Statistical Analyses of Second Indoor Bio-Release Field Evaluation Study at Idaho National Laboratory

In September 2008 a large-scale testing operation (referred to as the INL-2 test) was performed within a two-story building (PBF-632) at the Idaho National Laboratory (INL). The report “Operational Observations on the INL-2 Experiment” defines the seven objectives for this test and discusses the results and conclusions. This is further discussed in the introduction of this report. The INL-2 test consisted of five tests (events) in which a floor (level) of the building was contaminated with the harmless biological warfare agent simulant Bg and samples were taken in most, if not all, of the rooms on the contaminated floor. After the sampling, the building was decontaminated, and the next test performed. Judgmental samples and probabilistic samples were determined and taken during each test. Vacuum, wipe, and swab samples were taken within each room. The purpose of this report is to study an additional four topics that were not within the scope of the original report. These topics are: 1) assess the quantitative assumptions about the data being normally or log-normally distributed; 2) evaluate differences and quantify the sample to sample variability within a room and across the rooms; 3) perform geostatistical types of analyses to study spatial correlations; and 4) quantify the differences observed between surface types and sampling methods for each scenario and study the consistency across the scenarios. The following four paragraphs summarize the results of each of the four additional analyses. All samples after decontamination came back negative. Because of this, it was not appropriate to determine if these clearance samples were normally distributed. As Table 1 shows, the characterization data consists of values between and inclusive of 0 and 100 CFU/cm2 (100 was the value assigned when the number is too numerous to count). The 100 values are generally much bigger than the rest of the data, causing the data to be right skewed. There are also a significant number of zeros. Using QQ plots these data characteristics show a lack of normality from the data after contamination. Normality is improved when looking at log(CFU/cm2). Variance component analysis (VCA) and analysis of variance (ANOVA) were used to estimate the amount of variance due to each source and to determine which sources of variability were statistically significant. In general, the sampling methods interacted with the across event variability and with the across room variability. For this reason, it was decided to do analyses for each sampling method, individually. The between event variability and between room variability were significant for each method, except for the between event variability for the swabs. For both the wipes and vacuums, the within room standard deviation was much larger (26.9 for wipes and 7.086 for vacuums) than the between event standard deviation (6.552 for wipes and 1.348 for vacuums) and the between room standard deviation (6.783 for wipes and 1.040 for vacuums). Swabs between room standard deviation was 0.151, while both the within room and between event standard deviations are less than 0.10 (all measurements in CFU/cm2)

Experimental and Sampling Design for the INL-2 Sample Collection Operational Test

This report describes the experimental and sampling design developed to assess sampling approaches and methods for detecting contamination in a building and clearing the building for use after decontamination. An Idaho National Laboratory (INL) building will be contaminated with BG (Bacillus globigii, renamed Bacillus atrophaeus), a simulant for Bacillus anthracis (BA). The contamination, sampling, decontamination, and re-sampling will occur per the experimental and sampling design. This INL-2 Sample Collection Operational Test is being planned by the Validated Sampling Plan Working Group (VSPWG). The primary objectives are: 1) Evaluate judgmental and probabilistic sampling for characterization as well as probabilistic and combined (judgment and probabilistic) sampling approaches for clearance, 2) Conduct these evaluations for gradient contamination (from low or moderate down to absent or undetectable) for different initial concentrations of the contaminant, 3) Explore judgment composite sampling approaches to reduce sample numbers, 4) Collect baseline data to serve as an indication of the actual levels of contamination in the tests. A combined judgmental and random (CJR) approach uses Bayesian methodology to combine judgmental and probabilistic samples to make clearance statements of the form "X% confidence that at least Y% of an area does not contain detectable contamination” (X%/Y% clearance statements). The INL-2 experimental design has five test events, which 1) vary the floor of the INL building on which the contaminant will be released, 2) provide for varying the amount of contaminant released to obtain desired concentration gradients, and 3) investigate overt as well as covert release of contaminants. Desirable contaminant gradients would have moderate to low concentrations of contaminant in rooms near the release point, with concentrations down to zero in other rooms. Such gradients would provide a range of contamination levels to challenge the sampling, sample extraction, and analytical methods to be used in the INL-2 study. For each of the five test events, the specified floor of the INL building will be contaminated with BG using a point-release device located in the room specified in the experimental design. Then quality control (QC), reference material coupon (RMC), judgmental, and probabilistic samples will be collected according to the sampling plan for each test event. Judgmental samples will be selected based on professional judgment and prior information. Probabilistic samples were selected with a random aspect and in sufficient numbers to provide desired confidence for detecting contamination or clearing uncontaminated (or decontaminated) areas. Following sample collection for a given test event, the INL building will be decontaminated. For possibly contaminated areas, the numbers of probabilistic samples were chosen to provide 95% confidence of detecting contaminated areas of specified sizes. For rooms that may be uncontaminated following a contamination event, or for whole floors after decontamination, the numbers of judgmental and probabilistic samples were chosen using the CJR approach. The numbers of samples were chosen to support making X%/Y% clearance statements with X = 95% or 99% and Y = 96% or 97%. The experimental and sampling design also provides for making X%/Y% clearance statements using only probabilistic samples. For each test event, the numbers of characterization and clearance samples were selected within limits based on operational considerations while still maintaining high confidence for detection and clearance aspects. The sampling design for all five test events contains 2085 samples, with 1142 after contamination and 943 after decontamination. These numbers include QC, RMC, judgmental, and probabilistic samples. The experimental and sampling design specified in this report provides a good statistical foundation for achieving the objectives of the INL-2 study

Evaluation of Infrasound and Strobe Lights to Elicit Avoidance Behavior in Juvenile Salmon and Char.

Experimental tests were conducted using hatchery reared and wild juvenile chinook salmon Oncorhynchus tshawytscha, eastern brook trout Salvelinus fontinalis, and rainbow trout O. mykiss to determine specific behavior responses to infrasound (<20 Hz) and flashing strobe lights. Caged fish were acclimated in a static test tank and their behavior was recorded using low light cameras. Species specific behavior was characterized by measuring movements of the fish within the cage as well as observing startle and habituation responses. Wild chinook salmon (40-45 mm) and hatchery reared chinook salmon (45-50mm) exhibited avoidance responses when initially exposed to a 10 Hz volume displacement source. Rainbow and eastern brook trout (25-100 mm) did not respond with avoidance or other behaviors to infrasound. Habituation to the infrasound source was evident for chinook salmon during repeated exposures. Wild and hatchery chinook displayed a higher proportion of movement during the initial exposures to infrasound when the acclimation period in the test tank was 2-3 h as compared to a 12-15 h acclimation period. A flashing strobe light produced higher and more consistent movement rates in wild chinook (60% of the tests); hatchery reared chinook salmon (50%) and rainbow trout (80%). No measurable movement or other responses was observed for eastern brook trout. Little if any habituation was observed during repeated exposures to strobe lights. Results from this study indicate that consistent repeatable responses can be elicited from some fish using high intensity strobe lights under a controlled laboratory testing. The specific behaviors observed in these experiments might be used to predict how fish might react to low frequency sound and strobe lights in a screening facility. Because sub-yearling salmonids and resident species are susceptible from becoming entrained at water diversion structures we conducted tests in conjunction with our evaluation of juvenile fish screening facilities. This is the reason our tests focused on fry life stages

Calculating Confidence, Uncertainty, and Numbers of Samples When Using Statistical Sampling Approaches to Characterize and Clear Contaminated Areas

This report discusses the methodology, formulas, and inputs needed to make characterization and clearance decisions for Bacillus anthracis-contaminated and uncontaminated (or decontaminated) areas using a statistical sampling approach. Specifically, the report includes the methods and formulas for calculating the • number of samples required to achieve a specified confidence in characterization and clearance decisions • confidence in making characterization and clearance decisions for a specified number of samples for two common statistically based environmental sampling approaches. In particular, the report addresses an issue raised by the Government Accountability Office by providing methods and formulas to calculate the confidence that a decision area is uncontaminated (or successfully decontaminated) if all samples collected according to a statistical sampling approach have negative results. Key to addressing this topic is the probability that an individual sample result is a false negative, which is commonly referred to as the false negative rate (FNR). The two statistical sampling approaches currently discussed in this report are 1) hotspot sampling to detect small isolated contaminated locations during the characterization phase, and 2) combined judgment and random (CJR) sampling during the clearance phase. Typically if contamination is widely distributed in a decision area, it will be detectable via judgment sampling during the characterization phrase. Hotspot sampling is appropriate for characterization situations where contamination is not widely distributed and may not be detected by judgment sampling. CJR sampling is appropriate during the clearance phase when it is desired to augment judgment samples with statistical (random) samples. The hotspot and CJR statistical sampling approaches are discussed in the report for four situations: 1. qualitative data (detect and non-detect) when the FNR = 0 or when using statistical sampling methods that account for FNR > 0 2. qualitative data when the FNR > 0 but statistical sampling methods are used that assume the FNR = 0 3. quantitative data (e.g., contaminant concentrations expressed as CFU/cm2) when the FNR = 0 or when using statistical sampling methods that account for FNR > 0 4. quantitative data when the FNR > 0 but statistical sampling methods are used that assume the FNR = 0. For Situation 2, the hotspot sampling approach provides for stating with Z% confidence that a hotspot of specified shape and size with detectable contamination will be found. Also for Situation 2, the CJR approach provides for stating with X% confidence that at least Y% of the decision area does not contain detectable contamination. Forms of these statements for the other three situations are discussed in Section 2.2. Statistical methods that account for FNR > 0 currently only exist for the hotspot sampling approach with qualitative data (or quantitative data converted to qualitative data). This report documents the current status of methods and formulas for the hotspot and CJR sampling approaches. Limitations of these methods are identified. Extensions of the methods that are applicable when FNR = 0 to account for FNR > 0, or to address other limitations, will be documented in future revisions of this report if future funding supports the development of such extensions. For quantitative data, this report also presents statistical methods and formulas for 1. quantifying the uncertainty in measured sample results 2. estimating the true surface concentration corresponding to a surface sample 3. quantifying the uncertainty of the estimate of the true surface concentration. All of the methods and formulas discussed in the report were applied to example situations to illustrate application of the methods and interpretation of the results

Experimental Design for the INL Sample Collection Operational Test

This document describes the test events and numbers of samples comprising the experimental design that was developed for the contamination, decontamination, and sampling of a building at the Idaho National Laboratory (INL). This study is referred to as the INL Sample Collection Operational Test. Specific objectives were developed to guide the construction of the experimental design. The main objective is to assess the relative abilities of judgmental and probabilistic sampling strategies to detect contamination in individual rooms or on a whole floor of the INL building. A second objective is to assess the use of probabilistic and Bayesian (judgmental + probabilistic) sampling strategies to make clearance statements of the form “X% confidence that at least Y% of a room (or floor of the building) is not contaminated. The experimental design described in this report includes five test events. The test events (i) vary the floor of the building on which the contaminant will be released, (ii) provide for varying or adjusting the concentration of contaminant released to obtain the ideal concentration gradient across a floor of the building, and (iii) investigate overt as well as covert release of contaminants. The ideal contaminant gradient would have high concentrations of contaminant in rooms near the release point, with concentrations decreasing to zero in rooms at the opposite end of the building floor. For each of the five test events, the specified floor of the INL building will be contaminated with BG, a stand-in for Bacillus anthracis. The BG contaminant will be disseminated from a point-release device located in the room specified in the experimental design for each test event. Then judgmental and probabilistic samples will be collected according to the pre-specified sampling plan. Judgmental samples will be selected based on professional judgment and prior information. Probabilistic samples will be selected in sufficient numbers to provide desired confidence for detecting contamination or clearing uncontaminated (or decontaminated) areas. Following sample collection for a given test event, the INL building will be decontaminated using Cl2O gas. For possibly contaminated areas (individual rooms or the whole floor of a building), the numbers of probabilistic samples were chosen to provide 95% confidence of detecting contaminated areas of specified sizes. The numbers of judgmental samples were chosen based on guidance from experts in judgmental sampling. For rooms that may be uncontaminated following a contamination event, or for whole floors after decontamination, the numbers of judgmental and probabilistic samples were chosen using a Bayesian approach that provides for combining judgmental and probabilistic samples to make a clearance statement of the form “95% confidence that at least 99% of the room (or floor) is not contaminated”. The experimental design also provides for making 95%/Y% clearance statements using only probabilistic samples, where Y < 99. For each test event, the numbers of samples were selected for a minimal plan (containing fewer samples) and a preferred plan (containing more samples). The preferred plan is recommended over the minimal plan. The preferred plan specifies a total of 1452 samples, 912 after contamination and 540 after decontamination. The minimal plan specifies a total of 1119 samples, 744 after contamination and 375 after decontamination. If the advantages of the “after decontamination” portion of the preferred plan are judged to be small compared to the “after decontamination” portion of the minimal plan, it is an option to combine the “after contamination” portion of the preferred plan (912 samples) with the “after decontamination” portion of the minimal plan (375 samples). This hybrid plan would involve a total of 1287 samples

Identification of atypical flight patterns

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis

Energy Index For Aircraft Maneuvers

Method and system for analyzing, separately or in combination, kinetic energy and potential energy and/or their time derivatives, measured or estimated or computed, for an aircraft in approach phase or in takeoff phase, to determine if the aircraft is or will be put in an anomalous configuration in order to join a stable approach path or takeoff path. A 3 reference value of kinetic energy andor potential energy (or time derivatives thereof) is provided, and a comparison index .for the estimated energy and reference energy is computed and compared with a normal range of index values for a corresponding aircraft maneuver. If the computed energy index lies outside the normal index range, this phase of the aircraft is identified as anomalous, non-normal or potentially unstable

Historical Analysis of Aircraft Flight Parameters

Method and system for analyzing and displaying one or more present flight parameter values (FP(t) of an aircraft in motion at a measurement time t(sub n), and for comparing the present flight parameter value with a selected percentage band, containing historical flight parameter data for similar conditions

Information Display System for Atypical Flight Phase

Method and system for displaying information on one or more aircraft flights, where at least one flight is determined to have at least one atypical flight phase according to specified criteria. A flight parameter trace for an atypical phase is displayed and compared graphically with a group of traces, for the corresponding flight phase and corresponding flight parameter, for flights that do not manifest atypicality in that phase

Comparison of Two Quantitative Methods of Discerning Airspace Enlargement in Smoke-Exposed Mice

In this work, we compare two methods for evaluating and quantifying pulmonary airspace enlargement in a mouse model of chronic cigarette smoke exposure. Standard stereological sample preparation, sectioning, and imaging of mouse lung tissues were performed for semi-automated acquisition of mean linear intercept (Lm) data. After completion of the Lm measurements, D2, a metric of airspace enlargement, was measured in a blinded manner on the same lung images using a fully automated technique developed in-house. An analysis of variance (ANOVA) shows that although Lm was able to separate the smoke-exposed and control groups with statistical significance (p = 0.034), D2 was better able to differentiate the groups (p<0.001) and did so without any overlap between the control and smoke-exposed individual animal data. In addition, the fully automated implementation of D2 represented a time savings of at least 24x over semi-automated Lm measurements. Although D2 does not provide 3D stereological metrics of airspace dimensions as Lm does, results show that it has higher sensitivity and specificity for detecting the subtle airspace enlargement one would expect to find in mild or early stage emphysema. Therefore, D2 may serve as a more accurate screening measure for detecting early lung disease than Lm