into animal movement modeling: Improved activity budgets from use of ancillary tag information.

Animal movement research relies on biotelemetry, and telemetry‐based locations are increasingly augmented with ancillary information. This presents an underutilized opportunity to enhance movement process models. Given tags designed to record specific behaviors, efforts are increasing to update movement models beyond reliance solely upon horizontal movement information to improve inference of space use and activity budgets. We present two state‐space models adapted to incorporate ancillary data to inform three discrete movement states: directed, resident, and an activity state. These were developed for two case studies: (1) a “haulout” model for Weddell seals, and (2) an “activity” model for Antarctic fur seals which intersperse periods of diving activity and inactivity. The methodology is easily implementable with any ancillary data that can be expressed as a proportion (or binary) indicator. A comparison of the models augmented with ancillary information and unaugmented models confirmed that many behavioral states appeared mischaracterized in the latter. Important changes in subsequent activity budgets occurred. Haulout accounted for 0.17 of the overall Weddell seal time budget, with the estimated proportion of time spent in a resident state reduced from a posterior median of 0.69 (0.65–0.73; 95% HPDI) to 0.54 (0.50–0.58 HPDI). The drop was more dramatic in the Antarctic fur seal case, from 0.57 (0.52–0.63 HPDI) to 0.22 (0.20–0.25 HPDI), with 0.35 (0.31–0.39 HPDI) of time spent in the inactive (nondiving) state. These findings reinforce previously raised contentions about the drawbacks of behavioral states inferred solely from horizontal movements. Our findings have implications for assessing habitat requirements; estimating energetics and consumption; and management efforts such as mitigating fisheries interactions. Combining multiple sources of information within integrated frameworks should improve inference of relationships between movement decisions and fitness, the interplay between resource and habitat dependencies, and their changes at the population and landscape level.

A Statistical Examination of Image Stitching Software Packages For Use With Unmanned Aerial Systems

There is growing demand for the collection of ultra-high spatial resolution imagery, such as is collected using unmanned aerial systems (uas). Traditional methods of aerial photogrammetry are often difficult or time consuming to utilize due to the lack of sufficiently accurate ancillary information. The goal of this study was to compare geometric accuracy, visual quality, and price of three commonly available mosaicking software packages which offer a highly automated alternative to traditional methods: Photoscan Pro, Pix4D Pro Mapper, and Microsoft Image Composite Editor (ice). A total of 223 images with a spatial resolution of 1.26cm were collected by a uas along with 70 ground control points. Microsoft Image Composite Editor had significantly fewer visual errors (Chi Square, p < .001), but it had the poorest geometric accuracy with a rmse of 34.7cm (Tukey-Kramer, p < 0.05). Photoscan had the most visual errors (Chi Square, p < 0.001), and a rmse of 10.9cm. Pix4D had the best geometric accuracy with a rmse of 7.7cm, however this was not found to be statistically different from Photoscan (Tukey-Kramer, p > 0.05). In terms of price, Microsoft Image Composite Editor was the least expensive while Pix4D was the most expensive, although specific pricing varies depending on the type of licensing needed. These results suggest that unless high geometric accuracy or 3D images are required, ice is the best option for most uas photogrammetric applications.

The Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database: a long-term database for climate studies.

In this paper, we describe the construction of the Stratospheric Water and Ozone Satellite Homogenized (SWOOSH) database, which includes vertically resolved ozone and water vapor data from a subset of the limb profiling satellite instruments operating since the 1980s. The primary SWOOSH products are zonal-mean monthly-mean time series of water vapor and ozone mixing ratio on pressure levels (12 levels per decade from 316 to 1 hPa). The SWOOSH pressure level products are provided on several independent zonal-mean grids (2.5, 5, and 10°), and additional products include two coarse 3-D griddings (30° long × 10° lat, 20° × 5°) as well as a zonal-mean isentropic product. SWOOSH includes both individual satellite source data as well as a merged data product. A key aspect of the merged product is that the source records are homogenized to account for inter-satellite biases and to minimize artificial jumps in the record. We describe the SWOOSH homogenization process, which involves adjusting the satellite data records to a "reference" satellite using coincident observations during time periods of instrument overlap. The reference satellite is chosen based on the best agreement with independent balloon-based sounding measurements, with the goal of producing a long-term data record that is both homogeneous (i.e., with minimal artificial jumps in time) and accurate (i.e., unbiased). This paper details the choice of reference measurements, homogenization, and gridding process involved in the construction of the combined SWOOSH product and also presents the ancillary information stored in SWOOSH that can be used in future studies of water vapor and ozone variability. Furthermore, a discussion of uncertainties in the combined SWOOSH record is presented, and examples of the SWOOSH record are provided to illustrate its use for studies of ozone and water vapor variability on interannual to decadal timescales. The version 2.5 SWOOSH data are publicly available at doi:10.7289/V5TD9VBX.

Evaluation of the representativeness of ground-based visibility for analysing the spatial and temporal variability of aerosol optical thickness in China

Although visibility is a widely-used indicator to quantify the aerosol loadings, only a few studies have been analyzed the representativeness of visibility in deriving Aerosol Optical Thickness (AOT). In this paper, ground-based visibility, MODerate-resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR) monthly AOT products between July 2002 and December 2014 were analyzed in order to extract the dominant modes of variability using the Singular Value Decomposition (SVD) method. The method has significant merit to reduce data dimension and examine both spatial and temporal variability simultaneously. Results indicated that the satellite retrieved AOTs agreed well with ground-based visibility in terms of inter-annual variability. The correlation coefficients in the first deseasonalized mode are greater than 0.65 between visibility and satellite AOT products. However, large differences were observed in the seasonal variability between ground-based visibility and AOT. In addition, Aerosol vertical distribution from LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies (LIVAS) and cloud data from ground-based meteorological station were used to investigate the seasonal variability disagreement. The AOT values derived from LIVAS extinction coefficients between 0 and 500 m above surface have a stronger relationship with visibility, than total column AOT with visibility. It also indicates that seasonal variation of aerosol vertical distribution is the main cause of the disagreement between two parameters, and the uncertainties of satellite products also contribute to the disagreement. Results in this study highlighted that the visibility observation could only be used to depict the inter-annual AOT and more ancillary information could be used for studying seasonal AOT variation.

A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2

Abstract. We present a mapped climatology (GLODAPv2.2016b) of ocean biogeochemical variables based on the new GLODAP version 2 data product (Olsen et al., 2016; Key et al., 2015), which covers all ocean basins over the years 1972 to 2013. The quality-controlled and internally consistent GLODAPv2 was used to create global 1° × 1° mapped climatologies of salinity, temperature, oxygen, nitrate, phosphate, silicate, total dissolved inorganic carbon (TCO2), total alkalinity (TAlk), pH, and CaCO3 saturation states using the Data-Interpolating Variational Analysis (DIVA) mapping method. Improving on maps based on an earlier but similar dataset, GLODAPv1.1, this climatology also covers the Arctic Ocean. Climatologies were created for 33 standard depth surfaces. The conceivably confounding temporal trends in TCO2 and pH due to anthropogenic influence were removed prior to mapping by normalizing these data to the year 2002 using first-order calculations of anthropogenic carbon accumulation rates. We additionally provide maps of accumulated anthropogenic carbon in the year 2002 and of preindustrial TCO2. For all parameters, all data from the full 1972–2013 period were used, including data that did not receive full secondary quality control. The GLODAPv2.2016b global 1° × 1° mapped climatologies, including error fields and ancillary information, are available at the GLODAPv2 web page at the Carbon Dioxide Information Analysis Center (CDIAC; doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2).

Featured Collection Introduction: Open Water Data Initiative

Featured Collection Introduction: Open Water Data Initiative

A high definition view of the COSMOS Wall atz ~ 0.73

We present a study of a large filamentary structure at z~0.73 in the field of the COSMOS survey, the so-called COSMOS Wall. This structure encompasses a comprehensive range of environments from a dense cluster and a number of galaxy groups to filaments, less dense regions, and adjacent voids. It thus provides a valuable laboratory for the accurate mapping of environmental effects on galaxy evolution at a look-back time of ~6.5 Gyr, when the Universe was roughly half its present age. We performed deep spectroscopic observations with VIMOS at VLT of a K-band selected sample of galaxies in this complex structure, building a sample of galaxies complete in galaxy stellar mass down to a lower limit of log(M/M_sun)~ 9.8, which is significantly deeper than previously available data. Thanks to its location within the COSMOS survey, each galaxy benefits from a wealth of ancillary information. In this paper we detail the survey strategy and weighting scheme adopted to account for the biases introduced by the photometric pre-selection of our targets. We present our galaxy stellar mass and rest-frame magnitudes estimates together with a group catalog obtained with our new data and their member galaxies color/mass distribution. Owing to to our new sample we can perform a detailed, high definition mapping of the complex COSMOS Wall structure. The sharp environmental information, coupled with high quality spectroscopic information and rich ancillary data available in the COSMOS field, enables a detailed study of galaxy properties as a function of local environment in a redshift slice where environmental effects are important, and in a stellar mass range where mass and environment driven effects are both at work.

Limitations of a single-item assessment of suicide attempt history: Implications for standardized suicide risk assessment.

Although a suicide attempt history is among the single best predictors of risk for eventual death by suicide, little is known about the extent to which reporting of suicide attempts may vary by assessment type. The current study aimed to investigate the correspondence between suicide attempt history information obtained via a single-item self-report survey, multi-item self-report survey, and face-to-face clinical interview. Data were collected among a high-risk sample of undergraduates (N = 100) who endorsed a past attempt on a single-item prescreening survey. Participants subsequently completed a multi-item self-report survey, which was followed by a face-to-face clinical interview, both of which included additional questions regarding the timing and nature of previous attempts. Even though 100% of participants (n = 100) endorsed a suicide attempt history on the single-item prescreening survey, only 67% (n = 67) reported having made a suicide attempt on the multi-item follow-up survey. After incorporating ancillary information from the in-person interview, 60% of participants qualified for a Centers for Disease Control and Prevention (CDC)-defined suicide attempt. Of the 40% who did not qualify for a CDC-defined suicide attempt, 30% instead qualified for no attempt, 7% an aborted attempt, and 3% an interrupted attempt. These findings suggest that single-item assessments of suicide attempt history may result in the misclassification of prior suicidal behaviors. Given that such assessments are commonly used in research and clinical practice, these results emphasize the importance of utilizing follow-up questions and assessments to improve precision in the characterization and assessment of suicide risk. (PsycINFO Database Record

Flood Damage Analysis: First Floor Elevation Uncertainty Resulting from LiDAR-Derived Digital Surface Models

The use of high resolution ground-based light detection and ranging (LiDAR) datasets provides spatial density and vertical precision for obtaining highly accurate Digital Surface Models (DSMs). As a result, the reliability of flood damage analysis has improved significantly, owing to the increased accuracy of hydrodynamic models. In addition, considerable error reduction has been achieved in the estimation of first floor elevation, which is a critical parameter for determining structural and content damages in buildings. However, as with any discrete measurement technique, LiDAR data contain object space ambiguities, especially in urban areas where the presence of buildings and the floodplain gives rise to a highly complex landscape that is largely corrected by using ancillary information based on the addition of breaklines to a triangulated irregular network (TIN). The present study provides a methodological approach for assessing uncertainty regarding first floor elevation. This is based on: (i) generation an urban TIN from LiDAR data with a density of 0.5 points·m−2, complemented with the river bathymetry obtained from a field survey with a density of 0.3 points·m−2. The TIN was subsequently improved by adding breaklines and was finally transformed to a raster with a spatial resolution of 2 m; (ii) implementation of a two-dimensional (2D) hydrodynamic model based on the 500-year flood return period. The high resolution DSM obtained in the previous step, facilitated addressing the modelling, since it represented suitable urban features influencing hydraulics (e.g., streets and buildings); and (iii) determination of first floor elevation uncertainty within the 500-year flood zone by performing Monte Carlo simulations based on geostatistics and 1997 control elevation points in order to assess error. Deviations in first floor elevation (average: 0.56 m and standard deviation: 0.33 m) show that this parameter has to be neatly characterized in order to obtain reliable assessments of flood damage assessments and implement realistic risk management.