Estimating the concordance probability in a survival analysis with a discrete number of risk groups.
Heller, Glenn; Mo, Qianxing
2016-04-01
A clinical risk classification system is an important component of a treatment decision algorithm. A measure used to assess the strength of a risk classification system is discrimination, and when the outcome is survival time, the most commonly applied global measure of discrimination is the concordance probability. The concordance probability represents the pairwise probability of lower patient risk given longer survival time. The c-index and the concordance probability estimate have been used to estimate the concordance probability when patient-specific risk scores are continuous. In the current paper, the concordance probability estimate and an inverse probability censoring weighted c-index are modified to account for discrete risk scores. Simulations are generated to assess the finite sample properties of the concordance probability estimate and the weighted c-index. An application of these measures of discriminatory power to a metastatic prostate cancer risk classification system is examined.
Estimators of annual probability of infection for quantitative microbial risk assessment.
Karavarsamis, N; Hamilton, A J
2010-06-01
Four estimators of annual infection probability were compared pertinent to Quantitative Microbial Risk Analysis (QMRA). A stochastic model, the Gold Standard, was used as the benchmark. It is a product of independent daily infection probabilities which in turn are based on daily doses. An alternative and commonly-used estimator, here referred to as the Naïve, assumes a single daily infection probability from a single value of daily dose. The typical use of this estimator in stochastic QMRA involves the generation of a distribution of annual infection probabilities, but since each of these is based on a single realisation of the dose distribution, the resultant annual infection probability distribution simply represents a set of inaccurate estimates. While the medians of both distributions were within an order of magnitude for our test scenario, the 95th percentiles, which are sometimes used in QMRA as conservative estimates of risk, differed by around one order of magnitude. The other two estimators examined, the Geometric and Arithmetic, were closely related to the Naïve and use the same equation, and both proved to be poor estimators. Lastly, this paper proposes a simple adjustment to the Gold Standard equation accommodating periodic infection probabilities when the daily infection probabilities are unknown.
Estimation of risk probability for gravity-driven pyroclastic flows at Volcan Colima, Mexico
NASA Astrophysics Data System (ADS)
Sheridan, Michael F.; Macías, JoséLuis
1995-07-01
Mapped pyroclastic flow terminations at Colima volcano were used to determine energy lines. We assumed straight energy lines, initial flow velocities of zero and flow movement starting from the volcano summit. Heim coefficients ( H/L) of the flows plotted on a histogram cluster in two distinct modes. One corresponds to large pyroclastic flows (pumice flows and block-and-ash flows) for which Heim coefficients range from 0.22 to 0.28. This group has a mean value of 0.24 and a standard deviation of 0.021. The other mode corresponds to small block-and-ash avalanches which have Heim coefficients that range from 0.33 to 0.38, a mean value of 0.35 and a standard deviation of 0.025. No flow terminations yield Heim coefficients in the range from 0.28 to 0.33. This break probably separates fluidized pyroclastic flows from less mobile hot rock avalanches. Plots of Heim coefficients on arithmetic probability paper are approximate probability functions for the two types of flows. Heim coefficients calculated for straight lines that connect population centers with the volcano summit can be used with this type of graph to estimate the probability that either type of pyroclastic flow would reach the site. We used this technique to determine risk probabilities for various localities around Colima volcano. These calculations indicate that Laguna Verde, Yerbabuena, Cofradia-El Fresnal, El Naranjal, Atenguillo, La Becerrera, Montitlan and San Antonio have a probability ranging from 99 to 6% of being covered by large pyroclastic flows. Laguna Verde and Yerbabuena are the sites with the highest probability of being reached by small block-and-ash avalanches. The depression situated south-southwest of Colima volcano is an area with a very high probability of being affected by the pyroclastic phenomena considered above. The small avalanche produced by dome collapse of Colima on April 16, 1991 traveled along the barranca El Cordobán toward the area of the highest probability on our map.
PROBABILITY SURVEYS , CONDITIONAL PROBABILITIES AND ECOLOGICAL RISK ASSESSMENT
We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...
Probability Surveys, Conditional Probability, and Ecological Risk Assessment
We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency’s (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...
2016-07-01
A free mobile phone app has been launched providing nurses and other hospital clinicians with a simple way to identify high-risk surgical patients. The app is a phone version of the Surgical Outcome Risk Tool (SORT), originally developed for online use with computers by researchers from the National Confidential Enquiry into Patient Outcome and Death and the University College London Hospital Surgical Outcomes Research Centre. SORT uses information about patients' health and planned surgical procedures to estimate the risk of death within 30 days of an operation. The percentages are only estimates, taking into account the general risks of the procedures and some information about patients, and should not be confused with patient-specific estimates in individual cases. PMID:27369709
Point estimates for probability moments
Rosenblueth, Emilio
1975-01-01
Given a well-behaved real function Y of a real random variable X and the first two or three moments of X, expressions are derived for the moments of Y as linear combinations of powers of the point estimates y(x+) and y(x-), where x+ and x- are specific values of X. Higher-order approximations and approximations for discontinuous Y using more point estimates are also given. Second-moment approximations are generalized to the case when Y is a function of several variables. PMID:16578731
Estimating flood exceedance probabilities in estuarine regions
NASA Astrophysics Data System (ADS)
Westra, Seth; Leonard, Michael
2016-04-01
Flood events in estuarine regions can arise from the interaction of extreme rainfall and storm surge. Determining flood level exceedance probabilities in these regions is complicated by the dependence of these processes for extreme events. A comprehensive study of tide and rainfall gauges along the Australian coastline was conducted to determine the dependence of these extremes using a bivariate logistic threshold-excess model. The dependence strength is shown to vary as a function of distance over many hundreds of kilometres indicating that the dependence arises due to synoptic scale meteorological forcings. It is also shown to vary as a function of storm burst duration, time lag between the extreme rainfall and the storm surge event. The dependence estimates are then used with a bivariate design variable method to determine flood risk in estuarine regions for a number of case studies. Aspects of the method demonstrated in the case studies include, the resolution and range of the hydraulic response table, fitting of probability distributions, computational efficiency, uncertainty, potential variation in marginal distributions due to climate change, and application to two dimensional output from hydraulic models. Case studies are located on the Swan River (Western Australia), Nambucca River and Hawkesbury Nepean River (New South Wales).
Uncertainty analysis for Probable Maximum Precipitation estimates
NASA Astrophysics Data System (ADS)
Micovic, Zoran; Schaefer, Melvin G.; Taylor, George H.
2015-02-01
An analysis of uncertainty associated with Probable Maximum Precipitation (PMP) estimates is presented. The focus of the study is firmly on PMP estimates derived through meteorological analyses and not on statistically derived PMPs. Theoretical PMP cannot be computed directly and operational PMP estimates are developed through a stepwise procedure using a significant degree of subjective professional judgment. This paper presents a methodology for portraying the uncertain nature of PMP estimation by analyzing individual steps within the PMP derivation procedure whereby for each parameter requiring judgment, a set of possible values is specified and accompanied by expected probabilities. The resulting range of possible PMP values can be compared with the previously derived operational single-value PMP, providing measures of the conservatism and variability of the original estimate. To our knowledge, this is the first uncertainty analysis conducted for a PMP derived through meteorological analyses. The methodology was tested on the La Joie Dam watershed in British Columbia. The results indicate that the commonly used single-value PMP estimate could be more than 40% higher when possible changes in various meteorological variables used to derive the PMP are considered. The findings of this study imply that PMP estimates should always be characterized as a range of values recognizing the significant uncertainties involved in PMP estimation. In fact, we do not know at this time whether precipitation is actually upper-bounded, and if precipitation is upper-bounded, how closely PMP estimates approach the theoretical limit.
Conflict Probability Estimation for Free Flight
NASA Technical Reports Server (NTRS)
Paielli, Russell A.; Erzberger, Heinz
1996-01-01
The safety and efficiency of free flight will benefit from automated conflict prediction and resolution advisories. Conflict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however. An estimate is therefore needed of the probability that a conflict will occur, given a pair of predicted trajectories and their levels of uncertainty. A method is developed in this paper to estimate that conflict probability. The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and Monte Carlo validation are presented.
Holmberg, Christine; Waters, Erika A.; Whitehouse, Katie; Daly, Mary; McCaskill-Stevens, Worta
2015-01-01
Background Decision making experts emphasize that understanding and using probabilistic information is important for making informed decisions about medical treatments involving complex risk-benefit tradeoffs. Yet empirical research demonstrates that individuals may not use probabilities when making decisions. Objectives To explore decision making and the use of probabilities for decision making from the perspective of women who were risk-eligible to enroll in the Study of Tamoxifen and Raloxifene (STAR). Methods We conducted narrative interviews with 20 women who agreed to participate in STAR and 20 women who declined. The project was based on a narrative approach. Analysis included the development of summaries of each narrative, and thematic analysis with developing a coding scheme inductively to code all transcripts to identify emerging themes. Results Interviewees explained and embedded their STAR decisions within experiences encountered throughout their lives. Such lived experiences included but were not limited to breast cancer family history, personal history of breast biopsies, and experiences or assumptions about taking tamoxifen or medicines more generally. Conclusions Women’s explanations of their decisions about participating in a breast cancer chemoprevention trial were more complex than decision strategies that rely solely on a quantitative risk-benefit analysis of probabilities derived from populations In addition to precise risk information, clinicians and risk communicators should recognize the importance and legitimacy of lived experience in individual decision making. PMID:26183166
Model estimates hurricane wind speed probabilities
NASA Astrophysics Data System (ADS)
Mumane, Richard J.; Barton, Chris; Collins, Eric; Donnelly, Jeffrey; Eisner, James; Emanuel, Kerry; Ginis, Isaac; Howard, Susan; Landsea, Chris; Liu, Kam-biu; Malmquist, David; McKay, Megan; Michaels, Anthony; Nelson, Norm; O Brien, James; Scott, David; Webb, Thompson, III
In the United States, intense hurricanes (category 3, 4, and 5 on the Saffir/Simpson scale) with winds greater than 50 m s -1 have caused more damage than any other natural disaster [Pielke and Pielke, 1997]. Accurate estimates of wind speed exceedance probabilities (WSEP) due to intense hurricanes are therefore of great interest to (re)insurers, emergency planners, government officials, and populations in vulnerable coastal areas.The historical record of U.S. hurricane landfall is relatively complete only from about 1900, and most model estimates of WSEP are derived from this record. During the 1899-1998 period, only two category-5 and 16 category-4 hurricanes made landfall in the United States. The historical record therefore provides only a limited sample of the most intense hurricanes.
PROBABILITY SURVEYS, CONDITIONAL PROBABILITIES, AND ECOLOGICAL RISK ASSESSMENT
We show that probability-based environmental resource monitoring programs, such as U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Asscssment Program EMAP) can be analyzed with a conditional probability analysis (CPA) to conduct quantitative probabi...
VOLCANIC RISK ASSESSMENT - PROBABILITY AND CONSEQUENCES
G.A. Valentine; F.V. Perry; S. Dartevelle
2005-08-26
Risk is the product of the probability and consequences of an event. Both of these must be based upon sound science that integrates field data, experiments, and modeling, but must also be useful to decision makers who likely do not understand all aspects of the underlying science. We review a decision framework used in many fields such as performance assessment for hazardous and/or radioactive waste disposal sites that can serve to guide the volcanological community towards integrated risk assessment. In this framework the underlying scientific understanding of processes that affect probability and consequences drive the decision-level results, but in turn these results can drive focused research in areas that cause the greatest level of uncertainty at the decision level. We review two examples of the determination of volcanic event probability: (1) probability of a new volcano forming at the proposed Yucca Mountain radioactive waste repository, and (2) probability that a subsurface repository in Japan would be affected by the nearby formation of a new stratovolcano. We also provide examples of work on consequences of explosive eruptions, within the framework mentioned above. These include field-based studies aimed at providing data for ''closure'' of wall rock erosion terms in a conduit flow model, predictions of dynamic pressure and other variables related to damage by pyroclastic flow into underground structures, and vulnerability criteria for structures subjected to conditions of explosive eruption. Process models (e.g., multiphase flow) are important for testing the validity or relative importance of possible scenarios in a volcanic risk assessment. We show how time-dependent multiphase modeling of explosive ''eruption'' of basaltic magma into an open tunnel (drift) at the Yucca Mountain repository provides insight into proposed scenarios that include the development of secondary pathways to the Earth's surface. Addressing volcanic risk within a decision
Estimation of transition probabilities of credit ratings
NASA Astrophysics Data System (ADS)
Peng, Gan Chew; Hin, Pooi Ah
2015-12-01
The present research is based on the quarterly credit ratings of ten companies over 15 years taken from the database of the Taiwan Economic Journal. The components in the vector mi (mi1, mi2,⋯, mi10) may first be used to denote the credit ratings of the ten companies in the i-th quarter. The vector mi+1 in the next quarter is modelled to be dependent on the vector mi via a conditional distribution which is derived from a 20-dimensional power-normal mixture distribution. The transition probability Pkl (i ,j ) for getting mi+1,j = l given that mi, j = k is then computed from the conditional distribution. It is found that the variation of the transition probability Pkl (i ,j ) as i varies is able to give indication for the possible transition of the credit rating of the j-th company in the near future.
Probability shapes perceptual precision: A study in orientation estimation.
Jabar, Syaheed B; Anderson, Britt
2015-12-01
Probability is known to affect perceptual estimations, but an understanding of mechanisms is lacking. Moving beyond binary classification tasks, we had naive participants report the orientation of briefly viewed gratings where we systematically manipulated contingent probability. Participants rapidly developed faster and more precise estimations for high-probability tilts. The shapes of their error distributions, as indexed by a kurtosis measure, also showed a distortion from Gaussian. This kurtosis metric was robust, capturing probability effects that were graded, contextual, and varying as a function of stimulus orientation. Our data can be understood as a probability-induced reduction in the variability or "shape" of estimation errors, as would be expected if probability affects the perceptual representations. As probability manipulations are an implicit component of many endogenous cuing paradigms, changes at the perceptual level could account for changes in performance that might have traditionally been ascribed to "attention."
Fisher classifier and its probability of error estimation
NASA Technical Reports Server (NTRS)
Chittineni, C. B.
1979-01-01
Computationally efficient expressions are derived for estimating the probability of error using the leave-one-out method. The optimal threshold for the classification of patterns projected onto Fisher's direction is derived. A simple generalization of the Fisher classifier to multiple classes is presented. Computational expressions are developed for estimating the probability of error of the multiclass Fisher classifier.
NESTEM-QRAS: A Tool for Estimating Probability of Failure
NASA Technical Reports Server (NTRS)
Patel, Bhogilal M.; Nagpal, Vinod K.; Lalli, Vincent A.; Pai, Shantaram; Rusick, Jeffrey J.
2002-01-01
An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.
Estimating the probability for major gene Alzheimer disease
Farrer, L.A. Boston Univ. School of Public Health, Boston, MA ); Cupples, L.A. )
1994-02-01
Alzheimer disease (AD) is a neuropsychiatric illness caused by multiple etiologies. Prediction of whether AD is genetically based in a given family is problematic because of censoring bias among unaffected relatives as a consequence of the late onset of the disorder, diagnostic uncertainties, heterogeneity, and limited information in a single family. The authors have developed a method based on Bayesian probability to compute values for a continuous variable that ranks AD families as having a major gene form of AD (MGAD). In addition, they have compared the Bayesian method with a maximum-likelihood approach. These methods incorporate sex- and age-adjusted risk estimates and allow for phenocopies and familial clustering of age on onset. Agreement is high between the two approaches for ranking families as MGAD (Spearman rank [r] = .92). When either method is used, the numerical outcomes are sensitive to assumptions of the gene frequency and cumulative incidence of the disease in the population. Consequently, risk estimates should be used cautiously for counseling purposes; however, there are numerous valid applications of these procedures in genetic and epidemiological studies. 41 refs., 4 figs., 3 tabs.
Schlenker, R.A.
1981-01-01
The primary sources of information on the skeletal effects of internal emitters in humans are the US radium cases with occupational and medical exposures to /sup 226/ /sup 228/Ra and the German patients injected with /sup 224/Ra primarily for treatment of ankylosing spondylitis and tuberculosis. During the past decade, dose-response data from both study populations have been used by committees, e.g., the BEIR committees, to estimate risks at low dose levels. NCRP Committee 57 and its task groups are now engaged in making risk estimates for internal emitters. This paper presents brief discussions of the radium data, the results of some new analyses and suggestions for expressing risk estimates in a form appropriate to radiation protection.
Naive Probability: Model-Based Estimates of Unique Events.
Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Philip N
2015-08-01
We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning.
Naive Probability: Model-Based Estimates of Unique Events.
Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Philip N
2015-08-01
We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P(A), P(B), P(A and B), disjunctions: P(A), P(B), P(A or B or both), and conditional probabilities P(A), P(B), P(B|A). They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning. PMID:25363706
Conditional probability density function estimation with sigmoidal neural networks.
Sarajedini, A; Hecht-Nielsen, R; Chau, P M
1999-01-01
Real-world problems can often be couched in terms of conditional probability density function estimation. In particular, pattern recognition, signal detection, and financial prediction are among the multitude of applications requiring conditional density estimation. Previous developments in this direction have used neural nets to estimate statistics of the distribution or the marginal or joint distributions of the input-output variables. We have modified the joint distribution estimating sigmoidal neural network to estimate the conditional distribution. Thus, the probability density of the output conditioned on the inputs is estimated using a neural network. We have derived and implemented the learning laws to train the network. We show that this network has computational advantages over a brute force ratio of joint and marginal distributions. We also compare its performance to a kernel conditional density estimator in a larger scale (higher dimensional) problem simulating more realistic conditions.
Nonparametric probability density estimation by optimization theoretic techniques
NASA Technical Reports Server (NTRS)
Scott, D. W.
1976-01-01
Two nonparametric probability density estimators are considered. The first is the kernel estimator. The problem of choosing the kernel scaling factor based solely on a random sample is addressed. An interactive mode is discussed and an algorithm proposed to choose the scaling factor automatically. The second nonparametric probability estimate uses penalty function techniques with the maximum likelihood criterion. A discrete maximum penalized likelihood estimator is proposed and is shown to be consistent in the mean square error. A numerical implementation technique for the discrete solution is discussed and examples displayed. An extensive simulation study compares the integrated mean square error of the discrete and kernel estimators. The robustness of the discrete estimator is demonstrated graphically.
Low-probability flood risk modeling for New York City.
Aerts, Jeroen C J H; Lin, Ning; Botzen, Wouter; Emanuel, Kerry; de Moel, Hans
2013-05-01
The devastating impact by Hurricane Sandy (2012) again showed New York City (NYC) is one of the most vulnerable cities to coastal flooding around the globe. The low-lying areas in NYC can be flooded by nor'easter storms and North Atlantic hurricanes. The few studies that have estimated potential flood damage for NYC base their damage estimates on only a single, or a few, possible flood events. The objective of this study is to assess the full distribution of hurricane flood risk in NYC. This is done by calculating potential flood damage with a flood damage model that uses many possible storms and surge heights as input. These storms are representative for the low-probability/high-impact flood hazard faced by the city. Exceedance probability-loss curves are constructed under different assumptions about the severity of flood damage. The estimated flood damage to buildings for NYC is between US$59 and 129 millions/year. The damage caused by a 1/100-year storm surge is within a range of US$2 bn-5 bn, while this is between US$5 bn and 11 bn for a 1/500-year storm surge. An analysis of flood risk in each of the five boroughs of NYC finds that Brooklyn and Queens are the most vulnerable to flooding. This study examines several uncertainties in the various steps of the risk analysis, which resulted in variations in flood damage estimations. These uncertainties include: the interpolation of flood depths; the use of different flood damage curves; and the influence of the spectra of characteristics of the simulated hurricanes.
Estimating the empirical probability of submarine landslide occurrence
Geist, Eric L.; Parsons, Thomas E.; Mosher, David C.; Shipp, Craig; Moscardelli, Lorena; Chaytor, Jason D.; Baxter, Christopher D. P.; Lee, Homa J.; Urgeles, Roger
2010-01-01
The empirical probability for the occurrence of submarine landslides at a given location can be estimated from age dates of past landslides. In this study, tools developed to estimate earthquake probability from paleoseismic horizons are adapted to estimate submarine landslide probability. In both types of estimates, one has to account for the uncertainty associated with age-dating individual events as well as the open time intervals before and after the observed sequence of landslides. For observed sequences of submarine landslides, we typically only have the age date of the youngest event and possibly of a seismic horizon that lies below the oldest event in a landslide sequence. We use an empirical Bayes analysis based on the Poisson-Gamma conjugate prior model specifically applied to the landslide probability problem. This model assumes that landslide events as imaged in geophysical data are independent and occur in time according to a Poisson distribution characterized by a rate parameter λ. With this method, we are able to estimate the most likely value of λ and, importantly, the range of uncertainty in this estimate. Examples considered include landslide sequences observed in the Santa Barbara Channel, California, and in Port Valdez, Alaska. We confirm that given the uncertainties of age dating that landslide complexes can be treated as single events by performing statistical test of age dates representing the main failure episode of the Holocene Storegga landslide complex.
Estimation of State Transition Probabilities: A Neural Network Model
NASA Astrophysics Data System (ADS)
Saito, Hiroshi; Takiyama, Ken; Okada, Masato
2015-12-01
Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.
An application of recurrent nets to phone probability estimation.
Robinson, A J
1994-01-01
This paper presents an application of recurrent networks for phone probability estimation in large vocabulary speech recognition. The need for efficient exploitation of context information is discussed; a role for which the recurrent net appears suitable. An overview of early developments of recurrent nets for phone recognition is given along with the more recent improvements that include their integration with Markov models. Recognition results are presented for the DARPA TIMIT and Resource Management tasks, and it is concluded that recurrent nets are competitive with traditional means for performing phone probability estimation.
Bayesian Estimator of Protein-Protein Association Probabilities
2008-05-28
The Bayesian Estimator of Protein-Protein Association Probabilities (BEPro3) is a software tool for estimating probabilities of protein-protein association between bait and prey protein pairs using data from multiple-bait, multiple-replicate, protein LC-MS/MS affinity isolation experiments. BEPro3 is public domain software, has been tested on Windows XP and version 10.4 or newer of the Mac OS 10.4, and is freely available. A user guide, example dataset with analysis and additional documentation are included with the BEPro3 download.
Improving estimates of tree mortality probability using potential growth rate
Das, Adrian J.; Stephenson, Nathan L.
2015-01-01
Tree growth rate is frequently used to estimate mortality probability. Yet, growth metrics can vary in form, and the justification for using one over another is rarely clear. We tested whether a growth index (GI) that scales the realized diameter growth rate against the potential diameter growth rate (PDGR) would give better estimates of mortality probability than other measures. We also tested whether PDGR, being a function of tree size, might better correlate with the baseline mortality probability than direct measurements of size such as diameter or basal area. Using a long-term dataset from the Sierra Nevada, California, U.S.A., as well as existing species-specific estimates of PDGR, we developed growth–mortality models for four common species. For three of the four species, models that included GI, PDGR, or a combination of GI and PDGR were substantially better than models without them. For the fourth species, the models including GI and PDGR performed roughly as well as a model that included only the diameter growth rate. Our results suggest that using PDGR can improve our ability to estimate tree survival probability. However, in the absence of PDGR estimates, the diameter growth rate was the best empirical predictor of mortality, in contrast to assumptions often made in the literature.
Probability Estimation of CO2 Leakage Through Faults at Geologic Carbon Sequestration Sites
Zhang, Yingqi; Oldenburg, Curt; Finsterle, Stefan; Jordan, Preston; Zhang, Keni
2008-11-01
Leakage of CO{sub 2} and brine along faults at geologic carbon sequestration (GCS) sites is a primary concern for storage integrity. The focus of this study is on the estimation of the probability of leakage along faults or fractures. This leakage probability is controlled by the probability of a connected network of conduits existing at a given site, the probability of this network encountering the CO{sub 2} plume, and the probability of this network intersecting environmental resources that may be impacted by leakage. This work is designed to fit into a risk assessment and certification framework that uses compartments to represent vulnerable resources such as potable groundwater, health and safety, and the near-surface environment. The method we propose includes using percolation theory to estimate the connectivity of the faults, and generating fuzzy rules from discrete fracture network simulations to estimate leakage probability. By this approach, the probability of CO{sub 2} escaping into a compartment for a given system can be inferred from the fuzzy rules. The proposed method provides a quick way of estimating the probability of CO{sub 2} or brine leaking into a compartment. In addition, it provides the uncertainty range of the estimated probability.
Simulation and Estimation of Extreme Quantiles and Extreme Probabilities
Guyader, Arnaud; Hengartner, Nicolas; Matzner-Lober, Eric
2011-10-15
Let X be a random vector with distribution {mu} on Double-Struck-Capital-R {sup d} and {Phi} be a mapping from Double-Struck-Capital-R {sup d} to Double-Struck-Capital-R . That mapping acts as a black box, e.g., the result from some computer experiments for which no analytical expression is available. This paper presents an efficient algorithm to estimate a tail probability given a quantile or a quantile given a tail probability. The algorithm improves upon existing multilevel splitting methods and can be analyzed using Poisson process tools that lead to exact description of the distribution of the estimated probabilities and quantiles. The performance of the algorithm is demonstrated in a problem related to digital watermarking.
Using Correlation to Compute Better Probability Estimates in Plan Graphs
NASA Technical Reports Server (NTRS)
Bryce, Daniel; Smith, David E.
2006-01-01
Plan graphs are commonly used in planning to help compute heuristic "distance" estimates between states and goals. A few authors have also attempted to use plan graphs in probabilistic planning to compute estimates of the probability that propositions can be achieved and actions can be performed. This is done by propagating probability information forward through the plan graph from the initial conditions through each possible action to the action effects, and hence to the propositions at the next layer of the plan graph. The problem with these calculations is that they make very strong independence assumptions - in particular, they usually assume that the preconditions for each action are independent of each other. This can lead to gross overestimates in probability when the plans for those preconditions interfere with each other. It can also lead to gross underestimates of probability when there is synergy between the plans for two or more preconditions. In this paper we introduce a notion of the binary correlation between two propositions and actions within a plan graph, show how to propagate this information within a plan graph, and show how this improves probability estimates for planning. This notion of correlation can be thought of as a continuous generalization of the notion of mutual exclusion (mutex) often used in plan graphs. At one extreme (correlation=0) two propositions or actions are completely mutex. With correlation = 1, two propositions or actions are independent, and with correlation > 1, two propositions or actions are synergistic. Intermediate values can and do occur indicating different degrees to which propositions and action interfere or are synergistic. We compare this approach with another recent approach by Bryce that computes probability estimates using Monte Carlo simulation of possible worlds in plan graphs.
Methods for estimating drought streamflow probabilities for Virginia streams
Austin, Samuel H.
2014-01-01
Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.
Revising probability estimates: Why increasing likelihood means increasing impact.
Maglio, Sam J; Polman, Evan
2016-08-01
Forecasted probabilities rarely stay the same for long. Instead, they are subject to constant revision-moving upward or downward, uncertain events become more or less likely. Yet little is known about how people interpret probability estimates beyond static snapshots, like a 30% chance of rain. Here, we consider the cognitive, affective, and behavioral consequences of revisions to probability forecasts. Stemming from a lay belief that revisions signal the emergence of a trend, we find in 10 studies (comprising uncertain events such as weather, climate change, sex, sports, and wine) that upward changes to event-probability (e.g., increasing from 20% to 30%) cause events to feel less remote than downward changes (e.g., decreasing from 40% to 30%), and subsequently change people's behavior regarding those events despite the revised event-probabilities being the same. Our research sheds light on how revising the probabilities for future events changes how people manage those uncertain events. (PsycINFO Database Record PMID:27281350
Estimating transition probabilities in unmarked populations --entropy revisited
Cooch, E.G.; Link, W.A.
1999-01-01
The probability of surviving and moving between 'states' is of great interest to biologists. Robust estimation of these transitions using multiple observations of individually identifiable marked individuals has received considerable attention in recent years. However, in some situations, individuals are not identifiable (or have a very low recapture rate), although all individuals in a sample can be assigned to a particular state (e.g. breeding or non-breeding) without error. In such cases, only aggregate data (number of individuals in a given state at each occasion) are available. If the underlying matrix of transition probabilities does not vary through time and aggregate data are available for several time periods, then it is possible to estimate these parameters using least-squares methods. Even when such data are available, this assumption of stationarity will usually be deemed overly restrictive and, frequently, data will only be available for two time periods. In these cases, the problem reduces to estimating the most likely matrix (or matrices) leading to the observed frequency distribution of individuals in each state. An entropy maximization approach has been previously suggested. In this paper, we show that the entropy approach rests on a particular limiting assumption, and does not provide estimates of latent population parameters (the transition probabilities), but rather predictions of realized rates.
Estimating the exceedance probability of rain rate by logistic regression
NASA Technical Reports Server (NTRS)
Chiu, Long S.; Kedem, Benjamin
1990-01-01
Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.
Estimating probable flaw distributions in PWR steam generator tubes
Gorman, J.A.; Turner, A.P.L.
1997-02-01
This paper describes methods for estimating the number and size distributions of flaws of various types in PWR steam generator tubes. These estimates are needed when calculating the probable primary to secondary leakage through steam generator tubes under postulated accidents such as severe core accidents and steam line breaks. The paper describes methods for two types of predictions: (1) the numbers of tubes with detectable flaws of various types as a function of time, and (2) the distributions in size of these flaws. Results are provided for hypothetical severely affected, moderately affected and lightly affected units. Discussion is provided regarding uncertainties and assumptions in the data and analyses.
New method for estimating low-earth-orbit collision probabilities
NASA Technical Reports Server (NTRS)
Vedder, John D.; Tabor, Jill L.
1991-01-01
An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.
Probability Density and CFAR Threshold Estimation for Hyperspectral Imaging
Clark, G A
2004-09-21
The work reported here shows the proof of principle (using a small data set) for a suite of algorithms designed to estimate the probability density function of hyperspectral background data and compute the appropriate Constant False Alarm Rate (CFAR) matched filter decision threshold for a chemical plume detector. Future work will provide a thorough demonstration of the algorithms and their performance with a large data set. The LASI (Large Aperture Search Initiative) Project involves instrumentation and image processing for hyperspectral images of chemical plumes in the atmosphere. The work reported here involves research and development on algorithms for reducing the false alarm rate in chemical plume detection and identification algorithms operating on hyperspectral image cubes. The chemical plume detection algorithms to date have used matched filters designed using generalized maximum likelihood ratio hypothesis testing algorithms [1, 2, 5, 6, 7, 12, 10, 11, 13]. One of the key challenges in hyperspectral imaging research is the high false alarm rate that often results from the plume detector [1, 2]. The overall goal of this work is to extend the classical matched filter detector to apply Constant False Alarm Rate (CFAR) methods to reduce the false alarm rate, or Probability of False Alarm P{sub FA} of the matched filter [4, 8, 9, 12]. A detector designer is interested in minimizing the probability of false alarm while simultaneously maximizing the probability of detection P{sub D}. This is summarized by the Receiver Operating Characteristic Curve (ROC) [10, 11], which is actually a family of curves depicting P{sub D} vs. P{sub FA}parameterized by varying levels of signal to noise (or clutter) ratio (SNR or SCR). Often, it is advantageous to be able to specify a desired P{sub FA} and develop a ROC curve (P{sub D} vs. decision threshold r{sub 0}) for that case. That is the purpose of this work. Specifically, this work develops a set of algorithms and MATLAB
Risk Preferences, Probability Weighting, and Strategy Tradeoffs in Wildfire Management.
Hand, Michael S; Wibbenmeyer, Matthew J; Calkin, David E; Thompson, Matthew P
2015-10-01
Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery-choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation-related fatalities. Respondents choose one of two strategies, each of which includes "good" (low cost/low damage) and "bad" (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting.
Risk Preferences, Probability Weighting, and Strategy Tradeoffs in Wildfire Management.
Hand, Michael S; Wibbenmeyer, Matthew J; Calkin, David E; Thompson, Matthew P
2015-10-01
Wildfires present a complex applied risk management environment, but relatively little attention has been paid to behavioral and cognitive responses to risk among public agency wildfire managers. This study investigates responses to risk, including probability weighting and risk aversion, in a wildfire management context using a survey-based experiment administered to federal wildfire managers. Respondents were presented with a multiattribute lottery-choice experiment where each lottery is defined by three outcome attributes: expenditures for fire suppression, damage to private property, and exposure of firefighters to the risk of aviation-related fatalities. Respondents choose one of two strategies, each of which includes "good" (low cost/low damage) and "bad" (high cost/high damage) outcomes that occur with varying probabilities. The choice task also incorporates an information framing experiment to test whether information about fatality risk to firefighters alters managers' responses to risk. Results suggest that managers exhibit risk aversion and nonlinear probability weighting, which can result in choices that do not minimize expected expenditures, property damage, or firefighter exposure. Information framing tends to result in choices that reduce the risk of aviation fatalities, but exacerbates nonlinear probability weighting. PMID:26269258
Estimation of the probability of success in petroleum exploration
Davis, J.C.
1977-01-01
A probabilistic model for oil exploration can be developed by assessing the conditional relationship between perceived geologic variables and the subsequent discovery of petroleum. Such a model includes two probabilistic components, the first reflecting the association between a geologic condition (structural closure, for example) and the occurrence of oil, and the second reflecting the uncertainty associated with the estimation of geologic variables in areas of limited control. Estimates of the conditional relationship between geologic variables and subsequent production can be found by analyzing the exploration history of a "training area" judged to be geologically similar to the exploration area. The geologic variables are assessed over the training area using an historical subset of the available data, whose density corresponds to the present control density in the exploration area. The success or failure of wells drilled in the training area subsequent to the time corresponding to the historical subset provides empirical estimates of the probability of success conditional upon geology. Uncertainty in perception of geological conditions may be estimated from the distribution of errors made in geologic assessment using the historical subset of control wells. These errors may be expressed as a linear function of distance from available control. Alternatively, the uncertainty may be found by calculating the semivariogram of the geologic variables used in the analysis: the two procedures will yield approximately equivalent results. The empirical probability functions may then be transferred to the exploration area and used to estimate the likelihood of success of specific exploration plays. These estimates will reflect both the conditional relationship between the geological variables used to guide exploration and the uncertainty resulting from lack of control. The technique is illustrated with case histories from the mid-Continent area of the U.S.A. ?? 1977 Plenum
Probabilities and statistics for backscatter estimates obtained by a scatterometer
NASA Technical Reports Server (NTRS)
Pierson, Willard J., Jr.
1989-01-01
Methods for the recovery of winds near the surface of the ocean from measurements of the normalized radar backscattering cross section must recognize and make use of the statistics (i.e., the sampling variability) of the backscatter measurements. Radar backscatter values from a scatterometer are random variables with expected values given by a model. A model relates backscatter to properties of the waves on the ocean, which are in turn generated by the winds in the atmospheric marine boundary layer. The effective wind speed and direction at a known height for a neutrally stratified atmosphere are the values to be recovered from the model. The probability density function for the backscatter values is a normal probability distribution with the notable feature that the variance is a known function of the expected value. The sources of signal variability, the effects of this variability on the wind speed estimation, and criteria for the acceptance or rejection of models are discussed. A modified maximum likelihood method for estimating wind vectors is described. Ways to make corrections for the kinds of errors found for the Seasat SASS model function are described, and applications to a new scatterometer are given.
Accurate photometric redshift probability density estimation - method comparison and application
NASA Astrophysics Data System (ADS)
Rau, Markus Michael; Seitz, Stella; Brimioulle, Fabrice; Frank, Eibe; Friedrich, Oliver; Gruen, Daniel; Hoyle, Ben
2015-10-01
We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples. As a use case we apply our method to CFHTLS galaxies. The ordinal classification algorithm treats distinct redshift bins as ordered values, which improves the quality of photometric redshift PDFs, compared with non-ordinal classification architectures. We also propose a new single value point estimate of the galaxy redshift, which can be used to estimate the full redshift PDF of a galaxy sample. This method is competitive in terms of accuracy with contemporary algorithms, which stack the full redshift PDFs of all galaxies in the sample, but requires orders of magnitude less storage space. The methods described in this paper greatly improve the log-likelihood of individual object redshift PDFs, when compared with a popular neural network code (ANNZ). In our use case, this improvement reaches 50 per cent for high-redshift objects (z ≥ 0.75). We show that using these more accurate photometric redshift PDFs will lead to a reduction in the systematic biases by up to a factor of 4, when compared with less accurate PDFs obtained from commonly used methods. The cosmological analyses we examine and find improvement upon are the following: gravitational lensing cluster mass estimates, modelling of angular correlation functions and modelling of cosmic shear correlation functions.
Van Houtven, George; Johnson, F Reed; Kilambi, Vikram; Hauber, A Brett
2011-01-01
This study applies conjoint analysis to estimate health-related benefit-risk tradeoffs in a non-expected-utility framework. We demonstrate how this method can be used to test for and estimate nonlinear weighting of adverse-event probabilities and we explore the implications of nonlinear weighting on maximum acceptable risk (MAR) measures of risk tolerance. We obtained preference data from 570 Crohn's disease patients using a web-enabled conjoint survey. Respondents were presented with choice tasks involving treatment options that involve different efficacy benefits and different mortality risks for 3 possible side effects. Using conditional logit maximum likelihood estimation, we estimate preference parameters using 3 models that allow for nonlinear preference weighting of risks--a categorical model, a simple-weighting model, and a rank dependent utility (RDU) model. For the second 2 models we specify and jointly estimate 1- and 2-parameter probability weighting functions. Although the 2-parameter functions are more flexible, estimation of the 1-parameter functions generally performed better. Despite well-known conceptual limitations, the simple-weighting model allows us to estimate weighting function parameters that vary across 3 risk types, and we find some evidence of statistically significant differences across risks. The parameter estimates from RDU model with the single-parameter weighting function provide the most robust estimates of MAR. For an improvement in Crohn's symptom severity from moderate and mild, we estimate maximum 10-year mortality risk tolerances ranging from 2.6% to 7.1%. Our results provide further the evidence that quantitative benefit-risk analysis used to evaluate medical interventions should account explicitly for the nonlinear probability weighting of preferences.
Estimates of radiogenic cancer risks
Puskin, J.S.; Nelson, C.B.
1995-07-01
A methodology recently developed by the U.S. EPA for estimating the carcingenic risks from ionizing radiation is described. For most cancer sites, the risk model is one in which age-specific, relative risk coefficients are obtained by taking a geometric mean of the coefficients derived from the atomic bomb survivor data using two different methods for transporting risks from the Japanese to the U.S. population. The risk models are applied to estimate organ-specific risks per unit dose for a stationary population with mortality rates governed by 1980 U.S. vital statistics. With the exception of breast cancer, low-LET radiogenic cancer risk estimates are reduced by a factor of 2 at low doses and dose rates compared to acute high dose exposure conditions. For low dose (or dose rate) conditions, the risk of inducing a premature cancer death from uniform, whole body, low-LET irradiation is calculated to be 5.1 x 10{sup -2} Gy{sup -1}. Neglecting nonfatal skin cancers, the corresponding incidence risk is 7.6 x 10{sup -2} Gy{sup -1}. High-LET (alpha particle) risks are presumed to increase linearly with dose and to be independent of dose rate. High-LET risks are estimated to be 20 times the low-LET risks estimated under low dose rate conditions, except for leukemia and breast cancer where RBEs of 1 and 10 are adopted, respectively. 29 refs., 3 tabs.
Site Specific Probable Maximum Precipitation Estimates and Professional Judgement
NASA Astrophysics Data System (ADS)
Hayes, B. D.; Kao, S. C.; Kanney, J. F.; Quinlan, K. R.; DeNeale, S. T.
2015-12-01
State and federal regulatory authorities currently rely upon the US National Weather Service Hydrometeorological Reports (HMRs) to determine probable maximum precipitation (PMP) estimates (i.e., rainfall depths and durations) for estimating flooding hazards for relatively broad regions in the US. PMP estimates for the contributing watersheds upstream of vulnerable facilities are used to estimate riverine flooding hazards while site-specific estimates for small water sheds are appropriate for individual facilities such as nuclear power plants. The HMRs are often criticized due to their limitations on basin size, questionable applicability in regions affected by orographic effects, their lack of consist methods, and generally by their age. HMR-51 for generalized PMP estimates for the United States east of the 105th meridian, was published in 1978 and is sometimes perceived as overly conservative. The US Nuclear Regulatory Commission (NRC), is currently reviewing several flood hazard evaluation reports that rely on site specific PMP estimates that have been commercially developed. As such, NRC has recently investigated key areas of expert judgement via a generic audit and one in-depth site specific review as they relate to identifying and quantifying actual and potential storm moisture sources, determining storm transposition limits, and adjusting available moisture during storm transposition. Though much of the approach reviewed was considered a logical extension of HMRs, two key points of expert judgement stood out for further in-depth review. The first relates primarily to small storms and the use of a heuristic for storm representative dew point adjustment developed for the Electric Power Research Institute by North American Weather Consultants in 1993 in order to harmonize historic storms for which only 12 hour dew point data was available with more recent storms in a single database. The second issue relates to the use of climatological averages for spatially
Gray, David R
2010-12-01
As global trade increases so too does the probability of introduction of alien species to new locations. Estimating the probability of an alien species introduction and establishment following introduction is a necessary step in risk estimation (probability of an event times the consequences, in the currency of choice, of the event should it occur); risk estimation is a valuable tool for reducing the risk of biological invasion with limited resources. The Asian gypsy moth, Lymantria dispar (L.), is a pest species whose consequence of introduction and establishment in North America and New Zealand warrants over US$2 million per year in surveillance expenditure. This work describes the development of a two-dimensional phenology model (GLS-2d) that simulates insect development from source to destination and estimates: (1) the probability of introduction from the proportion of the source population that would achieve the next developmental stage at the destination and (2) the probability of establishment from the proportion of the introduced population that survives until a stable life cycle is reached at the destination. The effect of shipping schedule on the probabilities of introduction and establishment was examined by varying the departure date from 1 January to 25 December by weekly increments. The effect of port efficiency was examined by varying the length of time that invasion vectors (shipping containers and ship) were available for infection. The application of GLS-2d is demonstrated using three common marine trade routes (to Auckland, New Zealand, from Kobe, Japan, and to Vancouver, Canada, from Kobe and from Vladivostok, Russia).
Structural Reliability Using Probability Density Estimation Methods Within NESSUS
NASA Technical Reports Server (NTRS)
Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric
2003-01-01
A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been
Impaired probability estimation and decision-making in pathological gambling poker players.
Linnet, Jakob; Frøslev, Mette; Ramsgaard, Stine; Gebauer, Line; Mouridsen, Kim; Wohlert, Victoria
2012-03-01
Poker has gained tremendous popularity in recent years, increasing the risk for some individuals to develop pathological gambling. Here, we investigated cognitive biases in a computerized two-player poker task against a fictive opponent, among 12 pathological gambling poker players (PGP), 10 experienced poker players (ExP), and 11 inexperienced poker players (InP). Players were compared on probability estimation and decision-making with the hypothesis that ExP would have significantly lower cognitive biases than PGP and InP, and that the groups could be differentiated based on their cognitive bias styles. The results showed that ExP had a significantly lower average error margin in probability estimation than PGP and InP, and that PGP played hands with lower winning probability than ExP. Binomial logistic regression showed perfect differentiation (100%) between ExP and PGP, and 90.5% classification accuracy between ExP and InP. Multinomial logistic regression showed an overall classification accuracy of 23 out of 33 (69.7%) between the three groups. The classification accuracy of ExP was higher than that of PGP and InP due to the similarities in probability estimation and decision-making between PGP and InP. These impairments in probability estimation and decision-making of PGP may have implications for assessment and treatment of cognitive biases in pathological gambling poker players.
Lermer, Eva; Streicher, Bernhard; Sachs, Rainer; Raue, Martina; Frey, Dieter
2016-03-01
Recent findings on construal level theory (CLT) suggest that abstract thinking leads to a lower estimated probability of an event occurring compared to concrete thinking. We applied this idea to the risk context and explored the influence of construal level (CL) on the overestimation of small and underestimation of large probabilities for risk estimates concerning a vague target person (Study 1 and Study 3) and personal risk estimates (Study 2). We were specifically interested in whether the often-found overestimation of small probabilities could be reduced with abstract thinking, and the often-found underestimation of large probabilities was reduced with concrete thinking. The results showed that CL influenced risk estimates. In particular, a concrete mindset led to higher risk estimates compared to an abstract mindset for several adverse events, including events with small and large probabilities. This suggests that CL manipulation can indeed be used for improving the accuracy of lay people's estimates of small and large probabilities. Moreover, the results suggest that professional risk managers' risk estimates of common events (thus with a relatively high probability) could be improved by adopting a concrete mindset. However, the abstract manipulation did not lead managers to estimate extremely unlikely events more accurately. Potential reasons for different CL manipulation effects on risk estimates' accuracy between lay people and risk managers are discussed.
Havelaar, A H; Swart, A N
2014-10-01
Dose-response models in microbial risk assessment consider two steps in the process ultimately leading to illness: from exposure to (asymptomatic) infection, and from infection to (symptomatic) illness. Most data and theoretical approaches are available for the exposure-infection step; the infection-illness step has received less attention. Furthermore, current microbial risk assessment models do not account for acquired immunity. These limitations may lead to biased risk estimates. We consider effects of both dose dependency of the conditional probability of illness given infection, and acquired immunity to risk estimates, and demonstrate their effects in a case study on exposure to Campylobacter jejuni. To account for acquired immunity in risk estimates, an inflation factor is proposed. The inflation factor depends on the relative rates of loss of protection over exposure. The conditional probability of illness given infection is based on a previously published model, accounting for the within-host dynamics of illness. We find that at low (average) doses, the infection-illness model has the greatest impact on risk estimates, whereas at higher (average) doses and/or increased exposure frequencies, the acquired immunity model has the greatest impact. The proposed models are strongly nonlinear, and reducing exposure is not expected to lead to a proportional decrease in risk and, under certain conditions, may even lead to an increase in risk. The impact of different dose-response models on risk estimates is particularly pronounced when introducing heterogeneity in the population exposure distribution.
Exaggerated Risk: Prospect Theory and Probability Weighting in Risky Choice
ERIC Educational Resources Information Center
Kusev, Petko; van Schaik, Paul; Ayton, Peter; Dent, John; Chater, Nick
2009-01-01
In 5 experiments, we studied precautionary decisions in which participants decided whether or not to buy insurance with specified cost against an undesirable event with specified probability and cost. We compared the risks taken for precautionary decisions with those taken for equivalent monetary gambles. Fitting these data to Tversky and…
Evaluating methods for estimating existential risks.
Tonn, Bruce; Stiefel, Dorian
2013-10-01
Researchers and commissions contend that the risk of human extinction is high, but none of these estimates have been based upon a rigorous methodology suitable for estimating existential risks. This article evaluates several methods that could be used to estimate the probability of human extinction. Traditional methods evaluated include: simple elicitation; whole evidence Bayesian; evidential reasoning using imprecise probabilities; and Bayesian networks. Three innovative methods are also considered: influence modeling based on environmental scans; simple elicitation using extinction scenarios as anchors; and computationally intensive possible-worlds modeling. Evaluation criteria include: level of effort required by the probability assessors; level of effort needed to implement the method; ability of each method to model the human extinction event; ability to incorporate scientific estimates of contributory events; transparency of the inputs and outputs; acceptability to the academic community (e.g., with respect to intellectual soundness, familiarity, verisimilitude); credibility and utility of the outputs of the method to the policy community; difficulty of communicating the method's processes and outputs to nonexperts; and accuracy in other contexts. The article concludes by recommending that researchers assess the risks of human extinction by combining these methods. PMID:23551083
A Quantitative Method for Estimating Probable Public Costs of Hurricanes.
BOSWELL; DEYLE; SMITH; BAKER
1999-04-01
/ A method is presented for estimating probable public costs resulting from damage caused by hurricanes, measured as local government expenditures approved for reimbursement under the Stafford Act Section 406 Public Assistance Program. The method employs a multivariate model developed through multiple regression analysis of an array of independent variables that measure meteorological, socioeconomic, and physical conditions related to the landfall of hurricanes within a local government jurisdiction. From the regression analysis we chose a log-log (base 10) model that explains 74% of the variance in the expenditure data using population and wind speed as predictors. We illustrate application of the method for a local jurisdiction-Lee County, Florida, USA. The results show that potential public costs range from $4.7 million for a category 1 hurricane with winds of 137 kilometers per hour (85 miles per hour) to $130 million for a category 5 hurricane with winds of 265 kilometers per hour (165 miles per hour). Based on these figures, we estimate expected annual public costs of $2.3 million. These cost estimates: (1) provide useful guidance for anticipating the magnitude of the federal, state, and local expenditures that would be required for the array of possible hurricanes that could affect that jurisdiction; (2) allow policy makers to assess the implications of alternative federal and state policies for providing public assistance to jurisdictions that experience hurricane damage; and (3) provide information needed to develop a contingency fund or other financial mechanism for assuring that the community has sufficient funds available to meet its obligations. KEY WORDS: Hurricane; Public costs; Local government; Disaster recovery; Disaster response; Florida; Stafford Act
[Medical insurance estimation of risks].
Dunér, H
1975-11-01
The purpose of insurance medicine is to make a prognostic estimate of medical risk-factors in persons who apply for life, health, or accident insurance. Established risk-groups with a calculated average mortality and morbidity form the basis for premium rates and insurance terms. In most cases the applicant is accepted for insurance after a self-assessment of his health. Only around one per cent of the applications are refused, but there are cases in which the premium is raised, temporarily or permanently. It is often a matter of rough estimate, since the knowlege of the long-term prognosis for many diseases is incomplete. The insurance companies' rules for estimate of risk are revised at intervals of three or four years. The estimate of risk as regards life insurance has been gradually liberalised, while the medical conditions for health insurance have become stricter owing to an increase in the claims rate.
Reinforcing flood-risk estimation.
Reed, Duncan W
2002-07-15
Flood-frequency estimation is inherently uncertain. The practitioner applies a combination of gauged data, scientific method and hydrological judgement to derive a flood-frequency curve for a particular site. The resulting estimate can be thought fully satisfactory only if it is broadly consistent with all that is reliably known about the flood-frequency behaviour of the river. The paper takes as its main theme the search for information to strengthen a flood-risk estimate made from peak flows alone. Extra information comes in many forms, including documentary and monumental records of historical floods, and palaeological markers. Meteorological information is also useful, although rainfall rarity is difficult to assess objectively and can be a notoriously unreliable indicator of flood rarity. On highly permeable catchments, groundwater levels present additional data. Other types of information are relevant to judging hydrological similarity when the flood-frequency estimate derives from data pooled across several catchments. After highlighting information sources, the paper explores a second theme: that of consistency in flood-risk estimates. Following publication of the Flood estimation handbook, studies of flood risk are now using digital catchment data. Automated calculation methods allow estimates by standard methods to be mapped basin-wide, revealing anomalies at special sites such as river confluences. Such mapping presents collateral information of a new character. Can this be used to achieve flood-risk estimates that are coherent throughout a river basin? PMID:12804255
Reinforcing flood-risk estimation.
Reed, Duncan W
2002-07-15
Flood-frequency estimation is inherently uncertain. The practitioner applies a combination of gauged data, scientific method and hydrological judgement to derive a flood-frequency curve for a particular site. The resulting estimate can be thought fully satisfactory only if it is broadly consistent with all that is reliably known about the flood-frequency behaviour of the river. The paper takes as its main theme the search for information to strengthen a flood-risk estimate made from peak flows alone. Extra information comes in many forms, including documentary and monumental records of historical floods, and palaeological markers. Meteorological information is also useful, although rainfall rarity is difficult to assess objectively and can be a notoriously unreliable indicator of flood rarity. On highly permeable catchments, groundwater levels present additional data. Other types of information are relevant to judging hydrological similarity when the flood-frequency estimate derives from data pooled across several catchments. After highlighting information sources, the paper explores a second theme: that of consistency in flood-risk estimates. Following publication of the Flood estimation handbook, studies of flood risk are now using digital catchment data. Automated calculation methods allow estimates by standard methods to be mapped basin-wide, revealing anomalies at special sites such as river confluences. Such mapping presents collateral information of a new character. Can this be used to achieve flood-risk estimates that are coherent throughout a river basin?
Semi-supervised dimensionality reduction using estimated class membership probabilities
NASA Astrophysics Data System (ADS)
Li, Wei; Ruan, Qiuqi; Wan, Jun
2012-10-01
In solving pattern-recognition tasks with partially labeled training data, the semi-supervised dimensionality reduction method, which considers both labeled and unlabeled data, is preferable for improving the classification and generalization capability of the testing data. Among such techniques, graph-based semi-supervised learning methods have attracted a lot of attention due to their appealing properties in discovering discriminative structure and geometric structure of data points. Although they have achieved remarkable success, they cannot promise good performance when the size of the labeled data set is small, as a result of inaccurate class matrix variance approximated by insufficient labeled training data. In this paper, we tackle this problem by combining class membership probabilities estimated from unlabeled data and ground-truth class information associated with labeled data to more precisely characterize the class distribution. Therefore, it is expected to enhance performance in classification tasks. We refer to this approach as probabilistic semi-supervised discriminant analysis (PSDA). The proposed PSDA is applied to face and facial expression recognition tasks and is evaluated using the ORL, Extended Yale B, and CMU PIE face databases and the Cohn-Kanade facial expression database. The promising experimental results demonstrate the effectiveness of our proposed method.
Akanda, Md Abdus Salam; Alpizar-Jara, Russell
2014-01-01
Modeling individual heterogeneity in capture probabilities has been one of the most challenging tasks in capture–recapture studies. Heterogeneity in capture probabilities can be modeled as a function of individual covariates, but correlation structure among capture occasions should be taking into account. A proposed generalized estimating equations (GEE) and generalized linear mixed modeling (GLMM) approaches can be used to estimate capture probabilities and population size for capture–recapture closed population models. An example is used for an illustrative application and for comparison with currently used methodology. A simulation study is also conducted to show the performance of the estimation procedures. Our simulation results show that the proposed quasi-likelihood based on GEE approach provides lower SE than partial likelihood based on either generalized linear models (GLM) or GLMM approaches for estimating population size in a closed capture–recapture experiment. Estimator performance is good if a large proportion of individuals are captured. For cases where only a small proportion of individuals are captured, the estimates become unstable, but the GEE approach outperforms the other methods. PMID:24772290
Conditional Probabilities for Large Events Estimated by Small Earthquake Rate
NASA Astrophysics Data System (ADS)
Wu, Yi-Hsuan; Chen, Chien-Chih; Li, Hsien-Chi
2016-01-01
We examined forecasting quiescence and activation models to obtain the conditional probability that a large earthquake will occur in a specific time period on different scales in Taiwan. The basic idea of the quiescence and activation models is to use earthquakes that have magnitudes larger than the completeness magnitude to compute the expected properties of large earthquakes. We calculated the probability time series for the whole Taiwan region and for three subareas of Taiwan—the western, eastern, and northeastern Taiwan regions—using 40 years of data from the Central Weather Bureau catalog. In the probability time series for the eastern and northeastern Taiwan regions, a high probability value is usually yielded in cluster events such as events with foreshocks and events that all occur in a short time period. In addition to the time series, we produced probability maps by calculating the conditional probability for every grid point at the time just before a large earthquake. The probability maps show that high probability values are yielded around the epicenter before a large earthquake. The receiver operating characteristic (ROC) curves of the probability maps demonstrate that the probability maps are not random forecasts, but also suggest that lowering the magnitude of a forecasted large earthquake may not improve the forecast method itself. From both the probability time series and probability maps, it can be observed that the probability obtained from the quiescence model increases before a large earthquake and the probability obtained from the activation model increases as the large earthquakes occur. The results lead us to conclude that the quiescence model has better forecast potential than the activation model.
Estimating Terrorist Risk with Possibility Theory
J.L. Darby
2004-11-30
This report summarizes techniques that use possibility theory to estimate the risk of terrorist acts. These techniques were developed under the sponsorship of the Department of Homeland Security (DHS) as part of the National Infrastructure Simulation Analysis Center (NISAC) project. The techniques have been used to estimate the risk of various terrorist scenarios to support NISAC analyses during 2004. The techniques are based on the Logic Evolved Decision (LED) methodology developed over the past few years by Terry Bott and Steve Eisenhawer at LANL. [LED] The LED methodology involves the use of fuzzy sets, possibility theory, and approximate reasoning. LED captures the uncertainty due to vagueness and imprecision that is inherent in the fidelity of the information available for terrorist acts; probability theory cannot capture these uncertainties. This report does not address the philosophy supporting the development of nonprobabilistic approaches, and it does not discuss possibility theory in detail. The references provide a detailed discussion of these subjects. [Shafer] [Klir and Yuan] [Dubois and Prade] Suffice to say that these approaches were developed to address types of uncertainty that cannot be addressed by a probability measure. An earlier report discussed in detail the problems with using a probability measure to evaluate terrorist risk. [Darby Methodology]. Two related techniques are discussed in this report: (1) a numerical technique, and (2) a linguistic technique. The numerical technique uses traditional possibility theory applied to crisp sets, while the linguistic technique applies possibility theory to fuzzy sets. Both of these techniques as applied to terrorist risk for NISAC applications are implemented in software called PossibleRisk. The techniques implemented in PossibleRisk were developed specifically for use in estimating terrorist risk for the NISAC program. The LEDTools code can be used to perform the same linguistic evaluation as
Estimating the Probability of Elevated Nitrate Concentrations in Ground Water in Washington State
Frans, Lonna M.
2008-01-01
Logistic regression was used to relate anthropogenic (manmade) and natural variables to the occurrence of elevated nitrate concentrations in ground water in Washington State. Variables that were analyzed included well depth, ground-water recharge rate, precipitation, population density, fertilizer application amounts, soil characteristics, hydrogeomorphic regions, and land-use types. Two models were developed: one with and one without the hydrogeomorphic regions variable. The variables in both models that best explained the occurrence of elevated nitrate concentrations (defined as concentrations of nitrite plus nitrate as nitrogen greater than 2 milligrams per liter) were the percentage of agricultural land use in a 4-kilometer radius of a well, population density, precipitation, soil drainage class, and well depth. Based on the relations between these variables and measured nitrate concentrations, logistic regression models were developed to estimate the probability of nitrate concentrations in ground water exceeding 2 milligrams per liter. Maps of Washington State were produced that illustrate these estimated probabilities for wells drilled to 145 feet below land surface (median well depth) and the estimated depth to which wells would need to be drilled to have a 90-percent probability of drawing water with a nitrate concentration less than 2 milligrams per liter. Maps showing the estimated probability of elevated nitrate concentrations indicated that the agricultural regions are most at risk followed by urban areas. The estimated depths to which wells would need to be drilled to have a 90-percent probability of obtaining water with nitrate concentrations less than 2 milligrams per liter exceeded 1,000 feet in the agricultural regions; whereas, wells in urban areas generally would need to be drilled to depths in excess of 400 feet.
Estimating earthquake-induced failure probability and downtime of critical facilities.
Porter, Keith; Ramer, Kyle
2012-01-01
Fault trees have long been used to estimate failure risk in earthquakes, especially for nuclear power plants (NPPs). One interesting application is that one can assess and manage the probability that two facilities - a primary and backup - would be simultaneously rendered inoperative in a single earthquake. Another is that one can calculate the probabilistic time required to restore a facility to functionality, and the probability that, during any given planning period, the facility would be rendered inoperative for any specified duration. A large new peer-reviewed library of component damageability and repair-time data for the first time enables fault trees to be used to calculate the seismic risk of operational failure and downtime for a wide variety of buildings other than NPPs. With the new library, seismic risk of both the failure probability and probabilistic downtime can be assessed and managed, considering the facility's unique combination of structural and non-structural components, their seismic installation conditions, and the other systems on which the facility relies. An example is offered of real computer data centres operated by a California utility. The fault trees were created and tested in collaboration with utility operators, and the failure probability and downtime results validated in several ways. PMID:22576139
Eom, Bang Wool; Joo, Jungnam; Park, Boram; Yoon, Hong Man; Ryu, Keun Won; Kim, Soo Jin
2015-01-01
Purpose Intraabdominal abscess is one of the most common reasons for re-hospitalization after gastrectomy. This study aimed to develop a model for estimating the probability of intraabdominal abscesses that can be used during the postoperative period. Materials and Methods We retrospectively reviewed the clinicopathological data of 1,564 patients who underwent gastrectomy for gastric cancer between 2010 and 2012. Twenty-six related markers were analyzed, and multivariate logistic regression analysis was used to develop the probability estimation model for intraabdominal abscess. Internal validation using a bootstrap approach was employed to correct for bias, and the model was then validated using an independent dataset comprising of patients who underwent gastrectomy between January 2008 and March 2010. Discrimination and calibration abilities were checked in both datasets. Results The incidence of intraabdominal abscess in the development set was 7.80% (122/1,564). The surgical approach, operating time, pathologic N classification, body temperature, white blood cell count, C-reactive protein level, glucose level, and change in the hemoglobin level were significant predictors of intraabdominal abscess in the multivariate analysis. The probability estimation model that was developed on the basis of these results showed good discrimination and calibration abilities (concordance index=0.828, Hosmer-Lemeshow chi-statistic P=0.274). Finally, we combined both datasets to produce a nomogram that estimates the probability of intraabdominal abscess. Conclusions This nomogram can be useful for identifying patients at a high risk of intraabdominal abscess. Patients at a high risk may benefit from further evaluation or treatment before discharge. PMID:26816657
Brus, D J; de Gruijter, J J
2003-04-01
In estimating spatial means of environmental variables of a region from data collected by convenience or purposive sampling, validity of the results can be ensured by collecting additional data through probability sampling. The precision of the pi estimator that uses the probability sample can be increased by interpolating the values at the nonprobability sample points to the probability sample points, and using these interpolated values as an auxiliary variable in the difference or regression estimator. These estimators are (approximately) unbiased, even when the nonprobability sample is severely biased such as in preferential samples. The gain in precision compared to the pi estimator in combination with Simple Random Sampling is controlled by the correlation between the target variable and interpolated variable. This correlation is determined by the size (density) and spatial coverage of the nonprobability sample, and the spatial continuity of the target variable. In a case study the average ratio of the variances of the simple regression estimator and pi estimator was 0.68 for preferential samples of size 150 with moderate spatial clustering, and 0.80 for preferential samples of similar size with strong spatial clustering. In the latter case the simple regression estimator was substantially more precise than the simple difference estimator.
NASA Astrophysics Data System (ADS)
Baer, P.; Mastrandrea, M.
2006-12-01
Simple probabilistic models which attempt to estimate likely transient temperature change from specified CO2 emissions scenarios must make assumptions about at least six uncertain aspects of the causal chain between emissions and temperature: current radiative forcing (including but not limited to aerosols), current land use emissions, carbon sinks, future non-CO2 forcing, ocean heat uptake, and climate sensitivity. Of these, multiple PDFs (probability density functions) have been published for the climate sensitivity, a couple for current forcing and ocean heat uptake, one for future non-CO2 forcing, and none for current land use emissions or carbon cycle uncertainty (which are interdependent). Different assumptions about these parameters, as well as different model structures, will lead to different estimates of likely temperature increase from the same emissions pathway. Thus policymakers will be faced with a range of temperature probability distributions for the same emissions scenarios, each described by a central tendency and spread. Because our conventional understanding of uncertainty and probability requires that a probabilistically defined variable of interest have only a single mean (or median, or modal) value and a well-defined spread, this "multidimensional" uncertainty defies straightforward utilization in policymaking. We suggest that there are no simple solutions to the questions raised. Crucially, we must dispel the notion that there is a "true" probability probabilities of this type are necessarily subjective, and reasonable people may disagree. Indeed, we suggest that what is at stake is precisely the question, what is it reasonable to believe, and to act as if we believe? As a preliminary suggestion, we demonstrate how the output of a simple probabilistic climate model might be evaluated regarding the reasonableness of the outputs it calculates with different input PDFs. We suggest further that where there is insufficient evidence to clearly
NASA Technical Reports Server (NTRS)
Havens, K. A.; Minster, T. C.; Thadani, S. G.
1976-01-01
The probability of error or, alternatively, the probability of correct classification (PCC) is an important criterion in analyzing the performance of a classifier. Labeled samples (those with ground truth) are usually employed to evaluate the performance of a classifier. Occasionally, the numbers of labeled samples are inadequate, or no labeled samples are available to evaluate a classifier's performance; for example, when crop signatures from one area from which ground truth is available are used to classify another area from which no ground truth is available. This paper reports the results of an experiment to estimate the probability of error using unlabeled test samples (i.e., without the aid of ground truth).
Compositional cokriging for mapping the probability risk of groundwater contamination by nitrates.
Pardo-Igúzquiza, Eulogio; Chica-Olmo, Mario; Luque-Espinar, Juan A; Rodríguez-Galiano, Víctor
2015-11-01
Contamination by nitrates is an important cause of groundwater pollution and represents a potential risk to human health. Management decisions must be made using probability maps that assess the nitrate concentration potential of exceeding regulatory thresholds. However these maps are obtained with only a small number of sparse monitoring locations where the nitrate concentrations have been measured. It is therefore of great interest to have an efficient methodology for obtaining those probability maps. In this paper, we make use of the fact that the discrete probability density function is a compositional variable. The spatial discrete probability density function is estimated by compositional cokriging. There are several advantages in using this approach: (i) problems of classical indicator cokriging, like estimates outside the interval (0,1) and order relations, are avoided; (ii) secondary variables (e.g. aquifer parameters) can be included in the estimation of the probability maps; (iii) uncertainty maps of the probability maps can be obtained; (iv) finally there are modelling advantages because the variograms and cross-variograms of real variables that do not have the restrictions of indicator variograms and indicator cross-variograms. The methodology was applied to the Vega de Granada aquifer in Southern Spain and the advantages of the compositional cokriging approach were demonstrated.
NASA Astrophysics Data System (ADS)
Fung, D. C. N.; Wang, J. P.; Chang, S. H.; Chang, S. C.
2014-12-01
Using a revised statistical model built on past seismic probability models, the probability of different magnitude earthquakes occurring within variable timespans can be estimated. The revised model is based on Poisson distribution and includes the use of best-estimate values of the probability distribution of different magnitude earthquakes recurring from a fault from literature sources. Our study aims to apply this model to the Taipei metropolitan area with a population of 7 million, which lies in the Taipei Basin and is bounded by two normal faults: the Sanchaio and Taipei faults. The Sanchaio fault is suggested to be responsible for previous large magnitude earthquakes, such as the 1694 magnitude 7 earthquake in northwestern Taipei (Cheng et. al., 2010). Based on a magnitude 7 earthquake return period of 543 years, the model predicts the occurrence of a magnitude 7 earthquake within 20 years at 1.81%, within 79 years at 6.77% and within 300 years at 21.22%. These estimates increase significantly when considering a magnitude 6 earthquake; the chance of one occurring within the next 20 years is estimated to be 3.61%, 79 years at 13.54% and 300 years at 42.45%. The 79 year period represents the average lifespan of the Taiwan population. In contrast, based on data from 2013, the probability of Taiwan residents experiencing heart disease or malignant neoplasm is 11.5% and 29%. The inference of this study is that the calculated risk that the Taipei population is at from a potentially damaging magnitude 6 or greater earthquake occurring within their lifetime is just as great as of suffering from a heart attack or other health ailments.
Betrie, Getnet D; Sadiq, Rehan; Nichol, Craig; Morin, Kevin A; Tesfamariam, Solomon
2016-01-15
Acid rock drainage (ARD) is a major environmental problem that poses significant environmental risks during and after mining activities. A new methodology for environmental risk assessment based on probability bounds and a geochemical speciation model (PHREEQC) is presented. The methodology provides conservative and non-conservative ways of estimating risk of heavy metals posed to selected endpoints probabilistically, while propagating data and parameter uncertainties throughout the risk assessment steps. The methodology is demonstrated at a minesite located in British Columbia, Canada. The result of the methodology for the case study minesite shows the fate-and-transport of heavy metals is well simulated in the mine environment. In addition, the results of risk characterization for the case study show that there is risk due to transport of heavy metals into the environment.
Estimating the Probability of Electrical Short Circuits from Tin Whiskers. Part 2
NASA Technical Reports Server (NTRS)
Courey, Karim J.; Asfour, Shihab S.; Onar, Arzu; Bayliss, Jon A.; Ludwig, Larry L.; Wright, Maria C.
2010-01-01
To comply with lead-free legislation, many manufacturers have converted from tin-lead to pure tin finishes of electronic components. However, pure tin finishes have a greater propensity to grow tin whiskers than tin-lead finishes. Since tin whiskers present an electrical short circuit hazard in electronic components, simulations have been developed to quantify the risk of said short circuits occurring. Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that had an unknown probability associated with it. Note however that due to contact resistance electrical shorts may not occur at lower voltage levels. In our first article we developed an empirical probability model for tin whisker shorting. In this paper, we develop a more comprehensive empirical model using a refined experiment with a larger sample size, in which we studied the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From the resulting data we estimated the probability distribution of an electrical short, as a function of voltage. In addition, the unexpected polycrystalline structure seen in the focused ion beam (FIB) cross section in the first experiment was confirmed in this experiment using transmission electron microscopy (TEM). The FIB was also used to cross section two card guides to facilitate the measurement of the grain size of each card guide's tin plating to determine its finish .
Estimating the Probability of Electrical Short Circuits from Tin Whiskers. Part 2
NASA Technical Reports Server (NTRS)
Courey, Karim J.; Asfour, Shihab S.; Onar, Arzu; Bayliss, Jon A.; Ludwig, Larry L.; Wright, Maria C.
2009-01-01
To comply with lead-free legislation, many manufacturers have converted from tin-lead to pure tin finishes of electronic components. However, pure tin finishes have a greater propensity to grow tin whiskers than tin-lead finishes. Since tin whiskers present an electrical short circuit hazard in electronic components, simulations have been developed to quantify the risk of said short circuits occurring. Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that had an unknown probability associated with it. Note however that due to contact resistance electrical shorts may not occur at lower voltage levels. In our first article we developed an empirical probability model for tin whisker shorting. In this paper, we develop a more comprehensive empirical model using a refined experiment with a larger sample size, in which we studied the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From the resulting data we estimated the probability distribution of an electrical short, as a function of voltage.
Development of partial failure analysis method in probability risk assessments
Ni, T.; Modarres, M.
1996-12-01
This paper presents a new approach to evaluate the partial failure effect on current Probability Risk Assessments (PRAs). An integrated methodology of the thermal-hydraulic analysis and fuzzy logic simulation using the Dynamic Master Logic Diagram (DMLD) was developed. The thermal-hydraulic analysis used in this approach is to identify partial operation effect of any PRA system function in a plant model. The DMLD is used to simulate the system performance of the partial failure effect and inspect all minimal cut sets of system functions. This methodology can be applied in the context of a full scope PRA to reduce core damage frequency. An example of this application of the approach is presented. The partial failure data used in the example is from a survey study of partial failure effects from the Nuclear Plant Reliability Data System (NPRDS).
Probability Distribution Extraction from TEC Estimates based on Kernel Density Estimation
NASA Astrophysics Data System (ADS)
Demir, Uygar; Toker, Cenk; Çenet, Duygu
2016-07-01
Statistical analysis of the ionosphere, specifically the Total Electron Content (TEC), may reveal important information about its temporal and spatial characteristics. One of the core metrics that express the statistical properties of a stochastic process is its Probability Density Function (pdf). Furthermore, statistical parameters such as mean, variance and kurtosis, which can be derived from the pdf, may provide information about the spatial uniformity or clustering of the electron content. For example, the variance differentiates between a quiet ionosphere and a disturbed one, whereas kurtosis differentiates between a geomagnetic storm and an earthquake. Therefore, valuable information about the state of the ionosphere (and the natural phenomena that cause the disturbance) can be obtained by looking at the statistical parameters. In the literature, there are publications which try to fit the histogram of TEC estimates to some well-known pdf.s such as Gaussian, Exponential, etc. However, constraining a histogram to fit to a function with a fixed shape will increase estimation error, and all the information extracted from such pdf will continue to contain this error. In such techniques, it is highly likely to observe some artificial characteristics in the estimated pdf which is not present in the original data. In the present study, we use the Kernel Density Estimation (KDE) technique to estimate the pdf of the TEC. KDE is a non-parametric approach which does not impose a specific form on the TEC. As a result, better pdf estimates that almost perfectly fit to the observed TEC values can be obtained as compared to the techniques mentioned above. KDE is particularly good at representing the tail probabilities, and outliers. We also calculate the mean, variance and kurtosis of the measured TEC values. The technique is applied to the ionosphere over Turkey where the TEC values are estimated from the GNSS measurement from the TNPGN-Active (Turkish National Permanent
Estimation of probability of failure for damage-tolerant aerospace structures
NASA Astrophysics Data System (ADS)
Halbert, Keith
The majority of aircraft structures are designed to be damage-tolerant such that safe operation can continue in the presence of minor damage. It is necessary to schedule inspections so that minor damage can be found and repaired. It is generally not possible to perform structural inspections prior to every flight. The scheduling is traditionally accomplished through a deterministic set of methods referred to as Damage Tolerance Analysis (DTA). DTA has proven to produce safe aircraft but does not provide estimates of the probability of failure of future flights or the probability of repair of future inspections. Without these estimates maintenance costs cannot be accurately predicted. Also, estimation of failure probabilities is now a regulatory requirement for some aircraft. The set of methods concerned with the probabilistic formulation of this problem are collectively referred to as Probabilistic Damage Tolerance Analysis (PDTA). The goal of PDTA is to control the failure probability while holding maintenance costs to a reasonable level. This work focuses specifically on PDTA for fatigue cracking of metallic aircraft structures. The growth of a crack (or cracks) must be modeled using all available data and engineering knowledge. The length of a crack can be assessed only indirectly through evidence such as non-destructive inspection results, failures or lack of failures, and the observed severity of usage of the structure. The current set of industry PDTA tools are lacking in several ways: they may in some cases yield poor estimates of failure probabilities, they cannot realistically represent the variety of possible failure and maintenance scenarios, and they do not allow for model updates which incorporate observed evidence. A PDTA modeling methodology must be flexible enough to estimate accurately the failure and repair probabilities under a variety of maintenance scenarios, and be capable of incorporating observed evidence as it becomes available. This
Estimating the probability of coexistence in cross-feeding communities.
Vessman, Björn; Gerlee, Philip; Lundh, Torbjörn
2016-11-01
The dynamics of many microbial ecosystems are driven by cross-feeding interactions, in which metabolites excreted by some species are metabolised further by others. The population dynamics of such ecosystems are governed by frequency-dependent selection, which allows for stable coexistence of two or more species. We have analysed a model of cross-feeding based on the replicator equation, with the aim of establishing criteria for coexistence in ecosystems containing three species, given the information of the three species' ability to coexist in their three separate pairs, i.e. the long term dynamics in the three two-species component systems. The triple-system is studied statistically and the probability of coexistence in the species triplet is computed for two models of species interactions. The interaction parameters are modelled either as stochastically independent or organised in a hierarchy where any derived metabolite carries less energy than previous nutrients in the metabolic chain. We differentiate between different modes of coexistence with respect to the pair-wise dynamics of the species, and find that the probability of coexistence is close to 12 for triplet systems with three pair-wise coexistent pairs and for the so-called intransitive systems. Systems with two and one pair-wise coexistent pairs are more likely to exist for random interaction parameters, but are on the other hand much less likely to exhibit triplet coexistence. Hence we conclude that certain species triplets are, from a statistical point of view, rare, but if allowed to interact are likely to coexist. This knowledge might be helpful when constructing synthetic microbial communities for industrial purposes. PMID:27484301
Estimating background and threshold nitrate concentrations using probability graphs
Panno, S.V.; Kelly, W.R.; Martinsek, A.T.; Hackley, Keith C.
2006-01-01
Because of the ubiquitous nature of anthropogenic nitrate (NO 3-) in many parts of the world, determining background concentrations of NO3- in shallow ground water from natural sources is probably impossible in most environments. Present-day background must now include diffuse sources of NO3- such as disruption of soils and oxidation of organic matter, and atmospheric inputs from products of combustion and evaporation of ammonia from fertilizer and livestock waste. Anomalies can be defined as NO3- derived from nitrogen (N) inputs to the environment from anthropogenic activities, including synthetic fertilizers, livestock waste, and septic effluent. Cumulative probability graphs were used to identify threshold concentrations separating background and anomalous NO3-N concentrations and to assist in the determination of sources of N contamination for 232 spring water samples and 200 well water samples from karst aquifers. Thresholds were 0.4, 2.5, and 6.7 mg/L for spring water samples, and 0.1, 2.1, and 17 mg/L for well water samples. The 0.4 and 0.1 mg/L values are assumed to represent thresholds for present-day precipitation. Thresholds at 2.5 and 2.1 mg/L are interpreted to represent present-day background concentrations of NO3-N. The population of spring water samples with concentrations between 2.5 and 6.7 mg/L represents an amalgam of all sources of NO3- in the ground water basins that feed each spring; concentrations >6.7 mg/L were typically samples collected soon after springtime application of synthetic fertilizer. The 17 mg/L threshold (adjusted to 15 mg/L) for well water samples is interpreted as the level above which livestock wastes dominate the N sources. Copyright ?? 2006 The Author(s).
Student Estimates of Probability and Uncertainty in Statistical Physics
NASA Astrophysics Data System (ADS)
Mountcastle, Donald B.; Bucy, B. R.; Thompson, J. R.
2006-12-01
Equilibrium properties of macroscopic (large N) systems are highly predictable as N approaches and exceeds Avogadro’s number. Theories of statistical physics depend on these results. Typical pedagogical devices used in statistical physics textbooks to introduce entropy (S) and multiplicity [S = k ln(w), where w is the system multiplicity] include flipping coins and/or other equivalent binary events, repeated n times. Prior to instruction, our students usually give reasonable answers about the probabilities, but not the uncertainties of the predicted outcomes of such events. However, they reliably predict that the uncertainty in a measured quantity (e.g., the amount of rainfall) decreases as the number of measurements increases. Typical textbook presentations presume that students will either have or develop the insight that the relative uncertainty of binary outcomes will similarly decrease as the number of events increases. That is at odds with our findings among students in two successive statistical mechanics classes. Many of our students had previously completed mathematics courses in statistics, as well as a physics laboratory course that included analysis of statistical properties of distributions of dart scores as the number (n) of throws (one-dimensional target) increased. There was a wide divergence of predictions about how the standard deviation of the distribution of dart scores should change, or not, as n increases. We find that student predictions about statistics of coin flips, dart scores, and rainfall amounts as functions of n are inconsistent at best. Supported in part by NSF Grant #PHY-0406764.
Robust location and spread measures for nonparametric probability density function estimation.
López-Rubio, Ezequiel
2009-10-01
Robustness against outliers is a desirable property of any unsupervised learning scheme. In particular, probability density estimators benefit from incorporating this feature. A possible strategy to achieve this goal is to substitute the sample mean and the sample covariance matrix by more robust location and spread estimators. Here we use the L1-median to develop a nonparametric probability density function (PDF) estimator. We prove its most relevant properties, and we show its performance in density estimation and classification applications.
A simulation model for estimating probabilities of defects in welds
Chapman, O.J.V.; Khaleel, M.A.; Simonen, F.A.
1996-12-01
In recent work for the US Nuclear Regulatory Commission in collaboration with Battelle Pacific Northwest National Laboratory, Rolls-Royce and Associates, Ltd., has adapted an existing model for piping welds to address welds in reactor pressure vessels. This paper describes the flaw estimation methodology as it applies to flaws in reactor pressure vessel welds (but not flaws in base metal or flaws associated with the cladding process). Details of the associated computer software (RR-PRODIGAL) are provided. The approach uses expert elicitation and mathematical modeling to simulate the steps in manufacturing a weld and the errors that lead to different types of weld defects. The defects that may initiate in weld beads include center cracks, lack of fusion, slag, pores with tails, and cracks in heat affected zones. Various welding processes are addressed including submerged metal arc welding. The model simulates the effects of both radiographic and dye penetrant surface inspections. Output from the simulation gives occurrence frequencies for defects as a function of both flaw size and flaw location (surface connected and buried flaws). Numerical results are presented to show the effects of submerged metal arc versus manual metal arc weld processes.
NASA Astrophysics Data System (ADS)
England, J. F.
2006-12-01
Estimates of extreme floods and probabilities are needed in dam safety risk analysis. A multidisciplinary approach was developed to estimate extreme floods that integrated four main elements: radar hydrometeorology, stochastic storm transposition, paleoflood data, and 2d distributed rainfall-runoff modeling. The research focused on developing and applying a two-dimensional, distributed model to simulate extreme floods on the 12,000 km2 Arkansas River above Pueblo, Colorado with return periods up to 10,000 years. The four objectives were to: (1) develop a two-dimensional model suitable for large watersheds (area greater than 2,500 km2); (2) calibrate and validate the model to the June 1921 and May 1894 floods on the Arkansas River; (3) develop a flood frequency curve with the model using the stochastic storm transposition technique; and (4) conduct a sensitivity analysis for initial soil saturation, storm duration and area, and compare the flood frequency curve with gage and paleoflood data. The Two-dimensional Runoff, Erosion and EXport (TREX) model was developed as part of this research. Basin-average rainfall depths and probabilities were estimated using DAD data and stochastic storm transposition with elliptical storms for input to TREX. From these extreme rainstorms, the TREX model was used to estimate a flood frequency curve for this large watershed. Model-generated peak flows were as large as 90,000 to 282,000 ft3/s at Pueblo for 100- to 10,000-year return periods, respectively. Model-generated frequency curves were generally comparable to peak flow and paleoflood data-based frequency curves after radar-based storm location and area limits were applied. The model provides a unique physically-based method for determining flood frequency curves under varied scenarios of antecedent moisture conditions, space and time variability of rainfall and watershed characteristics, and storm center locations.
Extreme Earthquake Risk Estimation by Hybrid Modeling
NASA Astrophysics Data System (ADS)
Chavez, M.; Cabrera, E.; Ashworth, M.; Garcia, S.; Emerson, D.; Perea, N.; Salazar, A.; Moulinec, C.
2012-12-01
The estimation of the hazard and the economical consequences i.e. the risk associated to the occurrence of extreme magnitude earthquakes in the neighborhood of urban or lifeline infrastructure, such as the 11 March 2011 Mw 9, Tohoku, Japan, represents a complex challenge as it involves the propagation of seismic waves in large volumes of the earth crust, from unusually large seismic source ruptures up to the infrastructure location. The large number of casualties and huge economic losses observed for those earthquakes, some of which have a frequency of occurrence of hundreds or thousands of years, calls for the development of new paradigms and methodologies in order to generate better estimates, both of the seismic hazard, as well as of its consequences, and if possible, to estimate the probability distributions of their ground intensities and of their economical impacts (direct and indirect losses), this in order to implement technological and economical policies to mitigate and reduce, as much as possible, the mentioned consequences. Herewith, we propose a hybrid modeling which uses 3D seismic wave propagation (3DWP) and neural network (NN) modeling in order to estimate the seismic risk of extreme earthquakes. The 3DWP modeling is achieved by using a 3D finite difference code run in the ~100 thousands cores Blue Gene Q supercomputer of the STFC Daresbury Laboratory of UK, combined with empirical Green function (EGF) techniques and NN algorithms. In particular the 3DWP is used to generate broadband samples of the 3D wave propagation of extreme earthquakes (plausible) scenarios corresponding to synthetic seismic sources and to enlarge those samples by using feed-forward NN. We present the results of the validation of the proposed hybrid modeling for Mw 8 subduction events, and show examples of its application for the estimation of the hazard and the economical consequences, for extreme Mw 8.5 subduction earthquake scenarios with seismic sources in the Mexican
Estimating Risk: Stereotype Amplification and the Perceived Risk of Criminal Victimization
QUILLIAN, LINCOLN; PAGER, DEVAH
2010-01-01
This paper considers the process by which individuals estimate the risk of adverse events, with particular attention to the social context in which risk estimates are formed. We compare subjective probability estimates of crime victimization to actual victimization experiences among respondents from the 1994 to 2002 waves of the Survey of Economic Expectations (Dominitz and Manski 2002). Using zip code identifiers, we then match these survey data to local area characteristics from the census. The results show that: (1) the risk of criminal victimization is significantly overestimated relative to actual rates of victimization or other negative events; (2) neighborhood racial composition is strongly associated with perceived risk of victimization, whereas actual victimization risk is driven by nonracial neighborhood characteristics; and (3) white respondents appear more strongly affected by racial composition than nonwhites in forming their estimates of risk. We argue these results support a model of stereotype amplification in the formation of risk estimates. Implications for persistent racial inequality are considered. PMID:20686631
Statistical Surrogate Models for Estimating Probability of High-Consequence Climate Change
NASA Astrophysics Data System (ADS)
Field, R.; Constantine, P.; Boslough, M.
2011-12-01
We have posed the climate change problem in a framework similar to that used in safety engineering, by acknowledging that probabilistic risk assessments focused on low-probability, high-consequence climate events are perhaps more appropriate than studies focused simply on best estimates. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We have developed specialized statistical surrogate models (SSMs) that can be used to make predictions about the tails of the associated probability distributions. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field, that is, a random variable for every fixed location in the atmosphere at all times. The SSM can be calibrated to available spatial and temporal data from existing climate databases, or to a collection of outputs from general circulation models. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework was also developed to provide quantitative measures of confidence, via Bayesian credible intervals, to assess these risks. To illustrate the use of the SSM, we considered two collections of NCAR CCSM 3.0 output data. The first collection corresponds to average December surface temperature for years 1990-1999 based on a collection of 8 different model runs obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI). We calibrated the surrogate model to the available model data and make various point predictions. We also analyzed average precipitation rate in June, July, and August over a 54-year period assuming a cyclic Y2K ocean model. We
2014-01-01
Background Data on HCV-related cirrhosis progression are scarce in developing countries in general, and in Egypt in particular. The objective of this study was to estimate the probability of death and transition between different health stages of HCV (compensated cirrhosis, decompensated cirrhosis and hepatocellular carcinoma) for an Egyptian population of patients with HCV-related cirrhosis. Methods We used the “elicitation of expert opinions” method to obtain collective knowledge from a panel of 23 Egyptian experts (among whom 17 were hepatologists or gastroenterologists and 2 were infectiologists). The questionnaire was based on virtual medical cases and asked the experts to assess probability of death or probability of various cirrhosis complications. The design was a Delphi study: we attempted to obtain a consensus between experts via a series of questionnaires interspersed with group response feedback. Results We found substantial disparity between experts’ answers, and no consensus was reached at the end of the process. Moreover, we obtained high death probability and high risk of hepatocellular carcinoma. The annual transition probability to death was estimated at between 10.1% and 61.5% and the annual probability of occurrence of hepatocellular carcinoma was estimated at between 16.8% and 58.9% (depending on age, gender, time spent in cirrhosis and cirrhosis severity). Conclusions Our results show that eliciting expert opinions is not suited for determining the natural history of diseases due to practitioners’ difficulties in evaluating quantities. Cognitive bias occurring during this type of study might explain our results. PMID:24635942
Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas
2014-07-01
Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077).
Seaver, D.A.; Stillwell, W.G.
1983-03-01
This report describes and evaluates several procedures for using expert judgment to estimate human-error probabilities (HEPs) in nuclear power plant operations. These HEPs are currently needed for several purposes, particularly for probabilistic risk assessments. Data do not exist for estimating these HEPs, so expert judgment can provide these estimates in a timely manner. Five judgmental procedures are described here: paired comparisons, ranking and rating, direct numerical estimation, indirect numerical estimation and multiattribute utility measurement. These procedures are evaluated in terms of several criteria: quality of judgments, difficulty of data collection, empirical support, acceptability, theoretical justification, and data processing. Situational constraints such as the number of experts available, the number of HEPs to be estimated, the time available, the location of the experts, and the resources available are discussed in regard to their implications for selecting a procedure for use.
A double-observer approach for estimating detection probability and abundance from point counts
Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Fallon, F.W.; Fallon, J.E.; Heglund, P.J.
2000-01-01
Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated 'primary' observer indicates to another ('secondary') observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.
Generalizations and Extensions of the Probability of Superiority Effect Size Estimator
ERIC Educational Resources Information Center
Ruscio, John; Gera, Benjamin Lee
2013-01-01
Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…
Waters, Martha; McKernan, Lauralynn; Maier, Andrew; Jayjock, Michael; Schaeffer, Val; Brosseau, Lisa
2015-01-01
The fundamental goal of this article is to describe, define, and analyze the components of the risk characterization process for occupational exposures. Current methods are described for the probabilistic characterization of exposure, including newer techniques that have increasing applications for assessing data from occupational exposure scenarios. In addition, since the probability of health effects reflects variability in the exposure estimate as well as the dose-response curve-the integrated considerations of variability surrounding both components of the risk characterization provide greater information to the occupational hygienist. Probabilistic tools provide a more informed view of exposure as compared to use of discrete point estimates for these inputs to the risk characterization process. Active use of such tools for exposure and risk assessment will lead to a scientifically supported worker health protection program. Understanding the bases for an occupational risk assessment, focusing on important sources of variability and uncertainty enables characterizing occupational risk in terms of a probability, rather than a binary decision of acceptable risk or unacceptable risk. A critical review of existing methods highlights several conclusions: (1) exposure estimates and the dose-response are impacted by both variability and uncertainty and a well-developed risk characterization reflects and communicates this consideration; (2) occupational risk is probabilistic in nature and most accurately considered as a distribution, not a point estimate; and (3) occupational hygienists have a variety of tools available to incorporate concepts of risk characterization into occupational health and practice.
Waters, Martha; McKernan, Lauralynn; Maier, Andrew; Jayjock, Michael; Schaeffer, Val; Brosseau, Lisa
2015-01-01
The fundamental goal of this article is to describe, define, and analyze the components of the risk characterization process for occupational exposures. Current methods are described for the probabilistic characterization of exposure, including newer techniques that have increasing applications for assessing data from occupational exposure scenarios. In addition, since the probability of health effects reflects variability in the exposure estimate as well as the dose-response curve—the integrated considerations of variability surrounding both components of the risk characterization provide greater information to the occupational hygienist. Probabilistic tools provide a more informed view of exposure as compared to use of discrete point estimates for these inputs to the risk characterization process. Active use of such tools for exposure and risk assessment will lead to a scientifically supported worker health protection program. Understanding the bases for an occupational risk assessment, focusing on important sources of variability and uncertainty enables characterizing occupational risk in terms of a probability, rather than a binary decision of acceptable risk or unacceptable risk. A critical review of existing methods highlights several conclusions: (1) exposure estimates and the dose-response are impacted by both variability and uncertainty and a well-developed risk characterization reflects and communicates this consideration; (2) occupational risk is probabilistic in nature and most accurately considered as a distribution, not a point estimate; and (3) occupational hygienists have a variety of tools available to incorporate concepts of risk characterization into occupational health and practice. PMID:26302336
Improving quality of sample entropy estimation for continuous distribution probability functions
NASA Astrophysics Data System (ADS)
Miśkiewicz, Janusz
2016-05-01
Entropy is a one of the key parameters characterizing state of system in statistical physics. Although, the entropy is defined for systems described by discrete and continuous probability distribution function (PDF), in numerous applications the sample entropy is estimated by a histogram, which, in fact, denotes that the continuous PDF is represented by a set of probabilities. Such a procedure may lead to ambiguities and even misinterpretation of the results. Within this paper, two possible general algorithms based on continuous PDF estimation are discussed in the application to the Shannon and Tsallis entropies. It is shown that the proposed algorithms may improve entropy estimation, particularly in the case of small data sets.
Brand, Matthias; Schiebener, Johannes; Pertl, Marie-Theres; Delazer, Margarete
2014-01-01
Recent models on decision making under risk conditions have suggested that numerical abilities are important ingredients of advantageous decision-making performance, but empirical evidence is still limited. The results of our first study show that logical reasoning and basic mental calculation capacities predict ratio processing and that ratio processing predicts decision making under risk. In the second study, logical reasoning together with executive functions predicted probability processing (numeracy and probability knowledge), and probability processing predicted decision making under risk. These findings suggest that increasing an individual's understanding of ratios and probabilities should lead to more advantageous decisions under risk conditions. PMID:25252799
A removal model for estimating detection probabilities from point-count surveys
Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.
2000-01-01
We adapted a removal model to estimate detection probability during point count surveys. The model assumes one factor influencing detection during point counts is the singing frequency of birds. This may be true for surveys recording forest songbirds when most detections are by sound. The model requires counts to be divided into several time intervals. We used time intervals of 2, 5, and 10 min to develop a maximum-likelihood estimator for the detectability of birds during such surveys. We applied this technique to data from bird surveys conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. The overall detection probability for all birds was 75%. We found differences in detection probability among species. Species that sing frequently such as Winter Wren and Acadian Flycatcher had high detection probabilities (about 90%) and species that call infrequently such as Pileated Woodpecker had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. This method of estimating detectability during point count surveys offers a promising new approach to using count data to address questions of the bird abundance, density, and population trends.
Nichols, J.D.; Sauer, J.R.; Pollock, K.H.; Hestbeck, J.B.
1992-01-01
In stage-based demography, animals are often categorized into size (or mass) classes, and size-based probabilities of surviving and changing mass classes must be estimated before demographic analyses can be conducted. In this paper, we develop two procedures for the estimation of mass transition probabilities from capture-recapture data. The first approach uses a multistate capture-recapture model that is parameterized directly with the transition probabilities of interest. Maximum likelihood estimates are then obtained numerically using program SURVIV. The second approach involves a modification of Pollock's robust design. Estimation proceeds by conditioning on animals caught in a particualr class at time i, and then using closed models to estimate the number of these that are alive in other classes at i + 1. Both methods are illustrated by application to meadow vole, Microtus pennsylvanicus, capture-recapture data. The two methods produced reasonable estimates that were similar. Advantages of these two approaches include the directness of estimation, the absence of need for restrictive assumptions about the independence of survival and growth, the testability of assumptions, and the testability of related hypotheses of ecological interest (e.g., the hypothesis of temporal variation in transition probabilities).
Nonparametric maximum likelihood estimation of probability densities by penalty function methods
NASA Technical Reports Server (NTRS)
Demontricher, G. F.; Tapia, R. A.; Thompson, J. R.
1974-01-01
When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the nonparametric maximum likelihood procedure is undefined. A very general theory of maximum penalized likelihood estimation which should avoid many of these difficulties is presented. It is demonstrated that each reproducing kernel Hilbert space leads, in a very natural way, to a maximum penalized likelihood estimator and that a well-known class of reproducing kernel Hilbert spaces gives polynomial splines as the nonparametric maximum penalized likelihood estimates.
NASA Astrophysics Data System (ADS)
Frigm, R.; Johnson, L.
The Probability of Collision (Pc) has become a universal metric and statement of on-orbit collision risk. Although several flavors of the computation exist and are well-documented in the literature, the basic calculation requires the same input: estimates for the position, position uncertainty, and sizes of the two objects involved. The Pc is used operationally to make decisions on whether a given conjunction poses significant collision risk to the primary object (or space asset of concern). It is also used to determine necessity and degree of mitigative action (typically in the form of an orbital maneuver) to be performed. The predicted post-maneuver Pc also informs the maneuver planning process into regarding the timing, direction, and magnitude of the maneuver needed to mitigate the collision risk. Although the data sources, techniques, decision calculus, and workflows vary for different agencies and organizations, they all have a common thread. The standard conjunction assessment and collision risk concept of operations (CONOPS) predicts conjunctions, assesses the collision risk (typically, via the Pc), and plans and executes avoidance activities for conjunctions as a discrete events. As the space debris environment continues to increase and improvements are made to remote sensing capabilities and sensitivities to detect, track, and predict smaller debris objects, the number of conjunctions will in turn continue to increase. The expected order-of-magnitude increase in the number of predicted conjunctions will challenge the paradigm of treating each conjunction as a discrete event. The challenge will not be limited to workload issues, such as manpower and computing performance, but also the ability for satellite owner/operators to successfully execute their mission while also managing on-orbit collision risk. Executing a propulsive maneuver occasionally can easily be absorbed into the mission planning and operations tempo; whereas, continuously planning evasive
Hoblitt, Richard P.; Scott, William E.
2011-01-01
In response to a request from the U.S. Department of Energy, we estimate the thickness of tephra accumulation that has an annual probability of 1 in 10,000 of being equaled or exceeded at the Hanford Site in south-central Washington State, where a project to build the Tank Waste Treatment and Immobilization Plant is underway. We follow the methodology of a 1987 probabilistic assessment of tephra accumulation in the Pacific Northwest. For a given thickness of tephra, we calculate the product of three probabilities: (1) the annual probability of an eruption producing 0.1 km3 (bulk volume) or more of tephra, (2) the probability that the wind will be blowing toward the Hanford Site, and (3) the probability that tephra accumulations will equal or exceed the given thickness at a given distance. Mount St. Helens, which lies about 200 km upwind from the Hanford Site, has been the most prolific source of tephra fallout among Cascade volcanoes in the recent geologic past and its annual eruption probability based on this record (0.008) dominates assessment of future tephra falls at the site. The probability that the prevailing wind blows toward Hanford from Mount St. Helens is 0.180. We estimate exceedance probabilities of various thicknesses of tephra fallout from an analysis of 14 eruptions of the size expectable from Mount St. Helens and for which we have measurements of tephra fallout at 200 km. The result is that the estimated thickness of tephra accumulation that has an annual probability of 1 in 10,000 of being equaled or exceeded is about 10 centimeters. It is likely that this thickness is a maximum estimate because we used conservative estimates of eruption and wind probabilities and because the 14 deposits we used probably provide an over-estimate. The use of deposits in this analysis that were mostly compacted by the time they were studied and measured implies that the bulk density of the tephra fallout we consider here is in the range of 1,000-1,250 kg/m3. The
A removal model for estimating detection probabilities from point-count surveys
Farnsworth, G.L.; Pollock, K.H.; Nichols, J.D.; Simons, T.R.; Hines, J.E.; Sauer, J.R.
2002-01-01
Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (~90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.
Estimating probabilities of reservoir storage for the upper Delaware River basin
Hirsch, Robert M.
1981-01-01
A technique for estimating conditional probabilities of reservoir system storage is described and applied to the upper Delaware River Basin. The results indicate that there is a 73 percent probability that the three major New York City reservoirs (Pepacton, Cannonsville, and Neversink) would be full by June 1, 1981, and only a 9 percent probability that storage would return to the ' drought warning ' sector of the operations curve sometime in the next year. In contrast, if restrictions are lifted and there is an immediate return to normal operating policies, the probability of the reservoir system being full by June 1 is 37 percent and the probability that storage would return to the ' drought warning ' sector in the next year is 30 percent. (USGS)
Using of bayesian networks to estimate the probability of "NATECH" scenario occurrence
NASA Astrophysics Data System (ADS)
Dobes, Pavel; Dlabka, Jakub; Jelšovská, Katarína; Polorecká, Mária; Baudišová, Barbora; Danihelka, Pavel
2015-04-01
In the twentieth century, implementation of Bayesian statistics and probability was not much used (may be it wasn't a preferred approach) in the area of natural and industrial risk analysis and management. Neither it was used within analysis of so called NATECH accidents (chemical accidents triggered by natural events, such as e.g. earthquakes, floods, lightning etc.; ref. E. Krausmann, 2011, doi:10.5194/nhess-11-921-2011). Main role, from the beginning, played here so called "classical" frequentist probability (ref. Neyman, 1937), which rely up to now especially on the right/false results of experiments and monitoring and didn't enable to count on expert's beliefs, expectations and judgements (which is, on the other hand, one of the once again well known pillars of Bayessian approach to probability). In the last 20 or 30 years, there is possible to observe, through publications and conferences, the Renaissance of Baysssian statistics into many scientific disciplines (also into various branches of geosciences). The necessity of a certain level of trust in expert judgment within risk analysis is back? After several decades of development on this field, it could be proposed following hypothesis (to be checked): "We couldn't estimate probabilities of complex crisis situations and their TOP events (many NATECH events could be classified as crisis situations or emergencies), only by classical frequentist approach, but also by using of Bayessian approach (i.e. with help of prestaged Bayessian Network including expert belief and expectation as well as classical frequentist inputs). Because - there is not always enough quantitative information from monitoring of historical emergencies, there could be several dependant or independant variables necessary to consider and in generally - every emergency situation always have a little different run." In this topic, team of authors presents its proposal of prestaged typized Bayessian network model for specified NATECH scenario
Estimating the Probability of Asteroid Collision with the Earth by the Monte Carlo Method
NASA Astrophysics Data System (ADS)
Chernitsov, A. M.; Tamarov, V. A.; Barannikov, E. A.
2016-09-01
The commonly accepted method of estimating the probability of asteroid collision with the Earth is investigated on an example of two fictitious asteroids one of which must obviously collide with the Earth and the second must pass by at a dangerous distance from the Earth. The simplest Kepler model of motion is used. Confidence regions of asteroid motion are estimated by the Monte Carlo method. Two variants of constructing the confidence region are considered: in the form of points distributed over the entire volume and in the form of points mapped onto the boundary surface. The special feature of the multidimensional point distribution in the first variant of constructing the confidence region that can lead to zero probability of collision for bodies that collide with the Earth is demonstrated. The probability estimates obtained for even considerably smaller number of points in the confidence region determined by its boundary surface are free from this disadvantage.
Estimate of the probability of a lightning strike to the Galileo probe
NASA Astrophysics Data System (ADS)
Borucki, W. J.
1985-04-01
Lightning strikes to aerospace vehicles occur mainly in or near clouds. As the Galileo entry probe will pass most of its operational life in the clouds of Jupiter, which is known to have lightning activity, the present study is concerned with the risk of a lightning strike to the probe. A strike to the probe could cause physical damage to the structure and/or damage to the electronic equipment aboard the probe. It is thought to be possible, for instance, that the instrument failures which occurred on all four Pioneer Venus entry probes at an altitude of 12 km were due to an external electric discharge. The probability of a lightning strike to the Galileo probe is evaluated. It is found that the estimate of a strike to the probe is only 0.001, which is about the same as the expected failure rate due to other design factors. In the case of entry probes to cloud-covered planets, a consideration of measures for protecting the vehicle and its payload from lightning appears to be appropriate.
van der Hoop, Julie M; Vanderlaan, Angelia S M; Taggart, Christopher T
2012-10-01
Vessel strikes are the primary source of known mortality for the endangered North Atlantic right whale (Eubalaena glacialis). Multi-institutional efforts to reduce mortality associated with vessel strikes include vessel-routing amendments such as the International Maritime Organization voluntary "area to be avoided" (ATBA) in the Roseway Basin right whale feeding habitat on the southwestern Scotian Shelf. Though relative probabilities of lethal vessel strikes have been estimated and published, absolute probabilities remain unknown. We used a modeling approach to determine the regional effect of the ATBA, by estimating reductions in the expected number of lethal vessel strikes. This analysis differs from others in that it explicitly includes a spatiotemporal analysis of real-time transits of vessels through a population of simulated, swimming right whales. Combining automatic identification system (AIS) vessel navigation data and an observationally based whale movement model allowed us to determine the spatial and temporal intersection of vessels and whales, from which various probability estimates of lethal vessel strikes are derived. We estimate one lethal vessel strike every 0.775-2.07 years prior to ATBA implementation, consistent with and more constrained than previous estimates of every 2-16 years. Following implementation, a lethal vessel strike is expected every 41 years. When whale abundance is held constant across years, we estimate that voluntary vessel compliance with the ATBA results in an 82% reduction in the per capita rate of lethal strikes; very similar to a previously published estimate of 82% reduction in the relative risk of a lethal vessel strike. The models we developed can inform decision-making and policy design, based on their ability to provide absolute, population-corrected, time-varying estimates of lethal vessel strikes, and they are easily transported to other regions and situations.
Delavande, Adeline; Rohwedder, Susann
2013-01-01
Cross-country comparisons of differential survival by socioeconomic status (SES) are useful in many domains. Yet, to date, such studies have been rare. Reliably estimating differential survival in a single country has been challenging because it requires rich panel data with a large sample size. Cross-country estimates have proven even more difficult because the measures of SES need to be comparable internationally. We present an alternative method for acquiring information on differential survival by SES. Rather than using observations of actual survival, we relate individuals’ subjective probabilities of survival to SES variables in cross section. To show that subjective survival probabilities are informative proxies for actual survival when estimating differential survival, we compare estimates of differential survival based on actual survival with estimates based on subjective probabilities of survival for the same sample. The results are remarkably similar. We then use this approach to compare differential survival by SES for 10 European countries and the United States. Wealthier people have higher survival probabilities than those who are less wealthy, but the strength of the association differs across countries. Nations with a smaller gradient appear to be Belgium, France, and Italy, while the United States, England, and Sweden appear to have a larger gradient. PMID:22042664
Alvares, N; Lambert, H
2007-02-07
The Federal Aviation Administration (FAA) identified 17 accidents that may have resulted from fuel tank explosions on commercial aircraft from 1959 to 2001. Seven events involved JP 4 or JP 4/Jet A mixtures that are no longer used for commercial aircraft fuel. The remaining 10 events involved Jet A or Jet A1 fuels that are in current use by the commercial aircraft industry. Four fuel tank explosions occurred in center wing tanks (CWTs) where on-board appliances can potentially transfer heat to the tank. These tanks are designated as ''Heated Center Wing Tanks'' (HCWT). Since 1996, the FAA has significantly increased the rate at which it has mandated airworthiness directives (ADs) directed at elimination of ignition sources. This effort includes the adoption, in 2001, of Special Federal Aviation Regulation 88 of 14 CFR part 21 (SFAR 88 ''Fuel Tank System Fault Tolerance Evaluation Requirements''). This paper addresses SFAR 88 effectiveness in reducing HCWT ignition source probability. Our statistical analysis, relating the occurrence of both on-ground and in-flight HCWT explosions to the cumulative flight hours of commercial passenger aircraft containing HCWT's reveals that the best estimate of HCWT explosion rate is 1 explosion in 1.4 x 10{sup 8} flight hours. Based on an analysis of SFAR 88 by Sandia National Laboratories and our independent analysis, SFAR 88 reduces current risk of historical HCWT explosion by at least a factor of 10, thus meeting an FAA risk criteria of 1 accident in billion flight hours. This paper also surveys and analyzes parameters for Jet A fuel ignition in HCWT's. Because of the paucity of in-flight HCWT explosions, we conclude that the intersection of the parameters necessary and sufficient to result in an HCWT explosion with sufficient overpressure to rupture the HCWT is extremely rare.
Relating space radiation environments to risk estimates
Curtis, S.B.
1991-10-01
This lecture will provide a bridge from the physical energy or LET spectra as might be calculated in an organ to the risk of carcinogenesis, a particular concern for extended missions to the moon or beyond to Mars. Topics covered will include (1) LET spectra expected from galactic cosmic rays, (2) probabilities that individual cell nuclei in the body will be hit by heavy galactic cosmic ray particles, (3) the conventional methods of calculating risks from a mixed environment of high and low LET radiation, (4) an alternate method which provides certain advantages using fluence-related risk coefficients (risk cross sections), and (5) directions for future research and development of these ideas.
Jordan, Preston D.; Oldenburg, Curtis M.; Nicot, Jean-Philippe
2008-11-01
Leakage of CO{sub 2} out of the designated storage region via faults is a widely recognized concern for geologic carbon sequestration. The probability of such leakage can be separated into the probability of a plume encountering a fault and the probability of flow along such a fault. In the absence of deterministic fault location information, the first probability can be calculated from regional fault population statistics and modeling of the plume shape and size. In this study, fault statistical parameters were measured or estimated for WESTCARB's Phase III pilot test injection in the San Joaquin Valley, California. Combining CO{sub 2} plume model predictions with estimated fault characteristics resulted in a 3% probability that the CO{sub 2} plume will encounter a fault fully offsetting the 180 m (590 ft) thick seal. The probability of leakage is lower, likely much lower, as faults with this offset are probably low-permeability features in this area.
Estimation of Hail Risk in the UK and Europe
NASA Astrophysics Data System (ADS)
Robinson, Eric; Parker, Melanie; Higgs, Stephanie
2016-04-01
Observations of hail events in Europe, and the UK especially, are relatively limited. In order to determine hail risk it is therefore necessary to use information other than relying purely on the historical record. One such methodology is to leverage reanalysis data, in this case ERA-Interim, along with a numerical model (WRF) to recreate the past state of the atmosphere. Relevant atmospheric properties can be extracted and used in a regression model to determine hail probability for each day contained within the reanalyses. The results presented here show the results of using a regression model based on convective available potential energy, deep level shear and weather type. Combined these parameters represent the probability of severe thunderstorm, and in turn hail, activity. Once the probability of hail occurring on each day is determined this can be used as the basis of a stochastic catalogue which can be used in the estimation of hail risk.
Probability of Error in Estimating States of a Flow of Physical Events
NASA Astrophysics Data System (ADS)
Gortsev, A. M.; Solov'ev, A. A.
2016-09-01
A flow of physical events (photons, electrons, etc.) is considered. One of the mathematical models of such flows is the MAP flow of events. Analytical results for conditional and unconditional probabilities of erroneous decision in optimal estimation of states of the MAP flow of events are presented.
Juang, K.W.; Lee, D.Y.
1998-09-01
The probability of incorrectly delineating hazardous areas in a contaminated site is very important for decision-makers because it indicates the magnitude of confidence that decision-makers have in determining areas in need of remediation. In this study, simple indicator kriging (SIK) was used to estimate the probability of incorrectly delineating hazardous areas in a heavy metal-contaminated site, which is located at Taoyuan, Taiwan, and is about 10 ha in area. In the procedure, the values 0 and 1 were assigned to be the stationary means of the indicator codes in the SIK model to represent two hypotheses, hazardous and safe, respectively. The spatial distribution of the conditional probability of heavy metal concentrations lower than a threshold, given each hypothesis, was estimated using SIK. Then, the probabilities of false positives ({alpha}) (i.e., the probability of declaring a location hazardous when it is not) and false negatives ({beta}) (i.e., the probability of declaring a location safe when it is not) in delineating hazardous areas for the heavy metal-contaminated site could be obtained. The spatial distribution of the probabilities of false positives and false negatives could help in delineating hazardous areas based on a tolerable probability level of incorrect delineation. In addition, delineation complicated by the cost of remediation, hazards in the environment, and hazards to human health could be made based on the minimum values of {alpha} and {beta}. The results suggest that the proposed SIK procedure is useful for decision-makers who need to delineate hazardous areas in a heavy metal-contaminated site.
ERIC Educational Resources Information Center
Harris, Adam J. L.; Corner, Adam
2011-01-01
Verbal probability expressions are frequently used to communicate risk and uncertainty. The Intergovernmental Panel on Climate Change (IPCC), for example, uses them to convey risks associated with climate change. Given the potential for human action to mitigate future environmental risks, it is important to understand how people respond to these…
O'Connell, Allan F.; Talancy, Neil W.; Bailey, Larissa L.; Sauer, John R.; Cook, Robert; Gilbert, Andrew T.
2006-01-01
Large-scale, multispecies monitoring programs are widely used to assess changes in wildlife populations but they often assume constant detectability when documenting species occurrence. This assumption is rarely met in practice because animal populations vary across time and space. As a result, detectability of a species can be influenced by a number of physical, biological, or anthropogenic factors (e.g., weather, seasonality, topography, biological rhythms, sampling methods). To evaluate some of these influences, we estimated site occupancy rates using species-specific detection probabilities for meso- and large terrestrial mammal species on Cape Cod, Massachusetts, USA. We used model selection to assess the influence of different sampling methods and major environmental factors on our ability to detect individual species. Remote cameras detected the most species (9), followed by cubby boxes (7) and hair traps (4) over a 13-month period. Estimated site occupancy rates were similar among sampling methods for most species when detection probabilities exceeded 0.15, but we question estimates obtained from methods with detection probabilities between 0.05 and 0.15, and we consider methods with lower probabilities unacceptable for occupancy estimation and inference. Estimated detection probabilities can be used to accommodate variation in sampling methods, which allows for comparison of monitoring programs using different protocols. Vegetation and seasonality produced species-specific differences in detectability and occupancy, but differences were not consistent within or among species, which suggests that our results should be considered in the context of local habitat features and life history traits for the target species. We believe that site occupancy is a useful state variable and suggest that monitoring programs for mammals using occupancy data consider detectability prior to making inferences about species distributions or population change.
NASA Astrophysics Data System (ADS)
Boslough, M.
2011-12-01
Climate-related uncertainty is traditionally presented as an error bar, but it is becoming increasingly common to express it in terms of a probability density function (PDF). PDFs are a necessary component of probabilistic risk assessments, for which simple "best estimate" values are insufficient. Many groups have generated PDFs for climate sensitivity using a variety of methods. These PDFs are broadly consistent, but vary significantly in their details. One axiom of the verification and validation community is, "codes don't make predictions, people make predictions." This is a statement of the fact that subject domain experts generate results using assumptions within a range of epistemic uncertainty and interpret them according to their expert opinion. Different experts with different methods will arrive at different PDFs. For effective decision support, a single consensus PDF would be useful. We suggest that market methods can be used to aggregate an ensemble of opinions into a single distribution that expresses the consensus. Prediction markets have been shown to be highly successful at forecasting the outcome of events ranging from elections to box office returns. In prediction markets, traders can take a position on whether some future event will or will not occur. These positions are expressed as contracts that are traded in a double-action market that aggregates price, which can be interpreted as a consensus probability that the event will take place. Since climate sensitivity cannot directly be measured, it cannot be predicted. However, the changes in global mean surface temperature are a direct consequence of climate sensitivity, changes in forcing, and internal variability. Viable prediction markets require an undisputed event outcome on a specific date. Climate-related markets exist on Intrade.com, an online trading exchange. One such contract is titled "Global Temperature Anomaly for Dec 2011 to be greater than 0.65 Degrees C." Settlement is based
Langtimm, C.A.; O'Shea, T.J.; Pradel, R.; Beck, C.A.
1998-01-01
The population dynamics of large, long-lived mammals are particularly sensitive to changes in adult survival. Understanding factors affecting survival patterns is therefore critical for developing and testing theories of population dynamics and for developing management strategies aimed at preventing declines or extinction in such taxa. Few studies have used modern analytical approaches for analyzing variation and testing hypotheses about survival probabilities in large mammals. This paper reports a detailed analysis of annual adult survival in the Florida manatee (Trichechus manatus latirostris), an endangered marine mammal, based on a mark-recapture approach. Natural and boat-inflicted scars distinctively 'marked' individual manatees that were cataloged in a computer-based photographic system. Photo-documented resightings provided 'recaptures.' Using open population models, annual adult-survival probabilities were estimated for manatees observed in winter in three areas of Florida: Blue Spring, Crystal River, and the Atlantic coast. After using goodness-of-fit tests in Program RELEASE to search for violations of the assumptions of mark-recapture analysis, survival and sighting probabilities were modeled under several different biological hypotheses with Program SURGE. Estimates of mean annual probability of sighting varied from 0.948 for Blue Spring to 0.737 for Crystal River and 0.507 for the Atlantic coast. At Crystal River and Blue Spring, annual survival probabilities were best estimated as constant over the study period at 0.96 (95% CI = 0.951-0.975 and 0.900-0.985, respectively). On the Atlantic coast, where manatees are impacted more by human activities, annual survival probabilities had a significantly lower mean estimate of 0.91 (95% CI = 0.887-0.926) and varied unpredictably over the study period. For each study area, survival did not differ between sexes and was independent of relative adult age. The high constant adult-survival probabilities estimated
Quasi-likelihood estimation for relative risk regression models.
Carter, Rickey E; Lipsitz, Stuart R; Tilley, Barbara C
2005-01-01
For a prospective randomized clinical trial with two groups, the relative risk can be used as a measure of treatment effect and is directly interpretable as the ratio of success probabilities in the new treatment group versus the placebo group. For a prospective study with many covariates and a binary outcome (success or failure), relative risk regression may be of interest. If we model the log of the success probability as a linear function of covariates, the regression coefficients are log-relative risks. However, using such a log-linear model with a Bernoulli likelihood can lead to convergence problems in the Newton-Raphson algorithm. This is likely to occur when the success probabilities are close to one. A constrained likelihood method proposed by Wacholder (1986, American Journal of Epidemiology 123, 174-184), also has convergence problems. We propose a quasi-likelihood method of moments technique in which we naively assume the Bernoulli outcome is Poisson, with the mean (success probability) following a log-linear model. We use the Poisson maximum likelihood equations to estimate the regression coefficients without constraints. Using method of moment ideas, one can show that the estimates using the Poisson likelihood will be consistent and asymptotically normal. We apply these methods to a double-blinded randomized trial in primary biliary cirrhosis of the liver (Markus et al., 1989, New England Journal of Medicine 320, 1709-1713). PMID:15618526
Empirical estimation of the conditional probability of natech events within the United States.
Santella, Nicholas; Steinberg, Laura J; Aguirra, Gloria Andrea
2011-06-01
Natural disasters are the cause of a sizeable number of hazmat releases, referred to as "natechs." An enhanced understanding of natech probability, allowing for predictions of natech occurrence, is an important step in determining how industry and government should mitigate natech risk. This study quantifies the conditional probabilities of natechs at TRI/RMP and SICS 1311 facilities given the occurrence of hurricanes, earthquakes, tornadoes, and floods. During hurricanes, a higher probability of releases was observed due to storm surge (7.3 releases per 100 TRI/RMP facilities exposed vs. 6.2 for SIC 1311) compared to category 1-2 hurricane winds (5.6 TRI, 2.6 SIC 1311). Logistic regression confirms the statistical significance of the greater propensity for releases at RMP/TRI facilities, and during some hurricanes, when controlling for hazard zone. The probability of natechs at TRI/RMP facilities during earthquakes increased from 0.1 releases per 100 facilities at MMI V to 21.4 at MMI IX. The probability of a natech at TRI/RMP facilities within 25 miles of a tornado was small (∼0.025 per 100 facilities), reflecting the limited area directly affected by tornadoes. Areas inundated during flood events had a probability of 1.1 releases per 100 facilities but demonstrated widely varying natech occurrence during individual events, indicating that factors not quantified in this study such as flood depth and speed are important for predicting flood natechs. These results can inform natech risk analysis, aid government agencies responsible for planning response and remediation after natural disasters, and should be useful in raising awareness of natech risk within industry. PMID:21231945
Empirical estimation of the conditional probability of natech events within the United States.
Santella, Nicholas; Steinberg, Laura J; Aguirra, Gloria Andrea
2011-06-01
Natural disasters are the cause of a sizeable number of hazmat releases, referred to as "natechs." An enhanced understanding of natech probability, allowing for predictions of natech occurrence, is an important step in determining how industry and government should mitigate natech risk. This study quantifies the conditional probabilities of natechs at TRI/RMP and SICS 1311 facilities given the occurrence of hurricanes, earthquakes, tornadoes, and floods. During hurricanes, a higher probability of releases was observed due to storm surge (7.3 releases per 100 TRI/RMP facilities exposed vs. 6.2 for SIC 1311) compared to category 1-2 hurricane winds (5.6 TRI, 2.6 SIC 1311). Logistic regression confirms the statistical significance of the greater propensity for releases at RMP/TRI facilities, and during some hurricanes, when controlling for hazard zone. The probability of natechs at TRI/RMP facilities during earthquakes increased from 0.1 releases per 100 facilities at MMI V to 21.4 at MMI IX. The probability of a natech at TRI/RMP facilities within 25 miles of a tornado was small (∼0.025 per 100 facilities), reflecting the limited area directly affected by tornadoes. Areas inundated during flood events had a probability of 1.1 releases per 100 facilities but demonstrated widely varying natech occurrence during individual events, indicating that factors not quantified in this study such as flood depth and speed are important for predicting flood natechs. These results can inform natech risk analysis, aid government agencies responsible for planning response and remediation after natural disasters, and should be useful in raising awareness of natech risk within industry.
On the Estimation of Detection Probabilities for Sampling Stream-Dwelling Fishes.
Peterson, James T.
1999-11-01
To examine the adequacy of fish probability of detection estimates, I examined distributional properties of survey and monitoring data for bull trout (Salvelinus confluentus), brook trout (Salvelinus fontinalis), westslope cutthroat trout (Oncorhynchus clarki lewisi), chinook salmon parr (Oncorhynchus tshawytscha), and steelhead /redband trout (Oncorhynchus mykiss spp.), from 178 streams in the Interior Columbia River Basin. Negative binomial dispersion parameters varied considerably among species and streams, but were significantly (P<0.05) positively related to fish density. Across streams, the variances in fish abundances differed greatly among species and indicated that the data for all species were overdispersed with respect to the Poisson (i.e., the variances exceeded the means). This significantly affected Poisson probability of detection estimates, which were the highest across species and were, on average, 3.82, 2.66, and 3.47 times greater than baseline values. Required sample sizes for species detection at the 95% confidence level were also lowest for the Poisson, which underestimated sample size requirements an average of 72% across species. Negative binomial and Poisson-gamma probability of detection and sample size estimates were more accurate than the Poisson and generally less than 10% from baseline values. My results indicate the Poisson and binomial assumptions often are violated, which results in probability of detection estimates that are biased high and sample size estimates that are biased low. To increase the accuracy of these estimates, I recommend that future studies use predictive distributions than can incorporate multiple sources of uncertainty or excess variance and that all distributional assumptions be explicitly tested.
Procedure for estimating orbital debris risks
NASA Technical Reports Server (NTRS)
Crafts, J. L.; Lindberg, J. P.
1985-01-01
A procedure for estimating the potential orbital debris risk to the world's populace from payloads or spent stages left in orbit on future missions is presented. This approach provides a consistent, but simple, procedure to assess the risk due to random reentry with an adequate accuracy level for making programmatic decisions on planned low Earth orbit missions.
Effects of prior detections on estimates of detection probability, abundance, and occupancy
Riddle, Jason D.; Mordecai, Rua S.; Pollock, Kenneth H.; Simons, Theodore R.
2010-01-01
Survey methods that account for detection probability often require repeated detections of individual birds or repeated visits to a site to conduct Counts or collect presence-absence data. Initial encounters with individual species or individuals of a species could influence detection probabilities for subsequent encounters. For example, observers may be more likely to redetect a species or individual once they are aware of the presence of that species or individual at a particular site. Not accounting for these effects could result in biased estimators of detection probability, abundance, and occupancy. We tested for effects of prior detections in three data sets that differed dramatically by species, geographic location, and method of counting birds. We found strong support (AIC weights from 83% to 100%) for models that allowed for the effects of prior detections. These models produced estimates of detection probability, abundance, and occupancy that differed substantially from those produced by models that ignored the effects of prior detections. We discuss the consequences of the effects of prior detections on estimation for several sampling methods and provide recommendations for avoiding these effects through survey design or by modeling them when they cannot be avoided.
Michael, Andrew J.
2012-01-01
Estimates of the probability that an ML 4.8 earthquake, which occurred near the southern end of the San Andreas fault on 24 March 2009, would be followed by an M 7 mainshock over the following three days vary from 0.0009 using a Gutenberg–Richter model of aftershock statistics (Reasenberg and Jones, 1989) to 0.04 using a statistical model of foreshock behavior and long‐term estimates of large earthquake probabilities, including characteristic earthquakes (Agnew and Jones, 1991). I demonstrate that the disparity between the existing approaches depends on whether or not they conform to Gutenberg–Richter behavior. While Gutenberg–Richter behavior is well established over large regions, it could be violated on individual faults if they have characteristic earthquakes or over small areas if the spatial distribution of large‐event nucleations is disproportional to the rate of smaller events. I develop a new form of the aftershock model that includes characteristic behavior and combines the features of both models. This new model and the older foreshock model yield the same results when given the same inputs, but the new model has the advantage of producing probabilities for events of all magnitudes, rather than just for events larger than the initial one. Compared with the aftershock model, the new model has the advantage of taking into account long‐term earthquake probability models. Using consistent parameters, the probability of an M 7 mainshock on the southernmost San Andreas fault is 0.0001 for three days from long‐term models and the clustering probabilities following the ML 4.8 event are 0.00035 for a Gutenberg–Richter distribution and 0.013 for a characteristic‐earthquake magnitude–frequency distribution. Our decisions about the existence of characteristic earthquakes and how large earthquakes nucleate have a first‐order effect on the probabilities obtained from short‐term clustering models for these large events.
Estimating Super Heavy Element Event Random Probabilities Using Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Stoyer, Mark; Henderson, Roger; Kenneally, Jacqueline; Moody, Kenton; Nelson, Sarah; Shaughnessy, Dawn; Wilk, Philip
2009-10-01
Because superheavy element (SHE) experiments involve very low event rates and low statistics, estimating the probability that a given event sequence is due to random events is extremely important in judging the validity of the data. A Monte Carlo method developed at LLNL [1] is used on recent SHE experimental data to calculate random event probabilities. Current SHE experimental activities in collaboration with scientists at Dubna, Russia will be discussed. [4pt] [1] N.J. Stoyer, et al., Nucl. Instrum. Methods Phys. Res. A 455 (2000) 433.
Dodd, C.K.; Dorazio, R.M.
2004-01-01
A critical variable in both ecological and conservation field studies is determining how many individuals of a species are present within a defined sampling area. Labor intensive techniques such as capture-mark-recapture and removal sampling may provide estimates of abundance, but there are many logistical constraints to their widespread application. Many studies on terrestrial and aquatic salamanders use counts as an index of abundance, assuming that detection remains constant while sampling. If this constancy is violated, determination of detection probabilities is critical to the accurate estimation of abundance. Recently, a model was developed that provides a statistical approach that allows abundance and detection to be estimated simultaneously from spatially and temporally replicated counts. We adapted this model to estimate these parameters for salamanders sampled over a six vear period in area-constrained plots in Great Smoky Mountains National Park. Estimates of salamander abundance varied among years, but annual changes in abundance did not vary uniformly among species. Except for one species, abundance estimates were not correlated with site covariates (elevation/soil and water pH, conductivity, air and water temperature). The uncertainty in the estimates was so large as to make correlations ineffectual in predicting which covariates might influence abundance. Detection probabilities also varied among species and sometimes among years for the six species examined. We found such a high degree of variation in our counts and in estimates of detection among species, sites, and years as to cast doubt upon the appropriateness of using count data to monitor population trends using a small number of area-constrained survey plots. Still, the model provided reasonable estimates of abundance that could make it useful in estimating population size from count surveys.
Estimation of submarine mass failure probability from a sequence of deposits with age dates
Geist, Eric L.; Chaytor, Jason D.; Parsons, Thomas E.; ten Brink, Uri S.
2013-01-01
The empirical probability of submarine mass failure is quantified from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the first and after the last event. The likelihood techniques are evaluated using Akaike’s Information Criterion (AIC) and Akaike’s Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio- and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasiperiodically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.
Estimating the absolute position of a mobile robot using position probability grids
Burgard, W.; Fox, D.; Hennig, D.; Schmidt, T.
1996-12-31
In order to re-use existing models of the environment mobile robots must be able to estimate their position and orientation in such models. Most of the existing methods for position estimation are based on special purpose sensors or aim at tracking the robot`s position relative to the known starting point. This paper describes the position probability grid approach to estimating the robot`s absolute position and orientation in a metric model of the environment. Our method is designed to work with standard sensors and is independent of any knowledge about the starting point. It is a Bayesian approach based on certainty grids. In each cell of such a grid we store the probability that this cell refers to the current position of the robot. These probabilities are obtained by integrating the likelihoods of sensor readings over time. Results described in this paper show that our technique is able to reliably estimate the position of a robot in complex environments. Our approach has proven to be robust with respect to inaccurate environmental models, noisy sensors, and ambiguous situations.
Saviane, Chiara; Silver, R Angus
2006-06-15
Synapses play a crucial role in information processing in the brain. Amplitude fluctuations of synaptic responses can be used to extract information about the mechanisms underlying synaptic transmission and its modulation. In particular, multiple-probability fluctuation analysis can be used to estimate the number of functional release sites, the mean probability of release and the amplitude of the mean quantal response from fits of the relationship between the variance and mean amplitude of postsynaptic responses, recorded at different probabilities. To determine these quantal parameters, calculate their uncertainties and the goodness-of-fit of the model, it is important to weight the contribution of each data point in the fitting procedure. We therefore investigated the errors associated with measuring the variance by determining the best estimators of the variance of the variance and have used simulations of synaptic transmission to test their accuracy and reliability under different experimental conditions. For central synapses, which generally have a low number of release sites, the amplitude distribution of synaptic responses is not normal, thus the use of a theoretical variance of the variance based on the normal assumption is not a good approximation. However, appropriate estimators can be derived for the population and for limited sample sizes using a more general expression that involves higher moments and introducing unbiased estimators based on the h-statistics. Our results are likely to be relevant for various applications of fluctuation analysis when few channels or release sites are present.
Silver, R Angus
2003-12-15
Synapses are a key determinant of information processing in the central nervous system. Investigation of the mechanisms underlying synaptic transmission at central synapses is complicated by the inaccessibility of synaptic contacts and the fact that their temporal dynamics are governed by multiple parameters. Multiple-probability fluctuation analysis (MPFA) is a recently developed method for estimating quantal parameters from the variance and mean amplitude of evoked steady-state synaptic responses recorded under a range of release probability conditions. This article describes the theoretical basis and the underlying assumptions of MPFA, illustrating how a simplified multinomial model can be used to estimate mean quantal parameters at synapses where quantal size and release probability are nonuniform. Interpretations of the quantal parameter estimates are discussed in relation to uniquantal and multiquantal models of transmission. Practical aspects of this method are illustrated including a new method for estimating quantal size and variability, approaches for optimising data collection, error analysis and a method for identifying multivesicular release. The advantages and limitations of investigating synaptic function with MPFA are explored and contrasted with those for traditional quantal analysis and more recent optical quantal analysis methods.
NASA Technical Reports Server (NTRS)
Courey, Karim; Wright, Clara; Asfour, Shihab; Bayliss, Jon; Ludwig, Larry
2008-01-01
Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that has a currently unknown probability associated with it. Due to contact resistance, electrical shorts may not occur at lower voltage levels. In this experiment, we study the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From this data, we can estimate the probability of an electrical short, as a function of voltage, given that a free tin whisker has bridged two adjacent exposed electrical conductors. In addition, three tin whiskers grown from the same Space Shuttle Orbiter card guide used in the aforementioned experiment were cross sectioned and studied using a focused ion beam (FIB).
Impact of microbial count distributions on human health risk estimates.
Duarte, A S R; Nauta, M J
2015-02-16
Quantitative microbiological risk assessment (QMRA) is influenced by the choice of the probability distribution used to describe pathogen concentrations, as this may eventually have a large effect on the distribution of doses at exposure. When fitting a probability distribution to microbial enumeration data, several factors may have an impact on the accuracy of that fit. Analysis of the best statistical fits of different distributions alone does not provide a clear indication of the impact in terms of risk estimates. Thus, in this study we focus on the impact of fitting microbial distributions on risk estimates, at two different concentration scenarios and at a range of prevalence levels. By using five different parametric distributions, we investigate whether different characteristics of a good fit are crucial for an accurate risk estimate. Among the factors studied are the importance of accounting for the Poisson randomness in counts, the difference between treating "true" zeroes as such or as censored below a limit of quantification (LOQ) and the importance of making the correct assumption about the underlying distribution of concentrations. By running a simulation experiment with zero-inflated Poisson-lognormal distributed data and an existing QMRA model from retail to consumer level, it was possible to assess the difference between expected risk and the risk estimated with using a lognormal, a zero-inflated lognormal, a Poisson-gamma, a zero-inflated Poisson-gamma and a zero-inflated Poisson-lognormal distribution. We show that the impact of the choice of different probability distributions to describe concentrations at retail on risk estimates is dependent both on concentration and prevalence levels. We also show that the use of an LOQ should be done consciously, especially when zero-inflation is not used. In general, zero-inflation does not necessarily improve the absolute risk estimation, but performance of zero-inflated distributions in QMRA tends to be
Probability based remaining capacity estimation using data-driven and neural network model
NASA Astrophysics Data System (ADS)
Wang, Yujie; Yang, Duo; Zhang, Xu; Chen, Zonghai
2016-05-01
Since large numbers of lithium-ion batteries are composed in pack and the batteries are complex electrochemical devices, their monitoring and safety concerns are key issues for the applications of battery technology. An accurate estimation of battery remaining capacity is crucial for optimization of the vehicle control, preventing battery from over-charging and over-discharging and ensuring the safety during its service life. The remaining capacity estimation of a battery includes the estimation of state-of-charge (SOC) and state-of-energy (SOE). In this work, a probability based adaptive estimator is presented to obtain accurate and reliable estimation results for both SOC and SOE. For the SOC estimation, an n ordered RC equivalent circuit model is employed by combining an electrochemical model to obtain more accurate voltage prediction results. For the SOE estimation, a sliding window neural network model is proposed to investigate the relationship between the terminal voltage and the model inputs. To verify the accuracy and robustness of the proposed model and estimation algorithm, experiments under different dynamic operation current profiles are performed on the commercial 1665130-type lithium-ion batteries. The results illustrate that accurate and robust estimation can be obtained by the proposed method.
Estimating migratory connectivity of birds when re-encounter probabilities are heterogeneous
Cohen, Emily B.; Hostelter, Jeffrey A.; Royle, J. Andrew; Marra, Peter P.
2014-01-01
Understanding the biology and conducting effective conservation of migratory species requires an understanding of migratory connectivity – the geographic linkages of populations between stages of the annual cycle. Unfortunately, for most species, we are lacking such information. The North American Bird Banding Laboratory (BBL) houses an extensive database of marking, recaptures and recoveries, and such data could provide migratory connectivity information for many species. To date, however, few species have been analyzed for migratory connectivity largely because heterogeneous re-encounter probabilities make interpretation problematic. We accounted for regional variation in re-encounter probabilities by borrowing information across species and by using effort covariates on recapture and recovery probabilities in a multistate capture–recapture and recovery model. The effort covariates were derived from recaptures and recoveries of species within the same regions. We estimated the migratory connectivity for three tern species breeding in North America and over-wintering in the tropics, common (Sterna hirundo), roseate (Sterna dougallii), and Caspian terns (Hydroprogne caspia). For western breeding terns, model-derived estimates of migratory connectivity differed considerably from those derived directly from the proportions of re-encounters. Conversely, for eastern breeding terns, estimates were merely refined by the inclusion of re-encounter probabilities. In general, eastern breeding terns were strongly connected to eastern South America, and western breeding terns were strongly linked to the more western parts of the nonbreeding range under both models. Through simulation, we found this approach is likely useful for many species in the BBL database, although precision improved with higher re-encounter probabilities and stronger migratory connectivity. We describe an approach to deal with the inherent biases in BBL banding and re-encounter data to demonstrate
NASA Technical Reports Server (NTRS)
Courey, Karim; Wright, Clara; Asfour, Shihab; Onar, Arzu; Bayliss, Jon; Ludwig, Larry
2009-01-01
In this experiment, an empirical model to quantify the probability of occurrence of an electrical short circuit from tin whiskers as a function of voltage was developed. This empirical model can be used to improve existing risk simulation models. FIB and TEM images of a tin whisker confirm the rare polycrystalline structure on one of the three whiskers studied. FIB cross-section of the card guides verified that the tin finish was bright tin.
How should detection probability be incorporated into estimates of relative abundance?
MacKenzie, D.I.; Kendall, W.L.
2002-01-01
Determination of the relative abundance of two populations, separated by time or space, is of interest in many ecological situations. We focus on two estimators of relative abundance, which assume that the probability that an individual is detected at least once in the survey is either equal or unequal for the two populations. We present three methods for incorporating the collected information into our inference. The first method, proposed previously, is a traditional hypothesis test for evidence that detection probabilities are unequal. However, we feel that, a priori, it is more likely that detection probabilities are actually different; hence, the burden of proof should be shifted, requiring evidence that detection probabilities are practically equivalent. The second method we present, equivalence testing, is one approach to doing so. Third, we suggest that model averaging could be used by combining the two estimators according to derived model weights. These differing approaches are applied to a mark-recapture experiment on Nuttail's cottontail rabbit (Sylvilagus nuttallii) conducted in central Oregon during 1974 and 1975, which has been previously analyzed by other authors.
NASA Technical Reports Server (NTRS)
Courey, Karim J.; Asfour, Shihab S.; Onar, Arzu; Bayliss, Jon A.; Ludwig, Larry L.; Wright, Maria C.
2009-01-01
To comply with lead-free legislation, many manufacturers have converted from tin-lead to pure tin finishes of electronic components. However, pure tin finishes have a greater propensity to grow tin whiskers than tin-lead finishes. Since tin whiskers present an electrical short circuit hazard in electronic components, simulations have been developed to quantify the risk of said short circuits occurring. Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that had an unknown probability associated with it. Note however that due to contact resistance electrical shorts may not occur at lower voltage levels. In our first article we developed an empirical probability model for tin whisker shorting. In this paper, we develop a more comprehensive empirical model using a refined experiment with a larger sample size, in which we studied the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From the resulting data we estimated the probability distribution of an electrical short, as a function of voltage. In addition, the unexpected polycrystalline structure seen in the focused ion beam (FIB) cross section in the first experiment was confirmed in this experiment using transmission electron microscopy (TEM). The FIB was also used to cross section two card guides to facilitate the measurement of the grain size of each card guide's tin plating to determine its finish.
A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities
McClintock, B.T.; White, Gary C.; Burnham, K.P.
2006-01-01
This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden's estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AICc model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AICc model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation. ?? 2006 American Statistical Association and the International Biometric Society.
Kendall, W.L.; Nichols, J.D.
2002-01-01
Temporary emigration was identified some time ago as causing potential problems in capture-recapture studies, and in the last five years approaches have been developed for dealing with special cases of this general problem. Temporary emigration can be viewed more generally as involving transitions to and from an unobservable state, and frequently the state itself is one of biological interest (e.g., 'nonbreeder'). Development of models that permit estimation of relevant parameters in the presence of an unobservable state requires either extra information (e.g., as supplied by Pollock's robust design) or the following classes of model constraints: reducing the order of Markovian transition probabilities, imposing a degree of determinism on transition probabilities, removing state specificity of survival probabilities, and imposing temporal constancy of parameters. The objective of the work described in this paper is to investigate estimability of model parameters under a variety of models that include an unobservable state. Beginning with a very general model and no extra information, we used numerical methods to systematically investigate the use of ancillary information and constraints to yield models that are useful for estimation. The result is a catalog of models for which estimation is possible. An example analysis of sea turtle capture-recapture data under two different models showed similar point estimates but increased precision for the model that incorporated ancillary data (the robust design) when compared to the model with deterministic transitions only. This comparison and the results of our numerical investigation of model structures lead to design suggestions for capture-recapture studies in the presence of an unobservable state.
NASA Astrophysics Data System (ADS)
Barengoltz, Jack
2016-07-01
Monte Carlo (MC) is a common method to estimate probability, effectively by a simulation. For planetary protection, it may be used to estimate the probability of impact P{}_{I} by a launch vehicle (upper stage) of a protected planet. The object of the analysis is to provide a value for P{}_{I} with a given level of confidence (LOC) that the true value does not exceed the maximum allowed value of P{}_{I}. In order to determine the number of MC histories required, one must also guess the maximum number of hits that will occur in the analysis. This extra parameter is needed because a LOC is desired. If more hits occur, the MC analysis would indicate that the true value may exceed the specification value with a higher probability than the LOC. (In the worst case, even the mean value of the estimated P{}_{I} might exceed the specification value.) After the analysis is conducted, the actual number of hits is, of course, the mean. The number of hits arises from a small probability per history and a large number of histories; these are the classic requirements for a Poisson distribution. For a known Poisson distribution (the mean is the only parameter), the probability for some interval in the number of hits is calculable. Before the analysis, this is not possible. Fortunately, there are methods that can bound the unknown mean for a Poisson distribution. F. Garwoodfootnote{ F. Garwood (1936), ``Fiduciary limits for the Poisson distribution.'' Biometrika 28, 437-442.} published an appropriate method that uses the Chi-squared function, actually its inversefootnote{ The integral chi-squared function would yield probability α as a function of the mean µ and an actual value n.} (despite the notation used): This formula for the upper and lower limits of the mean μ with the two-tailed probability 1-α depends on the LOC α and an estimated value of the number of "successes" n. In a MC analysis for planetary protection, only the upper limit is of interest, i.e., the single
NASA Technical Reports Server (NTRS)
Edmonds, L. D.
2016-01-01
Because advancing technology has been producing smaller structures in electronic circuits, the floating gates in modern flash memories are becoming susceptible to prompt charge loss from ionizing radiation environments found in space. A method for estimating the risk of a charge-loss event is given.
NASA Technical Reports Server (NTRS)
Edmonds, L. D.
2016-01-01
Since advancing technology has been producing smaller structures in electronic circuits, the floating gates in modern flash memories are becoming susceptible to prompt charge loss from ionizing radiation environments found in space. A method for estimating the risk of a charge-loss event is given.
NASA Astrophysics Data System (ADS)
Lee, T. S.; Yoon, S.; Jeong, C.
2012-12-01
The primary purpose of frequency analysis in hydrology is to estimate the magnitude of an event with a given frequency of occurrence. The precision of frequency analysis depends on the selection of an appropriate probability distribution model (PDM) and parameter estimation techniques. A number of PDMs have been developed to describe the probability distribution of the hydrological variables. For each of the developed PDMs, estimated parameters are provided based on alternative estimation techniques, such as the method of moments (MOM), probability weighted moments (PWM), linear function of ranked observations (L-moments), and maximum likelihood (ML). Generally, the results using ML are more reliable than the other methods. However, the ML technique is more laborious than the other methods because an iterative numerical solution, such as the Newton-Raphson method, must be used for the parameter estimation of PDMs. In the meantime, meta-heuristic approaches have been developed to solve various engineering optimization problems (e.g., linear and stochastic, dynamic, nonlinear). These approaches include genetic algorithms, ant colony optimization, simulated annealing, tabu searches, and evolutionary computation methods. Meta-heuristic approaches use a stochastic random search instead of a gradient search so that intricate derivative information is unnecessary. Therefore, the meta-heuristic approaches have been shown to be a useful strategy to solve optimization problems in hydrology. A number of studies focus on using meta-heuristic approaches for estimation of hydrological variables with parameter estimation of PDMs. Applied meta-heuristic approaches offer reliable solutions but use more computation time than derivative-based methods. Therefore, the purpose of this study is to enhance the meta-heuristic approach for the parameter estimation of PDMs by using a recently developed algorithm known as a harmony search (HS). The performance of the HS is compared to the
NASA Astrophysics Data System (ADS)
Eleftheriadou, Anastasia K.; Baltzopoulou, Aikaterini D.; Karabinis, Athanasios I.
2016-06-01
The current seismic risk assessment is based on two discrete approaches, actual and probable, validating afterwards the produced results. In the first part of this research, the seismic risk is evaluated from the available data regarding the mean statistical repair/strengthening or replacement cost for the total number of damaged structures (180,427 buildings) after the 7/9/1999 Parnitha (Athens) earthquake. The actual evaluated seismic risk is afterwards compared to the estimated probable structural losses, which is presented in the second part of the paper, based on a damage scenario in the referring earthquake. The applied damage scenario is based on recently developed damage probability matrices (DPMs) from Athens (Greece) damage database. The seismic risk estimation refers to 750,085 buildings situated in the extended urban region of Athens. The building exposure is categorized in five typical structural types and represents 18.80 % of the entire building stock in Greece. The last information is provided by the National Statistics Service of Greece (NSSG) according to the 2000-2001 census. The seismic input is characterized by the ratio, a g/ a o, where a g is the regional peak ground acceleration (PGA) which is evaluated from the earlier estimated research macroseismic intensities, and a o is the PGA according to the hazard map of the 2003 Greek Seismic Code. Finally, the collected investigated financial data derived from different National Services responsible for the post-earthquake crisis management concerning the repair/strengthening or replacement costs or other categories of costs for the rehabilitation of earthquake victims (construction and function of settlements for earthquake homeless, rent supports, demolitions, shorings) are used to determine the final total seismic risk factor.
An estimate of the probability of capture of a binary star by a supermassive black hole
NASA Astrophysics Data System (ADS)
Dremova, G. N.; Dremov, V. V.; Tutukov, A. V.
2016-08-01
A simple model for the dynamics of stars located in a sphere with a radius of one-tenth of the central parsec, designed to enable estimation of the probability of capture in the close vicinity ( r < 10-3 pc) of a supermassive black hole (SMBH) is presented. In the case of binary stars, such a capture with a high probability results in the formation of a hyper-velocity star. The population of stars in a sphere of radius <0.1 pc is calculated based on data for the Galactic rotation curve. To simulate the distortion of initially circular orbits of stars, these are subjected to a series of random shock encounters ("kicks"), whose net effect is to "push" these binary systems into the region of potential formation of hyper-velocity stars. The mean crossing time of the border of the close vicinity of the SMBH ( r < 10-3 pc) by the stellar orbit can be used to estimate the probability that a binary system is captured, followed by the possible ejection of a hyper-velocity star.
Geissler, P.H.; Moyer, L.M.
1983-01-01
Four sampling and estimation methods for estimating the number of red-cockaded woodpecker colonies on National Forests in the Southeast were compared, using samples chosen from simulated populations based on the observed sample. The methods included (1) simple random sampling without replacement using a mean per sampling unit estimator, (2) simple random sampling without replacement with a ratio per pine area estimator, (3) probability proportional to 'size' sampling with replacement, and (4) probability proportional to 'size' without replacement using Murthy's estimator. The survey sample of 274 National Forest compartments (1000 acres each) constituted a superpopulation from which simulated stratum populations were selected with probability inversely proportional to the original probability of selection. Compartments were originally sampled with probabilities proportional to the probabilities that the compartments contained woodpeckers ('size'). These probabilities were estimated with a discriminant analysis based on tree species and tree age. The ratio estimator would have been the best estimator for this survey based on the mean square error. However, if more accurate predictions of woodpecker presence had been available, Murthy's estimator would have been the best. A subroutine to calculate Murthy's estimates is included; it is computationally feasible to analyze up to 10 samples per stratum.
Estimating survival and breeding probability for pond-breeding amphibians: a modified robust design
Bailey, L.L.; Kendall, W.L.; Church, D.R.; Wilbur, H.M.
2004-01-01
Many studies of pond-breeding amphibians involve sampling individuals during migration to and from breeding habitats. Interpreting population processes and dynamics from these studies is difficult because (1) only a proportion of the population is observable each season, while an unknown proportion remains unobservable (e.g., non-breeding adults) and (2) not all observable animals are captured. Imperfect capture probability can be easily accommodated in capture?recapture models, but temporary transitions between observable and unobservable states, often referred to as temporary emigration, is known to cause problems in both open- and closed-population models. We develop a multistate mark?recapture (MSMR) model, using an open-robust design that permits one entry and one exit from the study area per season. Our method extends previous temporary emigration models (MSMR with an unobservable state) in two ways. First, we relax the assumption of demographic closure (no mortality) between consecutive (secondary) samples, allowing estimation of within-pond survival. Also, we add the flexibility to express survival probability of unobservable individuals (e.g., ?non-breeders?) as a function of the survival probability of observable animals while in the same, terrestrial habitat. This allows for potentially different annual survival probabilities for observable and unobservable animals. We apply our model to a relictual population of eastern tiger salamanders (Ambystoma tigrinum tigrinum). Despite small sample sizes, demographic parameters were estimated with reasonable precision. We tested several a priori biological hypotheses and found evidence for seasonal differences in pond survival. Our methods could be applied to a variety of pond-breeding species and other taxa where individuals are captured entering or exiting a common area (e.g., spawning or roosting area, hibernacula).
Modeling and estimation of stage-specific daily survival probabilities of nests
Stanley, T.R.
2000-01-01
In studies of avian nesting success, it is often of interest to estimate stage-specific daily survival probabilities of nests. When data can be partitioned by nesting stage (e.g., incubation stage, nestling stage), piecewise application of the Mayfield method or Johnsona??s method is appropriate. However, when the data contain nests where the transition from one stage to the next occurred during the interval between visits, piecewise approaches are inappropriate. In this paper, I present a model that allows joint estimation of stage-specific daily survival probabilities even when the time of transition between stages is unknown. The model allows interval lengths between visits to nests to vary, and the exact time of failure of nests does not need to be known. The performance of the model at various sample sizes and interval lengths between visits was investigated using Monte Carlo simulations, and it was found that the model performed quite well: bias was small and confidence-interval coverage was at the nominal 95% rate. A SAS program for obtaining maximum likelihood estimates of parameters, and their standard errors, is provided in the Appendix.
Estimating superpopulation size and annual probability of breeding for pond-breeding salamanders
Kinkead, K.E.; Otis, D.L.
2007-01-01
It has long been accepted that amphibians can skip breeding in any given year, and environmental conditions act as a cue for breeding. In this paper, we quantify temporary emigration or nonbreeding probability for mole and spotted salamanders (Ambystoma talpoideum and A. maculatum). We estimated that 70% of mole salamanders may skip breeding during an average rainfall year and 90% may skip during a drought year. Spotted salamanders may be more likely to breed, with only 17% avoiding the breeding pond during an average rainfall year. We illustrate how superpopulations can be estimated using temporary emigration probability estimates. The superpopulation is the total number of salamanders associated with a given breeding pond. Although most salamanders stay within a certain distance of a breeding pond for the majority of their life spans, it is difficult to determine true overall population sizes for a given site if animals are only captured during a brief time frame each year with some animals unavailable for capture at any time during a given year. ?? 2007 by The Herpetologists' League, Inc.
Olson, Scott A.; Brouillette, Michael C.
2006-01-01
A logistic regression equation was developed for estimating the probability of a stream flowing intermittently at unregulated, rural stream sites in Vermont. These determinations can be used for a wide variety of regulatory and planning efforts at the Federal, State, regional, county and town levels, including such applications as assessing fish and wildlife habitats, wetlands classifications, recreational opportunities, water-supply potential, waste-assimilation capacities, and sediment transport. The equation will be used to create a derived product for the Vermont Hydrography Dataset having the streamflow characteristic of 'intermittent' or 'perennial.' The Vermont Hydrography Dataset is Vermont's implementation of the National Hydrography Dataset and was created at a scale of 1:5,000 based on statewide digital orthophotos. The equation was developed by relating field-verified perennial or intermittent status of a stream site during normal summer low-streamflow conditions in the summer of 2005 to selected basin characteristics of naturally flowing streams in Vermont. The database used to develop the equation included 682 stream sites with drainage areas ranging from 0.05 to 5.0 square miles. When the 682 sites were observed, 126 were intermittent (had no flow at the time of the observation) and 556 were perennial (had flowing water at the time of the observation). The results of the logistic regression analysis indicate that the probability of a stream having intermittent flow in Vermont is a function of drainage area, elevation of the site, the ratio of basin relief to basin perimeter, and the areal percentage of well- and moderately well-drained soils in the basin. Using a probability cutpoint (a lower probability indicates the site has perennial flow and a higher probability indicates the site has intermittent flow) of 0.5, the logistic regression equation correctly predicted the perennial or intermittent status of 116 test sites 85 percent of the time.
Estimated probability of arsenic in groundwater from bedrock aquifers in New Hampshire, 2011
Ayotte, Joseph D.; Cahillane, Matthew; Hayes, Laura; Robinson, Keith W.
2012-01-01
The statewide maps generated by the probability models are not designed to predict arsenic concentration in any single well, but they are expected to provide useful information in areas of the State that currently contain little to no data on arsenic concentration. They also may aid in resource decision making, in determining potential risk for private wells, and in ecological-level analysis of disease outcomes. The approach for modeling arsenic in groundwater could also be applied to other environmental contaminants that have potential implications for human health, such as uranium, radon, fluoride, manganese, volatile organic compounds, nitrate, and bacteria.
On the method of logarithmic cumulants for parametric probability density function estimation.
Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane
2013-10-01
Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible.
On the method of logarithmic cumulants for parametric probability density function estimation.
Krylov, Vladimir A; Moser, Gabriele; Serpico, Sebastiano B; Zerubia, Josiane
2013-10-01
Parameter estimation of probability density functions is one of the major steps in the area of statistical image and signal processing. In this paper we explore several properties and limitations of the recently proposed method of logarithmic cumulants (MoLC) parameter estimation approach which is an alternative to the classical maximum likelihood (ML) and method of moments (MoM) approaches. We derive the general sufficient condition for a strong consistency of the MoLC estimates which represents an important asymptotic property of any statistical estimator. This result enables the demonstration of the strong consistency of MoLC estimates for a selection of widely used distribution families originating from (but not restricted to) synthetic aperture radar image processing. We then derive the analytical conditions of applicability of MoLC to samples for the distribution families in our selection. Finally, we conduct various synthetic and real data experiments to assess the comparative properties, applicability and small sample performance of MoLC notably for the generalized gamma and K families of distributions. Supervised image classification experiments are considered for medical ultrasound and remote-sensing SAR imagery. The obtained results suggest that MoLC is a feasible and computationally fast yet not universally applicable alternative to MoM. MoLC becomes especially useful when the direct ML approach turns out to be unfeasible. PMID:23799694
Estimated Probability of a Cervical Spine Injury During an ISS Mission
NASA Technical Reports Server (NTRS)
Brooker, John E.; Weaver, Aaron S.; Myers, Jerry G.
2013-01-01
Introduction: The Integrated Medical Model (IMM) utilizes historical data, cohort data, and external simulations as input factors to provide estimates of crew health, resource utilization and mission outcomes. The Cervical Spine Injury Module (CSIM) is an external simulation designed to provide the IMM with parameter estimates for 1) a probability distribution function (PDF) of the incidence rate, 2) the mean incidence rate, and 3) the standard deviation associated with the mean resulting from injury/trauma of the neck. Methods: An injury mechanism based on an idealized low-velocity blunt impact to the superior posterior thorax of an ISS crewmember was used as the simulated mission environment. As a result of this impact, the cervical spine is inertially loaded from the mass of the head producing an extension-flexion motion deforming the soft tissues of the neck. A multibody biomechanical model was developed to estimate the kinematic and dynamic response of the head-neck system from a prescribed acceleration profile. Logistic regression was performed on a dataset containing AIS1 soft tissue neck injuries from rear-end automobile collisions with published Neck Injury Criterion values producing an injury transfer function (ITF). An injury event scenario (IES) was constructed such that crew 1 is moving through a primary or standard translation path transferring large volume equipment impacting stationary crew 2. The incidence rate for this IES was estimated from in-flight data and used to calculate the probability of occurrence. The uncertainty in the model input factors were estimated from representative datasets and expressed in terms of probability distributions. A Monte Carlo Method utilizing simple random sampling was employed to propagate both aleatory and epistemic uncertain factors. Scatterplots and partial correlation coefficients (PCC) were generated to determine input factor sensitivity. CSIM was developed in the SimMechanics/Simulink environment with a
NASA Astrophysics Data System (ADS)
Kim, Kyu Rang; Kim, Mijin; Choe, Ho-Seong; Han, Mae Ja; Lee, Hye-Rim; Oh, Jae-Won; Kim, Baek-Jo
2016-07-01
Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.
Crowe, D.E.; Longshore, K.M.
2010-01-01
We estimated relative abundance and density of Western Burrowing Owls (Athene cunicularia hypugaea) at two sites in the Mojave Desert (200304). We made modifications to previously established Burrowing Owl survey techniques for use in desert shrublands and evaluated several factors that might influence the detection of owls. We tested the effectiveness of the call-broadcast technique for surveying this species, the efficiency of this technique at early and late breeding stages, and the effectiveness of various numbers of vocalization intervals during broadcasting sessions. Only 1 (3) of 31 initial (new) owl responses was detected during passive-listening sessions. We found that surveying early in the nesting season was more likely to produce new owl detections compared to surveying later in the nesting season. New owls detected during each of the three vocalization intervals (each consisting of 30 sec of vocalizations followed by 30 sec of silence) of our broadcasting session were similar (37, 40, and 23; n 30). We used a combination of detection trials (sighting probability) and double-observer method to estimate the components of detection probability, i.e., availability and perception. Availability for all sites and years, as determined by detection trials, ranged from 46.158.2. Relative abundance, measured as frequency of occurrence and defined as the proportion of surveys with at least one owl, ranged from 19.232.0 for both sites and years. Density at our eastern Mojave Desert site was estimated at 0.09 ?? 0.01 (SE) owl territories/km2 and 0.16 ?? 0.02 (SE) owl territories/km2 during 2003 and 2004, respectively. In our southern Mojave Desert site, density estimates were 0.09 ?? 0.02 (SE) owl territories/km2 and 0.08 ?? 0.02 (SE) owl territories/km 2 during 2004 and 2005, respectively. ?? 2010 The Raptor Research Foundation, Inc.
Lahodny, G E; Gautam, R; Ivanek, R
2015-01-01
Indirect transmission through the environment, pathogen shedding by infectious hosts, replication of free-living pathogens within the environment, and environmental decontamination are suspected to play important roles in the spread and control of environmentally transmitted infectious diseases. To account for these factors, the classic Susceptible-Infectious-Recovered-Susceptible epidemic model is modified to include a compartment representing the amount of free-living pathogen within the environment. The model accounts for host demography, direct and indirect transmission, replication of free-living pathogens in the environment, and removal of free-living pathogens by natural death or environmental decontamination. Based on the assumptions of the deterministic model, a continuous-time Markov chain model is developed. An estimate for the probability of disease extinction or a major outbreak is obtained by approximating the Markov chain with a multitype branching process. Numerical simulations illustrate important differences between the deterministic and stochastic counterparts, relevant for outbreak prevention, that depend on indirect transmission, pathogen shedding by infectious hosts, replication of free-living pathogens, and environmental decontamination. The probability of a major outbreak is computed for salmonellosis in a herd of dairy cattle as well as cholera in a human population. An explicit expression for the probability of disease extinction or a major outbreak in terms of the model parameters is obtained for systems with no direct transmission or replication of free-living pathogens. PMID:25198247
Estimation of (n,f) Cross-Sections by Measuring Reaction Probability Ratios
Plettner, C; Ai, H; Beausang, C W; Bernstein, L A; Ahle, L; Amro, H; Babilon, M; Burke, J T; Caggiano, J A; Casten, R F; Church, J A; Cooper, J R; Crider, B; Gurdal, G; Heinz, A; McCutchan, E A; Moody, K; Punyon, J A; Qian, J; Ressler, J J; Schiller, A; Williams, E; Younes, W
2005-04-21
Neutron-induced reaction cross-sections on unstable nuclei are inherently difficult to measure due to target activity and the low intensity of neutron beams. In an alternative approach, named the 'surrogate' technique, one measures the decay probability of the same compound nucleus produced using a stable beam on a stable target to estimate the neutron-induced reaction cross-section. As an extension of the surrogate method, in this paper they introduce a new technique of measuring the fission probabilities of two different compound nuclei as a ratio, which has the advantage of removing most of the systematic uncertainties. This method was benchmarked in this report by measuring the probability of deuteron-induced fission events in coincidence with protons, and forming the ratio P({sup 236}U(d,pf))/P({sup 238}U(d,pf)), which serves as a surrogate for the known cross-section ratio of {sup 236}U(n,f)/{sup 238}U(n,f). IN addition, the P({sup 238}U(d,d{prime}f))/P({sup 236}U(d,d{prime}f)) ratio as a surrogate for the {sup 237}U(n,f)/{sup 235}U(n,f) cross-section ratio was measured for the first time in an unprecedented range of excitation energies.
Toward 3D-guided prostate biopsy target optimization: an estimation of tumor sampling probabilities
NASA Astrophysics Data System (ADS)
Martin, Peter R.; Cool, Derek W.; Romagnoli, Cesare; Fenster, Aaron; Ward, Aaron D.
2014-03-01
Magnetic resonance imaging (MRI)-targeted, 3D transrectal ultrasound (TRUS)-guided "fusion" prostate biopsy aims to reduce the ~23% false negative rate of clinical 2D TRUS-guided sextant biopsy. Although it has been reported to double the positive yield, MRI-targeted biopsy still yields false negatives. Therefore, we propose optimization of biopsy targeting to meet the clinician's desired tumor sampling probability, optimizing needle targets within each tumor and accounting for uncertainties due to guidance system errors, image registration errors, and irregular tumor shapes. We obtained multiparametric MRI and 3D TRUS images from 49 patients. A radiologist and radiology resident contoured 81 suspicious regions, yielding 3D surfaces that were registered to 3D TRUS. We estimated the probability, P, of obtaining a tumor sample with a single biopsy. Given an RMS needle delivery error of 3.5 mm for a contemporary fusion biopsy system, P >= 95% for 21 out of 81 tumors when the point of optimal sampling probability was targeted. Therefore, more than one biopsy core must be taken from 74% of the tumors to achieve P >= 95% for a biopsy system with an error of 3.5 mm. Our experiments indicated that the effect of error along the needle axis on the percentage of core involvement (and thus the measured tumor burden) was mitigated by the 18 mm core length.
Development of a statistical tool for the estimation of riverbank erosion probability
NASA Astrophysics Data System (ADS)
Varouchakis, Emmanouil
2016-04-01
Riverbank erosion affects river morphology and local habitat, and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict areas vulnerable to erosion is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a innovative statistical methodology is proposed to predict the probability of presence or absence of erosion in a river section. A physically based model determines the locations vulnerable to erosion by quantifying the potential eroded area. The derived results are used to determine validation locations for the evaluation of the statistical tool performance. The statistical tool is based on a series of independent local variables and employs the Logistic Regression methodology. It is developed in two forms, Logistic Regression and Locally Weighted Logistic Regression, which both deliver useful and accurate results. The second form though, provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed tool is easy to use, accurate and can be applied to any region and river. Varouchakis, E. A., Giannakis, G. V., Lilli, M. A., Ioannidou, E., Nikolaidis, N. P., and Karatzas, G. P.: Development of a statistical tool for the estimation of riverbank erosion probability, SOIL (EGU), in print, 2016.
Inconsistent probability estimates of a hypothesis: the role of contrasting support.
Bonini, Nicolao; Gonzalez, Michel
2005-01-01
This paper studies consistency in the judged probability of a target hypothesis in lists of mutually exclusive nonexhaustive hypotheses. Specifically, it controls the role played by the support of displayed competing hypotheses and the relatedness between the target hypothesis and its alternatives. Three experiments are reported. In all experiments, groups of people were presented with a list of mutually exclusive nonexhaustive causes of a person's death. In the first two experiments, they were asked to judge the probability of each cause as that of the person's decease. In the third experiment, people were asked for a frequency estimation task. Target causes were presented in all lists. Several other alternative causes to the target ones differed across the lists. Findings show that the judged probability/frequency of a target cause changes as a function of the support of the displayed competing causes. Specifically, it is higher when its competing displayed causes have low rather than high support. Findings are consistent with the contrastive support hypothesis within the support theory. PMID:15779531
How to estimate your tolerance for risk
Mackay, J.A.
1996-12-31
Risk tolerance is used to calculate the Risk Adjusted Value (RAV) of a proposed investment. The RAV incorporates both the expected value and risk attitude for a particular investment, taking into consideration your concern for catastrophic financial loss, as well as chance of success, cost and value if successful. Uncertainty can be incorporated into all of the above variables. Often a project is more valuable to a corporation if a partial working interest is taken rather than the entire working interest. The RAV can be used to calculate the optimum working interest and the value of that diversification. To estimate the Apparent Risk Tolerance (ART) of an individual, division or corporation several methods can be employed: (1) ART can be calculated from the working interest selected in prior investment decisions. (2) ART can be estimated from a selection of working interests by the decision maker in a proposed portfolio of projects. (3) ART can be approximated from data released to the Security and Exchange Commission (SEC) in the annual 10K supplements (for both your company and possible partners). (4) ART can be assigned based on corporate size, budget, or activity. Examples are provided for the various methods to identify risk tolerance and apply it in making optimum working interest calculations for individual projects and portfolios.
Risk Estimation Methodology for Launch Accidents.
Clayton, Daniel James; Lipinski, Ronald J.; Bechtel, Ryan D.
2014-02-01
As compact and light weight power sources with reliable, long lives, Radioisotope Power Systems (RPSs) have made space missions to explore the solar system possible. Due to the hazardous material that can be released during a launch accident, the potential health risk of an accident must be quantified, so that appropriate launch approval decisions can be made. One part of the risk estimation involves modeling the response of the RPS to potential accident environments. Due to the complexity of modeling the full RPS response deterministically on dynamic variables, the evaluation is performed in a stochastic manner with a Monte Carlo simulation. The potential consequences can be determined by modeling the transport of the hazardous material in the environment and in human biological pathways. The consequence analysis results are summed and weighted by appropriate likelihood values to give a collection of probabilistic results for the estimation of the potential health risk. This information is used to guide RPS designs, spacecraft designs, mission architecture, or launch procedures to potentially reduce the risk, as well as to inform decision makers of the potential health risks resulting from the use of RPSs for space missions.
Tillery, Anne C.; Matherne, Anne Marie; Verdin, Kristine L.
2012-01-01
In May and June 2012, the Whitewater-Baldy Fire burned approximately 1,200 square kilometers (300,000 acres) of the Gila National Forest, in southwestern New Mexico. The burned landscape is now at risk of damage from postwildfire erosion, such as that caused by debris flows and flash floods. This report presents a preliminary hazard assessment of the debris-flow potential from 128 basins burned by the Whitewater-Baldy Fire. A pair of empirical hazard-assessment models developed by using data from recently burned basins throughout the intermountain Western United States was used to estimate the probability of debris-flow occurrence and volume of debris flows along the burned area drainage network and for selected drainage basins within the burned area. The models incorporate measures of areal burned extent and severity, topography, soils, and storm rainfall intensity to estimate the probability and volume of debris flows following the fire. In response to the 2-year-recurrence, 30-minute-duration rainfall, modeling indicated that four basins have high probabilities of debris-flow occurrence (greater than or equal to 80 percent). For the 10-year-recurrence, 30-minute-duration rainfall, an additional 14 basins are included, and for the 25-year-recurrence, 30-minute-duration rainfall, an additional eight basins, 20 percent of the total, have high probabilities of debris-flow occurrence. In addition, probability analysis along the stream segments can identify specific reaches of greatest concern for debris flows within a basin. Basins with a high probability of debris-flow occurrence were concentrated in the west and central parts of the burned area, including tributaries to Whitewater Creek, Mineral Creek, and Willow Creek. Estimated debris-flow volumes ranged from about 3,000-4,000 cubic meters (m3) to greater than 500,000 m3 for all design storms modeled. Drainage basins with estimated volumes greater than 500,000 m3 included tributaries to Whitewater Creek, Willow
Fast and accurate probability density estimation in large high dimensional astronomical datasets
NASA Astrophysics Data System (ADS)
Gupta, Pramod; Connolly, Andrew J.; Gardner, Jeffrey P.
2015-01-01
Astronomical surveys will generate measurements of hundreds of attributes (e.g. color, size, shape) on hundreds of millions of sources. Analyzing these large, high dimensional data sets will require efficient algorithms for data analysis. An example of this is probability density estimation that is at the heart of many classification problems such as the separation of stars and quasars based on their colors. Popular density estimation techniques use binning or kernel density estimation. Kernel density estimation has a small memory footprint but often requires large computational resources. Binning has small computational requirements but usually binning is implemented with multi-dimensional arrays which leads to memory requirements which scale exponentially with the number of dimensions. Hence both techniques do not scale well to large data sets in high dimensions. We present an alternative approach of binning implemented with hash tables (BASH tables). This approach uses the sparseness of data in the high dimensional space to ensure that the memory requirements are small. However hashing requires some extra computation so a priori it is not clear if the reduction in memory requirements will lead to increased computational requirements. Through an implementation of BASH tables in C++ we show that the additional computational requirements of hashing are negligible. Hence this approach has small memory and computational requirements. We apply our density estimation technique to photometric selection of quasars using non-parametric Bayesian classification and show that the accuracy of the classification is same as the accuracy of earlier approaches. Since the BASH table approach is one to three orders of magnitude faster than the earlier approaches it may be useful in various other applications of density estimation in astrostatistics.
A simple derivation of risk-neutral probability in the binomial option pricing model
NASA Astrophysics Data System (ADS)
Orosi, Greg
2015-01-01
The traditional derivation of risk-neutral probability in the binomial option pricing framework used in introductory mathematical finance courses is straightforward, but employs several different concepts and is is not algebraically simple. In order to overcome this drawback of the standard approach, we provide an alternative derivation.
Estimation of upper bound probabilities for rare events resulting from nearby explosions
Luck, L.B.
1998-09-19
It is sometimes necessary to deploy, transport and store weapons containing high explosives (HE) in proximity. Accident analyses of these activities may include nearby explosion scenarios in which fragments from an exploding (donor) weapon impact a second (acceptor) weapon. Weapon arrays are designed to miti- gate consequences to potential acceptor weapons, but unless initiation of an accep- tor's HE is impossible, outcomes such as detonation must be considered. This paper describes an approach for estimating upper bound probabilities for fragment- dominated scenarios in which outcomes are expected to be rare events. Other aspectsl,z of nearby explosion problems were addressed previously. An example scenario is as follows. A donor weapon is postulated to detonate, and fragments of the donor weapon casing are accelerated outward. Some of the fragments may strike a nearby acceptor weapon whose HE is protected by casing materials. Most impacts are not capable of initiating the acceptor's HE. However, a sufficiently large and fast fragment could produce a shock-to-detonation transi- tion (SDT), which will result in detonation of the acceptor. Our approach will work for other outcomes of fragment impact, but this discussion focuses on detonation. Experiments show that detonating weapons typically produce a distribution of casing fragment sizes in which unusually large figments sometimes occur. Such fragments can occur because fragmentation physics includes predictable aspects as well as those best treated as random phenomena, such as the sizes of individual fragments. Likewise, some of the descriptors of fragment impact can be described as random phenomen% such as fragment orientation at impact (fragments typically are tumbling). Consideration of possibilities resulting from the various manifesta- tions of randomness can lead to worst-case examples tha~ in turn, lead to the out- comes of concern. For example, an unusually large fragment strikes an acceptor weapon with
Estimating Non-stationary Flood Risk in a Changing Climate
NASA Astrophysics Data System (ADS)
Yu, X.; Cohn, T. A.; Stedinger, J. R.
2015-12-01
Flood risk is usually described by a probability distribution for annual maximum streamflow which is assumed not to change with time. Federal, state and local governments in the United States are demanding guidance on flood frequency estimates that account for climate change. If a trend exists in peak flow series, ignoring it could result in large quantile estimator bias, while trying to estimate a trend will increase the flood quantile estimator's variance. Thus the issue is, what bias-variance tradeoff should we accept? This paper discusses approaches to flood frequency analysis (FFA) when flood series have trends. GCMs describe how annual runoff might vary over sub-continental scales, but this information is nearly useless for FFA in small watersheds. A LP3 Monte Carlo analysis and a re-sampling study of 100-year flood estimation (25- and 50-year projections) compares the performance of five methods: FFA as prescribed in national guidelines (Bulletin 17B), assumes the flood series is stationary and follows a log-Pearson type III (LP3) distribution; Fitting a LP3 distribution with time-varying parameters that include future trends in mean and perhaps variance, where slopes are assumed known; Fitting a LP3 distribution with time-varying parameters that capture future trends in mean and perhaps variance, where slopes are estimated from annual peak flow series; Employing only the most recent 30 years of flood records to fit a LP3 distribution; Applying a safety factor to the 100-year flood estimator (e.g. 25% increase). The 100-year flood estimator of method 2 has the smallest log-space mean squared error, though it is unlikely that the true trend would be known. Method 3 is only recommended over method 1 for large trends (≥ 0.5% per year). The 100-year flood estimators of method 1, 4, and 5 often have poor accuracy. Clearly, flood risk assessment will be a challenge in an uncertain world.
A methodology for estimating risks associated with landslides of contaminated soil into rivers.
Göransson, Gunnel; Norrman, Jenny; Larson, Magnus; Alén, Claes; Rosén, Lars
2014-02-15
Urban areas adjacent to surface water are exposed to soil movements such as erosion and slope failures (landslides). A landslide is a potential mechanism for mobilisation and spreading of pollutants. This mechanism is in general not included in environmental risk assessments for contaminated sites, and the consequences associated with contamination in the soil are typically not considered in landslide risk assessments. This study suggests a methodology to estimate the environmental risks associated with landslides in contaminated sites adjacent to rivers. The methodology is probabilistic and allows for datasets with large uncertainties and the use of expert judgements, providing quantitative estimates of probabilities for defined failures. The approach is illustrated by a case study along the river Göta Älv, Sweden, where failures are defined and probabilities for those failures are estimated. Failures are defined from a pollution perspective and in terms of exceeding environmental quality standards (EQSs) and acceptable contaminant loads. Models are then suggested to estimate probabilities of these failures. A landslide analysis is carried out to assess landslide probabilities based on data from a recent landslide risk classification study along the river Göta Älv. The suggested methodology is meant to be a supplement to either landslide risk assessment (LRA) or environmental risk assessment (ERA), providing quantitative estimates of the risks associated with landslide in contaminated sites. The proposed methodology can also act as a basis for communication and discussion, thereby contributing to intersectoral management solutions. From the case study it was found that the defined failures are governed primarily by the probability of a landslide occurring. The overall probabilities for failure are low; however, if a landslide occurs the probabilities of exceeding EQS are high and the probability of having at least a 10% increase in the contamination load
A methodology for estimating risks associated with landslides of contaminated soil into rivers.
Göransson, Gunnel; Norrman, Jenny; Larson, Magnus; Alén, Claes; Rosén, Lars
2014-02-15
Urban areas adjacent to surface water are exposed to soil movements such as erosion and slope failures (landslides). A landslide is a potential mechanism for mobilisation and spreading of pollutants. This mechanism is in general not included in environmental risk assessments for contaminated sites, and the consequences associated with contamination in the soil are typically not considered in landslide risk assessments. This study suggests a methodology to estimate the environmental risks associated with landslides in contaminated sites adjacent to rivers. The methodology is probabilistic and allows for datasets with large uncertainties and the use of expert judgements, providing quantitative estimates of probabilities for defined failures. The approach is illustrated by a case study along the river Göta Älv, Sweden, where failures are defined and probabilities for those failures are estimated. Failures are defined from a pollution perspective and in terms of exceeding environmental quality standards (EQSs) and acceptable contaminant loads. Models are then suggested to estimate probabilities of these failures. A landslide analysis is carried out to assess landslide probabilities based on data from a recent landslide risk classification study along the river Göta Älv. The suggested methodology is meant to be a supplement to either landslide risk assessment (LRA) or environmental risk assessment (ERA), providing quantitative estimates of the risks associated with landslide in contaminated sites. The proposed methodology can also act as a basis for communication and discussion, thereby contributing to intersectoral management solutions. From the case study it was found that the defined failures are governed primarily by the probability of a landslide occurring. The overall probabilities for failure are low; however, if a landslide occurs the probabilities of exceeding EQS are high and the probability of having at least a 10% increase in the contamination load
Accretion of Fine Particles: Sticking Probability Estimated by Optical Sizing of Fractal Aggregates
NASA Astrophysics Data System (ADS)
Sugiura, N.; Higuchi, Y.
1993-07-01
Sticking probability of fine particles is an important parameter that determines (1) the settling of fine particles to the equatorial plane of the solar nebula and hence the formation of planetesimals, and (2) the thermal structure of the nebula, which is dependent on the particle size through opacity. It is generally agreed that the sticking probability is 1 for submicrometer particles, but at sizes larger than 1 micrometer, there exist almost no data on the sticking probability. A recent study [1] showed that aggregates (with radius from 0.2 to 2 mm) did not stick when collided at a speed of 0.15 to 4 m/s. Therefore, somewhere between 1 micrometer and 200 micrometers, sticking probabilities of fine particles change from nearly 1 to nearly 0. We have been studying [2,3] sticking probabilities of dust aggregates in this size range using an optical sizing method. The optical sizing method has been well established for spherical particles. This method utilizes the fact that the smaller the size, the larger the angle of the scattered light. For spheres with various sizes, the size distribution is determined by solving Y(i) = M(i,j)X(j), where Y(i) is the scattered light intensity at angle i, X(j) is the number density of spheres with size j, and M(i,j) is the scattering matrix, which is determined by Mie theory. Dust aggregates, which we expect to be present in the early solar nebula, are not solid spheres, but probably have a porous fractal structure. For such aggregates the scattering matrix M(i,j) must be determined by taking account of all the interaction among constituent particles (discrete dipole approximation). Such calculation is possible only for very small aggregates, and for larger aggregates we estimate the scattering matrix by extrapolation, assuming that the fractal nature of the aggregates allows such extrapolation. In the experiments using magnesium oxide fine particles floating in a chamber at ambient pressure, the size distribution (determined by
Johnson, W.R.; Marshall, C.F.; Anderson, C.M.; Lear, E.M.
1994-08-01
The Federal Government has proposed to offer Outer Continental Shelf (OCS) lands in Cook Inlet for oil and gas leasing. Because oil spills may occur from activities associated with offshore oil production, the Minerals Management Service conducts a formal risk assessment. In evaluating the significance of accidental oil spills, it is important to remember that the occurrence of such spills is fundamentally probabilistic. The effects of oil spills that could occur during oil and gas production must be considered. This report summarizes results of an oil-spill risk analysis conducted for the proposed Cook Inlet OCS Lease Sale 149. The objective of this analysis was to estimate relative risks associated with oil and gas production for the proposed lease sale. To aid the analysis, conditional risk contour maps of seasonal conditional probabilities of spill contact were generated for each environmental resource or land segment in the study area. This aspect is discussed in this volume of the two volume report.
ANNz2: Photometric Redshift and Probability Distribution Function Estimation using Machine Learning
NASA Astrophysics Data System (ADS)
Sadeh, I.; Abdalla, F. B.; Lahav, O.
2016-10-01
We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister & Lahav, which now includes generation of full probability distribution functions (PDFs). ANNz2 utilizes multiple machine learning methods, such as artificial neural networks and boosted decision/regression trees. The objective of the algorithm is to optimize the performance of the photo-z estimation, to properly derive the associated uncertainties, and to produce both single-value solutions and PDFs. In addition, estimators are made available, which mitigate possible problems of non-representative or incomplete spectroscopic training samples. ANNz2 has already been used as part of the first weak lensing analysis of the Dark Energy Survey, and is included in the experiment's first public data release. Here we illustrate the functionality of the code using data from the tenth data release of the Sloan Digital Sky Survey and the Baryon Oscillation Spectroscopic Survey. The code is available for download at http://github.com/IftachSadeh/ANNZ.
Methods for estimating dispersal probabilities and related parameters using marked animals
Bennetts, R.E.; Nichols, J.D.; Pradel, R.; Lebreton, J.D.; Kitchens, W.M.; Clobert, Jean; Danchin, Etienne; Dhondt, Andre A.; Nichols, James D.
2001-01-01
Deriving valid inferences about the causes and consequences of dispersal from empirical studies depends largely on our ability reliably to estimate parameters associated with dispersal. Here, we present a review of the methods available for estimating dispersal and related parameters using marked individuals. We emphasize methods that place dispersal in a probabilistic framework. In this context, we define a dispersal event as a movement of a specified distance or from one predefined patch to another, the magnitude of the distance or the definition of a `patch? depending on the ecological or evolutionary question(s) being addressed. We have organized the chapter based on four general classes of data for animals that are captured, marked, and released alive: (1) recovery data, in which animals are recovered dead at a subsequent time, (2) recapture/resighting data, in which animals are either recaptured or resighted alive on subsequent sampling occasions, (3) known-status data, in which marked animals are reobserved alive or dead at specified times with probability 1.0, and (4) combined data, in which data are of more than one type (e.g., live recapture and ring recovery). For each data type, we discuss the data required, the estimation techniques, and the types of questions that might be addressed from studies conducted at single and multiple sites.
SAR amplitude probability density function estimation based on a generalized Gaussian model.
Moser, Gabriele; Zerubia, Josiane; Serpico, Sebastiano B
2006-06-01
In the context of remotely sensed data analysis, an important problem is the development of accurate models for the statistics of the pixel intensities. Focusing on synthetic aperture radar (SAR) data, this modeling process turns out to be a crucial task, for instance, for classification or for denoising purposes. In this paper, an innovative parametric estimation methodology for SAR amplitude data is proposed that adopts a generalized Gaussian (GG) model for the complex SAR backscattered signal. A closed-form expression for the corresponding amplitude probability density function (PDF) is derived and a specific parameter estimation algorithm is developed in order to deal with the proposed model. Specifically, the recently proposed "method-of-log-cumulants" (MoLC) is applied, which stems from the adoption of the Mellin transform (instead of the usual Fourier transform) in the computation of characteristic functions and from the corresponding generalization of the concepts of moment and cumulant. For the developed GG-based amplitude model, the resulting MoLC estimates turn out to be numerically feasible and are also analytically proved to be consistent. The proposed parametric approach was validated by using several real ERS-1, XSAR, E-SAR, and NASA/JPL airborne SAR images, and the experimental results prove that the method models the amplitude PDF better than several previously proposed parametric models for backscattering phenomena. PMID:16764268
NASA Astrophysics Data System (ADS)
Haigh, Ivan D.; Wijeratne, E. M. S.; MacPherson, Leigh R.; Pattiaratchi, Charitha B.; Mason, Matthew S.; Crompton, Ryan P.; George, Steve
2014-01-01
The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This ensures the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. This paper estimates for the first time present day extreme water level exceedence probabilities around the whole coastline of Australia. A high-resolution depth averaged hydrodynamic model has been configured for the Australian continental shelf region and has been forced with tidal levels from a global tidal model and meteorological fields from a global reanalysis to generate a 61-year hindcast of water levels. Output from this model has been successfully validated against measurements from 30 tide gauge sites. At each numeric coastal grid point, extreme value distributions have been fitted to the derived time series of annual maxima and the several largest water levels each year to estimate exceedence probabilities. This provides a reliable estimate of water level probabilities around southern Australia; a region mainly impacted by extra-tropical cyclones. However, as the meteorological forcing used only weakly includes the effects of tropical cyclones, extreme water level probabilities are underestimated around the western, northern and north-eastern Australian coastline. In a companion paper we build on the work presented here and more accurately include tropical cyclone-induced surges in the estimation of extreme water level. The multi-decadal hindcast generated here has been used primarily to estimate extreme water level exceedance probabilities but could be used more widely in the future for a variety of other research and practical
Signor, R S; Ashbolt, N J
2009-12-01
Some national drinking water guidelines provide guidance on how to define 'safe' drinking water. Regarding microbial water quality, a common position is that the chance of an individual becoming infected by some reference waterborne pathogen (e.g. Cryptsporidium) present in the drinking water should < 10(-4) in any year. However the instantaneous levels of risk to a water consumer vary over the course of a year, and waterborne disease outbreaks have been associated with shorter-duration periods of heightened risk. Performing probabilistic microbial risk assessments is becoming commonplace to capture the impacts of temporal variability on overall infection risk levels. A case is presented here for adoption of a shorter-duration reference period (i.e. daily) infection probability target over which to assess, report and benchmark such risks. A daily infection probability benchmark may provide added incentive and guidance for exercising control over short-term adverse risk fluctuation events and their causes. Management planning could involve outlining measures so that the daily target is met under a variety of pre-identified event scenarios. Other benefits of a daily target could include providing a platform for managers to design and assess management initiatives, as well as simplifying the technical components of the risk assessment process.
Estimated Probability of Traumatic Abdominal Injury During an International Space Station Mission
NASA Technical Reports Server (NTRS)
Lewandowski, Beth E.; Brooker, John E.; Weavr, Aaron S.; Myers, Jerry G., Jr.; McRae, Michael P.
2013-01-01
The Integrated Medical Model (IMM) is a decision support tool that is useful to spaceflight mission planners and medical system designers when assessing risks and optimizing medical systems. The IMM project maintains a database of medical conditions that could occur during a spaceflight. The IMM project is in the process of assigning an incidence rate, the associated functional impairment, and a best and a worst case end state for each condition. The purpose of this work was to develop the IMM Abdominal Injury Module (AIM). The AIM calculates an incidence rate of traumatic abdominal injury per person-year of spaceflight on the International Space Station (ISS). The AIM was built so that the probability of traumatic abdominal injury during one year on ISS could be predicted. This result will be incorporated into the IMM Abdominal Injury Clinical Finding Form and used within the parent IMM model.
Auditory risk estimates for youth target shooting
Meinke, Deanna K.; Murphy, William J.; Finan, Donald S.; Lankford, James E.; Flamme, Gregory A.; Stewart, Michael; Soendergaard, Jacob; Jerome, Trevor W.
2015-01-01
Objective To characterize the impulse noise exposure and auditory risk for youth recreational firearm users engaged in outdoor target shooting events. The youth shooting positions are typically standing or sitting at a table, which places the firearm closer to the ground or reflective surface when compared to adult shooters. Design Acoustic characteristics were examined and the auditory risk estimates were evaluated using contemporary damage-risk criteria for unprotected adult listeners and the 120-dB peak limit suggested by the World Health Organization (1999) for children. Study sample Impulses were generated by 26 firearm/ammunition configurations representing rifles, shotguns, and pistols used by youth. Measurements were obtained relative to a youth shooter’s left ear. Results All firearms generated peak levels that exceeded the 120 dB peak limit suggested by the WHO for children. In general, shooting from the seated position over a tabletop increases the peak levels, LAeq8 and reduces the unprotected maximum permissible exposures (MPEs) for both rifles and pistols. Pistols pose the greatest auditory risk when fired over a tabletop. Conclusion Youth should utilize smaller caliber weapons, preferably from the standing position, and always wear hearing protection whenever engaging in shooting activities to reduce the risk for auditory damage. PMID:24564688
Real Time Data Management for Estimating Probabilities of Incidents and Near Misses
NASA Astrophysics Data System (ADS)
Stanitsas, P. D.; Stephanedes, Y. J.
2011-08-01
Advances in real-time data collection, data storage and computational systems have led to development of algorithms for transport administrators and engineers that improve traffic safety and reduce cost of road operations. Despite these advances, problems in effectively integrating real-time data acquisition, processing, modelling and road-use strategies at complex intersections and motorways remain. These are related to increasing system performance in identification, analysis, detection and prediction of traffic state in real time. This research develops dynamic models to estimate the probability of road incidents, such as crashes and conflicts, and incident-prone conditions based on real-time data. The models support integration of anticipatory information and fee-based road use strategies in traveller information and management. Development includes macroscopic/microscopic probabilistic models, neural networks, and vector autoregressions tested via machine vision at EU and US sites.
Wenger, S.J.; Freeman, Mary C.
2008-01-01
Researchers have developed methods to account for imperfect detection of species with either occupancy (presence-absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.
NASA Astrophysics Data System (ADS)
Skripnichenko, P.; Galushina, T.; Loginova, M.
2015-08-01
This work is devoted to the description of the software EROS (Ephemeris Research and Observation Services), which is being developed both by the astronomy department of Ural Federal University and Tomsk State University. This software provides the ephemeris support for the positional observations. The most interesting feature of the software is an automatization of all the processes preparation for observations from the determination of the night duration to the ephemeris calculation and forming of a program observation schedule. The accuracy of ephemeris calculation mostly depends on initial data precision that defined from errors of observations which used to determination of orbital elements. In the case if object has a small number of observations which spread at short arc of orbit there is a real necessity to calculate not only at nominal orbit but probability domain both. In this paper under review ephemeris we will be understand a field on the celestial sphere which calculated based on the probability domain. Our software EROS has a relevant functional for estimation of review ephemeris. This work contains description of software system and results of the program using.
Smith, L.L.; Barichivich, W.J.; Staiger, J.S.; Smith, Kimberly G.; Dodd, C.K.
2006-01-01
We conducted an amphibian inventory at Okefenokee National Wildlife Refuge from August 2000 to June 2002 as part of the U.S. Department of the Interior's national Amphibian Research and Monitoring Initiative. Nineteen species of amphibians (15 anurans and 4 caudates) were documented within the Refuge, including one protected species, the Gopher Frog Rana capito. We also collected 1 y of monitoring data for amphibian populations and incorporated the results into the inventory. Detection probabilities and site occupancy estimates for four species, the Pinewoods Treefrog (Hyla femoralis), Pig Frog (Rana grylio), Southern Leopard Frog (R. sphenocephala) and Carpenter Frog (R. virgatipes) are presented here. Detection probabilities observed in this study indicate that spring and summer surveys offer the best opportunity to detect these species in the Refuge. Results of the inventory suggest that substantial changes may have occurred in the amphibian fauna within and adjacent to the swamp. However, monitoring the amphibian community of Okefenokee Swamp will prove difficult because of the logistical challenges associated with a rigorous statistical assessment of status and trends.
Adams, Vanessa M.; Pressey, Robert L.; Stoeckl, Natalie
2014-01-01
The need to integrate social and economic factors into conservation planning has become a focus of academic discussions and has important practical implications for the implementation of conservation areas, both private and public. We conducted a survey in the Daly Catchment, Northern Territory, to inform the design and implementation of a stewardship payment program. We used a choice model to estimate the likely level of participation in two legal arrangements - conservation covenants and management agreements - based on payment level and proportion of properties required to be managed. We then spatially predicted landholders’ probability of participating at the resolution of individual properties and incorporated these predictions into conservation planning software to examine the potential for the stewardship program to meet conservation objectives. We found that the properties that were least costly, per unit area, to manage were also the least likely to participate. This highlights a tension between planning for a cost-effective program and planning for a program that targets properties with the highest probability of participation. PMID:24892520
Adams, Vanessa M; Pressey, Robert L; Stoeckl, Natalie
2014-01-01
The need to integrate social and economic factors into conservation planning has become a focus of academic discussions and has important practical implications for the implementation of conservation areas, both private and public. We conducted a survey in the Daly Catchment, Northern Territory, to inform the design and implementation of a stewardship payment program. We used a choice model to estimate the likely level of participation in two legal arrangements--conservation covenants and management agreements--based on payment level and proportion of properties required to be managed. We then spatially predicted landholders' probability of participating at the resolution of individual properties and incorporated these predictions into conservation planning software to examine the potential for the stewardship program to meet conservation objectives. We found that the properties that were least costly, per unit area, to manage were also the least likely to participate. This highlights a tension between planning for a cost-effective program and planning for a program that targets properties with the highest probability of participation.
Measuring and Modeling Fault Density for Plume-Fault Encounter Probability Estimation
Jordan, P.D.; Oldenburg, C.M.; Nicot, J.-P.
2011-05-15
Emission of carbon dioxide from fossil-fueled power generation stations contributes to global climate change. Storage of this carbon dioxide within the pores of geologic strata (geologic carbon storage) is one approach to mitigating the climate change that would otherwise occur. The large storage volume needed for this mitigation requires injection into brine-filled pore space in reservoir strata overlain by cap rocks. One of the main concerns of storage in such rocks is leakage via faults. In the early stages of site selection, site-specific fault coverages are often not available. This necessitates a method for using available fault data to develop an estimate of the likelihood of injected carbon dioxide encountering and migrating up a fault, primarily due to buoyancy. Fault population statistics provide one of the main inputs to calculate the encounter probability. Previous fault population statistics work is shown to be applicable to areal fault density statistics. This result is applied to a case study in the southern portion of the San Joaquin Basin with the result that the probability of a carbon dioxide plume from a previously planned injection had a 3% chance of encountering a fully seal offsetting fault.
Carr, J.R. . Dept. of Geological Sciences); Mao, Nai-hsien )
1992-01-01
Disjunctive kriging has been compared previously to multigaussian kriging and indicator cokriging for estimation of cumulative distribution functions; it has yet to be compared extensively to probability kriging. Herein, disjunctive kriging and generalized probability kriging are applied to one real and one simulated data set and compared for estimation of the cumulative distribution functions. Generalized probability kriging is an extension, based on generalized cokriging theory, of simple probability kriging for the estimation of the indicator and uniform transforms at each cutoff, Z{sub k}. The disjunctive kriging and the generalized probability kriging give similar results for simulated data of normal distribution, but differ considerably for real data set with non-normal distribution.
The report evaluates approaches for estimating the probability of ingestion by birds of contaminated particles such as pesticide granules or lead particles (i.e. shot or bullet fragments). In addition, it presents an approach for using this information to estimate the risk of mo...
Estimation of the failure probability during EGS stimulation based on borehole data
NASA Astrophysics Data System (ADS)
Meller, C.; Kohl, Th.; Gaucher, E.
2012-04-01
In recent times the search for alternative sources of energy has been fostered by the scarcity of fossil fuels. With its ability to permanently provide electricity or heat with little emission of CO2, geothermal energy will have an important share in the energy mix of the future. Within Europe, scientists identified many locations with conditions suitable for Enhanced Geothermal System (EGS) projects. In order to provide sufficiently high reservoir permeability, EGS require borehole stimulations prior to installation of power plants (Gérard et al, 2006). Induced seismicity during water injection into reservoirs EGS systems is a factor that currently cannot be predicted nor controlled. Often, people living near EGS projects are frightened by smaller earthquakes occurring during stimulation or injection. As this fear can lead to widespread disapproval of geothermal power plants, it is appreciable to find a way to estimate the probability of fractures to shear when injecting water with a distinct pressure into a geothermal reservoir. This provides knowledge, which enables to predict the mechanical behavior of a reservoir in response to a change in pore pressure conditions. In the present study an approach for estimation of the shearing probability based on statistical analyses of fracture distribution, orientation and clusters, together with their geological properties is proposed. Based on geophysical logs of five wells in Soultz-sous-Forêts, France, and with the help of statistical tools, the Mohr criterion, geological and mineralogical properties of the host rock and the fracture fillings, correlations between the wells are analyzed. This is achieved with the self-written MATLAB-code Fracdens, which enables us to statistically analyze the log files in different ways. With the application of a pore pressure change, the evolution of the critical pressure on the fractures can be determined. A special focus is on the clay fillings of the fractures and how they reduce
Estimating relative risks for common outcome using PROC NLP.
Yu, Binbing; Wang, Zhuoqiao
2008-05-01
In cross-sectional or cohort studies with binary outcomes, it is biologically interpretable and of interest to estimate the relative risk or prevalence ratio, especially when the response rates are not rare. Several methods have been used to estimate the relative risk, among which the log-binomial models yield the maximum likelihood estimate (MLE) of the parameters. Because of restrictions on the parameter space, the log-binomial models often run into convergence problems. Some remedies, e.g., the Poisson and Cox regressions, have been proposed. However, these methods may give out-of-bound predicted response probabilities. In this paper, a new computation method using the SAS Nonlinear Programming (NLP) procedure is proposed to find the MLEs. The proposed NLP method was compared to the COPY method, a modified method to fit the log-binomial model. Issues in the implementation are discussed. For illustration, both methods were applied to data on the prevalence of microalbuminuria (micro-protein leakage into urine) for kidney disease patients from the Diabetes Control and Complications Trial. The sample SAS macro for calculating relative risk is provided in the appendix.
Neural response to reward anticipation under risk is nonlinear in probabilities.
Hsu, Ming; Krajbich, Ian; Zhao, Chen; Camerer, Colin F
2009-02-18
A widely observed phenomenon in decision making under risk is the apparent overweighting of unlikely events and the underweighting of nearly certain events. This violates standard assumptions in expected utility theory, which requires that expected utility be linear (objective) in probabilities. Models such as prospect theory have relaxed this assumption and introduced the notion of a "probability weighting function," which captures the key properties found in experimental data. This study reports functional magnetic resonance imaging (fMRI) data that neural response to expected reward is nonlinear in probabilities. Specifically, we found that activity in the striatum during valuation of monetary gambles are nonlinear in probabilities in the pattern predicted by prospect theory, suggesting that probability distortion is reflected at the level of the reward encoding process. The degree of nonlinearity reflected in individual subjects' decisions is also correlated with striatal activity across subjects. Our results shed light on the neural mechanisms of reward processing, and have implications for future neuroscientific studies of decision making involving extreme tails of the distribution, where probability weighting provides an explanation for commonly observed behavioral anomalies.
Dynamic probability control limits for risk-adjusted Bernoulli CUSUM charts.
Zhang, Xiang; Woodall, William H
2015-11-10
The risk-adjusted Bernoulli cumulative sum (CUSUM) chart developed by Steiner et al. (2000) is an increasingly popular tool for monitoring clinical and surgical performance. In practice, however, the use of a fixed control limit for the chart leads to a quite variable in-control average run length performance for patient populations with different risk score distributions. To overcome this problem, we determine simulation-based dynamic probability control limits (DPCLs) patient-by-patient for the risk-adjusted Bernoulli CUSUM charts. By maintaining the probability of a false alarm at a constant level conditional on no false alarm for previous observations, our risk-adjusted CUSUM charts with DPCLs have consistent in-control performance at the desired level with approximately geometrically distributed run lengths. Our simulation results demonstrate that our method does not rely on any information or assumptions about the patients' risk distributions. The use of DPCLs for risk-adjusted Bernoulli CUSUM charts allows each chart to be designed for the corresponding particular sequence of patients for a surgeon or hospital.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud to ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.
2010-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station.
Elliott, John G.; Flynn, Jennifer L.; Bossong, Clifford R.; Char, Stephen J.
2011-01-01
The subwatersheds with the greatest potential postwildfire and postprecipitation hazards are those with both high probabilities of debris-flow occurrence and large estimated volumes of debris-flow material. The high probabilities of postwildfire debris flows, the associated large estimated debris-flow volumes, and the densely populated areas along the creeks and near the outlets of the primary watersheds indicate that Indiana, Pennsylvania, and Spruce Creeks are associated with a relatively high combined debris-flow hazard.
Relating space radiation environments to risk estimates
NASA Technical Reports Server (NTRS)
Curtis, Stanley B.
1993-01-01
A number of considerations must go into the process of determining the risk of deleterious effects of space radiation to travelers. Among them are (1) determination of the components of the radiation environment (particle species, fluxes and energy spectra) which will encounter, (2) determination of the effects of shielding provided by the spacecraft and the bodies of the travelers which modify the incident particle spectra and mix of particles, and (3) determination of relevant biological effects of the radiation in the organs of interest. The latter can then lead to an estimation of risk from a given space scenario. Clearly, the process spans many scientific disciplines from solar and cosmic ray physics to radiation transport theeory to the multistage problem of the induction by radiation of initial lesions in living material and their evolution via physical, chemical, and biological processes at the molecular, cellular, and tissue levels to produce the end point of importance.
Nielson, Ryan M.; Gray, Brian R.; McDonald, Lyman L.; Heglund, Patricia J.
2011-01-01
Estimation of site occupancy rates when detection probabilities are <1 is well established in wildlife science. Data from multiple visits to a sample of sites are used to estimate detection probabilities and the proportion of sites occupied by focal species. In this article we describe how site occupancy methods can be applied to estimate occupancy rates of plants and other sessile organisms. We illustrate this approach and the pitfalls of ignoring incomplete detection using spatial data for 2 aquatic vascular plants collected under the Upper Mississippi River's Long Term Resource Monitoring Program (LTRMP). Site occupancy models considered include: a naïve model that ignores incomplete detection, a simple site occupancy model assuming a constant occupancy rate and a constant probability of detection across sites, several models that allow site occupancy rates and probabilities of detection to vary with habitat characteristics, and mixture models that allow for unexplained variation in detection probabilities. We used information theoretic methods to rank competing models and bootstrapping to evaluate the goodness-of-fit of the final models. Results of our analysis confirm that ignoring incomplete detection can result in biased estimates of occupancy rates. Estimates of site occupancy rates for 2 aquatic plant species were 19–36% higher compared to naive estimates that ignored probabilities of detection <1. Simulations indicate that final models have little bias when 50 or more sites are sampled, and little gains in precision could be expected for sample sizes >300. We recommend applying site occupancy methods for monitoring presence of aquatic species.
R-tools for estimating exceedance probabilities of Envelope Curves of hydrological extremes
NASA Astrophysics Data System (ADS)
Guse, Björn; Castellarin, Attilio
2013-04-01
Envelope curves of flood flows are classical hydrological tools that graphically summarize the current bound on our experience of extreme floods in a region. Castellarin et al. [2005] introduced Probabilistic Regional Envelope Curves (PRECs) and formulated an empirical estimator of the recurrence interval T associated with the curves themselves. PRECs can be used to estimate the T -year flood (design-flood) for any basin in a given region as a function of the catchment area alone. We present a collection of R-functions that can be used for (1) constructing the empirical envelope curve of flood flows for a given hydrological region and (2) estimating the curve's T on the basis of a mathematical representation of the cross-correlation structure of observed flood sequences. The R functions, which we tested on synthetic regional datasets of annual sequences characterized by different degrees of cross-correlation generated through Monte Carlo resampling, implement the algorithm proposed in Castellarin [2007], providing the user with straightforward means for predicting the exceedance probability 1-T associated with a regional envelope curve, and therefore the T -year flood in any ungauged basin in the region for large and very large T values. Furthermore, the algorithm can be easily coupled with other regional flood frequency analysis procedures to effectively improve the accuracy of flood quantile estimates at high T values [Guse et al., 2010], or extended to rainfall extremes for predicting extreme point-rainfall depths associated with a given duration and recurrence interval in any ungauged site within a region [Viglione et al., 2012]. References Castellarin (2007): Probabilistic envelope curves for design flood estimation at ungauged sites, Water Resour. Res., 43, W04406. Castellarin, Vogel, Matalas (2005): Probabilistic behavior of a regional envelope curve, Water Resour. Res., 41, W06018. Guse, Hofherr, Merz (2010): Introducing empirical and probabilistic regional
Chandra, A; Rudraiah, L; Zalenski, R J
2001-02-01
In summary, this article focused on the use of stress testing to risk-stratify patients at the conclusion of their emergency evaluation for ACI. As discussed, those patients in the probably not ACI category require additional risk stratification prior to discharge. It should be kept in mind that patients in this category are heterogeneous, containing subgroups at both higher and lower risk of ACI and cardiac events. The patients with lower pretest probability for ACI may only need exercise testing in the ED. Patients with higher pretest probability should undergo myocardial perfusion or echocardiographic stress testing to maximize diagnostic and prognostic information. Prognostic information is the key to provocative testing in the ED. Prognostic information is the component that will help emergency physicians identify the patients who may be discharged home safely without having to worry about a 6% annual cardiac death rate and a 10% overall death rate over the next 30 months. Stress testing provides this key prognostic data, and it can be obtained in short-stay chest pain observation units in a safe, timely, and cost-effective fashion. PMID:11214405
Bent, Gardner C.; Archfield, Stacey A.
2002-01-01
A logistic regression equation was developed for estimating the probability of a stream flowing perennially at a specific site in Massachusetts. The equation provides city and town conservation commissions and the Massachusetts Department of Environmental Protection with an additional method for assessing whether streams are perennial or intermittent at a specific site in Massachusetts. This information is needed to assist these environmental agencies, who administer the Commonwealth of Massachusetts Rivers Protection Act of 1996, which establishes a 200-foot-wide protected riverfront area extending along the length of each side of the stream from the mean annual high-water line along each side of perennial streams, with exceptions in some urban areas. The equation was developed by relating the verified perennial or intermittent status of a stream site to selected basin characteristics of naturally flowing streams (no regulation by dams, surface-water withdrawals, ground-water withdrawals, diversion, waste-water discharge, and so forth) in Massachusetts. Stream sites used in the analysis were identified as perennial or intermittent on the basis of review of measured streamflow at sites throughout Massachusetts and on visual observation at sites in the South Coastal Basin, southeastern Massachusetts. Measured or observed zero flow(s) during months of extended drought as defined by the 310 Code of Massachusetts Regulations (CMR) 10.58(2)(a) were not considered when designating the perennial or intermittent status of a stream site. The database used to develop the equation included a total of 305 stream sites (84 intermittent- and 89 perennial-stream sites in the State, and 50 intermittent- and 82 perennial-stream sites in the South Coastal Basin). Stream sites included in the database had drainage areas that ranged from 0.14 to 8.94 square miles in the State and from 0.02 to 7.00 square miles in the South Coastal Basin.Results of the logistic regression analysis
Estimating Risk of Alcohol Dependence Using Alcohol Screening Scores*
Rubinsky, Anna D.; Kivlahan, Daniel R.; Volk, Robert J.; Maynard, Charles; Bradley, Katharine A.
2010-01-01
Brief alcohol counseling interventions can reduce alcohol consumption and related morbidity among non-dependent risky drinkers, but more intensive alcohol treatment is recommended for persons with alcohol dependence. This study evaluated whether scores on common alcohol screening tests could identify patients likely to have current alcohol dependence so that more appropriate follow-up assessment and/or intervention could be offered. This cross-sectional study used secondary data from 392 male and 927 female adult family medicine outpatients (1993–1994). Likelihood ratios were used to empirically identify and evaluate ranges of scores of the AUDIT, the AUDIT-C, two single-item questions about frequency of binge drinking, and the CAGE questionnaire for detecting DSM-IV past-year alcohol dependence. Based on the prevalence of past-year alcohol dependence in this sample (men: 12.2%; women: 5.8%), zones of the AUDIT and AUDIT-C identified wide variability in the post-screening risk of alcohol dependence in men and women, even among those who screened positive for alcohol misuse. Among men, AUDIT zones 5–10, 11–14 and 15–40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 18–87%, and AUDIT-C zones 5–6, 7–9 and 10–12 were associated with probabilities ranging from 22–75%. Among women, AUDIT zones 3–4, 5–8, 9–12 and 13–40 were associated with post-screening probabilities of past-year alcohol dependence ranging from 6–94%, and AUDIT-C zones 3, 4–6, 7–9 and 10–12 were associated with probabilities ranging from 9–88%. AUDIT or AUDIT-C scores could be used to estimate the probability of past-year alcohol dependence among patients who screen positive for alcohol misuse and inform clinical decision-making. PMID:20042299
Over, Thomas; Saito, Riki J.; Veilleux, Andrea; Sharpe, Jennifer B.; Soong, David; Ishii, Audrey
2016-06-28
This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, generalized skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at
Haber, M; An, Q; Foppa, I M; Shay, D K; Ferdinands, J M; Orenstein, W A
2015-05-01
As influenza vaccination is now widely recommended, randomized clinical trials are no longer ethical in many populations. Therefore, observational studies on patients seeking medical care for acute respiratory illnesses (ARIs) are a popular option for estimating influenza vaccine effectiveness (VE). We developed a probability model for evaluating and comparing bias and precision of estimates of VE against symptomatic influenza from two commonly used case-control study designs: the test-negative design and the traditional case-control design. We show that when vaccination does not affect the probability of developing non-influenza ARI then VE estimates from test-negative design studies are unbiased even if vaccinees and non-vaccinees have different probabilities of seeking medical care against ARI, as long as the ratio of these probabilities is the same for illnesses resulting from influenza and non-influenza infections. Our numerical results suggest that in general, estimates from the test-negative design have smaller bias compared to estimates from the traditional case-control design as long as the probability of non-influenza ARI is similar among vaccinated and unvaccinated individuals. We did not find consistent differences between the standard errors of the estimates from the two study designs.
Software risk estimation and management techniques at JPL
NASA Technical Reports Server (NTRS)
Hihn, J.; Lum, K.
2002-01-01
In this talk we will discuss how uncertainty has been incorporated into the JPL software model, probabilistic-based estimates, and how risk is addressed, how cost risk is currently being explored via a variety of approaches, from traditional risk lists, to detailed WBS-based risk estimates to the Defect Detection and Prevention (DDP) tool.
Estimation of the Probable Maximum Flood for a Small Lowland River in Poland
NASA Astrophysics Data System (ADS)
Banasik, K.; Hejduk, L.
2009-04-01
The planning, designe and use of hydrotechnical structures often requires the assesment of maximu flood potentials. The most common term applied to this upper limit of flooding is the probable maximum flood (PMF). The PMP/UH (probable maximum precipitation/unit hydrograph) method has been used in the study to predict PMF from a small agricultural lowland river basin of Zagozdzonka (left tributary of Vistula river) in Poland. The river basin, located about 100 km south of Warsaw, with an area - upstream the gauge of Plachty - of 82 km2, has been investigated by Department of Water Engineering and Environmenal Restoration of Warsaw University of Life Sciences - SGGW since 1962. Over 40-year flow record was used in previous investigation for predicting T-year flood discharge (Banasik et al., 2003). The objective here was to estimate the PMF using the PMP/UH method and to compare the results with the 100-year flood. A new relation of depth-duration curve of PMP for the local climatic condition has been developed based on Polish maximum observed rainfall data (Ozga-Zielinska & Ozga-Zielinski, 2003). Exponential formula, with the value of exponent of 0.47, i.e. close to the exponent in formula for world PMP and also in the formula of PMP for Great Britain (Wilson, 1993), gives the rainfall depth about 40% lower than the Wilson's one. The effective rainfall (runoff volume) has been estimated from the PMP of various duration using the CN-method (USDA-SCS, 1986). The CN value as well as parameters of the IUH model (Nash, 1957) have been established from the 27 rainfall-runoff events, recorded in the river basin in the period 1980-2004. Varibility of the parameter values with the size of the events will be discussed in the paper. The results of the analyse have shown that the peak discharge of the PMF is 4.5 times larger then 100-year flood, and volume ratio of the respective direct hydrographs caused by rainfall events of critical duration is 4.0. References 1.Banasik K
Estimation of the Probable Maximum Flood for a Small Lowland River in Poland
NASA Astrophysics Data System (ADS)
Banasik, K.; Hejduk, L.
2009-04-01
The planning, designe and use of hydrotechnical structures often requires the assesment of maximu flood potentials. The most common term applied to this upper limit of flooding is the probable maximum flood (PMF). The PMP/UH (probable maximum precipitation/unit hydrograph) method has been used in the study to predict PMF from a small agricultural lowland river basin of Zagozdzonka (left tributary of Vistula river) in Poland. The river basin, located about 100 km south of Warsaw, with an area - upstream the gauge of Plachty - of 82 km2, has been investigated by Department of Water Engineering and Environmenal Restoration of Warsaw University of Life Sciences - SGGW since 1962. Over 40-year flow record was used in previous investigation for predicting T-year flood discharge (Banasik et al., 2003). The objective here was to estimate the PMF using the PMP/UH method and to compare the results with the 100-year flood. A new relation of depth-duration curve of PMP for the local climatic condition has been developed based on Polish maximum observed rainfall data (Ozga-Zielinska & Ozga-Zielinski, 2003). Exponential formula, with the value of exponent of 0.47, i.e. close to the exponent in formula for world PMP and also in the formula of PMP for Great Britain (Wilson, 1993), gives the rainfall depth about 40% lower than the Wilson's one. The effective rainfall (runoff volume) has been estimated from the PMP of various duration using the CN-method (USDA-SCS, 1986). The CN value as well as parameters of the IUH model (Nash, 1957) have been established from the 27 rainfall-runoff events, recorded in the river basin in the period 1980-2004. Varibility of the parameter values with the size of the events will be discussed in the paper. The results of the analyse have shown that the peak discharge of the PMF is 4.5 times larger then 100-year flood, and volume ratio of the respective direct hydrographs caused by rainfall events of critical duration is 4.0. References 1.Banasik K
Moment-Based Probability Modeling and Extreme Response Estimation, The FITS Routine Version 1.2
MANUEL,LANCE; KASHEF,TINA; WINTERSTEIN,STEVEN R.
1999-11-01
This report documents the use of the FITS routine, which provides automated fits of various analytical, commonly used probability models from input data. It is intended to complement the previously distributed FITTING routine documented in RMS Report 14 (Winterstein et al., 1994), which implements relatively complex four-moment distribution models whose parameters are fit with numerical optimization routines. Although these four-moment fits can be quite useful and faithful to the observed data, their complexity can make them difficult to automate within standard fitting algorithms. In contrast, FITS provides more robust (lower moment) fits of simpler, more conventional distribution forms. For each database of interest, the routine estimates the distribution of annual maximum response based on the data values and the duration, T, over which they were recorded. To focus on the upper tails of interest, the user can also supply an arbitrary lower-bound threshold, {chi}{sub low}, above which a shifted distribution model--exponential or Weibull--is fit.
NASA Astrophysics Data System (ADS)
', Jayajit; Mukherjee, Sayak; Hodge, Susan
2015-07-01
A common statistical situation concerns inferring an unknown distribution Q(x) from a known distribution P(y), where X (dimension n), and Y (dimension m) have a known functional relationship. Most commonly, n
A New Approach to Estimating the Probability for β-delayed Neutron Emission
McCutchan, E.A.; Sonzogni, A.A.; Johnson, T.D.; Abriola, D.; Birch, M.; Singh, B.
2014-06-15
The probability for neutron emission following β decay, Pn, is a crucial property for a wide range of physics and applications including nuclear structure, r-process nucleosynthesis, the control of nuclear reactors, and the post-processing of nuclear fuel. Despite much experimental effort, knowledge of Pn values is still lacking in very neutron-rich nuclei, requiring predictions from either systematics or theoretical models. Traditionally, systematic predictions were made by investigating the Pn value as a function of the decay Q value and the neutron separation energy in the daughter nucleus. A new approach to Pn systematics is presented which incorporates the half-life of the decay and the Q value for β-delayed neutron emission. This prescription correlates the known data better, and thus improves the estimation of Pn values for neutron-rich nuclei. Such an approach can be applied to generate input values for r-process network calculations or in the modeling of advanced fuel cycles.
Nilsson, Håkan; Juslin, Peter; Winman, Anders
2016-01-01
Costello and Watts (2014) present a model assuming that people's knowledge of probabilities adheres to probability theory, but that their probability judgments are perturbed by a random noise in the retrieval from memory. Predictions for the relationships between probability judgments for constituent events and their disjunctions and conjunctions, as well as for sums of such judgments were derived from probability theory. Costello and Watts (2014) report behavioral data showing that subjective probability judgments accord with these predictions. Based on the finding that subjective probability judgments follow probability theory, Costello and Watts (2014) conclude that the results imply that people's probability judgments embody the rules of probability theory and thereby refute theories of heuristic processing. Here, we demonstrate the invalidity of this conclusion by showing that all of the tested predictions follow straightforwardly from an account assuming heuristic probability integration (Nilsson, Winman, Juslin, & Hansson, 2009). We end with a discussion of a number of previous findings that harmonize very poorly with the predictions by the model suggested by Costello and Watts (2014). PMID:26709414
Seismic Risk Assessment and Loss Estimation for Tbilisi City
NASA Astrophysics Data System (ADS)
Tsereteli, Nino; Alania, Victor; Varazanashvili, Otar; Gugeshashvili, Tengiz; Arabidze, Vakhtang; Arevadze, Nika; Tsereteli, Emili; Gaphrindashvili, Giorgi; Gventcadze, Alexander; Goguadze, Nino; Vephkhvadze, Sophio
2013-04-01
The proper assessment of seismic risk is of crucial importance for society protection and city sustainable economic development, as it is the essential part to seismic hazard reduction. Estimation of seismic risk and losses is complicated tasks. There is always knowledge deficiency on real seismic hazard, local site effects, inventory on elements at risk, infrastructure vulnerability, especially for developing countries. Lately great efforts was done in the frame of EMME (earthquake Model for Middle East Region) project, where in the work packages WP1, WP2 , WP3 and WP4 where improved gaps related to seismic hazard assessment and vulnerability analysis. Finely in the frame of work package wp5 "City Scenario" additional work to this direction and detail investigation of local site conditions, active fault (3D) beneath Tbilisi were done. For estimation economic losses the algorithm was prepared taking into account obtained inventory. The long term usage of building is very complex. It relates to the reliability and durability of buildings. The long term usage and durability of a building is determined by the concept of depreciation. Depreciation of an entire building is calculated by summing the products of individual construction unit' depreciation rates and the corresponding value of these units within the building. This method of calculation is based on an assumption that depreciation is proportional to the building's (constructions) useful life. We used this methodology to create a matrix, which provides a way to evaluate the depreciation rates of buildings with different type and construction period and to determine their corresponding value. Finally loss was estimated resulting from shaking 10%, 5% and 2% exceedance probability in 50 years. Loss resulting from scenario earthquake (earthquake with possible maximum magnitude) also where estimated.
IMPROVED RISK ESTIMATES FOR CARBON TETRACHLORIDE
Benson, Janet M.; Springer, David L.
1999-12-31
Carbon tetrachloride has been used extensively within the DOE nuclear weapons facilities. Rocky Flats was formerly the largest volume consumer of CCl4 in the United States using 5000 gallons in 1977 alone (Ripple, 1992). At the Hanford site, several hundred thousand gallons of CCl4 were discharged between 1955 and 1973 into underground cribs for storage. Levels of CCl4 in groundwater at highly contaminated sites at the Hanford facility have exceeded 8 the drinking water standard of 5 ppb by several orders of magnitude (Illman, 1993). High levels of CCl4 at these facilities represent a potential health hazard for workers conducting cleanup operations and for surrounding communities. The level of CCl4 cleanup required at these sites and associated costs are driven by current human health risk estimates, which assume that CCl4 is a genotoxic carcinogen. The overall purpose of these studies was to improve the scientific basis for assessing the health risk associated with human exposure to CCl4. Specific research objectives of this project were to: (1) compare the rates of CCl4 metabolism by rats, mice and hamsters in vivo and extrapolate those rates to man based on parallel studies on the metabolism of CCl4 by rat, mouse, hamster and human hepatic microsomes in vitro; (2) using hepatic microsome preparations, determine the role of specific cytochrome P450 isoforms in CCl4-mediated toxicity and the effects of repeated inhalation and ingestion of CCl4 on these isoforms; and (3) evaluate the toxicokinetics of inhaled CCl4 in rats, mice and hamsters. This information has been used to improve the physiologically based pharmacokinetic (PBPK) model for CCl4 originally developed by Paustenbach et al. (1988) and more recently revised by Thrall and Kenny (1996). Another major objective of the project was to provide scientific evidence that CCl4, like chloroform, is a hepatocarcinogen only when exposure results in cell damage, cell killing and regenerative proliferation. In
Demaree, Heath A; Burns, Kevin J; Dedonno, Michael A; Agarwala, Edward K; Everhart, D Erik
2012-06-01
In path-dependent risk taking, like playing a slot machine, the wager on one trial may be affected by the outcome of the preceding trial. Previous studies have shown that a person's risk-taking preferences may change as a result of the preceding trial (win or loss). For example, the "house money effect" suggests that risk taking may increase after a win, whereas the "break even effect" posits that risk taking increases after a loss. Independent of those findings, a person's emotional state has been found to influence risk taking. For example, the "mood maintenance hypothesis" supports the notion that positive affect decreases risk taking, and related research finds that increased negative affect increases risk taking. Because winning and losing may influence one's emotional state, we sought to investigate how both previous outcomes, as well as a person's emotional responses to those outcomes, independently influence subsequent risk taking. To do this, data were collected using three simplified slot machines where the chance of winning each trial was set to 13%, 50%, and 87%, respectively. Evidence for the break even and house money effects were found on the 13% and 87% games, respectively. Likewise, emotional valence was found to predict risk taking on these two tasks, with emotional valence fully explaining the break even effect observed on the 13% game. In addition to these results, the present research revealed that risk taking is reduced following low-probability ("surprising") events (i.e., a win in the 13% condition or loss in the 87% condition). Dubbed "risk dishabituation," this phenomenon is discussed, along with its likely corresponding emotional experience--surprise. PMID:22023358
NASA Astrophysics Data System (ADS)
Suligowski, Roman
2014-05-01
Probable Maximum Precipitation based upon the physical mechanisms of precipitation formation at the Kielce Upland. This estimation stems from meteorological analysis of extremely high precipitation events, which occurred in the area between 1961 and 2007 causing serious flooding from rivers that drain the entire Kielce Upland. Meteorological situation has been assessed drawing on the synoptic maps, baric topography charts, satellite and radar images as well as the results of meteorological observations derived from surface weather observation stations. Most significant elements of this research include the comparison between distinctive synoptic situations over Europe and subsequent determination of typical rainfall generating mechanism. This allows the author to identify the source areas of air masses responsible for extremely high precipitation at the Kielce Upland. Analysis of the meteorological situations showed, that the source areas for humid air masses which cause the largest rainfalls at the Kielce Upland are the area of northern Adriatic Sea and the north-eastern coast of the Black Sea. Flood hazard at the Kielce Upland catchments was triggered by daily precipitation of over 60 mm. The highest representative dew point temperature in source areas of warm air masses (these responsible for high precipitation at the Kielce Upland) exceeded 20 degrees Celsius with a maximum of 24.9 degrees Celsius while precipitable water amounted to 80 mm. The value of precipitable water is also used for computation of factors featuring the system, namely the mass transformation factor and the system effectiveness factor. The mass transformation factor is computed based on precipitable water in the feeding mass and precipitable water in the source area. The system effectiveness factor (as the indicator of the maximum inflow velocity and the maximum velocity in the zone of front or ascending currents, forced by orography) is computed from the quotient of precipitable water in
The Human Bathtub: Safety and Risk Predictions Including the Dynamic Probability of Operator Errors
Duffey, Romney B.; Saull, John W.
2006-07-01
Reactor safety and risk are dominated by the potential and major contribution for human error in the design, operation, control, management, regulation and maintenance of the plant, and hence to all accidents. Given the possibility of accidents and errors, now we need to determine the outcome (error) probability, or the chance of failure. Conventionally, reliability engineering is associated with the failure rate of components, or systems, or mechanisms, not of human beings in and interacting with a technological system. The probability of failure requires a prior knowledge of the total number of outcomes, which for any predictive purposes we do not know or have. Analysis of failure rates due to human error and the rate of learning allow a new determination of the dynamic human error rate in technological systems, consistent with and derived from the available world data. The basis for the analysis is the 'learning hypothesis' that humans learn from experience, and consequently the accumulated experience defines the failure rate. A new 'best' equation has been derived for the human error, outcome or failure rate, which allows for calculation and prediction of the probability of human error. We also provide comparisons to the empirical Weibull parameter fitting used in and by conventional reliability engineering and probabilistic safety analysis methods. These new analyses show that arbitrary Weibull fitting parameters and typical empirical hazard function techniques cannot be used to predict the dynamics of human errors and outcomes in the presence of learning. Comparisons of these new insights show agreement with human error data from the world's commercial airlines, the two shuttle failures, and from nuclear plant operator actions and transient control behavior observed in transients in both plants and simulators. The results demonstrate that the human error probability (HEP) is dynamic, and that it may be predicted using the learning hypothesis and the minimum
de Uña-Álvarez, Jacobo; Meira-Machado, Luís
2015-06-01
Multi-state models are often used for modeling complex event history data. In these models the estimation of the transition probabilities is of particular interest, since they allow for long-term predictions of the process. These quantities have been traditionally estimated by the Aalen-Johansen estimator, which is consistent if the process is Markov. Several non-Markov estimators have been proposed in the recent literature, and their superiority with respect to the Aalen-Johansen estimator has been proved in situations in which the Markov condition is strongly violated. However, the existing estimators have the drawback of requiring that the support of the censoring distribution contains the support of the lifetime distribution, which is not often the case. In this article, we propose two new methods for estimating the transition probabilities in the progressive illness-death model. Some asymptotic results are derived. The proposed estimators are consistent regardless the Markov condition and the referred assumption about the censoring support. We explore the finite sample behavior of the estimators through simulations. The main conclusion of this piece of research is that the proposed estimators are much more efficient than the existing non-Markov estimators in most cases. An application to a clinical trial on colon cancer is included. Extensions to progressive processes beyond the three-state illness-death model are discussed.
Application of Radar-Rainfall Estimates to Probable Maximum Precipitation in the Carolinas
NASA Astrophysics Data System (ADS)
England, J. F.; Caldwell, R. J.; Sankovich, V.
2011-12-01
Extreme storm rainfall data are essential in the assessment of potential impacts on design precipitation amounts, which are used in flood design criteria for dams and nuclear power plants. Probable Maximum Precipitation (PMP) from National Weather Service Hydrometeorological Report 51 (HMR51) is currently used for design rainfall estimates in the eastern U.S. The extreme storm database associated with the report has not been updated since the early 1970s. In the past several decades, several extreme precipitation events have occurred that have the potential to alter the PMP values, particularly across the Southeast United States (e.g., Hurricane Floyd 1999). Unfortunately, these and other large precipitation-producing storms have not been analyzed with the detail required for application in design studies. This study focuses on warm-season tropical cyclones (TCs) in the Carolinas, as these systems are the critical maximum rainfall mechanisms in the region. The goal is to discern if recent tropical events may have reached or exceeded current PMP values. We have analyzed 10 storms using modern datasets and methodologies that provide enhanced spatial and temporal resolution relative to point measurements used in past studies. Specifically, hourly multisensor precipitation reanalysis (MPR) data are used to estimate storm total precipitation accumulations at various durations throughout each storm event. The accumulated grids serve as input to depth-area-duration calculations. Individual storms are then maximized using back-trajectories to determine source regions for moisture. The development of open source software has made this process time and resource efficient. Based on the current methodology, two of the ten storms analyzed have the potential to challenge HMR51 PMP values. Maximized depth-area curves for Hurricane Floyd indicate exceedance at 24- and 72-hour durations for large area sizes, while Hurricane Fran (1996) appears to exceed PMP at large area sizes for
Joseph, Pawlin Vasanthi; Balan, Brindha; Rajendran, Vidhyalakshmi; Prashanthi, Devi Marimuthu; Somnathan, Balasubramanian
2015-01-01
Background: Maps show well the spatial configuration of information. Considerable effort is devoted to the development of geographical information systems (GIS) that increase understanding of public health problems and in particular to collaborate efforts among clinicians, epidemiologists, ecologists, and geographers to map and forecast disease risk. Objectives: Small populations tend to give rise to the most extreme disease rates, even if the actual rates are similar across the areas. Such situations will follow the decision-maker's attention on these areas when they scrutinize the map for decision making or resource allocation. As an alternative, maps can be prepared using P-values (probabilistic values). Materials and Methods: The statistical significance of rates rather than the rates themselves are used to map the results. The incidence rates calculated for each village from 2000 to 2009 is used to estimate λ, the expected number of cases in the study area. The obtained results are mapped using Arc GIS 10.0. Results: The likelihood of infections from low to high is depicted in the map and it is observed that five villages namely, Odanthurai, Coimbatore Corporation, Ikkaraiboluvampatti, Puliakulam, and Pollachi Corporation are more likely to have significantly high incidences. Conclusion: In the probability map, some of the areas with exceptionally high or low rates disappear. These are typically small unpopulated areas, whose rates are unstable due to the small numbers problem. The probability map shows more specific regions of relative risks and expected outcomes. PMID:26170544
NASA Technical Reports Server (NTRS)
Frigm, Ryan C.; Hejduk, Matthew D.; Johnson, Lauren C.; Plakalovic, Dragan
2015-01-01
On-orbit collision risk is becoming an increasing mission risk to all operational satellites in Earth orbit. Managing this risk can be disruptive to mission and operations, present challenges for decision-makers, and is time-consuming for all parties involved. With the planned capability improvements to detecting and tracking smaller orbital debris and capacity improvements to routinely predict on-orbit conjunctions, this mission risk will continue to grow in terms of likelihood and effort. It is very real possibility that the future space environment will not allow collision risk management and mission operations to be conducted in the same manner as it is today. This paper presents the concept of a finite conjunction assessment-one where each discrete conjunction is not treated separately but, rather, as a continuous event that must be managed concurrently. The paper also introduces the Total Probability of Collision as an analogous metric for finite conjunction assessment operations and provides several options for its usage in a Concept of Operations.
Survivorship models for estimating the risk of decompression sickness.
Kumar, K V; Powell, M R
1994-07-01
Several approaches have been used for modeling the incidence of decompression sickness (DCS) such as Hill's dose-response and logistic regression. Most of these methods do not include the time-to-onset information in the model. Survival analysis (failure time analysis) is appropriate when the time to onset of an event is of interest. The applicability of survival analysis for modeling the risk of DCS is illustrated by using data obtained from hypobaric chamber exposures simulating extravehicular activities (n = 426). Univariate analysis of incidence-free survival proportions were obtained for Doppler-detectable circulating microbubbles (CMB), symptoms of DCS and test aborts. A log-linear failure time regression model with 360-min half-time tissue ratio (TR) as covariate was constructed, and estimated probabilities for various TR values were calculated. Further regression analysis by including CMB status in this model showed significant improvement (p < 0.05) in the estimation of DCS over the previous model. Since DCS is dependent on the exposure pressure as well as the duration of exposure, we recommend the use of survival analysis for modeling the risk of DCS. PMID:7945136
Estimation of health risks from radiation exposures
Randolph, M.L.
1983-08-01
An informal presentation is given of the cancer and genetic risks from exposures to ionizing radiations. The risks from plausible radiation exposures are shown to be comparable to other commonly encountered risks.
NASA Technical Reports Server (NTRS)
Wiegmann, Douglas A.a
2005-01-01
The NASA Aviation Safety Program (AvSP) has defined several products that will potentially modify airline and/or ATC operations, enhance aircraft systems, and improve the identification of potential hazardous situations within the National Airspace System (NAS). Consequently, there is a need to develop methods for evaluating the potential safety benefit of each of these intervention products so that resources can be effectively invested to produce the judgments to develop Bayesian Belief Networks (BBN's) that model the potential impact that specific interventions may have. Specifically, the present report summarizes methodologies for improving the elicitation of probability estimates during expert evaluations of AvSP products for use in BBN's. The work involved joint efforts between Professor James Luxhoj from Rutgers University and researchers at the University of Illinois. The Rutgers' project to develop BBN's received funding by NASA entitled "Probabilistic Decision Support for Evaluating Technology Insertion and Assessing Aviation Safety System Risk." The proposed project was funded separately but supported the existing Rutgers' program.
Neokosmidis, Ioannis; Kamalakis, Thomas; Chipouras, Aristides; Sphicopoulos, Thomas
2005-01-01
The performance of high-powered wavelength-division multiplexed (WDM) optical networks can be severely degraded by four-wave-mixing- (FWM-) induced distortion. The multicanonical Monte Carlo method (MCMC) is used to calculate the probability-density function (PDF) of the decision variable of a receiver, limited by FWM noise. Compared with the conventional Monte Carlo method previously used to estimate this PDF, the MCMC method is much faster and can accurately estimate smaller error probabilities. The method takes into account the correlation between the components of the FWM noise, unlike the Gaussian model, which is shown not to provide accurate results. PMID:15648621
NASA Astrophysics Data System (ADS)
Denzler, Stefan M.; Dacorogna, Michel M.; Muller, Ulrich A.; McNeil, Alexander J.
2005-05-01
Credit risk models like Moody's KMV are now well established in the market and give bond managers reliable default probabilities for individual firms. Until now it has been hard to relate those probabilities to the actual credit spreads observed on the market for corporate bonds. Inspired by the existence of scaling laws in financial markets by Dacorogna et al. 2001 and DiMatteo et al. 2005 deviating from the Gaussian behavior, we develop a model that quantitatively links those default probabilities to credit spreads (market prices). The main input quantities to this study are merely industry yield data of different times to maturity and expected default frequencies (EDFs) of Moody's KMV. The empirical results of this paper clearly indicate that the model can be used to calculate approximate credit spreads (market prices) from EDFs, independent of the time to maturity and the industry sector under consideration. Moreover, the model is effective in an out-of-sample setting, it produces consistent results on the European bond market where data are scarce and can be adequately used to approximate credit spreads on the corporate level.
Probable Health Risks Due to Exposure to Outdoor PM2.5 in India
NASA Astrophysics Data System (ADS)
Dey, S.; Chowdhury, S.
2014-12-01
Particulate matter of size <2.5 μm (commonly referred to as PM2.5) is considered to be the best indicator of health risks due to exposure to particulate pollution. Unlike the decreasing trends in the developed countries, aerosol loading continues to increase over the Indian subcontinent in the recent past, exposing ~1.6 billion population at risk. Lack of direct measurements prompted us to utilize satellite data in establishing a robust long-term database of surface PM2.5 at high spatial resolution. The hybrid approach utilizes a chemical transport model to constrain the relation between columnar aerosol optical depth (AOD) and surface PM2.5 and establish mean monthly conversion factor. Satellite-derived daily AODs for the period 2000-2012 are then converted to PM2.5 using the conversion factors. The dataset (after validation against coincident in-situ measurements and bias-correction) was used to carry out the exposure assessment. 51% of the population is exposed to PM2.5 concentration exceeding WHO air quality interim target-3 threshold (35 μg m-3). The health impacts are categorized in terms of four diseases - cardio ortho-pulmonary disease (COPD), stroke, ischemic heart disease (IHD) and lung cancer (LC). In absence of any region-specific cohort study, published studies are consulted to estimate risk. The risks relative to the background concentration of 10 μg m-3 are estimated by logarithmic fitting of the individual cohort studies against the corresponding PM2.5 concentration. This approach considers multiple (>100) cohort studies across a wide variety of adult population from various socio-economic backgrounds. Therefore, the calculated risks are considered to be better estimates in relative to any one particular type of risk function model (e.g. linear 50 or linear 70 or exponential). The risk values are used to calculate the additional mortality due to exposure to PM2.5 in each of the administrative districts in India to identify the vulnerable regions
Timonina, Anna; Hochrainer-Stigler, Stefan; Pflug, Georg; Jongman, Brenden; Rojas, Rodrigo
2015-11-01
Losses due to natural hazard events can be extraordinarily high and difficult to cope with. Therefore, there is considerable interest to estimate the potential impact of current and future extreme events at all scales in as much detail as possible. As hazards typically spread over wider areas, risk assessment must take into account interrelations between regions. Neglecting such interdependencies can lead to a severe underestimation of potential losses, especially for extreme events. This underestimation of extreme risk can lead to the failure of riskmanagement strategies when they are most needed, namely, in times of unprecedented events. In this article, we suggest a methodology to incorporate such interdependencies in risk via the use of copulas. We demonstrate that by coupling losses, dependencies can be incorporated in risk analysis, avoiding the underestimation of risk. Based on maximum discharge data of river basins and stream networks, we present and discuss different ways to couple loss distributions of basins while explicitly incorporating tail dependencies. We distinguish between coupling methods that require river structure data for the analysis and those that do not. For the later approach we propose a minimax algorithm to choose coupled basin pairs so that the underestimation of risk is avoided and the use of river structure data is not needed. The proposed methodology is especially useful for large-scale analysis and we motivate and apply our method using the case of Romania. The approach can be easily extended to other countries and natural hazards. PMID:26010101
Timonina, Anna; Hochrainer-Stigler, Stefan; Pflug, Georg; Jongman, Brenden; Rojas, Rodrigo
2015-11-01
Losses due to natural hazard events can be extraordinarily high and difficult to cope with. Therefore, there is considerable interest to estimate the potential impact of current and future extreme events at all scales in as much detail as possible. As hazards typically spread over wider areas, risk assessment must take into account interrelations between regions. Neglecting such interdependencies can lead to a severe underestimation of potential losses, especially for extreme events. This underestimation of extreme risk can lead to the failure of riskmanagement strategies when they are most needed, namely, in times of unprecedented events. In this article, we suggest a methodology to incorporate such interdependencies in risk via the use of copulas. We demonstrate that by coupling losses, dependencies can be incorporated in risk analysis, avoiding the underestimation of risk. Based on maximum discharge data of river basins and stream networks, we present and discuss different ways to couple loss distributions of basins while explicitly incorporating tail dependencies. We distinguish between coupling methods that require river structure data for the analysis and those that do not. For the later approach we propose a minimax algorithm to choose coupled basin pairs so that the underestimation of risk is avoided and the use of river structure data is not needed. The proposed methodology is especially useful for large-scale analysis and we motivate and apply our method using the case of Romania. The approach can be easily extended to other countries and natural hazards.
Su, Nan-Yao
2013-12-01
The reliability of the capture probability equilibrium model developed by Su and Lee (2008) for population estimate was tested in three-directional extended foraging arenas connecting to large Plexiglas cubes (96 by 96 by 96 cm) containing approximately 100,000-400,000 workers of the Formosan subterranean termite, Coptotermes formosanus Shiraki. After the release of marked termites in the arenas, the capture probability was averaged for three directions at equal distance from the release point. The daily data of directionally averaged capture probability were subject to a linear regression with distance as the independent variable to identify the capture probability equilibrium. When the daily data produced significant regressions with regression slope [b] < or = 0.05 or [b] approximately 0.05, the directionally averaged capture probability was considered to have reached equilibrium, and the regression intercept was used in the Lincoln index to derive the population estimate. Of the four laboratory colonies tested, three met the criteria, and the equilibrium models yielded population estimates that were not significantly different from the known numbers of workers in the arenas. PMID:24498746
NASA Astrophysics Data System (ADS)
Sawosz, P.; Kacprzak, M.; Weigl, W.; Borowska-Solonynko, A.; Krajewski, P.; Zolek, N.; Ciszek, B.; Maniewski, R.; Liebert, A.
2012-12-01
A time-gated intensified CCD camera was applied for time-resolved imaging of light penetrating in an optically turbid medium. Spatial distributions of light penetration probability in the plane perpendicular to the axes of the source and the detector were determined at different source positions. Furthermore, visiting probability profiles of diffuse reflectance measurement were obtained by the convolution of the light penetration distributions recorded at different source positions. Experiments were carried out on homogeneous phantoms, more realistic two-layered tissue phantoms based on the human skull filled with Intralipid-ink solution and on cadavers. It was noted that the photons visiting probability profiles depend strongly on the source-detector separation, the delay between the laser pulse and the photons collection window and the complex tissue composition of the human head.
NASA Technical Reports Server (NTRS)
Watson, Clifford C.
2011-01-01
Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.
NASA Technical Reports Server (NTRS)
Watson, Clifford
2010-01-01
Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the twodimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and threedimensional charting gives a visual confirmation of the relationship between causes and their controls
How does new evidence change our estimates of probabilities? Carnap's formula revisited
NASA Technical Reports Server (NTRS)
Kreinovich, Vladik; Quintana, Chris
1992-01-01
The formula originally proposed by R. Carnap in his analysis of induction is reviewed and its natural generalization is presented. A situation is considered where the probability of a certain event is determined without using standard statistical methods due to the lack of observation.
Optimization of next-event estimation probability in Monte Carlo shielding calculations
Hoffman, T.J.; Tang, J.S.
1983-01-01
In Monte Carlo radiation transport calculations with point detectors, the next-event estimation is employed to estimate the response to each detector from all collision sites. The computation time required for this estimation process is substantial and often exceeds the time required to generate and process particle histories in a calculation. This estimation from all collision sites is, therefore, very wasteful in Monte Carlo shielding calculations. For example, in the source region and in regions far away from the detectors, the next-event contribution of a particle is often very small and insignificant. A method for reducing this inefficiency is described. (WHK)
Incidence and risk factors of probable dengue virus infection among Dutch travellers to Asia.
Cobelens, Frank G J; Groen, Jan; Osterhaus, Albert D M E; Leentvaar-Kuipers, Anne; Wertheim-van Dillen, Pauline M E; Kager, Piet A
2002-04-01
We studied the incidence of dengue virus (DEN) infections in a cohort of Dutch short-term travellers to endemic areas in Asia during 1991-92. Sera were collected before and after travel. All post-travel sera were tested for DEN immunoglobulin M (IgM) [IgM capture (MAC)-enzyme-linked immunosorbent assay (ELISA)] and IgG (indirect ELISA). Probable DEN infection was defined as IgM seroconversion or a fourfold rise in IgG ratio in the absence of cross-reaction with antibody to Japanese encephalitis virus (JEV). Infections were considered clinically apparent in case of febrile illness (> 24 H) with headache, myalgia, arthralgia or rash. Probable DEN infection was found in 13 of 447 travellers (incidence rate 30/1000 person-months, 95% CI 17.4-51.6). One infection was considered secondary; no haemorrhagic fever occurred. The clinical-to-subclinical infection rate was 1 : 3.3. The risk of infection showed marked seasonal variation. DEN infections are frequent in travellers to endemic areas in Asia; most remain subclinical.
Voon, Valerie; Morris, Laurel S; Irvine, Michael A; Ruck, Christian; Worbe, Yulia; Derbyshire, Katherine; Rankov, Vladan; Schreiber, Liana Rn; Odlaug, Brian L; Harrison, Neil A; Wood, Jonathan; Robbins, Trevor W; Bullmore, Edward T; Grant, Jon E
2015-03-01
Pathological behaviors toward drugs and food rewards have underlying commonalities. Risk-taking has a fourfold pattern varying as a function of probability and valence leading to the nonlinearity of probability weighting with overweighting of small probabilities and underweighting of large probabilities. Here we assess these influences on risk-taking in patients with pathological behaviors toward drug and food rewards and examine structural neural correlates of nonlinearity of probability weighting in healthy volunteers. In the anticipation of rewards, subjects with binge eating disorder show greater risk-taking, similar to substance-use disorders. Methamphetamine-dependent subjects had greater nonlinearity of probability weighting along with impaired subjective discrimination of probability and reward magnitude. Ex-smokers also had lower risk-taking to rewards compared with non-smokers. In the anticipation of losses, obesity without binge eating had a similar pattern to other substance-use disorders. Obese subjects with binge eating also have impaired discrimination of subjective value similar to that of the methamphetamine-dependent subjects. Nonlinearity of probability weighting was associated with lower gray matter volume in dorsolateral and ventromedial prefrontal cortex and orbitofrontal cortex in healthy volunteers. Our findings support a distinct subtype of binge eating disorder in obesity with similarities in risk-taking in the reward domain to substance use disorders. The results dovetail with the current approach of defining mechanistically based dimensional approaches rather than categorical approaches to psychiatric disorders. The relationship to risk probability and valence may underlie the propensity toward pathological behaviors toward different types of rewards.
Accurate Estimation of the Entropy of Rotation-Translation Probability Distributions.
Fogolari, Federico; Dongmo Foumthuim, Cedrix Jurgal; Fortuna, Sara; Soler, Miguel Angel; Corazza, Alessandra; Esposito, Gennaro
2016-01-12
The estimation of rotational and translational entropies in the context of ligand binding has been the subject of long-time investigations. The high dimensionality (six) of the problem and the limited amount of sampling often prevent the required resolution to provide accurate estimates by the histogram method. Recently, the nearest-neighbor distance method has been applied to the problem, but the solutions provided either address rotation and translation separately, therefore lacking correlations, or use a heuristic approach. Here we address rotational-translational entropy estimation in the context of nearest-neighbor-based entropy estimation, solve the problem numerically, and provide an exact and an approximate method to estimate the full rotational-translational entropy.
NASA Technical Reports Server (NTRS)
Pierson, Willard J., Jr.
1989-01-01
The values of the Normalized Radar Backscattering Cross Section (NRCS), sigma (o), obtained by a scatterometer are random variables whose variance is a known function of the expected value. The probability density function can be obtained from the normal distribution. Models for the expected value obtain it as a function of the properties of the waves on the ocean and the winds that generated the waves. Point estimates of the expected value were found from various statistics given the parameters that define the probability density function for each value. Random intervals were derived with a preassigned probability of containing that value. A statistical test to determine whether or not successive values of sigma (o) are truly independent was derived. The maximum likelihood estimates for wind speed and direction were found, given a model for backscatter as a function of the properties of the waves on the ocean. These estimates are biased as a result of the terms in the equation that involve natural logarithms, and calculations of the point estimates of the maximum likelihood values are used to show that the contributions of the logarithmic terms are negligible and that the terms can be omitted.
O'Donnell, Matthew J.; Horton, Gregg E.; Letcher, Benjamin H.
2010-01-01
Portable passive integrated transponder (PIT) tag antenna systems can be valuable in providing reliable estimates of the abundance of tagged Atlantic salmon Salmo salar in small streams under a wide range of conditions. We developed and employed PIT tag antenna wand techniques in two controlled experiments and an additional case study to examine the factors that influenced our ability to estimate population size. We used Pollock's robust-design capture–mark–recapture model to obtain estimates of the probability of first detection (p), the probability of redetection (c), and abundance (N) in the two controlled experiments. First, we conducted an experiment in which tags were hidden in fixed locations. Although p and c varied among the three observers and among the three passes that each observer conducted, the estimates of N were identical to the true values and did not vary among observers. In the second experiment using free-swimming tagged fish, p and c varied among passes and time of day. Additionally, estimates of N varied between day and night and among age-classes but were within 10% of the true population size. In the case study, we used the Cormack–Jolly–Seber model to examine the variation in p, and we compared counts of tagged fish found with the antenna wand with counts collected via electrofishing. In that study, we found that although p varied for age-classes, sample dates, and time of day, antenna and electrofishing estimates of N were similar, indicating that population size can be reliably estimated via PIT tag antenna wands. However, factors such as the observer, time of day, age of fish, and stream discharge can influence the initial and subsequent detection probabilities.
NASA Astrophysics Data System (ADS)
Cheng, Haowen; Liu, Jing; Xu, Yang
The evaluation of convariance-matrix is an inevitable step when estimating collision probability based on the theory. Generally, there are two different methods to compute convariance-matrix. One is so-called Tracking-Delta-Fitting method, first introduced when estimating the collision probability using TLE catalogue data, in which convariance-matrix is evaluated by fitting series of differences between propagated orbits of formal data and updated orbit data. In the second method, convariance-matrix is evaluated in the process of orbit determination. Both of the methods has there difficulties when introduced in collision probability estimation. In the first method, the value of convariance-matrix is evaluated based only on historical orbit data, ignoring information of latest orbit determination. As a result, the accuracy of the method strongly depends on the stability of convariance-matrix of latest updated orbit. In the second method, the evaluation of convariance-matrix is acceptable when the determined orbit satisfies weighted-least-square estimation, depending on the accuracy of observation error convariance, which is hard to obtain in real application, evaluated by analyzing the residuals of orbit determination in our research. In this paper we provided numerical tests to compare these two methods. A simulation of cataloguing objects in LEO, MEO and GEO regions has been carried out for a time span of 3 months. The influence of orbit maneuver has been included in GEO objects cataloguing simulation. For LEO objects cataloguing, the effect of atmospheric density variation has also been considered. At the end of the paper accuracies of evaluated convariance-matrix and estimated collision probability have been tested and compared.
Segalman, D.; Reese, G.
1998-09-01
The von Mises stress is often used as the metric for evaluating design margins, particularly for structures made of ductile materials. For deterministic loads, both static and dynamic, the calculation of von Mises stress is straightforward, as is the resulting calculation of reliability. For loads modeled as random processes, the task is different; the response to such loads is itself a random process and its properties must be determined in terms of those of both the loads and the system. This has been done in the past by Monte Carlo sampling of numerical realizations that reproduce the second order statistics of the problem. Here, the authors present a method that provides analytic expressions for the probability distributions of von Mises stress which can be evaluated efficiently and with good precision numerically. Further, this new approach has the important advantage of providing the asymptotic properties of the probability distribution.
A novel approach to estimate the eruptive potential and probability in open conduit volcanoes.
De Gregorio, Sofia; Camarda, Marco
2016-07-26
In open conduit volcanoes, volatile-rich magma continuously enters into the feeding system nevertheless the eruptive activity occurs intermittently. From a practical perspective, the continuous steady input of magma in the feeding system is not able to produce eruptive events alone, but rather surplus of magma inputs are required to trigger the eruptive activity. The greater the amount of surplus of magma within the feeding system, the higher is the eruptive probability.Despite this observation, eruptive potential evaluations are commonly based on the regular magma supply, and in eruptive probability evaluations, generally any magma input has the same weight. Conversely, herein we present a novel approach based on the quantification of surplus of magma progressively intruded in the feeding system. To quantify the surplus of magma, we suggest to process temporal series of measurable parameters linked to the magma supply. We successfully performed a practical application on Mt Etna using the soil CO2 flux recorded over ten years.
A novel approach to estimate the eruptive potential and probability in open conduit volcanoes
De Gregorio, Sofia; Camarda, Marco
2016-01-01
In open conduit volcanoes, volatile-rich magma continuously enters into the feeding system nevertheless the eruptive activity occurs intermittently. From a practical perspective, the continuous steady input of magma in the feeding system is not able to produce eruptive events alone, but rather surplus of magma inputs are required to trigger the eruptive activity. The greater the amount of surplus of magma within the feeding system, the higher is the eruptive probability.Despite this observation, eruptive potential evaluations are commonly based on the regular magma supply, and in eruptive probability evaluations, generally any magma input has the same weight. Conversely, herein we present a novel approach based on the quantification of surplus of magma progressively intruded in the feeding system. To quantify the surplus of magma, we suggest to process temporal series of measurable parameters linked to the magma supply. We successfully performed a practical application on Mt Etna using the soil CO2 flux recorded over ten years. PMID:27456812
A novel approach to estimate the eruptive potential and probability in open conduit volcanoes.
De Gregorio, Sofia; Camarda, Marco
2016-01-01
In open conduit volcanoes, volatile-rich magma continuously enters into the feeding system nevertheless the eruptive activity occurs intermittently. From a practical perspective, the continuous steady input of magma in the feeding system is not able to produce eruptive events alone, but rather surplus of magma inputs are required to trigger the eruptive activity. The greater the amount of surplus of magma within the feeding system, the higher is the eruptive probability.Despite this observation, eruptive potential evaluations are commonly based on the regular magma supply, and in eruptive probability evaluations, generally any magma input has the same weight. Conversely, herein we present a novel approach based on the quantification of surplus of magma progressively intruded in the feeding system. To quantify the surplus of magma, we suggest to process temporal series of measurable parameters linked to the magma supply. We successfully performed a practical application on Mt Etna using the soil CO2 flux recorded over ten years. PMID:27456812
A novel approach to estimate the eruptive potential and probability in open conduit volcanoes
NASA Astrophysics Data System (ADS)
de Gregorio, Sofia; Camarda, Marco
2016-07-01
In open conduit volcanoes, volatile-rich magma continuously enters into the feeding system nevertheless the eruptive activity occurs intermittently. From a practical perspective, the continuous steady input of magma in the feeding system is not able to produce eruptive events alone, but rather surplus of magma inputs are required to trigger the eruptive activity. The greater the amount of surplus of magma within the feeding system, the higher is the eruptive probability.Despite this observation, eruptive potential evaluations are commonly based on the regular magma supply, and in eruptive probability evaluations, generally any magma input has the same weight. Conversely, herein we present a novel approach based on the quantification of surplus of magma progressively intruded in the feeding system. To quantify the surplus of magma, we suggest to process temporal series of measurable parameters linked to the magma supply. We successfully performed a practical application on Mt Etna using the soil CO2 flux recorded over ten years.
Information geometric algorithm for estimating switching probabilities in space-varying HMM.
Nascimento, Jacinto C; Barão, Miguel; Marques, Jorge S; Lemos, João M
2014-12-01
This paper proposes an iterative natural gradient algorithm to perform the optimization of switching probabilities in a space-varying hidden Markov model, in the context of human activity recognition in long-range surveillance. The proposed method is a version of the gradient method, developed under an information geometric viewpoint, where the usual Euclidean metric is replaced by a Riemannian metric on the space of transition probabilities. It is shown that the change in metric provides advantages over more traditional approaches, namely: 1) it turns the original constrained optimization into an unconstrained optimization problem; 2) the optimization behaves asymptotically as a Newton method and yields faster convergence than other methods for the same computational complexity; and 3) the natural gradient vector is an actual contravariant vector on the space of probability distributions for which an interpretation as the steepest descent direction is formally correct. Experiments on synthetic and real-world problems, focused on human activity recognition in long-range surveillance settings, show that the proposed methodology compares favorably with the state-of-the-art algorithms developed for the same purpose.
Exposure corrected risk estimates for childhood product related injuries.
Senturia, Y D; Binns, H J; Christoffel, K K; Tanz, R R
1993-08-01
This study assesses the effect of exposure correction on injury risk estimates for children, using Chicago-area survey data on age-specific exposure of children to seven products: amusement park rides, sleds, bunkbeds, skateboards, fireworks, toboggans, and air guns and rifles. National Electronic Injury Surveillance System estimates for 1987 were used as numerators with two denominators: (i) uncorrected age-specific U.S. Census estimates for 1987 and (ii) these estimates corrected for exposure. Except for bunkbeds, skateboards and sleds, corrected injury risk decreased as age increased. Uncorrected population injury rates underestimated the risk posed to product-using children, especially those who are youngest and those who use skateboards.
NASA Astrophysics Data System (ADS)
Tan, Elcin
A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the
O'Doherty, Kieran C
2007-02-01
The question of what probability actually is has long been debated in philosophy and statistics. Although the concept of probability is fundamental to many applications in the health sciences, these debates are generally not well known to health professionals. This paper begins with an outline of some of the different interpretations of probability. Examples are provided of how each interpretation manifests in clinical practice. The discipline of genetic counselling (familial cancer) is used to ground the discussion. In the second part of the paper, some of the implications that different interpretations of probability may have in practice are examined. The main purpose of the paper is to draw attention to the fact that there is much contention as to the nature of the concept of probability. In practice, this creates the potential for ambiguity and confusion. This paper constitutes a call for deeper engagement with the ways in which probability and risk are understood in health research and practice.
Bistatic-radar estimation of surface-slope probability distributions with applications to the moon.
NASA Technical Reports Server (NTRS)
Parker, M. N.; Tyler, G. L.
1973-01-01
A method for extracting surface-slope frequency distributions from bistatic-radar data has been developed and applied to the lunar surface. Telemetry transmissions from orbiting Apollo spacecraft were received on the earth after reflection from the lunar surface. The echo-frequency spectrum was related analytically to the probability distribution of lunar slopes. Standard regression techniques were used to solve the inverse problem of finding slope distributions from observed echo-frequency spectra. Data taken simultaneously at two wavelengths, 13 and 116 cm, have yielded diverse slope statistics.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa; Roeder, WIlliam P.; Merceret, Francis J.
2011-01-01
A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station. Future applications could include forensic meteorology.
Development of a statistical tool for the estimation of riverbank erosion probability
NASA Astrophysics Data System (ADS)
Varouchakis, E. A.; Giannakis, G. V.; Lilli, M. A.; Ioannidou, E.; Nikolaidis, N. P.; Karatzas, G. P.
2016-01-01
Riverbank erosion affects river morphology and local habitat, and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict areas vulnerable to erosion is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a statistical methodology is proposed to predict the probability of the presence or absence of erosion in a river section. A physically based model determines the locations vulnerable to erosion by quantifying the potential eroded area. The derived results are used to determine validation locations for the evaluation of the statistical tool performance. The statistical tool is based on a series of independent local variables and employs the logistic regression methodology. It is developed in two forms, logistic regression and locally weighted logistic regression, which both deliver useful and accurate results. The second form, though, provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed tool is easy to use and accurate and can be applied to any region and river.
Development of a statistical tool for the estimation of riverbank erosion probability
NASA Astrophysics Data System (ADS)
Varouchakis, E. A.; Giannakis, G. V.; Lilli, M. A.; Ioannidou, E.; Nikolaidis, N. P.; Karatzas, G. P.
2015-06-01
Riverbank erosion affects river morphology and local habitat and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict vulnerable to erosion areas is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a combined deterministic and statistical methodology is proposed to predict the probability of presence or absence of erosion in a river section. A physically based model determines the vulnerable to erosion locations by quantifying the potential eroded area. The derived results are used to determine validation locations for the statistical tool performance evaluation. The statistical tool is based on a series of independent local variables and employs the Logistic Regression methodology. It is developed in two forms, Logistic Regression and Locally Weighted Logistic Regression, which both deliver useful and accurate results. The second form though provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed methodology is easy to use, accurate and can be applied to any region and river.
Kibblewhite, M G; Bellamy, P H; Brewer, T R; Graves, A R; Dawson, C A; Rickson, R J; Truckell, I; Stuart, J
2014-03-01
Methods for the spatial estimation of risk of harm to soil by erosion by water and wind and by soil organic matter decline are explored. Rates of harm are estimated for combinations of soil type and land cover (as a proxy for hazard frequency) and used to estimate risk of soil erosion and loss of soil organic carbon (SOC) for 1 km(2)pixels. Scenarios are proposed for defining the acceptability of risk of harm to soil: the most precautionary one corresponds to no net harm after natural regeneration of soil (i.e. a 1 in 20 chance of exceeding an erosion rate of <1 tha(-1)y(-1) and SOC content decline of 0 kg t(-1)y(-1) for mineral soils and a carbon stock decline of 0 tha(-1)y(-1) for organic soils). Areas at higher and lower than possible acceptable risk are mapped. The veracity of boundaries is compromised if areas of unacceptable risk are mapped to administrative boundaries. Errors in monitoring change in risk of harm to soil and inadequate information on risk reduction measures' efficacy, at landscape scales, make it impossible to use or monitor quantitative targets for risk reduction adequately. The consequences for priority area definition of expressing varying acceptable risk of harm to soil as a varying probability of exceeding a fixed level of harm, or, a varying level of harm being exceeded with a fixed probability, are discussed. Soil data and predictive models for rates of harm to soil would need considerable development and validation to implement a priority area approach robustly. PMID:24412915
Kibblewhite, M G; Bellamy, P H; Brewer, T R; Graves, A R; Dawson, C A; Rickson, R J; Truckell, I; Stuart, J
2014-03-01
Methods for the spatial estimation of risk of harm to soil by erosion by water and wind and by soil organic matter decline are explored. Rates of harm are estimated for combinations of soil type and land cover (as a proxy for hazard frequency) and used to estimate risk of soil erosion and loss of soil organic carbon (SOC) for 1 km(2)pixels. Scenarios are proposed for defining the acceptability of risk of harm to soil: the most precautionary one corresponds to no net harm after natural regeneration of soil (i.e. a 1 in 20 chance of exceeding an erosion rate of <1 tha(-1)y(-1) and SOC content decline of 0 kg t(-1)y(-1) for mineral soils and a carbon stock decline of 0 tha(-1)y(-1) for organic soils). Areas at higher and lower than possible acceptable risk are mapped. The veracity of boundaries is compromised if areas of unacceptable risk are mapped to administrative boundaries. Errors in monitoring change in risk of harm to soil and inadequate information on risk reduction measures' efficacy, at landscape scales, make it impossible to use or monitor quantitative targets for risk reduction adequately. The consequences for priority area definition of expressing varying acceptable risk of harm to soil as a varying probability of exceeding a fixed level of harm, or, a varying level of harm being exceeded with a fixed probability, are discussed. Soil data and predictive models for rates of harm to soil would need considerable development and validation to implement a priority area approach robustly.
Wu, Shih-Wei; Delgado, Mauricio R; Maloney, Laurence T
2011-06-15
In decision under risk, people choose between lotteries that contain a list of potential outcomes paired with their probabilities of occurrence. We previously developed a method for translating such lotteries to mathematically equivalent "motor lotteries." The probability of each outcome in a motor lottery is determined by the subject's noise in executing a movement. In this study, we used functional magnetic resonance imaging in humans to compare the neural correlates of monetary outcome and probability in classical lottery tasks in which information about probability was explicitly communicated to the subjects and in mathematically equivalent motor lottery tasks in which probability was implicit in the subjects' own motor noise. We found that activity in the medial prefrontal cortex (mPFC) and the posterior cingulate cortex quantitatively represent the subjective utility of monetary outcome in both tasks. For probability, we found that the mPFC significantly tracked the distortion of such information in both tasks. Specifically, activity in mPFC represents probability information but not the physical properties of the stimuli correlated with this information. Together, the results demonstrate that mPFC represents probability from two distinct forms of decision under risk.
Precise, unbiased estimates of population size are an essential tool for fisheries management. For a wide variety of salmonid fishes, redd counts from a sample of reaches are commonly used to monitor annual trends in abundance. Using a 9-year time series of georeferenced censuses...
Radiobiologic risk estimation from dental radiology. Part II. Cancer incidence and fatality
Underhill, T.E.; Kimura, K.; Chilvarquer, I.; McDavid, W.D.; Langlais, R.P.; Preece, J.W.; Barnwell, G.
1988-08-01
With the use of the measured absorbed doses from part I of this article, the specific radiobiologic risk to the patient from (1) five different panoramic machines with rare-earth screens, (2) a 20-film complete-mouth survey with E-speed film, long round cone, (3) a 20-film complete-mouth survey with E-speed film, long rectangular cone, (4) a 4-film interproximal survey with E-speed film, long round cone, and (5) a 4-film interproximal survey with E-speed film, long rectangular cone, was calculated. The estimated risks are expressed in two ways: the probability of radiation-induced cancer in specific organs per million examinations and the probability of expression of a fatal cancer per million examinations. The highest risks calculated were from the complete-mouth survey with the use of round collimation. The lowest risks calculated were from panoramic radiography and four interproximal radiographs with rectangular collimation.
Radiobiologic risk estimation from dental radiology. Part II. Cancer incidence and fatality.
Underhill, T E; Kimura, K; Chilvarquer, I; McDavid, W D; Langlais, R P; Preece, J W; Barnwell, G
1988-08-01
With the use of the measured absorbed doses from part I of this article, the specific radiobiologic risk to the patient from (1) five different panoramic machines with rare-earth screens, (2) a 20-film complete-mouth survey with E-speed film, long round cone, (3) a 20-film complete-mouth survey with E-speed film, long rectangular cone, (4) a 4-film interproximal survey with E-speed film, long round cone, and (5) a 4-film interproximal survey with E-speed film, long rectangular cone, was calculated. The estimated risks are expressed in two ways: the probability of radiation-induced cancer in specific organs per million examinations and the probability of expression of a fatal cancer per million examinations. The highest risks calculated were from the complete-mouth survey with the use of round collimation. The lowest risks calculated were from panoramic radiography and four interproximal radiographs with rectangular collimation.
Political risk in fair market value estimates
Gruy, H.J.; Hartsock, J.H.
1996-09-01
Political risk arises from unstable governments, commercial establishments and infrastructure as well as labor unrest. All these factors vary from country to country and from time to time. Banks and insurance companies quantify these risks, but they are reluctant to divulge their opinions for fear of alienating possible customers that have been assigned a high risk. An investment in a fixed property such as an oil and gas lease, concession or other mineral interest is subject to political risk. No one will deny that money to be received several years in the future has a greater value today in a country with a stable government, stable tax regime, a sound economy and reliable labor force than in a Third World country where a revolution is brewing. Even in stable countries, the risk of tax law changes, exorbitant environmental production regulations and cleanup costs may vary. How do these factors affect fair market value and how are these calculations made? An important consideration discussed in this paper is the treatment of capital investments.
Luo, Lola; Small, Dylan; Stewart, Walter F.; Roy, Jason A.
2013-01-01
Chronic diseases are often described by stages of severity. Clinical decisions about what to do are influenced by the stage, whether a patient is progressing, and the rate of progression. For chronic kidney disease (CKD), relatively little is known about the transition rates between stages. To address this, we used electronic health records (EHR) data on a large primary care population, which should have the advantage of having both sufficient follow-up time and sample size to reliably estimate transition rates for CKD. However, EHR data have some features that threaten the validity of any analysis. In particular, the timing and frequency of laboratory values and clinical measurements are not determined a priori by research investigators, but rather, depend on many factors, including the current health of the patient. We developed an approach for estimating CKD stage transition rates using hidden Markov models (HMMs), when the level of information and observation time vary among individuals. To estimate the HMMs in a computationally manageable way, we used a “discretization” method to transform daily data into intervals of 30 days, 90 days, or 180 days. We assessed the accuracy and computation time of this method via simulation studies. We also used simulations to study the effect of informative observation times on the estimated transition rates. Our simulation results showed good performance of the method, even when missing data are non-ignorable. We applied the methods to EHR data from over 60,000 primary care patients who have chronic kidney disease (stage 2 and above). We estimated transition rates between six underlying disease states. The results were similar for men and women. PMID:25848580
Parametric Estimation in a Recurrent Competing Risks Model
Peña, Edsel A.
2014-01-01
A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the competing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. Maximum likelihood estimators of the parameters of the marginal distribution functions associated with each of the competing risks and also of the system lifetime distribution function are presented. Estimators are derived under perfect and partial repair strategies. Consistency and asymptotic properties of the estimators are obtained. The estimation methods are applied to a data set of failures for cars under warranty. Simulation studies are used to ascertain the small sample properties and the efficiency gains of the resulting estimators. PMID:25346751
Arnold, W Ray; Warren-Hicks, William J
2007-01-01
The object of this study was to estimate site- and region-specific dissolved copper criteria for a large embayment, the Chesapeake Bay, USA. The intent is to show the utility of 2 copper saltwater quality site-specific criteria estimation models and associated region-specific criteria selection methods. The criteria estimation models and selection methods are simple, efficient, and cost-effective tools for resource managers. The methods are proposed as potential substitutes for the US Environmental Protection Agency's water effect ratio methods. Dissolved organic carbon data and the copper criteria models were used to produce probability-based estimates of site-specific copper saltwater quality criteria. Site- and date-specific criteria estimations were made for 88 sites (n = 5,296) in the Chesapeake Bay. The average and range of estimated site-specific chronic dissolved copper criteria for the Chesapeake Bay were 7.5 and 5.3 to 16.9 microg Cu/L. The average and range of estimated site-specific acute dissolved copper criteria for the Chesapeake Bay were 11.7 and 8.3 to 26.4 microg Cu/L. The results suggest that applicable national and state copper criteria can increase in much of the Chesapeake Bay and remain protective. Virginia Department of Environmental Quality copper criteria near the mouth of the Chesapeake Bay, however, need to decrease to protect species of equal or greater sensitivity to that of the marine mussel, Mytilus sp.
Park, Dong-Uk; Colt, Joanne S.; Baris, Dalsu; Schwenn, Molly; Karagas, Margaret R.; Armenti, Karla R.; Johnson, Alison; Silverman, Debra T; Stewart, Patricia A
2014-01-01
We describe here an approach for estimating the probability that study subjects were exposed to metalworking fluids (MWFs) in a population-based case-control study of bladder cancer. Study subject reports on the frequency of machining and use of specific MWFs (straight, soluble, and synthetic/semi-synthetic) were used to estimate exposure probability when available. Those reports also were used to develop estimates for job groups, which were then applied to jobs without MWF reports. Estimates using both cases and controls and controls only were developed. The prevalence of machining varied substantially across job groups (10-90%), with the greatest percentage of jobs that machined being reported by machinists and tool and die workers. Reports of straight and soluble MWF use were fairly consistent across job groups (generally, 50-70%). Synthetic MWF use was lower (13-45%). There was little difference in reports by cases and controls vs. controls only. Approximately, 1% of the entire study population was assessed as definitely exposed to straight or soluble fluids in contrast to 0.2% definitely exposed to synthetic/semi-synthetics. A comparison between the reported use of the MWFs and the US production levels by decade found high correlations (r generally >0.7). Overall, the method described here is likely to have provided a systematic and reliable ranking that better reflects the variability of exposure to three types of MWFs than approaches applied in the past. PMID:25256317
Wullenweber, Andrea; Kroner, Oliver; Kohrman, Melissa; Maier, Andrew; Dourson, Michael; Rak, Andrew; Wexler, Philip; Tomljanovic, Chuck
2008-11-15
The rate of chemical synthesis and use has outpaced the development of risk values and the resolution of risk assessment methodology questions. In addition, available risk values derived by different organizations may vary due to scientific judgments, mission of the organization, or use of more recently published data. Further, each organization derives values for a unique chemical list so it can be challenging to locate data on a given chemical. Two Internet resources are available to address these issues. First, the International Toxicity Estimates for Risk (ITER) database (www.tera.org/iter) provides chronic human health risk assessment data from a variety of organizations worldwide in a side-by-side format, explains differences in risk values derived by different organizations, and links directly to each organization's website for more detailed information. It is also the only database that includes risk information from independent parties whose risk values have undergone independent peer review. Second, the Risk Information Exchange (RiskIE) is a database of in progress chemical risk assessment work, and includes non-chemical information related to human health risk assessment, such as training modules, white papers and risk documents. RiskIE is available at http://www.allianceforrisk.org/RiskIE.htm, and will join ITER on National Library of Medicine's TOXNET (http://toxnet.nlm.nih.gov/). Together, ITER and RiskIE provide risk assessors essential tools for easily identifying and comparing available risk data, for sharing in progress assessments, and for enhancing interaction among risk assessment groups to decrease duplication of effort and to harmonize risk assessment procedures across organizations.
Wullenweber, Andrea Kroner, Oliver; Kohrman, Melissa; Maier, Andrew; Dourson, Michael; Rak, Andrew; Wexler, Philip; Tomljanovic, Chuck
2008-11-15
The rate of chemical synthesis and use has outpaced the development of risk values and the resolution of risk assessment methodology questions. In addition, available risk values derived by different organizations may vary due to scientific judgments, mission of the organization, or use of more recently published data. Further, each organization derives values for a unique chemical list so it can be challenging to locate data on a given chemical. Two Internet resources are available to address these issues. First, the International Toxicity Estimates for Risk (ITER) database ( (www.tera.org/iter)) provides chronic human health risk assessment data from a variety of organizations worldwide in a side-by-side format, explains differences in risk values derived by different organizations, and links directly to each organization's website for more detailed information. It is also the only database that includes risk information from independent parties whose risk values have undergone independent peer review. Second, the Risk Information Exchange (RiskIE) is a database of in progress chemical risk assessment work, and includes non-chemical information related to human health risk assessment, such as training modules, white papers and risk documents. RiskIE is available at (http://www.allianceforrisk.org/RiskIE.htm), and will join ITER on National Library of Medicine's TOXNET ( (http://toxnet.nlm.nih.gov/)). Together, ITER and RiskIE provide risk assessors essential tools for easily identifying and comparing available risk data, for sharing in progress assessments, and for enhancing interaction among risk assessment groups to decrease duplication of effort and to harmonize risk assessment procedures across organizations.
NASA Astrophysics Data System (ADS)
Katsura, K.; Ogata, Y.
2004-12-01
Reasenberg and Jones [Science, 1989, 1994] proposed the aftershock probability forecasting based on the joint distribution [Utsu, J. Fac. Sci. Hokkaido Univ., 1970] of the modified Omori formula of aftershock decay and Gutenberg-Richter law of magnitude frequency, where the respective parameters are estimated by the maximum likelihood method [Ogata, J. Phys. Earth, 1983; Utsu, Geophys Bull. Hokkaido Univ., 1965, Aki, Bull. Earthq. Res. Inst., 1965]. The public forecast has been implemented by the responsible agencies in California and Japan. However, a considerable difficulty in the above procedure is that, due to the contamination of arriving seismic waves, detection rate of aftershocks is extremely low during a period immediately after the main shock, say, during the first day, when the forecasting is most critical for public in the affected area. Therefore, for the forecasting of a probability during such a period, they adopt a generic model with a set of the standard parameter values in California or Japan. For an effective and realistic estimation, I propose to utilize the statistical model introduced by Ogata and Katsura [Geophys. J. Int., 1993] for the simultaneous estimation of the b-values of Gutenberg-Richter law together with detection-rate (probability) of earthquakes of each magnitude-band from the provided data of all detected events, where the both parameters are allowed for changing in time. Thus, by using all detected aftershocks from the beginning of the period, we can estimate the underlying modified Omori rate of both detected and undetected events and their b-value changes, taking the time-varying missing rates of events into account. The similar computation is applied to the ETAS model for complex aftershock activity or regional seismicity where substantial missing events are expected immediately after a large aftershock or another strong earthquake in the vicinity. Demonstrations of the present procedure will be shown for the recent examples
Miles McQueen; Wayne Boyer; Mark Flynn; Sam Alessi
2006-03-01
For the past year we have applied a variety of risk assessment technologies to evaluate the risk to critical infrastructure from cyber attacks on control systems. More recently, we identified the need for a stand alone control system risk reduction estimation tool to provide owners and operators of control systems with a more useable, reliable, and credible method for managing the risks from cyber attack. Risk is defined as the probability of a successful attack times the value of the resulting loss, typically measured in lives and dollars. Qualitative and ad hoc techniques for measuring risk do not provide sufficient support for cost benefit analyses associated with cyber security mitigation actions. To address the need for better quantitative risk reduction models we surveyed previous quantitative risk assessment research; evaluated currently available tools; developed new quantitative techniques [17] [18]; implemented a prototype analysis tool to demonstrate how such a tool might be used; used the prototype to test a variety of underlying risk calculational engines (e.g. attack tree, attack graph); and identified technical and research needs. We concluded that significant gaps still exist and difficult research problems remain for quantitatively assessing the risk to control system components and networks, but that a useable quantitative risk reduction estimation tool is not beyond reach.
NASA Astrophysics Data System (ADS)
Mountcastle, Donald B.; Bucy, Brandon R.; Thompson, John R.
2007-11-01
Equilibrium properties of macroscopic systems are highly predictable as n, the number of particles approaches and exceeds Avogadro's number; theories of statistical physics depend on these results. Typical pedagogical devices used in statistical physics textbooks to introduce entropy (S) and multiplicity (ω) (where S = k ln(ω)) include flipping coins and/or other equivalent binary events, repeated n times. Prior to instruction, our statistical mechanics students usually gave reasonable answers about the probabilities, but not the relative uncertainties, of the predicted outcomes of such events. However, they reliably predicted that the uncertainty in a measured continuous quantity (e.g., the amount of rainfall) does decrease as the number of measurements increases. Typical textbook presentations assume that students understand that the relative uncertainty of binary outcomes will similarly decrease as the number of events increases. This is at odds with our findings, even though most of our students had previously completed mathematics courses in statistics, as well as an advanced electronics laboratory course that included statistical analysis of distributions of dart scores as n increased.
A physically-based earthquake recurrence model for estimation of long-term earthquake probabilities
Ellsworth, William L.; Matthews, Mark V.; Nadeau, Robert M.; Nishenko, Stuart P.; Reasenberg, Paul A.; Simpson, Robert W.
1999-01-01
A physically-motivated model for earthquake recurrence based on the Brownian relaxation oscillator is introduced. The renewal process defining this point process model can be described by the steady rise of a state variable from the ground state to failure threshold as modulated by Brownian motion. Failure times in this model follow the Brownian passage time (BPT) distribution, which is specified by the mean time to failure, μ, and the aperiodicity of the mean, α (equivalent to the familiar coefficient of variation). Analysis of 37 series of recurrent earthquakes, M -0.7 to 9.2, suggests a provisional generic value of α = 0.5. For this value of α, the hazard function (instantaneous failure rate of survivors) exceeds the mean rate for times > μ⁄2, and is ~ ~ 2 ⁄ μ for all times > μ. Application of this model to the next M 6 earthquake on the San Andreas fault at Parkfield, California suggests that the annual probability of the earthquake is between 1:10 and 1:13.
Giacovazzo; Siliqi; Fernández-Castaño; Comunale
1999-05-01
The probabilistic formulae [Giacovazzo, Siliqi & Fernández-Castaño (1999). Acta Cryst. A55, 512-524] relating standard and half-integral index reflections are modified for practical applications. The experimental tests prove the reliability of the probabilistic relationships. The approach is further developed to explore whether the moduli of the half-integral index reflections can be evaluated in the absence of phase information; i.e. by exploiting the moduli of the standard reflections only. The final formulae indicate that estimates can be obtained, even though the reliability factor is a constant.
Estimates of coextinction risk: how anuran parasites respond to the extinction of their hosts.
Campião, Karla Magalhães; de Aquino Ribas, Augusto Cesar; Cornell, Stephen J; Begon, Michael; Tavares, Luiz Eduardo Roland
2015-12-01
Amphibians are known as the most threatened vertebrate group. One of the outcomes of a species' extinction is the coextinction of its dependents. Here, we estimate the extinction risk of helminth parasites of South America anurans. Parasite coextinction probabilities were modeled, assuming parasite specificity and host vulnerability to extinction as determinants. Parasite species associated with few hosts were the most prone to extinction, and extinction risk varied amongst helminth species of different taxonomic groups and life cycle complexity. Considering host vulnerability in the model decreased the extinction probability of most parasites species. However, parasite specificity and host vulnerability combined to increase the extinction probabilities of 44% of the helminth species reported in a single anuran species.
Estimating Fire Risks at Industrial Nuclear Facilities
Coutts, D.A.
1999-07-12
The Savannah River Site (SRS) has a wide variety of nuclear production facilities that include chemical processing facilities, machine shops, production reactors, and laboratories. Current safety documentation must be maintained for the nuclear facilities at SRS. Fire Risk Analyses (FRAs) are used to support the safety documentation basis. These FRAs present the frequency that specified radiological and chemical consequences will be exceeded. The consequence values are based on mechanistic models assuming specific fire protection features fail to function as designed.
Xiao, Mingqing; Reeve, John D; Xu, Dashun; Cronin, James T
2013-09-01
One of the fundamental goals of ecology is to examine how dispersal affects the distribution and dynamics of insects across natural landscapes. These landscapes are frequently divided into patches of habitat embedded in a matrix of several non-habitat regions, and dispersal behavior could vary within each landscape element as well as the edges between elements. Reaction-diffusion models are a common way of modeling dispersal and species interactions in such landscapes, but to apply these models we also need methods of estimating the diffusion rate and any edge behavior parameters. In this paper, we present a method of estimating the diffusion rate using the mean occupancy time for a circular region. We also use mean occupancy time to estimate a parameter (the crossing probability) that governs one type of edge behavior often used in these models, a biased random walk. These new methods have some advantages over other methods of estimating these parameters, including reduced computational cost and ease of use in the field. They also provide a method of estimating the diffusion rate for a particular location in space, compared to existing methods that represent averages over large areas. We further examine the statistical properties of the new method through simulation, and discuss how mean occupancy time could be estimated in field experiments.
Soil-ecological risks for soil degradation estimation
NASA Astrophysics Data System (ADS)
Trifonova, Tatiana; Shirkin, Leonid; Kust, German; Andreeva, Olga
2016-04-01
Soil degradation includes the processes of soil properties and quality worsening, primarily from the point of view of their productivity and decrease of ecosystem services quality. Complete soil cover destruction and/or functioning termination of soil forms of organic life are considered as extreme stages of soil degradation, and for the fragile ecosystems they are normally considered in the network of their desertification, land degradation and droughts /DLDD/ concept. Block-model of ecotoxic effects, generating soil and ecosystem degradation, has been developed as a result of the long-term field and laboratory research of sod-podzol soils, contaminated with waste, containing heavy metals. The model highlights soil degradation mechanisms, caused by direct and indirect impact of ecotoxicants on "phytocenosis- soil" system and their combination, frequently causing synergistic effect. The sequence of occurring changes here can be formalized as a theory of change (succession of interrelated events). Several stages are distinguished here - from heavy metals leaching (releasing) in waste and their migration downward the soil profile to phytoproductivity decrease and certain phytocenosis composition changes. Phytoproductivity decrease leads to the reduction of cellulose content introduced into the soil. The described feedback mechanism acts as a factor of sod-podzolic soil self-purification and stability. It has been shown, that using phytomass productivity index, integrally reflecting the worsening of soil properties complex, it is possible to solve the problems dealing with the dose-reflecting reactions creation and determination of critical levels of load for phytocenosis and corresponding soil-ecological risks. Soil-ecological risk in "phytocenosis- soil" system means probable negative changes and the loss of some ecosystem functions during the transformation process of dead organic substance energy for the new biomass composition. Soil-ecological risks estimation is
Juslin, Peter; Lindskog, Marcus; Mayerhofer, Bastian
2015-03-01
While a wealth of evidence suggests that humans tend to rely on additive cue combination to make controlled judgments, many of the normative rules for probability combination require multiplicative combination. In this article, the authors combine the experimental paradigms on probability reasoning and multiple-cue judgment to allow a comparison between formally identical tasks that involve probability vs. other task contents. The purpose was to investigate if people have cognitive algorithms for the combination, specifically, of probability, affording multiplicative combination in the context of probability. Three experiments suggest that, although people show some signs of a qualitative understanding of the combination rules that are specific to probability, in all but the simplest cases they lack the cognitive algorithms needed for multiplication, but instead use a variety of additive heuristics to approximate the normative combination. Although these heuristics are surprisingly accurate, normative combination is not consistently achieved until the problems are framed in an additive way.
Juslin, Peter; Lindskog, Marcus; Mayerhofer, Bastian
2015-03-01
While a wealth of evidence suggests that humans tend to rely on additive cue combination to make controlled judgments, many of the normative rules for probability combination require multiplicative combination. In this article, the authors combine the experimental paradigms on probability reasoning and multiple-cue judgment to allow a comparison between formally identical tasks that involve probability vs. other task contents. The purpose was to investigate if people have cognitive algorithms for the combination, specifically, of probability, affording multiplicative combination in the context of probability. Three experiments suggest that, although people show some signs of a qualitative understanding of the combination rules that are specific to probability, in all but the simplest cases they lack the cognitive algorithms needed for multiplication, but instead use a variety of additive heuristics to approximate the normative combination. Although these heuristics are surprisingly accurate, normative combination is not consistently achieved until the problems are framed in an additive way. PMID:25514208
Krzyzak, A; Linder, T; Lugosi, C
1996-01-01
Studies convergence properties of radial basis function (RBF) networks for a large class of basis functions, and reviews the methods and results related to this topic. The authors obtain the network parameters through empirical risk minimization. The authors show the optimal nets to be consistent in the problem of nonlinear function approximation and in nonparametric classification. For the classification problem the authors consider two approaches: the selection of the RBF classifier via nonlinear function estimation and the direct method of minimizing the empirical error probability. The tools used in the analysis include distribution-free nonasymptotic probability inequalities and covering numbers for classes of functions.
Uncertainties in Estimates of the Risks of Late Effects from Space Radiation
NASA Technical Reports Server (NTRS)
Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Saganti, P.; Dicelli, J. F.
2002-01-01
The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.
Amundson, Courtney L.; Royle, J. Andrew; Handel, Colleen M.
2014-01-01
Imperfect detection during animal surveys biases estimates of abundance and can lead to improper conclusions regarding distribution and population trends. Farnsworth et al. (2005) developed a combined distance-sampling and time-removal model for point-transect surveys that addresses both availability (the probability that an animal is available for detection; e.g., that a bird sings) and perceptibility (the probability that an observer detects an animal, given that it is available for detection). We developed a hierarchical extension of the combined model that provides an integrated analysis framework for a collection of survey points at which both distance from the observer and time of initial detection are recorded. Implemented in a Bayesian framework, this extension facilitates evaluating covariates on abundance and detection probability, incorporating excess zero counts (i.e. zero-inflation), accounting for spatial autocorrelation, and estimating population density. Species-specific characteristics, such as behavioral displays and territorial dispersion, may lead to different patterns of availability and perceptibility, which may, in turn, influence the performance of such hierarchical models. Therefore, we first test our proposed model using simulated data under different scenarios of availability and perceptibility. We then illustrate its performance with empirical point-transect data for a songbird that consistently produces loud, frequent, primarily auditory signals, the Golden-crowned Sparrow (Zonotrichia atricapilla); and for 2 ptarmigan species (Lagopus spp.) that produce more intermittent, subtle, and primarily visual cues. Data were collected by multiple observers along point transects across a broad landscape in southwest Alaska, so we evaluated point-level covariates on perceptibility (observer and habitat), availability (date within season and time of day), and abundance (habitat, elevation, and slope), and included a nested point
Analysis of a probability-based SATCOM situational awareness model for parameter estimation
NASA Astrophysics Data System (ADS)
Martin, Todd W.; Chang, Kuo-Chu; Tian, Xin; Chen, Genshe
2016-05-01
Emerging satellite communication (SATCOM) systems are envisioned to incorporate advanced capabilities for dynamically adapting link and network configurations to meet user performance needs. These advanced capabilities require an understanding of the operating environment as well as the potential outcomes of adaptation decisions. A SATCOM situational awareness and decision-making approach is needed that represents the cause and effect linkage of relevant phenomenology and operating conditions on link performance. Similarly, the model must enable a corresponding diagnostic capability that allows SATCOM payload managers to assess likely causes of observed effects. Prior work demonstrated the ability to use a probabilistic reasoning model for a SATCOM situational awareness model. It provided the theoretical basis and demonstrated the ability to realize such a model. This paper presents an analysis of the probabilistic reasoning approach in the context of its ability to be used for diagnostic purposes. A quantitative assessment is presented to demonstrate the impact of uncertainty on estimation accuracy for several key parameters. The paper also discusses how the results could be used by a higher-level reasoning process to evaluate likely causes of performance shortfalls such as atmospheric conditions, pointing errors, and jamming.
Welton, Nicky J; Ades, A E
2005-01-01
Markov transition models are frequently used to model disease progression. The authors show how the solution to Kolmogorov's forward equations can be exploited to map between transition rates and probabilities from probability data in multistate models. They provide a uniform, Bayesian treatment of estimation and propagation of uncertainty of transition rates and probabilities when 1) observations are available on all transitions and exact time at risk in each state (fully observed data) and 2) observations are on initial state and final state after a fixed interval of time but not on the sequence of transitions (partially observed data). The authors show how underlying transition rates can be recovered from partially observed data using Markov chain Monte Carlo methods in WinBUGS, and they suggest diagnostics to investigate inconsistencies between evidence from different starting states. An illustrative example for a 3-state model is given, which shows how the methods extend to more complex Markov models using the software WBDiff to compute solutions. Finally, the authors illustrate how to statistically combine data from multiple sources, including partially observed data at several follow-up times and also how to calibrate a Markov model to be consistent with data from one specific study. PMID:16282214
Risk estimates for neonatal myotonic dystrophy.
Glånz, A; Fråser, F C
1984-01-01
Children who inherit the autosomal dominant gene for myotonic dystrophy from their mother rather than their father may develop the severe neonatal type rather than the late onset type. The families of 22 neonatal type probands and 59 late onset type probands were studied to determine the risk of occurrence and recurrence of the neonatal type. The frequency of the neonatal type in sibs of neonatal type probands was 29%, or 37% if cases of neonatal deaths are counted as affected. This is significantly higher than the 6% of the neonatal type found in the offspring of affected women not ascertained through a child with the neonatal type. These data suggest that certain women carrying the gene for myotonic dystrophy are predisposed to have children affected with the neonatal type rather than the late onset type. The female near relatives of these women do not seem to share this predisposition. The data should be useful for genetic counseling. PMID:6748014
Probability Discounting of Gains and Losses: Implications for Risk Attitudes and Impulsivity
ERIC Educational Resources Information Center
Shead, N. Will; Hodgins, David C.
2009-01-01
Sixty college students performed three discounting tasks: probability discounting of gains, probability discounting of losses, and delay discounting of gains. Each task used an adjusting-amount procedure, and participants' choices affected the amount and timing of their remuneration for participating. Both group and individual discounting…
Sensitivity of health risk estimates to air quality adjustment procedure
Whitfield, R.G.
1997-06-30
This letter is a summary of risk results associated with exposure estimates using two-parameter Weibull and quadratic air quality adjustment procedures (AQAPs). New exposure estimates were developed for children and child-occurrences, six urban areas, and five alternative air quality scenarios. In all cases, the Weibull and quadratic results are compared to previous results, which are based on a proportional AQAP.
Probabilistic methodology for estimating radiation-induced cancer risk
Dunning, D.E. Jr.; Leggett, R.W.; Williams, L.R.
1981-01-01
The RICRAC computer code was developed at Oak Ridge National Laboratory to provide a versatile and convenient methodology for radiation risk assessment. The code allows as input essentially any dose pattern commonly encountered in risk assessments for either acute or chronic exposures, and it includes consideration of the age structure of the exposed population. Results produced by the analysis include the probability of one or more radiation-induced cancer deaths in a specified population, expected numbers of deaths, and expected years of life lost as a result of premature fatalities. These calculatons include consideration of competing risks of death from all other causes. The program also generates a probability frequency distribution of the expected number of cancers in any specified cohort resulting from a given radiation dose. The methods may be applied to any specified population and dose scenario.
Wu, Tong; Yang, Zhi
2014-01-01
This paper presents a neural spike processing IC for simultaneous spike detection, alignment, and transmission on 8 recording channels with unsupervised closed-loop control. In this work, spikes are detected according to online estimated spiking probability maps, which reliably predict the possibility of spike occurrence. The closed-loop control has been made possible by estimating firing rates based on alignment results and turning on/off channels individually and automatically. The 8-channel neural spike processing IC, implemented in a 0.13 μm CMOS process, has a varied power dissipation from 36 μW to 54.4 μW per channel at a voltage supply of 1.2 V. The chip also achieves a 380× data rate reduction for the testing in vivo data, allowing easy integration with wireless data transmission modules. PMID:25571180
Uncertainties in estimates of the risks of late effects from space radiation.
Cucinotta, F A; Schimmerling, W; Wilson, J W; Peterson, L E; Saganti, P B; Dicello, J F
2004-01-01
Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits.
Uncertainties in estimates of the risks of late effects from space radiation
NASA Technical Reports Server (NTRS)
Cucinotta, F. A.; Schimmerling, W.; Wilson, J. W.; Peterson, L. E.; Saganti, P. B.; Dicello, J. F.
2004-01-01
Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits. Published by Elsevier Ltd on behalf of COSPAR.
Scinicariello, Franco; Portier, Christopher
2016-03-01
Non-cancer risk assessment traditionally assumes a threshold of effect, below which there is a negligible risk of an adverse effect. The Agency for Toxic Substances and Disease Registry derives health-based guidance values known as Minimal Risk Levels (MRLs) as estimates of the toxicity threshold for non-carcinogens. Although the definition of an MRL, as well as EPA reference dose values (RfD and RfC), is a level that corresponds to "negligible risk," they represent daily exposure doses or concentrations, not risks. We present a new approach to calculate the risk at exposure to specific doses for chemical mixtures, the assumption in this approach is to assign de minimis risk at the MRL. The assigned risk enables the estimation of parameters in an exponential model, providing a complete dose-response curve for each compound from the chosen point of departure to zero. We estimated parameters for 27 chemicals. The value of k, which determines the shape of the dose-response curve, was moderately insensitive to the choice of the risk at the MRL. The approach presented here allows for the calculation of a risk from a single substance or the combined risk from multiple chemical exposures in a community. The methodology is applicable from point of departure data derived from quantal data, such as data from benchmark dose analyses or from data that can be transformed into probabilities, such as lowest-observed-adverse-effect level. The individual risks are used to calculate risk ratios that can facilitate comparison and cost-benefit analyses of environmental contamination control strategies. PMID:25667015
Uncertainties in estimates of the risks of late effects from space radiation.
Cucinotta, F A; Schimmerling, W; Wilson, J W; Peterson, L E; Saganti, P B; Dicello, J F
2004-01-01
Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits. PMID:15881779
Scinicariello, Franco; Portier, Christopher
2016-03-01
Non-cancer risk assessment traditionally assumes a threshold of effect, below which there is a negligible risk of an adverse effect. The Agency for Toxic Substances and Disease Registry derives health-based guidance values known as Minimal Risk Levels (MRLs) as estimates of the toxicity threshold for non-carcinogens. Although the definition of an MRL, as well as EPA reference dose values (RfD and RfC), is a level that corresponds to "negligible risk," they represent daily exposure doses or concentrations, not risks. We present a new approach to calculate the risk at exposure to specific doses for chemical mixtures, the assumption in this approach is to assign de minimis risk at the MRL. The assigned risk enables the estimation of parameters in an exponential model, providing a complete dose-response curve for each compound from the chosen point of departure to zero. We estimated parameters for 27 chemicals. The value of k, which determines the shape of the dose-response curve, was moderately insensitive to the choice of the risk at the MRL. The approach presented here allows for the calculation of a risk from a single substance or the combined risk from multiple chemical exposures in a community. The methodology is applicable from point of departure data derived from quantal data, such as data from benchmark dose analyses or from data that can be transformed into probabilities, such as lowest-observed-adverse-effect level. The individual risks are used to calculate risk ratios that can facilitate comparison and cost-benefit analyses of environmental contamination control strategies.
ERIC Educational Resources Information Center
Green, Dido; Lingam, Raghu; Mattocks, Calum; Riddoch, Chris; Ness, Andy; Emond, Alan
2011-01-01
The aim of the current study was to test the hypothesis that children with probable Developmental Coordination Disorder have an increased risk of reduced moderate to vigorous physical activity (MVPA), using data from a large population based study. Prospectively collected data from 4331 children (boys = 2065, girls = 2266) who had completed motor…
Overall risk estimation for nonreactor nuclear facilities and implementation of safety goals
Kim, K.S.; Bradley, R.F.
1993-06-01
A typical safety analysis report (SAR) contains estimated frequencies.and consequences of various design basis accidents (DBA). However, the results are organized and presented in such a way that they are not conducive for summing up with mathematical rigor to express total or overall risk. This paper describes a mathematical formalism for deriving total risk indicators. The mathematical formalism is based on the complementary cumulative distribution function (CCDF) or exceedance probability of radioactivity release fraction and individual radiation dose. A simple protocol is presented for establishing exceedance probabilities from the results of DBA analyses typically available from an SAR. The exceedance probability of release fraction can be a useful indicator for gaining insights into the capability of confinement barriers, characteristics of source terms, and scope of the SAR. Fatality risks comparable to the DOE Safety Goals can be derived from the exceedance probability of individual doses. Example case analyses are presented to illustrate the use of the proposed protocol and mathematical formalism. The methodology is finally applied to proposed risk guidelines for individual accident events to show that these guidelines would be within the DOE Safety Goals.
Anderson, Christian C.; Bauer, Adam Q.; Holland, Mark R.; Pakula, Michal; Laugier, Pascal; Bretthorst, G. Larry; Miller, James G.
2010-01-01
Quantitative ultrasonic characterization of cancellous bone can be complicated by artifacts introduced by analyzing acquired data consisting of two propagating waves (a fast wave and a slow wave) as if only one wave were present. Recovering the ultrasonic properties of overlapping fast and slow waves could therefore lead to enhancement of bone quality assessment. The current study uses Bayesian probability theory to estimate phase velocity and normalized broadband ultrasonic attenuation (nBUA) parameters in a model of fast and slow wave propagation. Calculations are carried out using Markov chain Monte Carlo with simulated annealing to approximate the marginal posterior probability densities for parameters in the model. The technique is applied to simulated data, to data acquired on two phantoms capable of generating two waves in acquired signals, and to data acquired on a human femur condyle specimen. The models are in good agreement with both the simulated and experimental data, and the values of the estimated ultrasonic parameters fall within expected ranges. PMID:21110589
NASA Astrophysics Data System (ADS)
Maier-Paape, Stanislaus; Wanner, Thomas
This paper is the first in a series of two papers addressing the phenomenon of spinodal decomposition for the Cahn-Hilliard equation
Predicted probabilities' relationship to inclusion probabilities.
Fang, Di; Chong, Jenny; Wilson, Jeffrey R
2015-05-01
It has been shown that under a general multiplicative intercept model for risk, case-control (retrospective) data can be analyzed by maximum likelihood as if they had arisen prospectively, up to an unknown multiplicative constant, which depends on the relative sampling fraction. (1) With suitable auxiliary information, retrospective data can also be used to estimate response probabilities. (2) In other words, predictive probabilities obtained without adjustments from retrospective data will likely be different from those obtained from prospective data. We highlighted this using binary data from Medicare to determine the probability of readmission into the hospital within 30 days of discharge, which is particularly timely because Medicare has begun penalizing hospitals for certain readmissions. (3).
NASA Astrophysics Data System (ADS)
Vio, R.; Andreani, P.
2016-05-01
The reliable detection of weak signals is a critical issue in many astronomical contexts and may have severe consequences for determining number counts and luminosity functions, but also for optimizing the use of telescope time in follow-up observations. Because of its optimal properties, one of the most popular and widely-used detection technique is the matched filter (MF). This is a linear filter designed to maximise the detectability of a signal of known structure that is buried in additive Gaussian random noise. In this work we show that in the very common situation where the number and position of the searched signals within a data sequence (e.g. an emission line in a spectrum) or an image (e.g. a point-source in an interferometric map) are unknown, this technique, when applied in its standard form, may severely underestimate the probability of false detection. This is because the correct use of the MF relies upon a priori knowledge of the position of the signal of interest. In the absence of this information, the statistical significance of features that are actually noise is overestimated and detections claimed that are actually spurious. For this reason, we present an alternative method of computing the probability of false detection that is based on the probability density function (PDF) of the peaks of a random field. It is able to provide a correct estimate of the probability of false detection for the one-, two- and three-dimensional case. We apply this technique to a real two-dimensional interferometric map obtained with ALMA.
Gronewold, Andrew D; Wolpert, Robert L
2008-07-01
Most probable number (MPN) and colony-forming-unit (CFU) estimates of fecal coliform bacteria concentration are common measures of water quality in coastal shellfish harvesting and recreational waters. Estimating procedures for MPN and CFU have intrinsic variability and are subject to additional uncertainty arising from minor variations in experimental protocol. It has been observed empirically that the standard multiple-tube fermentation (MTF) decimal dilution analysis MPN procedure is more variable than the membrane filtration CFU procedure, and that MTF-derived MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the variability in, and discrepancy between, MPN and CFU measurements. We then compare our model to water quality samples analyzed using both MPN and CFU procedures, and find that the (often large) observed differences between MPN and CFU values for the same water body are well within the ranges predicted by our probabilistic model. Our results indicate that MPN and CFU intra-sample variability does not stem from human error or laboratory procedure variability, but is instead a simple consequence of the probabilistic basis for calculating the MPN. These results demonstrate how probabilistic models can be used to compare samples from different analytical procedures, and to determine whether transitions from one procedure to another are likely to cause a change in quality-based management decisions.
Tremblay, Raymond L.; McCarthy, Michael A.
2014-01-01
Predicting population dynamics for rare species is of paramount importance in order to evaluate the likelihood of extinction and planning conservation strategies. However, evaluating and predicting population viability can be hindered from a lack of data. Rare species frequently have small populations, so estimates of vital rates are often very uncertain due to lack of data. We evaluated the vital rates of seven small populations from two watersheds with varying light environment of a common epiphytic orchid using Bayesian methods of parameter estimation. From the Lefkovitch matrices we predicted the deterministic population growth rates, elasticities, stable stage distributions and the credible intervals of the statistics. Populations were surveyed on a monthly basis between 18–34 months. In some of the populations few or no transitions in some of the vital rates were observed throughout the sampling period, however, we were able to predict the most likely vital rates using a Bayesian model that incorporated the transitions rates from the other populations. Asymptotic population growth rate varied among the seven orchid populations. There was little difference in population growth rate among watersheds even though it was expected because of physical differences as a result of differing canopy cover and watershed width. Elasticity analyses of Lepanthes rupestris suggest that growth rate is more sensitive to survival followed by growth, shrinking and the reproductive rates. The Bayesian approach helped to estimate transition probabilities that were uncommon or variable in some populations. Moreover, it increased the precision of the parameter estimates as compared to traditional approaches. PMID:25068598
Estimating the re-identification risk of clinical data sets
2012-01-01
Background De-identification is a common way to protect patient privacy when disclosing clinical data for secondary purposes, such as research. One type of attack that de-identification protects against is linking the disclosed patient data with public and semi-public registries. Uniqueness is a commonly used measure of re-identification risk under this attack. If uniqueness can be measured accurately then the risk from this kind of attack can be managed. In practice, it is often not possible to measure uniqueness directly, therefore it must be estimated. Methods We evaluated the accuracy of uniqueness estimators on clinically relevant data sets. Four candidate estimators were identified because they were evaluated in the past and found to have good accuracy or because they were new and not evaluated comparatively before: the Zayatz estimator, slide negative binomial estimator, Pitman’s estimator, and mu-argus. A Monte Carlo simulation was performed to evaluate the uniqueness estimators on six clinically relevant data sets. We varied the sampling fraction and the uniqueness in the population (the value being estimated). The median relative error and inter-quartile range of the uniqueness estimates was measured across 1000 runs. Results There was no single estimator that performed well across all of the conditions. We developed a decision rule which selected between the Pitman, slide negative binomial and Zayatz estimators depending on the sampling fraction and the difference between estimates. This decision rule had the best consistent median relative error across multiple conditions and data sets. Conclusion This study identified an accurate decision rule that can be used by health privacy researchers and disclosure control professionals to estimate uniqueness in clinical data sets. The decision rule provides a reliable way to measure re-identification risk. PMID:22776564
These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.
Park, Dong-Uk; Colt, Joanne S; Baris, Dalsu; Schwenn, Molly; Karagas, Margaret R; Armenti, Karla R; Johnson, Alison; Silverman, Debra T; Stewart, Patricia A
2014-01-01
We describe an approach for estimating the probability that study subjects were exposed to metalworking fluids (MWFs) in a population-based case-control study of bladder cancer. Study subject reports on the frequency of machining and use of specific MWFs (straight, soluble, and synthetic/semi-synthetic) were used to estimate exposure probability when available. Those reports also were used to develop estimates for job groups, which were then applied to jobs without MWF reports. Estimates using both cases and controls and controls only were developed. The prevalence of machining varied substantially across job groups (0.1->0.9%), with the greatest percentage of jobs that machined being reported by machinists and tool and die workers. Reports of straight and soluble MWF use were fairly consistent across job groups (generally 50-70%). Synthetic MWF use was lower (13-45%). There was little difference in reports by cases and controls vs. controls only. Approximately, 1% of the entire study population was assessed as definitely exposed to straight or soluble fluids in contrast to 0.2% definitely exposed to synthetic/semi-synthetics. A comparison between the reported use of the MWFs and U.S. production levels found high correlations (r generally >0.7). Overall, the method described here is likely to have provided a systematic and reliable ranking that better reflects the variability of exposure to three types of MWFs than approaches applied in the past. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resources: a list of keywords in the occupational histories that were used to link study subjects to the metalworking fluids (MWFs) modules; recommendations from the literature on selection of MWFs based on type of machining operation, the metal being machined and decade; popular additives to MWFs; the number and proportion of controls who
Park, Dong-Uk; Colt, Joanne S; Baris, Dalsu; Schwenn, Molly; Karagas, Margaret R; Armenti, Karla R; Johnson, Alison; Silverman, Debra T; Stewart, Patricia A
2014-01-01
We describe an approach for estimating the probability that study subjects were exposed to metalworking fluids (MWFs) in a population-based case-control study of bladder cancer. Study subject reports on the frequency of machining and use of specific MWFs (straight, soluble, and synthetic/semi-synthetic) were used to estimate exposure probability when available. Those reports also were used to develop estimates for job groups, which were then applied to jobs without MWF reports. Estimates using both cases and controls and controls only were developed. The prevalence of machining varied substantially across job groups (0.1->0.9%), with the greatest percentage of jobs that machined being reported by machinists and tool and die workers. Reports of straight and soluble MWF use were fairly consistent across job groups (generally 50-70%). Synthetic MWF use was lower (13-45%). There was little difference in reports by cases and controls vs. controls only. Approximately, 1% of the entire study population was assessed as definitely exposed to straight or soluble fluids in contrast to 0.2% definitely exposed to synthetic/semi-synthetics. A comparison between the reported use of the MWFs and U.S. production levels found high correlations (r generally >0.7). Overall, the method described here is likely to have provided a systematic and reliable ranking that better reflects the variability of exposure to three types of MWFs than approaches applied in the past. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resources: a list of keywords in the occupational histories that were used to link study subjects to the metalworking fluids (MWFs) modules; recommendations from the literature on selection of MWFs based on type of machining operation, the metal being machined and decade; popular additives to MWFs; the number and proportion of controls who
NASA Technical Reports Server (NTRS)
Chappell, Lori J.; Cucinotta, Francis A.
2011-01-01
Radiation risks are estimated in a competing risk formalism where age or time after exposure estimates of increased risks for cancer and circulatory diseases are folded with a probability to survive to a given age. The survival function, also called the life-table, changes with calendar year, gender, smoking status and other demographic variables. An outstanding problem in risk estimation is the method of risk transfer between exposed populations and a second population where risks are to be estimated. Approaches used to transfer risks are based on: 1) Multiplicative risk transfer models -proportional to background disease rates. 2) Additive risk transfer model -risks independent of background rates. In addition, a Mixture model is often considered where the multiplicative and additive transfer assumptions are given weighted contributions. We studied the influence of the survival probability on the risk of exposure induced cancer and circulatory disease morbidity and mortality in the Multiplicative transfer model and the Mixture model. Risks for never-smokers (NS) compared to the average U.S. population are estimated to be reduced between 30% and 60% dependent on model assumptions. Lung cancer is the major contributor to the reduction for NS, with additional contributions from circulatory diseases and cancers of the stomach, liver, bladder, oral cavity, esophagus, colon, a portion of the solid cancer remainder, and leukemia. Greater improvements in risk estimates for NS s are possible, and would be dependent on improved understanding of risk transfer models, and elucidating the role of space radiation on the various stages of disease formation (e.g. initiation, promotion, and progression).
Eash, David A.; Barnes, Kimberlee K.; Veilleux, Andrea G.
2013-01-01
A statewide study was performed to develop regional regression equations for estimating selected annual exceedance-probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedance-probability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized least-squares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized least-squares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97
Estimating and Mapping the Population at Risk of Sleeping Sickness
Franco, José R.; Paone, Massimo; Diarra, Abdoulaye; Ruiz-Postigo, José Antonio; Fèvre, Eric M.; Mattioli, Raffaele C.; Jannin, Jean G.
2012-01-01
Background Human African trypanosomiasis (HAT), also known as sleeping sickness, persists as a public health problem in several sub-Saharan countries. Evidence-based, spatially explicit estimates of population at risk are needed to inform planning and implementation of field interventions, monitor disease trends, raise awareness and support advocacy. Comprehensive, geo-referenced epidemiological records from HAT-affected countries were combined with human population layers to map five categories of risk, ranging from “very high” to “very low,” and to estimate the corresponding at-risk population. Results Approximately 70 million people distributed over a surface of 1.55 million km2 are estimated to be at different levels of risk of contracting HAT. Trypanosoma brucei gambiense accounts for 82.2% of the population at risk, the remaining 17.8% being at risk of infection from T. b. rhodesiense. Twenty-one million people live in areas classified as moderate to very high risk, where more than 1 HAT case per 10,000 inhabitants per annum is reported. Discussion Updated estimates of the population at risk of sleeping sickness were made, based on quantitative information on the reported cases and the geographic distribution of human population. Due to substantial methodological differences, it is not possible to make direct comparisons with previous figures for at-risk population. By contrast, it will be possible to explore trends in the future. The presented maps of different HAT risk levels will help to develop site-specific strategies for control and surveillance, and to monitor progress achieved by ongoing efforts aimed at the elimination of sleeping sickness. PMID:23145192
Khosravi, Ahmad; Mansournia, Mohammad Ali; Mahmoodi, Mahmood; Pouyan, Ali Akbar; Holakouie-Naieni, Kourosh
2016-01-01
Background: Cigarette smoking is one of the most important health-related risk factors in terms of morbidity and mortality. In this study, we introduced a new method for deriving the transitional probabilities of smoking stages from a cross-sectional study and simulated a long-term smoking behavior for adolescents. Methods: In this study in 2010, a total of 4853 high school students were randomly selected and were completed a self-administered questionnaire about cigarette smoking. We used smoothed age- and sex-specific prevalence of smoking stages in a probabilistic discrete event system for estimating of transitional probabilities. A nonhomogenous discrete time Markov chain analysis was used to model the progression of the smoking in 10 years ahead in the same population. The mean age of the students was 15.69 ± 0.73 years (range: 14–19). Results: The smoothed prevalence proportion of current smoking varies between 3.58 and 26.14%. The age-adjusted odds of initiation in boys is 8.9 (95% confidence interval [CI]: 7.9–10.0) times of the odds of initiation of smoking in girls. Our study predicted that the prevalence proportion of current smokers increased from 7.55% in 2010 to 20.31% (95% CI: 19.44–21.37) for 2019. Conclusions: The present study showed a moderately but concerning prevalence of current smoking in Iranian adolescents and introduced a novel method for estimation of transitional probabilities from a cross-sectional study. The increasing trend of cigarette use among adolescents indicated the necessity of paying more attention to this group. PMID:27625766
Khosravi, Ahmad; Mansournia, Mohammad Ali; Mahmoodi, Mahmood; Pouyan, Ali Akbar; Holakouie-Naieni, Kourosh
2016-01-01
Background: Cigarette smoking is one of the most important health-related risk factors in terms of morbidity and mortality. In this study, we introduced a new method for deriving the transitional probabilities of smoking stages from a cross-sectional study and simulated a long-term smoking behavior for adolescents. Methods: In this study in 2010, a total of 4853 high school students were randomly selected and were completed a self-administered questionnaire about cigarette smoking. We used smoothed age- and sex-specific prevalence of smoking stages in a probabilistic discrete event system for estimating of transitional probabilities. A nonhomogenous discrete time Markov chain analysis was used to model the progression of the smoking in 10 years ahead in the same population. The mean age of the students was 15.69 ± 0.73 years (range: 14–19). Results: The smoothed prevalence proportion of current smoking varies between 3.58 and 26.14%. The age-adjusted odds of initiation in boys is 8.9 (95% confidence interval [CI]: 7.9–10.0) times of the odds of initiation of smoking in girls. Our study predicted that the prevalence proportion of current smokers increased from 7.55% in 2010 to 20.31% (95% CI: 19.44–21.37) for 2019. Conclusions: The present study showed a moderately but concerning prevalence of current smoking in Iranian adolescents and introduced a novel method for estimation of transitional probabilities from a cross-sectional study. The increasing trend of cigarette use among adolescents indicated the necessity of paying more attention to this group.
NASA Astrophysics Data System (ADS)
Jaynes, E. T.; Bretthorst, G. Larry
2003-04-01
Foreword; Preface; Part I. Principles and Elementary Applications: 1. Plausible reasoning; 2. The quantitative rules; 3. Elementary sampling theory; 4. Elementary hypothesis testing; 5. Queer uses for probability theory; 6. Elementary parameter estimation; 7. The central, Gaussian or normal distribution; 8. Sufficiency, ancillarity, and all that; 9. Repetitive experiments, probability and frequency; 10. Physics of 'random experiments'; Part II. Advanced Applications: 11. Discrete prior probabilities, the entropy principle; 12. Ignorance priors and transformation groups; 13. Decision theory: historical background; 14. Simple applications of decision theory; 15. Paradoxes of probability theory; 16. Orthodox methods: historical background; 17. Principles and pathology of orthodox statistics; 18. The Ap distribution and rule of succession; 19. Physical measurements; 20. Model comparison; 21. Outliers and robustness; 22. Introduction to communication theory; References; Appendix A. Other approaches to probability theory; Appendix B. Mathematical formalities and style; Appendix C. Convolutions and cumulants.
[Application of spatial relative risk estimation in communicable disease risk evaluation].
Zhang, Yewu; Guo, Qing; Wang, Xiaofeng; Yu, Meng; Su, Xuemei; Dong, Yan; Zhang, Chunxi
2015-05-01
This paper summaries the application of adaptive kernel density algorithm in the spatial relative risk estimation of communicable diseases by using the reported data of infectious diarrhea (other than cholera, dysentery, typhoid and paratyphoid) in Ludian county and surrounding area in Yunnan province in 2013. Statistically significant fluctuations in an estimated risk function were identified through the use of asymptotic tolerance contours, and finally these data were visualized though disease mapping. The results of spatial relative risk estimation and disease mapping showed that high risk areas were in southeastern Shaoyang next to Ludian. Therefore, the spatial relative risk estimation of disease by using adaptive kernel density algorithm and disease mapping technique is a powerful method in identifying high risk population and areas.
[Application of spatial relative risk estimation in communicable disease risk evaluation].
Zhang, Yewu; Guo, Qing; Wang, Xiaofeng; Yu, Meng; Su, Xuemei; Dong, Yan; Zhang, Chunxi
2015-05-01
This paper summaries the application of adaptive kernel density algorithm in the spatial relative risk estimation of communicable diseases by using the reported data of infectious diarrhea (other than cholera, dysentery, typhoid and paratyphoid) in Ludian county and surrounding area in Yunnan province in 2013. Statistically significant fluctuations in an estimated risk function were identified through the use of asymptotic tolerance contours, and finally these data were visualized though disease mapping. The results of spatial relative risk estimation and disease mapping showed that high risk areas were in southeastern Shaoyang next to Ludian. Therefore, the spatial relative risk estimation of disease by using adaptive kernel density algorithm and disease mapping technique is a powerful method in identifying high risk population and areas. PMID:26080648
Jenkins, Rachel; Othieno, Caleb; Omollo, Raymond; Ongeri, Linnet; Sifuna, Peter; Mboroki, James Kingora; Kiima, David; Ogutu, Bernhards
2015-10-01
This study aimed to assess the prevalence of probable post-traumatic stress disorder (PTSD), and its associated risk factors in a general household population in Kenya. Data were drawn from a cross-sectional household survey of mental disorders and their associated risk factors. The participants received a structured epidemiological assessment of common mental disorders, and symptoms of PTSD, accompanied by additional sections on socio-demographic data, life events, social networks, social supports, disability/activities of daily living, quality of life, use of health services, and service use. The study found that 48% had experienced a severe trauma, and an overall prevalence rate of 10.6% of probable PTSD, defined as a score of six or more on the trauma screening questionnaire (TSQ). The conditional probability of PTSD was 0.26. Risk factors include being female, single, self-employed, having experienced recent life events, having a common mental disorder (CMD)and living in an institution before age 16. The study indicates that probable PTSD is prevalent in this rural area of Kenya. The findings are relevant for the training of front line health workers, their support and supervision, for health management information systems, and for mental health promotion in state boarding schools. PMID:26516877
Jenkins, Rachel; Othieno, Caleb; Omollo, Raymond; Ongeri, Linnet; Sifuna, Peter; Mboroki, James Kingora; Kiima, David; Ogutu, Bernhards
2015-10-26
This study aimed to assess the prevalence of probable post-traumatic stress disorder (PTSD), and its associated risk factors in a general household population in Kenya. Data were drawn from a cross-sectional household survey of mental disorders and their associated risk factors. The participants received a structured epidemiological assessment of common mental disorders, and symptoms of PTSD, accompanied by additional sections on socio-demographic data, life events, social networks, social supports, disability/activities of daily living, quality of life, use of health services, and service use. The study found that 48% had experienced a severe trauma, and an overall prevalence rate of 10.6% of probable PTSD, defined as a score of six or more on the trauma screening questionnaire (TSQ). The conditional probability of PTSD was 0.26. Risk factors include being female, single, self-employed, having experienced recent life events, having a common mental disorder (CMD)and living in an institution before age 16. The study indicates that probable PTSD is prevalent in this rural area of Kenya. The findings are relevant for the training of front line health workers, their support and supervision, for health management information systems, and for mental health promotion in state boarding schools.
Jenkins, Rachel; Othieno, Caleb; Omollo, Raymond; Ongeri, Linnet; Sifuna, Peter; Mboroki, James Kingora; Kiima, David; Ogutu, Bernhards
2015-01-01
This study aimed to assess the prevalence of probable post-traumatic stress disorder (PTSD), and its associated risk factors in a general household population in Kenya. Data were drawn from a cross-sectional household survey of mental disorders and their associated risk factors. The participants received a structured epidemiological assessment of common mental disorders, and symptoms of PTSD, accompanied by additional sections on socio-demographic data, life events, social networks, social supports, disability/activities of daily living, quality of life, use of health services, and service use. The study found that 48% had experienced a severe trauma, and an overall prevalence rate of 10.6% of probable PTSD, defined as a score of six or more on the trauma screening questionnaire (TSQ). The conditional probability of PTSD was 0.26. Risk factors include being female, single, self-employed, having experienced recent life events, having a common mental disorder (CMD)and living in an institution before age 16. The study indicates that probable PTSD is prevalent in this rural area of Kenya. The findings are relevant for the training of front line health workers, their support and supervision, for health management information systems, and for mental health promotion in state boarding schools. PMID:26516877
On cancer risk estimation of urban air pollution.
Törnqvist, M; Ehrenberg, L
1994-01-01
The usefulness of data from various sources for a cancer risk estimation of urban air pollution is discussed. Considering the irreversibility of initiations, a multiplicative model is preferred for solid tumors. As has been concluded for exposure to ionizing radiation, the multiplicative model, in comparison with the additive model, predicts a relatively larger number of cases at high ages, with enhanced underestimation of risks by short follow-up times in disease-epidemiological studies. For related reasons, the extrapolation of risk from animal tests on the basis of daily absorbed dose per kilogram body weight or per square meter surface area without considering differences in life span may lead to an underestimation, and agreements with epidemiologically determined values may be fortuitous. Considering these possibilities, the most likely lifetime risks of cancer death at the average exposure levels in Sweden were estimated for certain pollution fractions or indicator compounds in urban air. The risks amount to approximately 50 deaths per 100,000 for inhaled particulate organic material (POM), with a contribution from ingested POM about three times larger, and alkenes, and butadiene cause 20 deaths, respectively, per 100,000 individuals. Also, benzene and formaldehyde are expected to be associated with considerable risk increments. Comparative potency methods were applied for POM and alkenes. Due to incompleteness of the list of compounds considered and the uncertainties of the above estimates, the total risk calculation from urban air has not been attempted here. PMID:7821292
Prah, Philip; Hickson, Ford; Bonell, Chris; McDaid, Lisa M; Johnson, Anne M; Wayal, Sonali; Clifton, Soazig; Sonnenberg, Pam; Nardone, Anthony; Erens, Bob; Copas, Andrew J; Riddell, Julie; Weatherburn, Peter; Mercer, Catherine H
2016-01-01
Objective To examine sociodemographic and behavioural differences between men who have sex with men (MSM) participating in recent UK convenience surveys and a national probability sample survey. Methods We compared 148 MSM aged 18–64 years interviewed for Britain's third National Survey of Sexual Attitudes and Lifestyles (Natsal-3) undertaken in 2010–2012, with men in the same age range participating in contemporaneous convenience surveys of MSM: 15 500 British resident men in the European MSM Internet Survey (EMIS); 797 in the London Gay Men's Sexual Health Survey; and 1234 in Scotland's Gay Men's Sexual Health Survey. Analyses compared men reporting at least one male sexual partner (past year) on similarly worded questions and multivariable analyses accounted for sociodemographic differences between the surveys. Results MSM in convenience surveys were younger and better educated than MSM in Natsal-3, and a larger proportion identified as gay (85%–95% vs 62%). Partner numbers were higher and same-sex anal sex more common in convenience surveys. Unprotected anal intercourse was more commonly reported in EMIS. Compared with Natsal-3, MSM in convenience surveys were more likely to report gonorrhoea diagnoses and HIV testing (both past year). Differences between the samples were reduced when restricting analysis to gay-identifying MSM. Conclusions National probability surveys better reflect the population of MSM but are limited by their smaller samples of MSM. Convenience surveys recruit larger samples of MSM but tend to over-represent MSM identifying as gay and reporting more sexual risk behaviours. Because both sampling strategies have strengths and weaknesses, methods are needed to triangulate data from probability and convenience surveys. PMID:26965869
NASA Astrophysics Data System (ADS)
Karwowski, Damian; Domański, Marek
2016-01-01
An improved context-based adaptive binary arithmetic coding (CABAC) is presented. The idea for the improvement is to use a more accurate mechanism for estimation of symbol probabilities in the standard CABAC algorithm. The authors' proposal of such a mechanism is based on the context-tree weighting technique. In the framework of a high-efficiency video coding (HEVC) video encoder, the improved CABAC allows 0.7% to 4.5% bitrate saving compared to the original CABAC algorithm. The application of the proposed algorithm marginally affects the complexity of HEVC video encoder, but the complexity of video decoder increases by 32% to 38%. In order to decrease the complexity of video decoding, a new tool has been proposed for the improved CABAC that enables scaling of the decoder complexity. Experiments show that this tool gives 5% to 7.5% reduction of the decoding time while still maintaining high efficiency in the data compression.
Wang, Yuan; Gao, Ying; Battsend, Munkhzul; Chen, Kexin; Lu, Wenli; Wang, Yaogang
2014-11-01
The optimal approach regarding breast cancer screening for Chinese women is unclear due to the relative low incidence rate. A risk assessment tool may be useful for selection of high-risk subsets of population for mammography screening in low-incidence and resource-limited developing country. The odd ratios for six main risk factors of breast cancer were pooled by review manager after a systematic research of literature. Health risk appraisal (HRA) model was developed to predict an individual's risk of developing breast cancer in the next 5 years from current age. The performance of this HRA model was assessed based on a first-round screening database. Estimated risk of breast cancer increased with age. Increases in the 5-year risk of developing breast cancer were found with the existence of any of included risk factors. When individuals who had risk above median risk (3.3‰) were selected from the validation database, the sensitivity is 60.0% and the specificity is 47.8%. The unweighted area under the curve (AUC) was 0.64 (95% CI = 0.50-0.78). The risk-prediction model reported in this article is based on a combination of risk factors and shows good overall predictive power, but it is still weak at predicting which particular women will develop the disease. It would be very helpful for the improvement of a current model if more population-based prospective follow-up studies were used for the validation. PMID:25085581
Peers Increase Adolescent Risk Taking Even When the Probabilities of Negative Outcomes Are Known
ERIC Educational Resources Information Center
Smith, Ashley R.; Chein, Jason; Steinberg, Laurence
2014-01-01
The majority of adolescent risk taking occurs in the presence of peers, and recent research suggests that the presence of peers may alter how the potential rewards and costs of a decision are valuated or perceived. The current study further explores this notion by investigating how peer observation affects adolescent risk taking when the…
Maunsell, John H. R.
2012-01-01
Correlations between trial-to-trial fluctuations in the responses of individual sensory neurons and perceptual reports, commonly quantified with choice probability (CP), have been widely used as an important tool for assessing the contributions of neurons to behavior. These correlations are usually weak and often require a large number of trials for a reliable estimate. Therefore, working with measures such as CP warrants care in data analysis as well as rigorous controls during data collection. Here we identify potential confounds that can arise in data analysis and lead to biased estimates of CP, and suggest methods to avoid the bias. In particular, we show that the common practice of combining neuronal responses across different stimulus conditions with z-score normalization can result in an underestimation of CP when the ratio of the numbers of trials for the two behavioral response categories differs across the stimulus conditions. We also discuss the effects of using variable time intervals for quantifying neuronal response on CP measurements. Finally, we demonstrate that serious artifacts can arise in reaction time tasks that use varying measurement intervals if the mean neuronal response and mean behavioral performance vary over time within trials. To emphasize the importance of addressing these concerns in neurophysiological data, we present a set of data collected from V1 cells in macaque monkeys while the animals performed a detection task. PMID:22993262
NASA Astrophysics Data System (ADS)
Hong, Ban Zhen; Keong, Lau Kok; Shariff, Azmi Mohd
2016-05-01
The employment of different mathematical models to address specifically for the bubble nucleation rates of water vapour and dissolved air molecules is essential as the physics for them to form bubble nuclei is different. The available methods to calculate bubble nucleation rate in binary mixture such as density functional theory are complicated to be coupled along with computational fluid dynamics (CFD) approach. In addition, effect of dissolved gas concentration was neglected in most study for the prediction of bubble nucleation rates. The most probable bubble nucleation rate for the water vapour and dissolved air mixture in a 2D quasi-stable flow across a cavitating nozzle in current work was estimated via the statistical mean of all possible bubble nucleation rates of the mixture (different mole fractions of water vapour and dissolved air) and the corresponding number of molecules in critical cluster. Theoretically, the bubble nucleation rate is greatly dependent on components' mole fraction in a critical cluster. Hence, the dissolved gas concentration effect was included in current work. Besides, the possible bubble nucleation rates were predicted based on the calculated number of molecules required to form a critical cluster. The estimation of components' mole fraction in critical cluster for water vapour and dissolved air mixture was obtained by coupling the enhanced classical nucleation theory and CFD approach. In addition, the distribution of bubble nuclei of water vapour and dissolved air mixture could be predicted via the utilisation of population balance model.
Southard, Rodney E.; Veilleux, Andrea G.
2014-01-01
Regression analysis techniques were used to develop a set of equations for rural ungaged stream sites for estimating discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. Basin and climatic characteristics were computed using geographic information software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses. Annual exceedance-probability discharge estimates were computed for 278 streamgages by using the expected moments algorithm to fit a log-Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data from water year 1844 to 2012. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized multiple Grubbs-Beck test was used to detect potentially influential low floods. Annual peak flows less than a minimum recordable discharge at a streamgage were incorporated into the at-site station analyses. An updated regional skew coefficient was determined for the State of Missouri using Bayesian weighted least-squares/generalized least squares regression analyses. At-site skew estimates for 108 long-term streamgages with 30 or more years of record and the 35 basin characteristics defined for this study were used to estimate the regional variability in skew. However, a constant generalized-skew value of -0.30 and a mean square error of 0.14 were determined in this study. Previous flood studies indicated that the distinct physical features of the three physiographic provinces have a pronounced effect on the magnitude of flood peaks. Trends in the magnitudes of the residuals from preliminary statewide regression analyses from previous studies confirmed that regional analyses in this study were
Effects of exposure uncertainty on estimation of radon risks
Chambers, D.B.; Lowe, L.M.; Stager, R.H.; Reilly, P.M.; Duport, P.
1992-12-31
Estimates of lung-cancer risk from exposure to radon daughters are largely based on epidemiological studies of underground miners. The reliability of exposure data for these miners is a cause for concern, as actual workplace measurements of radon and/or radon-daughter levels are either sparse or absent for the early years of mining, when much of the exposure occurred.
Estimates of endemic waterborne risks from community-intervention studies.
Calderon, Rebecca L; Craun, Gunther F
2006-01-01
The nature and magnitude of endemic waterborne disease are not well characterized in the United States. Epidemiologic studies of various designs can provide an estimate of the waterborne attributable risk along with other types of information. Community drinking water systems frequently improve their operations and may change drinking water treatment and their major source of water. In the United States, many of these treatment changes are the result of regulations promulgated under the Safe Drinking Water Act. A community-intervention study design takes advantage of these "natural" experiments to assess changes in health risks. In this paper, we review the community-intervention studies that have assessed changes in waterborne gastroenteritis risks among immunocompetent populations in industrialized countries. Published results are available from two studies in Australia, one study in the United Kingdom, and one study in the United States. Preliminary results from two other US studies are also available. Although the current information is limited, the risks reported in these community-intervention studies can help inform the national estimate of endemic waterborne gastroenteritis. Information is provided about endemic waterborne risks for unfiltered surface water sources and a groundwater under the influence of surface water. Community-intervention studies with recommended study modifications should be conducted to better estimate the benefits associated with improved drinking water treatment. PMID:16895087
Risk estimates for radiation-induced cancer and radiation protection standards
Sinclair, W.K. )
1989-11-01
At low doses, the primary biological effects of concern are stochastic in nature, i.e., they are more probable at higher doses, but their severity is independent of the dose. In the last decade, a new epidemiological information on radiation-induced cancer in humans has become available. In the Japanese survivors three new cycles of data (11 yr of experience) have accumulated, and a revised dosimetry system (DS86) has been introduced. UNSCEAR (United Nations Scientific Committee on the Effects of Atomic Radiation) reevaluated the risk of cancer from all human sources, which include other human populations such as those treated for ankylosing spondylitis and for cancer of the cervix. UNSCEAR has also evaluated the cancer risk for each of nine organs. For radiation protection purposes (low doses and dose rates, adult populations mainly), nominal values of risk since the 1977-80 period have been {approximately}1%/Sv. This value will need to be increased in the light of the new estimates. Also, risk estimates for various tissues must be reconsidered, and weighting factors used by International Commission on Radiological Protection need to be reexamined. Recommendations on occupational and public dose limits must also be reconsidered. The National Council on Radiation Protection and Measurements is in a comparatively good position with a recently produced set of recommendations that had higher cancer risk estimates in mind.
Neoplastic potential of gastric irradiation. IV. Risk estimates
Griem, M.L.; Justman, J.; Weiss, L.
1984-12-01
No significant tumor increase was found in the initial analysis of patients irradiated for peptic ulcer and followed through 1962. A preliminary study was undertaken 22 years later to estimate the risk of cancer due to gastric irradiation for peptic ulcer disease. A population of 2,049 irradiated patients and 763 medically managed patients has been identified. A relative risk of 3.7 was found for stomach cancer and an initial risk estimate of 5.5 x 10(-6) excess stomach cancers per person rad was calculated. A more complete follow-up is in progress to further elucidate this observation and decrease the ascertainment bias; however, preliminary data are in agreement with the Japanese atomic bomb reports.
Estimation of myocardial volume at risk from CT angiography
NASA Astrophysics Data System (ADS)
Zhu, Liangjia; Gao, Yi; Mohan, Vandana; Stillman, Arthur; Faber, Tracy; Tannenbaum, Allen
2011-03-01
The determination of myocardial volume at risk distal to coronary stenosis provides important information for prognosis and treatment of coronary artery disease. In this paper, we present a novel computational framework for estimating the myocardial volume at risk in computed tomography angiography (CTA) imagery. Initially, epicardial and endocardial surfaces, and coronary arteries are extracted using an active contour method. Then, the extracted coronary arteries are projected onto the epicardial surface, and each point on this surface is associated with its closest coronary artery using the geodesic distance measurement. The likely myocardial region at risk on the epicardial surface caused by a stenosis is approximated by the region in which all its inner points are associated with the sub-branches distal to the stenosis on the coronary artery tree. Finally, the likely myocardial volume at risk is approximated by the volume in between the region at risk on the epicardial surface and its projection on the endocardial surface, which is expected to yield computational savings over risk volume estimation using the entire image volume. Furthermore, we expect increased accuracy since, as compared to prior work using the Euclidean distance, we employ the geodesic distance in this work. The experimental results demonstrate the effectiveness of the proposed approach on pig heart CTA datasets.
Estimating cancer risk from dental cone-beam CT exposures based on skin dosimetry
NASA Astrophysics Data System (ADS)
Pauwels, Ruben; Cockmartin, Lesley; Ivanauskaité, Deimante; Urbonienė, Ausra; Gavala, Sophia; Donta, Catherine; Tsiklakis, Kostas; Jacobs, Reinhilde; Bosmans, Hilde; Bogaerts, Ria; Horner, Keith; SEDENTEXCT Project Consortium, The
2014-07-01
The aim of this study was to measure entrance skin doses on patients undergoing cone-beam computed tomography (CBCT) examinations, to establish conversion factors between skin and organ doses, and to estimate cancer risk from CBCT exposures. 266 patients (age 8-83) were included, involving three imaging centres. CBCT scans were acquired using the SCANORA 3D (Soredex, Tuusula, Finland) and NewTom 9000 (QR, Verona, Italy). Eight thermoluminescent dosimeters were attached to the patient's skin at standardized locations. Using previously published organ dose estimations on various CBCTs with an anthropomorphic phantom, correlation factors to convert skin dose to organ doses were calculated and applied to estimate patient organ doses. The BEIR VII age- and gender-dependent dose-risk model was applied to estimate the lifetime attributable cancer risk. For the SCANORA 3D, average skin doses over the eight locations varied between 484 and 1788 µGy. For the NewTom 9000 the range was between 821 and 1686 µGy for Centre 1 and between 292 and 2325 µGy for Centre 2. Entrance skin dose measurements demonstrated the combined effect of exposure and patient factors on the dose. The lifetime attributable cancer risk, expressed as the probability to develop a radiation-induced cancer, varied between 2.7 per million (age >60) and 9.8 per million (age 8-11) with an average of 6.0 per million. On average, the risk for female patients was 40% higher. The estimated radiation risk was primarily influenced by the age at exposure and the gender, pointing out the continuing need for justification and optimization of CBCT exposures, with a specific focus on children.
Estimating cancer risk from dental cone-beam CT exposures based on skin dosimetry.
Pauwels, Ruben; Cockmartin, Lesley; Ivanauskaité, Deimante; Urbonienė, Ausra; Gavala, Sophia; Donta, Catherine; Tsiklakis, Kostas; Jacobs, Reinhilde; Bosmans, Hilde; Bogaerts, Ria; Horner, Keith
2014-07-21
The aim of this study was to measure entrance skin doses on patients undergoing cone-beam computed tomography (CBCT) examinations, to establish conversion factors between skin and organ doses, and to estimate cancer risk from CBCT exposures. 266 patients (age 8-83) were included, involving three imaging centres. CBCT scans were acquired using the SCANORA 3D (Soredex, Tuusula, Finland) and NewTom 9000 (QR, Verona, Italy). Eight thermoluminescent dosimeters were attached to the patient's skin at standardized locations. Using previously published organ dose estimations on various CBCTs with an anthropomorphic phantom, correlation factors to convert skin dose to organ doses were calculated and applied to estimate patient organ doses. The BEIR VII age- and gender-dependent dose-risk model was applied to estimate the lifetime attributable cancer risk. For the SCANORA 3D, average skin doses over the eight locations varied between 484 and 1788 µGy. For the NewTom 9000 the range was between 821 and 1686 µGy for Centre 1 and between 292 and 2325 µGy for Centre 2. Entrance skin dose measurements demonstrated the combined effect of exposure and patient factors on the dose. The lifetime attributable cancer risk, expressed as the probability to develop a radiation-induced cancer, varied between 2.7 per million (age >60) and 9.8 per million (age 8-11) with an average of 6.0 per million. On average, the risk for female patients was 40% higher. The estimated radiation risk was primarily influenced by the age at exposure and the gender, pointing out the continuing need for justification and optimization of CBCT exposures, with a specific focus on children. PMID:24957710
Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.
2016-08-04
In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization
NASA Technical Reports Server (NTRS)
Veldkamp, T. I. E.; Wada, Y.; Aerts, J. C. J. H.; Ward, P. J.
2016-01-01
Changing hydro-climatic and socioeconomic conditions increasingly put pressure on fresh water resources and are expected to aggravate water scarcity conditions towards the future. Despite numerous calls for risk-based water scarcity assessments, a global-scale framework that includes UNISDR's definition of risk does not yet exist. This study provides a first step towards such a risk based assessment, applying a Gamma distribution to estimate water scarcity conditions at the global scale under historic and future conditions, using multiple climate change and population growth scenarios. Our study highlights that water scarcity risk, expressed in terms of expected annual exposed population, increases given all future scenarios, up to greater than 56.2% of the global population in 2080. Looking at the drivers of risk, we find that population growth outweigh the impacts of climate change at global and regional scales. Using a risk-based method to assess water scarcity, we show the results to be less sensitive than traditional water scarcity assessments to the use of fixed threshold to represent different levels of water scarcity. This becomes especially important when moving from global to local scales, whereby deviations increase up to 50% of estimated risk levels.
Mazonakis, Michalis; Berris, Theoharris; Damilakis, John; Lyraraki, Efrossyni
2013-10-15
Purpose: Heterotopic ossification (HO) is a frequent complication following total hip arthroplasty. This study was conducted to calculate the radiation dose to organs-at-risk and estimate the probability of cancer induction from radiotherapy for HO prophylaxis.Methods: Hip irradiation for HO with a 6 MV photon beam was simulated with the aid of a Monte Carlo model. A realistic humanoid phantom representing an average adult patient was implemented in Monte Carlo environment for dosimetric calculations. The average out-of-field radiation dose to stomach, liver, lung, prostate, bladder, thyroid, breast, uterus, and ovary was calculated. The organ-equivalent-dose to colon, that was partly included within the treatment field, was also determined. Organ dose calculations were carried out using three different field sizes. The dependence of organ doses upon the block insertion into primary beam for shielding colon and prosthesis was investigated. The lifetime attributable risk for cancer development was estimated using organ, age, and gender-specific risk coefficients.Results: For a typical target dose of 7 Gy, organ doses varied from 1.0 to 741.1 mGy by the field dimensions and organ location relative to the field edge. Blocked field irradiations resulted in a dose range of 1.4–146.3 mGy. The most probable detriment from open field treatment of male patients was colon cancer with a high risk of 564.3 × 10{sup −5} to 837.4 × 10{sup −5} depending upon the organ dose magnitude and the patient's age. The corresponding colon cancer risk for female patients was (372.2–541.0) × 10{sup −5}. The probability of bladder cancer development was more than 113.7 × 10{sup −5} and 110.3 × 10{sup −5} for males and females, respectively. The cancer risk range to other individual organs was reduced to (0.003–68.5) × 10{sup −5}.Conclusions: The risk for cancer induction from radiation therapy for HO prophylaxis after total hip arthroplasty varies considerably by the
NASA Technical Reports Server (NTRS)
Holland, Frederic A., Jr.
2004-01-01
Modern engineering design practices are tending more toward the treatment of design parameters as random variables as opposed to fixed, or deterministic, values. The probabilistic design approach attempts to account for the uncertainty in design parameters by representing them as a distribution of values rather than as a single value. The motivations for this effort include preventing excessive overdesign as well as assessing and assuring reliability, both of which are important for aerospace applications. However, the determination of the probability distribution is a fundamental problem in reliability analysis. A random variable is often defined by the parameters of the theoretical distribution function that gives the best fit to experimental data. In many cases the distribution must be assumed from very limited information or data. Often the types of information that are available or reasonably estimated are the minimum, maximum, and most likely values of the design parameter. For these situations the beta distribution model is very convenient because the parameters that define the distribution can be easily determined from these three pieces of information. Widely used in the field of operations research, the beta model is very flexible and is also useful for estimating the mean and standard deviation of a random variable given only the aforementioned three values. However, an assumption is required to determine the four parameters of the beta distribution from only these three pieces of information (some of the more common distributions, like the normal, lognormal, gamma, and Weibull distributions, have two or three parameters). The conventional method assumes that the standard deviation is a certain fraction of the range. The beta parameters are then determined by solving a set of equations simultaneously. A new method developed in-house at the NASA Glenn Research Center assumes a value for one of the beta shape parameters based on an analogy with the normal
Measurement of total risk of spontaneous abortion: the virtue of conditional risk estimation.
Modvig, J; Schmidt, L; Damsgaard, M T
1990-12-01
The concepts, methods, and problems of measuring spontaneous abortion risk are reviewed. The problems touched on include the process of pregnancy verification, the changes in risk by gestational age and maternal age, and the presence of induced abortions. Methods used in studies of spontaneous abortion risk include biochemical assays as well as life table technique, although the latter appears in two different forms. The consequences of using either of these are discussed. It is concluded that no study design so far is appropriate for measuring the total risk of spontaneous abortion from early conception to the end of the 27th week. It is proposed that pregnancy may be considered to consist of two or three specific periods and that different study designs should concentrate on measuring the conditional risk within each period. A careful estimate using this principle leads to an estimate of total risk of spontaneous abortion of 0.33.
NASA Technical Reports Server (NTRS)
Vitali, Roberto; Lutomski, Michael G.
2004-01-01
National Aeronautics and Space Administration s (NASA) International Space Station (ISS) Program uses Probabilistic Risk Assessment (PRA) as part of its Continuous Risk Management Process. It is used as a decision and management support tool to not only quantify risk for specific conditions, but more importantly comparing different operational and management options to determine the lowest risk option and provide rationale for management decisions. This paper presents the derivation of the probability distributions used to quantify the failure rates and the probability of failures of the basic events employed in the PRA model of the ISS. The paper will show how a Bayesian approach was used with different sources of data including the actual ISS on orbit failures to enhance the confidence in results of the PRA. As time progresses and more meaningful data is gathered from on orbit failures, an increasingly accurate failure rate probability distribution for the basic events of the ISS PRA model can be obtained. The ISS PRA has been developed by mapping the ISS critical systems such as propulsion, thermal control, or power generation into event sequences diagrams and fault trees. The lowest level of indenture of the fault trees was the orbital replacement units (ORU). The ORU level was chosen consistently with the level of statistically meaningful data that could be obtained from the aerospace industry and from the experts in the field. For example, data was gathered for the solenoid valves present in the propulsion system of the ISS. However valves themselves are composed of parts and the individual failure of these parts was not accounted for in the PRA model. In other words the failure of a spring within a valve was considered a failure of the valve itself.
Fujimoto, Shinichiro; Kondo, Takeshi; Yamamoto, Hideya; Yokoyama, Naoyuki; Tarutani, Yasuhiro; Takamura, Kazuhisa; Urabe, Yoji; Konno, Kumiko; Nishizaki, Yuji; Shinozaki, Tomohiro; Kihara, Yasuki; Daida, Hiroyuki; Isshiki, Takaaki; Takase, Shinichi
2015-09-01
Existing methods to calculate pre-test probability of obstructive coronary artery disease (CAD) have been established using selected high-risk patients who were referred to conventional coronary angiography. The purpose of this study is to develop and validate our new method for pre-test probability of obstructive CAD using patients who underwent coronary CT angiography (CTA), which could be applicable to a wider range of patient population. Using consecutive 4137 patients with suspected CAD who underwent coronary CTA at our institution, a multivariate logistic regression model including clinical factors as covariates calculated the pre-test probability (K-score) of obstructive CAD determined by coronary CTA. The K-score was compared with the Duke clinical score using the area under the curve (AUC) for the receiver-operating characteristic curve. External validation was performed by an independent sample of 319 patients. The final model included eight significant predictors: age, gender, coronary risk factor (hypertension, diabetes mellitus, dyslipidemia, smoking), history of cerebral infarction, and chest symptom. The AUC of the K-score was significantly greater than that of the Duke clinical score for both derivation (0.736 vs. 0.699) and validation (0.714 vs. 0.688) data sets. Among patients who underwent coronary CTA, newly developed K-score had better pre-test prediction ability of obstructive CAD compared to Duke clinical score in Japanese population.
At Risk of What? Possibilities over Probabilities in the Study of Young Lives
ERIC Educational Resources Information Center
Foster, Karen Rebecca; Spencer, Dale
2011-01-01
This paper draws on a series of 45 interviews with recipients of social assistance between the ages of 16 and 24 to offer a critical assessment of the language of "risk" and "resilience." After briefly tracing the development of this vocabulary and approach in youth research, this paper argues in line with existing critiques (Kelly 2000, te Riele…
Numeracy, Ratio Bias, and Denominator Neglect in Judgments of Risk and Probability
ERIC Educational Resources Information Center
Reyna, Valerie F.; Brainerd, Charles J.
2008-01-01
"Numeracy," so-called on analogy with literacy, is essential for making health and other social judgments in everyday life [Reyna, V. F., & Brainerd, C. J. (in press). The importance of mathematics in health and human judgment: Numeracy, risk communication, and medical decision making. "Learning and Individual Differences."]. Recent research on…
Estimation of wildfire size and risk changes due to fuels treatments
Cochrane, M.A.; Moran, C.J.; Wimberly, M.C.; Baer, A.D.; Finney, M.A.; Beckendorf, K.L.; Eidenshink, J.; Zhu, Z.
2012-01-01
Human land use practices, altered climates, and shifting forest and fire management policies have increased the frequency of large wildfires several-fold. Mitigation of potential fire behaviour and fire severity have increasingly been attempted through pre-fire alteration of wildland fuels using mechanical treatments and prescribed fires. Despite annual treatment of more than a million hectares of land, quantitative assessments of the effectiveness of existing fuel treatments at reducing the size of actual wildfires or how they might alter the risk of burning across landscapes are currently lacking. Here, we present a method for estimating spatial probabilities of burning as a function of extant fuels treatments for any wildland fire-affected landscape. We examined the landscape effects of more than 72 000 ha of wildland fuel treatments involved in 14 large wildfires that burned 314 000 ha of forests in nine US states between 2002 and 2010. Fuels treatments altered the probability of fire occurrence both positively and negatively across landscapes, effectively redistributing fire risk by changing surface fire spread rates and reducing the likelihood of crowning behaviour. Trade offs are created between formation of large areas with low probabilities of increased burning and smaller, well-defined regions with reduced fire risk.
NRC committee provides new risk estimates for exposure to radon
Not Available
1988-03-01
A new set of age-specific estimates describing the increased risk of lung cancer following exposure to radon was released in January by a National Research Council committee. The revised estimates result from new statistical techniques used to analyze previously collected data. In a study jointly sponsored by the Environmental Protection Agency (EPA) and the Nuclear Regulatory Commission, the committee concluded that lifetime exposure to one working level month (WLM) of radon per year, a standard measure used by radiation experts, increases an individual's chances of dying from lung cancer by 1.5 times compared with someone exposed only to background levels of radon. The committee estimated that, for every 1 million people exposed over a lifetime to one WLM of radon, about 350 additional deaths would occur due to lung cancer. The committee found that lung cancer risks associated with radon increased with increasing length of exposure. Moreover, it said that 15 years after exposure to radon has ended, the risk of lung cancer from the exposure declines to half the original risk.
Wu, Yunfeng; Shi, Lei
2011-04-01
Human locomotion is regulated by the central nervous system (CNS). The neurophysiological changes in the CNS due to amyotrophic lateral sclerosis (ALS) may cause altered gait cycle duration (stride interval) or other gait rhythm. This article used a statistical method to analyze the altered stride interval in patients with ALS. We first estimated the probability density functions (PDFs) of stride interval from the outlier-processed gait rhythm time series, by using the nonparametric Parzen-window approach. Based on the PDFs estimated, the mean of the left-foot stride interval and the modified Kullback-Leibler divergence (MKLD) can be computed to serve as dominant features. In the classification experiments, the least squares support vector machine (LS-SVM) with Gaussian kernels was applied to distinguish the stride patterns in ALS patients. According to the results obtained with the stride interval time series recorded from 16 healthy control subjects and 13 patients with ALS, the key findings of the present study are summarized as follows. (1) It is observed that the mean of stride interval computed based on the PDF for the left foot is correlated with that for the right foot in patients with ALS. (2) The MKLD parameter of the gait in ALS is significantly different from that in healthy controls. (3) The diagnostic performance of the nonlinear LS-SVM, evaluated by the leave-one-out cross-validation method, is superior to that obtained by the linear discriminant analysis. The LS-SVM can effectively separate the stride patterns between the groups of healthy controls and ALS patients with an overall accurate rate of 82.8% and an area of 0.869 under the receiver operating characteristic curve. PMID:21130016
Sato, Tatsuhiko; Hamada, Nobuyuki
2014-01-01
We here propose a new model assembly for estimating the surviving fraction of cells irradiated with various types of ionizing radiation, considering both targeted and nontargeted effects in the same framework. The probability densities of specific energies in two scales, which are the cell nucleus and its substructure called a domain, were employed as the physical index for characterizing the radiation fields. In the model assembly, our previously established double stochastic microdosimetric kinetic (DSMK) model was used to express the targeted effect, whereas a newly developed model was used to express the nontargeted effect. The radioresistance caused by overexpression of anti-apoptotic protein Bcl-2 known to frequently occur in human cancer was also considered by introducing the concept of the adaptive response in the DSMK model. The accuracy of the model assembly was examined by comparing the computationally and experimentally determined surviving fraction of Bcl-2 cells (Bcl-2 overexpressing HeLa cells) and Neo cells (neomycin resistant gene-expressing HeLa cells) irradiated with microbeam or broadbeam of energetic heavy ions, as well as the WI-38 normal human fibroblasts irradiated with X-ray microbeam. The model assembly reproduced very well the experimentally determined surviving fraction over a wide range of dose and linear energy transfer (LET) values. Our newly established model assembly will be worth being incorporated into treatment planning systems for heavy-ion therapy, brachytherapy, and boron neutron capture therapy, given critical roles of the frequent Bcl-2 overexpression and the nontargeted effect in estimating therapeutic outcomes and harmful effects of such advanced therapeutic modalities.
Wu, Yunfeng; Shi, Lei
2011-04-01
Human locomotion is regulated by the central nervous system (CNS). The neurophysiological changes in the CNS due to amyotrophic lateral sclerosis (ALS) may cause altered gait cycle duration (stride interval) or other gait rhythm. This article used a statistical method to analyze the altered stride interval in patients with ALS. We first estimated the probability density functions (PDFs) of stride interval from the outlier-processed gait rhythm time series, by using the nonparametric Parzen-window approach. Based on the PDFs estimated, the mean of the left-foot stride interval and the modified Kullback-Leibler divergence (MKLD) can be computed to serve as dominant features. In the classification experiments, the least squares support vector machine (LS-SVM) with Gaussian kernels was applied to distinguish the stride patterns in ALS patients. According to the results obtained with the stride interval time series recorded from 16 healthy control subjects and 13 patients with ALS, the key findings of the present study are summarized as follows. (1) It is observed that the mean of stride interval computed based on the PDF for the left foot is correlated with that for the right foot in patients with ALS. (2) The MKLD parameter of the gait in ALS is significantly different from that in healthy controls. (3) The diagnostic performance of the nonlinear LS-SVM, evaluated by the leave-one-out cross-validation method, is superior to that obtained by the linear discriminant analysis. The LS-SVM can effectively separate the stride patterns between the groups of healthy controls and ALS patients with an overall accurate rate of 82.8% and an area of 0.869 under the receiver operating characteristic curve.
Krieger, D.J.; Hoehn, J.P.
1999-05-01
Obtaining economically consistent values for changes in low probability health risks continues to be a challenge for contingent valuation (CV) as well as for other valuation methods. One of the cited condition for economic consistency is that estimated values be sensitive to the scope (differences in quantity or quality) of a good described in a CV application. The alleged limitations of CV pose a particular problem for environmental managers who must often make decisions that affect human health risks. This paper demonstrates that a well-designed CV application can elicit scope sensitive values even for programs that provide conceptually complex goods such as risk reduction. Specifically, it finds that the amount sport anglers are willing to pay for information about chemical residues in fish varies systematically with informativeness--a relationship suggested by the theory of information value.
Coe, J.A.; Godt, J.W.; Parise, M.; Moscariello, A.
2003-01-01
We have used stratigraphic and historic records of debris-flows to estimate mean recurrence intervals of past debris-flow events on 19 fans along the Interstate 70 highway corridor in the Front Range of Colorado. Estimated mean recurrence intervals were used in the Poisson probability model to estimate the probability of future debris-flow events on the fans. Mean recurrence intervals range from 7 to about 2900 years. Annual probabilities range from less than 0.1% to about 13%. A regression analysis of mean recurrence interval data and drainage-basin morphometry yields a regression model that may be suitable to estimate mean recurrence intervals on fans with no stratigraphic or historic records. Additional work is needed to verify this model. ?? 2003 Millpress.
Estimating Skin Cancer Risk: Evaluating Mobile Computer-Adaptive Testing
Djaja, Ngadiman; Janda, Monika; Olsen, Catherine M; Whiteman, David C
2016-01-01
Background Response burden is a major detriment to questionnaire completion rates. Computer adaptive testing may offer advantages over non-adaptive testing, including reduction of numbers of items required for precise measurement. Objective Our aim was to compare the efficiency of non-adaptive (NAT) and computer adaptive testing (CAT) facilitated by Partial Credit Model (PCM)-derived calibration to estimate skin cancer risk. Methods We used a random sample from a population-based Australian cohort study of skin cancer risk (N=43,794). All 30 items of the skin cancer risk scale were calibrated with the Rasch PCM. A total of 1000 cases generated following a normal distribution (mean [SD] 0 [1]) were simulated using three Rasch models with three fixed-item (dichotomous, rating scale, and partial credit) scenarios, respectively. We calculated the comparative efficiency and precision of CAT and NAT (shortening of questionnaire length and the count difference number ratio less than 5% using independent t tests). Results We found that use of CAT led to smaller person standard error of the estimated measure than NAT, with substantially higher efficiency but no loss of precision, reducing response burden by 48%, 66%, and 66% for dichotomous, Rating Scale Model, and PCM models, respectively. Conclusions CAT-based administrations of the skin cancer risk scale could substantially reduce participant burden without compromising measurement precision. A mobile computer adaptive test was developed to help people efficiently assess their skin cancer risk. PMID:26800642
Estimating the subjective risks of driving simulator accidents.
Dixit, Vinayak; Harrison, Glenn W; Rutström, E Elisabet
2014-01-01
We examine the subjective risks of driving behavior using a controlled virtual reality experiment. Use of a driving simulator allows us to observe choices over risky alternatives that are presented to the individual in a naturalistic manner, with many of the cues one would find in the field. However, the use of a simulator allows us the type of controls one expects from a laboratory environment. The subject was tasked with making a left-hand turn into incoming traffic, and the experimenter controlled the headways of oncoming traffic. Subjects were rewarded for making a successful turn, and lost income if they crashed. The experimental design provided opportunities for subjects to develop subjective beliefs about when it would be safe to turn, and it also elicited their attitudes towards risk. A simple structural model explains behavior, and showed evidence of heterogeneity in both the subjective beliefs that subjects formed and their risk attitudes. We find that subjective beliefs change with experience in the task and the driver's skill. A significant difference was observed in the perceived probability to successfully turn among the inexperienced drivers who did and did not crash even though there was no significant difference in drivers' risk attitudes among the two groups. We use experimental economics to design controlled, incentive compatible tasks that provide an opportunity to evaluate the impact on driver safety of subject's subjective beliefs about when it would be safe to turn as well as their attitudes towards risk. This method could be used to help insurance companies determine risk premia associated with risk attitudes or beliefs of crashing, to better incentivize safe driving.
A Review of Expertise and Judgment Processes for Risk Estimation
R. L. Boring
2007-06-01
A major challenge of risk and reliability analysis for human errors or hardware failures is the need to enlist expert opinion in areas for which adequate operational data are not available. Experts enlisted in this capacity provide probabilistic estimates of reliability, typically comprised of a measure of central tendency and uncertainty bounds. While formal guidelines for expert elicitation are readily available, they largely fail to provide a theoretical basis for expertise and judgment. This paper reviews expertise and judgment in the context of risk analysis; overviews judgment biases, the role of training, and multivariate judgments; and provides guidance on the appropriate use of atomistic and holistic judgment processes.
Eregno, Fasil Ejigu; Tryland, Ingun; Tjomsland, Torulv; Myrmel, Mette; Robertson, Lucy; Heistad, Arve
2016-04-01
This study investigated the public health risk from exposure to infectious microorganisms at Sandvika recreational beaches, Norway and dose-response relationships by combining hydrodynamic modelling with Quantitative Microbial Risk Assessment (QMRA). Meteorological and hydrological data were collected to produce a calibrated hydrodynamic model using Escherichia coli as an indicator of faecal contamination. Based on average concentrations of reference pathogens (norovirus, Campylobacter, Salmonella, Giardia and Cryptosporidium) relative to E. coli in Norwegian sewage from previous studies, the hydrodynamic model was used for simulating the concentrations of pathogens at the local beaches during and after a heavy rainfall event, using three different decay rates. The simulated concentrations were used as input for QMRA and the public health risk was estimated as probability of infection from a single exposure of bathers during the three consecutive days after the rainfall event. The level of risk on the first day after the rainfall event was acceptable for the bacterial and parasitic reference pathogens, but high for the viral reference pathogen at all beaches, and severe at Kalvøya-small and Kalvøya-big beaches, supporting the advice of avoiding swimming in the day(s) after heavy rainfall. The study demonstrates the potential of combining discharge-based hydrodynamic modelling with QMRA in the context of bathing water as a tool to evaluate public health risk and support beach management decisions. PMID:26802355
Clinical probability and risk analysis of patients with suspected pulmonary embolism
Yetgin, Gulden Ozeren; Aydin, Sule Akkose; Koksal, Ozlem; Ozdemir, Fatma; Mert, Dilek Kostak; Torun, Gokhan
2014-01-01
BACKGROUND: Pulmonary embolism (PE) is one of the most frequent diseases that could be missed in overcrowded emergency departments as in Turkey. Early and accurate diagnosis could decrease the mortality rate and this standard algorithm should be defined. This study is to find the accurate, fast, non-invasive, cost-effective, easy-to-access diagnostic tests, clinical scoring systems and the patients who should be tested for clinical diagnosis of PE in emergency department. METHODS: One hundred and forty patients admitted to the emergency department with the final diagnosis of PE regarding to anamnesis, physical examination and risk factors, were included in this prospective, cross-sectional study. The patients with a diagnosis of pulmonary embolism, acute coronary syndrome or infection and chronic obstructive pulmonary disease (COPD) were excluded from the study. The demographics, risk factors, radiological findings, vital signs, symptoms, physical-laboratory findings, diagnostic tests and clinical scoring systems of patients (Wells and Geneva) were noted. The diagnostic criteria for pulmonary emboli were: filling defect in the pulmonary artery lumen on spiral computed tomographic angiography and perfusion defect on perfusion scintigraphy. RESULTS: Totally, 90 (64%) of the patients had PE. Age, hypotension, having deep vein thrombosis were the risk factors, and oxygen saturation, shock index, BNP, troponin and fibrinogen levels as for the biochemical parameters were significantly different between the PE (+) and PE (−) groups (P<0.05). The Wells scoring system was more successful than the other scoring systems. CONCLUSION: Biochemical parameters, clinical findings, and scoring systems, when used altogether, can contribute to the diagnosis of PE. PMID:25548599
Estimation of radiation risk for astronauts on the Moon
NASA Astrophysics Data System (ADS)
Kuznetsov, N. V.; Nymmik, R. A.; Panasyuk, M. I.; Denisov, A. N.; Sobolevsky, N. M.
2012-05-01
The problem of estimating the risk of radiation for humans on the Moon is discussed, taking into account the probabilistic nature of occurrence of solar particle events. Calculations of the expected values of tissue-averaged equivalent dose rates, which are created by galactic and solar cosmic-ray particle fluxes on the lunar surface behind shielding, are made for different durations of lunar missions.
Markiewicz, Łukasz; Kubińska, Elżbieta
2015-01-01
Objective: This paper aims to provide insight into information processing differences between hot and cold risk taking decision tasks within a single domain. Decision theory defines risky situations using at least three parameters: outcome one (often a gain) with its probability and outcome two (often a loss) with a complementary probability. Although a rational agent should consider all of the parameters, s/he could potentially narrow their focus to only some of them, particularly when explicit Type 2 processes do not have the resources to override implicit Type 1 processes. Here we investigate differences in risky situation parameters' influence on hot and cold decisions. Although previous studies show lower information use in hot than in cold processes, they do not provide decision weight changes and therefore do not explain whether this difference results from worse concentration on each parameter of a risky situation (probability, gain amount, and loss amount) or from ignoring some parameters. Methods: Two studies were conducted, with participants performing the Columbia Card Task (CCT) in either its Cold or Hot version. In the first study, participants also performed the Cognitive Reflection Test (CRT) to monitor their ability to override Type 1 processing cues (implicit processes) with Type 2 explicit processes. Because hypothesis testing required comparison of the relative importance of risky situation decision weights (gain, loss, probability), we developed a novel way of measuring information use in the CCT by employing a conjoint analysis methodology. Results: Across the two studies, results indicated that in the CCT Cold condition decision makers concentrate on each information type (gain, loss, probability), but in the CCT Hot condition they concentrate mostly on a single parameter: probability of gain/loss. We also show that an individual's CRT score correlates with information use propensity in cold but not hot tasks. Thus, the affective dimension of
Risk estimation of infectious diseases determines the effectiveness of the control strategy
NASA Astrophysics Data System (ADS)
Zhang, Haifeng; Zhang, Jie; Li, Ping; Small, Michael; Wang, Binghong
2011-05-01
Usually, whether to take vaccination or not is a voluntary decision, which is determined by many factors, from societal factors (such as religious belief and human rights) to individual preferences (including psychology and altruism). Facing the outbreaks of infectious diseases, different people often have different estimations on the risk of infectious diseases. So, some persons are willing to vaccinate, but other persons are willing to take risks. In this paper, we establish two different risk assessment systems using the technique of dynamic programming, and then compare the effects of the two different systems on the prevention of diseases on complex networks. One is that the perceived probability of being infected for each individual is the same (uniform case). The other is that the perceived probability of being infected is positively correlated to individual degrees (preferential case). We show that these two risk assessment systems can yield completely different results, such as, the effectiveness of controlling diseases, the time evolution of the number of infections, and so on.
Use of binary logistic regression technique with MODIS data to estimate wild fire risk
NASA Astrophysics Data System (ADS)
Fan, Hong; Di, Liping; Yang, Wenli; Bonnlander, Brian; Li, Xiaoyan
2007-11-01
Many forest fires occur across the globe each year, which destroy life and property, and strongly impact ecosystems. In recent years, wildland fires and altered fire disturbance regimes have become a significant management and science problem affecting ecosystems and wildland/urban interface cross the United States and global. In this paper, we discuss the estimation of 504 probability models for forecasting fire risk for 14 fuel types, 12 months, one day/week/month in advance, which use 19 years of historical fire data in addition to meteorological and vegetation variables. MODIS land products are utilized as a major data source, and a logistical binary regression was adopted to solve fire forecast probability. In order to better modeling the change of fire risk along with the transition of seasons, some spatial and temporal stratification strategies were applied. In order to explore the possibilities of real time prediction, the Matlab distributing computing toolbox was used to accelerate the prediction. Finally, this study give an evaluation and validation of predict based on the ground truth collected. Validating results indicate these fire risk models have achieved nearly 70% accuracy of prediction and as well MODIS data are potential data source to implement near real-time fire risk prediction.
Improved risk estimates for carbon tetrachloride. 1998 annual progress report
Benson, J.M.; Springer, D.L.; Thrall, K.D.
1998-06-01
'The overall purpose of these studies is to improve the scientific basis for assessing the cancer risk associated with human exposure to carbon tetrachloride. Specifically, the toxicokinetics of inhaled carbon tetrachloride is being determined in rats, mice and hamsters. Species differences in the metabolism of carbon tetrachloride by rats, mice and hamsters is being determined in vivo and in vitro using tissues and microsomes from these rodent species and man. Dose-response relationships will be determined in all studies. The information will be used to improve the current physiologically based pharmacokinetic model for carbon tetrachloride. The authors will also determine whether carbon tetrachloride is a hepatocarcinogen only when exposure results in cell damage, cell killing, and regenerative cell proliferation. In combination, the results of these studies will provide the types of information needed to enable a refined risk estimate for carbon tetrachloride under EPA''s new guidelines for cancer risk assessment.'
Risk estimation based on chromosomal aberrations induced by radiation
NASA Technical Reports Server (NTRS)
Durante, M.; Bonassi, S.; George, K.; Cucinotta, F. A.
2001-01-01
The presence of a causal association between the frequency of chromosomal aberrations in peripheral blood lymphocytes and the risk of cancer has been substantiated recently by epidemiological studies. Cytogenetic analyses of crew members of the Mir Space Station have shown that a significant increase in the frequency of chromosomal aberrations can be detected after flight, and that such an increase is likely to be attributed to the radiation exposure. The risk of cancer can be estimated directly from the yields of chromosomal aberrations, taking into account some aspects of individual susceptibility and other factors unrelated to radiation. However, the use of an appropriate technique for the collection and analysis of chromosomes and the choice of the structural aberrations to be measured are crucial in providing sound results. Based on the fraction of aberrant lymphocytes detected before and after flight, the relative risk after a long-term Mir mission is estimated to be about 1.2-1.3. The new technique of mFISH can provide useful insights into the quantification of risk on an individual basis.
A comparison of genetic risk score with family history for estimating prostate cancer risk
Helfand, Brian T
2016-01-01
Prostate cancer (PCa) testing is recommended by most authoritative groups for high-risk men including those with a family history of the disease. However, family history information is often limited by patient knowledge and clinician intake, and thus, many men are incorrectly assigned to different risk groups. Alternate methods to assess PCa risk are required. In this review, we discuss how genetic variants, referred to as PCa-risk single-nucleotide polymorphisms, can be used to calculate a genetic risk score (GRS). GRS assigns a relatively unique value to all men based on the number of PCa-risk SNPs that an individual carries. This GRS value can provide a more precise estimate of a man's PCa risk. This is particularly relevant in situations when an individual is unaware of his family history. In addition, GRS has utility and can provide a more precise estimate of risk even among men with a positive family history. It can even distinguish risk among relatives with the same degree of family relationships. Taken together, this review serves to provide support for the clinical utility of GRS as an independent test to provide supplemental information to family history. As such, GRS can serve as a platform to help guide-shared decision-making processes regarding the timing and frequency of PCa testing and biopsies. PMID:27004541
NASA Astrophysics Data System (ADS)
Dutton, John A.; James, Richard P.; Ross, Jeremy D.
2013-06-01
Seasonal probability forecasts produced with numerical dynamics on supercomputers offer great potential value in managing risk and opportunity created by seasonal variability. The skill and reliability of contemporary forecast systems can be increased by calibration methods that use the historical performance of the forecast system to improve the ongoing real-time forecasts. Two calibration methods are applied to seasonal surface temperature forecasts of the US National Weather Service, the European Centre for Medium Range Weather Forecasts, and to a World Climate Service multi-model ensemble created by combining those two forecasts with Bayesian methods. As expected, the multi-model is somewhat more skillful and more reliable than the original models taken alone. The potential value of the multimodel in decision making is illustrated with the profits achieved in simulated trading of a weather derivative. In addition to examining the seasonal models, the article demonstrates that calibrated probability forecasts of weekly average temperatures for leads of 2-4 weeks are also skillful and reliable. The conversion of ensemble forecasts into probability distributions of impact variables is illustrated with degree days derived from the temperature forecasts. Some issues related to loss of stationarity owing to long-term warming are considered. The main conclusion of the article is that properly calibrated probabilistic forecasts possess sufficient skill and reliability to contribute to effective decisions in government and business activities that are sensitive to intraseasonal and seasonal climate variability.
Britton, Annie; O’Neill, Darragh; Bell, Steven
2016-01-01
Aims Increases in glass sizes and wine strength over the last 25 years in the UK are likely to have led to an underestimation of alcohol intake in population studies. We explore whether this probable misclassification affects the association between average alcohol intake and risk of mortality from all causes, cardiovascular disease and cancer. Methods Self-reported alcohol consumption in 1997–1999 among 7010 men and women in the Whitehall II cohort of British civil servants was linked to the risk of mortality until mid-2015. A conversion factor of 8 g of alcohol per wine glass (1 unit) was compared with a conversion of 16 g per wine glass (2 units). Results When applying a higher alcohol content conversion for wine consumption, the proportion of heavy/very heavy drinkers increased from 28% to 41% for men and 15% to 28% for women. There was a significantly increased risk of very heavy drinking compared with moderate drinking for deaths from all causes and cancer before and after change in wine conversion; however, the hazard ratios were reduced when a higher wine conversion was used. Conclusions In this population-based study, assuming higher alcohol content in wine glasses changed the estimates of mortality risk. We propose that investigator-led cohorts need to revisit conversion factors based on more accurate estimates of alcohol content in wine glasses. Prospectively, researchers need to collect more detailed information on alcohol including serving sizes and strength. Short summary The alcohol content in a wine glass is likely to be underestimated in population surveys as wine strength and serving size have increased in recent years. We demonstrate that in a large cohort study, this underestimation affects estimates of mortality risk. Investigator-led cohorts need to revisit conversion factors based on more accurate estimates of alcohol content in wine glasses. PMID:27261472
Be rich or don't be sick: estimating Vietnamese patients' risk of falling into destitution.
Vuong, Quan Hoang
2015-01-01
This paper represents the first research attempt to estimate the probabilities of Vietnamese patients falling into destitution due to financial burdens occurring during a curative hospital stay. The study models risk against such factors as level of insurance coverage, residency status of patient, and cost of treatment, among others. The results show that very high probabilities of destitution, approximately 70 %, apply to a large group of patients, who are non-residents, poor and ineligible for significant insurance coverage. There is also a probability of 58 % that seriously ill low-income patients who face higher health care costs would quit their treatment. These facts put the Vietnamese government's ambitious plan of increasing both universal coverage (UC) to 100 % of expenditure and the rate of UC beneficiaries to 100 %, to a serious test. The current study also raises issues of asymmetric information and alternative financing options for the poor, who are most exposed to risk of destitution following market-based health care reforms. PMID:26413435
Risk cross sections and their application to risk estimation in the galactic cosmic-ray environment.
Curtis, S B; Nealy, J E; Wilson, J W
1995-01-01
Radiation risk cross sections (i.e. risks per particle fluence) are discussed in the context of estimating the risk of radiation-induced cancer on long-term space flights from the galactic cosmic radiation outside the confines of the earth's magnetic field. Such quantities are useful for handling effects not seen after low-LET radiation. Since appropriate cross-section functions for cancer induction for each particle species are not yet available, the conventional quality factor is used as an approximation to obtain numerical results for risks of excess cancer mortality. Risks are obtained for seven of the most radiosensitive organs as determined by the ICRP [stomach, colon, lung, bone marrow (BFO), bladder, esophagus and breast], beneath 10 g/cm2 aluminum shielding at solar minimum. Spectra are obtained for excess relative risk for each cancer per LET interval by calculating the average fluence-LET spectrum for the organ and converting to risk by multiplying by a factor proportional to R gamma L Q(L) before integrating over L, the unrestricted LET. Here R gamma is the risk coefficient for low-LET radiation (excess relative mortality per Sv) for the particular organ in question. The total risks of excess cancer mortality obtained are 1.3 and 1.1% to female and male crew, respectively, for a 1-year exposure at solar minimum. Uncertainties in these values are estimated to range between factors of 4 and 15 and are dominated by the biological uncertainties in the risk coefficients for low-LET radiation and in the LET (or energy) dependence of the risk cross sections (as approximated by the quality factor). The direct substitution of appropriate risk cross sections will eventually circumvent entirely the need to calculate, measure or use absorbed dose, equivalent dose and quality factor for such a high-energy charged-particle environment. PMID:7997515
Risk cross sections and their application to risk estimation in the galactic cosmic-ray environment
NASA Technical Reports Server (NTRS)
Curtis, S. B.; Nealy, J. E.; Wilson, J. W.; Chatterjee, A. (Principal Investigator)
1995-01-01
Radiation risk cross sections (i.e. risks per particle fluence) are discussed in the context of estimating the risk of radiation-induced cancer on long-term space flights from the galactic cosmic radiation outside the confines of the earth's magnetic field. Such quantities are useful for handling effects not seen after low-LET radiation. Since appropriate cross-section functions for cancer induction for each particle species are not yet available, the conventional quality factor is used as an approximation to obtain numerical results for risks of excess cancer mortality. Risks are obtained for seven of the most radiosensitive organs as determined by the ICRP [stomach, colon, lung, bone marrow (BFO), bladder, esophagus and breast], beneath 10 g/cm2 aluminum shielding at solar minimum. Spectra are obtained for excess relative risk for each cancer per LET interval by calculating the average fluence-LET spectrum for the organ and converting to risk by multiplying by a factor proportional to R gamma L Q(L) before integrating over L, the unrestricted LET. Here R gamma is the risk coefficient for low-LET radiation (excess relative mortality per Sv) for the particular organ in question. The total risks of excess cancer mortality obtained are 1.3 and 1.1% to female and male crew, respectively, for a 1-year exposure at solar minimum. Uncertainties in these values are estimated to range between factors of 4 and 15 and are dominated by the biological uncertainties in the risk coefficients for low-LET radiation and in the LET (or energy) dependence of the risk cross sections (as approximated by the quality factor). The direct substitution of appropriate risk cross sections will eventually circumvent entirely the need to calculate, measure or use absorbed dose, equivalent dose and quality factor for such a high-energy charged-particle environment.
Estimation of value at risk and conditional value at risk using normal mixture distributions model
NASA Astrophysics Data System (ADS)
Kamaruzzaman, Zetty Ain; Isa, Zaidi
2013-04-01
Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.
Ennis, Erin J; Foley, Joe P
2016-07-15
A stochastic approach was utilized to estimate the probability of a successful isocratic or gradient separation in conventional chromatography for numbers of sample components, peak capacities, and saturation factors ranging from 2 to 30, 20-300, and 0.017-1, respectively. The stochastic probabilities were obtained under conditions of (i) constant peak width ("gradient" conditions) and (ii) peak width increasing linearly with time ("isocratic/constant N" conditions). The isocratic and gradient probabilities obtained stochastically were compared with the probabilities predicted by Martin et al. [Anal. Chem., 58 (1986) 2200-2207] and Davis and Stoll [J. Chromatogr. A, (2014) 128-142]; for a given number of components and peak capacity the same trend is always observed: probability obtained with the isocratic stochastic approach<probability obtained with the gradient stochastic approach≤probability predicted by Davis and Stoll < probability predicted by Martin et al. The differences are explained by the positive bias of the Martin equation and the lower average resolution observed for the isocratic simulations compared to the gradient simulations with the same peak capacity. When the stochastic results are applied to conventional HPLC and sequential elution liquid chromatography (SE-LC), the latter is shown to provide much greater probabilities of success for moderately complex samples (e.g., PHPLC=31.2% versus PSE-LC=69.1% for 12 components and the same analysis time). For a given number of components, the density of probability data provided over the range of peak capacities is sufficient to allow accurate interpolation of probabilities for peak capacities not reported, <1.5% error for saturation factors <0.20. Additional applications for the stochastic approach include isothermal and programmed-temperature gas chromatography.
Leukemia risk associated with benzene exposure in the pliofilm cohort. II. Risk estimates.
Paxton, M B; Chinchilli, V M; Brett, S M; Rodricks, J V
1994-04-01
The detailed work histories of the individual workers composing the Pliofilm cohort represent a unique resource for estimating the dose-response for leukemia that may follow occupational exposure to benzene. In this paper, we report the results of analyzing the updated Pliofilm cohort using the proportional hazards model, a more sophisticated technique that uses more of the available exposure data than the conditional logistic model used by Rinsky et al. The more rigorously defined exposure estimates derived by Paustenbach et al. are consistent with those of Crump and Allen in giving estimates of the slope of the leukemogenic dose-response that are not as steep as the slope resulting from the exposure estimates of Rinsky et al. We consider estimates of 0.3-0.5 additional leukemia deaths per thousand workers with 45 ppm-years of cumulative benzene exposure to be the best estimates currently available of leukemia risk from occupational exposure to benzene. These risks were estimated in the proportional hazards model when the exposure estimates of Crump and Allen or of Paustenbach et al. were used to derive a cumulative concentration-by-time metric. PMID:8008924
NASA Technical Reports Server (NTRS)
George, Kerry A.; Rhone, J.; Chappell, L. J.; Cucinotta, F. A.
2011-01-01
To date, cytogenetic damage has been assessed in blood lymphocytes from more than 30 astronauts before and after they participated in long-duration space missions of three months or more on board the International Space Station. Chromosome damage was assessed using fluorescence in situ hybridization whole chromosome analysis techniques. For all individuals, the frequency of chromosome damage measured within a month of return from space was higher than their preflight yield, and biodosimetry estimates were within the range expected from physical dosimetry. Follow up analyses have been performed on most of the astronauts at intervals ranging from around 6 months to many years after flight, and the cytogenetic effects of repeat long-duration missions have so far been assessed in four individuals. Chromosomal aberrations in peripheral blood lymphocytes have been validated as biomarkers of cancer risk and cytogenetic damage can therefore be used to characterize excess health risk incurred by individual crewmembers after their respective missions. Traditional risk assessment models are based on epidemiological data obtained on Earth in cohorts exposed predominantly to acute doses of gamma-rays, and the extrapolation to the space environment is highly problematic, involving very large uncertainties. Cytogenetic damage could play a key role in reducing uncertainty in risk estimation because it is incurred directly in the space environment, using specimens from the astronauts themselves. Relative cancer risks were estimated from the biodosimetry data using the quantitative approach derived from the European Study Group on Cytogenetic Biomarkers and Health database. Astronauts were categorized into low, medium, or high tertiles according to their yield of chromosome damage. Age adjusted tertile rankings were used to estimate cancer risk and results were compared with values obtained using traditional modeling approaches. Individual tertile rankings increased after space
The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).
Austin, Peter C
2010-09-10
Propensity score methods are increasingly being used to estimate the effects of treatments on health outcomes using observational data. There are four methods for using the propensity score to estimate treatment effects: covariate adjustment using the propensity score, stratification on the propensity score, propensity-score matching, and inverse probability of treatment weighting (IPTW) using the propensity score. When outcomes are binary, the effect of treatment on the outcome can be described using odds ratios, relative risks, risk differences, or the number needed to treat. Several clinical commentators suggested that risk differences and numbers needed to treat are more meaningful for clinical decision making than are odds ratios or relative risks. However, there is a paucity of information about the relative performance of the different propensity-score methods for estimating risk differences. We conducted a series of Monte Carlo simulations to examine this issue. We examined bias, variance estimation, coverage of confidence intervals, mean-squared error (MSE), and type I error rates. A doubly robust version of IPTW had superior performance compared with the other propensity-score methods. It resulted in unbiased estimation of risk differences, treatment effects with the lowest standard errors, confidence intervals with the correct coverage rates, and correct type I error rates. Stratification, matching on the propensity score, and covariate adjustment using the propensity score resulted in minor to modest bias in estimating risk differences. Estimators based on IPTW had lower MSE compared with other propensity-score methods. Differences between IPTW and propensity-score matching may reflect that these two methods estimate the average treatment effect and the average treatment effect for the treated, respectively.
NASA Technical Reports Server (NTRS)
Huddleston, Lisa L.; Roeder, William; Merceret, Francis J.
2010-01-01
A technique has been developed to calculate the probability that any nearby lightning stroke is within any radius of any point of interest. In practice, this provides the probability that a nearby lightning stroke was within a key distance of a facility, rather than the error ellipses centered on the stroke. This process takes the current bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to get the probability that the stroke is inside any specified radius. This new facility-centric technique will be much more useful to the space launch customers and may supersede the lightning error ellipse approach discussed in [5], [6].
Estimating Worker Risk Levels Using Accident/Incident Data
Kenoyer, Judson L.; Stenner, Robert D.; Andrews, William B.; Scherpelz, Robert I.; Aaberg, Rosanne L.
2000-09-26
The purpose of the work described in this report was to identify methods that are currently being used in the Department of Energy (DOE) complex to identify and control hazards/risks in the workplace, evaluate them in terms of their effectiveness in reducing risk to the workers, and to develop a preliminary method that could be used to predict the relative risks to workers performing proposed tasks using some of the current methodology. This report describes some of the performance indicators (i.e., safety metrics) that are currently being used to track relative levels of workplace safety in the DOE complex, how these fit into an Integrated Safety Management (ISM) system, some strengths and weaknesses of using a statistically based set of indicators, and methods to evaluate them. Also discussed are methods used to reduce risk to the workers and some of the techniques that appear to be working in the process of establishing a condition of continuous improvement. The results of these methods will be used in future work involved with the determination of modifying factors for a more complex model. The preliminary method to predict the relative risk level to workers during an extended future time period is based on a currently used performance indicator that uses several factors tracked in the CAIRS. The relative risks for workers in a sample (but real) facility on the Hanford site are estimated for a time period of twenty years and are based on workforce predictions. This is the first step in developing a more complex model that will incorporate other modifying factors related to the workers, work environment and status of the ISM system to adjust the preliminary prediction.
NASA Technical Reports Server (NTRS)
Cross, Robert
2005-01-01
Until Solid Rocket Motor ignition, the Space Shuttle is mated to the Mobil Launch Platform in part via eight (8) Solid Rocket Booster (SRB) hold-down bolts. The bolts are fractured using redundant pyrotechnics, and are designed to drop through a hold-down post on the Mobile Launch Platform before the Space Shuttle begins movement. The Space Shuttle program has experienced numerous failures where a bolt has "hung-up." That is, it did not clear the hold-down post before liftoff and was caught by the SRBs. This places an additional structural load on the vehicle that was not included in the original certification requirements. The Space Shuttle is currently being certified to withstand the loads induced by up to three (3) of eight (8) SRB hold-down post studs experiencing a "hang-up." The results af loads analyses performed for four (4) stud-hang ups indicate that the internal vehicle loads exceed current structural certification limits at several locations. To determine the risk to the vehicle from four (4) stud hang-ups, the likelihood of the scenario occurring must first be evaluated. Prior to the analysis discussed in this paper, the likelihood of occurrence had been estimated assuming that the stud hang-ups were completely independent events. That is, it was assumed that no common causes or factors existed between the individual stud hang-up events. A review of the data associated with the hang-up events, showed that a common factor (timing skew) was present. This paper summarizes a revised likelihood evaluation performed for the four (4) stud hang-ups case considering that there are common factors associated with the stud hang-ups. The results show that explicitly (i.e. not using standard common cause methodologies such as beta factor or Multiple Greek Letter modeling) taking into account the common factor of timing skew results in an increase in the estimated likelihood of four (4) stud hang-ups of an order of magnitude over the independent failure case.
NASA Technical Reports Server (NTRS)
Cross, Robert
2005-01-01
Until Solid Rocket Motor ignition, the Space Shuttle is mated to the Mobil Launch Platform in part via eight (8) Solid Rocket Booster (SRB) hold-down bolts. The bolts are fractured using redundant pyrotechnics, and are designed to drop through a hold-down post on the Mobile Launch Platform before the Space Shuttle begins movement. The Space Shuttle program has experienced numerous failures where a bolt has hung up. That is, it did not clear the hold-down post before liftoff and was caught by the SRBs. This places an additional structural load on the vehicle that was not included in the original certification requirements. The Space Shuttle is currently being certified to withstand the loads induced by up to three (3) of eight (8) SRB hold-down experiencing a "hang-up". The results of loads analyses performed for (4) stud hang-ups indicate that the internal vehicle loads exceed current structural certification limits at several locations. To determine the risk to the vehicle from four (4) stud hang-ups, the likelihood of the scenario occurring must first be evaluated. Prior to the analysis discussed in this paper, the likelihood of occurrence had been estimated assuming that the stud hang-ups were completely independent events. That is, it was assumed that no common causes or factors existed between the individual stud hang-up events. A review of the data associated with the hang-up events, showed that a common factor (timing skew) was present. This paper summarizes a revised likelihood evaluation performed for the four (4) stud hang-ups case considering that there are common factors associated with the stud hang-ups. The results show that explicitly (i.e. not using standard common cause methodologies such as beta factor or Multiple Greek Letter modeling) taking into account the common factor of timing skew results in an increase in the estimated likelihood of four (4) stud hang-ups of an order of magnitude over the independent failure case.
Global Building Inventory for Earthquake Loss Estimation and Risk Management
Jaiswal, Kishor; Wald, David; Porter, Keith
2010-01-01
We develop a global database of building inventories using taxonomy of global building types for use in near-real-time post-earthquake loss estimation and pre-earthquake risk analysis, for the U.S. Geological Survey’s Prompt Assessment of Global Earthquakes for Response (PAGER) program. The database is available for public use, subject to peer review, scrutiny, and open enhancement. On a country-by-country level, it contains estimates of the distribution of building types categorized by material, lateral force resisting system, and occupancy type (residential or nonresidential, urban or rural). The database draws on and harmonizes numerous sources: (1) UN statistics, (2) UN Habitat’s demographic and health survey (DHS) database, (3) national housing censuses, (4) the World Housing Encyclopedia and (5) other literature.
Estimation of risks associated with paediatric cochlear implantation.
Johnston, J Cyne; Smith, Andrée Durieux; Fitzpatrick, Elizabeth; O'Connor, Annette; Angus, Douglas; Benzies, Karen; Schramm, David
2010-09-01
The objectives of this study were to estimate the rates of complications associated with paediatric cochlear implantation use: a) at one Canadian cochlear implant (CI) centre, and b) in the published literature. It comprised a retrospective hospital-based chart review and a concurrent review of complications in the published literature. There were 224 children who had undergone surgery from 1994 to June 2007. Results indicate that the rates of complications at the local Canadian paediatric CI centre are not significantly different from the literature rates for all examined complication types. This hospital-based retrospective chart review and review of the literature provide readers with an estimation of the risks to aid in evidence-based decision-making surrounding paediatric cochlear implantation.
Casemore, David
2006-01-01
Worldwide literature on serological methods and sero-surveys on waterborne pathogens has been reviewed. Outbreak investigation and research reports have also been examined to aid understanding of the serological response and transmission dynamics. The aim was to seek an estimate of seroprevalence and to determine if this could inform the US national estimate of risk for endemic waterborne infection associated with public water supplies. Antibody responses indicate infection, both symptomatic and asymptomatic, so probably give a truer indication of prevalence. Outbreak data can probably be regarded as the upper bound for seroprevalence estimations. Antibody is not necessarily protective per se but is a good indicator for at least partial resistance to symptomatic infection; absence of antibody will normally imply susceptibility. Pathogens transmitted by water are commonly transmitted by other routes. However, the fact that other transmission routes are more common does not detract from the potential protective effect of immunity when waterborne transmission occurs. Data indicate that seroprevalence varies widely, reflecting geographic, social and hygiene factors, but is generally greater where surface water sources are used rather than groundwater. Areas of low seroprevalence may expect a high attack rate in the event of contamination of their water supply.
Code of Federal Regulations, 2010 CFR
2010-07-01
... Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for... identify and estimate safety and environmental management risks and appropriate risk reduction strategies... environmental management risks and report or correct the situation, as appropriate. Federal agencies must...
Austin, Peter C; Stuart, Elizabeth A
2015-12-10
The propensity score is defined as a subject's probability of treatment selection, conditional on observed baseline covariates. Weighting subjects by the inverse probability of treatment received creates a synthetic sample in which treatment assignment is independent of measured baseline covariates. Inverse probability of treatment weighting (IPTW) using the propensity score allows one to obtain unbiased estimates of average treatment effects. However, these estimates are only valid if there are no residual systematic differences in observed baseline characteristics between treated and control subjects in the sample weighted by the estimated inverse probability of treatment. We report on a systematic literature review, in which we found that the use of IPTW has increased rapidly in recent years, but that in the most recent year, a majority of studies did not formally examine whether weighting balanced measured covariates between treatment groups. We then proceed to describe a suite of quantitative and qualitative methods that allow one to assess whether measured baseline covariates are balanced between treatment groups in the weighted sample. The quantitative methods use the weighted standardized difference to compare means, prevalences, higher-order moments, and interactions. The qualitative methods employ graphical methods to compare the distribution of continuous baseline covariates between treated and control subjects in the weighted sample. Finally, we illustrate the application of these methods in an empirical case study. We propose a formal set of balance diagnostics that contribute towards an evolving concept of 'best practice' when using IPTW to estimate causal treatment effects using observational data. PMID:26238958
ERIC Educational Resources Information Center
Herek, Gregory M.
2009-01-01
Using survey responses collected via the Internet from a U.S. national probability sample of gay, lesbian, and bisexual adults (N = 662), this article reports prevalence estimates of criminal victimization and related experiences based on the target's sexual orientation. Approximately 20% of respondents reported having experienced a person or…
Estimate of the risks of disposing nonhazardous oil field wastes into salt caverns
Tomasko, D.; Elcock, D.; Veil, J.
1997-12-31
Argonne National Laboratory (ANL) has completed an evaluation of the possibility that adverse human health effects (carcinogenic and noncarcinogenic) could result from exposure to contaminants released from nonhazardous oil field wastes (NOW) disposed in domal salt caverns. Potential human health risks associated with hazardous substances (arsenic, benzene, cadmium, and chromium) in NOW were assessed under four postclosure cavern release scenarios: inadvertent cavern intrusion, failure of the cavern seal, failure of the cavern through cracks or leaky interbeds, and a partial collapse of the cavern roof. To estimate potential human health risks for these scenarios, contaminant concentrations at the receptor were calculated using a one-dimensional solution to an advection/dispersion equation that included first order degradation. Assuming a single, generic salt cavern and generic oil-field wastes, the best-estimate excess cancer risks ranged from 1.7 {times} 10{sup {minus}12} to 1.1 {times} 10{sup {minus}8} and hazard indices (referring to noncancer health effects) ranged from 7 {times} 10{sup {minus}9} to 7 {times} 10{sup {minus}4}. Under worse-case conditions in which the probability of cavern failure is 1.0, excess cancer risks ranged from 4.9 {times} 10{sup {minus}9} to 1.7 {times} 10{sup {minus}5} and hazard indices ranged from 7.0 {times} 10{sup {minus}4} to 0.07. Even under worst-case conditions, the risks are within the US Environmental Protection Agency (EPA) target range for acceptable exposure levels. From a human health risk perspective, salt caverns can, therefore, provide an acceptable disposal method for NOW.
Mara, D D; Sleigh, P A; Blumenthal, U J; Carr, R M
2007-03-01
The combination of standard quantitative microbial risk analysis (QMRA) techniques and 10,000-trial Monte Carlo risk simulations was used to estimate the human health risks associated with the use of wastewater for unrestricted and restricted crop irrigation. A risk of rotavirus infection of 10(-2) per person per year (pppy) was used as the reference level of acceptable risk. Using the model scenario of involuntary soil ingestion for restricted irrigation, the risk of rotavirus infection is approximately 10(-2) pppy when the wastewater contains < or =10(6) Escherichia coli per 100ml and when local agricultural practices are highly mechanised. For labour-intensive agriculture the risk of rotavirus infection is approximately 10(-2) pppy when the wastewater contains < or = 10(5) E. coli per 100ml; however, the wastewater quality should be < or = 10(4) E. coli per 100ml when children under 15 are exposed. With the model scenario of lettuce consumption for unrestricted irrigation, the use of wastewaters containing < or =10(4) E. coli per 100ml results in a rotavirus infection risk of approximately 10(-2) pppy; however, again based on epidemiological evidence from Mexico, the current WHO guideline level of < or =1,000 E. coli per 100ml should be retained for root crops eaten raw. PMID:17402278
Time-to-Compromise Model for Cyber Risk Reduction Estimation
Miles A. McQueen; Wayne F. Boyer; Mark A. Flynn; George A. Beitel
2005-09-01
We propose a new model for estimating the time to compromise a system component that is visible to an attacker. The model provides an estimate of the expected value of the time-to-compromise as a function of known and visible vulnerabilities, and attacker skill level. The time-to-compromise random process model is a composite of three subprocesses associated with attacker actions aimed at the exploitation of vulnerabilities. In a case study, the model was used to aid in a risk reduction estimate between a baseline Supervisory Control and Data Acquisition (SCADA) system and the baseline system enhanced through a specific set of control system security remedial actions. For our case study, the total number of system vulnerabilities was reduced by 86% but the dominant attack path was through a component where the number of vulnerabilities was reduced by only 42% and the time-to-compromise of that component was increased by only 13% to 30% depending on attacker skill level.
Ellison, L.E.; O'Shea, T.J.; Neubaum, D.J.; Neubaum, M.A.; Pearce, R.D.; Bowen, R.A.
2007-01-01
We compared conventional capture (primarily mist nets and harp traps) and passive integrated transponder (PIT) tagging techniques for estimating capture and survival probabilities of big brown bats (Eptesicus fuscus) roosting in buildings in Fort Collins, Colorado. A total of 987 female adult and juvenile bats were captured and marked by subdermal injection of PIT tags during the summers of 2001-2005 at five maternity colonies in buildings. Openings to roosts were equipped with PIT hoop-style readers, and exit and entry of bats were passively monitored on a daily basis throughout the summers of 2002-2005. PIT readers 'recaptured' adult and juvenile females more often than conventional capture events at each roost. Estimates of annual capture probabilities for all five colonies were on average twice as high when estimated from PIT reader data (P?? = 0.93-1.00) than when derived from conventional techniques (P?? = 0.26-0.66), and as a consequence annual survival estimates were more precisely estimated when using PIT reader encounters. Short-term, daily capture estimates were also higher using PIT readers than conventional captures. We discuss the advantages and limitations of using PIT tags and passive encounters with hoop readers vs. conventional capture techniques for estimating these vital parameters in big brown bats. ?? Museum and Institute of Zoology PAS.
Daly, Megan E.; Luxton, Gary; Choi, Clara Y.H.; Gibbs, Iris C.; Chang, Steven D.; Adler, John R.; Soltys, Scott G.
2012-04-01
Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear-quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18-30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8-30.9 Gy) and 22.0 Gy (range, 20.2-26.6 Gy), respectively. By use of conventional values for {alpha}/{beta}, volume parameter n, 50% complication probability dose TD{sub 50}, and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of {alpha}/{beta} and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of {alpha}/{beta} and n yielded better predictions (0.7 complications), with n = 0.023 and {alpha}/{beta} = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high {alpha}/{beta} value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models
Moving towards a new paradigm for global flood risk estimation
NASA Astrophysics Data System (ADS)
Troy, Tara J.; Devineni, Naresh; Lima, Carlos; Lall, Upmanu
2013-04-01
model is implemented at a finer resolution (<=1km) in order to more accurately model streamflow under flood conditions and estimate inundation. This approach allows for efficient computational simulation of the hydrology when not under potential for flooding with high-resolution flood wave modeling when there is flooding potential. We demonstrate the results of this flood risk estimation system for the Ohio River basin in the United States, a large river basin that is historically prone to flooding, with the intention of using it to do global flood risk assessment.
Qu, Mingkai; Li, Weidong; Zhang, Chuanrong; Huang, Biao; Zhao, Yongcun
2014-01-01
Estimating standard-exceeding probabilities of toxic metals in soil is crucial for environmental evaluation. Because soil pH and land use types have strong effects on the bioavailability of trace metals in soil, they were taken into account by some environmental protection agencies in making composite soil environmental quality standards (SEQSs) that contain multiple metal thresholds under different pH and land use conditions. This study proposed a method for estimating the standard-exceeding probability map of soil cadmium using a composite SEQS. The spatial variability and uncertainty of soil pH and site-specific land use type were incorporated through simulated realizations by sequential Gaussian simulation. A case study was conducted using a sample data set from a 150 km(2) area in Wuhan City and the composite SEQS for cadmium, recently set by the State Environmental Protection Administration of China. The method may be useful for evaluating the pollution risks of trace metals in soil with composite SEQSs.
Huang, Biao; Zhao, Yongcun
2014-01-01
Estimating standard-exceeding probabilities of toxic metals in soil is crucial for environmental evaluation. Because soil pH and land use types have strong effects on the bioavailability of trace metals in soil, they were taken into account by some environmental protection agencies in making composite soil environmental quality standards (SEQSs) that contain multiple metal thresholds under different pH and land use conditions. This study proposed a method for estimating the standard-exceeding probability map of soil cadmium using a composite SEQS. The spatial variability and uncertainty of soil pH and site-specific land use type were incorporated through simulated realizations by sequential Gaussian simulation. A case study was conducted using a sample data set from a 150 km2 area in Wuhan City and the composite SEQS for cadmium, recently set by the State Environmental Protection Administration of China. The method may be useful for evaluating the pollution risks of trace metals in soil with composite SEQSs. PMID:24672364
Declining bioavailability and inappropriate estimation of risk of persistent compounds
Kelsey, J.W.; Alexander, M.
1997-03-01
Earthworms (Eisenia foetida) assimilated decreasing amounts of atrazine, phenanthrene, and naphthalene that had been incubated for increasing periods of time in sterile soil. The amount of atrazine and phenanthrene removed from soil by mild extractants also decreased with time. The declines in bioavailability of the three compounds to earthworms and of naphthalene to bacteria were not reflected by analysis involving vigorous methods of solvent extraction; similar results for bioavailability of phenanthrene and 4-nitrophenol to bacteria were obtained in a previous study conducted at this laboratory. The authors suggest that regulations based on vigorous extractions for the analyses of persistent organic pollutants in soil do not appropriately estimate exposure or risk to susceptible populations.
How do we measure dose and estimate risk?
NASA Astrophysics Data System (ADS)
Hoeschen, Christoph; Regulla, Dieter; Schlattl, Helmut; Petoussi-Henss, Nina; Li, Wei Bo; Zankl, Maria
2011-03-01
Radiation exposure due to medical imaging is a topic of emerging importance. In Europe this topic has been dealt with for a long time and in other countries it is getting more and more important and it gets an aspect of public interest in the latest years. This is mainly true due to the fact that the average dose per person in developed countries is increasing rapidly since threedimensional imaging is getting more and more available and useful for diagnosis. This paper introduces the most common dose quantities used in medical radiation exposure characterization, discusses usual ways for determination of such quantities as well as some considerations how these values are linked to radiation risk estimation. For this last aspect the paper will refer to the linear non threshold theory for an imaging application.
Uncertainties in estimating health risks associated with exposure to ionising radiation.
Preston, R Julian; Boice, John D; Brill, A Bertrand; Chakraborty, Ranajit; Conolly, Rory; Hoffman, F Owen; Hornung, Richard W; Kocher, David C; Land, Charles E; Shore, Roy E; Woloschak, Gayle E
2013-09-01
The information for the present discussion on the uncertainties associated with estimation of radiation risks and probability of disease causation was assembled for the recently published NCRP Report No. 171 on this topic. This memorandum provides a timely overview of the topic, given that quantitative uncertainty analysis is the state of the art in health risk assessment and given its potential importance to developments in radiation protection. Over the past decade the increasing volume of epidemiology data and the supporting radiobiology findings have aided in the reduction of uncertainty in the risk estimates derived. However, it is equally apparent that there remain significant uncertainties related to dose assessment, low dose and low dose-rate extrapolation approaches (e.g. the selection of an appropriate dose and dose-rate effectiveness factor), the biological effectiveness where considerations of the health effects of high-LET and lower-energy low-LET radiations are required and the transfer of risks from a population for which health effects data are available to one for which such data are not available. The impact of radiation on human health has focused in recent years on cancer, although there has been a decided increase in the data for noncancer effects together with more reliable estimates of the risk following radiation exposure, even at relatively low doses (notably for cataracts and cardiovascular disease). New approaches for the estimation of hereditary risk have been developed with the use of human data whenever feasible, although the current estimates of heritable radiation effects still are based on mouse data because of an absence of effects in human studies. Uncertainties associated with estimation of these different types of health effects are discussed in a qualitative and semi-quantitative manner as appropriate. The way forward would seem to require additional epidemiological studies, especially studies of low dose and low dose
Uncertainties in estimating health risks associated with exposure to ionising radiation.
Preston, R Julian; Boice, John D; Brill, A Bertrand; Chakraborty, Ranajit; Conolly, Rory; Hoffman, F Owen; Hornung, Richard W; Kocher, David C; Land, Charles E; Shore, Roy E; Woloschak, Gayle E
2013-09-01
The information for the present discussion on the uncertainties associated with estimation of radiation risks and probability of disease causation was assembled for the recently published NCRP Report No. 171 on this topic. This memorandum provides a timely overview of the topic, given that quantitative uncertainty analysis is the state of the art in health risk assessment and given its potential importance to developments in radiation protection. Over the past decade the increasing volume of epidemiology data and the supporting radiobiology findings have aided in the reduction of uncertainty in the risk estimates derived. However, it is equally apparent that there remain significant uncertainties related to dose assessment, low dose and low dose-rate extrapolation approaches (e.g. the selection of an appropriate dose and dose-rate effectiveness factor), the biological effectiveness where considerations of the health effects of high-LET and lower-energy low-LET radiations are required and the transfer of risks from a population for which health effects data are available to one for which such data are not available. The impact of radiation on human health has focused in recent years on cancer, although there has been a decided increase in the data for noncancer effects together with more reliable estimates of the risk following radiation exposure, even at relatively low doses (notably for cataracts and cardiovascular disease). New approaches for the estimation of hereditary risk have been developed with the use of human data whenever feasible, although the current estimates of heritable radiation effects still are based on mouse data because of an absence of effects in human studies. Uncertainties associated with estimation of these different types of health effects are discussed in a qualitative and semi-quantitative manner as appropriate. The way forward would seem to require additional epidemiological studies, especially studies of low dose and low dose
Code of Federal Regulations, 2013 CFR
2013-07-01
... (Continued) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Safety and Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for... identify and estimate safety and environmental management risks and appropriate risk reduction...
Code of Federal Regulations, 2014 CFR
2014-01-01
... (Continued) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Safety and Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for... identify and estimate safety and environmental management risks and appropriate risk reduction...
Code of Federal Regulations, 2012 CFR
2012-01-01
... (Continued) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Safety and Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for... identify and estimate safety and environmental management risks and appropriate risk reduction...
Code of Federal Regulations, 2011 CFR
2011-01-01
... (Continued) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Safety and Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for... identify and estimate safety and environmental management risks and appropriate risk reduction...
Estimation of Tsunami Risk for the Caribbean Coast
NASA Astrophysics Data System (ADS)
Zahibo, N.
2004-05-01
The tsunami problem for the coast of the Caribbean basin is discussed. Briefly the historical data of tsunami in the Caribbean Sea are presented. Numerical simulation of potential tsunamis in the Caribbean Sea is performed in the framework of the nonlinear-shallow theory. The tsunami wave height distribution along the Caribbean Coast is computed. These results are used to estimate the far-field tsunami potential of various coastal locations in the Caribbean Sea. In fact, five zones with tsunami low risk are selected basing on prognostic computations, they are: the bay "Golfo de Batabano" and the coast of province "Ciego de Avila" in Cuba, the Nicaraguan Coast (between Bluefields and Puerto Cabezas), the border between Mexico and Belize, the bay "Golfo de Venezuela" in Venezuela. The analysis of historical data confirms that there was no tsunami in the selected zones. Also, the wave attenuation in the Caribbean Sea is investigated; in fact, wave amplitude decreases in an order if the tsunami source is located on the distance up to 1000 km from the coastal location. Both factors wave attenuation and wave height distribution should be taken into account in the planned warning system for the Caribbean Sea. Specially the problem of tsunami risk for Lesser Antilles including Guadeloupe is discussed.
How to Estimate Epidemic Risk from Incomplete Contact Diaries Data?
Mastrandrea, Rossana; Barrat, Alain
2016-01-01
Social interactions shape the patterns of spreading processes in a population. Techniques such as diaries or proximity sensors allow to collect data about encounters and to build networks of contacts between individuals. The contact networks obtained from these different techniques are however quantitatively different. Here, we first show how these discrepancies affect the prediction of the epidemic risk when these data are fed to numerical models of epidemic spread: low participation rate, under-reporting of contacts and overestimation of contact durations in contact diaries with respect to sensor data determine indeed important differences in the outcomes of the corresponding simulations with for instance an enhanced sensitivity to initial conditions. Most importantly, we investigate if and how information gathered from contact diaries can be used in such simulations in order to yield an accurate description of the epidemic risk, assuming that data from sensors represent the ground truth. The contact networks built from contact sensors and diaries present indeed several structural similarities: this suggests the possibility to construct, using only the contact diary network information, a surrogate contact network such that simulations using this surrogate network give the same estimation of the epidemic risk as simulations using the contact sensor network. We present and compare several methods to build such surrogate data, and show that it is indeed possible to obtain a good agreement between the outcomes of simulations using surrogate and sensor data, as long as the contact diary information is complemented by publicly available data describing the heterogeneity of the durations of human contacts. PMID:27341027
Liu, Xiao-Ru; Deng, Ze-Yuan; Hu, Jiang-Ning; Fan, Ya-Wei; Liu, Rong; Li, Jing; Peng, Jing-Tian; Su, Hai; Peng, Qiang; Li, Wei-Feng
2013-05-01
Industry-generated trans-fatty acids (TFA) are detrimental to risk of CHD, but ruminant-originated TFA have been reported as neutral or equivocal. Therefore, the total TFA amount should not be the only factor considered when measuring the effects of TFA. In the present study, we addressed whether a version of the TFA index that unifies the effects of different TFA isomers into one equation could be used to reflect CHD risk probability (RP). The present cross-sectional study involved 2713 individuals divided into four groups that represented different pathological severities and potential risks of CHD: acute coronary syndrome (ACS, n 581); chronic coronary artery disease (CCAD, n 631); high-risk population (HRP, n 659); healthy volunteers (HV, n 842). A 10-year CHD RP was calculated. Meanwhile, the equation of the TFA index was derived using five TFA isomers (trans-16 : 1n-7, trans-16 : 1n-9, trans-18 : 1n-7, trans-18 : 1n-9 and trans-18 : 2n-6n-9), which were detected in the whole blood, serum and erythrocyte membranes of each subject. The TFA index and the 10-year CHD RP were compared by linear models. It was shown that only in the erythrocyte membrane, the TFA isomers were significantly different between the groups. In the ACS group, industry-generated TFA (trans-16 : 1n-9, trans-18 : 1n-9 and trans-18 : 2n-6n-9) were the highest, whereas ruminant-originated TFA (trans-16 : 1n-7 and trans-18 : 1n-7), which manifested an inverse relationship with CHD, were the lowest, and vice versa in the HV group. The TFA index decreased progressively from 7·12 to 5·06, 3·11 and 1·92 in the ACS, CCAD, HRP and HV groups, respectively. The erythrocyte membrane TFA index was positively associated with the 10-year CHD RP (R 2 0·9981) and manifested a strong linear correlation, which might reflect the true pathological severity of CHD.
NASA Astrophysics Data System (ADS)
Siettos, Constantinos I.; Anastassopoulou, Cleo; Russo, Lucia; Grigoras, Christos; Mylonakis, Eleftherios
2016-06-01
Based on multiscale agent-based computations we estimated the per-contact probability of transmission by age of the Ebola virus disease (EVD) that swept through Liberia from May 2014 to March 2015. For the approximation of the epidemic dynamics we have developed a detailed agent-based model with small-world interactions between individuals categorized by age. For the estimation of the structure of the evolving contact network as well as the per-contact transmission probabilities by age group we exploited the so called Equation-Free framework. Model parameters were fitted to official case counts reported by the World Health Organization (WHO) as well as to recently published data of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate.
Cho, Hyunyi; Shen, Lijiang; Wilson, Kari M
2013-03-01
Perceived lack of realism in alcohol advertising messages promising positive outcomes and antialcohol and antidrug messages portraying negative outcomes of alcohol consumption has been a cause for public health concern. This study examined the effects of perceived realism dimensions on personal probability estimation through identification and message minimization. Data collected from college students in U.S. Midwest in 2010 (N = 315) were analyzed with multilevel structural equation modeling. Plausibility and narrative consistency mitigated message minimization, but they did not influence identification. Factuality and perceptual quality influenced both message minimization and identification, but their effects were smaller than those of typicality. Typicality was the strongest predictor of probability estimation. Implications of the results and suggestions for future research are provided.
NASA Astrophysics Data System (ADS)
Parsons, T.
2009-12-01
After a large earthquake, our concern immediately moves to the likelihood that another large shock could be triggered, threatening an already weakened building stock. A key question is whether it is best to map out Coulomb stress change calculations shortly after mainshocks to potentially highlight the most likely aftershock locations, or whether it is more prudent to wait until the best information is available. It has been shown repeatedly that spatial aftershock patterns can be matched with Coulomb stress change calculations a year or more after mainshocks. However, with the onset of rapid source slip model determinations, the method has produced encouraging results like the M=8.7 earthquake that was forecast using stress change calculations from 2004 great Sumatra earthquake by McCloskey et al. [2005]. Here, I look back at two additional prospective calculations published shortly after the 2005 M=7.6 Kashmir and 2008 M=8.0 Wenchuan earthquakes. With the benefit of 1.5-4 years of additional seismicity, it is possible to assess the performance of rapid Coulomb stress change calculations. In the second part of the talk, within the context of the ongoing Working Group on California Earthquake Probabilities (WGCEP) assessments, uncertainties associated with time-dependent probability calculations are convolved with uncertainties inherent to Coulomb stress change calculations to assess the strength of signal necessary for a physics-based calculation to merit consideration into a formal earthquake forecast. Conclusions are as follows: (1) subsequent aftershock occurrence shows that prospective static stress change calculations both for Kashmir and Wenchuan examples failed to adequately predict the spatial post-mainshock earthquake distributions. (2) For a San Andreas fault example with relatively well-understood recurrence, a static stress change on the order of 30 to 40 times the annual stressing rate would be required to cause a significant (90%) perturbation to the
Estimating the Risk of Renal Stone Events During Long-Duration Spaceflight
NASA Technical Reports Server (NTRS)
Reyes, David; Kerstman, Eric; Locke, James
2014-01-01
Introduction: Given the bone loss and increased urinary calcium excretion in the microgravity environment, persons participating in long-duration spaceflight may have an increased risk for renal stone formation. Renal stones are often an incidental finding of abdominal imaging studies done for other reasons. Thus, some crewmembers may have undiscovered, asymptomatic stones prior to their mission. Methods: An extensive literature search was conducted concerning the natural history of asymptomatic renal stones. For comparison, simulations were done using the Integrated Medical Model (IMM). The IMM is an evidence-based decision support tool that provides risk analysis and has the capability to optimize medical systems for missions by minimizing the occurrence of adverse mission outcomes such as evacuation and loss of crew life within specified mass and volume constraints. Results: The literature of the natural history of asymptomatic renal stones in the general medical population shows that the probability of symptomatic event is 8% to 34% at 1 to 3 years for stones < 7 mm. Extrapolated to a 6-month mission, for stones < 5 to 7 mm, the risk for any stone event is about 4 to 6%, with a 0.7% to 4% risk for intervention, respectively. IMM simulations compare favorably with risk estimates garnered from the terrestrial literature. The IMM forecasts that symptomatic renal stones may be one of the top drivers for medical evacuation of an International Space Station (ISS) mission. Discussion: Although the likelihood of a stone event is low, the consequences could be severe due to limitations of current ISS medical capabilities. Therefore, these risks need to be quantified to aid planning, limit crew morbidity and mitigate mission impacts. This will be especially critical for missions beyond earth orbit, where evacuation may not be an option.
Measurement error affects risk estimates for recruitment to the Hudson River stock of striped bass.
Dunning, Dennis J; Ross, Quentin E; Munch, Stephan B; Ginzburg, Lev R
2002-06-01
We examined the consequences of ignoring the distinction between measurement error and natural variability in an assessment of risk to the Hudson River stock of striped bass posed by entrainment at the Bowline Point, Indian Point, and Roseton power plants. Risk was defined as the probability that recruitment of age-1+ striped bass would decline by 80% or more, relative to the equilibrium value, at least once during the time periods examined (1, 5, 10, and 15 years). Measurement error, estimated using two abundance indices from independent beach seine surveys conducted on the Hudson River, accounted for 50% of the variability in one index and 56% of the variability in the other. If a measurement error of 50% was ignored and all of the variability in abundance was attributed to natural causes, the risk that recruitment of age-1+ striped bass would decline by 80% or more after 15 years was 0.308 at the current level of entrainment mortality (11%). However, the risk decreased almost tenfold (0.032) if a measurement error of 50% was considered. The change in risk attributable to decreasing the entrainment mortality rate from 11 to 0% was very small (0.009) and similar in magnitude to the change in risk associated with an action proposed in Amendment #5 to the Interstate Fishery Management Plan for Atlantic striped bass (0.006)--an increase in the instantaneous fishing mortality rate from 0.33 to 0.4. The proposed increase in fishing mortality was not considered an adverse environmental impact, which suggests that potentially costly efforts to reduce entrainment mortality on the Hudson River stock of striped bass are not warranted.
Estimating the risk of collisions between bicycles and motor vehicles at signalized intersections.
Wang, Yinhai; Nihan, Nancy L
2004-05-01
Collisions between bicycles and motor vehicles have caused severe life and property losses in many countries. The majority of bicycle-motor vehicle (BMV) accidents occur at intersections. In order to reduce the number of BMV accidents at intersections, a substantial understanding of the causal factors for the collisions is required. In this study, intersection BMV accidents were classified into three types based on the movements of the involved motor vehicles and bicycles. The three BMV accident classifications were through motor vehicle related collisions, left-turn motor vehicle related collisions, and right-turn motor vehicle related collisions. A methodology for estimating these BMV accident risks was developed based on probability theory. A significant difference between this proposed methodology and most current approaches is that the proposed approach explicitly relates the risk of each specific BMV accident type to its related flows. The methodology was demonstrated using a 4-year (1992-1995) data set collected from 115 signalized intersections in the Tokyo Metropolitan area. This data set contains BMV accident data, bicycle flow data, motor vehicle flow data, traffic control data, and geometric data for each intersection approach. For each BMV risk model, an independent explanatory variable set was chosen according to the characteristics of the accident type. Three negative binomial regression models (one corresponding to each BMV accident type) were estimated using the maximum likelihood method. The coefficient value and its significance level were estimated for each selected variable. The negative binomial dispersion parameters for all the three models were significant at 0.01 levels. This supported the choice of the negative binomial regression over the Poisson regression for the quantitative analyses in this study.
Akamatsu, T; Wang, D; Wang, K; Li, S; Dong, S; Zhao, X; Barlow, J; Stewart, B S; Richlen, M
2008-06-01
Yangtze finless porpoises were surveyed by using simultaneous visual and acoustical methods from 6 November to 13 December 2006. Two research vessels towed stereo acoustic data loggers, which were used to store the intensity and sound source direction of the high frequency sonar signals produced by finless porpoises at detection ranges up to 300 m on each side of the vessel. Simple stereo beam forming allowed the separation of distinct biosonar sound source, which enabled us to count the number of vocalizing porpoises. Acoustically, 204 porpoises were detected from one vessel and 199 from the other vessel in the same section of the Yangtze River. Visually, 163 and 162 porpoises were detected from two vessels within 300 m of the vessel track. The calculated detection probability using acoustic method was approximately twice that for visual detection for each vessel. The difference in detection probabilities between the two methods was caused by the large number of single individuals that were missed by visual observers. However, the sizes of large groups were underestimated by using the acoustic methods. Acoustic and visual observations complemented each other in the accurate detection of porpoises. The use of simple, relatively inexpensive acoustic monitoring systems should enhance population surveys of free-ranging, echolocating odontocetes.
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Peskov, Nikolay V.; Kirillov, Dmitry A.
2012-10-01
One of the problems arising in Time-Domain THz spectroscopy for the problem of security is the developing the criteria for assessment of probability for the detection and identification of the explosive and drugs. We analyze the efficiency of using the correlation function and another functional (more exactly, spectral norm) for this aim. These criteria are applied to spectral lines dynamics. For increasing the reliability of the assessment we subtract the averaged value of THz signal during time of analysis of the signal: it means deleting the constant from this part of the signal. Because of this, we can increase the contrast of assessment. We compare application of the Fourier-Gabor transform with unbounded (for example, Gaussian) window, which slides along the signal, for finding the spectral lines dynamics with application of the Fourier transform in short time interval (FTST), in which the Fourier transform is applied to parts of the signals, for the same aim. These methods are close each to other. Nevertheless, they differ by series of frequencies which they use. It is important for practice that the optimal window shape depends on chosen method for obtaining the spectral dynamics. The probability enhancements if we can find the train of pulses with different frequencies, which follow sequentially. We show that there is possibility to get pure spectral lines dynamics even under the condition of distorted spectrum of the substance response on the action of the THz pulse.
NASA Astrophysics Data System (ADS)
Guo, B.; Matteo, E. N.; Elliot, T. R.; Nogues, J. P.; Deng, H.; Fitts, J. P.; Pollak, M.; Bielicki, J.; Wilson, E.; Celia, M. A.; Peters, C. A.
2011-12-01
Using the semi-analytical ELSA model, wellbore leakage risk is estimated for CO2 injection into either the Mt. Simon or St. Peter formations, which are part of the Michigan Sedimentary Basin that lies beneath Ottawa County, MI. ELSA is a vertically integrated subsurface modeling tool that can be used to simulate both supercritical CO2 plume distribution/migration and pressure- induced brine displacement during CO2 injection. A composite 3D subsurface domain was constructed for the ELSA simulations based on estimated permeabilities for formation layers, as well as GIS databases containing subsurface stratigraphy, active and inactive and inactive wells, and potential interactions with subsurface activities. These activities include potable aquifers, oil and gas reservoirs, and waste injection sites, which represent potential liabilities if encountered by brine or supercritical CO2 displaced from the injection formation. Overall, the 3D subsurface domain encompasses an area of 1500 km2 to a depth of 2 km and contains over 3,000 wells. The permeabilities for abandoned wells are derived from a ranking system based on available well data including historical records and well logs. This distribution is then randomly sampled in Monte Carlo simulations that are used to generate a probability map for subsurface interferences or atmospheric release resulting from leakage of CO2 and /or brine from the injection formation. This method serves as the basis for comparative testing between various scenarios for injection, as well as for comparing the relative risk of leakage between injection formations or storage sites.
Risk estimation of HNA-3 incompatibility and alloimmunization in Thai populations.
Nathalang, Oytip; Intharanut, Kamphon; Siriphanthong, Kanokpol; Nathalang, Siriporn; Leetrakool, Nipapan
2015-01-01
Severe transfusion-related acute lung injury (TRALI) is often due to antibodies in blood components directed against human neutrophil antigen (HNA)-3a. This study aimed to report the genotype frequencies of the HNA-3 system and to estimate the potential risk of HNA-3 incompatibility and alloimmunization in two Thai populations. Eight hundred DNA samples obtained from 500 unrelated healthy blood donors at the National Blood Centre, Thai Red Cross Society, Bangkok and 300 samples from the Blood Bank, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand were included. HNA-3 genotyping was performed using an in-house polymerase chain reaction with sequence-specific primer (PCR-SSP) technique. The observed frequencies of the HNA-3a/3a, HNA-3a/3b, and HNA-3b/3b genotypes were 0.528, 0.380, and 0.092 in central Thais and 0.600, 0.350, and 0.050 in northern Thais, respectively. The frequencies were used to estimate HNA-3 incompatibility and risk of HNA-3a alloimmunization. The HNA-3 incompatibility in central Thais (33.28%) was higher than northern Thais (28.75%), corresponding to a significantly higher probability of HNA-3a alloimmunization (P<0.05) similar to Japanese and Chinese populations. This study showed the high risk of HNA-3 incompatibility and alloimmunization, especially in central Thai blood donors. A molecular-based identification of the HNA-3 genotype of female donors is suggested to reduce the risk of TRALI following plasma and whole blood allogeneic transfusion.
Hussein, M; Aldridge, S; Guerrero Urbano, T; Nisbet, A
2012-01-01
Objective The aim of this study was to investigate the effect of 6 and 15-MV photon energies on intensity-modulated radiation therapy (IMRT) prostate cancer treatment plan outcome and to compare the theoretical risks of secondary induced malignancies. Methods Separate prostate cancer IMRT plans were prepared for 6 and 15-MV beams. Organ-equivalent doses were obtained through thermoluminescent dosemeter measurements in an anthropomorphic Aldersen radiation therapy human phantom. The neutron dose contribution at 15 MV was measured using polyallyl-diglycol-carbonate neutron track etch detectors. Risk coefficients from the International Commission on Radiological Protection Report 103 were used to compare the risk of fatal secondary induced malignancies in out-of-field organs and tissues for 6 and 15 MV. For the bladder and the rectum, a comparative evaluation of the risk using three separate models was carried out. Dose–volume parameters for the rectum, bladder and prostate planning target volume were evaluated, as well as normal tissue complication probability (NTCP) and tumour control probability calculations. Results There is a small increased theoretical risk of developing a fatal cancer from 6 MV compared with 15 MV, taking into account all the organs. Dose–volume parameters for the rectum and bladder show that 15 MV results in better volume sparing in the regions below 70 Gy, but the volume exposed increases slightly beyond this in comparison with 6 MV, resulting in a higher NTCP for the rectum of 3.6% vs 3.0% (p=0.166). Conclusion The choice to treat using IMRT at 15 MV should not be excluded, but should be based on risk vs benefit while considering the age and life expectancy of the patient together with the relative risk of radiation-induced cancer and NTCPs. PMID:22010028
ESTIMATING RISK TO CALIFORNIA ENERGY INFRASTRUCTURE FROM PROJECTED CLIMATE CHANGE
Sathaye, Jayant; Dale, Larry; Larsen, Peter; Fitts, Gary; Koy, Kevin; Lewis, Sarah; Lucena, Andre
2011-06-22
This report outlines the results of a study of the impact of climate change on the energy infrastructure of California and the San Francisco Bay region, including impacts on power plant generation; transmission line and substation capacity during heat spells; wildfires near transmission lines; sea level encroachment upon power plants, substations, and natural gas facilities; and peak electrical demand. Some end-of-century impacts were projected:Expected warming will decrease gas-fired generator efficiency. The maximum statewide coincident loss is projected at 10.3 gigawatts (with current power plant infrastructure and population), an increase of 6.2 percent over current temperature-induced losses. By the end of the century, electricity demand for almost all summer days is expected to exceed the current ninetieth percentile per-capita peak load. As much as 21 percent growth is expected in ninetieth percentile peak demand (per-capita, exclusive of population growth). When generator losses are included in the demand, the ninetieth percentile peaks may increase up to 25 percent. As the climate warms, California's peak supply capacity will need to grow faster than the population.Substation capacity is projected to decrease an average of 2.7 percent. A 5C (9F) air temperature increase (the average increase predicted for hot days in August) will diminish the capacity of a fully-loaded transmission line by an average of 7.5 percent.The potential exposure of transmission lines to wildfire is expected to increase with time. We have identified some lines whose probability of exposure to fire are expected to increase by as much as 40 percent. Up to 25 coastal power plants and 86 substations are at risk of flooding (or partial flooding) due to sea level rise.
Yarwood, Annie; Han, Buhm; Raychaudhuri, Soumya; Bowes, John; Lunt, Mark; Pappas, Dimitrios A; Kremer, Joel; Greenberg, Jeffrey D; Plenge, Robert; Worthington, Jane; Barton, Anne; Eyre, Steve
2015-01-01
Background There is currently great interest in the incorporation of genetic susceptibility loci into screening models to identify individuals at high risk of disease. Here, we present the first risk prediction model including all 46 known genetic loci associated with rheumatoid arthritis (RA). Methods A weighted genetic risk score (wGRS) was created using 45 RA non-human leucocyte antigen (HLA) susceptibility loci, imputed amino acids at HLA-DRB1 (11, 71 and 74), HLA-DPB1 (position 9) HLA-B (position 9) and gender. The wGRS was tested in 11 366 RA cases and 15 489 healthy controls. The risk of developing RA was estimated using logistic regression by dividing the wGRS into quintiles. The ability of the wGRS to discriminate between cases and controls was assessed by receiver operator characteristic analysis and discrimination improvement tests. Results Individuals in the highest risk group showed significantly increased odds of developing anti-cyclic citrullinated peptide-positive RA compared to the lowest risk group (OR 27.13, 95% CI 23.70 to 31.05). The wGRS was validated in an independent cohort that showed similar results (area under the curve 0.78, OR 18.00, 95% CI 13.67 to 23.71). Comparison of the full wGRS with a wGRS in which HLA amino acids were replaced by a HLA tag single-nucleotide polymorphism showed a significant loss of sensitivity and specificity. Conclusions Our study suggests that in RA, even when using all known genetic susceptibility variants, prediction performance remains modest; while this is insufficiently accurate for general population screening, it may prove of more use in targeted studies. Our study has also highlighted the importance of including HLA variation in risk prediction models. PMID:24092415
Biokinetic and dosimetric modelling in the estimation of radiation risks from internal emitters.
Harrison, John
2009-06-01
The International Commission on Radiological Protection (ICRP) has developed biokinetic and dosimetric models that enable the calculation of organ and tissue doses for a wide range of radionuclides. These are used to calculate equivalent and effective dose coefficients (dose in Sv Bq(-1) intake), considering occupational and environmental exposures. Dose coefficients have also been given for a range of radiopharmaceuticals used in diagnostic medicine. Using equivalent and effective dose, exposures from external sources and from different radionuclides can be summed for comparison with dose limits, constraints and reference levels that relate to risks from whole-body radiation exposure. Risk estimates are derived largely from follow-up studies of the survivors of the atomic bombings at Hiroshima and Nagasaki in 1945. New dose coefficients will be required following the publication in 2007 of new ICRP recommendations. ICRP biokinetic and dosimetric models are subject to continuing review and improvement, although it is arguable that the degree of sophistication of some of the most recent models is greater than required for the calculation of effective dose to a reference person for the purposes of regulatory control. However, the models are also used in the calculation of best estimates of doses and risks to individuals, in epidemiological studies and to determine probability of cancer causation. Models are then adjusted to best fit the characteristics of the individuals and population under consideration. For example, doses resulting from massive discharges of strontium-90 and other radionuclides to the Techa River from the Russian Mayak plutonium plant in the early years of its operation are being estimated using models adapted to take account of measurements on local residents and other population-specific data. Best estimates of doses to haemopoietic bone marrow, in utero and postnatally, are being used in epidemiological studies of radiation-induced leukaemia
Stevens, Michael R.; Flynn, Jennifer L.; Stephens, Verlin C.; Verdin, Kristine L.
2011-01-01
During 2009, the U.S. Geological Survey, in cooperation with Gunnison County, initiated a study to estimate the potential for postwildfire debris flows to occur in the drainage basins occupied by Carbonate, Slate, Raspberry, and Milton Creeks near Marble, Colorado. Currently (2010), these drainage basins are unburned but could be burned by a future wildfire. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of postwildfire debris-flow occurrence and debris-flow volumes for drainage basins occupied by Carbonate, Slate, Raspberry, and Milton Creeks near Marble. Data for the postwildfire debris-flow models included drainage basin area; area burned and burn severity; percentage of burned area; soil properties; rainfall total and intensity for the 5- and 25-year-recurrence, 1-hour-duration-rainfall; and topographic and soil property characteristics of the drainage basins occupied by the four creeks. A quasi-two-dimensional floodplain computer model (FLO-2D) was used to estimate the spatial distribution and the maximum instantaneous depth of the postwildfire debris-flow material during debris flow on the existing debris-flow fans that issue from the outlets of the four major drainage basins. The postwildfire debris-flow probabilities at the outlet of each drainage basin range from 1 to 19 percent for the 5-year-recurrence, 1-hour-duration rainfall, and from 3 to 35 percent for 25-year-recurrence, 1-hour-duration rainfall. The largest probabilities for postwildfire debris flow are estimated for Raspberry Creek (19 and 35 percent), whereas estimated debris-flow probabilities for the three other creeks range from 1 to 6 percent. The estimated postwildfire debris-flow volumes at the outlet of each creek range from 7,500 to 101,000 cubic meters for the 5-year-recurrence, 1-hour-duration rainfall, and from 9,400 to 126,000 cubic meters for
Gogolak, C.V.
1986-11-01
The concentration of a contaminant measured in a particular medium might be distributed as a positive random variable when it is present, but it may not always be present. If there is a level below which the concentration cannot be distinguished from zero by the analytical apparatus, a sample from such a population will be censored on the left. The presence of both zeros and positive values in the censored portion of such samples complicates the problem of estimating the parameters of the underlying positive random variable and the probability of a zero observation. Using the method of maximum likelihood, it is shown that the solution to this estimation problem reduces largely to that of estimating the parameters of the distribution truncated at the point of censorship. The maximum likelihood estimate of the proportion of zero values follows directly. The derivation of the maximum likelihood estimates for a lognormal population with zeros is given in detail, and the asymptotic properties of the estimates are examined. The estimation method was used to fit several different distributions to a set of severely censored /sup 85/Kr monitoring data from six locations at the Savannah River Plant chemical separations facilities.
The Impact of Perceived Frailty on Surgeons’ Estimates of Surgical Risk
Ferguson, Mark K.; Farnan, Jeanne; Hemmerich, Josh A.; Slawinski, Kris; Acevedo, Julissa; Small, Stephen
2015-01-01
Background Physicians are only moderately accurate in estimating surgical risk based on clinical vignettes. We assessed the impact of perceived frailty by measuring the influence of a short video of a standardized patient on surgical risk estimates. Methods Thoracic surgeons and cardiothoracic trainees estimated the risk of major complications for lobectomy based on clinical vignettes of varied risk categories (low, average, high). After each vignette, subjects viewed a randomly selected video of a standardized patient exhibiting either vigorous or frail behavior, then re-estimated risk. Subjects were asked to rate 5 vignettes paired with 5 different standardized patients. Results Seventy-one physicians participated. Initial risk estimates varied according to the vignette risk category: low, 15.2 ± 11.2% risk; average, 23.7 ± 16.1%; high, 37.3 ± 18.9%; p<0.001 by ANOVA. Concordant information in vignettes and videos moderately altered estimates (high risk vignette, frail video: 10.6 ± 27.5% increase in estimate, p=0.006; low risk vignette, vigorous video: 14.5 ± 45.0% decrease, p=0.009). Discordant findings influenced risk estimates more substantially (high risk vignette, vigorous video: 21.2 ± 23.5% decrease in second risk estimate, p<0.001; low risk vignette, frail video: 151.9 ± 209.8% increase, p<0.001). Conclusions Surgeons differentiated relative risk of lobectomy based on clinical vignettes. The effect of viewing videos was small when vignettes and videos were concordant; the effect was more substantial when vignettes and videos were discordant. The information will be helpful in training future surgeons in frailty recognition and risk estimation. PMID:24932570
RADON EXPOSURE ASSESSMENT AND DOSIMETRY APPLIED TO EPIDEMIOLOGY AND RISK ESTIMATION
Epidemiological studies of underground miners provide the primary basis for radon risk estimates for indoor exposures as well as mine exposures. A major source of uncertainty in these risk estimates is the uncertainty in radon progeny exposure estimates for the miners. In addit...
Inokuchi, Shota; Kitayama, Tetsushi; Fujii, Koji; Nakahara, Hiroaki; Nakanishi, Hiroaki; Saito, Kazuyuki; Mizuno, Natsuko; Sekiguchi, Kazumasa
2016-03-01
Phenomena called allele dropouts are often observed in crime stain profiles. Allele dropouts are generated because one of a pair of heterozygous alleles is underrepresented by stochastic influences and is indicated by a low peak detection threshold. Therefore, it is important that such risks are statistically evaluated. In recent years, attempts to interpret allele dropout probabilities by logistic regression using the information on peak heights have been reported. However, these previous studies are limited to the use of a human identification kit and fragment analyzer. In the present study, we calculated allele dropout probabilities by logistic regression using contemporary capillary electrophoresis instruments, 3500xL Genetic Analyzer and 3130xl Genetic Analyzer with various commercially available human identification kits such as AmpFℓSTR® Identifiler® Plus PCR Amplification Kit. Furthermore, the differences in logistic curves between peak detection thresholds using analytical threshold (AT) and values recommended by the manufacturer were compared. The standard logistic curves for calculating allele dropout probabilities from the peak height of sister alleles were characterized. The present study confirmed that ATs were lower than the values recommended by the manufacturer in human identification kits; therefore, it is possible to reduce allele dropout probabilities and obtain more information using AT as the peak detection threshold.
NASA Astrophysics Data System (ADS)
Augustin, C. M.
2015-12-01
Carbon capture and storage (CCS) has been suggested by the Intergovernmental Panel on Climate Change as a partial solution to the greenhouse gas emissions problem. As CCS has become mainstream, researchers have raised multiple risk assessment issues typical of emerging technologies. In our research, we examine issues occuring when stored carbon dioxide (CO2) migrates to the near-surface or surface. We believe that both the public misperception and the physical reality of potential environmental, health, and commercial impacts of leak events from such subsurface sites have prevented widespread adoption of CCS. This paper is presented in three parts; the first is an evaluation of the systemic risk of a CCS site CO2 leak and models indicating potential likelihood of a leakage event. As the likelihood of a CCS site leak is stochastic and nonlinear, we present several Bayesian simulations for leak events based on research done with other low-probability, high-consequence gaseous pollutant releases. Though we found a large, acute leak to be exceptionally rare, we demonstrate potential for a localized, chronic leak at a CCS site. To that end, we present the second piece of this paper. Using a combination of spatio-temporal models and reaction-path models, we demonstrate the interplay between leak migrations, material interactions, and atmospheric dispersion for leaks of various duration and volume. These leak-event scenarios have implications for human, environmental, and economic health; they also have a significant impact on implementation support. Public acceptance of CCS is essential for a national low-carbon future, and this is what we address in the final part of this paper. We demonstrate that CCS remains unknown to the general public in the United States. Despite its unknown state, we provide survey findings -analyzed in Slovic and Weber's 2002 framework - that show a high unknown, high dread risk perception of leaks from a CCS site. Secondary findings are a
NASA Astrophysics Data System (ADS)
Anagnostou, E. N.; Seyyedi, H.; Beighley, E., II; McCollum, J.
2014-12-01
Carbon capture and storage (CCS) has been suggested by the Intergovernmental Panel on Climate Change as a partial solution to the greenhouse gas emissions problem. As CCS has become mainstream, researchers have raised multiple risk assessment issues typical of emerging technologies. In our research, we examine issues occuring when stored carbon dioxide (CO2) migrates to the near-surface or surface. We believe that both the public misperception and the physical reality of potential environmental, health, and commercial impacts of leak events from such subsurface sites have prevented widespread adoption of CCS. This paper is presented in three parts; the first is an evaluation of the systemic risk of a CCS site CO2 leak and models indicating potential likelihood of a leakage event. As the likelihood of a CCS site leak is stochastic and nonlinear, we present several Bayesian simulations for leak events based on research done with other low-probability, high-consequence gaseous pollutant releases. Though we found a large, acute leak to be exceptionally rare, we demonstrate potential for a localized, chronic leak at a CCS site. To that end, we present the second piece of this paper. Using a combination of spatio-temporal models and reaction-path models, we demonstrate the interplay between leak migrations, material interactions, and atmospheric dispersion for leaks of various duration and volume. These leak-event scenarios have implications for human, environmental, and economic health; they also have a significant impact on implementation support. Public acceptance of CCS is essential for a national low-carbon future, and this is what we address in the final part of this paper. We demonstrate that CCS remains unknown to the general public in the United States. Despite its unknown state, we provide survey findings -analyzed in Slovic and Weber's 2002 framework - that show a high unknown, high dread risk perception of leaks from a CCS site. Secondary findings are a
NASA Astrophysics Data System (ADS)
Kuznetsov, N. V.; Popov, V. D.; Khamidullina, N. M.
2005-05-01
When designing the radio-electronic equipment for long-term operation in a space environment, one of the most important problems is a correct estimation of radiation stability of its electric and radio components (ERC) against radiation-stimulated doze failures and one-particle effects (upsets). These problems are solved in this paper for the integrated microcircuits (IMC) of various types that are to be installed onboard the Fobos-Grunt spacecraft designed at the Federal State Unitary Enterprise “Lavochkin Research and Production Association.” The launching of this spacecraft is planned for 2009.
Rood, A S; McGavran, P D; Aanenson, J W; Till, J E
2001-08-01
Carbon tetrachloride is a degreasing agent that was used at the Rocky Flats Plant (RFP) in Colorado to clean product components and equipment. The chemical is considered a volatile organic compound and a probable human carcinogen. During the time the plant operated (1953-1989), most of the carbon tetrachloride was released to the atmosphere through building exhaust ducts. A smaller amount was released to the air via evaporation from open-air burn pits and ground-surface discharge points. Airborne releases from the plant were conservatively estimated to be equivalent to the amount of carbon tetrachloride consumed annually by the plant, which was estimated to be between 3.6 and 180 Mg per year. This assumption was supported by calculations that showed that most of the carbon tetrachloride discharged to the ground surface would subsequently be released to the atmosphere. Atmospheric transport of carbon tetrachloride from the plant to the surrounding community was estimated using a Gaussian Puff dispersion model (RATCHET). Time-integrated concentrations were estimated for nine hypothetical but realistic exposure scenarios that considered variation in lifestyle, location, age, and gender. Uncertainty distributions were developed for cancer slope factors and atmospheric dispersion factors. These uncertainties were propagated through to the final risk estimate using Monte Carlo techniques. The geometric mean risk estimates varied from 5.2 x 10(-6) for a hypothetical rancher or laborer working near the RFP to 3.4 x 10(-9) for an infant scenario. The distribution of incremental lifetime cancer incidence risk for the hypothetical rancher was between 1.3 x 10(-6) (5% value) and 2.1 x 10(-5) (95% value). These estimates are similar to or exceed estimated cancer risks posed by releases of radionuclides from the site. PMID:11726020
NASA Astrophysics Data System (ADS)
Lolli, B.; Gasperini, P.
We analyzed the available instrumental catalogs of Italian earthquakes from 1960 to 1996 to compute the parameters of the time-magnitude distribution model proposed by Reasenberg e Jones (1989, 1994) and currently used to make aftershock predictions in California. We found that empirical corrections ranging from 0.3 (before 1976) to 0.5 magnitude units (between 1976 and 1980) are necessary to make the dataset ho- mogeneous over the entire period. The estimated model parameters result quite stable with respect to mainshock magnitude and sequence detection algorithm, while their spatial variations suggest that regional estimates might predict the behavior of future sequences better than ones computed by the whole Italian dataset. In order to improve the goodness of fit for sequences including multiple mainshocks (like the one occurred in Central Italy from September 1997 to May 1998) we developed a quasi epidemic model (QETAS) consisting of the superposition of a small number of Omori's pro- cesses originated by strong aftershocks. We found that the inclusion in the QETAS model of the shocks with magnitude larger than mainshock magnitude minus one (that are usually located and sized in near real-time by the observatories) improves significantly the ability of the algorithm to predict the sequence behaviors.
This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.
The role of models in estimating consequences as part of the risk assessment process.
Forde-Folle, K; Mitchell, D; Zepeda, C
2011-08-01
The degree of disease risk represented by the introduction, spread, or establishment of one or several diseases through the importation of animals and animal products is assessed by importing countries through an analysis of risk. The components of a risk analysis include hazard identification, risk assessment, risk management, and risk communication. A risk assessment starts with identification of the hazard(s) and then continues with four interrelated steps: release assessment, exposure assessment, consequence assessment, and risk estimation. Risk assessments may be either qualitative or quantitative. This paper describes how, through the integration of epidemiological and economic models, the potential adverse biological and economic consequences of exposure can be quantified.
State Estimates of Adolescent Cigarette Use and Perceptions of Risk of Smoking: 2012 and 2013
... 2015 STATE ESTIMATES OF ADOLESCENT CIGARETTE USE AND PERCEPTIONS OF RISK OF SMOKING: 2012 AND 2013 AUTHORS ... with an inverse association between use and risk perceptions (i.e., the prevalence of use is lower ...
Abrunhosa, Luís; Morales, Héctor; Soares, Célia; Calado, Thalita; Vila-Chã, Ana Sofia; Pereira, Martinha; Venâncio, Armando
2016-01-01
Mycotoxins are toxic secondary metabolites produced by filamentous fungi that occur naturally in agricultural commodities worldwide. Aflatoxins, ochratoxin A, patulin, fumonisins, zearalenone, trichothecenes, and ergot alkaloids are presently the most important for food and feed safety. These compounds are produced by several species that belong to the Aspergillus, Penicillium, Fusarium, and Claviceps genera and can be carcinogenic, mutagenic, teratogenic, cytotoxic, neurotoxic, nephrotoxic, estrogenic, and immunosuppressant. Human and animal exposure to mycotoxins is generally assessed by taking into account data on the occurrence of mycotoxins in food and feed as well as data on the consumption patterns of the concerned population. This evaluation is crucial to support measures to reduce consumer exposure to mycotoxins. This work reviews the occurrence and levels of mycotoxins in Portuguese food and feed to provide a global overview of this issue in Portugal. With the information collected, the exposure of the Portuguese population to those mycotoxins is assessed, and the estimated dietary intakes are presented.
Time-dependent landslide probability mapping
Campbell, Russell H.; Bernknopf, Richard L.; ,
1993-01-01
Case studies where time of failure is known for rainfall-triggered debris flows can be used to estimate the parameters of a hazard model in which the probability of failure is a function of time. As an example, a time-dependent function for the conditional probability of a soil slip is estimated from independent variables representing hillside morphology, approximations of material properties, and the duration and rate of rainfall. If probabilities are calculated in a GIS (geomorphic information system ) environment, the spatial distribution of the result for any given hour can be displayed on a map. Although the probability levels in this example are uncalibrated, the method offers a potential for evaluating different physical models and different earth-science variables by comparing the map distribution of predicted probabilities with inventory maps for different areas and different storms. If linked with spatial and temporal socio-economic variables, this method could be used for short-term risk assessment.
Cancer risk estimation caused by radiation exposure during endovascular procedure
NASA Astrophysics Data System (ADS)
Kang, Y. H.; Cho, J. H.; Yun, W. S.; Park, K. H.; Kim, H. G.; Kwon, S. M.
2014-05-01
The objective of this study was to identify the radiation exposure dose of patients, as well as staff caused by fluoroscopy for C-arm-assisted vascular surgical operation and to estimate carcinogenic risk due to such exposure dose. The study was conducted in 71 patients (53 men and 18 women) who had undergone vascular surgical intervention at the division of vascular surgery in the University Hospital from November of 2011 to April of 2012. It had used a mobile C-arm device and calculated the radiation exposure dose of patient (dose-area product, DAP). Effective dose was measured by attaching optically stimulated luminescence on the radiation protectors of staff who participates in the surgery to measure the radiation exposure dose of staff during the vascular surgical operation. From the study results, DAP value of patients was 308.7 Gy cm2 in average, and the maximum value was 3085 Gy cm2. When converted to the effective dose, the resulted mean was 6.2 m Gy and the maximum effective dose was 61.7 milliSievert (mSv). The effective dose of staff was 3.85 mSv; while the radiation technician was 1.04 mSv, the nurse was 1.31 mSv. All cancer incidences of operator are corresponding to 2355 persons per 100,000 persons, which deemed 1 of 42 persons is likely to have all cancer incidences. In conclusion, the vascular surgeons should keep the radiation protection for patient, staff, and all participants in the intervention in mind as supervisor of fluoroscopy while trying to understand the effects by radiation by themselves to prevent invisible danger during the intervention and to minimize the harm.
ESTIMATED SIL LEVELS AND RISK COMPARISONS FOR RELIEF VALVES AS A FUNCTION OF TIME-IN-SERVICE
Harris, S.
2012-03-26
Risk-based inspection methods enable estimation of the probability of spring-operated relief valves failing on demand at the United States Department of Energy's Savannah River Site (SRS) in Aiken, South Carolina. The paper illustrates an approach based on application of the Frechet and Weibull distributions to SRS and Center for Chemical Process Safety (CCPS) Process Equipment Reliability Database (PERD) proof test results. The methodology enables the estimation of ANSI/ISA-84.00.01 Safety Integrity Levels (SILs) as well as the potential change in SIL level due to modification of the maintenance schedule. Current SRS practices are reviewed and recommendations are made for extending inspection intervals. The paper compares risk-based inspection with specific SILs as maintenance intervals are adjusted. Groups of valves are identified in which maintenance times can be extended as well as different groups in which an increased safety margin may be needed.
ERIC Educational Resources Information Center
Neel, John H.
Induced probabilities have been largely ignored by educational researchers. Simply stated, if a new or random variable is defined in terms of a first random variable, then induced probability is the probability or density of the new random variable that can be found by summation or integration over the appropriate domains of the original random…
Estimation of Wild Fire Risk Area based on Climate and Maximum Entropy in Korean Peninsular
NASA Astrophysics Data System (ADS)
Kim, T.; Lim, C. H.; Song, C.; Lee, W. K.
2015-12-01
The number of forest fires and accompanying human injuries and physical damages has been increased by frequent drought. In this study, forest fire danger zone of Korea is estimated to predict and prepare for future forest fire hazard regions. The MaxEnt (Maximum Entropy) model is used to estimate the forest fire hazard region which estimates the probability distribution of the status. The MaxEnt model is primarily for the analysis of species distribution, but its applicability for various natural disasters is getting recognition. The detailed forest fire occurrence data collected by the MODIS for past 5 years (2010-2014) is used as occurrence data for the model. Also meteorology, topography, vegetation data are used as environmental variable. In particular, various meteorological variables are used to check impact of climate such as annual average temperature, annual precipitation, precipitation of dry season, annual effective humidity, effective humidity of dry season, aridity index. Consequently, the result was valid based on the AUC(Area Under the Curve) value (= 0.805) which is used to predict accuracy in the MaxEnt model. Also predicted forest fire locations were practically corresponded with the actual forest fire distribution map. Meteorological variables such as effective humidity showed the greatest contribution, and topography variables such as TWI (Topographic Wetness Index) and slope also contributed on the forest fire. As a result, the east coast and the south part of Korea peninsula were predicted to have high risk on the forest fire. In contrast, high-altitude mountain area and the west coast appeared to be safe with the forest fire. The result of this study is similar with former studies, which indicates high risks of forest fire in accessible area and reflects climatic characteristics of east and south part in dry season. To sum up, we estimated the forest fire hazard zone with existing forest fire locations and environment variables and had
NASA Astrophysics Data System (ADS)
Abdrakhimov, A. M.; Basilevsky, A. T.; Ivanov, M. A.; Kokhanov, A. A.; Karachevtseva, I. P.; Head, J. W.
2015-09-01
The paper describes the method of estimating the distribution of slopes by the portion of shaded areas measured in the images acquired at different Sun elevations. The measurements were performed for the benefit of the Luna-Glob Russian mission. The western ellipse for the spacecraft landing in the crater Bogus-lawsky in the southern polar region of the Moon was investigated. The percentage of the shaded area was measured in the images acquired with the LROC NAC camera with a resolution of ~0.5 m. Due to the close vicinity of the pole, it is difficult to build digital terrain models (DTMs) for this region from the LROC NAC images. Because of this, the method described has been suggested. For the landing ellipse investigated, 52 LROC NAC images obtained at the Sun elevation from 4° to 19° were used. In these images the shaded portions of the area were measured, and the values of these portions were transferred to the values of the occurrence of slopes (in this case, at the 3.5-m baseline) with the calibration by the surface characteristics of the Lunokhod-1 study area. For this area, the digital terrain model of the ~0.5-m resolution and 13 LROC NAC images obtained at different elevations of the Sun are available. From the results of measurements and the corresponding calibration, it was found that, in the studied landing ellipse, the occurrence of slopes gentler than 10° at the baseline of 3.5 m is 90%, while it is 9.6, 5.7, and 3.9% for the slopes steeper than 10°, 15°, and 20°, respectively. Obviously, this method can be recommended for application if there is no DTM of required granularity for the regions of interest, but there are high-resolution images taken at different elevations of the Sun.
El-Melegy, Moumen T
2013-07-01
This paper addresses the problem of fitting a functional model to data corrupted with outliers using a multilayered feed-forward neural network. Although it is of high importance in practical applications, this problem has not received careful attention from the neural network research community. One recent approach to solving this problem is to use a neural network training algorithm based on the random sample consensus (RANSAC) framework. This paper proposes a new algorithm that offers two enhancements over the original RANSAC algorithm. The first one improves the algorithm accuracy and robustness by employing an M-estimator cost function to decide on the best estimated model from the randomly selected samples. The other one improves the time performance of the algorithm by utilizing a statistical pretest based on Wald's sequential probability ratio test. The proposed algorithm is successfully evaluated on synthetic and real data, contaminated with varying degrees of outliers, and compared with existing neural network training algorithms.
Tojinbara, Kageaki; Sugiura, K; Yamada, A; Kakitani, I; Kwan, N C L; Sugiura, K
2016-01-01
Data of 98 rabies cases in dogs and cats from the 1948-1954 rabies epidemic in Tokyo were used to estimate the probability distribution of the incubation period. Lognormal, gamma and Weibull distributions were used to model the incubation period. The maximum likelihood estimates of the mean incubation period ranged from 27.30 to 28.56 days according to different distributions. The mean incubation period was shortest with the lognormal distribution (27.30 days), and longest with the Weibull distribution (28.56 days). The best distribution in terms of AIC value was the lognormal distribution with mean value of 27.30 (95% CI: 23.46-31.55) days and standard deviation of 20.20 (15.27-26.31) days. There were no significant differences between the incubation periods for dogs and cats, or between those for male and female dogs.
... 2014 estimates to 2012–2013 estimates). However, youth perceptions of great risk of harm from monthly marijuana ... change. State Estimates of Adolescent Marijuana Use and Perceptions of Risk of Harm From Marijuana Use: 2013 ...
Indoor radon and lung cancer. Estimating the risks
Samet, J.M. )
1992-01-01
Radon is ubiquitous in indoor environments. Epidemiologic studies of underground miners with exposure to radon and experimental evidence have established that radon causes lung cancer. The finding that this naturally occurring carcinogen is present in the air of homes and other buildings has raised concern about the lung cancer risk to the general population from radon. I review current approaches for assessing the risk of indoor radon, emphasizing the extrapolation of the risks for miners to the general population. Although uncertainties are inherent in this risk assessment, the present evidence warrants identifying homes that have unacceptably high concentrations.23 references.
Indoor radon and lung cancer. Estimating the risks.
Samet, J. M.
1992-01-01
Radon is ubiquitous in indoor environments. Epidemiologic studies of underground miners with exposure to radon and experimental evidence have established that radon causes lung cancer. The finding that this naturally occurring carcinogen is present in the air of homes and other buildings has raised concern about the lung cancer risk to the general population from radon. I review current approaches for assessing the risk of indoor radon, emphasizing the extrapolation of the risks for miners to the general population. Although uncertainties are inherent in this risk assessment, the present evidence warrants identifying homes that have unacceptably high concentrations. PMID:1734594
Elmore, Stacey A; Huyvaert, Kathryn P; Bailey, Larissa L; Iqbal, Asma; Su, Chunlei; Dixon, Brent R; Alisauskas, Ray T; Gajadhar, Alvin A; Jenkins, Emily J
2016-08-01
Increasingly, birds are recognised as important hosts for the ubiquitous parasite Toxoplasma gondii, although little experimental evidence exists to determine which tissues should be tested to maximise the detection probability of T. gondii. Also, Arctic-nesting geese are suspected to be important sources of T. gondii in terrestrial Arctic ecosystems, but the parasite has not previously been reported in the tissues of these geese. Using a domestic goose model, we applied a multi-scale occupancy framework to demonstrate that the probability of detection of T. gondii was highest in the brain (0.689, 95% confidence interval=0.486, 0.839) and the heart (0.809, 95% confidence interval=0.693, 0.888). Inoculated geese had an estimated T. gondii infection probability of 0.849, (95% confidence interval=0.643, 0.946), highlighting uncertainty in the system, even under experimental conditions. Guided by these results, we tested the brains and hearts of wild Ross's Geese (Chen rossii, n=50) and Lesser Snow Geese (Chen caerulescens, n=50) from Karrak Lake, Nunavut, Canada. We detected 51 suspected positive tissue samples from 33 wild geese using real-time PCR with melt-curve analysis. The wild goose prevalence estimates generated by our multi-scale occupancy analysis were higher than the naïve estimates of prevalence, indicating that multiple PCR repetitions on the same organs and testing more than one organ could improve T. gondii detection. Genetic characterisation revealed Type III T. gondii alleles in six wild geese and Sarcocystis spp. in 25 samples. Our study demonstrates that Arctic nesting geese are capable of harbouring T. gondii in their tissues and could transport the parasite from their southern overwintering grounds into the Arctic region. We demonstrate how a multi-scale occupancy framework can be used in a domestic animal model to guide resource-limited sample collection and tissue analysis in wildlife. Secondly, we confirm the value of traditional occupancy in
Elmore, Stacey A; Huyvaert, Kathryn P; Bailey, Larissa L; Iqbal, Asma; Su, Chunlei; Dixon, Brent R; Alisauskas, Ray T; Gajadhar, Alvin A; Jenkins, Emily J
2016-08-01
Increasingly, birds are recognised as important hosts for the ubiquitous parasite Toxoplasma gondii, although little experimental evidence exists to determine which tissues should be tested to maximise the detection probability of T. gondii. Also, Arctic-nesting geese are suspected to be important sources of T. gondii in terrestrial Arctic ecosystems, but the parasite has not previously been reported in the tissues of these geese. Using a domestic goose model, we applied a multi-scale occupancy framework to demonstrate that the probability of detection of T. gondii was highest in the brain (0.689, 95% confidence interval=0.486, 0.839) and the heart (0.809, 95% confidence interval=0.693, 0.888). Inoculated geese had an estimated T. gondii infection probability of 0.849, (95% confidence interval=0.643, 0.946), highlighting uncertainty in the system, even under experimental conditions. Guided by these results, we tested the brains and hearts of wild Ross's Geese (Chen rossii, n=50) and Lesser Snow Geese (Chen caerulescens, n=50) from Karrak Lake, Nunavut, Canada. We detected 51 suspected positive tissue samples from 33 wild geese using real-time PCR with melt-curve analysis. The wild goose prevalence estimates generated by our multi-scale occupancy analysis were higher than the naïve estimates of prevalence, indicating that multiple PCR repetitions on the same organs and testing more than one organ could improve T. gondii detection. Genetic characterisation revealed Type III T. gondii alleles in six wild geese and Sarcocystis spp. in 25 samples. Our study demonstrates that Arctic nesting geese are capable of harbouring T. gondii in their tissues and could transport the parasite from their southern overwintering grounds into the Arctic region. We demonstrate how a multi-scale occupancy framework can be used in a domestic animal model to guide resource-limited sample collection and tissue analysis in wildlife. Secondly, we confirm the value of traditional occupancy in
Jang, Cheng-Shin
2016-01-01
The Tamsui River watershed situated in Northern Taiwan provides a variety of water recreational opportunities such as riverbank park activities, fishing, cruising, rowing, sailing, and swimming. However, river water quality strongly affects water recreational quality. Moreover, the health of recreationists who are partially or fully exposed to polluted river water may be jeopardized. A river pollution index (RPI) composed of dissolved oxygen, biochemical oxygen demand, suspended solids, and ammonia nitrogen is typically used to gauge the river water quality and regulate the water body use in Taiwan. The purpose of this study was to probabilistically determine the RPI categories in the Tamsui River watershed and to assess the urban water recreational quality on the basis of the estimated RPI categories. First, according to various RPI categories, one-dimensional indicator kriging (IK) was adopted to estimate the occurrence probabilities of the RPI categories. The maximum occurrence probability among the categories was then employed to determine the most suitable RPI category. Finally, the most serious categories and seasonal variations of RPI were adopted to evaluate the quality of current water recreational opportunities in the Tamsui River watershed. The results revealed that the midstream and downstream sections of the Tamsui River and its tributaries with poor river water quality afford low water recreational quality, and water recreationists should avoid full or limited exposure to these bodies of water. However, the upstream sections of the Tamsui River watershed with high river water quality are suitable for all water recreational activities.
Holbrook, Christopher M.; Johnson, Nicholas S.; Steibel, Juan P.; Twohey, Michael B.; Binder, Thomas R.; Krueger, Charles C.; Jones, Michael L.
2014-01-01
Improved methods are needed to evaluate barriers and traps for control and assessment of invasive sea lamprey (Petromyzon marinus) in the Great Lakes. A Bayesian state-space model provided reach-specific probabilities of movement, including trap capture and dam passage, for 148 acoustic tagged invasive sea lamprey in the lower Cheboygan River, Michigan, a tributary to Lake Huron. Reach-specific movement probabilities were combined to obtain estimates of spatial distribution and abundance needed to evaluate a barrier and trap complex for sea lamprey control and assessment. Of an estimated 21 828 – 29 300 adult sea lampreys in the river, 0%–2%, or 0–514 untagged lampreys, could have passed upstream of the dam, and 46%–61% were caught in the trap. Although no tagged lampreys passed above the dam (0/148), our sample size was not sufficient to consider the lock and dam a complete barrier to sea lamprey. Results also showed that existing traps are in good locations because 83%–96% of the population was vulnerable to existing traps. However, only 52%–69% of lampreys vulnerable to traps were caught, suggesting that traps can be improved. The approach used in this study was a novel use of Bayesian state-space models that may have broader applications, including evaluation of barriers for other invasive species (e.g., Asian carp (Hypophthalmichthys spp.)) and fish passage structures for other diadromous fishes.
Jang, Cheng-Shin
2016-01-01
The Tamsui River watershed situated in Northern Taiwan provides a variety of water recreational opportunities such as riverbank park activities, fishing, cruising, rowing, sailing, and swimming. However, river water quality strongly affects water recreational quality. Moreover, the health of recreationists who are partially or fully exposed to polluted river water may be jeopardized. A river pollution index (RPI) composed of dissolved oxygen, biochemical oxygen demand, suspended solids, and ammonia nitrogen is typically used to gauge the river water quality and regulate the water body use in Taiwan. The purpose of this study was to probabilistically determine the RPI categories in the Tamsui River watershed and to assess the urban water recreational quality on the basis of the estimated RPI categories. First, according to various RPI categories, one-dimensional indicator kriging (IK) was adopted to estimate the occurrence probabilities of the RPI categories. The maximum occurrence probability among the categories was then employed to determine the most suitable RPI category. Finally, the most serious categories and seasonal variations of RPI were adopted to evaluate the quality of current water recreational opportunities in the Tamsui River watershed. The results revealed that the midstream and downstream sections of the Tamsui River and its tributaries with poor river water quality afford low water recreational quality, and water recreationists should avoid full or limited exposure to these bodies of water. However, the upstream sections of the Tamsui River watershed with high river water quality are suitable for all water recreational activities. PMID:26676412
NASA Astrophysics Data System (ADS)
Popov, V. D.; Khamidullina, N. M.
2006-10-01
In developing radio-electronic devices (RED) of spacecraft operating in the fields of ionizing radiation in space, one of the most important problems is the correct estimation of their radiation tolerance. The “weakest link” in the element base of onboard microelectronic devices under radiation effect is the integrated microcircuits (IMC), especially of large scale (LSI) and very large scale (VLSI) degree of integration. The main characteristic of IMC, which is taken into account when making decisions on using some particular type of IMC in the onboard RED, is the probability of non-failure operation (NFO) at the end of the spacecraft’s lifetime. It should be noted that, until now, the NFO has been calculated only from the reliability characteristics, disregarding the radiation effect. This paper presents the so-called “reliability” approach to determination of radiation tolerance of IMC, which allows one to estimate the probability of non-failure operation of various types of IMC with due account of radiation-stimulated dose failures. The described technique is applied to RED onboard the Spektr-R spacecraft to be launched in 2007.
NASA Astrophysics Data System (ADS)
Berlanga, Juan M.; Harbaugh, John W.
the basis of frequency distributions of trend-surface residuals obtained by fitting and subtracting polynomial trend surfaces from the machine-contoured reflection time maps. We found that there is a strong preferential relationship between the occurrence of petroleum (i.e. its presence versus absence) and particular ranges of trend-surface residual values. An estimate of the probability of oil occurring at any particular geographic point can be calculated on the basis of the estimated trend-surface residual value. This estimate, however, must be tempered by the probable error in the estimate of the residual value provided by the error function. The result, we believe, is a simple but effective procedure for estimating exploration outcome probabilities where seismic data provide the principal form of information in advance of drilling. Implicit in this approach is the comparison between a maturely explored area, for which both seismic and production data are available, and which serves as a statistical "training area", with the "target" area which is undergoing exploration and for which probability forecasts are to be calculated.
CCSI Risk Estimation: An Application of Expert Elicitation
Engel, David W.; Dalton, Angela C.
2012-10-01
The Carbon Capture Simulation Initiative (CCSI) is a multi-laboratory simulation-driven effort to develop carbon capture technologies with the goal of accelerating commercialization and adoption in the near future. One of the key CCSI technical challenges is representing and quantifying the inherent uncertainty and risks associated with developing, testing, and deploying the technology in simulated and real operational settings. To address this challenge, the CCSI Element 7 team developed a holistic risk analysis and decision-making framework. The purpose of this report is to document the CCSI Element 7 structured systematic expert elicitation to identify additional risk factors. We review the significance of and established approaches to expert elicitation, describe the CCSI risk elicitation plan and implementation strategies, and conclude by discussing the next steps and highlighting the contribution of risk elicitation toward the achievement of the overarching CCSI objectives.
Do We Know Whether Researchers and Reviewers are Estimating Risk and Benefit Accurately?
Hey, Spencer Phillips; Kimmelman, Jonathan
2016-10-01
Accurate estimation of risk and benefit is integral to good clinical research planning, ethical review, and study implementation. Some commentators have argued that various actors in clinical research systems are prone to biased or arbitrary risk/benefit estimation. In this commentary, we suggest the evidence supporting such claims is very limited. Most prior work has imputed risk/benefit beliefs based on past behavior or goals, rather than directly measuring them. We describe an approach - forecast analysis - that would enable direct and effective measure of the quality of risk/benefit estimation. We then consider some objections and limitations to the forecasting approach. PMID:27197044
Do We Know Whether Researchers and Reviewers are Estimating Risk and Benefit Accurately?
Hey, Spencer Phillips; Kimmelman, Jonathan
2016-10-01
Accurate estimation of risk and benefit is integral to good clinical research planning, ethical review, and study implementation. Some commentators have argued that various actors in clinical research systems are prone to biased or arbitrary risk/benefit estimation. In this commentary, we suggest the evidence supporting such claims is very limited. Most prior work has imputed risk/benefit beliefs based on past behavior or goals, rather than directly measuring them. We describe an approach - forecast analysis - that would enable direct and effective measure of the quality of risk/benefit estimation. We then consider some objections and limitations to the forecasting approach.
Feig, S.A.; Ehrlich, S.M. )
1990-03-01
On the basis of recent epidemiologic studies, the National Institutes of Health in 1985 provided a new estimate for radiation risk to the breast that employed a relative risk model and acknowledged greater dependence on age at exposure. Lifetime risks from a single mammogram may be calculated from this estimate and are lower than those based on the previous 1977 National Cancer Institute estimate. Possible years of life expectancy lost from annual mammography beginning at age 40 years may also be calculated and are negligible compared with estimates for years of life expectancy gained from such screening.
NEED FOR INDIVIDUAL CANCER RISK ESTIMATES IN X-RAY AND NUCLEAR MEDICINE IMAGING.
Mattsson, Sören
2016-06-01
To facilitate the justification of an X-ray or nuclear medicine investigation and for informing patients, it is desirable that the individual patient's radiation dose and potential cancer risk can be prospectively assessed and documented. The current dose-reporting is based on effective dose, which ignores body size and does not reflect the strong dependence of risk on the age at exposure. Risk estimations should better be done through individual organ dose assessments, which need careful exposure characterisation as well as anatomical description of the individual patient. In nuclear medicine, reference biokinetic models should also be replaced with models describing individual physiological states and biokinetics. There is a need to adjust population-based cancer risk estimates to the possible risk of leukaemia and solid tumours for the individual depending on age and gender. The article summarises reasons for individual cancer risk estimates and gives examples of methods and results of such estimates. PMID:26994092
Cui, Fangfang; Zhang, Lan; Yu, Chuanhua; Hu, Songbo; Zhang, Yunquan
2016-01-01
In order to estimate the health losses caused by common risk factors in the Hubei province, China, we calculated the deaths and disability-adjusted life years (DALYs) attributable to 11 risk factors. We estimated the exposure distributions of risk factors in Hubei Province in 2013 from the monitoring system on chronic disease and related risk factors, combined with relative risk (RR) in order to calculate the population attributable fraction. Deaths and DALYs attributed to the selected risk factors were then estimated together with cause-specific deaths and DALYs. In total, 53.39% of the total deaths and 36.23% of the total DALYs in Hubei were a result of the 11 selected risk factors. The top five risk factors were high blood pressure, smoking, high body mass index, diet low in fruits and alcohol use, accounting for 14.68%, 12.57%, 6.03%, 3.90% and 3.19% of total deaths, respectively, and 9.41%, 7.22%, 4.42%, 2.51% and 2.44% of total DALYs, respectively. These risk factors, especially high blood pressure, smoking and high body mass index, significantly influenced quality of life, causing a large number of deaths and DALYs. The burden of chronic disease could be substantially reduced if these risk factors were effectively controlled, which would allow people to enjoy healthier lives. PMID:27669279
Cui, Fangfang; Zhang, Lan; Yu, Chuanhua; Hu, Songbo; Zhang, Yunquan
2016-01-01
In order to estimate the health losses caused by common risk factors in the Hubei province, China, we calculated the deaths and disability-adjusted life years (DALYs) attributable to 11 risk factors. We estimated the exposure distributions of risk factors in Hubei Province in 2013 from the monitoring system on chronic disease and related risk factors, combined with relative risk (RR) in order to calculate the population attributable fraction. Deaths and DALYs attributed to the selected risk factors were then estimated together with cause-specific deaths and DALYs. In total, 53.39% of the total deaths and 36.23% of the total DALYs in Hubei were a result of the 11 selected risk factors. The top five risk factors were high blood pressure, smoking, high body mass index, diet low in fruits and alcohol use, accounting for 14.68%, 12.57%, 6.03%, 3.90% and 3.19% of total deaths, respectively, and 9.41%, 7.22%, 4.42%, 2.51% and 2.44% of total DALYs, respectively. These risk factors, especially high blood pressure, smoking and high body mass index, significantly influenced quality of life, causing a large number of deaths and DALYs. The burden of chronic disease could be substantially reduced if these risk factors were effectively controlled, which would allow people to enjoy healthier lives. PMID:27669279
Olson, Scott A.; with a section by Veilleux, Andrea G.
2014-01-01
This report provides estimates of flood discharges at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont. The equations were developed using generalized least-squares regression. Flood-frequency and drainage-basin characteristics from 145 streamgages were used in developing the equations. The drainage-basin characteristics used as explanatory variables in the regression equations include drainage area, percentage of wetland area, and the basin-wide mean of the average annual precipitation. The average standard errors of prediction for estimating the flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 36.0, 38.7, 42.4, 44.9, 47.3, 50.7, and 55.1 percent, respectively. Flood discharges at selected AEPs for streamgages were computed by using the Expected Moments Algorithm. To improve estimates of the flood discharges for given exceedance probabilities at streamgages in Vermont, a new generalized skew coefficient was developed. The new generalized skew for the region is a constant, 0.44. The mean square error of the generalized skew coefficient is 0.078. This report describes a technique for using results from the regression equations to adjust an AEP discharge computed from a streamgage record. This report also describes a technique for using a drainage-area adjustment to estimate flood discharge at a selected AEP for an ungaged site upstream or downstream from a streamgage. The final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is a World Wide Web application providing automated regression-equation solutions for user-selected sites on streams.
The Impact of a Frailty Education Module on Surgical Resident Estimates of Lobectomy Risk
Ferguson, Mark K.; Thompson, Katherine; Huisingh-Scheetz, Megan; Farnan, Jeanne; Hemmerich, Joshua; Acevedo, Julissa; Small, Stephen
2015-01-01
Background Frailty is a risk factor for adverse events after surgery. Residents’ ability to recognize frailty is underdeveloped. We assessed the influence of a frailty education module on surgical residents’ estimates of lobectomy risk. Methods Traditional track cardiothoracic surgery residents were randomized to take an on-line short course on frailty (experimental group) or to receive no training (control group). Residents read a clinical vignette, made an initial risk estimate of major complications for lobectomy, and rated clinical factors on their importance to their estimates. They viewed a video of a standardized patient portraying the patient in the vignette, randomly selected to exhibit either vigorous or frail behavior, and provided a final risk estimate. After rating 5 vignettes, they completed a test on their frailty knowledge. Results Forty-one residents participated (20 in the experimental group). Initial risk estimates were similar between the groups. The experimental group rated clinical factors as “very important” in their initial risk estimates more often than did the control group (47.6% vs 38.5%; p<0.001). Viewing videos resulted in a significant change from initial to final risk estimates (frail: 50±75% increase, p=0.008; vigorous: 14±32% decrease, p=0.043). The magnitude of change in risk estimates was greater for the experimental group (10.0±8.1 vs 5.1±7.7; p<0.001). The experimental group answered more frailty test questions correctly (93.7% vs 75.2%; p<0.001). Conclusions A frailty education module improved resident knowledge of frailty and influenced surgical risk estimates. Training in frailty may help educate residents in frailty recognition and surgical risk assessment. PMID:26004924
NASA Astrophysics Data System (ADS)
Boiselet, Aurelien; Scotti, Oona; Lyon-Caen, Hélène
2014-05-01
-SISCOR Working Group. On the basis of this consensual logic tree, median probability of occurrences of M>=6 events were computed for the region of study. Time-dependent models (Brownian Passage time and Weibull probability distributions) were also explored. The probability of a M>=6.0 event is found to be greater in the western region compared to the eastern part of the Corinth rift, whether a fault-based or a classical seismotectonic approach is used. Percentile probability estimates are also provided to represent the range of uncertainties in the results. The percentile results show that, in general, probability estimates following the classical approach (based on the definition of seismotectonic source zones), cover the median values estimated following the fault-based approach. On the contrary, the fault-based approach in this region is still affected by a high degree of uncertainty, because of the poor constraints on the 3D geometries of the faults and the high uncertainties in their slip rates.
NASA Technical Reports Server (NTRS)
Cucinotta, Francis A.; Chappell, Lori J.; Wang, Minli; Kim, Myung-Hee
2011-01-01
The uncertainties in estimating the health risks from galactic cosmic rays (GCR) and solar particle events (SPE) are a major limitation to the length of space missions and the evaluation of potential risk mitigation approaches. NASA limits astronaut exposures to a 3% risk of exposure induced cancer death (REID), and protects against uncertainties in risks projections using an assessment of 95% confidence intervals after propagating the error from all model factors (environment and organ exposure, risk coefficients, dose-rate modifiers, and quality factors). Because there are potentially significant late mortality risks from diseases of the circulatory system and central nervous system (CNS) which are less well defined than cancer risks, the cancer REID limit is not necessarily conservative. In this report, we discuss estimates of lifetime risks from space radiation and new estimates of model uncertainties are described. The key updates to the NASA risk projection model are: 1) Revised values for low LET risk coefficients for tissue specific cancer incidence, with incidence rates transported to an average U.S. population to estimate the probability of Risk of Exposure Induced Cancer (REIC) and REID. 2) An analysis of smoking attributable cancer risks for never-smokers that shows significantly reduced lung cancer risk as well as overall cancer risks from radiation compared to risk estimated for the average U.S. population. 3) Derivation of track structure based quality functions depends on particle fluence, charge number, Z and kinetic energy, E. 4) The assignment of a smaller maximum in quality function for leukemia than for solid cancers. 5) The use of the ICRP tissue weights is shown to over-estimate cancer risks from SPEs by a factor of 2 or more. Summing cancer risks for each tissue is recommended as a more accurate approach to estimate SPE cancer risks. 6) Additional considerations on circulatory and CNS disease risks. Our analysis shows that an individual s
Biomechanical Risk Estimates for Mild Traumatic Brain Injury
Funk, J. R.; Duma, S. M.; Manoogian, S. J.; Rowson, S.
2007-01-01
The objective of this study was to characterize the risk of mild traumatic brain injury (MTBI) in living humans based on a large set of head impact data taken from American football players at the collegiate level. Real-time head accelerations were recorded from helmet-mounted accelerometers designed to stay in contact with the player’s head. Over 27,000 head impacts were recorded, including four impacts resulting in MTBI. Parametric risk curves were developed by normalizing MTBI incidence data by head impact exposure data. An important finding of this research is that living humans, at least in the setting of collegiate football, sustain much more significant head impacts without apparent injury than previously thought. The following preliminary nominal injury assessment reference values associated with a 10% risk of MTBI are proposed: a peak linear head acceleration of 165 g, a HIC of 400, and a peak angular head acceleration of 9000 rad/s2. PMID:18184501
NASA Technical Reports Server (NTRS)
Tretter, S. A.
1977-01-01
A report is given to supplement the progress report of June 17, 1977. In that progress report gamma, lognormal, and Rayleigh probability density functions were fitted to the times between lightning flashes in the storms of 9/12/75, 8/26/75, and 7/13/76 by the maximum likelihood method. The goodness of fit is checked by the Kolmogoroff-Smirnoff test. Plots of the estimated densities along with normalized histograms are included to provide a visual check on the goodness of fit. The lognormal densities are the most peaked and have the highest tails. This results in the best fit to the normalized histogram in most cases. The Rayleigh densities have too broad and rounded peaks to give good fits. In addition, they have the lowest tails. The gamma densities fall inbetween and give the best fit in a few cases.
Herek, Gregory M
2009-01-01
Using survey responses collected via the Internet from a U.S. national probability sample of gay, lesbian, and bisexual adults (N = 662), this article reports prevalence estimates of criminal victimization and related experiences based on the target's sexual orientation. Approximately 20% of respondents reported having experienced a person or property crime based on their sexual orientation; about half had experienced verbal harassment, and more than 1 in 10 reported having experienced employment or housing discrimination. Gay men were significantly more likely than lesbians or bisexuals to experience violence and property crimes. Employment and housing discrimination were significantly more likely among gay men and lesbians than among bisexual men and women. Implications for future research and policy are discussed.
NASA Technical Reports Server (NTRS)
Crosson, William L.; Duchon, Claude E.; Raghavan, Ravikumar; Goodman, Steven J.
1996-01-01
Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from flash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 30OR(sup 1.4) (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching method (PMM). Rainfall derived from the power law Z-R was found to he highly biased (+90%-l10%) compared to rain gauge measurements for various temporal and spatial integrations. Application of a 36.5-dBZ reflectivity threshold (determined via the PMM) was found to improve the performance of the power law Z-R, reducing the biases substantially to 20%-33%. Correlations between precipitation estimates obtained with either Z-R relationship and mean gauge values are much higher for areal averages than for point locations. Precipitation estimates from the PMM are an improvement over those obtained using the power law in that biases and root-mean-square errors are much lower. The minimum timescale for application of the PMM with the composite radar dataset was found to be several days for area-average precipitation. The minimum spatial scale is harder to quantify, although it is concluded that it is less than 350 sq km. Implications relevant to the WSR-88D system are
Frans, Lonna M.
2000-01-01
Logistic regression was used to relate anthropogenic (man-made) and natural factors to the occurrence of elevated concentrations of nitrite plus nitrate as nitrogen in ground water in the Columbia Basin Ground Water Management Area, eastern Washington. Variables that were analyzed included well depth, depth of well casing, ground-water recharge rates, presence of canals, fertilizer application amounts, soils, surficial geology, and land-use types. The variables that best explain the occurrence of nitrate concentrations above 3 milligrams per liter in wells were the amount of fertilizer applied annually within a 2-kilometer radius of a well and the depth of the well casing; the variables that best explain the occurrence of nitrate above 10 milligrams per liter included the amount of fertilizer applied annually within a 3-kilometer radius of a well, the depth of the well casing, and the mean soil hydrologic group, which is a measure of soil infiltration rate. Based on the relations between these variables and elevated nitrate concentrations, models were developed using logistic regression that predict the probability that ground water will exceed a nitrate concentration of either 3 milligrams per liter or 10 milligrams per liter. Maps were produced that illustrate the predicted probability that ground-water nitrate concentrations will exceed 3 milligrams per liter or 10 milligrams per liter for wells cased to 78 feet below land surface (median casing depth) and the predicted depth to which wells would need to be cased in order to have an 80-percent probability of drawing water with a nitrate concentration below either 3 milligrams per liter or 10 milligrams per liter. Maps showing the predicted probability for the occurrence of elevated nitrate concentrations indicate that the irrigated agricultural regions are most at risk. The predicted depths to which wells need to be cased in order to have an 80-percent chance of obtaining low nitrate ground water exceed 600 feet
Stevens, Michael R.; Bossong, Clifford R.; Litke, David W.; Viger, Roland J.; Rupert, Michael G.; Char, Stephen J.
2008-01-01
Debris flows pose substantial threats to life, property, infrastructure, and water resources. Post-wildfire debris flows may be of catastrophic proportions compared to debris flows occurring in unburned areas. During 2006, the U.S. Geological Survey (USGS), in cooperation with the Northern Colorado Water Conservancy District, initiated a pre-wildfire study to determine the potential for post-wildfire debris flows in the Three Lakes watershed, Grand County, Colorado. The objective was to estimate the probability of post-wildfire debris flows and to estimate the approximate volumes of debris flows from 109 subbasins in the Three Lakes watershed in order to provide the Northern Colorado Water Conservancy District with a relative measure of which subbasins might constitute the most serious debris flow hazards. This report describes the results of the study and provides estimated probabilities of debris-flow occurrence and the estimated volumes of debris flow that could be produced in 109 subbasins of the watershed under an assumed moderate- to high-burn severity of all forested areas. The estimates are needed because the Three Lakes watershed includes communities and substantial water-resources and water-supply infrastructure that are important to residents both east and west of the Continental Divide. Using information provided in this report, land and water-supply managers can consider where to concentrate pre-wildfire planning, pre-wildfire preparedness, and pre-wildfire mitigation in advance of wildfires. Also, in the event of a large wildfire, this information will help managers identify the watersheds with the greatest post-wildfire debris-flow hazards.
NASA Astrophysics Data System (ADS)
Ramos, M.; Ferrer, S.; Villaescusa, J. I.; Verdú, G.; Salas, M. D.; Cuevas, M. D.
2005-02-01
The authors report on a method to calculate radiological risks, applicable to breast screening programs and other controlled medical exposures to ionizing radiation. In particular, it has been applied to make a risk assessment in the Valencian Breast Cancer Early Detection Program (VBCEDP) in Spain. This method is based on a parametric approach, through Markov processes, of hazard functions for radio-induced breast cancer incidence and mortality, with mean glandular breast dose, attained age and age-at-exposure as covariates. Excess relative risk functions of breast cancer mortality have been obtained from two different case-control studies exposed to ionizing radiation, with different follow-up time: the Canadian Fluoroscopy Cohort Study (1950-1987) and the Life Span Study (1950-1985 and 1950-1990), whereas relative risk functions for incidence have been obtained from the Life Span Study (1958-1993), the Massachusetts tuberculosis cohorts (1926-1985 and 1970-1985), the New York post-partum mastitis patients (1930-1981) and the Swedish benign breast disease cohort (1958-1987). Relative risks from these cohorts have been transported to the target population undergoing screening in the Valencian Community, a region in Spain with about four and a half million inhabitants. The SCREENRISK software has been developed to estimate radiological detriments in breast screening. Some hypotheses corresponding to different screening conditions have been considered in order to estimate the total risk associated with a woman who takes part in all screening rounds. In the case of the VBCEDP, the total radio-induced risk probability for fatal breast cancer is in a range between [5 × 10-6, 6 × 10-4] versus the natural rate of dying from breast cancer in the Valencian Community which is 9.2 × 10-3. The results show that these indicators could be included in quality control tests and could be adequate for making comparisons between several screening programs.
NASA Astrophysics Data System (ADS)
Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.
2013-12-01
In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example
NASA Astrophysics Data System (ADS)
Toma-Danila, Dragos; Florinela Manea, Elena; Ortanza Cioflan, Carmen
2014-05-01
Bucharest, capital of Romania (with 1678000 inhabitants in 2011), is one of the most exposed big cities in Europe to seismic damage. The major earthquakes affecting the city have their origin in the Vrancea region. The Vrancea intermediate-depth source generates, statistically, 2-3 shocks with moment magnitude >7.0 per century. Although the focal distance is greater than 170 km, the historical records (from the 1838, 1894, 1908, 1940 and 1977 events) reveal severe effects in the Bucharest area, e.g. intensities IX (MSK) for the case of 1940 event. During the 1977 earthquake, 1420 people were killed and 33 large buildings collapsed. The nowadays building stock is vulnerable both due to construction (material, age) and soil conditions (high amplification, generated within the weak consolidated Quaternary deposits, their thickness is varying 250-500m throughout the city). A number of 373 old buildings, out of 2563, evaluated by experts are more likely to experience severe damage/collapse in the next major earthquake. The total number of residential buildings, in 2011, was 113900. In order to guide the mitigation measures, different studies tried to estimate the seismic risk of Bucharest, in terms of buildings, population or economic damage probability. Unfortunately, most of them were based on incomplete sets of data, whether regarding the hazard or the building stock in detail. However, during the DACEA Project, the National Institute for Earth Physics, together with the Technical University of Civil Engineering Bucharest and NORSAR Institute managed to compile a database for buildings in southern Romania (according to the 1999 census), with 48 associated capacity and fragility curves. Until now, the developed real-time estimation system was not implemented for Bucharest. This paper presents more than an adaptation of this system to Bucharest; first, we analyze the previous seismic risk studies, from a SWOT perspective. This reveals that most of the studies don't use
NASA Technical Reports Server (NTRS)
Butler, Doug; Bauman, David; Johnson-Throop, Kathy
2011-01-01
The Integrated Medical Model (IMM) Project has been developing a probabilistic risk assessment tool, the IMM, to help evaluate in-flight crew health needs and impacts to the mission due to medical events. This package is a follow-up to a data package provided in June 2009. The IMM currently represents 83 medical conditions and associated ISS resources required to mitigate medical events. IMM end state forecasts relevant to the ISS PRA model include evacuation (EVAC) and loss of crew life (LOCL). The current version of the IMM provides the basis for the operational version of IMM expected in the January 2011 timeframe. The objectives of this data package are: 1. To provide a preliminary understanding of medical risk data used to update the ISS PRA Model. The IMM has had limited validation and an initial characterization of maturity has been completed using NASA STD 7009 Standard for Models and Simulation. The IMM has been internally validated by IMM personnel but has not been validated by an independent body external to the IMM Project. 2. To support a continued dialogue between the ISS PRA and IMM teams. To ensure accurate data interpretation, and that IMM output format and content meets the needs of the ISS Risk Management Office and ISS PRA Model, periodic discussions are anticipated between the risk teams. 3. To help assess the differences between the current ISS PRA and IMM medical risk forecasts of EVAC and LOCL. Follow-on activities are anticipated based on the differences between the current ISS PRA medical risk data and the latest medical risk data produced by IMM.
NASA Astrophysics Data System (ADS)
Catoire, Laurent; Naudet, Valérie
2004-12-01
A simple empirical equation is presented for the estimation of closed-cup flash points for pure organic liquids. Data needed for the estimation of a flash point (FP) are the normal boiling point (Teb), the standard enthalpy of vaporization at 298.15 K [ΔvapH°(298.15 K)] of the compound, and the number of carbon atoms (n) in the molecule. The bounds for this equation are: -100⩽FP(°C)⩽+200; 250⩽Teb(K)⩽650; 20⩽Δvap H°(298.15 K)/(kJ mol-1)⩽110; 1⩽n⩽21. Compared to other methods (empirical equations, structural group contribution methods, and neural network quantitative structure-property relationships), this simple equation is shown to predict accurately the flash points for a variety of compounds, whatever their chemical groups (monofunctional compounds and polyfunctional compounds) and whatever their structure (linear, branched, cyclic). The same equation is shown to be valid for hydrocarbons, organic nitrogen compounds, organic oxygen compounds, organic sulfur compounds, organic halogen compounds, and organic silicone compounds. It seems that the flash points of organic deuterium compounds, organic tin compounds, organic nickel compounds, organic phosphorus compounds, organic boron compounds, and organic germanium compounds can also be predicted accurately by this equation. A mean absolute deviation of about 3 °C, a standard deviation of about 2 °C, and a maximum absolute deviation of 10 °C are obtained when predictions are compared to experimental data for more than 600 compounds. For all these compounds, the absolute deviation is equal or lower than the reproductibility expected at a 95% confidence level for closed-cup flash point measurement. This estimation technique has its limitations concerning the polyhalogenated compounds for which the equation should be used with caution. The mean absolute deviation and maximum absolute deviation observed and the fact that the equation provides unbiaised predictions lead to the conclusion that
CubeSat mission design software tool for risk estimating relationships
NASA Astrophysics Data System (ADS)
Gamble, Katharine Brumbaugh; Lightsey, E. Glenn
2014-09-01
In an effort to make the CubeSat risk estimation and management process more scientific, a software tool has been created that enables mission designers to estimate mission risks. CubeSat mission designers are able to input mission characteristics, such as form factor, mass, development cycle, and launch information, in order to determine the mission risk root causes which historically present the highest risk for their mission. Historical data was collected from the CubeSat community and analyzed to provide a statistical background to characterize these Risk Estimating Relationships (RERs). This paper develops and validates the mathematical model based on the same cost estimating relationship methodology used by the Unmanned Spacecraft Cost Model (USCM) and the Small Satellite Cost Model (SSCM). The RER development uses general error regression models to determine the best fit relat