Is blood pressure reduction a valid surrogate endpoint for stroke prevention? an analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the surrogate threshold effect (STE) and the biomarker-surrogacy (BioSurrogate) evaluation schema (BSES)

PubMed Central

2012-01-01

Background Blood pressure is considered to be a leading example of a valid surrogate endpoint. The aims of this study were to (i) formally evaluate systolic and diastolic blood pressure reduction as a surrogate endpoint for stroke prevention and (ii) determine what blood pressure reduction would predict a stroke benefit. Methods We identified randomised trials of at least six months duration comparing any pharmacologic anti-hypertensive treatment to placebo or no treatment, and reporting baseline blood pressure, on-trial blood pressure, and fatal and non-fatal stroke. Trials with fewer than five strokes in at least one arm were excluded. Errors-in-variables weighted least squares regression modelled the reduction in stroke as a function of systolic blood pressure reduction and diastolic blood pressure reduction respectively. The lower 95% prediction band was used to determine the minimum systolic blood pressure and diastolic blood pressure difference, the surrogate threshold effect (STE), below which there would be no predicted stroke benefit. The STE was used to generate the surrogate threshold effect proportion (STEP), a surrogacy metric, which with the R-squared trial-level association was used to evaluate blood pressure as a surrogate endpoint for stroke using the Biomarker-Surrogacy Evaluation Schema (BSES3). Results In 18 qualifying trials representing all pharmacologic drug classes of antihypertensives, assuming a reliability coefficient of 0.9, the surrogate threshold effect for a stroke benefit was 7.1 mmHg for systolic blood pressure and 2.4 mmHg for diastolic blood pressure. The trial-level association was 0.41 and 0.64 and the STEP was 66% and 78% for systolic and diastolic blood pressure respectively. The STE and STEP were more robust to measurement error in the independent variable than R-squared trial-level associations. Using the BSES3, assuming a reliability coefficient of 0.9, systolic blood pressure was a B + grade and diastolic blood pressure was an A grade surrogate endpoint for stroke prevention. In comparison, using the same stroke data sets, no STEs could be estimated for cardiovascular (CV) mortality or all-cause mortality reduction, although the STE for CV mortality approached 25 mmHg for systolic blood pressure. Conclusions In this report we provide the first surrogate threshold effect (STE) values for systolic and diastolic blood pressure. We suggest the STEs have face and content validity, evidenced by the inclusivity of trial populations, subject populations and pharmacologic intervention populations in their calculation. We propose that the STE and STEP metrics offer another method of evaluating the evidence supporting surrogate endpoints. We demonstrate how surrogacy evaluations are strengthened if formally evaluated within specific-context evaluation frameworks using the Biomarker- Surrogate Evaluation Schema (BSES3), and we discuss the implications of our evaluation of blood pressure on other biomarkers and patient-reported instruments in relation to surrogacy metrics and trial design. PMID:22409774

Surrogate markers for time-varying treatments and outcomes

PubMed Central

Hsu, Jesse Y; Kennedy, Edward H; Roy, Jason A; Stephens-Shields, Alisa J; Small, Dylan S; Joffe, Marshall M

2015-01-01

Background A surrogate marker is a variable commonly used in clinical trials to guide treatment decisions when the outcome of ultimate interest is not available. A good surrogate marker is one where the treatment effect on the surrogate is a strong predictor of the effect of treatment on the outcome. We review the situation when there is one treatment delivered at baseline, one surrogate measured at one later time point and one ultimate outcome of interest, and discuss new issues arising when variables are time-varying. Methods Most of the literature on surrogate markers has only considered simple settings with one treatment, one surrogate, and one outcome of interest at a fixed time point. However, more complicated time-varying settings are common in practice. In this paper, we describe the unique challenges in two settings, time-varying treatments and time-varying surrogates, while relating the ideas back to the causal-effects and causal-association paradigms. Conclusions In addition to discussing and extending popular notions of surrogacy to time-varying settings, we give examples illustrating that one can be misled by not taking into account time-varying information about the surrogate or treatment. We hope this paper has provided some motivation for future work on estimation and inference in such settings. PMID:25948621

A review of surrogate models and their application to groundwater modeling

NASA Astrophysics Data System (ADS)

Asher, M. J.; Croke, B. F. W.; Jakeman, A. J.; Peeters, L. J. M.

2015-08-01

The spatially and temporally variable parameters and inputs to complex groundwater models typically result in long runtimes which hinder comprehensive calibration, sensitivity, and uncertainty analysis. Surrogate modeling aims to provide a simpler, and hence faster, model which emulates the specified output of a more complex model in function of its inputs and parameters. In this review paper, we summarize surrogate modeling techniques in three categories: data-driven, projection, and hierarchical-based approaches. Data-driven surrogates approximate a groundwater model through an empirical model that captures the input-output mapping of the original model. Projection-based models reduce the dimensionality of the parameter space by projecting the governing equations onto a basis of orthonormal vectors. In hierarchical or multifidelity methods the surrogate is created by simplifying the representation of the physical system, such as by ignoring certain processes, or reducing the numerical resolution. In discussing the application to groundwater modeling of these methods, we note several imbalances in the existing literature: a large body of work on data-driven approaches seemingly ignores major drawbacks to the methods; only a fraction of the literature focuses on creating surrogates to reproduce outputs of fully distributed groundwater models, despite these being ubiquitous in practice; and a number of the more advanced surrogate modeling methods are yet to be fully applied in a groundwater modeling context.

Habitat suitability index model for brook trout in streams of the Southern Blue Ridge Province: surrogate variables, model evaluation, and suggested improvements

Treesearch

Christoper J. Schmitt; A. Dennis Lemly; Parley V. Winger

1993-01-01

Data from several sources were collated and analyzed by correlation, regression, and principal components analysis to define surrrogate variables for use in the brook trout (Salvelinus fontinalis) habitat suitability index (HSI) model, and to evaluate the applicability of the model for assessing habitat in high elevation streams of the southern Blue Ridge Province (...

Multi-Scale Modeling, Surrogate-Based Analysis, and Optimization of Lithium-Ion Batteries for Vehicle Applications

NASA Astrophysics Data System (ADS)

Du, Wenbo

A common attribute of electric-powered aerospace vehicles and systems such as unmanned aerial vehicles, hybrid- and fully-electric aircraft, and satellites is that their performance is usually limited by the energy density of their batteries. Although lithium-ion batteries offer distinct advantages such as high voltage and low weight over other battery technologies, they are a relatively new development, and thus significant gaps in the understanding of the physical phenomena that govern battery performance remain. As a result of this limited understanding, batteries must often undergo a cumbersome design process involving many manual iterations based on rules of thumb and ad-hoc design principles. A systematic study of the relationship between operational, geometric, morphological, and material-dependent properties and performance metrics such as energy and power density is non-trivial due to the multiphysics, multiphase, and multiscale nature of the battery system. To address these challenges, two numerical frameworks are established in this dissertation: a process for analyzing and optimizing several key design variables using surrogate modeling tools and gradient-based optimizers, and a multi-scale model that incorporates more detailed microstructural information into the computationally efficient but limited macro-homogeneous model. In the surrogate modeling process, multi-dimensional maps for the cell energy density with respect to design variables such as the particle size, ion diffusivity, and electron conductivity of the porous cathode material are created. A combined surrogate- and gradient-based approach is employed to identify optimal values for cathode thickness and porosity under various operating conditions, and quantify the uncertainty in the surrogate model. The performance of multiple cathode materials is also compared by defining dimensionless transport parameters. The multi-scale model makes use of detailed 3-D FEM simulations conducted at the particle-level. A monodisperse system of ellipsoidal particles is used to simulate the effective transport coefficients and interfacial reaction current density within the porous microstructure. Microscopic simulation results are shown to match well with experimental measurements, while differing significantly from homogenization approximations used in the macroscopic model. Global sensitivity analysis and surrogate modeling tools are applied to couple the two length scales and complete the multi-scale model.

Bioaccessibility of metals in alloys: Evaluation of three surrogate biofluids

PubMed Central

Hillwalker, Wendy E.; Anderson, Kim A.

2014-01-01

Bioaccessibility in vitro tests measure the solubility of materials in surrogate biofluids. However, the lack of uniform methods and the effects of variable test parameters on material solubility limit interpretation. One aim of this study was to measure and compare bioaccessibility of selected economically important alloys and metals in surrogate physiologically based biofluids representing oral, inhalation and dermal exposures. A second aim was to experimentally test different biofluid formulations and residence times in vitro. A third aim was evaluation of dissolution behavior of alloys with in vitro lung and dermal biofluid surrogates. This study evaluated the bioaccessibility of sixteen elements in six alloys and 3 elemental/metal powders. We found that the alloys/metals, the chemical properties of the surrogate fluid, and residence time all had major impacts on metal solubility. The large variability of bioaccessibility indicates the relevancy of assessing alloys as toxicologically distinct relative to individual metals. PMID:24212234

Bayesian network representing system dynamics in risk analysis of nuclear systems

NASA Astrophysics Data System (ADS)

Varuttamaseni, Athi

2011-12-01

A dynamic Bayesian network (DBN) model is used in conjunction with the alternating conditional expectation (ACE) regression method to analyze the risk associated with the loss of feedwater accident coupled with a subsequent initiation of the feed and bleed operation in the Zion-1 nuclear power plant. The use of the DBN allows the joint probability distribution to be factorized, enabling the analysis to be done on many simpler network structures rather than on one complicated structure. The construction of the DBN model assumes conditional independence relations among certain key reactor parameters. The choice of parameter to model is based on considerations of the macroscopic balance statements governing the behavior of the reactor under a quasi-static assumption. The DBN is used to relate the peak clad temperature to a set of independent variables that are known to be important in determining the success of the feed and bleed operation. A simple linear relationship is then used to relate the clad temperature to the core damage probability. To obtain a quantitative relationship among different nodes in the DBN, surrogates of the RELAP5 reactor transient analysis code are used. These surrogates are generated by applying the ACE algorithm to output data obtained from about 50 RELAP5 cases covering a wide range of the selected independent variables. These surrogates allow important safety parameters such as the fuel clad temperature to be expressed as a function of key reactor parameters such as the coolant temperature and pressure together with important independent variables such as the scram delay time. The time-dependent core damage probability is calculated by sampling the independent variables from their probability distributions and propagate the information up through the Bayesian network to give the clad temperature. With the knowledge of the clad temperature and the assumption that the core damage probability has a one-to-one relationship to it, we have calculated the core damage probably as a function of transient time. The use of the DBN model in combination with ACE allows risk analysis to be performed with much less effort than if the analysis were done using the standard techniques.

Long-term characterization of residential runoff and assessing potential surrogates of fecal indicator organisms.

PubMed

Reano, Dane C; Haver, Darren L; Oki, Lorence R; Yates, Marylynn V

2015-05-01

Investigations into the microbiological impacts of urban runoff on receiving water bodies, especially during storm conditions, have yielded general paradigms that influence runoff abatement and control management strategies. To determine whether these trends are present in other runoff sources, the physical, chemical, and microbiological components of residential runoff from eight neighborhoods in Northern and Southern California were characterized over the course of five years. Sampling occurred regularly and during storm events, resulting in 833 data sets. Analysis of runoff data assisted in characterizing residential runoff, elucidating differences between dry and storm conditions, and identifying surrogates capable of assessing microbiological quality. Results indicate that although microbial loading increases during storm events similar to urban runoff, annual microbial loading in these study sites principally occurs during dry conditions (24% storm, 76% dry). Generated artificial neural network and multiple linear regression models assessed surrogate performance by accurately predicting Escherichia coli concentrations from validation data sets (R(2) = 0.74 and 0.77, respectively), but required input from other fecal indicator organism (FIO) variables to maintain performance (R(2) = 0.27 and 0.18, respectively, without FIO). This long-term analysis of residential runoff highlights characteristics distinct from urban runoff and establishes necessary variables for determining microbiological quality, thus better informing future management strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

When life imitates art: surrogate decision making at the end of life.

PubMed

Shapiro, Susan P

2007-01-01

The privileging of the substituted judgment standard as the gold standard for surrogate decision making in law and bioethics has constrained the research agenda in end-of-life decision making. The empirical literature is inundated with a plethora of "Newlywed Game" designs, in which potential patients and potential surrogates respond to hypothetical scenarios to see how often they "get it right." The preoccupation with determining the capacity of surrogates to accurately reproduce the judgments of another makes a number of assumptions that blind scholars to the variables central to understanding how surrogates actually make medical decisions on behalf of another. These assumptions include that patient preferences are knowable, surrogates have adequate and accurate information, time stands still, patients get the surrogates they want, patients want and surrogates utilize substituted judgment criteria, and surrogates are disinterested. This article examines these assumptions and considers the challenges of designing research that makes them problematic.

Heart-Rate Variability-More than Heart Beats?

PubMed

Ernst, Gernot

2017-01-01

Heart-rate variability (HRV) is frequently introduced as mirroring imbalances within the autonomous nerve system. Many investigations are based on the paradigm that increased sympathetic tone is associated with decreased parasympathetic tone and vice versa . But HRV is probably more than an indicator for probable disturbances in the autonomous system. Some perturbations trigger not reciprocal, but parallel changes of vagal and sympathetic nerve activity. HRV has also been considered as a surrogate parameter of the complex interaction between brain and cardiovascular system. Systems biology is an inter-disciplinary field of study focusing on complex interactions within biological systems like the cardiovascular system, with the help of computational models and time series analysis, beyond others. Time series are considered surrogates of the particular system, reflecting robustness or fragility. Increased variability is usually seen as associated with a good health condition, whereas lowered variability might signify pathological changes. This might explain why lower HRV parameters were related to decreased life expectancy in several studies. Newer integrating theories have been proposed. According to them, HRV reflects as much the state of the heart as the state of the brain. The polyvagal theory suggests that the physiological state dictates the range of behavior and psychological experience. Stressful events perpetuate the rhythms of autonomic states, and subsequently, behaviors. Reduced variability will according to this theory not only be a surrogate but represent a fundamental homeostasis mechanism in a pathological state. The neurovisceral integration model proposes that cardiac vagal tone, described in HRV beyond others as HF-index, can mirror the functional balance of the neural networks implicated in emotion-cognition interactions. Both recent models represent a more holistic approach to understanding the significance of HRV.

Choice of surrogate tissue influences neonatal EWAS findings.

PubMed

Lin, Xinyi; Teh, Ai Ling; Chen, Li; Lim, Ives Yubin; Tan, Pei Fang; MacIsaac, Julia L; Morin, Alexander M; Yap, Fabian; Tan, Kok Hian; Saw, Seang Mei; Lee, Yung Seng; Holbrook, Joanna D; Godfrey, Keith M; Meaney, Michael J; Kobor, Michael S; Chong, Yap Seng; Gluckman, Peter D; Karnani, Neerja

2017-12-05

Epigenomes are tissue specific and thus the choice of surrogate tissue can play a critical role in interpreting neonatal epigenome-wide association studies (EWAS) and in their extrapolation to target tissue. To develop a better understanding of the link between tissue specificity and neonatal EWAS, and the contributions of genotype and prenatal factors, we compared genome-wide DNA methylation of cord tissue and cord blood, two of the most accessible surrogate tissues at birth. In 295 neonates, DNA methylation was profiled using Infinium HumanMethylation450 beadchip arrays. Sites of inter-individual variability in DNA methylation were mapped and compared across the two surrogate tissues at birth, i.e., cord tissue and cord blood. To ascertain the similarity to target tissues, DNA methylation profiles of surrogate tissues were compared to 25 primary tissues/cell types mapped under the Epigenome Roadmap project. Tissue-specific influences of genotype on the variable CpGs were also analyzed. Finally, to interrogate the impact of the in utero environment, EWAS on 45 prenatal factors were performed and compared across the surrogate tissues. Neonatal EWAS results were tissue specific. In comparison to cord blood, cord tissue showed higher inter-individual variability in the epigenome, with a lower proportion of CpGs influenced by genotype. Both neonatal tissues were good surrogates for target tissues of mesodermal origin. They also showed distinct phenotypic associations, with effect sizes of the overlapping CpGs being in the same order of magnitude. The inter-relationship between genetics, prenatal factors and epigenetics is tissue specific, and requires careful consideration in designing and interpreting future neonatal EWAS. This birth cohort is a prospective observational study, designed to study the developmental origins of health and disease, and was retrospectively registered on 1 July 2010 under the identifier NCT01174875 .

Using abiotic variables to predict importance of sites for species representation.

PubMed

Albuquerque, Fabio; Beier, Paul

2015-10-01

In systematic conservation planning, species distribution data for all sites in a planning area are used to prioritize each site in terms of the site's importance toward meeting the goal of species representation. But comprehensive species data are not available in most planning areas and would be expensive to acquire. As a shortcut, ecologists use surrogates, such as occurrences of birds or another well-surveyed taxon, or land types defined from remotely sensed data, in the hope that sites that represent the surrogates also represent biodiversity. Unfortunately, surrogates have not performed reliably. We propose a new type of surrogate, predicted importance, that can be developed from species data for a q% subset of sites. With species data from this subset of sites, importance can be modeled as a function of abiotic variables available at no charge for all terrestrial areas on Earth. Predicted importance can then be used as a surrogate to prioritize all sites. We tested this surrogate with 8 sets of species data. For each data set, we used a q% subset of sites to model importance as a function of abiotic variables, used the resulting function to predict importance for all sites, and evaluated the number of species in the sites with highest predicted importance. Sites with the highest predicted importance represented species efficiently for all data sets when q = 25% and for 7 of 8 data sets when q = 20%. Predicted importance requires less survey effort than direct selection for species representation and meets representation goals well compared with other surrogates currently in use. This less expensive surrogate may be useful in those areas of the world that need it most, namely tropical regions with the highest biodiversity, greatest biodiversity loss, most severe lack of inventory data, and poorly developed protected area networks. © 2015 Society for Conservation Biology.

Three Dimensional CFD Analysis of the GTX Combustor

NASA Technical Reports Server (NTRS)

Steffen, C. J., Jr.; Bond, R. B.; Edwards, J. R.

2002-01-01

The annular combustor geometry of a combined-cycle engine has been analyzed with three-dimensional computational fluid dynamics. Both subsonic combustion and supersonic combustion flowfields have been simulated. The subsonic combustion analysis was executed in conjunction with a direct-connect test rig. Two cold-flow and one hot-flow results are presented. The simulations compare favorably with the test data for the two cold flow calculations; the hot-flow data was not yet available. The hot-flow simulation indicates that the conventional ejector-ramjet cycle would not provide adequate mixing at the conditions tested. The supersonic combustion ramjet flowfield was simulated with frozen chemistry model. A five-parameter test matrix was specified, according to statistical design-of-experiments theory. Twenty-seven separate simulations were used to assemble surrogate models for combustor mixing efficiency and total pressure recovery. ScramJet injector design parameters (injector angle, location, and fuel split) as well as mission variables (total fuel massflow and freestream Mach number) were included in the analysis. A promising injector design has been identified that provides good mixing characteristics with low total pressure losses. The surrogate models can be used to develop performance maps of different injector designs. Several complex three-way variable interactions appear within the dataset that are not adequately resolved with the current statistical analysis.

Trends in Utilization of Surrogate Endpoints in Contemporary Cardiovascular Clinical Trials.

PubMed

Patel, Ravi B; Vaduganathan, Muthiah; Samman-Tahhan, Ayman; Kalogeropoulos, Andreas P; Georgiopoulou, Vasiliki V; Fonarow, Gregg C; Gheorghiade, Mihai; Butler, Javed

2016-06-01

Surrogate endpoints facilitate trial efficiency but are variably linked to clinical outcomes, and limited data are available exploring their utilization in cardiovascular clinical trials over time. We abstracted data regarding primary clinical, intermediate, and surrogate endpoints from all phase II to IV cardiovascular clinical trials from 2001 to 2012 published in the 8 highest Web of Science impact factor journals. Two investigators independently classified the type of primary endpoint. Of the 1,224 trials evaluated, 677 (55.3%) primary endpoints were clinical, 165 (13.5%) intermediate, and 382 (31.2%) surrogate. The relative proportions of these endpoints remained constant over time (p = 0.98). Trials using surrogate endpoints were smaller (187 vs 1,028 patients) and enrolled patients more expeditiously (1.4 vs 0.9 patients per site per month) compared with trials using clinical endpoints (p <0.001 for both comparisons). Surrogate endpoint trials were independently more likely to meet their primary endpoint compared to trials with clinical endpoints (adjusted odds ratio 1.56, 95% CI 1.05 to 2.34; p = 0.03). Rates of positive results in clinical endpoint trials have decreased over time from 66.1% in 2001 to 2003 to 47.2% in 2010 to 2012 (p = 0.001), whereas these rates have remained stable over the same period for surrogate (72.0% to 69.3%, p = 0.27) and intermediate endpoints (74.4% to 71.4%, p = 0.98). In conclusion, approximately a third of contemporary cardiovascular trials use surrogate endpoints. These trials are completed more expeditiously and are more likely to meet their primary outcomes. The overall scientific contribution of these surrogate endpoint trials requires further attention given their variable association with definitive outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

An Integrated Optimization Design Method Based on Surrogate Modeling Applied to Diverging Duct Design

NASA Astrophysics Data System (ADS)

Hanan, Lu; Qiushi, Li; Shaobin, Li

2016-12-01

This paper presents an integrated optimization design method in which uniform design, response surface methodology and genetic algorithm are used in combination. In detail, uniform design is used to select the experimental sampling points in the experimental domain and the system performance is evaluated by means of computational fluid dynamics to construct a database. After that, response surface methodology is employed to generate a surrogate mathematical model relating the optimization objective and the design variables. Subsequently, genetic algorithm is adopted and applied to the surrogate model to acquire the optimal solution in the case of satisfying some constraints. The method has been applied to the optimization design of an axisymmetric diverging duct, dealing with three design variables including one qualitative variable and two quantitative variables. The method of modeling and optimization design performs well in improving the duct aerodynamic performance and can be also applied to wider fields of mechanical design and seen as a useful tool for engineering designers, by reducing the design time and computation consumption.

Calculating terrain indices along streams: A new method for separating stream sides

Treesearch

T. J. Grabs; K. G. Jencso; B. L. McGlynn; J. Seibert

2010-01-01

There is increasing interest in assessing riparian zones and their hydrological and biogeochemical buffering capacity with indices derived from hydrologic landscape analysis of digital elevation data. Upslope contributing area is a common surrogate for lateral water flows and can be used to assess the variability of local water inflows to riparian zones and streams....

Best (but oft-forgotten) practices: mediation analysis.

PubMed

Fairchild, Amanda J; McDaniel, Heather L

2017-06-01

This contribution in the "Best (but Oft-Forgotten) Practices" series considers mediation analysis. A mediator (sometimes referred to as an intermediate variable, surrogate endpoint, or intermediate endpoint) is a third variable that explains how or why ≥2 other variables relate in a putative causal pathway. The current article discusses mediation analysis with the ultimate intention of helping nutrition researchers to clarify the rationale for examining mediation, avoid common pitfalls when using the model, and conduct well-informed analyses that can contribute to improving causal inference in evaluations of underlying mechanisms of effects on nutrition-related behavioral and health outcomes. We give specific attention to underevaluated limitations inherent in common approaches to mediation. In addition, we discuss how to conduct a power analysis for mediation models and offer an applied example to demonstrate mediation analysis. Finally, we provide an example write-up of mediation analysis results as a model for applied researchers. © 2017 American Society for Nutrition.

Best (but oft-forgotten) practices: mediation analysis12

PubMed Central

McDaniel, Heather L

2017-01-01

This contribution in the “Best (but Oft-Forgotten) Practices” series considers mediation analysis. A mediator (sometimes referred to as an intermediate variable, surrogate endpoint, or intermediate endpoint) is a third variable that explains how or why ≥2 other variables relate in a putative causal pathway. The current article discusses mediation analysis with the ultimate intention of helping nutrition researchers to clarify the rationale for examining mediation, avoid common pitfalls when using the model, and conduct well-informed analyses that can contribute to improving causal inference in evaluations of underlying mechanisms of effects on nutrition-related behavioral and health outcomes. We give specific attention to underevaluated limitations inherent in common approaches to mediation. In addition, we discuss how to conduct a power analysis for mediation models and offer an applied example to demonstrate mediation analysis. Finally, we provide an example write-up of mediation analysis results as a model for applied researchers. PMID:28446497

Heart-Rate Variability—More than Heart Beats?

PubMed Central

Ernst, Gernot

2017-01-01

Heart-rate variability (HRV) is frequently introduced as mirroring imbalances within the autonomous nerve system. Many investigations are based on the paradigm that increased sympathetic tone is associated with decreased parasympathetic tone and vice versa. But HRV is probably more than an indicator for probable disturbances in the autonomous system. Some perturbations trigger not reciprocal, but parallel changes of vagal and sympathetic nerve activity. HRV has also been considered as a surrogate parameter of the complex interaction between brain and cardiovascular system. Systems biology is an inter-disciplinary field of study focusing on complex interactions within biological systems like the cardiovascular system, with the help of computational models and time series analysis, beyond others. Time series are considered surrogates of the particular system, reflecting robustness or fragility. Increased variability is usually seen as associated with a good health condition, whereas lowered variability might signify pathological changes. This might explain why lower HRV parameters were related to decreased life expectancy in several studies. Newer integrating theories have been proposed. According to them, HRV reflects as much the state of the heart as the state of the brain. The polyvagal theory suggests that the physiological state dictates the range of behavior and psychological experience. Stressful events perpetuate the rhythms of autonomic states, and subsequently, behaviors. Reduced variability will according to this theory not only be a surrogate but represent a fundamental homeostasis mechanism in a pathological state. The neurovisceral integration model proposes that cardiac vagal tone, described in HRV beyond others as HF-index, can mirror the functional balance of the neural networks implicated in emotion–cognition interactions. Both recent models represent a more holistic approach to understanding the significance of HRV. PMID:28955705

Surrogate Endpoints and Risk Adaptive Strategies in Previously Untreated Follicular Lymphoma.

PubMed

Narkhede, Mayur S; Cheson, Bruce D

2018-05-05

Follicular lymphoma is the second most common subtype of non-Hodgkin lymphoma with an estimated 3.18 cases per 100,000 people. Despite the prolongation of survival with chemoimmunotherapy, variability in response to initial treatment and outcome still exists. Whereas prolonging overall survival is important, it is generally an unreasonable primary endpoint in the front-line setting. The long follow-up needed and the influence of subsequent therapies creates a potential bias. Thus, clinical trials require approximately 5 to 8 years from activation to completion and analysis of outcomes. This duration results in enormous cost and a delay in developing newer therapies. Thus, there is a need to identify markers or surrogate endpoints that can be used in clinical trials to expedite the development of new treatments. This review will discuss various clinical, radiologic, and laboratory measures used to assess outcomes and overall survival in patients with untreated follicular lymphoma, and gauge their utility in clinical trials as surrogate endpoints. Copyright © 2018 Elsevier Inc. All rights reserved.

Habitats as Surrogates of Taxonomic and Functional Fish Assemblages in Coral Reef Ecosystems: A Critical Analysis of Factors Driving Effectiveness

PubMed Central

Van Wynsberge, Simon; Andréfouët, Serge; Hamel, Mélanie A.; Kulbicki, Michel

2012-01-01

Species check-lists are helpful to establish Marine Protected Areas (MPAs) and protect local richness, endemicity, rarity, and biodiversity in general. However, such exhaustive taxonomic lists (i.e., true surrogate of biodiversity) require extensive and expensive censuses, and the use of estimator surrogates (e.g., habitats) is an appealing alternative. In truth, surrogate effectiveness appears from the literature highly variable both in marine and terrestrial ecosystems, making it difficult to provide practical recommendations for managers. Here, we evaluate how the biodiversity reference data set and its inherent bias can influence effectiveness. Specifically, we defined habitats by geomorphology, rugosity, and benthic cover and architecture criteria, and mapped them with satellite images for a New-Caledonian site. Fish taxonomic and functional lists were elaborated from Underwater Visual Censuses, stratified according to geomorphology and exposure. We then tested if MPA networks designed to maximize habitat richness, diversity and rarity could also effectively maximize fish richness, diversity, and rarity. Effectiveness appeared highly sensitive to the fish census design itself, in relation to the type of habitat map used and the scale of analysis. Spatial distribution of habitats (estimator surrogate’s distribution), quantity and location of fish census stations (target surrogate’s sampling), and random processes in the MPA design all affected effectiveness to the point that one small change in the data set could lead to opposite conclusions. We suggest that previous conclusions on surrogacy effectiveness, either positive or negative, marine or terrestrial, should be considered with caution, except in instances where very dense data sets were used without pseudo-replication. Although this does not rule out the validity of using surrogates of species lists for conservation planning, the critical joint examination of both target and estimator surrogates is needed for every case study. PMID:22815891

Magnetic Resonance Imaging–Guided versus Surrogate-Based Motion Tracking in Liver Radiation Therapy: A Prospective Comparative Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paganelli, Chiara, E-mail: chiara.paganelli@polimi.it; Seregni, Matteo; Fattori, Giovanni

Purpose: This study applied automatic feature detection on cine–magnetic resonance imaging (MRI) liver images in order to provide a prospective comparison between MRI-guided and surrogate-based tracking methods for motion-compensated liver radiation therapy. Methods and Materials: In a population of 30 subjects (5 volunteers plus 25 patients), 2 oblique sagittal slices were acquired across the liver at high temporal resolution. An algorithm based on scale invariant feature transform (SIFT) was used to extract and track multiple features throughout the image sequence. The position of abdominal markers was also measured directly from the image series, and the internal motion of each featuremore » was quantified through multiparametric analysis. Surrogate-based tumor tracking with a state-of-the-art external/internal correlation model was simulated. The geometrical tracking error was measured, and its correlation with external motion parameters was also investigated. Finally, the potential gain in tracking accuracy relying on MRI guidance was quantified as a function of the maximum allowed tracking error. Results: An average of 45 features was extracted for each subject across the whole liver. The multi-parametric motion analysis reported relevant inter- and intrasubject variability, highlighting the value of patient-specific and spatially-distributed measurements. Surrogate-based tracking errors (relative to the motion amplitude) were were in the range 7% to 23% (1.02-3.57mm) and were significantly influenced by external motion parameters. The gain of MRI guidance compared to surrogate-based motion tracking was larger than 30% in 50% of the subjects when considering a 1.5-mm tracking error tolerance. Conclusions: Automatic feature detection applied to cine-MRI allows detailed liver motion description to be obtained. Such information was used to quantify the performance of surrogate-based tracking methods and to provide a prospective comparison with respect to MRI-guided radiation therapy, which could support the definition of patient-specific optimal treatment strategies.« less

Testing Pairwise Association between Spatially Autocorrelated Variables: A New Approach Using Surrogate Lattice Data

PubMed Central

Deblauwe, Vincent; Kennel, Pol; Couteron, Pierre

2012-01-01

Background Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. Methodology/Principal Findings The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. Conclusions/Significance The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for validation of species distribution models. An implementation of the method in Java for the generation of wavelet-based surrogates is available online as supporting material. PMID:23144961

Modeling Individual Damped Linear Oscillator Processes with Differential Equations: Using Surrogate Data Analysis to Estimate the Smoothing Parameter

ERIC Educational Resources Information Center

Deboeck, Pascal R.; Boker, Steven M.; Bergeman, C. S.

2008-01-01

Among the many methods available for modeling intraindividual time series, differential equation modeling has several advantages that make it promising for applications to psychological data. One interesting differential equation model is that of the damped linear oscillator (DLO), which can be used to model variables that have a tendency to…

Joint nonparametric correction estimator for excess relative risk regression in survival analysis with exposure measurement error

PubMed Central

Wang, Ching-Yun; Cullings, Harry; Song, Xiao; Kopecky, Kenneth J.

2017-01-01

SUMMARY Observational epidemiological studies often confront the problem of estimating exposure-disease relationships when the exposure is not measured exactly. In the paper, we investigate exposure measurement error in excess relative risk regression, which is a widely used model in radiation exposure effect research. In the study cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies a generalized version of the classical additive measurement error model, but it may or may not have repeated measurements. In addition, an instrumental variable is available for individuals in a subset of the whole cohort. We develop a nonparametric correction (NPC) estimator using data from the subcohort, and further propose a joint nonparametric correction (JNPC) estimator using all observed data to adjust for exposure measurement error. An optimal linear combination estimator of JNPC and NPC is further developed. The proposed estimators are nonparametric, which are consistent without imposing a covariate or error distribution, and are robust to heteroscedastic errors. Finite sample performance is examined via a simulation study. We apply the developed methods to data from the Radiation Effects Research Foundation, in which chromosome aberration is used to adjust for the effects of radiation dose measurement error on the estimation of radiation dose responses. PMID:29354018

A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement.

PubMed

Taylor, Paul G; Small, Michael; Lee, Kwee-Yum; Landeo, Raul; O'Meara, Damien M; Millett, Emma L

2016-10-01

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.

Program to Optimize Simulated Trajectories II (POST2) Surrogate Models for Mars Ascent Vehicle (MAV) Performance Assessment

NASA Technical Reports Server (NTRS)

Zwack, M. R.; Dees, P. D.; Thomas, H. D.; Polsgrove, T. P.; Holt, J. B.

2017-01-01

The primary purpose of the multiPOST tool is to enable the execution of much larger sets of vehicle cases to allow for broader trade space exploration. However, this exploration is not achieved solely with the increased case throughput. The multiPOST tool is applied to carry out a Design of Experiments (DOE), which is a set of cases that have been structured to capture a maximum amount of information about the design space with minimal computational effort. The results of the DOE are then used to fit a surrogate model, ultimately enabling parametric design space exploration. The approach used for the MAV study includes both DOE and surrogate modeling. First, the primary design considerations for the vehicle were used to develop the variables and ranges for the multiPOST DOE. The final set of DOE variables were carefully selected in order to capture the desired vehicle trades and take into account any special considerations for surrogate modeling. Next, the DOE sets were executed through multiPOST. Following successful completion of the DOE cases, a manual verification trial was performed. The trial involved randomly selecting cases from the DOE set and running them by hand. The results from the human analyst's run and multiPOST were then compared to ensure that the automated runs were being executed properly. Completion of the verification trials was then followed by surrogate model fitting. After fits to the multiPOST data were successfully created, the surrogate models were used as a stand-in for POST2 to carry out the desired MAV trades. Using the surrogate models in lieu of POST2 allowed for visualization of vehicle sensitivities to the input variables as well as rapid evaluation of vehicle performance. Although the models introduce some error into the output of the trade study, they were very effective at identifying areas of interest within the trade space for further refinement by human analysts. The next section will cover all of the ground rules and assumptions associated with DOE setup and multiPOST execution. Section 3.1 gives the final DOE variables and ranges, while section 3.2 addresses the POST2 specific assumptions. The results of the verification trials are given in section 4. Section 5 gives the surrogate model fitting results, including the goodness-of-fit metrics for each fit. Finally, the MAV specific results are discussed in section 6.

Synergies in the space of control variables within the equilibrium-point hypothesis.

PubMed

Ambike, S; Mattos, D; Zatsiorsky, V M; Latash, M L

2016-02-19

We use an approach rooted in the recent theory of synergies to analyze possible co-variation between two hypothetical control variables involved in finger force production based on the equilibrium-point (EP) hypothesis. These control variables are the referent coordinate (R) and apparent stiffness (C) of the finger. We tested a hypothesis that inter-trial co-variation in the {R; C} space during repeated, accurate force production trials stabilizes the fingertip force. This was expected to correspond to a relatively low amount of inter-trial variability affecting force and a high amount of variability keeping the force unchanged. We used the "inverse piano" apparatus to apply small and smooth positional perturbations to fingers during force production tasks. Across trials, R and C showed strong co-variation with the data points lying close to a hyperbolic curve. Hyperbolic regressions accounted for over 99% of the variance in the {R; C} space. Another analysis was conducted by randomizing the original {R; C} data sets and creating surrogate data sets that were then used to compute predicted force values. The surrogate sets always showed much higher force variance compared to the actual data, thus reinforcing the conclusion that finger force control was organized in the {R; C} space, as predicted by the EP hypothesis, and involved co-variation in that space stabilizing total force. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Synergies in the space of control variables within the equilibrium-point hypothesis

PubMed Central

Ambike, Satyajit; Mattos, Daniela; Zatsiorsky, Vladimir M.; Latash, Mark L.

2015-01-01

We use an approach rooted in the recent theory of synergies to analyze possible co-variation between two hypothetical control variables involved in finger force production based in the equilibrium-point hypothesis. These control variables are the referent coordinate (R) and apparent stiffness (C) of the finger. We tested a hypothesis that inter-trial co-variation in the {R; C} space during repeated, accurate force production trials stabilizes the fingertip force. This was expected to correspond to a relatively low amount of inter-trial variability affecting force and a high amount of variability keeping the force unchanged. We used the “inverse piano” apparatus to apply small and smooth positional perturbations to fingers during force production tasks. Across trials, R and C showed strong co-variation with the data points lying close to a hyperbolic curve. Hyperbolic regressions accounted for over 99% of the variance in the {R; C} space. Another analysis was conducted by randomizing the original {R; C} data sets and creating surrogate data sets that were then used to compute predicted force values. The surrogate sets always showed much higher force variance compared to the actual data, thus reinforcing the conclusion that finger force control was organized in the {R; C} space, as predicted by the equilibrium-point hypothesis, and involved co-variation in that space stabilizing total force. PMID:26701299

Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate data analysis.

PubMed

Indic, Premananda; Bloch-Salisbury, Elisabeth; Bednarek, Frank; Brown, Emery N; Paydarfar, David; Barbieri, Riccardo

2011-07-01

Cardio-respiratory interactions are weak at the earliest stages of human development, suggesting that assessment of their presence and integrity may be an important indicator of development in infants. Despite the valuable research devoted to infant development, there is still a need for specifically targeted standards and methods to assess cardiopulmonary functions in the early stages of life. We present a new methodological framework for the analysis of cardiovascular variables in preterm infants. Our approach is based on a set of mathematical tools that have been successful in quantifying important cardiovascular control mechanisms in adult humans, here specifically adapted to reflect the physiology of the developing cardiovascular system. We applied our methodology in a study of cardio-respiratory responses for 11 preterm infants. We quantified cardio-respiratory interactions using specifically tailored multivariate autoregressive analysis and calculated the coherence as well as gain using causal approaches. The significance of the interactions in each subject was determined by surrogate data analysis. The method was tested in control conditions as well as in two different experimental conditions; with and without use of mild mechanosensory intervention. Our multivariate analysis revealed a significantly higher coherence, as confirmed by surrogate data analysis, in the frequency range associated with eupneic breathing compared to the other ranges. Our analysis validates the models behind our new approaches, and our results confirm the presence of cardio-respiratory coupling in early stages of development, particularly during periods of mild mechanosensory intervention, thus encouraging further application of our approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

40 CFR Appendix A to Part 63 - Test Methods

Code of Federal Regulations, 2010 CFR

2010-07-01

... components by a different analyst). 3.3Surrogate Reference Materials. The analyst may use surrogate compounds... the variance of the proposed method is significantly different from that of the validated method by... variables can be determined in eight experiments rather than 128 (W.J. Youden, Statistical Manual of the...

Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14

USGS Publications Warehouse

Wood, Molly S.; Fosness, Ryan L.; Etheridge, Alexandra B.

2015-12-14

Acoustic surrogate ratings were developed between backscatter data collected using acoustic Doppler velocity meters (ADVMs) and results of suspended-sediment samples. Ratings were successfully fit to various sediment size classes (total, fines, and sands) using ADVMs of different frequencies (1.5 and 3 megahertz). Surrogate ratings also were developed using variations of streamflow and seasonal explanatory variables. The streamflow surrogate ratings produced average annual sediment load estimates that were 8–32 percent higher, depending on site and sediment type, than estimates produced using the acoustic surrogate ratings. The streamflow surrogate ratings tended to overestimate suspended-sediment concentrations and loads during periods of elevated releases from Libby Dam as well as on the falling limb of the streamflow hydrograph. Estimates from the acoustic surrogate ratings more closely matched suspended-sediment sample results than did estimates from the streamflow surrogate ratings during these periods as well as for rating validation samples collected in water year 2014. Acoustic surrogate technologies are an effective means to obtain continuous, accurate estimates of suspended-sediment concentrations and loads for general monitoring and sediment-transport modeling. In the Kootenai River, continued operation of the acoustic surrogate sites and use of the acoustic surrogate ratings to calculate continuous suspended-sediment concentrations and loads will allow for tracking changes in sediment transport over time.

Isoflurane and Ketamine Anesthesia have Different Effects on Ventilatory Pattern Variability in Rats

PubMed Central

Chung, Augustine; Fishman, Mikkel; Dasenbrook, Elliot C.; Loparo, Kenneth A.; Dick, Thomas E.; Jacono, Frank J.

2013-01-01

We hypothesize that isoflurane and ketamine impact ventilatory pattern variability (VPV) differently. Adult Sprague-Dawley rats were recorded in a whole-body plethysmograph before, during and after deep anesthesia. VPV was quantified from 60-s epochs using a complementary set of analytic techniques that included constructing surrogate data sets that preserved the linear structure but disrupted nonlinear deterministic properties of the original data. Even though isoflurane decreased and ketamine increased respiratory rate, VPV as quantified by the coefficient of variation decreased for both anesthetics. Further, mutual information increased and sample entropy decreased and the nonlinear complexity index (NLCI) increased during anesthesia despite qualitative differences in the shape and period of the waveform. Surprisingly mutual information and sample entropy did not change in the surrogate sets constructed from isoflurane data, but in those constructed from ketamine data, mutual information increased and sample entropy decreased significantly in the surrogate segments constructed from anesthetized relative to unanesthetized epochs. These data suggest that separate mechanisms modulate linear and nonlinear variability of breathing. PMID:23246800

An Empirical Assessment and Comparison of Species-Based and Habitat-Based Surrogates: A Case Study of Forest Vertebrates and Large Old Trees

PubMed Central

Lindenmayer, David B.; Barton, Philip S.; Lane, Peter W.; Westgate, Martin J.; McBurney, Lachlan; Blair, David; Gibbons, Philip; Likens, Gene E.

2014-01-01

A holy grail of conservation is to find simple but reliable measures of environmental change to guide management. For example, particular species or particular habitat attributes are often used as proxies for the abundance or diversity of a subset of other taxa. However, the efficacy of such kinds of species-based surrogates and habitat-based surrogates is rarely assessed, nor are different kinds of surrogates compared in terms of their relative effectiveness. We use 30-year datasets on arboreal marsupials and vegetation structure to quantify the effectiveness of: (1) the abundance of a particular species of arboreal marsupial as a species-based surrogate for other arboreal marsupial taxa, (2) hollow-bearing tree abundance as a habitat-based surrogate for arboreal marsupial abundance, and (3) a combination of species- and habitat-based surrogates. We also quantify the robustness of species-based and habitat-based surrogates over time. We then use the same approach to model overall species richness of arboreal marsupials. We show that a species-based surrogate can appear to be a valid surrogate until a habitat-based surrogate is co-examined, after which the effectiveness of the former is lost. The addition of a species-based surrogate to a habitat-based surrogate made little difference in explaining arboreal marsupial abundance, but altered the co-occurrence relationship between species. Hence, there was limited value in simultaneously using a combination of kinds of surrogates. The habitat-based surrogate also generally performed significantly better and was easier and less costly to gather than the species-based surrogate. We found that over 30 years of study, the relationships which underpinned the habitat-based surrogate generally remained positive but variable over time. Our work highlights why it is important to compare the effectiveness of different broad classes of surrogates and identify situations when either species- or habitat-based surrogates are likely to be superior. PMID:24587050

An empirical assessment and comparison of species-based and habitat-based surrogates: a case study of forest vertebrates and large old trees.

PubMed

Lindenmayer, David B; Barton, Philip S; Lane, Peter W; Westgate, Martin J; McBurney, Lachlan; Blair, David; Gibbons, Philip; Likens, Gene E

2014-01-01

A holy grail of conservation is to find simple but reliable measures of environmental change to guide management. For example, particular species or particular habitat attributes are often used as proxies for the abundance or diversity of a subset of other taxa. However, the efficacy of such kinds of species-based surrogates and habitat-based surrogates is rarely assessed, nor are different kinds of surrogates compared in terms of their relative effectiveness. We use 30-year datasets on arboreal marsupials and vegetation structure to quantify the effectiveness of: (1) the abundance of a particular species of arboreal marsupial as a species-based surrogate for other arboreal marsupial taxa, (2) hollow-bearing tree abundance as a habitat-based surrogate for arboreal marsupial abundance, and (3) a combination of species- and habitat-based surrogates. We also quantify the robustness of species-based and habitat-based surrogates over time. We then use the same approach to model overall species richness of arboreal marsupials. We show that a species-based surrogate can appear to be a valid surrogate until a habitat-based surrogate is co-examined, after which the effectiveness of the former is lost. The addition of a species-based surrogate to a habitat-based surrogate made little difference in explaining arboreal marsupial abundance, but altered the co-occurrence relationship between species. Hence, there was limited value in simultaneously using a combination of kinds of surrogates. The habitat-based surrogate also generally performed significantly better and was easier and less costly to gather than the species-based surrogate. We found that over 30 years of study, the relationships which underpinned the habitat-based surrogate generally remained positive but variable over time. Our work highlights why it is important to compare the effectiveness of different broad classes of surrogates and identify situations when either species- or habitat-based surrogates are likely to be superior.

Surrogate-based optimization of hydraulic fracturing in pre-existing fracture networks

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Sun, Yunwei; Fu, Pengcheng; Carrigan, Charles R.; Lu, Zhiming; Tong, Charles H.; Buscheck, Thomas A.

2013-08-01

Hydraulic fracturing has been used widely to stimulate production of oil, natural gas, and geothermal energy in formations with low natural permeability. Numerical optimization of fracture stimulation often requires a large number of evaluations of objective functions and constraints from forward hydraulic fracturing models, which are computationally expensive and even prohibitive in some situations. Moreover, there are a variety of uncertainties associated with the pre-existing fracture distributions and rock mechanical properties, which affect the optimized decisions for hydraulic fracturing. In this study, a surrogate-based approach is developed for efficient optimization of hydraulic fracturing well design in the presence of natural-system uncertainties. The fractal dimension is derived from the simulated fracturing network as the objective for maximizing energy recovery sweep efficiency. The surrogate model, which is constructed using training data from high-fidelity fracturing models for mapping the relationship between uncertain input parameters and the fractal dimension, provides fast approximation of the objective functions and constraints. A suite of surrogate models constructed using different fitting methods is evaluated and validated for fast predictions. Global sensitivity analysis is conducted to gain insights into the impact of the input variables on the output of interest, and further used for parameter screening. The high efficiency of the surrogate-based approach is demonstrated for three optimization scenarios with different and uncertain ambient conditions. Our results suggest the critical importance of considering uncertain pre-existing fracture networks in optimization studies of hydraulic fracturing.

Model-assisted probability of detection of flaws in aluminum blocks using polynomial chaos expansions

NASA Astrophysics Data System (ADS)

Du, Xiaosong; Leifsson, Leifur; Grandin, Robert; Meeker, William; Roberts, Ronald; Song, Jiming

2018-04-01

Probability of detection (POD) is widely used for measuring reliability of nondestructive testing (NDT) systems. Typically, POD is determined experimentally, while it can be enhanced by utilizing physics-based computational models in combination with model-assisted POD (MAPOD) methods. With the development of advanced physics-based methods, such as ultrasonic NDT testing, the empirical information, needed for POD methods, can be reduced. However, performing accurate numerical simulations can be prohibitively time-consuming, especially as part of stochastic analysis. In this work, stochastic surrogate models for computational physics-based measurement simulations are developed for cost savings of MAPOD methods while simultaneously ensuring sufficient accuracy. The stochastic surrogate is used to propagate the random input variables through the physics-based simulation model to obtain the joint probability distribution of the output. The POD curves are then generated based on those results. Here, the stochastic surrogates are constructed using non-intrusive polynomial chaos (NIPC) expansions. In particular, the NIPC methods used are the quadrature, ordinary least-squares (OLS), and least-angle regression sparse (LARS) techniques. The proposed approach is demonstrated on the ultrasonic testing simulation of a flat bottom hole flaw in an aluminum block. The results show that the stochastic surrogates have at least two orders of magnitude faster convergence on the statistics than direct Monte Carlo sampling (MCS). Moreover, the evaluation of the stochastic surrogate models is over three orders of magnitude faster than the underlying simulation model for this case, which is the UTSim2 model.

Surrogate matrix and surrogate analyte approaches for definitive quantitation of endogenous biomolecules.

PubMed

Jones, Barry R; Schultz, Gary A; Eckstein, James A; Ackermann, Bradley L

2012-10-01

Quantitation of biomarkers by LC-MS/MS is complicated by the presence of endogenous analytes. This challenge is most commonly overcome by calibration using an authentic standard spiked into a surrogate matrix devoid of the target analyte. A second approach involves use of a stable-isotope-labeled standard as a surrogate analyte to allow calibration in the actual biological matrix. For both methods, parallelism between calibration standards and the target analyte in biological matrix must be demonstrated in order to ensure accurate quantitation. In this communication, the surrogate matrix and surrogate analyte approaches are compared for the analysis of five amino acids in human plasma: alanine, valine, methionine, leucine and isoleucine. In addition, methodology based on standard addition is introduced, which enables a robust examination of parallelism in both surrogate analyte and surrogate matrix methods prior to formal validation. Results from additional assays are presented to introduce the standard-addition methodology and to highlight the strengths and weaknesses of each approach. For the analysis of amino acids in human plasma, comparable precision and accuracy were obtained by the surrogate matrix and surrogate analyte methods. Both assays were well within tolerances prescribed by regulatory guidance for validation of xenobiotic assays. When stable-isotope-labeled standards are readily available, the surrogate analyte approach allows for facile method development. By comparison, the surrogate matrix method requires greater up-front method development; however, this deficit is offset by the long-term advantage of simplified sample analysis.

Development Program of Dual Mode Impact Delay Module for Artillery Fuzes.

DTIC Science & Technology

1979-12-31

analysis phase to demonstrate design confidence and reliability of performance in the artillery firing environment. See Figure I for drawing of the latest...Device P/N KF88590 as proposed by us. This analysis will be based on results of penalty test« in which the test variables will include loading and...istently and unmistakably Dextrinated lead azide was, tent surrogate. On the basis of stab s Id be predicted that any system whi r mated lead azide

Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10

USGS Publications Warehouse

Wood, Molly S.; Teasdale, Gregg N.

2013-01-01

Elevated levels of fluvial sediment can reduce the biological productivity of aquatic systems, impair freshwater quality, decrease reservoir storage capacity, and decrease the capacity of hydraulic structures. The need to measure fluvial sediment has led to the development of sediment surrogate technologies, particularly in locations where streamflow alone is not a good estimator of sediment load because of regulated flow, load hysteresis, episodic sediment sources, and non-equilibrium sediment transport. An effective surrogate technology is low maintenance and sturdy over a range of hydrologic conditions, and measured variables can be modeled to estimate suspended-sediment concentration (SSC), load, and duration of elevated levels on a real-time basis. Among the most promising techniques is the measurement of acoustic backscatter strength using acoustic Doppler velocity meters (ADVMs) deployed in rivers. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, Walla Walla District, evaluated the use of acoustic backscatter, turbidity, laser diffraction, and streamflow as surrogates for estimating real-time SSC and loads in the Clearwater and Snake Rivers, which adjoin in Lewiston, Idaho, and flow into Lower Granite Reservoir. The study was conducted from May 2008 to September 2010 and is part of the U.S. Army Corps of Engineers Lower Snake River Programmatic Sediment Management Plan to identify and manage sediment sources in basins draining into lower Snake River reservoirs. Commercially available acoustic instruments have shown great promise in sediment surrogate studies because they require little maintenance and measure profiles of the surrogate parameter across a sampling volume rather than at a single point. The strength of acoustic backscatter theoretically increases as more particles are suspended in the water to reflect the acoustic pulse emitted by the ADVM. ADVMs of different frequencies (0.5, 1.5, and 3 Megahertz) were tested to target various sediment grain sizes. Laser diffraction and turbidity also were tested as surrogate technologies. Models between SSC and surrogate variables were developed using ordinary least-squares regression. Acoustic backscatter using the high frequency ADVM at each site was the best predictor of sediment, explaining 93 and 92 percent of the variability in SSC and matching sediment sample data within +8.6 and +10 percent, on average, at the Clearwater River and Snake River study sites, respectively. Additional surrogate models were developed to estimate sand and fines fractions of suspended sediment based on acoustic backscatter. Acoustic backscatter generally appears to be a better estimator of suspended sediment concentration and load over short (storm event and monthly) and long (annual) time scales than transport curves derived solely from the regression of conventional sediment measurements and streamflow. Changing grain sizes, the presence of organic matter, and aggregation of sediments in the river likely introduce some variability in the model between acoustic backscatter and SSC.

Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria

USGS Publications Warehouse

Stumpf, Rick P; Davis, Timothy W.; Wynne, Timothy T.; Graham, Jennifer L.; Loftin, Keith A.; Johengen, T.H.; Gossiaux, D.; Palladino, D.; Burtner, A.

2016-01-01

Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.

Vagal-dependent nonlinear variability in the respiratory pattern of anesthetized, spontaneously breathing rats

PubMed Central

Dhingra, R. R.; Jacono, F. J.; Fishman, M.; Loparo, K. A.; Rybak, I. A.

2011-01-01

Physiological rhythms, including respiration, exhibit endogenous variability associated with health, and deviations from this are associated with disease. Specific changes in the linear and nonlinear sources of breathing variability have not been investigated. In this study, we used information theory-based techniques, combined with surrogate data testing, to quantify and characterize the vagal-dependent nonlinear pattern variability in urethane-anesthetized, spontaneously breathing adult rats. Surrogate data sets preserved the amplitude distribution and linear correlations of the original data set, but nonlinear correlation structure in the data was removed. Differences in mutual information and sample entropy between original and surrogate data sets indicated the presence of deterministic nonlinear or stochastic non-Gaussian variability. With vagi intact (n = 11), the respiratory cycle exhibited significant nonlinear behavior in templates of points separated by time delays ranging from one sample to one cycle length. After vagotomy (n = 6), even though nonlinear variability was reduced significantly, nonlinear properties were still evident at various time delays. Nonlinear deterministic variability did not change further after subsequent bilateral microinjection of MK-801, an N-methyl-d-aspartate receptor antagonist, in the Kölliker-Fuse nuclei. Reversing the sequence (n = 5), blocking N-methyl-d-aspartate receptors bilaterally in the dorsolateral pons significantly decreased nonlinear variability in the respiratory pattern, even with the vagi intact, and subsequent vagotomy did not change nonlinear variability. Thus both vagal and dorsolateral pontine influences contribute to nonlinear respiratory pattern variability. Furthermore, breathing dynamics of the intact system are mutually dependent on vagal and pontine sources of nonlinear complexity. Understanding the structure and modulation of variability provides insight into disease effects on respiratory patterning. PMID:21527661

Using serum urate as a validated surrogate end point for flares in patients with gout: protocol for a systematic review and meta-regression analysis

PubMed Central

Morillon, Melanie B; Stamp, Lisa; Taylor, William; Fransen, Jaap; Dalbeth, Nicola; Singh, Jasvinder A; Lassere, Marissa

2016-01-01

Introduction Gout is the most common inflammatory arthritis in men over 40 years of age. Long-term urate-lowering therapy is considered a key strategy for effective gout management. The primary outcome measure for efficacy in clinical trials of urate-lowering therapy is serum urate levels, effectively acting as a surrogate for patient-centred outcomes such as frequency of gout attacks or pain. Yet it is not clearly demonstrated that the strength of the relationship between serum urate and clinically relevant outcomes is sufficiently strong for serum urate to be considered an adequate surrogate. Our objective is to investigate the strength of the relationship between changes in serum urate in randomised controlled trials and changes in clinically relevant outcomes according to the ‘Biomarker-Surrogacy Evaluation Schema version 3’ (BSES3), documenting the validity of selected instruments by applying the ‘OMERACT Filter 2.0’. Methods and analysis A systematic review described in terms of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines will identify all relevant studies. Standardised data elements will be extracted from each study by 2 independent reviewers and disagreements are resolved by discussion. The data will be analysed by meta-regression of the between-arm differences in the change in serum urate level (independent variable) from baseline to 3 months (or 6 and 12 months if 3-month values are not available) against flare rate, tophus size and number and pain at the final study visit (dependent variables). Ethics and dissemination This study will not require specific ethics approval since it is based on analysis of published (aggregated) data. The intended audience will include healthcare researchers, policymakers and clinicians. Results of the study will be disseminated by peer-reviewed publications. Trial registration number CRD42016026991. PMID:27650765

Consistent patterns of variation in macrobenthic assemblages and environmental variables over multiple spatial scales using taxonomic and functional approaches.

PubMed

Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos

2016-09-01

Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

NASA Astrophysics Data System (ADS)

Eduardo Virgilio Silva, Luiz; Otavio Murta, Luiz

2012-12-01

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiffmax) for q ≠1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiffmax values were capable of distinguish HRV groups (p-values 5.10×10-3, 1.11×10-7, and 5.50×10-7 for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis.

Impact of competitor species composition on predicting diameter growth and survival rates of Douglas-fir trees in southwestern Oregon

USGS Publications Warehouse

Bravo, Felipe; Hann, D.W.; Maguire, Douglas A.

2001-01-01

Mixed conifer and hardwood stands in southwestern Oregon were studied to explore the hypothesis that competition effects on individual-tree growth and survival will differ according to the species comprising the competition measure. Likewise, it was hypothesized that competition measures should extrapolate best if crown-based surrogates are given preference over diameter-based (basal area based) surrogates. Diameter growth and probability of survival were modeled for individual Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) trees growing in pure stands. Alternative models expressing one-sided and two-sided competition as a function of either basal area or crown structure were then applied to other plots in which Douglas-fir was mixed with other conifers and (or) hardwood species. Crown-based variables outperformed basal area based variables as surrogates for one-sided competition in both diameter growth and survival probability, regardless of species composition. In contrast, two-sided competition was best represented by total basal area of competing trees. Surrogates reflecting differences in crown morphology among species relate more closely to the mechanics of competition for light and, hence, facilitate extrapolation to species combinations for which no observations are available.

SU-F-T-113: Inherent Functional Dependence of Spinal Cord Doses of Variable Irradiated Volumes in Spine SBRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, L; Braunstein, S; Chiu, J

2016-06-15

Purpose: Spinal cord tolerance for SBRT has been recommended for the maximum point dose level or at irradiated volumes such as 0.35 mL or 10% of contoured volumes. In this study, we investigated an inherent functional relationship that associates these dose surrogates for irradiated spinal cord volumes of up to 3.0 mL. Methods: A hidden variable termed as Effective Dose Radius (EDR) was formulated based on a dose fall-off model to correlate dose at irradiated spinal cord volumes ranging from 0 mL (point maximum) to 3.0 mL. A cohort of 15 spine SBRT cases was randomly selected to derive anmore » EDR-parameterized formula. The mean prescription dose for the studied cases was 21.0±8.0 Gy (range, 10–40Gy) delivered in 3±1 fractions with target volumes of 39.1 ± 70.6 mL. Linear regression and variance analysis were performed for the fitting parameters of variable EDR values. Results: No direct correlation was found between the dose at maximum point and doses at variable spinal cord volumes. For example, Pearson R{sup 2} = 0.643 and R{sup 2}= 0.491 were obtained when correlating the point maximum dose with the spinal cord dose at 1 mL and 3 mL, respectively. However, near perfect correlation (R{sup 2} ≥0.99) was obtained when corresponding parameterized EDRs. Specifically, Pearson R{sup 2}= 0.996 and R{sup 2} = 0.990 were obtained when correlating EDR (maximum point dose) with EDR (dose at 1 mL) and EDR(dose at 3 mL), respectively. As a result, high confidence level look-up tables were established to correlate spinal cord doses at the maximum point to any finite irradiated volumes. Conclusion: An inherent functional relationship was demonstrated for spine SBRT. Such a relationship unifies dose surrogates at variable cord volumes and proves that a single dose surrogate (e.g. point maximum dose) is mathematically sufficient in constraining the overall spinal cord dose tolerance for SBRT.« less

Integrating environmental gap analysis with spatial conservation prioritization: a case study from Victoria, Australia.

PubMed

Sharafi, Seyedeh Mahdieh; Moilanen, Atte; White, Matt; Burgman, Mark

2012-12-15

Gap analysis is used to analyse reserve networks and their coverage of biodiversity, thus identifying gaps in biodiversity representation that may be filled by additional conservation measures. Gap analysis has been used to identify priorities for species and habitat types. When it is applied to identify gaps in the coverage of environmental variables, it embodies the assumption that combinations of environmental variables are effective surrogates for biodiversity attributes. The question remains of how to fill gaps in conservation systems efficiently. Conservation prioritization software can identify those areas outside existing conservation areas that contribute to the efficient covering of gaps in biodiversity features. We show how environmental gap analysis can be implemented using high-resolution information about environmental variables and ecosystem condition with the publicly available conservation prioritization software, Zonation. Our method is based on the conversion of combinations of environmental variables into biodiversity features. We also replicated the analysis by using Species Distribution Models (SDMs) as biodiversity features to evaluate the robustness and utility of our environment-based analysis. We apply the technique to a planning case study of the state of Victoria, Australia. Copyright © 2012 Elsevier Ltd. All rights reserved.

Beyond multi-fractals: surrogate time series and fields

NASA Astrophysics Data System (ADS)

Venema, V.; Simmer, C.

2007-12-01

Most natural complex are characterised by variability on a large range of temporal and spatial scales. The two main methodologies to generate such structures are Fourier/FARIMA based algorithms and multifractal methods. The former is restricted to Gaussian data, whereas the latter requires the structure to be self-similar. This work will present so-called surrogate data as an alternative that works with any (empirical) distribution and power spectrum. The best-known surrogate algorithm is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm. We have studied six different geophysical time series (two clouds, runoff of a small and a large river, temperature and rain) and their surrogates. The power spectra and consequently the 2nd order structure functions were replicated accurately. Even the fourth order structure function was more accurately reproduced by the surrogates as would be possible by a fractal method, because the measured structure deviated too strong from fractal scaling. Only in case of the daily rain sums a fractal method could have been more accurate. Just as Fourier and multifractal methods, the current surrogates are not able to model the asymmetric increment distributions observed for runoff, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found differences for the structure functions on small scales. Surrogate methods are especially valuable for empirical studies, because the time series and fields that are generated are able to mimic measured variables accurately. Our main application is radiative transfer through structured clouds. Like many geophysical fields, clouds can only be sampled sparsely, e.g. with in-situ airborne instruments. However, for radiative transfer calculations we need full 3-dimensional cloud fields. A first study relating the measured properties of the cloud droplets and the radiative properties of the cloud field by generating surrogate cloud fields yielded good results within the measurement error. A further test of the suitability of the surrogate clouds for radiative transfer is evaluated by comparing the radiative properties of model cloud fields of sparse cumulus and stratocumulus with their surrogate fields. The bias and root mean square error in various radiative properties is small and the deviations in the radiances and irradiances are not statistically significant, i.e. these deviations can be attributed to the Monte Carlo noise of the radiative transfer calculations. We compared these results with optical properties of synthetic clouds that have either the correct distribution (but no spatial correlations) or the correct power spectrum (but a Gaussian distribution). These clouds did show statistical significant deviations. For more information see: http://www.meteo.uni-bonn.de/venema/themes/surrogates/

Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals.

PubMed

Er, Leay-Kiaw; Wu, Semon; Chou, Hsin-Hua; Hsu, Lung-An; Teng, Ming-Sheng; Sun, Yu-Chen; Ko, Yu-Lin

2016-01-01

Insulin resistance (IR) and the consequences of compensatory hyperinsulinemia are pathogenic factors for a set of metabolic abnormalities, which contribute to the development of diabetes mellitus and cardiovascular diseases. We compared traditional lipid levels and ratios and combined them with fasting plasma glucose (FPG) levels or adiposity status for determining their efficiency as independent risk factors for IR. We enrolled 511 Taiwanese individuals for the analysis. The clinical usefulness of various parameters--such as traditional lipid levels and ratios; visceral adiposity indicators, visceral adiposity index (VAI), and lipid accumulation product (LAP); the product of triglyceride (TG) and FPG (the TyG index); TyG with adiposity status (TyG-body mass index [BMI]) and TyG-waist circumference index [WC]); and adipokine levels and ratios--was analyzed to identify IR. For all lipid ratios, the TG/high-density lipoprotein cholesterol (HDL-C) ratio had the highest additional percentage of variation in the homeostasis model assessment of insulin resistance (HOMA-IR; 7.0% in total); for all variables of interest, TyG-BMI and leptin-adiponectin ratio (LAR) were strongly associated with HOMA-IR, with 16.6% and 23.2% of variability, respectively. A logistic regression analysis revealed similar patterns. A receiver operating characteristic (ROC) curve analysis indicated that TG/HDL-C was a more efficient IR discriminator than other lipid variables or ratios. The area under the ROC curve (AUC) for VAI (0.734) and TyG (0.708) was larger than that for TG/HDL-C (0.707). TyG-BMI and LAR had the largest AUC (0.801 and 0.801, respectively). TyG-BMI is a simple, powerful, and clinically useful surrogate marker for early identification of IR.

Triglyceride Glucose-Body Mass Index Is a Simple and Clinically Useful Surrogate Marker for Insulin Resistance in Nondiabetic Individuals

PubMed Central

Er, Leay-Kiaw; Wu, Semon; Chou, Hsin-Hua; Hsu, Lung-An; Teng, Ming-Sheng; Sun, Yu-Chen; Ko, Yu-Lin

2016-01-01

Background Insulin resistance (IR) and the consequences of compensatory hyperinsulinemia are pathogenic factors for a set of metabolic abnormalities, which contribute to the development of diabetes mellitus and cardiovascular diseases. We compared traditional lipid levels and ratios and combined them with fasting plasma glucose (FPG) levels or adiposity status for determining their efficiency as independent risk factors for IR. Methods We enrolled 511 Taiwanese individuals for the analysis. The clinical usefulness of various parameters—such as traditional lipid levels and ratios; visceral adiposity indicators, visceral adiposity index (VAI), and lipid accumulation product (LAP); the product of triglyceride (TG) and FPG (the TyG index); TyG with adiposity status (TyG-body mass index [BMI]) and TyG-waist circumference index [WC]); and adipokine levels and ratios—was analyzed to identify IR. Results For all lipid ratios, the TG/high-density lipoprotein cholesterol (HDL-C) ratio had the highest additional percentage of variation in the homeostasis model assessment of insulin resistance (HOMA-IR; 7.0% in total); for all variables of interest, TyG-BMI and leptin-adiponectin ratio (LAR) were strongly associated with HOMA-IR, with 16.6% and 23.2% of variability, respectively. A logistic regression analysis revealed similar patterns. A receiver operating characteristic (ROC) curve analysis indicated that TG/HDL-C was a more efficient IR discriminator than other lipid variables or ratios. The area under the ROC curve (AUC) for VAI (0.734) and TyG (0.708) was larger than that for TG/HDL-C (0.707). TyG-BMI and LAR had the largest AUC (0.801 and 0.801, respectively). Conclusion TyG-BMI is a simple, powerful, and clinically useful surrogate marker for early identification of IR. PMID:26930652

An Evidence-Based Videotaped Running Biomechanics Analysis.

PubMed

Souza, Richard B

2016-02-01

Running biomechanics play an important role in the development of injuries. Performing a running biomechanics analysis on injured runners can help to develop treatment strategies. This article provides a framework for a systematic video-based running biomechanics analysis plan based on the current evidence on running injuries, using 2-dimensional (2D) video and readily available tools. Fourteen measurements are proposed in this analysis plan from lateral and posterior video. Identifying simple 2D surrogates for 3D biomechanic variables of interest allows for widespread translation of best practices, and have the best opportunity to impact the highly prevalent problem of the injured runner. Copyright © 2016 Elsevier Inc. All rights reserved.

Annual sediment flux estimates in a tidal strait using surrogate measurements

USGS Publications Warehouse

Ganju, N.K.; Schoellhamer, D.H.

2006-01-01

Annual suspended-sediment flux estimates through Carquinez Strait (the seaward boundary of Suisun Bay, California) are provided based on surrogate measurements for advective, dispersive, and Stokes drift flux. The surrogates are landward watershed discharge, suspended-sediment concentration at one location in the Strait, and the longitudinal salinity gradient. The first two surrogates substitute for tidally averaged discharge and velocity-weighted suspended-sediment concentration in the Strait, thereby providing advective flux estimates, while Stokes drift is estimated with suspended-sediment concentration alone. Dispersive flux is estimated using the product of longitudinal salinity gradient and the root-mean-square value of velocity-weighted suspended-sediment concentration as an added surrogate variable. Cross-sectional measurements validated the use of surrogates during the monitoring period. During high freshwater flow advective and dispersive flux were in the seaward direction, while landward dispersive flux dominated and advective flux approached zero during low freshwater flow. Stokes drift flux was consistently in the landward direction. Wetter than average years led to net export from Suisun Bay, while dry years led to net sediment import. Relatively low watershed sediment fluxes to Suisun Bay contribute to net export during the wet season, while gravitational circulation in Carquinez Strait and higher suspended-sediment concentrations in San Pablo Bay (seaward end of Carquinez Strait) are responsible for the net import of sediment during the dry season. Annual predictions of suspended-sediment fluxes, using these methods, will allow for a sediment budget for Suisun Bay, which has implications for marsh restoration and nutrient/contaminant transport. These methods also provide a general framework for estimating sediment fluxes in estuarine environments, where temporal and spatial variability of transport are large. ?? 2006 Elsevier Ltd. All rights reserved.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-01

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

Investigating conflict in ICUs - Is the clinicians’ perspective enough?

PubMed Central

Schuster, Rachel A.; Hong, Seo Yeon; Arnold, Robert M.; White, Douglas B.

2013-01-01

Objective Most studies have assessed conflict between clinicians and surrogate decision makers in ICUs from only clinicians’ perspectives. It is unknown if surrogates’ perceptions differ from clinicians’. We sought to determine the degree of agreement between physicians and surrogates about conflict, and to identify predictors of physician-surrogate conflict. Design Prospective cohort study. Setting Four ICUs of two hospitals in San Francisco, California. Patients 230 surrogate decision makers and 100 physicians of 175 critically ill patients. Measurements Questionnaires addressing participants’ perceptions of whether there was physician-surrogate conflict, as well as attitudes and preferences about clinician-surrogate communication; kappa scores to quantify physician-surrogate concordance about the presence of conflict; and hierarchical multivariate modeling to determine predictors of conflict. Main Results Either the physician or surrogate identified conflict in 63% of cases. Physicians were less likely to perceive conflict than surrogates (27.8% vs 42.3%; p=0.007). Agreement between physicians and surrogates about conflict was poor (kappa = 0.14). Multivariable analysis with surrogate-assessed conflict as the outcome revealed that higher levels of surrogates’ satisfaction with physicians’ bedside manner were associated with lower odds of conflict (OR: 0.75 per 1 point increase in satisfaction, 95% CI 0.59–0.96). Multivariable analysis with physician-assessed conflict as the outcome revealed that the surrogate having felt discriminated against in the healthcare setting was associated with higher odds of conflict (OR 17.5, 95% CI 1.6–190.1) while surrogates’ satisfaction with physicians’ bedside manner was associated with lower odds of conflict (0–10 scale, OR 0.76 per 1 point increase, 95% CI 0.58–0.99). Conclusions Conflict between physicians and surrogates is common in ICUs. There is little agreement between physicians and surrogates about whether physician-surrogate conflict has occurred. Further work is needed to develop reliable and valid methods to assess conflict. In the interim, future studies should assess conflict from the perspective of both clinicians and surrogates. PMID:24434440

A parallel offline CFD and closed-form approximation strategy for computationally efficient analysis of complex fluid flows

NASA Astrophysics Data System (ADS)

Allphin, Devin

Computational fluid dynamics (CFD) solution approximations for complex fluid flow problems have become a common and powerful engineering analysis technique. These tools, though qualitatively useful, remain limited in practice by their underlying inverse relationship between simulation accuracy and overall computational expense. While a great volume of research has focused on remedying these issues inherent to CFD, one traditionally overlooked area of resource reduction for engineering analysis concerns the basic definition and determination of functional relationships for the studied fluid flow variables. This artificial relationship-building technique, called meta-modeling or surrogate/offline approximation, uses design of experiments (DOE) theory to efficiently approximate non-physical coupling between the variables of interest in a fluid flow analysis problem. By mathematically approximating these variables, DOE methods can effectively reduce the required quantity of CFD simulations, freeing computational resources for other analytical focuses. An idealized interpretation of a fluid flow problem can also be employed to create suitably accurate approximations of fluid flow variables for the purposes of engineering analysis. When used in parallel with a meta-modeling approximation, a closed-form approximation can provide useful feedback concerning proper construction, suitability, or even necessity of an offline approximation tool. It also provides a short-circuit pathway for further reducing the overall computational demands of a fluid flow analysis, again freeing resources for otherwise unsuitable resource expenditures. To validate these inferences, a design optimization problem was presented requiring the inexpensive estimation of aerodynamic forces applied to a valve operating on a simulated piston-cylinder heat engine. The determination of these forces was to be found using parallel surrogate and exact approximation methods, thus evidencing the comparative benefits of this technique. For the offline approximation, latin hypercube sampling (LHS) was used for design space filling across four (4) independent design variable degrees of freedom (DOF). Flow solutions at the mapped test sites were converged using STAR-CCM+ with aerodynamic forces from the CFD models then functionally approximated using Kriging interpolation. For the closed-form approximation, the problem was interpreted as an ideal 2-D converging-diverging (C-D) nozzle, where aerodynamic forces were directly mapped by application of the Euler equation solutions for isentropic compression/expansion. A cost-weighting procedure was finally established for creating model-selective discretionary logic, with a synthesized parallel simulation resource summary provided.

Cerebral autoregulation in the preterm newborn using near-infrared spectroscopy: a comparison of time-domain and frequency-domain analyses

NASA Astrophysics Data System (ADS)

Eriksen, Vibeke R.; Hahn, Gitte H.; Greisen, Gorm

2015-03-01

The aim was to compare two conventional methods used to describe cerebral autoregulation (CA): frequency-domain analysis and time-domain analysis. We measured cerebral oxygenation (as a surrogate for cerebral blood flow) and mean arterial blood pressure (MAP) in 60 preterm infants. In the frequency domain, outcome variables were coherence and gain, whereas the cerebral oximetry index (COx) and the regression coefficient were the outcome variables in the time domain. Correlation between coherence and COx was poor. The disagreement between the two methods was due to the MAP and cerebral oxygenation signals being in counterphase in three cases. High gain and high coherence may arise spuriously when cerebral oxygenation decreases as MAP increases; hence, time-domain analysis appears to be a more robust-and simpler-method to describe CA.

Risk estimates for persistent high-risk human papillomavirus infections as surrogate endpoints of progressive cervical disease critically depend on reference category: analysis of the combined prospective cohort of the New Independent States of the Former Soviet Union and Latin American Screening studies.

PubMed

Syrjänen, K; Shabalova, I; Naud, P; Kozachenko, V; Derchain, S; Zakharchenko, S; Roteli-Martins, C; Nerovjna, R; Longatto-Filho, A; Kljukina, L; Tatti, S; Branovskaja, M; Hammes, L S; Branca, M; Grunjberga, V; Eržen, M; Juschenko, A; Costa, S; Sarian, L; Podistov, J; Syrjänen, S

2011-06-01

To make feasible future clinical trials with new-generation human papillomavirus (HPV) vaccines, novel virological surrogate endpoints of progressive disease have been proposed, including high-risk HPV (HR-HPV) persistence for six months (6M+) or 12 months (12M+). The risk estimates (relative risks [RRs]) of these 'virological endpoints' are influenced by several variables, not yet validated adequately. We compared the impact of three referent groups: (i) HPV-negative, (ii) HPV-transient, (iii) HPV-mixed outcome on the risk estimates for 6M+ or 12M+ HR-HPV persistence as predictors of progressive disease. Generalized estimating equation models were used to estimate the strength of 6M+ and 12M+ HR-HPV persistence with disease progression to squamous intraepithelial lesions (SILs), cervical intraepithelial neoplasia (CIN) grade 1+, CIN2+, CIN/SIL endpoints, comparing three optional reference categories (i)-(iii) in a prospective sub-cohort of 1865 women from the combined New Independent States of the Former Soviet Union (NIS) and Latin American Screening (LAMS) studies cohort (n = 15,301). The RRs of these viral endpoints as predictors of progressive disease are affected by the length of viral persistence (6M+ or 12M+) and the surrogate endpoint (SIL, CIN1, CIN2, CIN/SIL). Most dramatic is the effect of the referent group used in risk estimates, with the HPV-negative referent group giving the highest and most consistent RRs for both 6M+ and 12M+ viral persistence, irrespective of which surrogate is used. In addition to deciding on whether to use 6M+ or 12M+ persistence criteria, and cytological, histological or combined surrogate endpoints, one should adopt the HPV-negative referent group as the gold standard in all future studies using viral persistence as the surrogate endpoint of progressive disease.

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

PubMed Central

Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

2015-01-01

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

LVAD patients' and surrogates' perspectives on SPIRIT-HF: An advance care planning discussion.

PubMed

Metzger, Maureen; Song, Mi-Kyung; Devane-Johnson, Stephanie

2016-01-01

To describe LVAD patients' and surrogates' experiences with, and perspectives on SPIRIT-HF, an advance care planning (ACP) intervention. ACP is important for patients with LVAD, yet little is known about their experiences or those of their surrogates who have participated in ACP discussions. We used qualitative content analysis techniques to conduct a secondary analysis of 28 interviews with patients with LVAD (n = 14) and their surrogates (n = 14) who had participated in an RCT pilot study of SPIRIT-HF. Main themes from the data include: 1) sharing their HF stories was very beneficial; 2) participating in SPIRIT-HF led to greater peace of mind for patients and surrogates; 3) "one size does not fit all" when it comes to timing of ACP discussions. An understanding patient and surrogate perspectives may inform clinicians' approach to ACP discussions. Copyright © 2016 Elsevier Inc. All rights reserved.

Religion and Spirituality in Surrogate Decision Making for Hospitalized Older Adults.

PubMed

Geros-Willfond, Kristin N; Ivy, Steven S; Montz, Kianna; Bohan, Sara E; Torke, Alexia M

2016-06-01

We conducted semi-structured interviews with 46 surrogate decision makers for hospitalized older adults to characterize the role of spirituality and religion in decision making. Three themes emerged: (1) religion as a guide to decision making, (2) control, and (3) faith, death and dying. For religious surrogates, religion played a central role in end of life decisions. There was variability regarding whether God or humans were perceived to be in control; however, beliefs about control led to varying perspectives on acceptance of comfort-focused treatment. We conclude that clinicians should attend to religious considerations due to their impact on decision making.

Religion and Spirituality in Surrogate Decision Making for Hospitalized Older Adults

PubMed Central

Geros, Kristin N.; Ivy, Steven S.; Montz, Kianna; Bohan, Sara E.; Torke, Alexia M.

2015-01-01

We conducted semi-structured interviews with 46 surrogate decision makers for hospitalized older adults to characterize the role of spirituality and religion in decision making. Three themes emerged: (1) religion as a guide to decision making, (2) control, and (3) faith, death and dying. For religious surrogates, religion played a central role in end of life decisions. There was variability regarding whether God or humans were perceived to be in control; however beliefs about control led to varying perspectives on acceptance of comfort-focused treatment. We conclude that clinicians should attend to religious considerations due to their impact on decision making. PMID:26337437

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rabiti, Cristian; Alfonsi, Andrea; Huang, Dongli

This report collect the effort performed to improve the reliability analysis capabilities of the RAVEN code and explore new opportunity in the usage of surrogate model by extending the current RAVEN capabilities to multi physics surrogate models and construction of surrogate models for high dimensionality fields.

The intermediate endpoint effect in logistic and probit regression

PubMed Central

MacKinnon, DP; Lockwood, CM; Brown, CH; Wang, W; Hoffman, JM

2010-01-01

Background An intermediate endpoint is hypothesized to be in the middle of the causal sequence relating an independent variable to a dependent variable. The intermediate variable is also called a surrogate or mediating variable and the corresponding effect is called the mediated, surrogate endpoint, or intermediate endpoint effect. Clinical studies are often designed to change an intermediate or surrogate endpoint and through this intermediate change influence the ultimate endpoint. In many intermediate endpoint clinical studies the dependent variable is binary, and logistic or probit regression is used. Purpose The purpose of this study is to describe a limitation of a widely used approach to assessing intermediate endpoint effects and to propose an alternative method, based on products of coefficients, that yields more accurate results. Methods The intermediate endpoint model for a binary outcome is described for a true binary outcome and for a dichotomization of a latent continuous outcome. Plots of true values and a simulation study are used to evaluate the different methods. Results Distorted estimates of the intermediate endpoint effect and incorrect conclusions can result from the application of widely used methods to assess the intermediate endpoint effect. The same problem occurs for the proportion of an effect explained by an intermediate endpoint, which has been suggested as a useful measure for identifying intermediate endpoints. A solution to this problem is given based on the relationship between latent variable modeling and logistic or probit regression. Limitations More complicated intermediate variable models are not addressed in the study, although the methods described in the article can be extended to these more complicated models. Conclusions Researchers are encouraged to use an intermediate endpoint method based on the product of regression coefficients. A common method based on difference in coefficient methods can lead to distorted conclusions regarding the intermediate effect. PMID:17942466

The Different Moral Bases of Patient and Surrogate Decision-Making.

PubMed

Brudney, Daniel

2018-01-01

My topic is a problem with our practice of surrogate decision-making in health care, namely, the problem of the surrogate who is not doing her job-the surrogate who cannot be reached or the surrogate who seems to refuse to understand or to be unable to understand the clinical situation. The analysis raises a question about the surrogate who simply disagrees with the medical team. One might think that such a surrogate is doing her job-the team just doesn't like how she is doing it. My analysis raises the question of whether (or perhaps when) she should be overridden. In approaching this problem, I focus not on the range of difficulties in practice but on the underlying moral conceptual issue. My concern will be to show that the moral values that underpin patient decision-making are fundamentally different from those that underpin surrogate decision-making. Identifying the distinctions will set parameters for any successful solution to the "Who should decide?" A patient has a specific kind of moral right to make her own medical decisions. A surrogate has no analogous moral right to decide for someone else. We want the surrogate to make the decision because we believe that she has a relevant epistemological advantage over anyone else on the scene. If and when she has no such advantage or if she refuses or is unable to use it, then there might not be sufficient reason to let her be the decision-maker. © 2018 The Hastings Center.

Validated surrogate endpoints needed for peri-implantitis.

PubMed

Lee, Dong Won

2011-01-01

Pubmed, Cochrane and Lilac databases, Google, Google Scholar, hand searching of websites of major dental journals. The reference list of five recently published systematic reviews on peri-implantitis treatment were also screened for potential studies. Randomised controlled trials and non-randomised studies in English, German, French, Spanish and Italian on peri-implantitis treatment in humans were included. Case series, case reports and cross sectional or non-therapy studies were excluded from the assessment of endpoints. No minimum follow up time was set for studies that were included. Data were extracted in duplicate by two reviewers and disagreements were resolved by consensus. True endpoints for peri-implantitis treatment were considered only if they provided evidence of tangible benefit to the patient. The outcome variables regarded as true endpoints were implant failure, aesthetic assessment and variables related to quality of life, but these were only considered if they were clearly identified as an objective of the research, not as an outcome of treatment. Surrogate endpoints were considered as those measurements of clinical outcomes such as probing pocket depth and clinical attachment level. Fourteen studies were included in this review with data on implant failure presented solely as consequence of peri-implantitis therapy. No true endpoint was described for any study on peri-implantitis. Mean pocket probing depth, clinical attachment level and bleeding on probing were the three surrogate endpoints cited most often in the literature. All endpoints used in the trials reviewed are surrogates of clinical events, such as implant failure. Clinical surrogate endpoints should be validated to assess the real effect of these measures on true endpoints.

An Evaluation of Fuel-Reduction Treatments Across a Landscape Gradient in Piedmont Forests: Preliminary Results of the National Fire and Fire Surrogate Study

Treesearch

Thomas A. Waldrop; Dallas W. Glass; Sandra Rideout; Victor B. Shelburne

2004-01-01

The National Fire and Fire Surrogate (NFFS) Study is a large-scale study of the impacts of fuel-reduction treatments on ecological and economic variables. This paper examines prescribed burning and thinning as fuel-reduction treatments on one site of the national study, the southeastern Piedmont. Fuel loads were examined across a landscape gradient before and after...

Operationalizing biodiversity for conservation planning.

PubMed

Sarkar, Sahotra; Margules, Chris

2002-07-01

Biodiversity has acquired such a general meaning that people now find it difficult to pin down a precise sense for planning and policy-making aimed at biodiversity conservation. Because biodiversity is rooted in place, the task of conserving biodiversity should target places for conservation action; and because all places contain biodiversity, but not all places can be targeted for action, places have to be prioritized. What is needed for this is a measure of the extent to which biodiversity varies from place to place. We do not need a precise measure of biodiversity to prioritize places. Relative estimates of similarity or difference can be derived using partial measures, or what have come to be called biodiversity surrogates. Biodiversity surrogates are supposed to stand in for general biodiversity in planning applications. We distinguish between true surrogates, those that might truly stand in for general biodiversity, and estimator surrogates, which have true surrogates as their target variable. For example, species richness has traditionally been the estimator surrogate for the true surrogate, species diversity. But species richness does not capture the differences in composition between places; the essence of biodiversity. Another measure, called complementarity, explicitly captures the differences between places as we iterate the process of place prioritization, starting with an initial place. The relative concept of biodiversity built into the definition of complementarity has the level of precision needed to undertake conservation planning.

Prognostic factors versus markers of response to treatment versus surrogate endpoints: Three different concepts.

PubMed

Sormani, Maria Pia

2017-03-01

Multiple sclerosis is a highly heterogeneous disease; the quantitative assessment of disease progression is problematic for many reasons, including the lack of objective methods to measure disability and the long follow-up times needed to detect relevant and stable changes. For these reasons, the importance of prognostic markers, markers of response to treatments and of surrogate endpoints, is crucial in multiple sclerosis research. Aim of this report is to clarify some basic definitions and methodological issues about baseline factors to be considered prognostic markers or markers of response to treatment; to define the dynamic role that variables must have to be considered surrogate markers in relation to specific treatments.

Surrogacy assessment using principal stratification when surrogate and outcome measures are multivariate normal.

PubMed

Conlon, Anna S C; Taylor, Jeremy M G; Elliott, Michael R

2014-04-01

In clinical trials, a surrogate outcome variable (S) can be measured before the outcome of interest (T) and may provide early information regarding the treatment (Z) effect on T. Using the principal surrogacy framework introduced by Frangakis and Rubin (2002. Principal stratification in causal inference. Biometrics 58, 21-29), we consider an approach that has a causal interpretation and develop a Bayesian estimation strategy for surrogate validation when the joint distribution of potential surrogate and outcome measures is multivariate normal. From the joint conditional distribution of the potential outcomes of T, given the potential outcomes of S, we propose surrogacy validation measures from this model. As the model is not fully identifiable from the data, we propose some reasonable prior distributions and assumptions that can be placed on weakly identified parameters to aid in estimation. We explore the relationship between our surrogacy measures and the surrogacy measures proposed by Prentice (1989. Surrogate endpoints in clinical trials: definition and operational criteria. Statistics in Medicine 8, 431-440). The method is applied to data from a macular degeneration study and an ovarian cancer study.

Surrogacy assessment using principal stratification when surrogate and outcome measures are multivariate normal

PubMed Central

Conlon, Anna S. C.; Taylor, Jeremy M. G.; Elliott, Michael R.

2014-01-01

In clinical trials, a surrogate outcome variable (S) can be measured before the outcome of interest (T) and may provide early information regarding the treatment (Z) effect on T. Using the principal surrogacy framework introduced by Frangakis and Rubin (2002. Principal stratification in causal inference. Biometrics 58, 21–29), we consider an approach that has a causal interpretation and develop a Bayesian estimation strategy for surrogate validation when the joint distribution of potential surrogate and outcome measures is multivariate normal. From the joint conditional distribution of the potential outcomes of T, given the potential outcomes of S, we propose surrogacy validation measures from this model. As the model is not fully identifiable from the data, we propose some reasonable prior distributions and assumptions that can be placed on weakly identified parameters to aid in estimation. We explore the relationship between our surrogacy measures and the surrogacy measures proposed by Prentice (1989. Surrogate endpoints in clinical trials: definition and operational criteria. Statistics in Medicine 8, 431–440). The method is applied to data from a macular degeneration study and an ovarian cancer study. PMID:24285772

Shape Optimization by Bayesian-Validated Computer-Simulation Surrogates

NASA Technical Reports Server (NTRS)

Patera, Anthony T.

1997-01-01

A nonparametric-validated, surrogate approach to optimization has been applied to the computational optimization of eddy-promoter heat exchangers and to the experimental optimization of a multielement airfoil. In addition to the baseline surrogate framework, a surrogate-Pareto framework has been applied to the two-criteria, eddy-promoter design problem. The Pareto analysis improves the predictability of the surrogate results, preserves generality, and provides a means to rapidly determine design trade-offs. Significant contributions have been made in the geometric description used for the eddy-promoter inclusions as well as to the surrogate framework itself. A level-set based, geometric description has been developed to define the shape of the eddy-promoter inclusions. The level-set technique allows for topology changes (from single-body,eddy-promoter configurations to two-body configurations) without requiring any additional logic. The continuity of the output responses for input variations that cross the boundary between topologies has been demonstrated. Input-output continuity is required for the straightforward application of surrogate techniques in which simplified, interpolative models are fitted through a construction set of data. The surrogate framework developed previously has been extended in a number of ways. First, the formulation for a general, two-output, two-performance metric problem is presented. Surrogates are constructed and validated for the outputs. The performance metrics can be functions of both outputs, as well as explicitly of the inputs, and serve to characterize the design preferences. By segregating the outputs and the performance metrics, an additional level of flexibility is provided to the designer. The validated outputs can be used in future design studies and the error estimates provided by the output validation step still apply, and require no additional appeals to the expensive analysis. Second, a candidate-based a posteriori error analysis capability has been developed which provides probabilistic error estimates on the true performance for a design randomly selected near the surrogate-predicted optimal design.

Incorporation of Fixed Installation Costs into Optimization of Groundwater Remediation with a New Efficient Surrogate Nonlinear Mixed Integer Optimization Algorithm

NASA Astrophysics Data System (ADS)

Shoemaker, Christine; Wan, Ying

2016-04-01

Optimization of nonlinear water resources management issues which have a mixture of fixed (e.g. construction cost for a well) and variable (e.g. cost per gallon of water pumped) costs has been not well addressed because prior algorithms for the resulting nonlinear mixed integer problems have required many groundwater simulations (with different configurations of decision variable), especially when the solution space is multimodal. In particular heuristic methods like genetic algorithms have often been used in the water resources area, but they require so many groundwater simulations that only small systems have been solved. Hence there is a need to have a method that reduces the number of expensive groundwater simulations. A recently published algorithm for nonlinear mixed integer programming using surrogates was shown in this study to greatly reduce the computational effort for obtaining accurate answers to problems involving fixed costs for well construction as well as variable costs for pumping because of a substantial reduction in the number of groundwater simulations required to obtain an accurate answer. Results are presented for a US EPA hazardous waste site. The nonlinear mixed integer surrogate algorithm is general and can be used on other problems arising in hydrology with open source codes in Matlab and python ("pySOT" in Bitbucket).

Queue position in the endoscopic schedule impacts effectiveness of colonoscopy.

PubMed

Lee, Alexander; Iskander, John M; Gupta, Nitin; Borg, Brian B; Zuckerman, Gary; Banerjee, Bhaskar; Gyawali, C Prakash

2011-08-01

Endoscopist fatigue potentially impacts colonoscopy. Fatigue is difficult to quantitate, but polyp detection rates between non-fatigued and fatigued time periods could represent a surrogate marker. We assessed whether timing variables impacted polyp detection rates at a busy tertiary care endoscopy suite. Consecutive patients undergoing colonoscopy were retrospectively identified. Indications, clinical demographics, pre-procedural, and procedural variables were extracted from chart review; colonoscopy findings were determined from the procedure reports. Three separate timing variables were assessed as surrogate markers for endoscopist fatigue: morning vs. afternoon procedures, start times throughout the day, and queue position, a unique variable that takes into account the number of procedures performed before the colonoscopy of interest. Univariate and multivariate analyses were performed to determine whether timing variables and other clinical, pre-procedural, and procedural variables predicted polyp detection. During the 4-month study period, 1,083 outpatient colonoscopy procedures (57.5±0.5 years, 59.5% female) were identified, performed by 28 endoscopists (mean 38.7 procedures/endoscopist), with a mean polyp detection rate of 0.851/colonoscopy. At least, one adenoma was detected in 297 procedures (27.4%). A 12.4% reduction in mean detected polyps was detected between morning and afternoon procedures (0.90±0.06 vs. 0.76±0.06, P=0.15). Using start time on a continuous scale, however, each elapsed hour in the day was associated with a 4.6% reduction in polyp detection (P=0.005). When queue position was assessed, a 5.4% reduction in polyp detection was noted with each increase in queue position (P=0.016). These results remained significant when controlled for each individual endoscopist. Polyp detection rates decline as time passes during an endoscopist's schedule, potentially from endoscopist fatigue. Queue position may be a novel surrogate measure for operator fatigue.

Variable reliability of surrogate measures of insulin sensitivity after Roux-en-Y gastric bypass.

PubMed

Bojsen-Møller, Kirstine N; Dirksen, Carsten; Svane, Maria S; Jørgensen, Nils B; Holst, Jens J; Richter, Erik A; Madsbad, Sten

2017-05-01

Roux-en-Y gastric bypass (RYGB) induces weight loss and improves insulin sensitivity when evaluated by the hyperinsulinemic-euglycemic clamp (HEC). Surrogate indices of insulin sensitivity calculated from insulin and glucose concentrations at fasting or after an oral glucose tolerance test (OGTT) are frequently used, but have not been validated after RYGB. Our aim was to evaluate whether surrogate indices reliably estimate changes in insulin sensitivity after RYGB. Four fasting surrogates (inverse-HOMA-IR, HOMA2-%S, QUICKI, revised-QUICKI) and three OGTT-derived surrogates (Matsuda, Gutt, OGIS) were compared with HEC-estimated peripheral insulin sensitivity ( R d or R d /I, depending on how the index was originally validated) and the tracer-determined hepatic insulin sensitivity index (HISI) in patients with preoperative type 2 diabetes ( n = 10) and normal glucose tolerance ( n = 10) 1 wk, 3 mo, and 1 yr postoperatively. Post-RYGB changes in inverse-HOMA-IR and HOMA2-%S did not correlate with changes in R d at any visit, but were comparable to changes in HISI at 1 wk. Changes in QUICKI and revised-QUICKI correlated with R d /I after surgery. Changes in the Matsuda and Gutt indices did not correlate with changes in R d /I and R d , respectively, whereas OGIS changes correlated with R d changes at 1 yr post-RYGB. In conclusion, surrogate measures of insulin sensitivity may not reflect results obtained with gold standard methodology after RYGB, underscoring the importance of critical reflection when surrogate endpoints are used. Fasting surrogate indices may be particularly affected by post-RYGB changes in insulin clearance, whereas the validity of OGTT-derived surrogates may be compromised by surgical rearrangements of the gut. Copyright © 2017 the American Physiological Society.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE PAGES

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-27

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

Family involvement in decision making for people with dementia in residential aged care: a systematic review of quantitative literature.

PubMed

Petriwskyj, Andrea; Gibson, Alexandra; Parker, Deborah; Banks, Susan; Andrews, Sharon; Robinson, Andrew

2014-06-01

Ensuring older adults' involvement in their care is accepted as good practice and is vital, particularly for people with dementia, whose care and treatment needs change considerably over the course of the illness. However, involving family members in decision making on people's behalf is still practically difficult for staff and family. The aim of this review was to identify and appraise the existing quantitative evidence about family involvement in decision making for people with dementia living in residential aged care. The present Joanna Briggs Institute (JBI) metasynthesis assessed studies that investigated involvement of family members in decision making for people with dementia in residential aged care settings. While quantitative and qualitative studies were included in the review, this paper presents the quantitative findings. A comprehensive search of 15 electronic databases was performed. The search was limited to papers published in English, from 1990 to 2013. Twenty-six studies were identified as being relevant; 10 were quantitative, with 1 mixed method study. Two independent reviewers assessed the studies for methodological validity and extracted the data using the JBI Meta Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI). The findings were synthesized and presented in narrative form. The findings related to decisions encountered and made by family surrogates, variables associated with decisions, surrogates' perceptions of, and preferences for, their roles, as well as outcomes for people with dementia and their families. The results identified patterns within, and variables associated with, surrogate decision making, all of which highlight the complexity and variation regarding family involvement. Attention needs to be paid to supporting family members in decision making in collaboration with staff.

Improving Mixed Variable Optimization of Computational and Model Parameters Using Multiple Surrogate Functions

DTIC Science & Technology

2008-03-01

multiplicative corrections as well as space mapping transformations for models defined over a lower dimensional space. A corrected surrogate model for the...correction functions used in [72]. If the low fidelity model g(x̃) is defined over a lower dimensional space then a space mapping transformation is...required. As defined in [21, 72], space mapping is a method of mapping between models of different dimensionality or fidelity. Let P denote the space

Metabolic markers and ALT cutoff level for diagnosing nonalcoholic fatty liver disease: a community-based cross-sectional study.

PubMed

Miyake, Teruki; Kumagi, Teru; Hirooka, Masashi; Koizumi, Mitsuhito; Furukawa, Shinya; Ueda, Teruhisa; Tokumoto, Yoshio; Ikeda, Yoshio; Abe, Masanori; Kitai, Kohichiro; Hiasa, Yoichi; Matsuura, Bunzo; Onji, Morikazu

2012-06-01

Untreated nonalcoholic fatty liver disease (NAFLD) may progress to liver cirrhosis or failure and is associated with the development of hepatocellular carcinoma, diabetes, and cardiovascular disease. It is therefore essential to diagnose and treat NAFLD at an early stage. To assist in this effort, this retrospective study explored the risk factors for NAFLD, and derived new surrogates, a revised alanine aminotransferase (ALT) cutoff level and a novel NAFLD index, to identify previously undiagnosed cases of NAFLD. Using a community-based, cross-sectional design, the records of 6,370 Japanese subjects who had undergone at least 1 annual health check-up were reviewed for the identification of subjects meeting the diagnostic criteria for NAFLD and the variables associated with NAFLD for the estimation of ideal ALT cutoff levels. The results of multivariate analysis of the 1,346 subjects who met the diagnostic criteria for NAFLD confirmed that metabolic disease markers and a novel NAFLD index, using the variables derived from multivariate analysis, were also markers of NAFLD. The ALT cutoff levels for NAFLD diagnosis were estimated at 25 U/L for males and 17 U/L for females. ALT level and the novel NAFLD index were confirmed to be surrogate markers for NAFLD in addition to metabolic disease markers. The ALT cutoff level used in NAFLD diagnosis should be revised downward to identify subjects at risk of NAFLD to prevent NAFLD progression and the development of associated diseases.

Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models

NASA Astrophysics Data System (ADS)

Koziel, Slawomir; Bekasiewicz, Adrian

2016-10-01

Multi-objective optimization of antenna structures is a challenging task owing to the high computational cost of evaluating the design objectives as well as the large number of adjustable parameters. Design speed-up can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation models and design refinement methods permits identification of the Pareto-optimal set of designs within a reasonable timeframe. Here, a study concerning the scalability of surrogate-assisted multi-objective antenna design is carried out based on a set of benchmark problems, with the dimensionality of the design space ranging from six to 24 and a CPU cost of the EM antenna model from 10 to 20 min per simulation. Numerical results indicate that the computational overhead of the design process increases more or less quadratically with the number of adjustable geometric parameters of the antenna structure at hand, which is a promising result from the point of view of handling even more complex problems.

Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Congedo, Pietro M.; Abgrall, Rémi

2016-06-01

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable for real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.

Creation of an Upper Stage Trajectory Capability Boundary to Enable Booster System Trade Space Exploration

NASA Technical Reports Server (NTRS)

Walsh, Ptrick; Coulon, Adam; Edwards, Stephen; Mavris, Dimitri N.

2012-01-01

The problem of trajectory optimization is important in all space missions. The solution of this problem enables one to specify the optimum thrust steering program which should be followed to achieve a specified mission objective, simultaneously satisfying the constraints.1 It is well known that whether or not the ascent trajectory is optimal can have a significant impact on propellant usage for a given payload, or on payload weight for the same gross vehicle weight.2 Consequently, ascent guidance commands are usually optimized in some fashion. Multi-stage vehicles add complexity to this analysis process as changes in vehicle properties in one stage propagate to the other stages through gear ratios and changes in the optimal trajectory. These effects can cause an increase in analysis time as more variables are added and convergence of the optimizer to system closure requires more analysis iterations. In this paper, an approach to simplifying this multi-stage problem through the creation of an upper stage capability boundary is presented. This work was completed as part of a larger study focused on trade space exploration for the advanced booster system that will eventually form a part of NASA s new Space Launch System.3 The approach developed leverages Design of Experiments and Surrogate Modeling4 techniques to create a predictive model of the SLS upper stage performance. The design of the SLS core stages is considered fixed for the purposes of this study, which results in trajectory parameters such as staging conditions being the only variables relevant to the upper stage. Through the creation of a surrogate model, which takes staging conditions as inputs and predicts the payload mass delivered by the SLS upper stage to a reference orbit as the response, it is possible to identify a "surface" of staging conditions which all satisfy the SLS requirement of placing 130 metric tons into low-Earth orbit (LEO).3 This identified surface represents the 130 metric ton capability boundary for the upper stage, such that if the combined first stage and boosters can achieve any one staging point on that surface, then the design is identified as feasible. With the surrogate model created, design and analysis of advanced booster concepts is streamlined, as optimization of the upper stage trajectory is no longer required in every design loop.

Pathologic complete response and disease-free survival are not surrogate endpoints for 5-year survival in rectal cancer: an analysis of 22 randomized trials.

PubMed

Petrelli, Fausto; Borgonovo, Karen; Cabiddu, Mary; Ghilardi, Mara; Lonati, Veronica; Barni, Sandro

2017-02-01

We performed a literature-based analysis of randomized clinical trials to assess the pathologic complete response (pCR) (ypT0N0 after neoadjuvant therapy) and 3-year disease-free survival (DFS) as potential surrogate endpoints for 5-year overall survival (OS) in rectal cancer treated with neoadjuvant (chemo)radiotherapy (CT)RT. A systematic literature search of PubMed, EMBASE, the Web of Science, SCOPUS, CINAHL, and the Cochrane Library was performed. Treatment effects on 3-year DFS and 5-year OS were expressed as rates of patients alive (%), and those on pCR as differences in pCR rates (∆ pCR% ). A weighted regression analysis was performed at individual- and trial-level to test the association between treatment effects on surrogate (∆ pCR% and ∆ 3yDFS ) and the main clinical outcome (∆ 5yOS ). Twenty-two trials involving 10,050 patients, were included in the analysis. The individual level surrogacy showed that the pCR% and 3-year DFS were poorly correlated with 5-year OS (R=0.52; 95% CI, 0.31-0.91; P=0.002; and R=0.60; 95% CI, 0.36-1; P=0.002). The trial-level surrogacy analysis confirmed that the two treatment effects on surrogates (∆ pCR% and ∆ 3yDFS ) are not strong surrogates for treatment effects on 5-year OS % (R=0.2; 95% CI, -0.29-0.78; P=0.5 and R=0.64; 95% CI, 0.29-1; P=0.06). These findings were confirmed in neoadjuvant CTRT studies but not in phase III trials were 3-year DFS could still represent a valid surrogate. This analysis does not support the use of pCR and 3-year DFS% as appropriate surrogate endpoints for 5-year OS% in patients with rectal cancer treated with neoadjuvant therapy.

Active subspace uncertainty quantification for a polydomain ferroelectric phase-field model

NASA Astrophysics Data System (ADS)

Leon, Lider S.; Smith, Ralph C.; Miles, Paul; Oates, William S.

2018-03-01

Quantum-informed ferroelectric phase field models capable of predicting material behavior, are necessary for facilitating the development and production of many adaptive structures and intelligent systems. Uncertainty is present in these models, given the quantum scale at which calculations take place. A necessary analysis is to determine how the uncertainty in the response can be attributed to the uncertainty in the model inputs or parameters. A second analysis is to identify active subspaces within the original parameter space, which quantify directions in which the model response varies most dominantly, thus reducing sampling effort and computational cost. In this investigation, we identify an active subspace for a poly-domain ferroelectric phase-field model. Using the active variables as our independent variables, we then construct a surrogate model and perform Bayesian inference. Once we quantify the uncertainties in the active variables, we obtain uncertainties for the original parameters via an inverse mapping. The analysis provides insight into how active subspace methodologies can be used to reduce computational power needed to perform Bayesian inference on model parameters informed by experimental or simulated data.

SURROGATE TISSUE ANALYSIS: MONITORING TOXICANT EXPOSURE AND HEALTH STATUS OF INACCESSIBLE TISSUES THROUGH THE ANALYSIS OF ACCESSIBLE TISSUES AND CELLS

EPA Science Inventory

Surrogate Tissue Analysis: Monitoring Toxicant Exposure And Health Status Of Inaccessible Tissues Through The Analysis Of Accessible Tissues And Cells*
John C. Rockett1, Michael E. Burczynski 2, Albert J. Fornace, Jr.3, Paul.C. Herrmann4, Stephen A. Krawetz5, and David J. Dix1...

Shape-optimization of round-to-slot holes for improving film cooling effectiveness on a flat surface

NASA Astrophysics Data System (ADS)

Huang, Ying; Zhang, Jing-zhou; Wang, Chun-hua

2018-01-01

Single-objective optimization for improving adiabatic film cooling effectiveness is performed for single row of round-to-slot film cooling holes on a flat surface by using CFD analysis and surrogate approximation methods. Among the main geometric parameters, dimensionless hole-to-hole pitch (P/d) and slot length-to-diameter (l/d) are fixed as 2.4 and 2 respectively, and the other parameters (hole height-to-diameter ratio, slot width-to-diameter and inclination angle) are chosen as the design variables. Given a wide range of possible geometric variables, the geometric optimization of round-to-slot holes is carried out under two typical blowing ratios of M = 0.5 and M = 1.5 by selecting a spatially-averaged adiabatic film cooling effectiveness between x/d = 2 and x/d = 12 as the objective function to be maximized. Radial basis function neural network is applied for constructing the surrogate model and then the optimal design point is searched by a genetic algorithm. It is revealed that the optimal round-to-slot hole is of converging feature under a low blowing ratio but of diffusing feature under a high blowing ratio. Further, the influence principle of optimal round-to-slot geometry on film cooling performance is illustrated according to the detailed flow and thermal behaviors.

Gender-dependence of substituted judgment on quality of life in patients with dementia

PubMed Central

2011-01-01

Background Substituted judgment asks the proxy to decide what the patient would have decided, had he or she been competent. It is unclear whether substituted judgment of the patient's quality of life can serve as a surrogate measure in patients with dementia. Methods 212 patients with dementia and their proxies were interviewed in their homes. Dementia syndrome was characterized with cognitive, non-cognitive and functional scales. Quality of life (QoL) was assessed with the QoL-AD. Results Substituted judgment of the patient's QoL was unrelated to dementia severity but also correlated with the proxie's own QoL (r = 0.356; p < 0.001). Gender-specific analysis reveals that for male proxies the most important variable is severity of patient's depression (r = -0.895; p = 0.001) while for female proxies it is the proxie's own QoL (r = 0.371; p < 0.001). Subjective burden correlates with the proxie's QoL in females (r = -0.282; p = 0.001) but not in males (r = -0.163, p = 0.161). Conclusion Substituted judgment of the patient's QoL does not correlate with dementia severity. Substituted judgment is subject to proxy-related variables in a gender-dependent fashion and therefore not suited to serve as an appropriate surrogate of the patients' quality of life. PMID:21961477

Shape-optimization of round-to-slot holes for improving film cooling effectiveness on a flat surface

NASA Astrophysics Data System (ADS)

Huang, Ying; Zhang, Jing-zhou; Wang, Chun-hua

2018-06-01

Single-objective optimization for improving adiabatic film cooling effectiveness is performed for single row of round-to-slot film cooling holes on a flat surface by using CFD analysis and surrogate approximation methods. Among the main geometric parameters, dimensionless hole-to-hole pitch ( P/ d) and slot length-to-diameter ( l/ d) are fixed as 2.4 and 2 respectively, and the other parameters (hole height-to-diameter ratio, slot width-to-diameter and inclination angle) are chosen as the design variables. Given a wide range of possible geometric variables, the geometric optimization of round-to-slot holes is carried out under two typical blowing ratios of M = 0.5 and M = 1.5 by selecting a spatially-averaged adiabatic film cooling effectiveness between x/ d = 2 and x/ d = 12 as the objective function to be maximized. Radial basis function neural network is applied for constructing the surrogate model and then the optimal design point is searched by a genetic algorithm. It is revealed that the optimal round-to-slot hole is of converging feature under a low blowing ratio but of diffusing feature under a high blowing ratio. Further, the influence principle of optimal round-to-slot geometry on film cooling performance is illustrated according to the detailed flow and thermal behaviors.

Advance Care Planning Beyond Advance Directives: Perspectives from Patients and Surrogates

PubMed Central

McMahan, Ryan; Knight, Sara J.; Fried, Terri R.; Sudore, Rebecca L.

2014-01-01

Context Advance care planning (ACP) has focused on documenting life-sustaining treatment preferences in advance directives (ADs). ADs alone may be insufficient to prepare diverse patients and surrogates for complex medical decisions. Objectives To understand what steps best prepare patients and surrogates for decision making. Methods We conducted 13 English/Spanish focus groups with participants from a Veterans Affairs and county hospital and the community. Seven groups included patients (n=38) aged ≥65 years, who reported making serious medical decisions. Six separate groups included surrogates (n=31), aged ≥18 years, who made decisions for others. Semi-structured focus groups asked what activities best prepared participants for decision making. Two investigators independently coded data and performed thematic content analysis. Disputes were resolved by consensus. Results Mean±SD patient age was 78±8 years and 61% were non-white. Mean±SD surrogate age was 57±10 years and 91% were non-white. Qualitative analysis identified four overarching themes about how to best prepare for decision making: 1) identify values based on past experiences and quality of life, 2) choose surrogates wisely and verify they understand their role, 3) decide whether to grant leeway in surrogate decision making, and 4) inform other family and friends of one's wishes to prevent conflict. Conclusion Beyond ADs, patients and surrogates recommend several additional steps to prepare for medical decision making including using past experiences to identify values, verifying the surrogate understands their role, deciding whether to grant surrogates leeway, and informing other family and friends of one's wishes. Future ACP interventions should consider incorporating these additional ACP activities. PMID:23200188

Overcoming complexities: Damage detection using dictionary learning framework

NASA Astrophysics Data System (ADS)

Alguri, K. Supreet; Melville, Joseph; Deemer, Chris; Harley, Joel B.

2018-04-01

For in situ damage detection, guided wave structural health monitoring systems have been widely researched due to their ability to evaluate large areas and their ability detect many types of damage. These systems often evaluate structural health by recording initial baseline measurements from a pristine (i.e., undamaged) test structure and then comparing later measurements with that baseline. Yet, it is not always feasible to have a pristine baseline. As an alternative, substituting the baseline with data from a surrogate (nearly identical and pristine) structure is a logical option. While effective in some circumstance, surrogate data is often still a poor substitute for pristine baseline measurements due to minor differences between the structures. To overcome this challenge, we present a dictionary learning framework to adapt surrogate baseline data to better represent an undamaged test structure. We compare the performance of our framework with two other surrogate-based damage detection strategies: (1) using raw surrogate data for comparison and (2) using sparse wavenumber analysis, a precursor to our framework for improving the surrogate data. We apply our framework to guided wave data from two 108 mm by 108 mm aluminum plates. With 20 measurements, we show that our dictionary learning framework achieves a 98% accuracy, raw surrogate data achieves a 92% accuracy, and sparse wavenumber analysis achieves a 57% accuracy.

A surrogate model for thermal characteristics of stratospheric airship

NASA Astrophysics Data System (ADS)

Zhao, Da; Liu, Dongxu; Zhu, Ming

2018-06-01

A simple and accurate surrogate model is extremely needed to reduce the analysis complexity of thermal characteristics for a stratospheric airship. In this paper, a surrogate model based on the Least Squares Support Vector Regression (LSSVR) is proposed. The Gravitational Search Algorithm (GSA) is used to optimize hyper parameters. A novel framework consisting of a preprocessing classifier and two regression models is designed to train the surrogate model. Various temperature datasets of the airship envelope and the internal gas are obtained by a three-dimensional transient model for thermal characteristics. Using these thermal datasets, two-factor and multi-factor surrogate models are trained and several comparison simulations are conducted. Results illustrate that the surrogate models based on LSSVR-GSA have good fitting and generalization abilities. The pre-treated classification strategy proposed in this paper plays a significant role in improving the accuracy of the surrogate model.

Statistical controversies in clinical research: an initial evaluation of a surrogate end point using a single randomized clinical trial and the Prentice criteria

PubMed Central

Heller, G.

2015-01-01

Surrogate end point research has grown in recent years with the increasing development and usage of biomarkers in clinical research. Surrogacy analysis is derived through randomized clinical trial data and it is carried out at the individual level and at the trial level. A common surrogate analysis at the individual level is the application of the Prentice criteria. An approach for the evaluation of the Prentice criteria is discussed, with a focus on its most difficult component, the determination of whether the treatment effect is captured by the surrogate. An interpretation of this criterion is illustrated using data from a randomized clinical trial in prostate cancer. PMID:26254442

The value of surrogate endpoints for predicting real-world survival across five cancer types.

PubMed

Shafrin, Jason; Brookmeyer, Ron; Peneva, Desi; Park, Jinhee; Zhang, Jie; Figlin, Robert A; Lakdawalla, Darius N

2016-01-01

It is unclear how well different outcome measures in randomized controlled trials (RCTs) perform in predicting real-world cancer survival. We assess the ability of RCT overall survival (OS) and surrogate endpoints - progression-free survival (PFS) and time to progression (TTP) - to predict real-world OS across five cancers. We identified 20 treatments and 31 indications for breast, colorectal, lung, ovarian, and pancreatic cancer that had a phase III RCT reporting median OS and median PFS or TTP. Median real-world OS was determined using a Kaplan-Meier estimator applied to patients in the Surveillance and Epidemiology End Results (SEER)-Medicare database (1991-2010). Performance of RCT OS and PFS/TTP in predicting real-world OS was measured using t-tests, median absolute prediction error, and R(2) from linear regressions. Among 72,600 SEER-Medicare patients similar to RCT participants, median survival was 5.9 months for trial surrogates, 14.1 months for trial OS, and 13.4 months for real-world OS. For this sample, regression models using clinical trial OS and trial surrogates as independent variables predicted real-world OS significantly better than models using surrogates alone (P = 0.026). Among all real-world patients using sample treatments (N = 309,182), however, adding trial OS did not improve predictive power over predictions based on surrogates alone (P = 0.194). Results were qualitatively similar using median absolute prediction error and R(2) metrics. Among the five tumor types investigated, trial OS and surrogates were each independently valuable in predicting real-world OS outcomes for patients similar to trial participants. In broader real-world populations, however, trial OS added little incremental value over surrogates alone.

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

PubMed

Bujkiewicz, Sylwia; Thompson, John R; Riley, Richard D; Abrams, Keith R

2016-03-30

A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between-study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between-study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual-level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

GENOMIC AND PROTEOMIC ANALYSIS OF SURROGATE TISSUES FOR ASSESSING TOXIC EXPOSURES AND DISEASE STATES

EPA Science Inventory

Genomic and Proteomic Analysis of Surrogate Tissues for Assessing Toxic Exposures and Disease States
David J. Dix and John C. Rockett
Reproductive Toxicology Division, National Health and Environmental Effects Research Laboratory, Office of Research and Development, USEPA, ...

Conceptualizing surrogate decision making at end of life in the intensive care unit using cognitive task analysis.

PubMed

Dionne-Odom, J Nicholas; Willis, Danny G; Bakitas, Marie; Crandall, Beth; Grace, Pamela J

2015-01-01

Surrogate decision makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. To identify and describe the underlying psychological processes of surrogate decision making for adults at EOL in the ICU. Qualitative case study design using a cognitive task analysis interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center's ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semistructured cognitive task analysis interviews. The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions (gist impressions, distressing emotions, and moral intuitions) impact an SDM's judgment about the acceptability of either the patient's medical treatments or his or her condition. The framework offers initial insights about the underlying psychological processes of surrogate decision making and may facilitate enhanced decision support for SDMs. Copyright © 2015 Elsevier Inc. All rights reserved.

Recurrence network measures for hypothesis testing using surrogate data: Application to black hole light curves

NASA Astrophysics Data System (ADS)

Jacob, Rinku; Harikrishnan, K. P.; Misra, R.; Ambika, G.

2018-01-01

Recurrence networks and the associated statistical measures have become important tools in the analysis of time series data. In this work, we test how effective the recurrence network measures are in analyzing real world data involving two main types of noise, white noise and colored noise. We use two prominent network measures as discriminating statistic for hypothesis testing using surrogate data for a specific null hypothesis that the data is derived from a linear stochastic process. We show that the characteristic path length is especially efficient as a discriminating measure with the conclusions reasonably accurate even with limited number of data points in the time series. We also highlight an additional advantage of the network approach in identifying the dimensionality of the system underlying the time series through a convergence measure derived from the probability distribution of the local clustering coefficients. As examples of real world data, we use the light curves from a prominent black hole system and show that a combined analysis using three primary network measures can provide vital information regarding the nature of temporal variability of light curves from different spectroscopic classes.

A formal and data-based comparison of measures of motor-equivalent covariation.

PubMed

Verrel, Julius

2011-09-15

Different analysis methods have been developed for assessing motor-equivalent organization of movement variability. In the uncontrolled manifold (UCM) method, the structure of variability is analyzed by comparing goal-equivalent and non-goal-equivalent variability components at the level of elemental variables (e.g., joint angles). In contrast, in the covariation by randomization (CR) approach, motor-equivalent organization is assessed by comparing variability at the task level between empirical and decorrelated surrogate data. UCM effects can be due to both covariation among elemental variables and selective channeling of variability to elemental variables with low task sensitivity ("individual variation"), suggesting a link between the UCM and CR method. However, the precise relationship between the notion of covariation in the two approaches has not been analyzed in detail yet. Analysis of empirical and simulated data from a study on manual pointing shows that in general the two approaches are not equivalent, but the respective covariation measures are highly correlated (ρ > 0.7) for two proposed definitions of covariation in the UCM context. For one-dimensional task spaces, a formal comparison is possible and in fact the two notions of covariation are equivalent. In situations in which individual variation does not contribute to UCM effects, for which necessary and sufficient conditions are derived, this entails the equivalence of the UCM and CR analysis. Implications for the interpretation of UCM effects are discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

A new proportion measure of the treatment effect captured by candidate surrogate endpoints.

PubMed

Kobayashi, Fumiaki; Kuroki, Manabu

2014-08-30

The use of surrogate endpoints is expected to play an important role in the development of new drugs, as they can be used to reduce the sample size and/or duration of randomized clinical trials. Biostatistical researchers and practitioners have proposed various surrogacy measures; however, (i) most of these surrogacy measures often fall outside the range [0,1] without any assumptions, (ii) these surrogacy measures do not provide a cut-off value for judging a surrogacy level of candidate surrogate endpoints, and (iii) most surrogacy measures are highly variable; thus, the confidence intervals are often unacceptably wide. In order to solve problems (i) and (ii), we propose a new surrogacy measure, a proportion of the treatment effect captured by candidate surrogate endpoints (PCS), on the basis of the decomposition of the treatment effect into parts captured and non-captured by the candidate surrogate endpoints. In order to solve problem (iii), we propose an estimation method based on the half-range mode method with the bootstrap distribution of the estimated surrogacy measures. Finally, through numerical experiments and two empirical examples, we show that the PCS with the proposed estimation method overcomes these difficulties. The results of this paper contribute to the reliable evaluation of how much of the treatment effect is captured by candidate surrogate endpoints. Copyright © 2014 John Wiley & Sons, Ltd.

Surviving Surrogate Decision-Making: What Helps and Hampers the Experience of Making Medical Decisions for Others

PubMed Central

Starks, Helene; Taylor, Janelle S.; Hopley, Elizabeth K.; Fryer-Edwards, Kelly

2007-01-01

BACKGROUND A majority of end-of-life medical decisions are made by surrogate decision-makers who have varying degrees of preparation and comfort with their role. Having a seriously ill family member is stressful for surrogates. Moreover, most clinicians have had little training in working effectively with surrogates. OBJECTIVES To better understand the challenges of decision-making from the surrogate’s perspective. DESIGN Semistructured telephone interview study of the experience of surrogate decision-making. PARTICIPANTS Fifty designated surrogates with previous decision-making experience. APPROACH We asked surrogates to describe and reflect on their experience of making medical decisions for others. After coding transcripts, we conducted a content analysis to identify and categorize factors that made decision-making more or less difficult for surrogates. RESULTS Surrogates identified four types of factors: (1) surrogate characteristics and life circumstances (such as coping strategies and competing responsibilities), (2) surrogates’ social networks (such as intrafamily discord about the “right” decision), (3) surrogate–patient relationships and communication (such as difficulties with honoring known preferences), and (4) surrogate–clinician communication and relationship (such as interacting with a single physician whom the surrogate recognizes as the clinical spokesperson vs. many clinicians). CONCLUSIONS These data provide insights into the challenges that surrogates encounter when making decisions for loved ones and indicate areas where clinicians could intervene to facilitate the process of surrogate decision-making. Clinicians may want to include surrogates in advance care planning prior to decision-making, identify and address surrogate stressors during decision-making, and designate one person to communicate information about the patient’s condition, prognosis, and treatment options. PMID:17619223

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Jiangjiang; Li, Weixuan; Lin, Guang

In decision-making for groundwater management and contamination remediation, it is important to accurately evaluate the probability of the occurrence of a failure event. For small failure probability analysis, a large number of model evaluations are needed in the Monte Carlo (MC) simulation, which is impractical for CPU-demanding models. One approach to alleviate the computational cost caused by the model evaluations is to construct a computationally inexpensive surrogate model instead. However, using a surrogate approximation can cause an extra error in the failure probability analysis. Moreover, constructing accurate surrogates is challenging for high-dimensional models, i.e., models containing many uncertain input parameters.more » To address these issues, we propose an efficient two-stage MC approach for small failure probability analysis in high-dimensional groundwater contaminant transport modeling. In the first stage, a low-dimensional representation of the original high-dimensional model is sought with Karhunen–Loève expansion and sliced inverse regression jointly, which allows for the easy construction of a surrogate with polynomial chaos expansion. Then a surrogate-based MC simulation is implemented. In the second stage, the small number of samples that are close to the failure boundary are re-evaluated with the original model, which corrects the bias introduced by the surrogate approximation. The proposed approach is tested with a numerical case study and is shown to be 100 times faster than the traditional MC approach in achieving the same level of estimation accuracy.« less

Statistical Surrogate Modeling of Atmospheric Dispersion Events Using Bayesian Adaptive Splines

NASA Astrophysics Data System (ADS)

Francom, D.; Sansó, B.; Bulaevskaya, V.; Lucas, D. D.

2016-12-01

Uncertainty in the inputs of complex computer models, including atmospheric dispersion and transport codes, is often assessed via statistical surrogate models. Surrogate models are computationally efficient statistical approximations of expensive computer models that enable uncertainty analysis. We introduce Bayesian adaptive spline methods for producing surrogate models that capture the major spatiotemporal patterns of the parent model, while satisfying all the necessities of flexibility, accuracy and computational feasibility. We present novel methodological and computational approaches motivated by a controlled atmospheric tracer release experiment conducted at the Diablo Canyon nuclear power plant in California. Traditional methods for building statistical surrogate models often do not scale well to experiments with large amounts of data. Our approach is well suited to experiments involving large numbers of model inputs, large numbers of simulations, and functional output for each simulation. Our approach allows us to perform global sensitivity analysis with ease. We also present an approach to calibration of simulators using field data.

Identifying family members who may struggle in the role of surrogate decision maker.

PubMed

Majesko, Alyssa; Hong, Seo Yeon; Weissfeld, Lisa; White, Douglas B

2012-08-01

Although acting as a surrogate decision maker can be highly distressing for some family members of intensive care unit patients, little is known about whether there are modifiable risk factors for the occurrence of such difficulties. To identify: 1) factors associated with lower levels of confidence among family members to function as surrogates and 2) whether the quality of clinician-family communication is associated with the timing of decisions to forego life support. We conducted a prospective study of 230 surrogate decision makers for incapacitated, mechanically ventilated patients at high risk of death in four intensive care units at University of California San Francisco Medical Center from 2006 to 2007. Surrogates completed a questionnaire addressing their perceived ability to act as a surrogate and the quality of their communication with physicians. We used clustered multivariate logistic regression to identify predictors of low levels of perceived ability to act as a surrogate and a Cox proportional hazard model to determine whether quality of communication was associated with the timing of decisions to withdraw life support. There was substantial variability in family members' confidence to act as surrogate decision makers, with 27% rating their perceived ability as 7 or lower on a 10-point scale. Independent predictors of lower role confidence were the lack of prior experience as a surrogate (odds ratio 2.2, 95% confidence interval [1.04-4.46], p=.04), no prior discussions with the patient about treatment preferences (odds ratio 3.7, 95% confidence interval [1.79-7.76], p<.001), and poor quality of communication with the ICU physician (odds ratio 1.2, 95% confidence interval [1.09-1.35] p<.001). Higher quality physician-family communication was associated with a significantly shorter duration of life-sustaining treatment among patients who died (β=0.11, p=.001). Family members without prior experience as a surrogate and those who had not engaged in advanced discussions with the patient about treatment preferences were at higher risk to report less confidence in carrying out the surrogate role. Better-quality clinician-family communication was associated with both more confidence among family members to act as surrogates and a shorter duration of use of life support among patients who died.

Sperm count as a surrogate endpoint for male fertility control.

PubMed

Benda, Norbert; Gerlinger, Christoph

2007-11-30

When assessing the effectiveness of a hormonal method of fertility control in men, the classical approach used for the assessment of hormonal contraceptives in women, by estimating the pregnancy rate or using a life-table analysis for the time to pregnancy, is difficult to apply in a clinical development program. The main reasons are the dissociation of the treated unit, i.e. the man, and the observed unit, i.e. his female partner, the high variability in the frequency of male intercourse, the logistical cost and ethical concerns related to the monitoring of the trial. A reasonable surrogate endpoint of the definite endpoint time to pregnancy is sperm count. In addition to the avoidance of the mentioned problems, trials that compare different treatments are possible with reasonable sample sizes, and study duration can be shorter. However, current products do not suppress sperm production to 100 per cent in all men and the sperm count is only observed with measurement error. Complete azoospermia might not be necessary in order to achieve an acceptable failure rate compared with other forms of male fertility control. Therefore, the use of sperm count as a surrogate endpoint must rely on the results of a previous trial in which both the definitive- and surrogate-endpoint results were assessed. The paper discusses different estimation functions of the mean pregnancy rate (corresponding to the cumulative hazard) that are based on the results of sperm count trial and a previous trial in which both sperm count and time to pregnancy were assessed, as well as the underlying assumptions. Sample size estimations are given for pregnancy rate estimation with a given precision.

Committee-Based Active Learning for Surrogate-Assisted Particle Swarm Optimization of Expensive Problems.

PubMed

Wang, Handing; Jin, Yaochu; Doherty, John

2017-09-01

Function evaluations (FEs) of many real-world optimization problems are time or resource consuming, posing a serious challenge to the application of evolutionary algorithms (EAs) to solve these problems. To address this challenge, the research on surrogate-assisted EAs has attracted increasing attention from both academia and industry over the past decades. However, most existing surrogate-assisted EAs (SAEAs) either still require thousands of expensive FEs to obtain acceptable solutions, or are only applied to very low-dimensional problems. In this paper, a novel surrogate-assisted particle swarm optimization (PSO) inspired from committee-based active learning (CAL) is proposed. In the proposed algorithm, a global model management strategy inspired from CAL is developed, which searches for the best and most uncertain solutions according to a surrogate ensemble using a PSO algorithm and evaluates these solutions using the expensive objective function. In addition, a local surrogate model is built around the best solution obtained so far. Then, a PSO algorithm searches on the local surrogate to find its optimum and evaluates it. The evolutionary search using the global model management strategy switches to the local search once no further improvement can be observed, and vice versa. This iterative search process continues until the computational budget is exhausted. Experimental results comparing the proposed algorithm with a few state-of-the-art SAEAs on both benchmark problems up to 30 decision variables as well as an airfoil design problem demonstrate that the proposed algorithm is able to achieve better or competitive solutions with a limited budget of hundreds of exact FEs.

Time-variant random interval natural frequency analysis of structures

NASA Astrophysics Data System (ADS)

Wu, Binhua; Wu, Di; Gao, Wei; Song, Chongmin

2018-02-01

This paper presents a new robust method namely, unified interval Chebyshev-based random perturbation method, to tackle hybrid random interval structural natural frequency problem. In the proposed approach, random perturbation method is implemented to furnish the statistical features (i.e., mean and standard deviation) and Chebyshev surrogate model strategy is incorporated to formulate the statistical information of natural frequency with regards to the interval inputs. The comprehensive analysis framework combines the superiority of both methods in a way that computational cost is dramatically reduced. This presented method is thus capable of investigating the day-to-day based time-variant natural frequency of structures accurately and efficiently under concrete intrinsic creep effect with probabilistic and interval uncertain variables. The extreme bounds of the mean and standard deviation of natural frequency are captured through the embedded optimization strategy within the analysis procedure. Three particularly motivated numerical examples with progressive relationship in perspective of both structure type and uncertainty variables are demonstrated to justify the computational applicability, accuracy and efficiency of the proposed method.

Weighted Iterative Bayesian Compressive Sensing (WIBCS) for High Dimensional Polynomial Surrogate Construction

NASA Astrophysics Data System (ADS)

Sargsyan, K.; Ricciuto, D. M.; Safta, C.; Debusschere, B.; Najm, H. N.; Thornton, P. E.

2016-12-01

Surrogate construction has become a routine procedure when facing computationally intensive studies requiring multiple evaluations of complex models. In particular, surrogate models, otherwise called emulators or response surfaces, replace complex models in uncertainty quantification (UQ) studies, including uncertainty propagation (forward UQ) and parameter estimation (inverse UQ). Further, surrogates based on Polynomial Chaos (PC) expansions are especially convenient for forward UQ and global sensitivity analysis, also known as variance-based decomposition. However, the PC surrogate construction strongly suffers from the curse of dimensionality. With a large number of input parameters, the number of model simulations required for accurate surrogate construction is prohibitively large. Relatedly, non-adaptive PC expansions typically include infeasibly large number of basis terms far exceeding the number of available model evaluations. We develop Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth and PC surrogate construction leading to a sparse, high-dimensional PC surrogate with a very few model evaluations. The surrogate is then readily employed for global sensitivity analysis leading to further dimensionality reduction. Besides numerical tests, we demonstrate the construction on the example of Accelerated Climate Model for Energy (ACME) Land Model for several output QoIs at nearly 100 FLUXNET sites covering multiple plant functional types and climates, varying 65 input parameters over broad ranges of possible values. This work is supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research, Accelerated Climate Modeling for Energy (ACME) project. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

GENOMIC ANALYSIS OF SURROGATE TISSUES FOR ASSESSING ENVIRONMENTAL EXPOSURES AND FUTURE DISEASE STATES

EPA Science Inventory

Genomic Analysis of Surrogate Tissues for Assessing Environmental Exposures and Future Disease States

John C. Rockett, Chad R. Blystone, Amber K. Goetz, Rachel N. Murrell, Hongzu Ren, Judith E. Schmid, Jessica Stapelfeldt, Lillian F. Strader, Kary E. Thompson, Douglas B. T...

Modeling Spatial and Temporal Variability of Residential Air Exchange Rates for the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)

EPA Science Inventory

Air pollution health studies often use outdoor concentrations as exposure surrogates. Failure to account for variability of residential infiltration of outdoor pollutants can induce exposure errors and lead to bias and incorrect confidence intervals in health effect estimates. Th...

A comparative research of different ensemble surrogate models based on set pair analysis for the DNAPL-contaminated aquifer remediation strategy optimization.

PubMed

Hou, Zeyu; Lu, Wenxi; Xue, Haibo; Lin, Jin

2017-08-01

Surrogate-based simulation-optimization technique is an effective approach for optimizing the surfactant enhanced aquifer remediation (SEAR) strategy for clearing DNAPLs. The performance of the surrogate model, which is used to replace the simulation model for the aim of reducing computation burden, is the key of corresponding researches. However, previous researches are generally based on a stand-alone surrogate model, and rarely make efforts to improve the approximation accuracy of the surrogate model to the simulation model sufficiently by combining various methods. In this regard, we present set pair analysis (SPA) as a new method to build ensemble surrogate (ES) model, and conducted a comparative research to select a better ES modeling pattern for the SEAR strategy optimization problems. Surrogate models were developed using radial basis function artificial neural network (RBFANN), support vector regression (SVR), and Kriging. One ES model is assembling RBFANN model, SVR model, and Kriging model using set pair weights according their performance, and the other is assembling several Kriging (the best surrogate modeling method of three) models built with different training sample datasets. Finally, an optimization model, in which the ES model was embedded, was established to obtain the optimal remediation strategy. The results showed the residuals of the outputs between the best ES model and simulation model for 100 testing samples were lower than 1.5%. Using an ES model instead of the simulation model was critical for considerably reducing the computation time of simulation-optimization process and maintaining high computation accuracy simultaneously. Copyright © 2017 Elsevier B.V. All rights reserved.

Mechanical Design and Analysis of a Unilateral Cervical Spinal Cord Contusion Injury Model in Non-Human Primates.

PubMed

Sparrey, Carolyn J; Salegio, Ernesto A; Camisa, William; Tam, Horace; Beattie, Michael S; Bresnahan, Jacqueline C

2016-06-15

Non-human primate (NHP) models of spinal cord injury better reflect human injury and provide a better foundation to evaluate potential treatments and functional outcomes. We combined finite element (FE) and surrogate models with impact data derived from in vivo experiments to define the impact mechanics needed to generate a moderate severity unilateral cervical contusion injury in NHPs (Macaca mulatta). Three independent variables (impactor displacement, alignment, and pre-load) were examined to determine their effects on tissue level stresses and strains. Mechanical measures of peak force, peak displacement, peak energy, and tissue stiffness were analyzed as potential determinants of injury severity. Data generated from FE simulations predicted a lateral shift of the spinal cord at high levels of compression (>64%) during impact. Submillimeter changes in mediolateral impactor position over the midline increased peak impact forces (>50%). Surrogate cords established a 0.5 N pre-load protocol for positioning the impactor tip onto the dural surface to define a consistent dorsoventral baseline position before impact, which corresponded with cerebrospinal fluid displacement and entrapment of the spinal cord against the vertebral canal. Based on our simulations, impactor alignment and pre-load were strong contributors to the variable mechanical and functional outcomes observed in in vivo experiments. Peak displacement of 4 mm after a 0.5N pre-load aligned 0.5-1.0 mm over the midline should result in a moderate severity injury; however, the observed peak force and calculated peak energy and tissue stiffness are required to properly characterize the severity and variability of in vivo NHP contusion injuries.

Short-term variability of blood pressure and heart rate in hyperthyroidism.

PubMed

Girard, A; Hugues, F C; Le Jeunne, C; Elghozi, J L

1998-06-01

The effect of hyperthyroidism on the short-term memory variability of blood pressure and heart rate was evaluated in 12 untreated hyperthyroid patients during thyrotoxicosis and after a 6 1/2 month treatment designed to achieve a stable euthyroid state. Beat-by-beat finger blood pressure was measured with a Finapres device. The pulse interval, from which pulse rate was derived, was obtained from the blood pressure signal. Due to the significant change in heart rhythm associated with thyrotoxicosis, both pulse interval (taken as a surrogate of heart period) and pulse rate (taken as a surrogate of heart rate) were computed. Power spectral analysis showed a reduction in the overall heart period variability in the supine position in the hyperthyroid compared to the euthyroid state. This effect was observed in the low-frequency (0.005-0.068 Hz), mid-frequency (0.068-0.127 Hz) and high-frequency (respiratory) domains as well, with a significant reduction of the modulus of these bands of 31%, 35% and 47%, respectively. The heart rate spectral modulus also exhibited a reduction of the high-frequency component (31%) in the supine position in the hyperthyroid subjects. These changes in heart rhythmicity corroborate a vagal deficit in hyperthyroidism. In addition, blood pressure spectral power exhibited a significant deficit in the orthostatism-induced mid-frequency systolic blood pressure rise in the hyperthyroid state (64%) compared with the euthyroid state. This observation may reflect a reduced vascular sympathetic activation with standing. The resulting vasodilatation could well contribute to normalize blood pressure in thyrotoxicosis in which cardiac output is increased.

Stormwater run-off from an industrial log yard: characterization, contaminant correlation and first-flush phenomenon.

PubMed

Kaczala, Fabio; Marques, Marcia; Vinrot, Eva; Hogland, William

2012-01-01

The stormwater run-off generated in an industrial log yard during eight run-off events was studied with the main focus on the transport of toxic metals. Associations between water quality constituents and potential surrogates were evaluated by correlation analysis. The first-flush phenomenon was verified by normalized M(V) curves. The results have shown that, whereas some metals such as Zn, Ba, Cd, As and Fe were always detected in these waters, others (Cr, Pb, Cu, Ni, V, Co) were not. Large variations in the water constituents' concentrations were observed, with Fe, Pb and V being the most variable ones. Concentrations of Zn and Cu in the run-off waters exceeded the values established by the Swedish environmental authorities in 100% and 97% of samples, respectively. The correlation analyses indicated TSS as a potential surrogate of Pb, V, Co, Ni, As, Ba, Cr and COD (0.949 > R > 0.808), making it reasonable to state that a treatment system with focus on TSS removal would also reduce toxic metals from these waters. The first-flush phenomenon was evident for most of the constituents. Significant differences (p < 0.05) in the first-flush magnitude of different run-off events were observed confirming that hydro-meteorological variables such as dry period, precipitation duration and average intensity play important roles. Metal loads originating from the log yard were mainly composed ofZn, Cu and Ba. Knowledge of the physicochemical characteristics, discharge dynamics and the storm variables involved in the process is a crucial step for the proposal and implementation of a stormwater management programme.

Testing for intracycle determinism in pseudoperiodic time series.

PubMed

Coelho, Mara C S; Mendes, Eduardo M A M; Aguirre, Luis A

2008-06-01

A determinism test is proposed based on the well-known method of the surrogate data. Assuming predictability to be a signature of determinism, the proposed method checks for intracycle (e.g., short-term) determinism in the pseudoperiodic time series for which standard methods of surrogate analysis do not apply. The approach presented is composed of two steps. First, the data are preprocessed to reduce the effects of seasonal and trend components. Second, standard tests of surrogate analysis can then be used. The determinism test is applied to simulated and experimental pseudoperiodic time series and the results show the applicability of the proposed test.

Conceptualizing Surrogate Decision-Making at End of Life in the Intensive Care Unit using Cognitive Task Analysis

PubMed Central

Dionne-Odom, J. Nicholas; Willis, Danny G.; Bakitas, Marie; Crandall, Beth; Grace, Pamela J.

2014-01-01

Background Surrogate decision-makers (SDMs) face difficult decisions at end of life (EOL) for decisionally incapacitated intensive care unit (ICU) patients. Purpose Identify and describe the underlying psychological processes of surrogate decision-making for adults at EOL in the ICU. Method Qualitative case study design using a cognitive task analysis (CTA) interviewing approach. Participants were recruited from October 2012 to June 2013 from an academic tertiary medical center’s ICU located in the rural Northeastern United States. Nineteen SDMs for patients who had died in the ICU completed in-depth semi-structured CTA interviews. Discussion The conceptual framework formulated from data analysis reveals that three underlying, iterative, psychological dimensions: gist impressions, distressing emotions, and moral intuitions impact a SDM’s judgment about the acceptability of either the patient’s medical treatments or his or her condition. Conclusion The framework offers initial insights about the underlying psychological processes of surrogate decision-making and may facilitate enhanced decision support for SDMs. PMID:25982772

A cross-cultural study on surrogate mother's empathy and maternal-foetal attachment.

PubMed

Lorenceau, Ellen Schenkel; Mazzucca, Luis; Tisseron, Serge; Pizitz, Todd D

2015-06-01

Traditional and gestational surrogate mothers assist infertile couples by carrying their children. In 2005, a meta-analysis on surrogacy was conducted but no study had examined empathy and maternal-foetal attachment of surrogate mothers. Assessments of surrogate mothers show no sign of psychopathology, but one study showed differences on several MMPI-2 scales compared to a normative sample: surrogate mothers identified with stereotypically masculine traits such as assertiveness and competition. They had a higher self-esteem and lower levels of anxiety and depression. To determine if there is a difference in empathy and maternal-foetal attachment of surrogate mothers compared to a comparison group of mothers. Three groups of European traditional and gestational surrogate mothers (n=10), Anglo-Saxon traditional and gestational surrogate mothers (n=34) and a European normative sample of mothers (n=32) completed four published psychometric instruments: the Interpersonal Reactivity Index (empathy index), the Hospital Anxiety and Depressions Scale and the MC20, a social desirability scale. Pregnant surrogate mothers filled the Maternal Antenatal Attachment Scale (n=11). Statistical non-parametric analyses of variance were conducted. Depending on cultural background, surrogate mothers present differences in terms of empathy, anxiety and depression, social desirability and quality of attachment to the foetus compared to a normative sample. Environment plays a role for traditional and gestational surrogacy. Surrogate mothers of both groups are less anxious and depressed than normative samples. Maternal-foetal attachment is strong with a slightly lower quality of attachment. Surrogate mother's empathy indexes are similar to normative samples, sometimes higher. Copyright © 2014 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Critical care physicians' approaches to negotiating with surrogate decision makers: a qualitative study.

PubMed

Brush, David R; Brown, Crystal E; Alexander, G Caleb

2012-04-01

To describe how critical care physicians manage conflicts with surrogates about withdrawing or withholding patients' life support. Qualitative analysis of key informant interviews with critical care physicians during 2010. We transcribed interviews verbatim and used grounded theory to code and revise a taxonomy of themes and to identify illustrative quotes. Three academic medical centers, one academic-affiliated medical center, and four private practice groups or private hospitals in a large Midwestern city Fourteen critical care physicians. None. Physicians reported tailoring their approach to address specific reasons for disagreement with surrogates. Five common approaches were identified: 1) building trust; 2) educating and informing; 3) providing surrogates more time; 4) adjusting surrogate and physician roles; and 5) highlighting specific values. When mistrust was an issue, physicians endeavored to build a more trusting relationship with the surrogate before readdressing decision making. Physicians also reported correcting misunderstandings by providing targeted education, and some reported highlighting specific patient, surrogate, or physician values that they hoped would guide surrogates to agree with them. When surrogates struggled with decisionmaking roles, physicians attempted to reinforce the concept of substituted judgment. Physicians noted that some surrogates needed time to "come to terms" with the patent's illness before agreeing with physicians. Many physicians had witnessed colleagues negotiate in ways they found objectionable such as providing misleading information, injecting their own values into the negotiation or behaving unprofessionally toward surrogates. Although some physicians viewed their efforts to encourage surrogates' agreement as persuasive, others strongly denied persuading surrogates and described their actions as "guiding" or "negotiating." Physicians reported using a tailored approach to resolve decisional conflicts about life support and attempted to change surrogates' decisions in accordance with what the physician thought was in the patients' best interests. Although physicians acknowledged their efforts to change surrogates' decisions, many physicians did not perceive these efforts as persuasive.

Surrogate marker analysis in cancer clinical trials through time-to-event mediation techniques.

PubMed

Vandenberghe, Sjouke; Duchateau, Luc; Slaets, Leen; Bogaerts, Jan; Vansteelandt, Stijn

2017-01-01

The meta-analytic approach is the gold standard for validation of surrogate markers, but has the drawback of requiring data from several trials. We refine modern mediation analysis techniques for time-to-event endpoints and apply them to investigate whether pathological complete response can be used as a surrogate marker for disease-free survival in the EORTC 10994/BIG 1-00 randomised phase 3 trial in which locally advanced breast cancer patients were randomised to either taxane or anthracycline based neoadjuvant chemotherapy. In the mediation analysis, the treatment effect is decomposed into an indirect effect via pathological complete response and the remaining direct effect. It shows that only 4.2% of the treatment effect on disease-free survival after five years is mediated by the treatment effect on pathological complete response. There is thus no evidence from our analysis that pathological complete response is a valuable surrogate marker to evaluate the effect of taxane versus anthracycline based chemotherapies on progression free survival of locally advanced breast cancer patients. The proposed analysis strategy is broadly applicable to mediation analyses of time-to-event endpoints, is easy to apply and outperforms existing strategies in terms of precision as well as robustness against model misspecification.

Evaluating and interpreting cross-taxon congruence: Potential pitfalls and solutions

NASA Astrophysics Data System (ADS)

Gioria, Margherita; Bacaro, Giovanni; Feehan, John

2011-05-01

Characterizing the relationship between different taxonomic groups is critical to identify potential surrogates for biodiversity. Previous studies have shown that cross-taxa relationships are generally weak and/or inconsistent. The difficulties in finding predictive patterns have often been attributed to the spatial and temporal scales of these studies and on the differences in the measure used to evaluate such relationships (species richness versus composition). However, the choice of the analytical approach used to evaluate cross-taxon congruence inevitably represents a major source of variation. Here, we described the use of a range of methods that can be used to comprehensively assess cross-taxa relationships. To do so, we used data for two taxonomic groups, wetland plants and water beetles, collected from 54 farmland ponds in Ireland. Specifically, we used the Pearson correlation and rarefaction curves to analyse patterns in species richness, while Mantel tests, Procrustes analysis, and co-correspondence analysis were used to evaluate congruence in species composition. We compared the results of these analyses and we described some of the potential pitfalls associated with the use of each of these statistical approaches. Cross-taxon congruence was moderate to strong, depending on the choice of the analytical approach, on the nature of the response variable, and on local and environmental conditions. Our findings indicate that multiple approaches and measures of community structure are required for a comprehensive assessment of cross-taxa relationships. In particular, we showed that selection of surrogate taxa in conservation planning should not be based on a single statistic expressing the degree of correlation in species richness or composition. Potential solutions to the analytical issues associated with the assessment of cross-taxon congruence are provided and the implications of our findings in the selection of surrogates for biodiversity are discussed.

Creatinine Change on Vasoconstrictors as Mortality Surrogate in Hepatorenal Syndrome: Systematic Review & Meta-Analysis

PubMed Central

Belcher, Justin M.; Coca, Steven G.; Parikh, Chirag R.

2015-01-01

Background and Aims Hepatorenal syndrome is a severe complication of cirrhosis and associates with significant mortality. Vasoconstrictor medications improve renal function in patients with hepatorenal syndrome. However, it is unclear to what extent changes in serum creatinine during treatment may act as a surrogate for changes in mortality. We have performed a meta-analysis of randomized trials of vasoconstrictors assessing the association between changes in serum creatinine, taken as a continuous variable, and mortality, both while on treatment and during the follow-up period for survivors. Methods The electronic databases of PubMed, Web of Science and Embase were searched for randomized trials evaluating the efficacy of vasoconstrictor therapy for treatment of HRS type 1 or 2. The relative risk (RR) for mortality was calculated against delta creatinine. The proportion of treatment effect explained (PTE) was calculated for delta creatinine. Results Seven trials enrolling 345 patients were included. The correlation between delta creatinine and ln (RR) was moderately good (R2 = 0.61). The intercept and parameter estimate indicated a fall in creatinine while on treatment of 1 mg/dL resulted in a 27% reduction in RR for mortality compared to the control arm. In patients surviving the treatment period, a fall in creatinine while on treatment of 1 mg/dL resulted in a 16% reduction in RR for post-treatment mortality during follow-up. The PTE of delta creatinine for overall mortality was 0.91 and 0.26 for post-treatment mortality. Conclusions Changes in serum creatinine in response to vasoconstrictor therapy appear to be a valid surrogate for mortality, even in the period following the completion of treatment. PMID:26295585

Health information-seeking on behalf of others: characteristics of "surrogate seekers".

PubMed

Cutrona, Sarah L; Mazor, Kathleen M; Vieux, Sana N; Luger, Tana M; Volkman, Julie E; Finney Rutten, Lila J

2015-03-01

Understanding the behaviors of surrogate seekers (those who seek health information for others) may guide efforts to improve health information transmission. We used 2011-2012 data from the Health Information National Trends Survey to describe behaviors of online surrogate seekers. Respondents were asked about use of the Internet for surrogate-seeking over the prior 12 months. Data were weighted to calculate population estimates. Two thirds (66.6%) reported surrogate-seeking. Compared to those who sought health information online for only themselves, surrogate seekers were more likely to live in households with others (weighted percent 89.4 vs. 82.5% of self-seekers; p < 0.05); no significant differences in sex, race, income or education were observed. Surrogate seekers were more likely to report activities requiring user-generated content: email communication with healthcare providers; visits to social networking sites to read and share about medical topics and participation in online health support groups. On multivariate analysis, those who had looked online for healthcare providers were more likely to be surrogate seekers (OR 1.67, 95% CI 1.08-2.59). In addition to seeking health information, surrogate seekers create and pass along communications that may influence medical care decisions. Research is needed to identify ways to facilitate transmission of accurate health information.

Health information seeking on behalf of others: Characteristics of ‘surrogate seekers’

PubMed Central

Cutrona, Sarah L.; Mazor, Kathleen M.; Vieux, Sana N.; Luger, Tana M.; Volkman, Julie E.; Finney Rutten, Lila J.

2014-01-01

Understanding the behaviors of surrogate-seekers (those who seek health information for others) may guide efforts to improve health information transmission. We used 2011–2012 data from the Health Information National Trends Survey to describe behaviors of online surrogate-seekers. Respondents were asked about use of the Internet for surrogate-seeking over the prior 12 months. Data were weighted to calculate population estimates. Two-thirds (66.6%) reported surrogate-seeking. Compared to those who sought health information online for only themselves, surrogate-seekers were more likely to live in households with others (weighted percent 89.4% vs. 82.5% of self-seekers; p < 0.05); no significant differences in sex, race, income or education were observed. Surrogate-seekers were more likely to report activities requiring user-generated content: email communication with healthcare providers; visits to social networking sites to read and share about medical topics and participation in online health support groups. On multivariate analysis, those who had looked online for healthcare providers were more likely to be surrogate-seekers (OR 1.67, 95% CI 1.08–2.59). In addition to seeking health information, surrogate-seekers create and pass along communications that may influence medical care decisions. Research is needed to identify ways to facilitate transmission of accurate health information. PMID:24989816

Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach

NASA Astrophysics Data System (ADS)

Chowdhury, R.; Adhikari, S.

2012-10-01

Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.

An urban observatory for quantifying phosphorus and suspended solid loads in combined natural and stormwater conveyances.

PubMed

Melcher, Anthony A; Horsburgh, Jeffery S

2017-06-01

Water quality in urban streams and stormwater systems is highly dynamic, both spatially and temporally, and can change drastically during storm events. Infrequent grab samples commonly collected for estimating pollutant loadings are insufficient to characterize water quality in many urban water systems. In situ water quality measurements are being used as surrogates for continuous pollutant load estimates; however, relatively few studies have tested the validity of surrogate indicators in urban stormwater conveyances. In this paper, we describe an observatory aimed at demonstrating the infrastructure required for surrogate monitoring in urban water systems and for capturing the dynamic behavior of stormwater-driven pollutant loads. We describe the instrumentation of multiple, autonomous water quality and quantity monitoring sites within an urban observatory. We also describe smart and adaptive sampling procedures implemented to improve data collection for developing surrogate relationships and for capturing the temporal and spatial variability of pollutant loading events in urban watersheds. Results show that the observatory is able to capture short-duration storm events within multiple catchments and, through inter-site communication, sampling efforts can be synchronized across multiple monitoring sites.

[The Intentions Affecting the Medical Decision-Making Behavior of Surrogate Decision Makers of Critically Ill Patients and Related Factors].

PubMed

Su, Szu-Huei; Wu, Li-Min

2018-04-01

The severity of diseases and high mortality rates that typify the intensive care unit often make it difficult for surrogate decision makers to make decisions for critically ill patients regarding whether to continue medical treatments or to accept palliative care. To explore the behavioral intentions that underlie the medical decisions of surrogate decision makers of critically ill patients and the related factors. A cross-sectional, correlation study design was used. A total of 193 surrogate decision makers from six ICUs in a medical center in southern Taiwan were enrolled as participants. Three structured questionnaires were used, including a demographic datasheet, the Family Relationship Scale, and the Behavioral Intention of Medical Decisions Scale. Significantly positive correlations were found between the behavioral intentions underlying medical decisions and the following variables: the relationship of the participant to the patient (Eta = .343, p = .020), the age of the patient (r = .295, p < .01), and whether the patient had signed a currently valid advance healthcare directive (Eta = .223, p = .002). Furthermore, a significantly negative correlation was found between these intentions and length of stay in the ICU (r = -.263, p < .01). Patient age, whether the patient had signed a currently valid advance healthcare directive, and length of stay in the ICU were all predictive factors for the behavioral intentions underlying the medical decisions of the surrogate decision makers, explaining 13.9% of the total variance. In assessing the behavioral intentions underlying the medical decisions of surrogate decision makers, health providers should consider the relationship between critical patients and their surrogate decision makers, patient age, the length of ICU stay, and whether the patient has a pre-signed advance healthcare directive in order to maximize the effectiveness of medical care provided to critically ill patients.

Surrogate Model Application to the Identification of Optimal Groundwater Exploitation Scheme Based on Regression Kriging Method—A Case Study of Western Jilin Province

PubMed Central

An, Yongkai; Lu, Wenxi; Cheng, Weiguo

2015-01-01

This paper introduces a surrogate model to identify an optimal exploitation scheme, while the western Jilin province was selected as the study area. A numerical simulation model of groundwater flow was established first, and four exploitation wells were set in the Tongyu county and Qian Gorlos county respectively so as to supply water to Daan county. Second, the Latin Hypercube Sampling (LHS) method was used to collect data in the feasible region for input variables. A surrogate model of the numerical simulation model of groundwater flow was developed using the regression kriging method. An optimization model was established to search an optimal groundwater exploitation scheme using the minimum average drawdown of groundwater table and the minimum cost of groundwater exploitation as multi-objective functions. Finally, the surrogate model was invoked by the optimization model in the process of solving the optimization problem. Results show that the relative error and root mean square error of the groundwater table drawdown between the simulation model and the surrogate model for 10 validation samples are both lower than 5%, which is a high approximation accuracy. The contrast between the surrogate-based simulation optimization model and the conventional simulation optimization model for solving the same optimization problem, shows the former only needs 5.5 hours, and the latter needs 25 days. The above results indicate that the surrogate model developed in this study could not only considerably reduce the computational burden of the simulation optimization process, but also maintain high computational accuracy. This can thus provide an effective method for identifying an optimal groundwater exploitation scheme quickly and accurately. PMID:26264008

Potential surrogate endpoints for prostate cancer survival: analysis of a phase III randomized trial.

PubMed

Ray, Michael E; Bae, Kyounghwa; Hussain, Maha H A; Hanks, Gerald E; Shipley, William U; Sandler, Howard M

2009-02-18

The identification of surrogate endpoints for prostate cancer-specific survival may shorten the length of clinical trials for prostate cancer. We evaluated distant metastasis and general clinical treatment failure as potential surrogates for prostate cancer-specific survival by use of data from the Radiation Therapy and Oncology Group 92-02 randomized trial. Patients (n = 1554 randomly assigned and 1521 evaluable for this analysis) with locally advanced prostate cancer had been treated with 4 months of neoadjuvant and concurrent androgen deprivation therapy with external beam radiation therapy and then randomly assigned to no additional therapy (control arm) or 24 additional months of androgen deprivation therapy (experimental arm). Data from landmark analyses at 3 and 5 years for general clinical treatment failure (defined as documented local disease progression, regional or distant metastasis, initiation of androgen deprivation therapy, or a prostate-specific antigen level of 25 ng/mL or higher after radiation therapy) and/or distant metastasis were tested as surrogate endpoints for prostate cancer-specific survival at 10 years by use of Prentice's four criteria. All statistical tests were two-sided. At 3 years, 1364 patients were alive and contributed data for analysis. Both distant metastasis and general clinical treatment failure at 3 years were consistent with all four of Prentice's criteria for being surrogate endpoints for prostate cancer-specific survival at 10 years. At 5 years, 1178 patients were alive and contributed data for analysis. Although prostate cancer-specific survival was not statistically significantly different between treatment arms at 5 years (P = .08), both endpoints were consistent with Prentice's remaining criteria. Distant metastasis and general clinical treatment failure at 3 years may be candidate surrogate endpoints for prostate cancer-specific survival at 10 years. These endpoints, however, must be validated in other datasets.

Oncotype DX breast cancer recurrence score can be predicted with a novel nomogram using clinicopathologic data.

PubMed

Orucevic, Amila; Bell, John L; McNabb, Alison P; Heidel, Robert E

2017-05-01

Oncotype DX (ODX) recurrence score (RS) breast cancer (BC) assay is costly, and performed in only ~1/3 of estrogen receptor (ER)-positive BC patients in the USA. We have now developed a user-friendly nomogram surrogate prediction model for ODX based on a large dataset from the National Cancer Data Base (NCDB) to assist in selecting patients for which further ODX testing may not be necessary and as a surrogate for patients for which ODX testing is not affordable or available. Six clinicopathologic variables of 27,719 ODX-tested ER+/HER2-/lymph node-negative patients with 6-50 mm tumor size captured by the NCDB from 2010 to 2012 were assessed with logistic regression to predict high-risk or low-risk ODXRS test results with TAILORx-trial and commercial cut-off values; 12,763 ODX-tested patients in 2013 were used for external validation. The predictive accuracy of the regression model was yielded using a Receiver Operator Characteristic analysis. Model fit was analyzed by plotting the predicted probabilities against the actual probabilities. A user-friendly calculator version of nomograms is available online at the University of Tennessee Medical Center website (Knoxville, TN). Grade and progesterone receptor status were the highest predictors of both low-risk and high-risk ODXRS, followed by age, tumor size, histologic tumor type and lymph-vascular invasion (C-indexes-.0.85 vs. 0.88 for TAILORx-trial vs. commercial cut-off values, respectively). This is the first study of this scale showing confidently that clinicopathologic variables can be used for prediction of low-risk or high-risk ODXRS using our nomogram models. These novel nomograms will be useful tools to help physicians and patients decide whether further ODX testing is necessary and are excellent surrogates for patients for which ODX testing is not affordable or available.

Modified cross sample entropy and surrogate data analysis method for financial time series

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2015-09-01

For researching multiscale behaviors from the angle of entropy, we propose a modified cross sample entropy (MCSE) and combine surrogate data analysis with it in order to compute entropy differences between original dynamics and surrogate series (MCSDiff). MCSDiff is applied to simulated signals to show accuracy and then employed to US and Chinese stock markets. We illustrate the presence of multiscale behavior in the MCSDiff results and reveal that there are synchrony containing in the original financial time series and they have some intrinsic relations, which are destroyed by surrogate data analysis. Furthermore, the multifractal behaviors of cross-correlations between these financial time series are investigated by multifractal detrended cross-correlation analysis (MF-DCCA) method, since multifractal analysis is a multiscale analysis. We explore the multifractal properties of cross-correlation between these US and Chinese markets and show the distinctiveness of NQCI and HSI among the markets in their own region. It can be concluded that the weaker cross-correlation between US markets gives the evidence for the better inner mechanism in the US stock markets than that of Chinese stock markets. To study the multiscale features and properties of financial time series can provide valuable information for understanding the inner mechanism of financial markets.

Determination of oral mucosal Poisson's ratio and coefficient of friction from in-vivo contact pressure measurements.

PubMed

Chen, Junning; Suenaga, Hanako; Hogg, Michael; Li, Wei; Swain, Michael; Li, Qing

2016-01-01

Despite their considerable importance to biomechanics, there are no existing methods available to directly measure apparent Poisson's ratio and friction coefficient of oral mucosa. This study aimed to develop an inverse procedure to determine these two biomechanical parameters by utilizing in vivo experiment of contact pressure between partial denture and beneath mucosa through nonlinear finite element (FE) analysis and surrogate response surface (RS) modelling technique. First, the in vivo denture-mucosa contact pressure was measured by a tactile electronic sensing sheet. Second, a 3D FE model was constructed based on the patient CT images. Third, a range of apparent Poisson's ratios and the coefficients of friction from literature was considered as the design variables in a series of FE runs for constructing a RS surrogate model. Finally, the discrepancy between computed in silico and measured in vivo results was minimized to identify the best matching Poisson's ratio and coefficient of friction. The established non-invasive methodology was demonstrated effective to identify such biomechanical parameters of oral mucosa and can be potentially used for determining the biomaterial properties of other soft biological tissues.

Combining conversation analysis and event sequencing to study health communication.

PubMed

Pecanac, Kristen E

2018-06-01

Good communication is essential in patient-centered care. The purpose of this paper is to describe conversation analysis and event sequencing and explain how integrating these methods strengthened the analysis in a study of communication between clinicians and surrogate decision makers in an intensive care unit. Conversation analysis was first used to determine how clinicians introduced the need for decision-making regarding life-sustaining treatment and how surrogate decision makers responded. Event sequence analysis then was used to determine the transitional probability (probability of one event leading to another in the interaction) that a given type of clinician introduction would lead to surrogate resistance or alignment. Conversation analysis provides a detailed analysis of the interaction between participants in a conversation. When combined with a quantitative analysis of the patterns of communication in an interaction, these data add information on the communication strategies that produce positive outcomes. Researchers can apply this mixed-methods approach to identify beneficial conversational practices and design interventions to improve health communication. © 2018 Wiley Periodicals, Inc.

Sources of Variability in Children's Drawings

ERIC Educational Resources Information Center

Simon, Lia; Stokes, Patricia D.

2015-01-01

An experiment involving 90 students in the 1st, 3rd, and 5th grades investigated how visual examples and grade (our surrogate for age) affected variability in a drawing task. The task involved using circles as the main element in a set of drawings. There were two examples: One was simple and single (a smiley face inside a circle); the other,…

Surrogacy Assessment Using Principal Stratification and a Gaussian Copula Model

PubMed Central

Taylor, J.M.G.; Elliott, M.R.

2014-01-01

In clinical trials, a surrogate outcome (S) can be measured before the outcome of interest (T) and may provide early information regarding the treatment (Z) effect on T. Many methods of surrogacy validation rely on models for the conditional distribution of T given Z and S. However, S is a post-randomization variable, and unobserved, simultaneous predictors of S and T may exist, resulting in a non-causal interpretation. Frangakis and Rubin1 developed the concept of principal surrogacy, stratifying on the joint distribution of the surrogate marker under treatment and control to assess the association between the causal effects of treatment on the marker and the causal effects of treatment on the clinical outcome. Working within the principal surrogacy framework, we address the scenario of an ordinal categorical variable as a surrogate for a censored failure time true endpoint. A Gaussian copula model is used to model the joint distribution of the potential outcomes of T, given the potential outcomes of S. Because the proposed model cannot be fully identified from the data, we use a Bayesian estimation approach with prior distributions consistent with reasonable assumptions in the surrogacy assessment setting. The method is applied to data from a colorectal cancer clinical trial, previously analyzed by Burzykowski et al..2 PMID:24947559

Surrogacy assessment using principal stratification and a Gaussian copula model.

PubMed

Conlon, Asc; Taylor, Jmg; Elliott, M R

2017-02-01

In clinical trials, a surrogate outcome ( S) can be measured before the outcome of interest ( T) and may provide early information regarding the treatment ( Z) effect on T. Many methods of surrogacy validation rely on models for the conditional distribution of T given Z and S. However, S is a post-randomization variable, and unobserved, simultaneous predictors of S and T may exist, resulting in a non-causal interpretation. Frangakis and Rubin developed the concept of principal surrogacy, stratifying on the joint distribution of the surrogate marker under treatment and control to assess the association between the causal effects of treatment on the marker and the causal effects of treatment on the clinical outcome. Working within the principal surrogacy framework, we address the scenario of an ordinal categorical variable as a surrogate for a censored failure time true endpoint. A Gaussian copula model is used to model the joint distribution of the potential outcomes of T, given the potential outcomes of S. Because the proposed model cannot be fully identified from the data, we use a Bayesian estimation approach with prior distributions consistent with reasonable assumptions in the surrogacy assessment setting. The method is applied to data from a colorectal cancer clinical trial, previously analyzed by Burzykowski et al.

Creation of a Rapid High-Fidelity Aerodynamics Module for a Multidisciplinary Design Environment

NASA Technical Reports Server (NTRS)

Srinivasan, Muktha; Whittecar, William; Edwards, Stephen; Mavris, Dimitri N.

2012-01-01

In the traditional aerospace vehicle design process, each successive design phase is accompanied by an increment in the modeling fidelity of the disciplinary analyses being performed. This trend follows a corresponding shrinking of the design space as more and more design decisions are locked in. The correlated increase in knowledge about the design and decrease in design freedom occurs partly because increases in modeling fidelity are usually accompanied by significant increases in the computational expense of performing the analyses. When running high fidelity analyses, it is not usually feasible to explore a large number of variations, and so design space exploration is reserved for conceptual design, and higher fidelity analyses are run only once a specific point design has been selected to carry forward. The designs produced by this traditional process have been recognized as being limited by the uncertainty that is present early on due to the use of lower fidelity analyses. For example, uncertainty in aerodynamics predictions produces uncertainty in trajectory optimization, which can impact overall vehicle sizing. This effect can become more significant when trajectories are being shaped by active constraints. For example, if an optimal trajectory is running up against a normal load factor constraint, inaccuracies in the aerodynamic coefficient predictions can cause a feasible trajectory to be considered infeasible, or vice versa. For this reason, a trade must always be performed between the desired fidelity and the resources available. Apart from this trade between fidelity and computational expense, it is very desirable to use higher fidelity analyses earlier in the design process. A large body of work has been performed to this end, led by efforts in the area of surrogate modeling. In surrogate modeling, an up-front investment is made by running a high fidelity code over a Design of Experiments (DOE); once completed, the DOE data is used to create a surrogate model, which captures the relationships between input variables and responses into regression equations. Depending on the dimensionality of the problem and the fidelity of the code for which a surrogate model is being created, the initial DOE can itself be computationally prohibitive to run. Cokriging, a modeling approach from the field of geostatistics, provides a desirable compromise between computational expense and fidelity. To do this, cokriging leverages a large body of data generated by a low fidelity analysis, combines it with a smaller set of data from a higher fidelity analysis, and creates a kriging surrogate model with prediction fidelity approaching that of the higher fidelity analysis. When integrated into a multidisciplinary environment, a disciplinary analysis module employing cokriging can raise the analysis fidelity without drastically impacting the expense of design iterations. This is demonstrated through the creation of an aerodynamics analysis module in NASA s OpenMDAO framework. Aerodynamic analyses including Missile DATCOM, APAS, and USM3D are leveraged to create high fidelity aerodynamics decks for parametric vehicle geometries, which are created in NASA s Vehicle Sketch Pad (VSP). Several trade studies are performed to examine the achieved level of model fidelity, and the overall impact to vehicle design is quantified.

Discovering variable fractional orders of advection-dispersion equations from field data using multi-fidelity Bayesian optimization

NASA Astrophysics Data System (ADS)

Pang, Guofei; Perdikaris, Paris; Cai, Wei; Karniadakis, George Em

2017-11-01

The fractional advection-dispersion equation (FADE) can describe accurately the solute transport in groundwater but its fractional order has to be determined a priori. Here, we employ multi-fidelity Bayesian optimization to obtain the fractional order under various conditions, and we obtain more accurate results compared to previously published data. Moreover, the present method is very efficient as we use different levels of resolution to construct a stochastic surrogate model and quantify its uncertainty. We consider two different problem set ups. In the first set up, we obtain variable fractional orders of one-dimensional FADE, considering both synthetic and field data. In the second set up, we identify constant fractional orders of two-dimensional FADE using synthetic data. We employ multi-resolution simulations using two-level and three-level Gaussian process regression models to construct the surrogates.

Is Decedent Race an Independent Predictor of Organ Donor Consent, or Merely a Surrogate Marker of Socioeconomic Status?

PubMed Central

DuBay, Derek A.; Redden, David; Haque, Akhlaque; Gray, Stephen; Fouad, Mona; Siminoff, Laura A.; Holt, Cheryl; Kohler, Connie; Eckhoff, Devin

2013-01-01

Background Studies have demonstrated that African American race is a strong predictor of non-donation. However, it is often and correctly argued that African American race is a crude explanatory variable that is a surrogate marker of socioeconomic status (SES), education and access to health care. We hypothesized that when controlling for these factors, African American race would cease to be a predictor of organ donation. Methods A retrospective review was performed of 1292 Alabama decedents approached for organ donation between 2006 and 2009. Multivariable logistic regression models were constructed to identify the most parsimonious model that could explain the variation in the log-odds of obtaining consent. Results Consent for donation was obtained from 49% of the decedent's families. Household income was a predictor of organ donor consent only in Caucasians. Surprisingly, household income was not statistically different between consented and non-consented African American decedents ($25,147 vs. $26,137; p=0.90). On multivariable analysis, education, urban residence and shorter distance between the decedent residence and donor hospital were significantly associated with obtaining consent for organ donation. On univariate analysis, the odds of donor consent in Caucasians compared to African Americans was 2.76 (95% CI 2.17 – 3.57). When controlling for SES and access to healthcare variables, the odds of donor consent increased to 4.36 (95% CI 2.88 – 6.61). Conclusions We interpret this result to indicate that there remains unknown but important factor(s) associated with both race and obtaining organ donor consent. Further studies are required to isolate and determine whether this factor(s) is modifiable. PMID:23018878

Interlaboratory comparison of red-cell ATP, 2,3-diphosphoglycerate and haemolysis measurements.

PubMed

Hess, J R; Kagen, L R; van der Meer, P F; Simon, T; Cardigan, R; Greenwalt, T J; AuBuchon, J P; Brand, A; Lockwood, W; Zanella, A; Adamson, J; Snyder, E; Taylor, H L; Moroff, G; Hogman, C

2005-07-01

Red blood cell (RBC) storage systems are licensed based on their ability to prevent haemolysis and maintain RBC 24-h in vivo recovery. Preclinical testing includes measurement of RBC ATP as a surrogate for recovery, 2,3-diphosphoglycerate (DPG) as a surrogate for oxygen affinity, and free haemoglobin, which is indicative of red cell lysis. The reproducibility of RBC ATP, DPG and haemolysis measurements between centres was investigated. Five, 4-day-old leucoreduced AS-1 RBC units were pooled, aliquotted and shipped on ice to 14 laboratories in the USA and European Union (EU). Each laboratory was to sample the bag twice on day 7 and measure RBC ATP, DPG, haemoglobin and haemolysis levels in triplicate on each sample. The variability of results was assessed by using coefficients of variation (CV) and analysis of variance. Measurements were highly reproducible at the individual sites. Between sites, the CV was 16% for ATP, 35% for DPG, 2% for total haemoglobin and 54% for haemolysis. For ATP and total haemoglobin, 94 and 80% of the variance in measurements was contributed by differences between sites, and more than 80% of the variance for DPG and haemolysis measurements came from markedly discordant results from three sites and one site, respectively. In descending order, mathematical errors, unvalidated analytical methods, a lack of shared standards and fluid handling errors contributed to the variability in measurements from different sites. While the methods used by laboratories engaged in RBC storage system clinical trials demonstrated good precision, differences in results between laboratories may hinder comparative analysis. Efforts to improve performance should focus on developing robust methods, especially for measuring RBC ATP.

Constructing Surrogate Models of Complex Systems with Enhanced Sparsity: Quantifying the Influence of Conformational Uncertainty in Biomolecular Solvation

DOE PAGES

Lei, Huan; Yang, Xiu; Zheng, Bin; ...

2015-11-05

Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational “active space” random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance ofmore » the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Finally, our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.« less

Measures of Residual Risk with Connections to Regression, Risk Tracking, Surrogate Models, and Ambiguity

DTIC Science & Technology

2015-04-15

manage , predict, and mitigate the risk in the original variable. Residual risk can be exemplified as a quantification of the improved... the random variable of interest is viewed in concert with a related random vector that helps to manage , predict, and mitigate the risk in the original... manage , predict and mitigate the risk in the original variable. Residual risk can be exemplified as a quantification of the improved situation faced

Comments on Surrogates measures and consistent surrogates (by Tyler VanderWeele)

DTIC Science & Technology

2013-03-01

as a criterion for “good” surrogate, why can’t we create a new, formal definition of “ surrogacy ” that (1) will automatically avoid the paradox and (2...requirement of avoiding the paradox could not, in itself, constitute a satisfactory definition of surrogacy . As with other paradoxes of causal...situation in practice. A treatment that has such a negative direct effect on outcome would rarely be a candidate for surrogacy analysis. In practice

Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations

NASA Astrophysics Data System (ADS)

Mitry, Mina

Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.

An evaluation of surrogate chemical exposure measures and autism prevalence in Texas.

PubMed

Lewandowski, T A; Bartell, S M; Yager, J W; Levin, L

2009-01-01

There is currently considerable discussion in the scientific community as well as within the general public concerning the role mercury (Hg) exposures may play in the apparent increased incidence of neurodevelopmental disorders (particularly autism) in children. Although the primary focus of this debate has focused on ethylmercury from vaccinations, linkage to other sources of Hg has been proposed. An ecologic association between 2001 Toxic Release Inventory (TRI; www.epa.gov/tri) data for Hg and 2000-2001 school district autism prevalence was previously reported in Texas. Evaluations using industrial release data as surrogate exposure measures may be problematic, particularly for chemicals like Hg that have complex environmental fates. To explore the robustness of TRI-based analyses of the Hg-autism hypothesis in Texas, a detailed analysis was undertaken examining the extent of the ecological relationship during multiple years and examining whether surrogate exposure measures would yield similar conclusions. Using multilevel Poisson regression analysis and data obtained from a number of publicly available databases, it was found that air Hg release data were significantly associated with autism prevalence in Texas school districts when considering data for 2001 and 2002 (2001: RR = 4.45, 95% CI = 1.60-12.36, 2002: RR = 2.70, 95% CI = 1.17-6.15). Significant associations were not found using data from 2003 to 2005. A significant association was not observed when considering air Hg data for 2000 or 2001 and school district autism prevalence data for 2005-2006 or 2006-2007, an analysis allowing for a 5-yr time period between presumed exposure and entry into the public school system (2000: RR = 1.03, 95% CI = 0.59-1.83, 2001: RR = 0.94, 95% CI = 0.59-1.47). Significant associations were not observed for any year nor for the time lagged analyses when censored autism counts were replaced by threes instead of zeros. An evaluation of TRI air emissions data for several other pollutants did not find significant associations except for nickel (RR = 1.71, 1.12-2.60), which has no history of being associated with neurodevelopmental disorders. An evaluation using downwind location from coal-fired power plants as the exposure surrogate variable also did not yield statistically significant results. The analysis suggests Hg emissions are not consistently associated with autism prevalence in Texas school districts. The lack of consistency across time may be the result of the influence of a more significant factor which remains unidentified. Alternatively, it may be that the significant association observed in 2001 and 2002 does not represent a true causal association.

Surrogate endpoints for cancer screening trials: general principles and an illustration using the UK Flexible Sigmoidoscopy Screening Trial.

PubMed

Cuzick, Jack; Cafferty, Fay H; Edwards, Robert; Møller, Henrik; Duffy, Stephen W

2007-01-01

Cancer screening is aimed primarily at reducing deaths. Thus, site-specific cancer mortality is the appropriate endpoint for evaluating screening interventions. However, it is also the most demanding endpoint, requiring follow-up and a large numbers of patients order to have adequate power. Therefore, it is highly desirable to have surrogate endpoints that can reliably predict mortality reductions many years earlier. We here review a range of surrogate markers in terms of their potential advantages and pitfalls, and argue that a measure which weights incident cancers according to their predicted mortality has many advantages over other measures and should be used more routinely. Application to the UK Flexible Sigmoidoscopy Screening Trial data suggests that predicted colorectal cancer mortality, based on stage-specific incidence, is a more powerful endpoint than actual mortality and could advance the analysis time by about three years. Total colorectal cancer incidence as a surrogate endpoint provides little advance in the analysis time over actual mortality. The approach requires reliable prognostic data, (e.g. stage), for both the study cohort and a representative sample of the whole population. The routine collection of such data should be a priority for cancer registries. Surrogate endpoints should not replace a long-term analysis based directly on mortality, but can provide reliable early indicators which can be useful both for monitoring ongoing screening programmes and for making policy decisions.

On the relationship between the causal-inference and meta-analytic paradigms for the validation of surrogate endpoints.

PubMed

Alonso, Ariel; Van der Elst, Wim; Molenberghs, Geert; Buyse, Marc; Burzykowski, Tomasz

2015-03-01

The increasing cost of drug development has raised the demand for surrogate endpoints when evaluating new drugs in clinical trials. However, over the years, it has become clear that surrogate endpoints need to be statistically evaluated and deemed valid, before they can be used as substitutes of "true" endpoints in clinical studies. Nowadays, two paradigms, based on causal-inference and meta-analysis, dominate the scene. Nonetheless, although the literature emanating from these paradigms is wide, till now the relationship between them has largely been left unexplored. In the present work, we discuss the conceptual framework underlying both approaches and study the relationship between them using theoretical elements and the analysis of a real case study. Furthermore, we show that the meta-analytic approach can be embedded within a causal-inference framework on the one hand and that it can be heuristically justified why surrogate endpoints successfully evaluated using this approach will often be appealing from a causal-inference perspective as well, on the other. A newly developed and user friendly R package Surrogate is provided to carry out the evaluation exercise. © 2014, The International Biometric Society.

Using a chemistry transport model to account for the spatial variability of exposure concentrations in epidemiologic air pollution studies.

PubMed

Valari, Myrto; Menut, Laurent; Chatignoux, Edouard

2011-02-01

Environmental epidemiology and more specifically time-series analysis have traditionally used area-averaged pollutant concentrations measured at central monitors as exposure surrogates to associate health outcomes with air pollution. However, spatial aggregation has been shown to contribute to the overall bias in the estimation of the exposure-response functions. This paper presents the benefit of adding features of the spatial variability of exposure by using concentration fields modeled with a chemistry transport model instead of monitor data and accounting for human activity patterns. On the basis of county-level census data for the city of Paris, France, and a Monte Carlo simulation, a simple activity model was developed accounting for the temporal variability between working and evening hours as well as during transit. By combining activity data with modeled concentrations, the downtown, suburban, and rural spatial patterns in exposure to nitrogen dioxide, ozone, and PM2.5 (particulate matter [PM] < or = 10 microm in aerodynamic diameter) were captured and parametrized. Exposures predicted with this model were used in a time-series study of the short-term effect of air pollution on total nonaccidental mortality for the 4-yr period from 2001 to 2004. It was shown that the time series of the exposure surrogates developed here are less correlated across co-pollutants than in the case of the area-averaged monitor data. This led to less biased exposure-response functions when all three co-pollutants were inserted simultaneously in the same regression model. This finding yields insight into pollutant-specific health effects that are otherwise masked by the high correlation among co-pollutants.

Mechanical Design and Analysis of a Unilateral Cervical Spinal Cord Contusion Injury Model in Non-Human Primates

PubMed Central

Salegio, Ernesto A.; Camisa, William; Tam, Horace; Beattie, Michael S.; Bresnahan, Jacqueline C.

2016-01-01

Abstract Non-human primate (NHP) models of spinal cord injury better reflect human injury and provide a better foundation to evaluate potential treatments and functional outcomes. We combined finite element (FE) and surrogate models with impact data derived from in vivo experiments to define the impact mechanics needed to generate a moderate severity unilateral cervical contusion injury in NHPs (Macaca mulatta). Three independent variables (impactor displacement, alignment, and pre-load) were examined to determine their effects on tissue level stresses and strains. Mechanical measures of peak force, peak displacement, peak energy, and tissue stiffness were analyzed as potential determinants of injury severity. Data generated from FE simulations predicted a lateral shift of the spinal cord at high levels of compression (>64%) during impact. Submillimeter changes in mediolateral impactor position over the midline increased peak impact forces (>50%). Surrogate cords established a 0.5 N pre-load protocol for positioning the impactor tip onto the dural surface to define a consistent dorsoventral baseline position before impact, which corresponded with cerebrospinal fluid displacement and entrapment of the spinal cord against the vertebral canal. Based on our simulations, impactor alignment and pre-load were strong contributors to the variable mechanical and functional outcomes observed in in vivo experiments. Peak displacement of 4 mm after a 0.5N pre-load aligned 0.5–1.0 mm over the midline should result in a moderate severity injury; however, the observed peak force and calculated peak energy and tissue stiffness are required to properly characterize the severity and variability of in vivo NHP contusion injuries. PMID:26670940

Habitat suitability index model for brook trout in streams of the Southern Blue Ridge Province: Surrogate variables, model evaluation, and suggested improvements

USGS Publications Warehouse

Schmitt, C.J.; Lemly, A.D.; Winger, P.V.

1993-01-01

Data from several sources were collated and analyzed by correlation, regression, and principal components analysis to define surrrogate variables for use in the brook trout (Salvelinus fontinalis) habitat suitability index (HSI) model, and to evaluate the applicability of the model for assessing habitat in high elevation streams of the southern Blue Ridge Province (SBRP). In all data sets examined, pH and alkalinity were highly correlated, and both declined with increasing elevation; however, the magnitude of the decline varied with underlying rock formations and other factors, thereby restricting the utility of elevation as a surrogate for pH. In the data sets that contained biological information, brook trout abundance (as biomass, density, or both) tended to increase with elevation and decrease with the abundance of rainbow trout (Oncorhynchus mykiss), and was not significantly correlated (P >0.05) with the abundance of most benthic macroinvertebrate taxa normally construed as important in the diet of brook trout. Using multiple linear regression, the authors formulated an alternative HSI model A? based on point estimates of gradient, pH, elevation, stream width, and rainbow trout density A? which explained 40 to 50 percent of the variance in brook trout density in 256 stream reaches. Although logically developed, the present U.S. Fish and Wildlife Service HSI model, proposed in 1982, seems deficient in several areas, especially when applied to SBRP streams. The authors recommend that the water quality component in the model be updated and reevaluated, focusing on the differential sensitivities of each life stage, the stochastic nature of the water quality variables, and the possible existence of habitat requirements that differ among brook trout strains.

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

A Strategic Approach to Medical Care for Exploration Missions

NASA Technical Reports Server (NTRS)

Canga, Michael A.; Shah, Ronak V.; Mindock, Jennifer A.; Antonsen, Erik L.

2016-01-01

Exploration missions will present significant new challenges to crew health, including effects of variable gravity environments, limited communication with Earth-based personnel for diagnosis and consultation for medical events, limited resupply, and limited ability for crew return. Providing health care capabilities for exploration class missions will require system trades be performed to identify a minimum set of requirements and crosscutting capabilities, which can be used in design of exploration medical systems. Medical data, information, and knowledge collected during current space missions must be catalogued and put in formats that facilitate querying and analysis. These data are used to inform the medical research and development program through analysis of risk trade studies between medical care capabilities and system constraints such as mass, power, volume, and training. Medical capability as a quantifiable variable is proposed as a surrogate risk metric and explored for trade space analysis that can improve communication between the medical and engineering approaches to mission design. The resulting medical system design approach selected will inform NASA mission architecture, vehicle, and subsystem design for the next generation of spacecraft.

Determination of Diethyl Phthalate and Polyhexamethylene Guanidine in Surrogate Alcohol from Russia

PubMed Central

Monakhova, Yulia B.; Kuballa, Thomas; Leitz, Jenny; Lachenmeier, Dirk W.

2011-01-01

Analytical methods based on spectroscopic techniques were developed and validated for the determination of diethyl phthalate (DEP) and polyhexamethylene guanidine (PHMG), which may occur in unrecorded alcohol. Analysis for PHMG was based on UV-VIS spectrophotometry after derivatization with Eosin Y and 1H NMR spectroscopy of the DMSO extract. Analysis of DEP was performed with direct UV-VIS and 1H NMR methods. Multivariate curve resolution and spectra computation methods were used to confirm the presence of PHMG and DEP in the investigated beverages. Of 22 analysed alcohol samples, two contained DEP or PHMG. 1H NMR analysis also revealed the presence of signals of hawthorn extract in three medicinal alcohols used as surrogate alcohol. The simple and cheap UV-VIS methods can be used for rapid screening of surrogate alcohol samples for impurities, while 1H NMR is recommended for specific confirmatory analysis if required. PMID:21647285

Determination of diethyl phthalate and polyhexamethylene guanidine in surrogate alcohol from Russia.

PubMed

Monakhova, Yulia B; Kuballa, Thomas; Leitz, Jenny; Lachenmeier, Dirk W

2011-01-01

Analytical methods based on spectroscopic techniques were developed and validated for the determination of diethyl phthalate (DEP) and polyhexamethylene guanidine (PHMG), which may occur in unrecorded alcohol. Analysis for PHMG was based on UV-VIS spectrophotometry after derivatization with Eosin Y and (1)H NMR spectroscopy of the DMSO extract. Analysis of DEP was performed with direct UV-VIS and (1)H NMR methods. Multivariate curve resolution and spectra computation methods were used to confirm the presence of PHMG and DEP in the investigated beverages. Of 22 analysed alcohol samples, two contained DEP or PHMG. (1)H NMR analysis also revealed the presence of signals of hawthorn extract in three medicinal alcohols used as surrogate alcohol. The simple and cheap UV-VIS methods can be used for rapid screening of surrogate alcohol samples for impurities, while (1)H NMR is recommended for specific confirmatory analysis if required.

Spatial variability in intertidal macroalgal assemblages on the North Portuguese coast: consistence between species and functional group approaches

NASA Astrophysics Data System (ADS)

Veiga, P.; Rubal, M.; Vieira, R.; Arenas, F.; Sousa-Pinto, I.

2013-03-01

Natural assemblages are variable in space and time; therefore, quantification of their variability is imperative to identify relevant scales for investigating natural or anthropogenic processes shaping these assemblages. We studied the variability of intertidal macroalgal assemblages on the North Portuguese coast, considering three spatial scales (from metres to 10 s of kilometres) following a hierarchical design. We tested the hypotheses that (1) spatial pattern will be invariant at all the studied scales and (2) spatial variability of macroalgal assemblages obtained by using species will be consistent with that obtained using functional groups. This was done considering as univariate variables: total biomass and number of taxa as well as biomass of the most important species and functional groups and as multivariate variables the structure of macroalgal assemblages, both considering species and functional groups. Most of the univariate results confirmed the first hypothesis except for the total number of taxa and foliose macroalgae that showed significant variability at the scale of site and area, respectively. In contrast, when multivariate patterns were examined, the first hypothesis was rejected except at the scale of 10 s of kilometres. Both uni- and multivariate results indicated that variation was larger at the smallest scale, and thus, small-scale processes seem to have more effect on spatial variability patterns. Macroalgal assemblages, both considering species and functional groups as surrogate, showed consistent spatial patterns, and therefore, the second hypothesis was confirmed. Consequently, functional groups may be considered a reliable biological surrogate to study changes on macroalgal assemblages at least along the investigated Portuguese coastline.

Investigation of Navier-Stokes Code Verification and Design Optimization

NASA Technical Reports Server (NTRS)

Vaidyanathan, Rajkumar

2004-01-01

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

CTEPP STANDARD OPERATING PROCEDURE FOR PREPARATION OF SURROGATE RECOVERY STANDARD AND INTERNAL STANDARD SOLUTIONS FOR NEUTRAL TARGET ANALYTES (SOP-5.25)

EPA Science Inventory

This standard operating procedure describes the method used for preparing internal standard, surrogate recovery standard and calibration standard solutions for neutral analytes used for gas chromatography/mass spectrometry analysis.

Uncertainty quantification of resonant ultrasound spectroscopy for material property and single crystal orientation estimation on a complex part

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Mayes, Alexander; Jauriqui, Leanne; Biedermann, Eric; Heffernan, Julieanne; Livings, Richard; Goodlet, Brent; Mazdiyasni, Siamack

2018-04-01

A case study is presented evaluating uncertainty in Resonance Ultrasound Spectroscopy (RUS) inversion for a single crystal (SX) Ni-based superalloy Mar-M247 cylindrical dog-bone specimens. A number of surrogate models were developed with FEM model solutions, using different sampling schemes (regular grid, Monte Carlo sampling, Latin Hyper-cube sampling) and model approaches, N-dimensional cubic spline interpolation and Kriging. Repeated studies were used to quantify the well-posedness of the inversion problem, and the uncertainty was assessed in material property and crystallographic orientation estimates given typical geometric dimension variability in aerospace components. Surrogate model quality was found to be an important factor in inversion results when the model more closely represents the test data. One important discovery was when the model matches well with test data, a Kriging surrogate model using un-sorted Latin Hypercube sampled data performed as well as the best results from an N-dimensional interpolation model using sorted data. However, both surrogate model quality and mode sorting were found to be less critical when inverting properties from either experimental data or simulated test cases with uncontrolled geometric variation.

Aerobic Exercise during Pregnancy and Presence of Fetal-Maternal Heart Rate Synchronization

PubMed Central

Van Leeuwen, Peter; Gustafson, Kathleen M.; Cysarz, Dirk; Geue, Daniel; May, Linda E.; Grönemeyer, Dietrich

2014-01-01

It has been shown that short-term direct interaction between maternal and fetal heart rates may take place and that this interaction is affected by the rate of maternal respiration. The aim of this study was to determine the effect of maternal aerobic exercise during pregnancy on the occurrence of fetal-maternal heart rate synchronization. Methods In 40 pregnant women at the 36th week of gestation, 21 of whom exercised regularly, we acquired 18 min. RR interval time series obtained simultaneously in the mothers and their fetuses from magnetocardiographic recordings. The time series of the two groups were examined with respect to their heart rate variability, the maternal respiratory rate and the presence of synchronization epochs as determined on the basis of synchrograms. Surrogate data were used to assess whether the occurrence of synchronization was due to chance. Results In the original data, we found synchronization occurred less often in pregnancies in which the mothers had exercised regularly. These subjects also displayed higher combined fetal-maternal heart rate variability and lower maternal respiratory rates. Analysis of the surrogate data showed shorter epochs of synchronization and a lack of the phase coordination found between maternal and fetal beat timing in the original data. Conclusion The results suggest that fetal-maternal heart rate coupling is present but generally weak. Maternal exercise has a damping effect on its occurrence, most likely due to an increase in beat-to-beat differences, higher vagal tone and slower breathing rates. PMID:25162592

Aerobic exercise during pregnancy and presence of fetal-maternal heart rate synchronization.

PubMed

Van Leeuwen, Peter; Gustafson, Kathleen M; Cysarz, Dirk; Geue, Daniel; May, Linda E; Grönemeyer, Dietrich

2014-01-01

It has been shown that short-term direct interaction between maternal and fetal heart rates may take place and that this interaction is affected by the rate of maternal respiration. The aim of this study was to determine the effect of maternal aerobic exercise during pregnancy on the occurrence of fetal-maternal heart rate synchronization. In 40 pregnant women at the 36th week of gestation, 21 of whom exercised regularly, we acquired 18 min. RR interval time series obtained simultaneously in the mothers and their fetuses from magnetocardiographic recordings. The time series of the two groups were examined with respect to their heart rate variability, the maternal respiratory rate and the presence of synchronization epochs as determined on the basis of synchrograms. Surrogate data were used to assess whether the occurrence of synchronization was due to chance. In the original data, we found synchronization occurred less often in pregnancies in which the mothers had exercised regularly. These subjects also displayed higher combined fetal-maternal heart rate variability and lower maternal respiratory rates. Analysis of the surrogate data showed shorter epochs of synchronization and a lack of the phase coordination found between maternal and fetal beat timing in the original data. The results suggest that fetal-maternal heart rate coupling is present but generally weak. Maternal exercise has a damping effect on its occurrence, most likely due to an increase in beat-to-beat differences, higher vagal tone and slower breathing rates.

Critical care physicians’ approaches to negotiating with surrogate decision makers: a qualitative study

PubMed Central

Brush, David R.; Brown, Crystal E.; Alexander, G. Caleb

2013-01-01

Objective To describe how critical care physicians manage conflicts with surrogates about withdrawing or withholding patients’ life support. Design Qualitative analysis of key informant interviews with critical care physicians during 2010. We transcribed interviews verbatim and used grounded theory to code and revise a taxonomy of themes and to identify illustrative quotes. Setting 3 academic medical centers, 1 academic-affiliated medical center and 4 private practice groups or private hospitals in a large Midwestern city Subjects 14 critical care physicians Measurements and main results Physicians reported tailoring their approach to address specific reasons for disagreement with surrogates. Five common approaches were identified: (1) building trust, (2) educating and informing, (3) providing surrogates more time, (4) adjusting surrogate and physician roles, and (5) highlighting specific values. When mistrust was an issue, physicians endeavored to build a more trusting relationship with the surrogate before re-addressing decision making. Physicians also reported correcting misunderstandings by providing targeted education, and some reported highlighting specific patient, surrogate, or physician values that they hoped would guide surrogates to agree with them. When surrogates struggled with decision making roles, physicians attempted to reinforce the concept of substituted judgment. Physicians noted that some surrogates needed time to “come to terms” with the patent’s illness before agreeing with physicians. Many physicians had witnessed colleagues negotiate in ways they found objectionable, such as providing misleading information, injecting their own values into the negotiation, or behaving unprofessionally towards surrogates. While some physicians viewed their efforts to encourage surrogates’ agreement as persuasive, others strongly denied persuading surrogates and described their actions as “guiding” or “negotiating.” Conclusions Physicians reported using a tailored approach to resolve decisional conflicts about life support; and attempted to change surrogates’ decisions in accordance with what the physician thought was in the patients’ best interests. While physicians acknowledged their efforts to change surrogate’s decisions, many physicians did not perceive these as persuasive. PMID:22080645

Doubt and belief in physicians' ability to prognosticate during critical illness: The perspective of surrogate decision makers

PubMed Central

Zier, Lucas S.; Burack, Jeffrey H.; Micco, Guy; Chipman, Anne K.; Frank, James A.; Luce, John M.; White, Douglas B.

2009-01-01

Objectives: Although discussing a prognosis is a duty of physicians caring for critically ill patients, little is known about surrogate decision-makers' beliefs about physicians' ability to prognosticate. We sought to determine: 1) surrogates' beliefs about whether physicians can accurately prognosticate for critically ill patients; and 2) how individuals use prognostic information in their role as surrogate decision-makers. Design, Setting, and Patients: Multicenter study in intensive care units of a public hospital, a tertiary care hospital, and a veterans' hospital. We conducted semistructured interviews with 50 surrogate decision-makers of critically ill patients. We analyzed the interview transcripts using grounded theory methods to inductively develop a framework to describe surrogates' beliefs about physicians' ability to prognosticate. Validation methods included triangulation by multidisciplinary analysis and member checking. Measurements and Main Results: Overall, 88% (44 of 50) of surrogates expressed doubt about physicians' ability to prognosticate for critically ill patients. Four distinct themes emerged that explained surrogates' doubts about prognostic accuracy: a belief that God could alter the course of the illness, a belief that predicting the future is inherently uncertain, prior experiences where physicians' prognostications were inaccurate, and experiences with prognostication during the patient's intensive care unit stay. Participants also identified several factors that led to belief in physicians' prognostications, such as receiving similar prognostic estimates from multiple physicians and prior experiences with accurate prognostication. Surrogates' doubts about prognostic accuracy did not prevent them from wanting prognostic information. Instead, most surrogate decision-makers view physicians' prognostications as rough estimates that are valuable in informing decisions, but are not determinative. Surrogates identified the act of prognostic disclosure as a key step in preparing emotionally and practically for the possibility that a patient may not survive. Conclusions: Although many surrogate decision-makers harbor some doubt about the accuracy of physicians' prognostications, they highly value discussions about prognosis and use the information for multiple purposes. (Crit Care Med 2008; 36: 2341–2347) PMID:18596630

Measures of Residual Risk with Connections to Regression, Risk Tracking, Surrogate Models, and Ambiguity

DTIC Science & Technology

2015-01-07

vector that helps to manage , predict, and mitigate the risk in the original variable. Residual risk can be exemplified as a quantification of the improved... the random variable of interest is viewed in concert with a related random vector that helps to manage , predict, and mitigate the risk in the original...measures of risk. They view a random variable of interest in concert with an auxiliary random vector that helps to manage , predict and mitigate the risk

Effects of Exposure Measurement Error in the Analysis of Health Effects from Traffic-Related Air Pollution

EPA Science Inventory

In large epidemiological studies, many researchers use surrogates of air pollution exposure such as geographic information system (GIS)-based characterizations of traffic or simple housing characteristics. It is important to validate these surrogates against measured pollutant co...

Tissue is alive: New technologies are needed to address the problems of protein biomarker pre-analytical variability.

PubMed

Espina, Virginia; Mueller, Claudius; Edmiston, Kirsten; Sciro, Manuela; Petricoin, Emanuel F; Liotta, Lance A

2009-08-01

Instability of tissue protein biomarkers is a critical issue for molecular profiling. Pre-analytical variables during tissue procurement, such as time delays during which the tissue remains stored at room temperature, can cause significant variability and bias in downstream molecular analysis. Living tissue, ex vivo, goes through a defined stage of reactive changes that begin with oxidative, hypoxic and metabolic stress, and culminate in apoptosis. Depending on the delay time ex vivo, and reactive stage, protein biomarkers, such as signal pathway phosphoproteins will be elevated or suppressed in a manner which does not represent the biomarker levels at the time of excision. Proteomic data documenting reactive tissue protein changes post collection indicate the need to recognize and address tissue stability, preservation of post-translational modifications, and preservation of morphologic features for molecular analysis. Based on the analysis of phosphoproteins, one of the most labile tissue protein biomarkers, we set forth tissue procurement guidelines for clinical research. We propose technical solutions for (i) assessing the state of protein analyte preservation and specimen quality via identification of a panel of natural proteins (surrogate stability markers), and (ii) using multi-purpose fixative solution designed to stabilize, preserve and maintain proteins, nucleic acids, and tissue architecture.

Tissue is alive: New technologies are needed to address the problems of protein biomarker pre-analytical variability

PubMed Central

Espina, Virginia; Mueller, Claudius; Edmiston, Kirsten; Sciro, Manuela; Petricoin, Emanuel F.; Liotta, Lance A.

2010-01-01

Instability of tissue protein biomarkers is a critical issue for molecular profiling. Pre-analytical variables during tissue procurement, such as time delays during which the tissue remains stored at room temperature, can cause significant variability and bias in downstream molecular analysis. Living tissue, ex vivo, goes through a defined stage of reactive changes that begin with oxidative, hypoxic and metabolic stress, and culminate in apoptosis. Depending on the delay time ex vivo, and reactive stage, protein biomarkers, such as signal pathway phosphoproteins will be elevated or suppressed in a manner which does not represent the biomarker levels at the time of excision. Proteomic data documenting reactive tissue protein changes post collection indicate the need to recognize and address tissue stability, preservation of post-translational modifications, and preservation of morphologic features for molecular analysis. Based on the analysis of phosphoproteins, one of the most labile tissue protein biomarkers, we set forth tissue procurement guidelines for clinical research. We propose technical solutions for (i) assessing the state of protein analyte preservation and specimen quality via identification of a panel of natural proteins (surrogate stability markers), and (ii) using multi-purpose fixative solution designed to stabilize, preserve and maintain proteins, nucleic acids, and tissue architecture. PMID:20871745

Parameter inference in small world network disease models with approximate Bayesian Computational methods

NASA Astrophysics Data System (ADS)

Walker, David M.; Allingham, David; Lee, Heung Wing Joseph; Small, Michael

2010-02-01

Small world network models have been effective in capturing the variable behaviour of reported case data of the SARS coronavirus outbreak in Hong Kong during 2003. Simulations of these models have previously been realized using informed “guesses” of the proposed model parameters and tested for consistency with the reported data by surrogate analysis. In this paper we attempt to provide statistically rigorous parameter distributions using Approximate Bayesian Computation sampling methods. We find that such sampling schemes are a useful framework for fitting parameters of stochastic small world network models where simulation of the system is straightforward but expressing a likelihood is cumbersome.

Using the entire history in the analysis of nested case cohort samples.

PubMed

Rivera, C L; Lumley, T

2016-08-15

Countermatching designs can provide more efficient estimates than simple matching or case-cohort designs in certain situations such as when good surrogate variables for an exposure of interest are available. We extend pseudolikelihood estimation for the Cox model under countermatching designs to models where time-varying covariates are considered. We also implement pseudolikelihood with calibrated weights to improve efficiency in nested case-control designs in the presence of time-varying variables. A simulation study is carried out, which considers four different scenarios including a binary time-dependent variable, a continuous time-dependent variable, and the case including interactions in each. Simulation results show that pseudolikelihood with calibrated weights under countermatching offers large gains in efficiency if compared to case-cohort. Pseudolikelihood with calibrated weights yielded more efficient estimators than pseudolikelihood estimators. Additionally, estimators were more efficient under countermatching than under case-cohort for the situations considered. The methods are illustrated using the Colorado Plateau uranium miners cohort. Furthermore, we present a general method to generate survival times with time-varying covariates. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Quantification of variability and uncertainty for air toxic emission inventories with censored emission factor data.

PubMed

Frey, H Christopher; Zhao, Yuchao

2004-11-15

Probabilistic emission inventories were developed for urban air toxic emissions of benzene, formaldehyde, chromium, and arsenic for the example of Houston. Variability and uncertainty in emission factors were quantified for 71-97% of total emissions, depending upon the pollutant and data availability. Parametric distributions for interunit variability were fit using maximum likelihood estimation (MLE), and uncertainty in mean emission factors was estimated using parametric bootstrap simulation. For data sets containing one or more nondetected values, empirical bootstrap simulation was used to randomly sample detection limits for nondetected values and observations for sample values, and parametric distributions for variability were fit using MLE estimators for censored data. The goodness-of-fit for censored data was evaluated by comparison of cumulative distributions of bootstrap confidence intervals and empirical data. The emission inventory 95% uncertainty ranges are as small as -25% to +42% for chromium to as large as -75% to +224% for arsenic with correlated surrogates. Uncertainty was dominated by only a few source categories. Recommendations are made for future improvements to the analysis.

The Hydrological Response of Snowmelt Dominated Catchments to Climate Change

NASA Astrophysics Data System (ADS)

Arrigoni, A. S.; Moore, J. N.

2007-12-01

Hydrological systems dominated by snowmelt discharge contribute greater than half the freshwater resource available to the western United States. Globally, the contribution of mountain discharge to total runoff is twice the expected for their geographical coverage. Therefore, snowmelt dominated mountain catchments have proportionally a more prominent role than other systems to our freshwater resource. A changing climate, or even a more variable climate, could have a significant impact on these systems, and consequently on our freshwater resource. Ergo, a better understanding of how changes and variations in climate will influence mountain catchments is a necessity for improving future water management under predicted/proposed climate change. The research presented here is a first order analysis to improve our understanding of these systems by monitoring and analyzing high mountain catchments along the entirety of the Mission Mountain Front, Montana USA. The Mission Mountain Range is an ideal location for conducting this research as it runs directly north to south with elevations progressively increasing from 7600 feet in the northern section, to over 9700 feet at the southern end. The lower elevation catchments will be used as surrogates for variable climate change, while the high elevation catchments will be used as surrogates for a more stable, cooler, climate regime. We use a combination of USGS and Tribal stream gauges, as well as stage gauge loggers in the headwaters of the catchments, SNOTEL datasets, and weather station datasets. This information is used to determine if, how, and why the snowmelt hydrographs vary between catchments, within the catchments between the upper and lower segments, and the dominant driver or drivers of the hydrograph form in relation to changing climatic variables such as temperature and precipitation. This research will improve current comprehension of how mountain catchments respond to climatic variables, and additionally will expand upon the current understanding of general catchment hydrology.

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michalski, D; Huq, M; Bednarz, G

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same ismore » for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for 4D-based clinical technologies, can be better controlled if nonlinear-based methodology, which reflects respiration characteristic, is applied. Funding provided by Varian Medical Systems via Investigator Initiated Research Project.« less

Emotional experiences in surrogate mothers: A qualitative study

PubMed Central

Ahmari Tehran, Hoda; Tashi, Shohreh; Mehran, Nahid; Eskandari, Narges; Dadkhah Tehrani, Tahmineh

2014-01-01

Background: Surrogacy is one of the new techniques of assisted reproduction technology in which a woman carries and bears a child for another woman. In Iran, many Shia clerics and jurists considered it permissible so there is no religious prohibition for it. In addition to the risk of physical complications for complete surrogate mothers, the possibility of psychological complications resulted from emotional attachment to a living creature in the surrogate mother as another injury requires counseling and assessment prior to acceptance by infertile couples and complete surrogate mothers. Objective: The purpose of this study was to assess the emotional experiences of surrogate mothers. Materials and Methods: This was a qualitative, phenomenological study. We selected eight complete surrogate mothers in Isfahan. We used convenient sampling method and in-depth interview to collect the information. The data analysis was fulfilled via Colaizzi’s seven-stage method. Reliability and validity study of the roots in the four-axis was done. Results: The findings of these interviews were classified into two main themes and four sub themes: acquired experiences in pregnancy (feelings toward pregnancy, relationship with family, relatives and commissioning couple) and consequences of surrogacy (complications of pregnancy, religious and financial problems of surrogacy). Conclusion: Surrogacy pregnancy should be considered as high-risk emotional experience because many of surrogate mothers may face negative experiences. Therefore, it is recommended that surrogates should receive professional counseling prior to, during and following pregnancy. PMID:25114669

Hypothesis test for synchronization: twin surrogates revisited.

PubMed

Romano, M Carmen; Thiel, Marco; Kurths, Jürgen; Mergenthaler, Konstantin; Engbert, Ralf

2009-03-01

The method of twin surrogates has been introduced to test for phase synchronization of complex systems in the case of passive experiments. In this paper we derive new analytical expressions for the number of twins depending on the size of the neighborhood, as well as on the length of the trajectory. This allows us to determine the optimal parameters for the generation of twin surrogates. Furthermore, we determine the quality of the twin surrogates with respect to several linear and nonlinear statistics depending on the parameters of the method. In the second part of the paper we perform a hypothesis test for phase synchronization in the case of experimental data from fixational eye movements. These miniature eye movements have been shown to play a central role in neural information processing underlying the perception of static visual scenes. The high number of data sets (21 subjects and 30 trials per person) allows us to compare the generated twin surrogates with the "natural" surrogates that correspond to the different trials. We show that the generated twin surrogates reproduce very well all linear and nonlinear characteristics of the underlying experimental system. The synchronization analysis of fixational eye movements by means of twin surrogates reveals that the synchronization between the left and right eye is significant, indicating that either the centers in the brain stem generating fixational eye movements are closely linked, or, alternatively that there is only one center controlling both eyes.

Emotional experiences in surrogate mothers: A qualitative study.

PubMed

Ahmari Tehran, Hoda; Tashi, Shohreh; Mehran, Nahid; Eskandari, Narges; Dadkhah Tehrani, Tahmineh

2014-07-01

Surrogacy is one of the new techniques of assisted reproduction technology in which a woman carries and bears a child for another woman. In Iran, many Shia clerics and jurists considered it permissible so there is no religious prohibition for it. In addition to the risk of physical complications for complete surrogate mothers, the possibility of psychological complications resulted from emotional attachment to a living creature in the surrogate mother as another injury requires counseling and assessment prior to acceptance by infertile couples and complete surrogate mothers. The purpose of this study was to assess the emotional experiences of surrogate mothers. This was a qualitative, phenomenological study. We selected eight complete surrogate mothers in Isfahan. We used convenient sampling method and in-depth interview to collect the information. The data analysis was fulfilled via Colaizzi's seven-stage method. Reliability and validity study of the roots in the four-axis was done. The findings of these interviews were classified into two main themes and four sub themes: acquired experiences in pregnancy (feelings toward pregnancy, relationship with family, relatives and commissioning couple) and consequences of surrogacy (complications of pregnancy, religious and financial problems of surrogacy). Surrogacy pregnancy should be considered as high-risk emotional experience because many of surrogate mothers may face negative experiences. Therefore, it is recommended that surrogates should receive professional counseling prior to, during and following pregnancy.

Does the decision in a validation process of a surrogate endpoint change with level of significance of treatment effect? A proposal on validation of surrogate endpoints.

PubMed

Sertdemir, Y; Burgut, R

2009-01-01

In recent years the use of surrogate end points (S) has become an interesting issue. In clinical trials, it is important to get treatment outcomes as early as possible. For this reason there is a need for surrogate endpoints (S) which are measured earlier than the true endpoint (T). However, before a surrogate endpoint can be used it must be validated. For a candidate surrogate endpoint, for example time to recurrence, the validation result may change dramatically between clinical trials. The aim of this study is to show how the validation criterion (R(2)(trial)) proposed by Buyse et al. are influenced by the magnitude of treatment effect with an application using real data. The criterion R(2)(trial) proposed by Buyse et al. (2000) is applied to the four data sets from colon cancer clinical trials (C-01, C-02, C-03 and C-04). Each clinical trial is analyzed separately for treatment effect on survival (true endpoint) and recurrence free survival (surrogate endpoint) and this analysis is done also for each center in each trial. Results are used for standard validation analysis. The centers were grouped by the Wald statistic in 3 equal groups. Validation criteria R(2)(trial) were 0.641 95% CI (0.432-0.782), 0.223 95% CI (0.008-0.503), 0.761 95% CI (0.550-0.872) and 0.560 95% CI (0.404-0.687) for C-01, C-02, C-03 and C-04 respectively. The R(2)(trial) criteria changed by the Wald statistics observed for the centers used in the validation process. Higher the Wald statistic groups are higher the R(2)(trial) values observed. The recurrence free survival is not a good surrogate for overall survival in clinical trials with non significant treatment effects and moderate for significant treatment effects. This shows that the level of significance of treatment effect should be taken into account in validation process of surrogate endpoints.

Effectiveness of Biodiversity Surrogates for Conservation Planning: Different Measures of Effectiveness Generate a Kaleidoscope of Variation

PubMed Central

Grantham, Hedley S.; Pressey, Robert L.; Wells, Jessie A.; Beattie, Andrew J.

2010-01-01

Conservation planners represent many aspects of biodiversity by using surrogates with spatial distributions readily observed or quantified, but tests of their effectiveness have produced varied and conflicting results. We identified four factors likely to have a strong influence on the apparent effectiveness of surrogates: (1) the choice of surrogate; (2) differences among study regions, which might be large and unquantified (3) the test method, that is, how effectiveness is quantified, and (4) the test features that the surrogates are intended to represent. Analysis of an unusually rich dataset enabled us, for the first time, to disentangle these factors and to compare their individual and interacting influences. Using two data-rich regions, we estimated effectiveness using five alternative methods: two forms of incidental representation, two forms of species accumulation index and irreplaceability correlation, to assess the performance of ‘forest ecosystems’ and ‘environmental units’ as surrogates for six groups of threatened species—the test features—mammals, birds, reptiles, frogs, plants and all of these combined. Four methods tested the effectiveness of the surrogates by selecting areas for conservation of the surrogates then estimating how effective those areas were at representing test features. One method measured the spatial match between conservation priorities for surrogates and test features. For methods that selected conservation areas, we measured effectiveness using two analytical approaches: (1) when representation targets for the surrogates were achieved (incidental representation), or (2) progressively as areas were selected (species accumulation index). We estimated the spatial correlation of conservation priorities using an index known as summed irreplaceability. In general, the effectiveness of surrogates for our taxa (mostly threatened species) was low, although environmental units tended to be more effective than forest ecosystems. The surrogates were most effective for plants and mammals and least effective for frogs and reptiles. The five testing methods differed in their rankings of effectiveness of the two surrogates in relation to different groups of test features. There were differences between study areas in terms of the effectiveness of surrogates for different test feature groups. Overall, the effectiveness of the surrogates was sensitive to all four factors. This indicates the need for caution in generalizing surrogacy tests. PMID:20644726

Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals.

PubMed

Hedayatifar, L; Vahabi, M; Jafari, G R

2011-08-01

When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.

Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals

NASA Astrophysics Data System (ADS)

Hedayatifar, L.; Vahabi, M.; Jafari, G. R.

2011-08-01

When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.

A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

NASA Astrophysics Data System (ADS)

Yondo, Raul; Andrés, Esther; Valero, Eusebio

2018-01-01

Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-order) aerodynamic models or flight testing are some of the fundamental but complex steps in the various design phases of recent civil transport aircrafts. Current aircraft aerodynamic designs have increase in complexity (multidisciplinary, multi-objective or multi-fidelity) and need to address the challenges posed by the nonlinearity of the objective functions and constraints, uncertainty quantification in aerodynamic problems or the restrained computational budgets. With the aim to reduce the computational burden and generate low-cost but accurate models that mimic those full order models at different values of the design variables, Recent progresses have witnessed the introduction, in real-time and many-query analyses, of surrogate-based approaches as rapid and cheaper to simulate models. In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria. Benefits, drawbacks and comparative discussions in applying those methods are described. Furthermore, the paper familiarizes the readers with surrogate models that have been successfully applied to the general field of fluid dynamics, but not yet in the aerospace industry. Additionally, the review revisits the most popular sampling strategies used in conducting physical and simulation-based experiments in aircraft aerodynamic design. Attractive or smart designs infrequently used in the field and discussions on advanced sampling methodologies are presented, to give a glance on the various efficient possibilities to a priori sample the parameter space. Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial aerodynamicists, despite their increased interest among the research communities.

Fractal fluctuations in spatiotemporal variables when walking on a self-paced treadmill.

PubMed

Choi, Jin-Seung; Kang, Dong-Won; Seo, Jeong-Woo; Tack, Gye-Rae

2017-12-08

This study investigated the fractal dynamic properties of stride time (ST), stride length (SL) and stride speed (SS) during walking on a self-paced treadmill (STM) in which the belt speed is automatically controlled by the walking speed. Twelve healthy young subjects participated in the study. The subjects walked at their preferred walking speed under four conditions: STM, STM with a metronome (STM+met), fixed-speed (conventional) treadmill (FTM), and FTM with a metronome (FTM+met). To compare the fractal dynamics between conditions, the mean, variability, and fractal dynamics of ST, SL, and SS were compared. Moreover, the relationship among the variables was examined under each walking condition using three types of surrogates. The mean values of all variables did not differ between the two treadmills, and the variability of all variables was generally larger for STM than for FTM. The use of a metronome resulted in a decrease in variability in ST and SS for all conditions. The fractal dynamic characteristics of SS were maintained with STM, in contrast to FTM, and only the fractal dynamic characteristics of ST disappeared when using a metronome. In addition, the fractal dynamic patterns of the cross-correlated surrogate results were identical to those of all variables for the two treadmills. In terms of the fractal dynamic properties, STM walking was generally closer to overground walking than FTM walking. Although further research is needed, the present results will be useful in research on gait fractal dynamics and rehabilitation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints

PubMed Central

Thompson, John R; Spata, Enti; Abrams, Keith R

2015-01-01

We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing–remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions. PMID:26271918

Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints.

PubMed

Bujkiewicz, Sylwia; Thompson, John R; Spata, Enti; Abrams, Keith R

2017-10-01

We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing-remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions.

Identification of five chronic obstructive pulmonary disease subgroups with different prognoses in the ECLIPSE cohort using cluster analysis.

PubMed

Rennard, Stephen I; Locantore, Nicholas; Delafont, Bruno; Tal-Singer, Ruth; Silverman, Edwin K; Vestbo, Jørgen; Miller, Bruce E; Bakke, Per; Celli, Bartolomé; Calverley, Peter M A; Coxson, Harvey; Crim, Courtney; Edwards, Lisa D; Lomas, David A; MacNee, William; Wouters, Emiel F M; Yates, Julie C; Coca, Ignacio; Agustí, Alvar

2015-03-01

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that likely includes clinically relevant subgroups. To identify subgroups of COPD in ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) subjects using cluster analysis and to assess clinically meaningful outcomes of the clusters during 3 years of longitudinal follow-up. Factor analysis was used to reduce 41 variables determined at recruitment in 2,164 patients with COPD to 13 main factors, and the variables with the highest loading were used for cluster analysis. Clusters were evaluated for their relationship with clinically meaningful outcomes during 3 years of follow-up. The relationships among clinical parameters were evaluated within clusters. Five subgroups were distinguished using cross-sectional clinical features. These groups differed regarding outcomes. Cluster A included patients with milder disease and had fewer deaths and hospitalizations. Cluster B had less systemic inflammation at baseline but had notable changes in health status and emphysema extent. Cluster C had many comorbidities, evidence of systemic inflammation, and the highest mortality. Cluster D had low FEV1, severe emphysema, and the highest exacerbation and COPD hospitalization rate. Cluster E was intermediate for most variables and may represent a mixed group that includes further clusters. The relationships among clinical variables within clusters differed from that in the entire COPD population. Cluster analysis using baseline data in ECLIPSE identified five COPD subgroups that differ in outcomes and inflammatory biomarkers and show different relationships between clinical parameters, suggesting the clusters represent clinically and biologically different subtypes of COPD.

Convergence analysis of surrogate-based methods for Bayesian inverse problems

NASA Astrophysics Data System (ADS)

Yan, Liang; Zhang, Yuan-Xiang

2017-12-01

The major challenges in the Bayesian inverse problems arise from the need for repeated evaluations of the forward model, as required by Markov chain Monte Carlo (MCMC) methods for posterior sampling. Many attempts at accelerating Bayesian inference have relied on surrogates for the forward model, typically constructed through repeated forward simulations that are performed in an offline phase. Although such approaches can be quite effective at reducing computation cost, there has been little analysis of the approximation on posterior inference. In this work, we prove error bounds on the Kullback-Leibler (KL) distance between the true posterior distribution and the approximation based on surrogate models. Our rigorous error analysis show that if the forward model approximation converges at certain rate in the prior-weighted L 2 norm, then the posterior distribution generated by the approximation converges to the true posterior at least two times faster in the KL sense. The error bound on the Hellinger distance is also provided. To provide concrete examples focusing on the use of the surrogate model based methods, we present an efficient technique for constructing stochastic surrogate models to accelerate the Bayesian inference approach. The Christoffel least squares algorithms, based on generalized polynomial chaos, are used to construct a polynomial approximation of the forward solution over the support of the prior distribution. The numerical strategy and the predicted convergence rates are then demonstrated on the nonlinear inverse problems, involving the inference of parameters appearing in partial differential equations.

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

NASA Technical Reports Server (NTRS)

Zwack, Mathew R.; Dees, Patrick D.; Holt, James B.

2016-01-01

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are fit to the outputs of each environment and are "integrated" via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any ''what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will help ensure lower LCC of launch vehicle designs originating from ACO.

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

NASA Technical Reports Server (NTRS)

Zwack, Mathew R.; Dees, Patrick D.; Holt, James B.

2016-01-01

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases.1 Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission.2 Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an Advanced Design Methods (ADM) based approach. This approach applies the concepts of Design of Experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development e ort. In order to t a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of Ground Rules and Assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated \\what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are t to the outputs of each environment and are integrated via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any \\what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will have the potential to lower LCC of launch vehicle designs originating from ACO.

Surrogate endpoints for overall survival in combined chemotherapy and radiotherapy trials in nasopharyngeal carcinoma: Meta-analysis of randomised controlled trials.

PubMed

Chen, Yu-Pei; Sun, Ying; Chen, Lei; Mao, Yan-Ping; Tang, Ling-Long; Li, Wen-Fei; Liu, Xu; Zhang, Wen-Na; Zhou, Guan-Qun; Guo, Rui; Lin, Ai-Hua; Ma, Jun

2015-08-01

We used a literature-based meta-analysis to assess whether failure-free survival (FFS) or progression-free survival (PFS) could be reliable surrogate endpoints for overall survival (OS) in trials of combined chemotherapy and radiotherapy for nasopharyngeal carcinoma (NPC). We identified randomised trials that evaluated combined chemoradiotherapy strategies, and reported FFS or PFS and OS in NPC. We analysed the treatment effects on FFS or PFS, and OS. We used the coefficient of determination (R(2)), and the surrogate threshold effect (STE) to assess the trial-level correlation. Twenty-one trials (5212 patients), with sixteen treatment-control comparisons for FFS, and nine for PFS, were analysed. FFS was strongly correlated with OS (R(2)=0.88, STE=0.84), as was PFS (R(2)=0.90, STE=0.88). Moreover, FFS and PFS at 3 years were still strongly correlated with 5-year OS (R(2)=0.80, STE=0.83; R(2)=0.85, STE=0.84). Both FFS and PFS could be valid surrogate endpoints for OS in trials of combined chemotherapy and radiotherapy for NPC; PFS may be a more acceptable surrogate endpoint compared with FFS. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Characterizing Ohio River NOM Variability and Reconstituted-Lyophilized NOM as a Source Surrogate

EPA Science Inventory

Surface water contains natural organic matter (NOM) that reacts with disinfectants creating disinfection byproducts (DBPs), some of which are USEPA regulated contaminants. Characterizing NOM can provide insight with respect to DBP formation and water treatment process adaptation...

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; Zhang, Guannan; Ye, Ming; Wu, Jianfeng; Wu, Jichun

2017-12-01

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

Parametric geometric model and hydrodynamic shape optimization of a flying-wing structure underwater glider

NASA Astrophysics Data System (ADS)

Wang, Zhen-yu; Yu, Jian-cheng; Zhang, Ai-qun; Wang, Ya-xing; Zhao, Wen-tao

2017-12-01

Combining high precision numerical analysis methods with optimization algorithms to make a systematic exploration of a design space has become an important topic in the modern design methods. During the design process of an underwater glider's flying-wing structure, a surrogate model is introduced to decrease the computation time for a high precision analysis. By these means, the contradiction between precision and efficiency is solved effectively. Based on the parametric geometry modeling, mesh generation and computational fluid dynamics analysis, a surrogate model is constructed by adopting the design of experiment (DOE) theory to solve the multi-objects design optimization problem of the underwater glider. The procedure of a surrogate model construction is presented, and the Gaussian kernel function is specifically discussed. The Particle Swarm Optimization (PSO) algorithm is applied to hydrodynamic design optimization. The hydrodynamic performance of the optimized flying-wing structure underwater glider increases by 9.1%.

Simultaneous Thermal Analysis of Remediated Nitrate Salt Surrogates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wayne, David Matthew

The actinide engineering and science group (MET-1) have completed simultaneous thermal analysis and offgas analysis by mass spectrometry (STA-MS) of remediated nitrate salt (RNS) surrogates formulated by the high explosives science and technology group (M-7). The 1.0 to 1.5g surrogate samples were first analyzed as received, then a new set was analyzed with 100-200mL 10M HNO 3 +0.3 MHF added, and a third set was analyzed after 200 mL of a concentrated Pu-AM spike (in 10M HNO 3 +0.3 MHF) was added. The acid and spike solutions were formulated by the actinide analytical chemistry group (C-AAC) using reagent-grade HNO 3more » and HF, which was also used to dissolve a small quantity of mixed, high-fired PuO 2/ AmO 2 oxide.« less

Recurrent patterns of atrial depolarization during atrial fibrillation assessed by recurrence plot quantification.

PubMed

Censi, F; Barbaro, V; Bartolini, P; Calcagnini, G; Michelucci, A; Gensini, G F; Cerutti, S

2000-01-01

The aim of this study was to determine the presence of organization of atrial activation processes during atrial fibrillation (AF) by assessing whether the activation sequences are wholly random or are governed by deterministic mechanisms. We performed both linear and nonlinear analyses based on the cross correlation function (CCF) and recurrence plot quantification (RPQ), respectively. Recurrence plots were quantified by three variables: percent recurrence (PR), percent determinism (PD), and entropy of recurrences (ER). We recorded bipolar intra-atrial electrograms in two atrial sites during chronic AF in 19 informed subjects, following two protocols. In one, both recording sites were in the right atrium; in the other protocol, one site was in the right atrium, the other one in the left atrium. We extracted 19 episodes of type I AF (Wells' classification). RPQ detected transient recurrent patterns in all the episodes, while CCF was significant only in ten episodes. Surrogate data analysis, based on a cross-phase randomization procedure, decreased PR, PD, and ER values. The detection of spatiotemporal recurrent patterns together with the surrogate data results indicate that during AF a certain degree of local organization exists, likely caused by deterministic mechanisms of activation.

Constrained optimization by radial basis function interpolation for high-dimensional expensive black-box problems with infeasible initial points

NASA Astrophysics Data System (ADS)

Regis, Rommel G.

2014-02-01

This article develops two new algorithms for constrained expensive black-box optimization that use radial basis function surrogates for the objective and constraint functions. These algorithms are called COBRA and Extended ConstrLMSRBF and, unlike previous surrogate-based approaches, they can be used for high-dimensional problems where all initial points are infeasible. They both follow a two-phase approach where the first phase finds a feasible point while the second phase improves this feasible point. COBRA and Extended ConstrLMSRBF are compared with alternative methods on 20 test problems and on the MOPTA08 benchmark automotive problem (D.R. Jones, Presented at MOPTA 2008), which has 124 decision variables and 68 black-box inequality constraints. The alternatives include a sequential penalty derivative-free algorithm, a direct search method with kriging surrogates, and two multistart methods. Numerical results show that COBRA algorithms are competitive with Extended ConstrLMSRBF and they generally outperform the alternatives on the MOPTA08 problem and most of the test problems.

Empirical relationships among atmospheric variables from rawinsonde and field data as surrogates for AVIRIS measurements: Estimation of regional land surface evapotranspiration

NASA Technical Reports Server (NTRS)

Conel, James E.; Hoover, Gordon; Nolin, Anne; Alley, Ron; Margolis, Jack

1992-01-01

Empirical relationships between variables are ways of securing estimates of quantities difficult to measure by remote sensing methods. The use of empirical functions was explored between: (1) atmospheric column moisture abundance W (gm H2O/cm(sup 2) and surface absolute water vapor density rho(q-bar) (gm H2O/cm(sup 3), with rho density of moist air (gm/cm(sup 3), q-bar specific humidity (gm H2O/gm moist air), and (2) column abundance and surface moisture flux E (gm H2O/(cm(sup 2)sec)) to infer regional evapotranspiration from Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) water vapor mapping data. AVIRIS provides, via analysis of atmospheric water absorption features, estimates of column moisture abundance at very high mapping rate (at approximately 100 km(sup 2)/40 sec) over large areas at 20 m ground resolution.

Quantification of free and total desmosine and isodesmosine in human urine by liquid chromatography tandem mass spectrometry: a comparison of the surrogate-analyte and the surrogate-matrix approach for quantitation.

PubMed

Ongay, Sara; Hendriks, Gert; Hermans, Jos; van den Berge, Maarten; ten Hacken, Nick H T; van de Merbel, Nico C; Bischoff, Rainer

2014-01-24

In spite of the data suggesting the potential of urinary desmosine (DES) and isodesmosine (IDS) as biomarkers for elevated lung elastic fiber turnover, further validation in large-scale studies of COPD populations, as well as the analysis of longitudinal samples is required. Validated analytical methods that allow the accurate and precise quantification of DES and IDS in human urine are mandatory in order to properly evaluate the outcome of such clinical studies. In this work, we present the development and full validation of two methods that allow DES and IDS measurement in human urine, one for the free and one for the total (free+peptide-bound) forms. To this end we compared the two principle approaches that are used for the absolute quantification of endogenous compounds in biological samples, analysis against calibrators containing authentic analyte in surrogate matrix or containing surrogate analyte in authentic matrix. The validated methods were employed for the analysis of a small set of samples including healthy never-smokers, healthy current-smokers and COPD patients. This is the first time that the analysis of urinary free DES, free IDS, total DES, and total IDS has been fully validated and that the surrogate analyte approach has been evaluated for their quantification in biological samples. Results indicate that the presented methods have the necessary quality and level of validation to assess the potential of urinary DES and IDS levels as biomarkers for the progression of COPD and the effect of therapeutic interventions. Copyright © 2014 Elsevier B.V. All rights reserved.

Exposure Classification and Temporal Variability in Urinary Bisphenol A Concentrations among Couples in Utah--The HOPE Study.

PubMed

Cox, Kyley J; Porucznik, Christina A; Anderson, David J; Brozek, Eric M; Szczotka, Kathryn M; Bailey, Nicole M; Wilkins, Diana G; Stanford, Joseph B

2016-04-01

Bisphenol A (BPA) is an endocrine disruptor and potential reproductive toxicant, but results of epidemiologic studies have been mixed and have been criticized for inadequate exposure assessment that often relies on a single measurement. Our goal was to describe the distribution of BPA concentrations in serial urinary specimens, assess temporal variability, and provide estimates of exposure classification when randomly selected samples are used to predict average exposure. We collected and analyzed 2,614 urine specimens from 83 Utah couples beginning in 2012. Female participants collected daily first-morning urine specimens during one to two menstrual cycles and male partners collected specimens during the woman's fertile window for each cycle. We measured urinary BPA concentrations and calculated geometric means (GM) for each cycle, characterized the distribution of observed values and temporal variability using intraclass correlation coefficients, and performed surrogate category analyses to determine how well repeat samples could classify exposure. The GM urine BPA concentration was 2.78 ng/mL among males and 2.44 ng/mL among females. BPA had a high degree of variability among both males (ICC = 0.18; 95% CI: 0.11, 0.26) and females (ICC = 0.11; 95% CI: 0.08, 0.16). Based on our more stringent surrogate category analysis, to reach proportions ≥ 0.80 for sensitivity, specificity, and positive predictive value (PPV) among females, 6 and 10 repeat samples for the high and low tertiles, respectively, were required. For the medium tertile, specificity reached 0.87 with 10 repeat samples, but even with 11 samples, sensitivity and PPV did not exceed 0.36. Five repeat samples, among males, yielded sensitivity and PPV values ≥ 0.75 for the high and low tertiles, but, similar to females, classification for the medium tertile was less accurate. Repeated urinary specimens are required to characterize typical BPA exposure. Cox KJ, Porucznik CA, Anderson DJ, Brozek EM, Szczotka KM, Bailey NM, Wilkins DG, Stanford JB. 2016. Exposure classification and temporal variability in urinary bisphenol A concentrations among couples in Utah-the HOPE study. Environ Health Perspect 124:498-506; http://dx.doi.org/10.1289/ehp.1509752.

Narrative Interest Standard: A Novel Approach to Surrogate Decision-Making for People With Dementia.

PubMed

Wilkins, James M

2017-06-17

Dementia is a common neurodegenerative process that can significantly impair decision-making capacity as the disease progresses. When a person is found to lack capacity to make a decision, a surrogate decision-maker is generally sought to aid in decision-making. Typical bases for surrogate decision-making include the substituted judgment standard and the best interest standard. Given the heterogeneous and progressive course of dementia, however, these standards for surrogate decision-making are often insufficient in providing guidance for the decision-making for a person with dementia, escalating the likelihood of conflict in these decisions. In this article, the narrative interest standard is presented as a novel and more appropriate approach to surrogate decision-making for people with dementia. Through case presentation and ethical analysis, the standard mechanisms for surrogate decision-making for people with dementia are reviewed and critiqued. The narrative interest standard is then introduced and discussed as a dementia-specific model for surrogate decision-making. Through incorporation of elements of a best interest standard in focusing on the current benefit-burden ratio and elements of narrative to provide context, history, and flexibility for values and preferences that may change over time, the narrative interest standard allows for elaboration of an enriched context for surrogate decision-making for people with dementia. More importantly, however, a narrative approach encourages the direct contribution from people with dementia in authoring the story of what matters to them in their lives.

Enhancing non-motorized safety by simulating non-motorized exposure using a transportation planning approach : final report.

DOT National Transportation Integrated Search

2016-06-01

Safety researchers and analysists have employed land use and urban form variables as surrogates for traffic exposure information (pedestrian and bicyclist volumes and vehicular traffic). The quality of these crash prediction models is affected by the...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lei, Huan; Yang, Xiu; Zheng, Bin

Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational “active space” random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance ofmore » the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Finally, our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lei, Huan; Yang, Xiu; Zheng, Bin

Biomolecules exhibit conformational fluctuations near equilibrium states, inducing uncertainty in various biological properties in a dynamic way. We have developed a general method to quantify the uncertainty of target properties induced by conformational fluctuations. Using a generalized polynomial chaos (gPC) expansion, we construct a surrogate model of the target property with respect to varying conformational states. We also propose a method to increase the sparsity of the gPC expansion by defining a set of conformational “active space” random variables. With the increased sparsity, we employ the compressive sensing method to accurately construct the surrogate model. We demonstrate the performance ofmore » the surrogate model by evaluating fluctuation-induced uncertainty in solvent-accessible surface area for the bovine trypsin inhibitor protein system and show that the new approach offers more accurate statistical information than standard Monte Carlo approaches. Further more, the constructed surrogate model also enables us to directly evaluate the target property under various conformational states, yielding a more accurate response surface than standard sparse grid collocation methods. In particular, the new method provides higher accuracy in high-dimensional systems, such as biomolecules, where sparse grid performance is limited by the accuracy of the computed quantity of interest. Our new framework is generalizable and can be used to investigate the uncertainty of a wide variety of target properties in biomolecular systems.« less

Experimental Design for a Sponge-Wipe Study to Relate the Recovery Efficiency and False Negative Rate to the Concentration of a Bacillus anthracis Surrogate for Six Surface Materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piepel, Gregory F.; Amidan, Brett G.; Krauter, Paula

2011-05-01

Two concerns were raised by the Government Accountability Office following the 2001 building contaminations via letters containing Bacillus anthracis (BA). These included the: 1) lack of validated sampling methods, and 2) need to use statistical sampling to quantify the confidence of no contamination when all samples have negative results. Critical to addressing these concerns is quantifying the false negative rate (FNR). The FNR may depend on the 1) method of contaminant deposition, 2) surface concentration of the contaminant, 3) surface material being sampled, 4) sample collection method, 5) sample storage/transportation conditions, 6) sample processing method, and 7) sample analytical method.more » A review of the literature found 17 laboratory studies that focused on swab, wipe, or vacuum samples collected from a variety of surface materials contaminated by BA or a surrogate, and used culture methods to determine the surface contaminant concentration. These studies quantified performance of the sampling and analysis methods in terms of recovery efficiency (RE) and not FNR (which left a major gap in available information). Quantifying the FNR under a variety of conditions is a key aspect of validating sample and analysis methods, and also for calculating the confidence in characterization or clearance decisions based on a statistical sampling plan. A laboratory study was planned to partially fill the gap in FNR results. This report documents the experimental design developed by Pacific Northwest National Laboratory and Sandia National Laboratories (SNL) for a sponge-wipe method. The testing was performed by SNL and is now completed. The study investigated the effects on key response variables from six surface materials contaminated with eight surface concentrations of a BA surrogate (Bacillus atrophaeus). The key response variables include measures of the contamination on test coupons of surface materials tested, contamination recovered from coupons by sponge-wipe samples, RE, and FNR. The experimental design involves 16 test runs, performed in two blocks of eight runs. Three surface materials (stainless steel, vinyl tile, and ceramic tile) were tested in the first block, while three other surface materials (plastic, painted wood paneling, and faux leather) were tested in the second block. The eight surface concentrations of the surrogate were randomly assigned to test runs within each block. Some of the concentrations were very low and presented challenges for deposition, sampling, and analysis. However, such tests are needed to investigate RE and FNR over the full range of concentrations of interest. In each run, there were 10 test coupons of each of the three surface materials. A positive control sample was generated at the same time as each test sample. The positive control results will be used to 1) calculate RE values for the wipe sampling and analysis method, and 2) fit RE- and FNR-concentration equations, for each of the six surface materials. Data analyses will support 1) estimating the FNR for each combination of contaminant concentration and surface material, 2) estimating the surface concentrations and their uncertainties of the contaminant for each combination of concentration and surface material, 3) estimating RE (%) and their uncertainties for each combination of contaminant concentration and surface material, 4) fitting FNR-concentration and RE-concentration equations for each of the six surface materials, 5) assessing goodness-of-fit of the equations, and 6) quantifying the uncertainty in FNR and RE predictions made with the fitted equations.« less

Experimental Design for a Sponge-Wipe Study to Relate the Recovery Efficiency and False Negative Rate to the Concentration of a Bacillus anthracis Surrogate for Six Surface Materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piepel, Gregory F.; Amidan, Brett G.; Krauter, Paula

2010-12-16

Two concerns were raised by the Government Accountability Office following the 2001 building contaminations via letters containing Bacillus anthracis (BA). These included the: 1) lack of validated sampling methods, and 2) need to use statistical sampling to quantify the confidence of no contamination when all samples have negative results. Critical to addressing these concerns is quantifying the probability of correct detection (PCD) (or equivalently the false negative rate FNR = 1 - PCD). The PCD/FNR may depend on the 1) method of contaminant deposition, 2) surface concentration of the contaminant, 3) surface material being sampled, 4) sample collection method, 5)more » sample storage/transportation conditions, 6) sample processing method, and 7) sample analytical method. A review of the literature found 17 laboratory studies that focused on swab, wipe, or vacuum samples collected from a variety of surface materials contaminated by BA or a surrogate, and used culture methods to determine the surface contaminant concentration. These studies quantified performance of the sampling and analysis methods in terms of recovery efficiency (RE) and not PCD/FNR (which left a major gap in available information). Quantifying the PCD/FNR under a variety of conditions is a key aspect of validating sample and analysis methods, and also for calculating the confidence in characterization or clearance decisions based on a statistical sampling plan. A laboratory study was planned to partially fill the gap in PCD/FNR results. This report documents the experimental design developed by Pacific Northwest National Laboratory and Sandia National Laboratories (SNL) for a sponge-wipe method. The study will investigate the effects on key response variables from six surface materials contaminated with eight surface concentrations of a BA surrogate (Bacillus atrophaeus). The key response variables include measures of the contamination on test coupons of surface materials tested, contamination recovered from coupons by sponge-wipe samples, RE, and PCD/FNR. The experimental design involves 16 test runs, to be performed in two blocks of eight runs. Three surface materials (stainless steel, vinyl tile, and ceramic tile) were tested in the first block, while three other surface materials (plastic, painted wood paneling, and faux leather) will be tested in the second block. The eight surface concentrations of the surrogate were randomly assigned to test runs within each block. Some of the concentrations will be very low and may present challenges for deposition, sampling, and analysis. However, such tests are needed to investigate RE and PCD/FNR over the full range of concentrations of interest. In each run, there will be 10 test coupons of each of the three surface materials. A positive control sample will be generated prior to each test sample. The positive control results will be used to 1) calculate RE values for the wipe sampling and analysis method, and 2) fit RE- and PCD-concentration equations, for each of the six surface materials. Data analyses will support 1) estimating the PCD for each combination of contaminant concentration and surface material, 2) estimating the surface concentrations and their uncertainties of the contaminant for each combination of concentration and surface material, 3) estimating RE (%) and their uncertainties for each combination of contaminant concentration and surface material, 4) fitting PCD-concentration and RE-concentration equations for each of the six surface materials, 5) assessing goodness-of-fit of the equations, and 6) quantifying the uncertainty in PCD and RE predictions made with the fitted equations.« less

Comparison between Surrogate Indexes of Insulin Sensitivity/Resistance and Hyperinsulinemic Euglycemic Glucose Clamps in Rhesus Monkeys

PubMed Central

Lee, Ho-Won; Muniyappa, Ranganath; Yan, Xu; Yue, Lilly Q.; Linden, Ellen H.; Chen, Hui; Hansen, Barbara C.

2011-01-01

The euglycemic glucose clamp is the reference method for assessing insulin sensitivity in humans and animals. However, clamps are ill-suited for large studies because of extensive requirements for cost, time, labor, and technical expertise. Simple surrogate indexes of insulin sensitivity/resistance including quantitative insulin-sensitivity check index (QUICKI) and homeostasis model assessment (HOMA) have been developed and validated in humans. However, validation studies of QUICKI and HOMA in both rats and mice suggest that differences in metabolic physiology between rodents and humans limit their value in rodents. Rhesus monkeys are a species more similar to humans than rodents. Therefore, in the present study, we evaluated data from 199 glucose clamp studies obtained from a large cohort of 86 monkeys with a broad range of insulin sensitivity. Data were used to evaluate simple surrogate indexes of insulin sensitivity/resistance (QUICKI, HOMA, Log HOMA, 1/HOMA, and 1/Fasting insulin) with respect to linear regression, predictive accuracy using a calibration model, and diagnostic performance using receiver operating characteristic. Most surrogates had modest linear correlations with SIClamp (r ≈ 0.4–0.64) with comparable correlation coefficients. Predictive accuracy determined by calibration model analysis demonstrated better predictive accuracy of QUICKI than HOMA and Log HOMA. Receiver operating characteristic analysis showed equivalent sensitivity and specificity of most surrogate indexes to detect insulin resistance. Thus, unlike in rodents but similar to humans, surrogate indexes of insulin sensitivity/resistance including QUICKI and log HOMA may be reasonable to use in large studies of rhesus monkeys where it may be impractical to conduct glucose clamp studies. PMID:21209021

Analysis of safety impacts of access management alternatives using the surrogate safety assessment model : final report.

DOT National Transportation Integrated Search

2017-06-01

The purpose of this study was to evaluate if the Surrogate Safety Assessment Model (SSAM) could be used to assess the safety of a highway segment or an intersection in terms of the number and type of conflicts and to compare the safety effects of mul...

CTEPP STANDARD OPERATING PROCEDURE FOR PREPARATION OF SURROGATE RECOVERY STANDARD AND INTERNAL STANDARD SOLUTIONS FOR POLAR TARGET ANALYTES (SOP-5.26)

EPA Science Inventory

This SOP describes the method used for preparing surrogate recovery standard and internal standard solutions for the analysis of polar target analytes. It also describes the method for preparing calibration standard solutions for polar analytes used for gas chromatography/mass sp...

Engagement in Advance Care Planning and Surrogates' Knowledge of Patients' Treatment Goals.

PubMed

Fried, Terri R; Zenoni, Maria; Iannone, Lynne; O'Leary, John; Fenton, Brenda T

2017-08-01

A key objective of advance care planning (ACP) is improving surrogates' knowledge of patients' treatment goals. Little is known about whether ACP outside of a trial accomplishes this. The objective was to examine patient and surrogate reports of ACP engagement and associations with surrogate knowledge of goals. Cohort study SETTING: Primary care in a Veterans Affairs Medical Center. 350 community-dwelling veterans age ≥55 years and the individual they would choose to make medical decisions on their behalf, interviewed separately. Treatment goals were assessed by veterans' ratings of 3 health states: severe physical disability, cognitive disability, and pain, as an acceptable or unacceptable result of treatment for severe illness. Surrogates had knowledge if they correctly predicted all 3 responses. Veterans and surrogates were asked about living will and health care proxy completion and communication about life-sustaining treatment and quality versus quantity of life (QOL). Over 40% of dyads agreed that the veteran had not completed a living will or health care proxy and that there was no QOL communication. For each activity, sizeable proportions (18-34%) disagreed about participation. In dyads who agreed QOL communication had occurred, 30% of surrogates had knowledge, compared to 21% in dyads who agreed communication had not occurred and 15% in dyads who disagreed (P = .01). This relationship persisted in multivariable analysis. Agreement about other ACP activities was not associated with knowledge. Disagreement about ACP participation was common. Agreement about communication regarding QOL was modestly associated with surrogate knowledge of treatment goals. Eliciting surrogates' perspectives is critical to ACP. Even dyads who agree about participation may need additional support for successful engagement. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

A Rigorous Framework for Optimization of Expensive Functions by Surrogates

NASA Technical Reports Server (NTRS)

Booker, Andrew J.; Dennis, J. E., Jr.; Frank, Paul D.; Serafini, David B.; Torczon, Virginia; Trosset, Michael W.

1998-01-01

The goal of the research reported here is to develop rigorous optimization algorithms to apply to some engineering design problems for which design application of traditional optimization approaches is not practical. This paper presents and analyzes a framework for generating a sequence of approximations to the objective function and managing the use of these approximations as surrogates for optimization. The result is to obtain convergence to a minimizer of an expensive objective function subject to simple constraints. The approach is widely applicable because it does not require, or even explicitly approximate, derivatives of the objective. Numerical results are presented for a 31-variable helicopter rotor blade design example and for a standard optimization test example.

OpenMDAO: Framework for Flexible Multidisciplinary Design, Analysis and Optimization Methods

NASA Technical Reports Server (NTRS)

Heath, Christopher M.; Gray, Justin S.

2012-01-01

The OpenMDAO project is underway at NASA to develop a framework which simplifies the implementation of state-of-the-art tools and methods for multidisciplinary design, analysis and optimization. Foremost, OpenMDAO has been designed to handle variable problem formulations, encourage reconfigurability, and promote model reuse. This work demonstrates the concept of iteration hierarchies in OpenMDAO to achieve a flexible environment for supporting advanced optimization methods which include adaptive sampling and surrogate modeling techniques. In this effort, two efficient global optimization methods were applied to solve a constrained, single-objective and constrained, multiobjective version of a joint aircraft/engine sizing problem. The aircraft model, NASA's nextgeneration advanced single-aisle civil transport, is being studied as part of the Subsonic Fixed Wing project to help meet simultaneous program goals for reduced fuel burn, emissions, and noise. This analysis serves as a realistic test problem to demonstrate the flexibility and reconfigurability offered by OpenMDAO.

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

DOE PAGES

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; ...

2017-12-27

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

Meta-analyses evaluating surrogate endpoints for overall survival in cancer randomized trials: A critical review.

PubMed

Savina, Marion; Gourgou, Sophie; Italiano, Antoine; Dinart, Derek; Rondeau, Virginie; Penel, Nicolas; Mathoulin-Pelissier, Simone; Bellera, Carine

2018-03-01

In cancer randomized controlled trials (RCT), alternative endpoints are increasingly being used in place of overall survival (OS) to reduce sample size, duration and cost of trials. It is necessary to ensure that these endpoints are valid surrogates for OS. Our aim was to identify meta-analyses that evaluated surrogate endpoints for OS and assess the strength of evidence for each meta-analysis (MA). We performed a systematic review to identify MA of cancer RCTs assessing surrogate endpoints for OS. We evaluated the strength of the association between the endpoints based on (i) the German Institute of Quality and Efficiency in Health Care guidelines and (ii) the Biomarker-Surrogate Evaluation Schema. Fifty-three publications reported on 164 MA, with heterogeneous statistical methods Disease-free survival (DFS) and progression-free survival (PFS) showed good surrogacy properties for OS in colorectal, lung and head and neck cancers. DFS was highly correlated to OS in gastric cancer. The statistical methodology used to evaluate surrogate endpoints requires consistency in order to facilitate the accurate interpretation of the results. Despite the limited number of clinical settings with validated surrogate endpoints for OS, there is evidence of good surrogacy for DFS and PFS in tumor types that account for a large proportion of cancer cases. Copyright © 2017 Elsevier B.V. All rights reserved.

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

USING METEOROLOGICAL MODEL OUTPUT AS A SURROGATE FOR ON-SITE OBSERVATIONS TO PREDICT DEPOSITION VELOCITY

EPA Science Inventory

The National Oceanic and Atmospheric Administration's Multi-Layer Model (NOAA-MLM) is used by several operational dry deposition networks for estimating the deposition velocity of O , SO , HNO , and particles. The NOAA-MLM requires hourly values of meteorological variables and...

MODIS EVI as a Surrogate for Net Primary Production across Precipitation Regimes

USDA-ARS?s Scientific Manuscript database

According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patte...

NOWCASTING AND FORECASTING BEACH BACTERIA CONCENTRATIONS USING EPA VIRTUAL BEACH SOFTWARE

EPA Science Inventory

Evidence shows that traditional persistence-based beach closure decision making is inadequate, beaches are closed when they could be open and kept open when they should be closed. Intense interest is now focused on efforts to nowcast beach conditions using surrogate variables, su...

A simple analytical procedure to replace HPLC for monitoring treatment concentrations of chloramine-T on fish culture facilities

USGS Publications Warehouse

Dawson, Verdel K.; Meinertz, Jeffery R.; Schmidt, Larry J.; Gingerich, William H.

2003-01-01

Concentrations of chloramine-T must be monitored during experimental treatments of fish when studying the effectiveness of the drug for controlling bacterial gill disease. A surrogate analytical method for analysis of chloramine-T to replace the existing high-performance liquid chromatography (HPLC) method is described. A surrogate method was needed because the existing HPLC method is expensive, requires a specialist to use, and is not generally available at fish hatcheries. Criteria for selection of a replacement method included ease of use, analysis time, cost, safety, sensitivity, accuracy, and precision. The most promising approach was to use the determination of chlorine concentrations as an indicator of chloramine-T. Of the currently available methods for analysis of chlorine, the DPD (N,N-diethyl-p-phenylenediamine) colorimetric method best fit the established criteria. The surrogate method was evaluated under a variety of water quality conditions. Regression analysis of all DPD colorimetric analyses with the HPLC values produced a linear model (Y=0.9602 X+0.1259) with an r2 value of 0.9960. The average accuracy (percent recovery) of the DPD method relative to the HPLC method for the combined set of water quality data was 101.5%. The surrogate method was also evaluated with chloramine-T solutions that contained various concentrations of fish feed or selected densities of rainbow trout. When samples were analyzed within 2 h, the results of the surrogate method were consistent with those of the HPLC method. When samples with high concentrations of organic material were allowed to age more than 2 h before being analyzed, the DPD method seemed to be susceptible to interference, possibly from the development of other chloramine compounds. However, even after aging samples 6 h, the accuracy of the surrogate DPD method relative to the HPLC method was within the range of 80–120%. Based on the data comparing the two methods, the U.S. Food and Drug Administration has concluded that the DPD colorimetric method is appropriate to use to measure chloramine-T in water during pivotal efficacy trials designed to support the approval of chloramine-T for use in fish culture.

Asymmetric multiscale multifractal analysis of wind speed signals

NASA Astrophysics Data System (ADS)

Zhang, Xiaonei; Zeng, Ming; Meng, Qinghao

We develop a new method called asymmetric multiscale multifractal analysis (A-MMA) to explore the multifractality and asymmetric autocorrelations of the signals with a variable scale range. Three numerical experiments are provided to demonstrate the effectiveness of our approach. Then, the proposed method is applied to investigate multifractality and asymmetric autocorrelations of difference sequences between wind speed fluctuations with uptrends or downtrends. The results show that these sequences appear to be far more complex and contain abundant fractal dynamics information. Through analyzing the Hurst surfaces of nine difference sequences, we found that all series exhibit multifractal properties and multiscale structures. Meanwhile, the asymmetric autocorrelations are observed in all variable scale ranges and the asymmetry results are of good consistency within a certain spatial range. The sources of multifractality and asymmetry in nine difference series are further discussed using the corresponding shuffled series and surrogate series. We conclude that the multifractality of these series is due to both long-range autocorrelation and broad probability density function, but the major source of multifractality is long-range autocorrelation, and the source of asymmetry is affected by the spatial distance.

Investigating parameters participating in the infant respiratory control system attractor.

PubMed

Terrill, Philip I; Wilson, Stephen J; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

2008-01-01

Theoretically, any participating parameter in a non-linear system represents the dynamics of the whole system. Taken's time delay embedding theory provides the fundamental basis for allowing non-linear analysis to be performed on physiological, time-series data. In practice, only one measurable parameter is required to be measured to convey an accurate representation of the system dynamics. In this paper, the infant respiratory control system is represented using three variables-a digitally sampled respiratory inductive plethysmography waveform, and the derived parameters tidal volume and inter-breath interval time series data. For 14 healthy infants, these data streams were analysed using recurrence plot analysis across one night of sleep. The measured attractor size of these variables followed the same qualitative trends across the nights study. Results suggest that the attractor size measures of the derived IBI and tidal volume are representative surrogates for the raw respiratory waveform. The extent to which the relative attractor sizes of IBI and tidal volume remain constant through changing sleep state could potentially be used to quantify pathology, or maturation of breathing control.

Does preprocessing change nonlinear measures of heart rate variability?

PubMed

Gomes, Murilo E D; Guimarães, Homero N; Ribeiro, Antônio L P; Aguirre, Luis A

2002-11-01

This work investigated if methods used to produce a uniformly sampled heart rate variability (HRV) time series significantly change the deterministic signature underlying the dynamics of such signals and some nonlinear measures of HRV. Two methods of preprocessing were used: the convolution of inverse interval function values with a rectangular window and the cubic polynomial interpolation. The HRV time series were obtained from 33 Wistar rats submitted to autonomic blockade protocols and from 17 healthy adults. The analysis of determinism was carried out by the method of surrogate data sets and nonlinear autoregressive moving average modelling and prediction. The scaling exponents alpha, alpha(1) and alpha(2) derived from the detrended fluctuation analysis were calculated from raw HRV time series and respective preprocessed signals. It was shown that the technique of cubic interpolation of HRV time series did not significantly change any nonlinear characteristic studied in this work, while the method of convolution only affected the alpha(1) index. The results suggested that preprocessed time series may be used to study HRV in the field of nonlinear dynamics.

Knowledge of advance directive and perceptions of end-of-life care in Chinese-American elders: The role of acculturation.

PubMed

Gao, Xiang; Sun, Fei; Ko, Eunjeong; Kwak, Jung; Shen, Huei-Wern

2015-12-01

This study aimed to describe knowledge of an advance directive (AD) and preferences regarding end-of-life (EoL) care communication, decision making, and designation of surrogates in Chinese-American elders and to examine the role of acculturation variables in AD awareness. Survey data were collected through face-to-face interviews on a sample of 385 Chinese-American elders aged 55 or above living in the Phoenix metropolitan area. The choice of language (Mandarin, Cantonese, or English) and place of interview (senior apartments, Chinese senior centers, or homes) was at the respondent's preference. Hierarchical logistic regression analysis was employed to examine the influence of acculturation variables on AD awareness. Some 21% of participants had heard about ADs, and only 10% had completed one. Elders with higher acculturation levels (OR = 1.04, p < 0.10) and those residing more than 20 years in the United States (OR = 6.87, p < 0.01) were more likely to be aware of ADs after controlling for the effects of demographics, health, and experiences of EoL care. The majority preferred physicians to initiate AD discussions (84.9%) and identified burdens on families as the most important factor in making EoL decisions (89.3%). About 55.1 % considered daughters as the preferred healthcare surrogate. Acculturation levels influence awareness of an AD, and family values are crucial in EoL care decision making. Cultural factors should be considered in designing and delivering appropriate programs to promote knowledge of EoL care among Chinese-American elders and their families.

A Strategic Approach to Medical Care for Exploration Missions

NASA Technical Reports Server (NTRS)

Antonsen, E.; Canga, M.

2016-01-01

Exploration missions will present significant new challenges to crew health, including effects of variable gravity environments, limited communication with Earth-based personnel for diagnosis and consultation for medical events, limited resupply, and limited ability for crew return. Providing health care capabilities for exploration class missions will require system trades be performed to identify a minimum set of requirements and crosscutting capabilities which can be used in design of exploration medical systems. Current and future medical data, information, and knowledge must be cataloged and put in formats that facilitate querying and analysis. These data may then be used to inform the medical research and development program through analysis of risk trade studies between medical care capabilities and system constraints such as mass, power, volume, and training. These studies will be used to define a Medical Concept of Operations to facilitate stakeholder discussions on expected medical capability for exploration missions. Medical Capability as a quantifiable variable is proposed as a surrogate risk metric and explored for trade space analysis that can improve communication between the medical and engineering approaches to mission design. The resulting medical system approach selected will inform NASA mission architecture, vehicle, and subsystem design for the next generation of spacecraft.

Limitations of polynomial chaos expansions in the Bayesian solution of inverse problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Fei; Department of Mathematics, University of California, Berkeley; Morzfeld, Matthias, E-mail: mmo@math.lbl.gov

2015-02-01

Polynomial chaos expansions are used to reduce the computational cost in the Bayesian solutions of inverse problems by creating a surrogate posterior that can be evaluated inexpensively. We show, by analysis and example, that when the data contain significant information beyond what is assumed in the prior, the surrogate posterior can be very different from the posterior, and the resulting estimates become inaccurate. One can improve the accuracy by adaptively increasing the order of the polynomial chaos, but the cost may increase too fast for this to be cost effective compared to Monte Carlo sampling without a surrogate posterior.

A Priori Analysis of a Compressible Flamelet Model using RANS Data for a Dual-Mode Scramjet Combustor

NASA Technical Reports Server (NTRS)

Quinlan, Jesse R.; Drozda, Tomasz G.; McDaniel, James C.; Lacaze, Guilhem; Oefelein, Joseph

2015-01-01

In an effort to make large eddy simulation of hydrocarbon-fueled scramjet combustors more computationally accessible using realistic chemical reaction mechanisms, a compressible flamelet/progress variable (FPV) model was proposed that extends current FPV model formulations to high-speed, compressible flows. Development of this model relied on observations garnered from an a priori analysis of the Reynolds-Averaged Navier-Stokes (RANS) data obtained for the Hypersonic International Flight Research and Experimentation (HI-FiRE) dual-mode scramjet combustor. The RANS data were obtained using a reduced chemical mechanism for the combustion of a JP-7 surrogate and were validated using avail- able experimental data. These RANS data were then post-processed to obtain, in an a priori fashion, the scalar fields corresponding to an FPV-based modeling approach. In the current work, in addition to the proposed compressible flamelet model, a standard incompressible FPV model was also considered. Several candidate progress variables were investigated for their ability to recover static temperature and major and minor product species. The effects of pressure and temperature on the tabulated progress variable source term were characterized, and model coupling terms embedded in the Reynolds- averaged Navier-Stokes equations were studied. Finally, results for the novel compressible flamelet/progress variable model were presented to demonstrate the improvement attained by modeling the effects of pressure and flamelet boundary conditions on the combustion.

Beauty and the beast: Some perspectives on efficient model analysis, surrogate models, and the future of modeling

NASA Astrophysics Data System (ADS)

Hill, M. C.; Jakeman, J.; Razavi, S.; Tolson, B.

2015-12-01

For many environmental systems model runtimes have remained very long as more capable computers have been used to add more processes and more time and space discretization. Scientists have also added more parameters and kinds of observations, and many model runs are needed to explore the models. Computational demand equals run time multiplied by number of model runs divided by parallelization opportunities. Model exploration is conducted using sensitivity analysis, optimization, and uncertainty quantification. Sensitivity analysis is used to reveal consequences of what may be very complex simulated relations, optimization is used to identify parameter values that fit the data best, or at least better, and uncertainty quantification is used to evaluate the precision of simulated results. The long execution times make such analyses a challenge. Methods for addressing this challenges include computationally frugal analysis of the demanding original model and a number of ingenious surrogate modeling methods. Both commonly use about 50-100 runs of the demanding original model. In this talk we consider the tradeoffs between (1) original model development decisions, (2) computationally frugal analysis of the original model, and (3) using many model runs of the fast surrogate model. Some questions of interest are as follows. If the added processes and discretization invested in (1) are compared with the restrictions and approximations in model analysis produced by long model execution times, is there a net benefit related of the goals of the model? Are there changes to the numerical methods that could reduce the computational demands while giving up less fidelity than is compromised by using computationally frugal methods or surrogate models for model analysis? Both the computationally frugal methods and surrogate models require that the solution of interest be a smooth function of the parameters or interest. How does the information obtained from the local methods typical of (2) and the global averaged methods typical of (3) compare for typical systems? The discussion will use examples of response of the Greenland glacier to global warming and surface and groundwater modeling.

Pull out strength calculator for pedicle screws using a surrogate ensemble approach.

PubMed

Varghese, Vicky; Ramu, Palaniappan; Krishnan, Venkatesh; Saravana Kumar, Gurunathan

2016-12-01

Pedicle screw instrumentation is widely used in the treatment of spinal disorders and deformities. Currently, the surgeon decides the holding power of instrumentation based on the perioperative feeling which is subjective in nature. The objective of the paper is to develop a surrogate model which will predict the pullout strength of pedicle screw based on density, insertion angle, insertion depth and reinsertion. A Taguchi's orthogonal array was used to design an experiment to find the factors effecting pullout strength of pedicle screw. The pullout studies were carried using polyaxial pedicle screw on rigid polyurethane foam block according to American society for testing of materials (ASTM F543). Analysis of variance (ANOVA) and Tukey's honestly significant difference multiple comparison tests were done to find factor effect. Based on the experimental results, surrogate models based on Krigging, polynomial response surface and radial basis function were developed for predicting the pullout strength for different combination of factors. An ensemble of these surrogates based on weighted average surrogate model was also evaluated for prediction. Density, insertion depth, insertion angle and reinsertion have a significant effect (p <0.05) on pullout strength of pedicle screw. Weighted average surrogate performed the best in predicting the pull out strength amongst the surrogate models considered in this study and acted as insurance against bad prediction. A predictive model for pullout strength of pedicle screw was developed using experimental values and surrogate models. This can be used in pre-surgical planning and decision support system for spine surgeon. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Statistical surrogate models for prediction of high-consequence climate change.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

2011-09-01

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. 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 therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest.more » A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. 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 is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.« less

Residents' perceptions about surrogate decision makers' financial conflicts of interest in ventilator withdrawal.

PubMed

Wastila, Lisa J; Farber, Neil J

2014-05-01

There have been no studies to date that examine physicians' decisions to withdraw life-sustaining treatment for patients based on their surrogates' financial gain. The authors' objective was to ascertain physician attitudes about withdrawing life-sustaining treatment when financial considerations are involved. A survey was developed and pretested containing eight scenarios in which a terminally ill patient's spouse had a decision to make regarding withdrawal of the ventilator, which was deemed medically futile. Nested variables included agreement or disagreement between the spouse and patient, decision to withdraw or continue the ventilator, and financial gain or no financial gain for the spouse. The authors surveyed all internal medicine residents at the University of California, San Diego in the autumn of 2011 and winter of 2012. The responses on each of the three variables for which respondents were likely to withdraw the ventilator were analyzed via student's t-tests. Residents were more likely to withdraw the ventilator when requested to do so than when it was requested to be continued. They were also more likely to withdraw the ventilator when there was agreement in the decision between the spouse and the patient. Residents were more likely to withdraw the ventilator when the spouse would not benefit financially. Internal medicine residents make some decisions about whether to withdraw life-sustaining treatment based on financial considerations. There needs to be ongoing communication with residents about end-of-life decisions where conflicts may exist between the surrogate decision makers and patients or physicians.

76 FR 35403 - Certain Frozen Fish Fillets From the Socialist Republic of Vietnam: Final Results of the...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-17

... opportunity to comment on the Preliminary Results and, based upon our analysis of the comments and information... reviews. We extended the deadlines for submission of surrogate value comments and case briefs.\\2\\ On March..., Office 9, to Interested Parties: Extending Surrogate Value Submission & Briefing Schedule for New Shipper...

Ability among adolescents for the metabolic syndrome to predict elevations in factors associated with type 2 diabetes and cardiovascular disease: data from the national health and nutrition examination survey 1999-2006.

PubMed

DeBoer, Mark D; Gurka, Matthew J

2010-08-01

The aim of this study was to compare currently proposed sets of pediatric metabolic syndrome criteria for the ability to predict elevations in "surrogate" factors that are associated with metabolic syndrome and with future cardiovascular disease and type 2 diabetes mellitus. These surrogate factors were fasting insulin, hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein (hsCRP), and uric acid. Waist circumference (WC), blood pressure, triglycerides, high-density lipoprotein cholesterol (HDL-C), fasting glucose, fasting insulin, HbA1c, hsCRP, and uric acid measurements were obtained from 2,624 adolescent (12-18 years old) participants of the 1999-2006 National Health and Nutrition Examination Surveys. We identified children with metabolic syndrome as defined by six commonly used sets of pediatric metabolic syndrome criteria. We then defined elevations in the surrogate factors as values in the top 5% for the cohort and calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each set of metabolic syndrome criteria and for each surrogate factor. Current pediatric metabolic syndrome criteria exhibited variable sensitivity and specificity for surrogate predictions. Metabolic syndrome criteria had the highest sensitivity for predicting fasting insulin (40-70%), followed by uric acid (31-54%), hsCRP (13-31%), and HbA1c (7-21%). The criteria of de Ferranti (which includes children with WC >75(th) percentile, compared to all other sets including children with WC >90(th) percentile) exhibited the highest sensitivity for predicting each of the surrogates, with only modest decrease in specificity compared to the other sets of criteria. However, the de Ferranti criteria also exhibited the lowest PPV values. Conversely, the pediatric International Diabetes Federation criteria exhibited the lowest sensitivity and the highest specificity. Pediatric metabolic syndrome criteria exhibit moderate sensitivity for detecting elevations in surrogate factors associated with metabolic syndrome and with risk for future disease. Inclusion of children with more modestly elevated WC improved sensitivity.

Robust optimization of a tandem grating solar thermal absorber

NASA Astrophysics Data System (ADS)

Choi, Jongin; Kim, Mingeon; Kang, Kyeonghwan; Lee, Ikjin; Lee, Bong Jae

2018-04-01

Ideal solar thermal absorbers need to have a high value of the spectral absorptance in the broad solar spectrum to utilize the solar radiation effectively. Majority of recent studies about solar thermal absorbers focus on achieving nearly perfect absorption using nanostructures, whose characteristic dimension is smaller than the wavelength of sunlight. However, precise fabrication of such nanostructures is not easy in reality; that is, unavoidable errors always occur to some extent in the dimension of fabricated nanostructures, causing an undesirable deviation of the absorption performance between the designed structure and the actually fabricated one. In order to minimize the variation in the solar absorptance due to the fabrication error, the robust optimization can be performed during the design process. However, the optimization of solar thermal absorber considering all design variables often requires tremendous computational costs to find an optimum combination of design variables with the robustness as well as the high performance. To achieve this goal, we apply the robust optimization using the Kriging method and the genetic algorithm for designing a tandem grating solar absorber. By constructing a surrogate model through the Kriging method, computational cost can be substantially reduced because exact calculation of the performance for every combination of variables is not necessary. Using the surrogate model and the genetic algorithm, we successfully design an effective solar thermal absorber exhibiting a low-level of performance degradation due to the fabrication uncertainty of design variables.

Characterizing Variability in Ohio River NOM and Validating Reconstituted Freeze-Dried NOM as a Surrogate for its Aqueous Source

EPA Science Inventory

Surface water contains natural organic matter (NOM) which reacts with disinfectants creating disinfection byproducts (DBPs), some of which are USEPA regulated contaminants. Characterizing NOM can provide important insight on DBP formation and water treatment process adaptation t...

Spatiotemporally‐Resolved Air Exchange Rate as a Modifier of Acute Air Pollution‐Related Morbidity in AtlantaMorbidity in Atlanta

EPA Science Inventory

Epidemiological studies frequently use central site concentrations as surrogates of exposure to air pollutants. Variability in air pollutant infiltration due to differential air exchange rates (AERs) is potentially a major factor affecting the relationship between central site c...

Evaluation of two new surrogate indices including parameters not using insulin to assess insulin sensitivity/resistance in non-diabetic postmenopausal women: a MONET group study.

PubMed

Bastard, J-P; Lavoie, M-E; Messier, V; Prud'homme, D; Rabasa-Lhoret, R

2012-06-01

The study evaluated and compared, with other surrogate indices of insulin sensitivity/resistance (IS/R), the relevance of the TyG index, a product of fasting glucose and triglyceride (TG) levels, and the EGIR index, which includes TG, high-density lipoprotein cholesterol (HDL-c) and waist circumference in its formula to estimate IS/R, in non-diabetic postmenopausal women. A secondary analysis was performed using the baseline data for 163 non-diabetic postmenopausal women from the Montreal-Ottawa New Emerging Team (MONET) population database. The subjects participated in hyperinsulinaemic-euglycaemic (HIEG) clamp and oral glucose tolerance (OGTT) tests. Correlations and comparisons between surrogate indices were performed in addition to inter-rater agreement tests. The optimal value of surrogate indices for diagnosis of IS/R was established on a receiver operating characteristic (ROC) scatter plot. A significant correlation was found between the HIEG clamp and all IS/R surrogate indices tested [r=-0.370 (TyG index) to 0.608 (SIisOGTT index); P<0.001]. On ROC curve analysis, a higher AUROC was found for SIisOGTT (0.791) than for TyG and EGIR (0.706 and 0.675, respectively; P=0.07 and P<0.05, respectively). The TyG and EGIR IS/R indices were only relatively modestly related to the HIEG clamp. In contrast, both fasting- and OGTT-derived IS/R surrogate indices, which include insulin values in their formulae, appeared to be more accurate in estimating IS/R in our study population. Thus, the TyG and EGIR IS/R indices need to be tested and validated more extensively in different populations before being put to large-scale clinical use. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Flood regionalization: A hybrid geographic and predictor-variable region-of-influence regression method

USGS Publications Warehouse

Eng, K.; Milly, P.C.D.; Tasker, Gary D.

2007-01-01

To facilitate estimation of streamflow characteristics at an ungauged site, hydrologists often define a region of influence containing gauged sites hydrologically similar to the estimation site. This region can be defined either in geographic space or in the space of the variables that are used to predict streamflow (predictor variables). These approaches are complementary, and a combination of the two may be superior to either. Here we propose a hybrid region-of-influence (HRoI) regression method that combines the two approaches. The new method was applied with streamflow records from 1,091 gauges in the southeastern United States to estimate the 50-year peak flow (Q50). The HRoI approach yielded lower root-mean-square estimation errors and produced fewer extreme errors than either the predictor-variable or geographic region-of-influence approaches. It is concluded, for Q50 in the study region, that similarity with respect to the basin characteristics considered (area, slope, and annual precipitation) is important, but incomplete, and that the consideration of geographic proximity of stations provides a useful surrogate for characteristics that are not included in the analysis. ?? 2007 ASCE.

Within- and between-child variation in repeated urinary pesticide metabolite measurements over a 1-year period.

PubMed

Attfield, Kathleen R; Hughes, Michael D; Spengler, John D; Lu, Chensheng

2014-02-01

Children are exposed to pesticides from many sources and routes, including dietary and incidental ingestion, dermal absorption, and inhalation. Linking health outcomes to these exposures using urinary metabolites requires understanding temporal variability within subjects to avoid exposure misclassification. We characterized the within- and between-child variability of urinary organophosphorus and pyrethroid metabolites in 23 participants of the Children's Pesticide Exposure Study-Washington over 1 year and examined the ability of one to four spot urine samples to categorize mean exposures. Each child provided urine samples twice daily over 7- to 16-day sessions in four seasons in 2003 and 2004. Samples were analyzed for five pyrethroid and five organophosphorus (OP) metabolites. After adjusting for specific gravity, we used a customized maximum likelihood estimation linear mixed-effects model that accounted for values below the limit of detection to calculate intraclass correlation coefficients (ICC) and conducted surrogate category analyses. Within-child variability was 2-11 times greater than between-child variability. When restricted to samples collected during a single season, ICCs were higher in the fall, winter, and spring than in summer for OPs, and higher in summer and winter for pyrethroids, indicating an increase in between-person variability relative to within-person variability during these seasons. Surrogate category analyses demonstrated that a single spot urine sample did not categorize metabolite concentrations well, and that four or more samples would be needed to categorize children into quartiles consistently. Urinary biomarkers of these short half-life pesticides exhibited substantial within-person variability in children observed over four seasons. Researchers investigating pesticides and health outcomes in children may need repeated biomarker measurements to derive accurate estimates of exposure and relative risks.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots.

PubMed

Tošić, Tamara; Sellers, Kristin K; Fröhlich, Flavio; Fedotenkova, Mariia; Beim Graben, Peter; Hutt, Axel

2015-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots

PubMed Central

Tošić, Tamara; Sellers, Kristin K.; Fröhlich, Flavio; Fedotenkova, Mariia; beim Graben, Peter; Hutt, Axel

2016-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain. PMID:26834580

Baroreflex Coupling Assessed by Cross-Compression Entropy

PubMed Central

Schumann, Andy; Schulz, Steffen; Voss, Andreas; Scharbrodt, Susann; Baumert, Mathias; Bär, Karl-Jürgen

2017-01-01

Estimating interactions between physiological systems is an important challenge in modern biomedical research. Here, we explore a new concept for quantifying information common in two time series by cross-compressibility. Cross-compression entropy (CCE) exploits the ZIP data compression algorithm extended to bivariate data analysis. First, time series are transformed into symbol vectors. Symbols of the target time series are coded by the symbols of the source series. Uncoupled and linearly coupled surrogates were derived from cardiovascular recordings of 36 healthy controls obtained during rest to demonstrate suitability of this method for assessing physiological coupling. CCE at rest was compared to that of isometric handgrip exercise. Finally, spontaneous baroreflex interaction assessed by CCEBRS was compared between 21 patients suffering from acute schizophrenia and 21 matched controls. The CCEBRS of original time series was significantly higher than in uncoupled surrogates in 89% of the subjects and higher than in linearly coupled surrogates in 47% of the subjects. Handgrip exercise led to sympathetic activation and vagal inhibition accompanied by reduced baroreflex sensitivity. CCEBRS decreased from 0.553 ± 0.030 at rest to 0.514 ± 0.035 during exercise (p < 0.001). In acute schizophrenia, heart rate, and blood pressure were elevated. Heart rate variability indicated a change of sympathovagal balance. The CCEBRS of patients with schizophrenia was reduced compared to healthy controls (0.546 ± 0.042 vs. 0.507 ± 0.046, p < 0.01) and revealed a decrease of blood pressure influence on heart rate in patients with schizophrenia. Our results indicate that CCE is suitable for the investigation of linear and non-linear coupling in cardiovascular time series. CCE can quantify causal interactions in short, noisy and non-stationary physiological time series. PMID:28539889

Surrogate immiscible liquid pairs with refractive indexes matchable over a wide range of density and viscosity ratios

NASA Astrophysics Data System (ADS)

Saksena, Rajat; Christensen, Kenneth T.; Pearlstein, Arne J.

2015-08-01

In liquid-liquid flows, use of optical diagnostics is limited by interphase refractive index mismatch, which leads to optical distortion and complicates data interpretation, and sometimes also by opacity. Both problems can be eliminated using a surrogate pair of immiscible index-matched transparent liquids, whose density and viscosity ratios match corresponding ratios for the original liquid pair. We show that a wide range of density and viscosity ratios is accessible using aqueous solutions of 1,2-propanediol and CsBr (for which index, density, and viscosity are available), and solutions of light and heavy silicone oils and 1-bromooctane (for which we measured the same properties at 119 compositions). For each liquid phase, polynomials in the composition variables, least-squares fitted to index and density and to the logarithm of kinematic viscosity, were used to determine accessible density and viscosity ratios for each matchable index. Index-matched solution pairs can be prepared with density and viscosity ratios equal to those for water-liquid CO2 at 0 °C over a range of pressure (allowing water-liquid CO2 behavior at inconveniently high pressure to be simulated by 1-bar experiments), and for water-crude oil and water-trichloroethylene (avoiding opacity and toxicity problems, respectively), each over a range of temperature. For representative index-matched solutions, equilibration changes index, density, and viscosity only slightly, and mass spectrometry and elemental analysis show that no component of either phase has significant interphase solubility. Finally, procedures are described for iteratively reducing the residual index mismatch in surrogate solution pairs prepared on the basis of approximate polynomial fits to experimental data, and for systematically dealing with nonzero interphase solubility.

Aerodynamic Optimization of Rocket Control Surface Geometry Using Cartesian Methods and CAD Geometry

NASA Technical Reports Server (NTRS)

Nelson, Andrea; Aftosmis, Michael J.; Nemec, Marian; Pulliam, Thomas H.

2004-01-01

Aerodynamic design is an iterative process involving geometry manipulation and complex computational analysis subject to physical constraints and aerodynamic objectives. A design cycle consists of first establishing the performance of a baseline design, which is usually created with low-fidelity engineering tools, and then progressively optimizing the design to maximize its performance. Optimization techniques have evolved from relying exclusively on designer intuition and insight in traditional trial and error methods, to sophisticated local and global search methods. Recent attempts at automating the search through a large design space with formal optimization methods include both database driven and direct evaluation schemes. Databases are being used in conjunction with surrogate and neural network models as a basis on which to run optimization algorithms. Optimization algorithms are also being driven by the direct evaluation of objectives and constraints using high-fidelity simulations. Surrogate methods use data points obtained from simulations, and possibly gradients evaluated at the data points, to create mathematical approximations of a database. Neural network models work in a similar fashion, using a number of high-fidelity database calculations as training iterations to create a database model. Optimal designs are obtained by coupling an optimization algorithm to the database model. Evaluation of the current best design then gives either a new local optima and/or increases the fidelity of the approximation model for the next iteration. Surrogate methods have also been developed that iterate on the selection of data points to decrease the uncertainty of the approximation model prior to searching for an optimal design. The database approximation models for each of these cases, however, become computationally expensive with increase in dimensionality. Thus the method of using optimization algorithms to search a database model becomes problematic as the number of design variables is increased.

Inverse Modeling Using Markov Chain Monte Carlo Aided by Adaptive Stochastic Collocation Method with Transformation

NASA Astrophysics Data System (ADS)

Zhang, D.; Liao, Q.

2016-12-01

The Bayesian inference provides a convenient framework to solve statistical inverse problems. In this method, the parameters to be identified are treated as random variables. The prior knowledge, the system nonlinearity, and the measurement errors can be directly incorporated in the posterior probability density function (PDF) of the parameters. The Markov chain Monte Carlo (MCMC) method is a powerful tool to generate samples from the posterior PDF. However, since the MCMC usually requires thousands or even millions of forward simulations, it can be a computationally intensive endeavor, particularly when faced with large-scale flow and transport models. To address this issue, we construct a surrogate system for the model responses in the form of polynomials by the stochastic collocation method. In addition, we employ interpolation based on the nested sparse grids and takes into account the different importance of the parameters, under the condition of high random dimensions in the stochastic space. Furthermore, in case of low regularity such as discontinuous or unsmooth relation between the input parameters and the output responses, we introduce an additional transform process to improve the accuracy of the surrogate model. Once we build the surrogate system, we may evaluate the likelihood with very little computational cost. We analyzed the convergence rate of the forward solution and the surrogate posterior by Kullback-Leibler divergence, which quantifies the difference between probability distributions. The fast convergence of the forward solution implies fast convergence of the surrogate posterior to the true posterior. We also tested the proposed algorithm on water-flooding two-phase flow reservoir examples. The posterior PDF calculated from a very long chain with direct forward simulation is assumed to be accurate. The posterior PDF calculated using the surrogate model is in reasonable agreement with the reference, revealing a great improvement in terms of computational efficiency.

Italian gay fathers' experiences of transnational surrogacy and their relationship with the surrogate pre- and post-birth.

PubMed

Carone, Nicola; Baiocco, Roberto; Lingiardi, Vittorio

2017-02-01

This study aims to explore the experience of transnational surrogacy and the relationship with the surrogate pre- and post-birth in Italian gay father families. Couple and individual semi-structured interviews were carried out with 30 Italian gay partnered fathers with at least one child born through gestational surrogacy in California or Canada. No couples had known their surrogates or egg donors previously. The Interpretative Phenomenological Analysis indicated that three interrelated themes could be helpful for understanding the gay fathers' experience of their geographical distance from the surrogate: the perceived loss of control over the pregnancy; the surrogate as a person who facilitates the fathers' feelings of being emotionally connected to their developing child; the surrogate as an 'aunty' who, along with her family, maintains a relationship with the fathers. None of the fathers mentioned the egg donor during the interview. The study inspires reflections in offshore fertility practitioners on how pre- and ongoing surrogacy counselling for prospective gay fathers should be tailored. It further calls for the necessity of offering psychological counselling in gay fathers' resident countries in order to promote informed decisions before starting surrogacy abroad and to elaborate on potential difficulties related to surrogacy after the child's birth. Copyright © 2016 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

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 applied the calibrated surrogate model to study the probability that the precipitation rate falls below certain thresholds and utilized the Bayesian approach to quantify our confidence in these predictions. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.

Bending testing and characterization of surrogate nuclear fuel rods made of Zircaloy-4 cladding and aluminum oxide pellets

NASA Astrophysics Data System (ADS)

Wang, Hong; Wang, Jy-An John

2016-10-01

Behavior of surrogate nuclear fuel rods made of Zircaloy-4 (Zry-4) cladding with alumina pellets under reversed cyclic bending was studied. Tests were performed under load or moment control at 5 Hz. The surrogate rods fractured under moment amplitudes greater than 10.16 Nm with fatigue lives between 2.4 × 103 and 2.2 × 106 cycles. Fatigue response of Zry-4 cladding was characterized by using flexural rigidity. Degradation of flexural rigidity was shown to depend on the moment and the prefatigue condition of specimens. Pellet-to-pellet interface (PPI), pellet-to-cladding interface (PCI), and pellet condition affect surrogate rod failure. Both debonding of PPI/PCI and pellet fracturing contribute to surrogate rod bending fatigue. The effect of sensor spacing on curvature measurement using three-point deflections was studied; the method based on effective gauge length is effective in sensor spacing correction. The database developed and the understanding gained in this study can serve as input to analysis of SNF (spent nuclear fuel) vibration integrity.

Estimation of Model's Marginal likelihood Using Adaptive Sparse Grid Surrogates in Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Zeng, X.

2015-12-01

A large number of model executions are required to obtain alternative conceptual models' predictions and their posterior probabilities in Bayesian model averaging (BMA). The posterior model probability is estimated through models' marginal likelihood and prior probability. The heavy computation burden hinders the implementation of BMA prediction, especially for the elaborated marginal likelihood estimator. For overcoming the computation burden of BMA, an adaptive sparse grid (SG) stochastic collocation method is used to build surrogates for alternative conceptual models through the numerical experiment of a synthetical groundwater model. BMA predictions depend on model posterior weights (or marginal likelihoods), and this study also evaluated four marginal likelihood estimators, including arithmetic mean estimator (AME), harmonic mean estimator (HME), stabilized harmonic mean estimator (SHME), and thermodynamic integration estimator (TIE). The results demonstrate that TIE is accurate in estimating conceptual models' marginal likelihoods. The BMA-TIE has better predictive performance than other BMA predictions. TIE has high stability for estimating conceptual model's marginal likelihood. The repeated estimated conceptual model's marginal likelihoods by TIE have significant less variability than that estimated by other estimators. In addition, the SG surrogates are efficient to facilitate BMA predictions, especially for BMA-TIE. The number of model executions needed for building surrogates is 4.13%, 6.89%, 3.44%, and 0.43% of the required model executions of BMA-AME, BMA-HME, BMA-SHME, and BMA-TIE, respectively.

Migration surrogates and their association with obesity among within-country migrants

PubMed Central

Bernabe-Ortiz, Antonio; Gilman, Robert H.; Smeeth, Liam; Miranda, J. Jaime

2010-01-01

Limited studies have evaluated the link between acculturation and health outcomes of within-country migrants. The objective of this study was to evaluate whether well-known acculturation surrogates were associated with obesity among Peruvian rural-to-urban migrants. We performed a cross sectional survey, the PERU MIGRANT study, using single-stage random sampling. Evaluation included weight, height, and waist circumference (WC) as well as acculturation surrogates. Obesity was assessed using body mass index (BMI) and WC. Length of residence, age at migration, language proficiency and language preferences (Spanish or Quechua) were assessed in logistic regression models to calculate odd ratios (OR) and 95% confidence intervals (CI) adjusting for potential confounders. A total of 589 rural-to-urban migrants were enrolled. The mean age was 47.8 (SD: 11.7, range: 30-92) and 280 (47.5%) were males. Obesity prevalence assessed by BMI was 30.4% among women and 10.7% among men (p<0.001), whereas abdominal obesity assessed by WC was 29.1% among women and 19.1% among men (p<0.01). Obesity was associated with older age at first migration, language speaking proficiency and language preferences. The association between obesity and acculturation surrogates is variable in this population. Thus, acculturation per se can explore positive channels associated with better health outcomes. The patterns shown in this report suggest a more complex association for these factors. PMID:20395946

Assessing Exposure to Household Air Pollution: A Systematic Review and Pooled Analysis of Carbon Monoxide as a Surrogate Measure of Particulate Matter

EPA Science Inventory

ACKGROUND: Household air pollution from solid fuel burning is a leading contributor to disease burden globally. Fine particulate matter (PM2.5) is thought to be responsible for many of these health impacts. A co-pollutant, carbon monoxide (CO) has been widely used as a surrogate ...

Assessing Exposure to Household Air Pollution: A Systematic Review and Pooled Analysis of Carbon Monoxide as a Surrogate Measure of Particulate Matter

EPA Science Inventory

ACKGROUND: Household air pollution from solid fuel burning is a leading contributor to disease burden globally. Fine particulate matter (PM2.5) is thought to be responsible for many of these health impacts. A co-pollutant, carbon monoxide (CO) has been widely used as a surrogate...

"We want to offer you peace of mind": Marketing of transnational commercial surrogacy services to intended parents.

PubMed

Gezinski, Lindsay B; Karandikar, Sharvari; Levitt, Alexis; Ghaffarian, Roxanne

2017-01-01

The purpose of this research study was to conduct a content analysis of commercial surrogacy websites to explore how surrogacy is marketed to intended parents. The researchers developed a template to code website data, and a total of 345 website pages were reviewed. Websites depicted surrogacy as a solution to a problem, privileged genetic parenthood, ignored the potential for exploitation, dismissed surrogates' capacity to bond with the fetuses they carry, emphasized that surrogacy arrangements are mutually beneficial, ignored structural inequalities, and depicted surrogates as conforming to strict gender roles. These framings introduce vulnerabilities to both intended parents and surrogate mothers.

Ensemble of surrogates-based optimization for identifying an optimal surfactant-enhanced aquifer remediation strategy at heterogeneous DNAPL-contaminated sites

NASA Astrophysics Data System (ADS)

Jiang, Xue; Lu, Wenxi; Hou, Zeyu; Zhao, Haiqing; Na, Jin

2015-11-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

Ensemble of Surrogates-based Optimization for Identifying an Optimal Surfactant-enhanced Aquifer Remediation Strategy at Heterogeneous DNAPL-contaminated Sites

NASA Astrophysics Data System (ADS)

Lu, W., Sr.; Xin, X.; Luo, J.; Jiang, X.; Zhang, Y.; Zhao, Y.; Chen, M.; Hou, Z.; Ouyang, Q.

2015-12-01

The purpose of this study was to identify an optimal surfactant-enhanced aquifer remediation (SEAR) strategy for aquifers contaminated by dense non-aqueous phase liquid (DNAPL) based on an ensemble of surrogates-based optimization technique. A saturated heterogeneous medium contaminated by nitrobenzene was selected as case study. A new kind of surrogate-based SEAR optimization employing an ensemble surrogate (ES) model together with a genetic algorithm (GA) is presented. Four methods, namely radial basis function artificial neural network (RBFANN), kriging (KRG), support vector regression (SVR), and kernel extreme learning machines (KELM), were used to create four individual surrogate models, which were then compared. The comparison enabled us to select the two most accurate models (KELM and KRG) to establish an ES model of the SEAR simulation model, and the developed ES model as well as these four stand-alone surrogate models was compared. The results showed that the average relative error of the average nitrobenzene removal rates between the ES model and the simulation model for 20 test samples was 0.8%, which is a high approximation accuracy, and which indicates that the ES model provides more accurate predictions than the stand-alone surrogate models. Then, a nonlinear optimization model was formulated for the minimum cost, and the developed ES model was embedded into this optimization model as a constrained condition. Besides, GA was used to solve the optimization model to provide the optimal SEAR strategy. The developed ensemble surrogate-optimization approach was effective in seeking a cost-effective SEAR strategy for heterogeneous DNAPL-contaminated sites. This research is expected to enrich and develop the theoretical and technical implications for the analysis of remediation strategy optimization of DNAPL-contaminated aquifers.

Predicting analysis time in events-driven clinical trials using accumulating time-to-event surrogate information.

PubMed

Wang, Jianming; Ke, Chunlei; Yu, Zhinuan; Fu, Lei; Dornseif, Bruce

2016-05-01

For clinical trials with time-to-event endpoints, predicting the accrual of the events of interest with precision is critical in determining the timing of interim and final analyses. For example, overall survival (OS) is often chosen as the primary efficacy endpoint in oncology studies, with planned interim and final analyses at a pre-specified number of deaths. Often, correlated surrogate information, such as time-to-progression (TTP) and progression-free survival, are also collected as secondary efficacy endpoints. It would be appealing to borrow strength from the surrogate information to improve the precision of the analysis time prediction. Currently available methods in the literature for predicting analysis timings do not consider utilizing the surrogate information. In this article, using OS and TTP as an example, a general parametric model for OS and TTP is proposed, with the assumption that disease progression could change the course of the overall survival. Progression-free survival, related both to OS and TTP, will be handled separately, as it can be derived from OS and TTP. The authors seek to develop a prediction procedure using a Bayesian method and provide detailed implementation strategies under certain assumptions. Simulations are performed to evaluate the performance of the proposed method. An application to a real study is also provided. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Correlation structures in short-term variabilities of stock indices and exchange rates

NASA Astrophysics Data System (ADS)

Nakamura, Tomomichi; Small, Michael

2007-09-01

Financial data usually show irregular fluctuations and some trends. We investigate whether there are correlation structures in short-term variabilities (irregular fluctuations) among financial data from the viewpoint of deterministic dynamical systems. Our method is based on the small-shuffle surrogate method. The data we use are daily closing price of Standard & Poor's 500 and the volume, and daily foreign exchange rates, Euro/US Dollar (USD), British Pound/USD and Japanese Yen/USD. We found that these data are not independent.

The effect of particle size distribution on the design of urban stormwater control measures

USGS Publications Warehouse

Selbig, William R.; Fienen, Michael N.; Horwatich, Judy A.; Bannerman, Roger T.

2016-01-01

An urban pollutant loading model was used to demonstrate how incorrect assumptions on the particle size distribution (PSD) in urban runoff can alter the design characteristics of stormwater control measures (SCMs) used to remove solids in stormwater. Field-measured PSD, although highly variable, is generally coarser than the widely-accepted PSD characterized by the Nationwide Urban Runoff Program (NURP). PSDs can be predicted based on environmental surrogate data. There were no appreciable differences in predicted PSD when grouped by season. Model simulations of a wet detention pond and catch basin showed a much smaller surface area is needed to achieve the same level of solids removal using the median value of field-measured PSD as compared to NURP PSD. Therefore, SCMs that used the NURP PSD in the design process could be unnecessarily oversized. The median of measured PSDs, although more site-specific than NURP PSDs, could still misrepresent the efficiency of an SCM because it may not adequately capture the variability of individual runoff events. Future pollutant loading models may account for this variability through regression with environmental surrogates, but until then, without proper site characterization, the adoption of a single PSD to represent all runoff conditions may result in SCMs that are under- or over-sized, rendering them ineffective or unnecessarily costly.

Dynamics of intracranial electroencephalographic recordings from epilepsy patients using univariate and bivariate recurrence networks.

PubMed

Subramaniyam, Narayan Puthanmadam; Hyttinen, Jari

2015-02-01

Recently Andrezejak et al. combined the randomness and nonlinear independence test with iterative amplitude adjusted Fourier transform (iAAFT) surrogates to distinguish between the dynamics of seizure-free intracranial electroencephalographic (EEG) signals recorded from epileptogenic (focal) and nonepileptogenic (nonfocal) brain areas of epileptic patients. However, stationarity is a part of the null hypothesis for iAAFT surrogates and thus nonstationarity can violate the null hypothesis. In this work we first propose the application of the randomness and nonlinear independence test based on recurrence network measures to distinguish between the dynamics of focal and nonfocal EEG signals. Furthermore, we combine these tests with both iAAFT and truncated Fourier transform (TFT) surrogate methods, which also preserves the nonstationarity of the original data in the surrogates along with its linear structure. Our results indicate that focal EEG signals exhibit an increased degree of structural complexity and interdependency compared to nonfocal EEG signals. In general, we find higher rejections for randomness and nonlinear independence tests for focal EEG signals compared to nonfocal EEG signals. In particular, the univariate recurrence network measures, the average clustering coefficient C and assortativity R, and the bivariate recurrence network measure, the average cross-clustering coefficient C(cross), can successfully distinguish between the focal and nonfocal EEG signals, even when the analysis is restricted to nonstationary signals, irrespective of the type of surrogates used. On the other hand, we find that the univariate recurrence network measures, the average path length L, and the average betweenness centrality BC fail to distinguish between the focal and nonfocal EEG signals when iAAFT surrogates are used. However, these two measures can distinguish between focal and nonfocal EEG signals when TFT surrogates are used for nonstationary signals. We also report an improvement in the performance of nonlinear prediction error N and nonlinear interdependence measure L used by Andrezejak et al., when TFT surrogates are used for nonstationary EEG signals. We also find that the outcome of the nonlinear independence test based on the average cross-clustering coefficient C(cross) is independent of the outcome of the randomness test based on the average clustering coefficient C. Thus, the univariate and bivariate recurrence network measures provide independent information regarding the dynamics of the focal and nonfocal EEG signals. In conclusion, recurrence network analysis combined with nonstationary surrogates can be applied to derive reliable biomarkers to distinguish between epileptogenic and nonepileptogenic brain areas using EEG signals.

Dynamics of intracranial electroencephalographic recordings from epilepsy patients using univariate and bivariate recurrence networks

NASA Astrophysics Data System (ADS)

Subramaniyam, Narayan Puthanmadam; Hyttinen, Jari

2015-02-01

Recently Andrezejak et al. combined the randomness and nonlinear independence test with iterative amplitude adjusted Fourier transform (iAAFT) surrogates to distinguish between the dynamics of seizure-free intracranial electroencephalographic (EEG) signals recorded from epileptogenic (focal) and nonepileptogenic (nonfocal) brain areas of epileptic patients. However, stationarity is a part of the null hypothesis for iAAFT surrogates and thus nonstationarity can violate the null hypothesis. In this work we first propose the application of the randomness and nonlinear independence test based on recurrence network measures to distinguish between the dynamics of focal and nonfocal EEG signals. Furthermore, we combine these tests with both iAAFT and truncated Fourier transform (TFT) surrogate methods, which also preserves the nonstationarity of the original data in the surrogates along with its linear structure. Our results indicate that focal EEG signals exhibit an increased degree of structural complexity and interdependency compared to nonfocal EEG signals. In general, we find higher rejections for randomness and nonlinear independence tests for focal EEG signals compared to nonfocal EEG signals. In particular, the univariate recurrence network measures, the average clustering coefficient C and assortativity R , and the bivariate recurrence network measure, the average cross-clustering coefficient Ccross, can successfully distinguish between the focal and nonfocal EEG signals, even when the analysis is restricted to nonstationary signals, irrespective of the type of surrogates used. On the other hand, we find that the univariate recurrence network measures, the average path length L , and the average betweenness centrality BC fail to distinguish between the focal and nonfocal EEG signals when iAAFT surrogates are used. However, these two measures can distinguish between focal and nonfocal EEG signals when TFT surrogates are used for nonstationary signals. We also report an improvement in the performance of nonlinear prediction error N and nonlinear interdependence measure L used by Andrezejak et al., when TFT surrogates are used for nonstationary EEG signals. We also find that the outcome of the nonlinear independence test based on the average cross-clustering coefficient Ccross is independent of the outcome of the randomness test based on the average clustering coefficient C . Thus, the univariate and bivariate recurrence network measures provide independent information regarding the dynamics of the focal and nonfocal EEG signals. In conclusion, recurrence network analysis combined with nonstationary surrogates can be applied to derive reliable biomarkers to distinguish between epileptogenic and nonepileptogenic brain areas using EEG signals.

[Ants’ higher taxa as surrogates of species richness in a chronosequence of fallows, old-grown forests and agroforestry systems in the Eastern Amazon, Brazil].

PubMed

Muñoz Gutiérrez, Jhonatan Andrés; Roussea, Guillaume Xavier; Andrade-Silva, Joudellys; Delabie, Jacques Hubert Charles

2017-03-01

Deforestation in Amazon forests is one of the main causes for biodiversity loss worldwide. Ants are key into the ecosystem because act like engineers; hence, the loss of ants’ biodiversity may be a guide to measure the loss of essential functions into the ecosystems. The aim of this study was to evaluate soil ant’s richness and to estimate whether higher taxa levels (Subfamily and Genus) can be used as surrogates of species richness in different vegetation types (fallows, old-growth forests and agroforestry systems) in Eastern Amazon. The samples were taken in 65 areas in the Maranhão and Pará States in the period 2011-2014. The sampling scheme followed the procedure of Tropical Soil Biology and Fertility (TSBF). Initially, the vegetation types were characterized according to their age and estimated species richness. Linear and exponential functions were applied to evaluate if higher taxa can be used as surrogates and correlated with the Pearson coefficient. In total, 180 species distributed in 60 genera were identified. The results showed that ant species richness was higher in intermediate fallows (88) and old secondary forest (76), and was lower in agroforestry systems (38) and mature riparian forest (35). The genus level was the best surrogate to estimate the ant’s species richness across the different vegetation types, and explained 72-97 % (P < 0.001) of the total species variability. The results confirmed that the genus level is an excellent surrogate to estimate the ant’s species richness in the region and that both fallows and agroforestry systems may contribute in the conservation of Eastern Amazon ant community.

Surrogate Immiscible Liquid Solution Pairs with Refractive Indexes Matchable Over a Wide Range of Density and Viscosity Ratios

NASA Astrophysics Data System (ADS)

Saksena, Rajat; Christensen, Kenneth T.; Pearlstein, Arne J.

2014-11-01

Use of laser diagnostics in liquid-liquid flows is limited by refractive index mismatch. This can be avoided using a surrogate pair of immiscible index-matched liquids, with density and viscosity ratios matching those of the original liquid pair. We demonstrate that a wide range of density and viscosity ratios is accessible using aqueous solutions of 1,2-propanediol and CsBr (for which index, density, and viscosity are available), and solutions of light and heavy silicone oils and 1-bromooctane (for which we measured the same properties at 119 compositions). For each liquid phase, polynomials in the composition variables were fitted to index and density and to the logarithm of kinematic viscosity, and the fits were used to determine accessible density and viscosity ratios for each matchable index. Index-matched solution pairs can be prepared with density and viscosity ratios equal to those for water-liquid CO2 at 0oC over a range of pressure, and for water-crude oil and water-trichloroethylene, each over a range of temperature. For representative index-matched solutions, equilibration changes index, density, and viscosity only slightly, and chemical analysis show that no component of either solution has significant interphase solubility. Partially supported by Intl. Inst. for Carbon-Neutral Energy Research.

Aerodynamic design applying automatic differentiation and using robust variable fidelity optimization

NASA Astrophysics Data System (ADS)

Takemiya, Tetsushi

In modern aerospace engineering, the physics-based computational design method is becoming more important, as it is more efficient than experiments and because it is more suitable in designing new types of aircraft (e.g., unmanned aerial vehicles or supersonic business jets) than the conventional design method, which heavily relies on historical data. To enhance the reliability of the physics-based computational design method, researchers have made tremendous efforts to improve the fidelity of models. However, high-fidelity models require longer computational time, so the advantage of efficiency is partially lost. This problem has been overcome with the development of variable fidelity optimization (VFO). In VFO, different fidelity models are simultaneously employed in order to improve the speed and the accuracy of convergence in an optimization process. Among the various types of VFO methods, one of the most promising methods is the approximation management framework (AMF). In the AMF, objective and constraint functions of a low-fidelity model are scaled at a design point so that the scaled functions, which are referred to as "surrogate functions," match those of a high-fidelity model. Since scaling functions and the low-fidelity model constitutes surrogate functions, evaluating the surrogate functions is faster than evaluating the high-fidelity model. Therefore, in the optimization process, in which gradient-based optimization is implemented and thus many function calls are required, the surrogate functions are used instead of the high-fidelity model to obtain a new design point. The best feature of the AMF is that it may converge to a local optimum of the high-fidelity model in much less computational time than the high-fidelity model. However, through literature surveys and implementations of the AMF, the author xx found that (1) the AMF is very vulnerable when the computational analysis models have numerical noise, which is very common in high-fidelity models, and that (2) the AMF terminates optimization erroneously when the optimization problems have constraints. The first problem is due to inaccuracy in computing derivatives in the AMF, and the second problem is due to erroneous treatment of the trust region ratio, which sets the size of the domain for an optimization in the AMF. In order to solve the first problem of the AMF, automatic differentiation (AD) technique, which reads the codes of analysis models and automatically generates new derivative codes based on some mathematical rules, is applied. If derivatives are computed with the generated derivative code, they are analytical, and the required computational time is independent of the number of design variables, which is very advantageous for realistic aerospace engineering problems. However, if analysis models implement iterative computations such as computational fluid dynamics (CFD), which solves system partial differential equations iteratively, computing derivatives through the AD requires a massive memory size. The author solved this deficiency by modifying the AD approach and developing a more efficient implementation with CFD, and successfully applied the AD to general CFD software. In order to solve the second problem of the AMF, the governing equation of the trust region ratio, which is very strict against the violation of constraints, is modified so that it can accept the violation of constraints within some tolerance. By accepting violations of constraints during the optimization process, the AMF can continue optimization without terminating immaturely and eventually find the true optimum design point. With these modifications, the AMF is referred to as "Robust AMF," and it is applied to airfoil and wing aerodynamic design problems using Euler CFD software. The former problem has 21 design variables, and the latter 64. In both problems, derivatives computed with the proposed AD method are first compared with those computed with the finite differentiation (FD) method, and then, the Robust AMF is implemented along with the sequential quadratic programming (SQP) optimization method with only high-fidelity models. The proposed AD method computes derivatives more accurately and faster than the FD method, and the Robust AMF successfully optimizes shapes of the airfoil and the wing in a much shorter time than SQP with only high-fidelity models. These results clearly show the effectiveness of the Robust AMF. Finally, the feasibility of reducing computational time for calculating derivatives and the necessity of AMF with an optimum design point always in the feasible region are discussed as future work.

A simple analytical procedure to replace HPLC for monitoring treatment concentrations of chloramine-T on fish culture facilities

USGS Publications Warehouse

Dawson, V.K.; Meinertz, J.R.; Schmidt, L.J.; Gingerich, W.H.

2003-01-01

Concentrations of chloramine-T must be monitored during experimental treatments of fish when studying the effectiveness of the drug for controlling bacterial gill disease. A surrogate analytical method for analysis of chloramine-T to replace the existing high-performance liquid chromatography (HPLC) method is described. A surrogate method was needed because the existing HPLC method is expensive, requires a specialist to use, and is not generally available at fish hatcheries. Criteria for selection of a replacement method included ease of use, analysis time, cost, safety, sensitivity, accuracy, and precision. The most promising approach was to use the determination of chlorine concentrations as an indicator of chloramine-T. Of the currently available methods for analysis of chlorine, the DPD (N,N-diethyl-p-phenylenediamine) colorimetric method best fit the established criteria. The surrogate method was evaluated under a variety of water quality conditions. Regression analysis of all DPD colorimetric analyses with the HPLC values produced a linear model (Y=0.9602 X+0.1259) with an r2 value of 0.9960. The average accuracy (percent recovery) of the DPD method relative to the HPLC method for the combined set of water quality data was 101.5%. The surrogate method was also evaluated with chloramine-T solutions that contained various concentrations of fish feed or selected densities of rainbow trout. When samples were analyzed within 2 h, the results of the surrogate method were consistent with those of the HPLC method. When samples with high concentrations of organic material were allowed to age more than 2 h before being analyzed, the DPD method seemed to be susceptible to interference, possibly from the development of other chloramine compounds. However, even after aging samples 6 h, the accuracy of the surrogate DPD method relative to the HPLC method was within the range of 80-120%. Based on the data comparing the two methods, the U.S. Food and Drug Administration has concluded that the DPD colorimetric method is appropriate to use to measure chloramine-T in water during pivotal efficacy trials designed to support the approval of chloramine-T for use in fish culture. ?? 2003 Elsevier Science B.V. All rights reserved.

The Validity of Left Ventricular Mass as a Surrogate End Point for All-Cause and Cardiovascular Mortality Outcomes in People With CKD: A Systematic Review and Meta-analysis.

PubMed

Badve, Sunil V; Palmer, Suetonia C; Strippoli, Giovanni F M; Roberts, Matthew A; Teixeira-Pinto, Armando; Boudville, Neil; Cass, Alan; Hawley, Carmel M; Hiremath, Swapnil S; Pascoe, Elaine M; Perkovic, Vlado; Whalley, Gillian A; Craig, Jonathan C; Johnson, David W

2016-10-01

Left ventricular mass (LVM) is a widely used surrogate end point in randomized trials involving people with chronic kidney disease (CKD) because treatment-induced LVM reductions are assumed to lower cardiovascular risk. The aim of this study was to assess the validity of LVM as a surrogate end point for all-cause and cardiovascular mortality in CKD. Systematic review and meta-analysis. Participants with any stages of CKD. Randomized controlled trials with 3 or more months' follow-up that reported LVM data. Any pharmacologic or nonpharmacologic intervention. The surrogate outcome of interest was LVM change from baseline to last measurement, and clinical outcomes of interest were all-cause and cardiovascular mortality. Standardized mean differences (SMDs) of LVM change and relative risk for mortality were estimated using pairwise random-effects meta-analysis. Correlations between surrogate and clinical outcomes were summarized across all interventions combined using bivariate random-effects Bayesian models, and 95% credible intervals were computed. 73 trials (6,732 participants) covering 25 intervention classes were included in the meta-analysis. Overall, risk of bias was uncertain or high. Only 3 interventions reduced LVM: erythropoiesis-stimulating agents (9 trials; SMD, -0.13; 95% CI, -0.23 to -0.03), renin-angiotensin-aldosterone system inhibitors (13 trials; SMD, -0.28; 95% CI, -0.45 to -0.12), and isosorbide mononitrate (2 trials; SMD, -0.43; 95% CI, -0.72 to -0.14). All interventions had uncertain effects on all-cause and cardiovascular mortality. There were weak and imprecise associations between the effects of interventions on LVM change and all-cause (32 trials; 5,044 participants; correlation coefficient, 0.28; 95% credible interval, -0.13 to 0.59) and cardiovascular mortality (13 trials; 2,327 participants; correlation coefficient, 0.30; 95% credible interval, -0.54 to 0.76). Limited long-term data, suboptimal quality of included studies. There was no clear and consistent association between intervention-induced LVM change and mortality. Evidence for LVM as a valid surrogate end point in CKD is currently lacking. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Validation of a deformable MRI to CT registration algorithm employing same day planning MRI for surrogate analysis.

PubMed

Padgett, Kyle R; Stoyanova, Radka; Pirozzi, Sara; Johnson, Perry; Piper, Jon; Dogan, Nesrin; Pollack, Alan

2018-03-01

Validating deformable multimodality image registrations is challenging due to intrinsic differences in signal characteristics and their spatial intensity distributions. Evaluating multimodality registrations using these spatial intensity distributions is also complicated by the fact that these metrics are often employed in the registration optimization process. This work evaluates rigid and deformable image registrations of the prostate in between diagnostic-MRI and radiation treatment planning-CT by utilizing a planning-MRI after fiducial marker placement as a surrogate. The surrogate allows for the direct quantitative analysis that can be difficult in the multimodality domain. For thirteen prostate patients, T2 images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day as the planning-CT (planning-MRI). The diagnostic-MRI was deformed to the planning-CT utilizing a commercially available algorithm which synthesizes a deformable image registration (DIR) algorithm from local rigid registrations. The planning-MRI provided an independent surrogate for the planning-CT for assessing registration accuracy using image similarity metrics, including Pearson correlation and normalized mutual information (NMI). A local analysis was performed by looking only within the prostate, proximal seminal vesicles, penile bulb, and combined areas. The planning-MRI provided an excellent surrogate for the planning-CT with residual error in fiducial alignment between the two datasets being submillimeter, 0.78 mm. DIR was superior to the rigid registration in 11 of 13 cases demonstrating a 27.37% improvement in NMI (P < 0.009) within a regional area surrounding the prostate and associated critical organs. Pearson correlations showed similar results, demonstrating a 13.02% improvement (P < 0.013). By utilizing the planning-MRI as a surrogate for the planning-CT, an independent evaluation of registration accuracy is possible. This population provides an ideal testing ground for MRI to CT DIR by obviating the need for multimodality comparisons which are inherently more challenging. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Multiplicative surrogate standard deviation: a group metric for the glycemic variability of individual hospitalized patients.

PubMed

Braithwaite, Susan S; Umpierrez, Guillermo E; Chase, J Geoffrey

2013-09-01

Group metrics are described to quantify blood glucose (BG) variability of hospitalized patients. The "multiplicative surrogate standard deviation" (MSSD) is the reverse-transformed group mean of the standard deviations (SDs) of the logarithmically transformed BG data set of each patient. The "geometric group mean" (GGM) is the reverse-transformed group mean of the means of the logarithmically transformed BG data set of each patient. Before reverse transformation is performed, the mean of means and mean of SDs each has its own SD, which becomes a multiplicative standard deviation (MSD) after reverse transformation. Statistical predictions and comparisons of parametric or nonparametric tests remain valid after reverse transformation. A subset of a previously published BG data set of 20 critically ill patients from the first 72 h of treatment under the SPRINT protocol was transformed logarithmically. After rank ordering according to the SD of the logarithmically transformed BG data of each patient, the cohort was divided into two equal groups, those having lower or higher variability. For the entire cohort, the GGM was 106 (÷/× 1.07) mg/dl, and MSSD was 1.24 (÷/× 1.07). For the subgroups having lower and higher variability, respectively, the GGM did not differ, 104 (÷/× 1.07) versus 109 (÷/× 1.07) mg/dl, but the MSSD differed, 1.17 (÷/× 1.03) versus 1.31 (÷/× 1.05), p = .00004. By using the MSSD with its MSD, groups can be characterized and compared according to glycemic variability of individual patient members. © 2013 Diabetes Technology Society.

Regression calibration for models with two predictor variables measured with error and their interaction, using instrumental variables and longitudinal data.

PubMed

Strand, Matthew; Sillau, Stefan; Grunwald, Gary K; Rabinovitch, Nathan

2014-02-10

Regression calibration provides a way to obtain unbiased estimators of fixed effects in regression models when one or more predictors are measured with error. Recent development of measurement error methods has focused on models that include interaction terms between measured-with-error predictors, and separately, methods for estimation in models that account for correlated data. In this work, we derive explicit and novel forms of regression calibration estimators and associated asymptotic variances for longitudinal models that include interaction terms, when data from instrumental and unbiased surrogate variables are available but not the actual predictors of interest. The longitudinal data are fit using linear mixed models that contain random intercepts and account for serial correlation and unequally spaced observations. The motivating application involves a longitudinal study of exposure to two pollutants (predictors) - outdoor fine particulate matter and cigarette smoke - and their association in interactive form with levels of a biomarker of inflammation, leukotriene E4 (LTE 4 , outcome) in asthmatic children. Because the exposure concentrations could not be directly observed, we used measurements from a fixed outdoor monitor and urinary cotinine concentrations as instrumental variables, and we used concentrations of fine ambient particulate matter and cigarette smoke measured with error by personal monitors as unbiased surrogate variables. We applied the derived regression calibration methods to estimate coefficients of the unobserved predictors and their interaction, allowing for direct comparison of toxicity of the different pollutants. We used simulations to verify accuracy of inferential methods based on asymptotic theory. Copyright © 2013 John Wiley & Sons, Ltd.

Development of size-selective sampling of Bacillus anthracis surrogate spores from simulated building air intake mixtures for analysis via laser-induced breakdown spectroscopy.

PubMed

Gibb-Snyder, Emily; Gullett, Brian; Ryan, Shawn; Oudejans, Lukas; Touati, Abderrahmane

2006-08-01

Size-selective sampling of Bacillus anthracis surrogate spores from realistic, common aerosol mixtures was developed for analysis by laser-induced breakdown spectroscopy (LIBS). A two-stage impactor was found to be the preferential sampling technique for LIBS analysis because it was able to concentrate the spores in the mixtures while decreasing the collection of potentially interfering aerosols. Three common spore/aerosol scenarios were evaluated, diesel truck exhaust (to simulate a truck running outside of a building air intake), urban outdoor aerosol (to simulate common building air), and finally a protein aerosol (to simulate either an agent mixture (ricin/anthrax) or a contaminated anthrax sample). Two statistical methods, linear correlation and principal component analysis, were assessed for differentiation of surrogate spore spectra from other common aerosols. Criteria for determining percentages of false positives and false negatives via correlation analysis were evaluated. A single laser shot analysis of approximately 4 percent of the spores in a mixture of 0.75 m(3) urban outdoor air doped with approximately 1.1 x 10(5) spores resulted in a 0.04 proportion of false negatives. For that same sample volume of urban air without spores, the proportion of false positives was 0.08.

The Prevalence and Characteristics of Fibromyalgia in the 2012 National Health Interview Survey.

PubMed

Walitt, Brian; Nahin, Richard L; Katz, Robert S; Bergman, Martin J; Wolfe, Frederick

2015-01-01

Most knowledge of fibromyalgia comes from the clinical setting, where healthcare-seeking behavior and selection issues influence study results. The characteristics of fibromyalgia in the general population have not been studied in detail. We developed and tested surrogate study specific criteria for fibromyalgia in rheumatology practices using variables from the US National Health Interview Survey (NHIS) and the modification (for surveys) of the 2010 American College of Rheumatology (ACR) preliminary fibromyalgia criteria. The surrogate criteria were applied to the 2012 NHIS and identified persons who satisfied criteria from symptom data. The NHIS weighted sample of 8446 persons represents 225.7 million US adults. Fibromyalgia was identified in 1.75% (95% CI 1.42, 2.07), or 3.94 million persons. However, 73% of identified cases self-reported a physician's diagnosis other than fibromyalgia. Identified cases had high levels of self-reported pain, non-pain symptoms, comorbidity, psychological distress, medical costs, Social Security and work disability. Caseness was associated with gender, education, ethnicity, citizenship and unhealthy behaviors. Demographics, behaviors, and comorbidity were predictive of case status. Examination of the surrogate polysymptomatic distress scale (PSD) of the 2010 ACR criteria found fibromyalgia symptoms extending through the full length of the scale. Persons identified with criteria-based fibromyalgia have severe symptoms, but most (73%) have not received a clinical diagnosis of fibromyalgia. The association of fibromyalgia-like symptoms over the full length of the PSD scale with physiological as well as mental stressors suggests PSD may be a universal response variable rather than one restricted to fibromyalgia.

The Prevalence and Characteristics of Fibromyalgia in the 2012 National Health Interview Survey

PubMed Central

Walitt, Brian; Nahin, Richard L.; Katz, Robert S.; Bergman, Martin J.; Wolfe, Frederick

2015-01-01

Background Most knowledge of fibromyalgia comes from the clinical setting, where healthcare-seeking behavior and selection issues influence study results. The characteristics of fibromyalgia in the general population have not been studied in detail. Methods We developed and tested surrogate study specific criteria for fibromyalgia in rheumatology practices using variables from the US National Health Interview Survey (NHIS) and the modification (for surveys) of the 2010 American College of Rheumatology (ACR) preliminary fibromyalgia criteria. The surrogate criteria were applied to the 2012 NHIS and identified persons who satisfied criteria from symptom data. The NHIS weighted sample of 8446 persons represents 225.7 million US adults. Results Fibromyalgia was identified in 1.75% (95% CI 1.42, 2.07), or 3.94 million persons. However, 73% of identified cases self-reported a physician’s diagnosis other than fibromyalgia. Identified cases had high levels of self-reported pain, non-pain symptoms, comorbidity, psychological distress, medical costs, Social Security and work disability. Caseness was associated with gender, education, ethnicity, citizenship and unhealthy behaviors. Demographics, behaviors, and comorbidity were predictive of case status. Examination of the surrogate polysymptomatic distress scale (PSD) of the 2010 ACR criteria found fibromyalgia symptoms extending through the full length of the scale. Conclusions Persons identified with criteria-based fibromyalgia have severe symptoms, but most (73%) have not received a clinical diagnosis of fibromyalgia. The association of fibromyalgia-like symptoms over the full length of the PSD scale with physiological as well as mental stressors suggests PSD may be a universal response variable rather than one restricted to fibromyalgia. PMID:26379048

Biomarker Surrogates Do Not Accurately Predict Sputum Eosinophils and Neutrophils in Asthma

PubMed Central

Hastie, Annette T.; Moore, Wendy C.; Li, Huashi; Rector, Brian M.; Ortega, Victor E.; Pascual, Rodolfo M.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

2013-01-01

Background Sputum eosinophils (Eos) are a strong predictor of airway inflammation, exacerbations, and aid asthma management, whereas sputum neutrophils (Neu) indicate a different severe asthma phenotype, potentially less responsive to TH2-targeted therapy. Variables such as blood Eos, total IgE, fractional exhaled nitric oxide (FeNO) or FEV1% predicted, may predict airway Eos, while age, FEV1%predicted, or blood Neu may predict sputum Neu. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway Eos and Neu, individually or combined, is not established. Objectives To determine whether blood Eos, FeNO, and IgE accurately predict sputum eosinophils, and age, FEV1% predicted, and blood Neu accurately predict sputum neutrophils (Neu). Methods Subjects in the Wake Forest Severe Asthma Research Program (N=328) were characterized by blood and sputum cells, healthcare utilization, lung function, FeNO, and IgE. Multiple analytical techniques were utilized. Results Despite significant association with sputum Eos, blood Eos, FeNO and total IgE did not accurately predict sputum Eos, and combinations of these variables failed to improve prediction. Age, FEV1%predicted and blood Neu were similarly unsatisfactory for prediction of sputum Neu. Factor analysis and stepwise selection found FeNO, IgE and FEV1% predicted, but not blood Eos, correctly predicted 69% of sputum Eos

The role of serum non-cholesterol sterols as surrogate markers of absolute cholesterol synthesis and absorption.

PubMed

Miettinen, T A; Gylling, H; Nissinen, M J

2011-10-01

To study the whole-body cholesterol metabolism in man, cholesterol synthesis and absorption need to be measured. Because of the complicated methods of the measurements, new approaches were developed including the analysis of serum non-cholesterol sterols. In current lipidologic papers and even in intervention studies, serum non-cholesterol sterols are frequently used as surrogate markers of cholesterol metabolism without any validation to the absolute metabolic variables. The present review compares serum non-cholesterol sterols with absolute measurements of cholesterol synthesis and absorption in published papers to find out whether the serum markers are valid indicators of cholesterol metabolism in various conditions. During statin treatment, during interventions of dietary fat, and in type 2 diabetes the relative and absolute variables of cholesterol synthesis and absorption were frequently but not constantly correlated with each other. In some occasions, especially in subjects with apolipoprotein E3/4 and E4/4 phenotypes, the relative metabolic markers were even more sensitive than the absolute ones to reflect changes in cholesterol metabolism during dietary interventions. Even in general population at very high absorption the homeostasis of cholesterol metabolism is disturbed damaging the validity of the serum markers. It is worth using several instead of only one precursor and absorption sterol marker for making conclusions of altered synthesis or absorption of cholesterol, and even then the presence of at least some absolute measurement is valuable. During consumption of plant sterol-enriched diets and in situations of interfered cholesterol homeostasis the relative markers do not adequately reflect cholesterol metabolism. Accordingly, the validity of the relative markers of cholesterol metabolism should not be considered as self-evident. Copyright © 2011 Elsevier B.V. All rights reserved.

Serum cystatin C: a surrogate marker for the characteristics of peritoneal membrane in dialysis patients.

PubMed

Al-Wakeel, Jamal S; Hammad, Durdana; Memon, Nawaz Ali; Tarif, Nauman; Shah, Iqbal; Chaudhary, Abdulrauf

2009-03-01

To evaluate whether cystatin C levels can be a surrogate marker of creatinine clearance and reflect the characteristics of peritoneal membrane in dialysis patients, we performed peritoneal equilibration tests (PET) in 18 anuric adult chronic peritoneal dialysis (PD) patients with a mean age of 39.7 +/- 20 years. All the samples were analyzed for urea, creatinine, and cystatin C. Peritoneal transport, mass transfer, and peritoneal clearance of cystatin C were calculated. Correlation and regression analysis was done using cystatin C as a dependent variable and age, sex, height, weight, body surface area, and creatinine as independent variables. Cystatin C demonstrated a significant time dependent increase of dialysate concentration and decline in the serum concentrations during PET, and a strong correlation between serum creatinine and serum cystatin C concentrations(r: 0.62, p= 0.008). The trans-peritoneal clearance (mL/min/1.73 m 2 ) of cystatin C was related to its serum concentration and was similar to creatinine in its pattern but of smaller magnitude. Peritoneal mass transfer (mg/4 hr per 1.73 m 2 ) for cystatin C serum creatinine was 1.68 +/- 0.67 and 73.3 +/- 29.8, respectively. The dialysis/plasma D/P cystatin C concentration was > or = 0.1 at 4 hrs of PET denoted high peritoneal transport, while the values of < 0.1 denoted low transport type. We conclude that cystatin C follows the same pattern of peritoneal exchange as creatinine but the magnitude of transfer is many folds lower than creatinine. At present clinical utility of cystatin C in the evaluation of solute clearance is probably limited due to the minute amounts transferred across the membrane and the high renal clearance in the presence of residual renal function.

PERSONAL MEASURES OF POWER-FREQUENCY MAGNETIC FIELD EXPOSURE AMONG MEN FROM AN INFERTILITY CLINIC: DISTRIBUTION, TEMPORAL VARIABILITY AND CORRELATION WITH THEIR FEMALE PARTNERS' EXPOSURE

PubMed Central

Lewis, Ryan C.; Hauser, Russ; Maynard, Andrew D.; Neitzel, Richard L.; Wang, Lu; Kavet, Robert; Morey, Patricia; Ford, Jennifer B.; Meeker, John D.

2016-01-01

Power-frequency magnetic field exposure science as it relates to men and couples have not been explored despite the advantage of this information in the design and interpretation of reproductive health epidemiology studies. This analysis examined the distribution and temporal variability of exposures in men, and the correlation of exposures within couples using data from a longitudinal study of 25 men and their female partners recruited from an infertility clinic. The average and 90th percentile demonstrated fair to good reproducibility, whereas the maximum showed poor reproducibility over repeated sampling days, each separated by a median of 4.6 weeks. Average magnetic field exposures were also strongly correlated within couples, suggesting that one partner's data could be used as a surrogate in the absence of data from the other for this metric. Environment was also an important effect modifier in these explored matters. These issues should be considered in future relevant epidemiology studies. PMID:26705359

Validation of the Family Inpatient Communication Survey.

PubMed

Torke, Alexia M; Monahan, Patrick; Callahan, Christopher M; Helft, Paul R; Sachs, Greg A; Wocial, Lucia D; Slaven, James E; Montz, Kianna; Inger, Lev; Burke, Emily S

2017-01-01

Although many family members who make surrogate decisions report problems with communication, there is no validated instrument to accurately measure surrogate/clinician communication for older adults in the acute hospital setting. The objective of this study was to validate a survey of surrogate-rated communication quality in the hospital that would be useful to clinicians, researchers, and health systems. After expert review and cognitive interviewing (n = 10 surrogates), we enrolled 350 surrogates (250 development sample and 100 validation sample) of hospitalized adults aged 65 years and older from three hospitals in one metropolitan area. The communication survey and a measure of decision quality were administered within hospital days 3 and 10. Mental health and satisfaction measures were administered six to eight weeks later. Factor analysis showed support for both one-factor (Total Communication) and two-factor models (Information and Emotional Support). Item reduction led to a final 30-item scale. For the validation sample, internal reliability (Cronbach's alpha) was 0.96 (total), 0.94 (Information), and 0.90 (Emotional Support). Confirmatory factor analysis fit statistics were adequate (one-factor model, comparative fit index = 0.981, root mean square error of approximation = 0.62, weighted root mean square residual = 1.011; two-factor model comparative fit index = 0.984, root mean square error of approximation = 0.055, weighted root mean square residual = 0.930). Total score and subscales showed significant associations with the Decision Conflict Scale (Pearson correlation -0.43, P < 0.001 for total score). Emotional Support was associated with improved mental health outcomes at six to eight weeks, such as anxiety (-0.19 P < 0.001), and Information was associated with satisfaction with the hospital stay (0.49, P < 0.001). The survey shows high reliability and validity in measuring communication experiences for hospital surrogates. The scale has promise for measurement of communication quality and is predictive of important outcomes, such as surrogate satisfaction and well-being. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Detrended Fluctuation Analysis and Adaptive Fractal Analysis of Stride Time Data in Parkinson's Disease: Stitching Together Short Gait Trials

PubMed Central

Liebherr, Magnus; Haas, Christian T.

2014-01-01

Variability indicates motor control disturbances and is suitable to identify gait pathologies. It can be quantified by linear parameters (amplitude estimators) and more sophisticated nonlinear methods (structural information). Detrended Fluctuation Analysis (DFA) is one method to measure structural information, e.g., from stride time series. Recently, an improved method, Adaptive Fractal Analysis (AFA), has been proposed. This method has not been applied to gait data before. Fractal scaling methods (FS) require long stride-to-stride data to obtain valid results. However, in clinical studies, it is not usual to measure a large number of strides (e.g., strides). Amongst others, clinical gait analysis is limited due to short walkways, thus, FS seem to be inapplicable. The purpose of the present study was to evaluate FS under clinical conditions. Stride time data of five self-paced walking trials ( strides each) of subjects with PD and a healthy control group (CG) was measured. To generate longer time series, stride time sequences were stitched together. The coefficient of variation (CV), fractal scaling exponents (DFA) and (AFA) were calculated. Two surrogate tests were performed: A) the whole time series was randomly shuffled; B) the single trials were randomly shuffled separately and afterwards stitched together. CV did not discriminate between PD and CG. However, significant differences between PD and CG were found concerning and . Surrogate version B yielded a higher mean squared error and empirical quantiles than version A. Hence, we conclude that the stitching procedure creates an artificial structure resulting in an overestimation of true . The method of stitching together sections of gait seems to be appropriate in order to distinguish between PD and CG with FS. It provides an approach to integrate FS as standard in clinical gait analysis and to overcome limitations such as short walkways. PMID:24465708

Comparative study of surrogate models for groundwater contamination source identification at DNAPL-contaminated sites

NASA Astrophysics Data System (ADS)

Hou, Zeyu; Lu, Wenxi

2018-05-01

Knowledge of groundwater contamination sources is critical for effectively protecting groundwater resources, estimating risks, mitigating disaster, and designing remediation strategies. Many methods for groundwater contamination source identification (GCSI) have been developed in recent years, including the simulation-optimization technique. This study proposes utilizing a support vector regression (SVR) model and a kernel extreme learning machine (KELM) model to enrich the content of the surrogate model. The surrogate model was itself key in replacing the simulation model, reducing the huge computational burden of iterations in the simulation-optimization technique to solve GCSI problems, especially in GCSI problems of aquifers contaminated by dense nonaqueous phase liquids (DNAPLs). A comparative study between the Kriging, SVR, and KELM models is reported. Additionally, there is analysis of the influence of parameter optimization and the structure of the training sample dataset on the approximation accuracy of the surrogate model. It was found that the KELM model was the most accurate surrogate model, and its performance was significantly improved after parameter optimization. The approximation accuracy of the surrogate model to the simulation model did not always improve with increasing numbers of training samples. Using the appropriate number of training samples was critical for improving the performance of the surrogate model and avoiding unnecessary computational workload. It was concluded that the KELM model developed in this work could reasonably predict system responses in given operation conditions. Replacing the simulation model with a KELM model considerably reduced the computational burden of the simulation-optimization process and also maintained high computation accuracy.

A surrogate analyte method to determine D-serine in mouse brain using liquid chromatography-tandem mass spectrometry.

PubMed

Kinoshita, Kohnosuke; Jingu, Shigeji; Yamaguchi, Jun-ichi

2013-01-15

A bioanalytical method for determining endogenous d-serine levels in the mouse brain using a surrogate analyte and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed. [2,3,3-(2)H]D-serine and [(15)N]D-serine were used as a surrogate analyte and an internal standard, respectively. The surrogate analyte was spiked into brain homogenate to yield calibration standards and quality control (QC) samples. Both endogenous and surrogate analytes were extracted using protein precipitation followed by solid phase extraction. Enantiomeric separation was achieved on a chiral crown ether column with an analysis time of only 6 min without any derivatization. The column eluent was introduced into an electrospray interface of a triple-quadrupole mass spectrometer. The calibration range was 1.00 to 300 nmol/g, and the method showed acceptable accuracy and precision at all QC concentration levels from a validation point of view. In addition, the brain d-serine levels of normal mice determined using this method were the same as those obtained by a standard addition method, which is time-consuming but is often used for the accurate measurement of endogenous substances. Thus, this surrogate analyte method should be applicable to the measurement of d-serine levels as a potential biomarker for monitoring certain effects of drug candidates on the central nervous system. Copyright © 2012 Elsevier Inc. All rights reserved.

Impact of copula directional specification on multi-trial evaluation of surrogate endpoints

PubMed Central

Renfro, Lindsay A.; Shang, Hongwei; Sargent, Daniel J.

2014-01-01

Evaluation of surrogate endpoints using patient-level data from multiple trials is the gold standard, where multi-trial copula models are used to quantify both patient-level and trial-level surrogacy. While limited consideration has been given in the literature to copula choice (e.g., Clayton), no prior consideration has been given to direction of implementation (via survival versus distribution functions). We demonstrate that evenwith the “correct” copula family, directional misspecification leads to biased estimates of patient-level and trial-level surrogacy. We illustrate with a simulation study and a re-analysis of disease-free survival as a surrogate for overall survival in early stage colon cancer. PMID:24905465

Not all Laminaria digitata are the same! Phenotypic plasticity and the selection of appropriate surrogate macroalgae for ecohydraulic experimentation

NASA Astrophysics Data System (ADS)

Thomas, Robert E.; McLelland, Stuart J.; Henry, Pierre-Yves T.; Paul, Maike; Eiff, Olivier; Evertsen, Antti-Jussi O.; Aberle, Jochen; Teacă, Adrian

2015-04-01

Whilst early physical modelling and theoretical studies of the interactions between vegetation and flowing water employed rigid structures such as wooden dowels, recent studies have progressed to flexible surrogate plants. However, even appropriately-scaled flexible surrogates fail to capture the variability in thallus morphology, flexibility and strength, both within and between individuals, and frontal or planform area over space and time. Furthermore, although there have been a number of field studies, measurements of hydraulic variables have generally been limited to time-averaged at-a-point measurements that aim to approximate the depth-mean velocity. This is problematic because in spatially heterogeneous flows, point measurements are dependent upon the sampling location. Herein, we describe research carried out by the participants in the PISCES work package of the HYDRALAB IV project that sought to address these limitations and assess the level of complexity needed to adequately reproduce the hydrodynamics of the natural system in physical models. We selected an 11 m long × 6 m wide region of a tidal inlet, the Hopavågen Bay, Sør-Trøndelag, Norway, that contained 19 Laminaria digitata thalli and 101 other macroalgae thalli. Two L. digitata specimens ~0.50 m apart were selected for detailed study and a 2 m long × 8 m wide frame was oriented around them by enforcing zero cross-stream discharge at its upstream edge. We then quantified: 1. the mean and turbulent flow field of the undisturbed condition (Case A); 2. the positions, geometrical and biomechanical properties of the macroalgae; and 3. the mean and turbulent flow field after the macroalgae were completely removed (Case B). Later, Case A was replicated in the same location (±0.025 m) before the 19 L. digitata thalli were replaced with 19 "optimized" surrogates (Case C). These three cases were then repeated in the Total Environment Simulator at the University of Hull, UK. Live macroalgae thalli could not be transported from Norway to the UK, so we used the same species of live macroalgae harvested from a wave-dominated coast in the UK. These algae exhibited longer, narrower and more flexible blades. The same surrogate plants were used in both the field and flume experiments. In all cases, a profiling ADV was used to collect 45 velocity profiles composed of up to seven 35 mm-high profiles collected for 240 s at 100 Hz, at a streamwise spacing of 0.25 m and cross-stream spacing of 0.20 m. The results show that the live macroalgae in the flume simulation exerted less influence on the flow field than the live macroalgae at the field site. In contrast, the "optimized" surrogate macroalgae behaved similarly to the live algae at the field site and yielded similar mean and turbulent velocity fields as our prototype live macroalgae. This emphasizes both the importance of phenotypic plasticity and the importance of selecting surrogates that adequately represent the mean characteristics of the species of interest.

Imputation of a true endpoint from a surrogate: application to a cluster randomized controlled trial with partial information on the true endpoint.

PubMed

Nixon, Richard M; Duffy, Stephen W; Fender, Guy R K

2003-09-24

The Anglia Menorrhagia Education Study (AMES) is a randomized controlled trial testing the effectiveness of an education package applied to general practices. Binary data are available from two sources; general practitioner reported referrals to hospital, and referrals to hospital determined by independent audit of the general practices. The former may be regarded as a surrogate for the latter, which is regarded as the true endpoint. Data are only available for the true end point on a sub set of the practices, but there are surrogate data for almost all of the audited practices and for most of the remaining practices. The aim of this paper was to estimate the treatment effect using data from every practice in the study. Where the true endpoint was not available, it was estimated by three approaches, a regression method, multiple imputation and a full likelihood model. Including the surrogate data in the analysis yielded an estimate of the treatment effect which was more precise than an estimate gained from using the true end point data alone. The full likelihood method provides a new imputation tool at the disposal of trials with surrogate data.

3.4.1: Numerical Methods for Propagating Uncertainty Across Scales and for Hybrid Stochastic-Deterministic Systems

DTIC Science & Technology

2017-10-04

Fisher’s equation, as well as a two‐dimensional Allen‐ Cahn equation. We  observe  good performance of the  method  for nonlinear problems as well as...rates, discrepancies between  the  two  methods   are  observed ,  hence  revealing  strong  additional  coupling  between  different  fluctuating variables...of random fields based on  observations  of surrogate models or hierarchies of surrogate models.  Our  method  builds upon recent work on recursive

Surrogate measures and consistent surrogates

PubMed Central

VanderWeele, Tyler J.

2014-01-01

Summary Surrogates which allow one to predict the effect of the treatment on the outcome of interest from the effect of the treatment on the surrogate are of importance when it is difficult or expensive to measure the primary outcome. Unfortunately, the use of such surrogates can give rise to paradoxical situations in which the effect of the treatment on the surrogate is positive, the surrogate and outcome are strongly positively correlated, but the effect of the treatment on the outcome is negative, a phenomenon sometimes referred to as the "surrogate paradox." New results are given for consistent surrogates that extend the existing literature on sufficient conditions that ensure the surrogate paradox is not manifest. Specifically, it is shown that for the surrogate paradox to beman.est it must be the case that either there is (i) a direct effect of treatment on the outcome not through the surrogate and in the opposite direction as that through the surrogate or (ii) confounding for the effect of the surrogate on the outcome, or (iii) a lack of transitivity so that treatment does not positively affect the surrogate for all the same individuals for which the surrogate positively affects the outcome. The conditions for consistent surrogates and the results of the paper are important because they allow investigators to predict the direction of the effect of the treatment on the outcome simply from the direction of the effect of the treatment on the surrogate. These results on consistent surrogates are then related to the four approaches to surrogate outcomes described by Joffe and Greene (2009, Biometrics 65, 530–538) to assess whether the standard criterion used by these approaches to assess whether a surrogate is "good" suffices to avoid the surrogate paradox. PMID:24073861

Outcome switching in randomized controlled oncology trials reporting on surrogate endpoints: a cross-sectional analysis.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-08-23

Inconsistent reporting of clinical trials is well-known in the literature. Despite this, factors associated with poor practice such as outcome switching in clinical trials are poorly understood. We performed a cross-sectional analysis to evaluate the prevalence of, and the factors associated with outcome switching. PubMed and Embase were searched for pharmaceutical randomized controlled trials (RCTs) in oncology reporting on a surrogate primary outcome published in 2015. Outcome switching was present in 18% (39/216). First-author male sex was significantly more likely associated with outcome switching compared to female sex with an OR of 3.05 (95% CI 1.07-8.64, p = 0.04) after multivariable adjustment. For-profit funded RCTs were less likely associated with outcome switching compared to non-profit funded research with an OR of 0.22 (95% CI 0.07-0.74, p = 0.01). First author male sex was more likely associated with outcome switching compared to female sex in drug oncology RCTs reporting on a primary surrogate endpoint. For-profit funded research was less likely associated with outcome switching compared to research funded by non-profit organizations. Furthermore, 18 percent of drug oncology trials reporting on a surrogate endpoint could have a higher risk of false positive results due to primary outcome switching.

Uncertainty propagation of p-boxes using sparse polynomial chaos expansions

NASA Astrophysics Data System (ADS)

Schöbi, Roland; Sudret, Bruno

2017-06-01

In modern engineering, physical processes are modelled and analysed using advanced computer simulations, such as finite element models. Furthermore, concepts of reliability analysis and robust design are becoming popular, hence, making efficient quantification and propagation of uncertainties an important aspect. In this context, a typical workflow includes the characterization of the uncertainty in the input variables. In this paper, input variables are modelled by probability-boxes (p-boxes), accounting for both aleatory and epistemic uncertainty. The propagation of p-boxes leads to p-boxes of the output of the computational model. A two-level meta-modelling approach is proposed using non-intrusive sparse polynomial chaos expansions to surrogate the exact computational model and, hence, to facilitate the uncertainty quantification analysis. The capabilities of the proposed approach are illustrated through applications using a benchmark analytical function and two realistic engineering problem settings. They show that the proposed two-level approach allows for an accurate estimation of the statistics of the response quantity of interest using a small number of evaluations of the exact computational model. This is crucial in cases where the computational costs are dominated by the runs of high-fidelity computational models.

Uncertainty propagation of p-boxes using sparse polynomial chaos expansions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schöbi, Roland, E-mail: schoebi@ibk.baug.ethz.ch; Sudret, Bruno, E-mail: sudret@ibk.baug.ethz.ch

2017-06-15

In modern engineering, physical processes are modelled and analysed using advanced computer simulations, such as finite element models. Furthermore, concepts of reliability analysis and robust design are becoming popular, hence, making efficient quantification and propagation of uncertainties an important aspect. In this context, a typical workflow includes the characterization of the uncertainty in the input variables. In this paper, input variables are modelled by probability-boxes (p-boxes), accounting for both aleatory and epistemic uncertainty. The propagation of p-boxes leads to p-boxes of the output of the computational model. A two-level meta-modelling approach is proposed using non-intrusive sparse polynomial chaos expansions tomore » surrogate the exact computational model and, hence, to facilitate the uncertainty quantification analysis. The capabilities of the proposed approach are illustrated through applications using a benchmark analytical function and two realistic engineering problem settings. They show that the proposed two-level approach allows for an accurate estimation of the statistics of the response quantity of interest using a small number of evaluations of the exact computational model. This is crucial in cases where the computational costs are dominated by the runs of high-fidelity computational models.« less

Upper and Lower Neck Loads in Belted Human Surrogates in Frontal Impacts

PubMed Central

Yoganandan, Narayan; Pintar, Frank A.; Moore, Jason; Rinaldi, James; Schlick, Michael; Maiman, Dennis J.

2012-01-01

The upper and lower neck loads in the restrained Hybrid III dummy and Test Device for Human Occupant Restraint (THOR) were computed in simulated frontal impact sled tests at low, medium, and high velocities; repeatability performance of the two dummies were evaluated at all energy inputs; peak forces and moments were compared with computed loads at the occipital condyles and cervical-thoracic junctions from tests using post mortem human surrogates (PMHS). A custom sled buck was used to position the surrogates. Repeated tests were conducted at each velocity for each dummy and sufficient time was allowed to elapse between the two experiments. The upper and lower neck forces and moments were determined from load cell measures and its locations with respect to the ends of the neck. Both dummies showed good repeatability for axial and shear forces and bending moments at all changes in velocity inputs. Morphological characteristics in the neck loading responses were similar in all surrogates, although the peak magnitudes of the variables differed. In general, the THOR better mimicked the PMHS response than the Hybrid III dummy, and factors such as neck design and chest compliance were attributed to the observed variations. While both dummies were not designed for use at the two extremes of the tested velocities, results from the present study indicate that, currently the THOR may be the preferred anthropomorphic testing device in crashworthiness research studies and full-scale vehicle tests at all velocities. PMID:23169123

Surrogate health information seeking in Europe: Influence of source type and social network variables.

PubMed

Reifegerste, Doreen; Bachl, Marko; Baumann, Eva

2017-07-01

Health information seeking on behalf of others is an important form of social support by which laypeople provide important sources of information for patients. Based on social network theory, we analyze whether this phenomenon also occurs in offline sources. We also seek to learn more about the type of relationships between information seekers and patients, as research to date indicates that surrogate seeking mostly occurs in close relationships between the seeker and the patient. Using a large-scale representative survey from the 28 member states of the European Union (N=26,566), our data comprise all respondents who reported seeking health information online or offline (n=18,750; 70.6%). Within the past year, 61.0% of the online health information seekers and 61.1% of the offline health information seekers had searched on behalf of someone else. Independent of the information channel, surrogate seekers primarily searched for health information for family members (online: 89.8%; offline: 92.8%); they were significantly less likely to search for information on behalf of someone with whom they had weaker ties, such as colleagues (online: 25.1%; offline: 24.4%). In a multilevel generalized linear model, living together with someone was by far the most relevant determinant for surrogate seeking, with differences between countries or Internet activity being less important. These results support the assumptions of social network theory. Implications are discussed, especially with regard to the provision of adequate health information. Copyright © 2017 Elsevier B.V. All rights reserved.

Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina

EPA Science Inventory

Air pollution health studies of fine particulate matter (diameter ≤2.5 μm, PM2.5) often use outdoor concentrations as exposure surrogates. Failure to account for variability of indoor infiltration of ambient PM2.5 and time indoors can induce exposure errors. We developed an...

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery.

PubMed

Belgiu, Mariana; Dr Guţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

PubMed Central

Belgiu, Mariana; Drǎguţ, Lucian; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules. PMID:24623959

Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery

NASA Astrophysics Data System (ADS)

Belgiu, Mariana; ǎguţ, Lucian, , Dr; Strobl, Josef

2014-01-01

The increasing availability of high resolution imagery has triggered the need for automated image analysis techniques, with reduced human intervention and reproducible analysis procedures. The knowledge gained in the past might be of use to achieving this goal, if systematically organized into libraries which would guide the image analysis procedure. In this study we aimed at evaluating the variability of digital classifications carried out by three experts who were all assigned the same interpretation task. Besides the three classifications performed by independent operators, we developed an additional rule-based classification that relied on the image classifications best practices found in the literature, and used it as a surrogate for libraries of object characteristics. The results showed statistically significant differences among all operators who classified the same reference imagery. The classifications carried out by the experts achieved satisfactory results when transferred to another area for extracting the same classes of interest, without modification of the developed rules.

Material and morphology parameter sensitivity analysis in particulate composite materials

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyu; Oskay, Caglar

2017-12-01

This manuscript presents a novel parameter sensitivity analysis framework for damage and failure modeling of particulate composite materials subjected to dynamic loading. The proposed framework employs global sensitivity analysis to study the variance in the failure response as a function of model parameters. In view of the computational complexity of performing thousands of detailed microstructural simulations to characterize sensitivities, Gaussian process (GP) surrogate modeling is incorporated into the framework. In order to capture the discontinuity in response surfaces, the GP models are integrated with a support vector machine classification algorithm that identifies the discontinuities within response surfaces. The proposed framework is employed to quantify variability and sensitivities in the failure response of polymer bonded particulate energetic materials under dynamic loads to material properties and morphological parameters that define the material microstructure. Particular emphasis is placed on the identification of sensitivity to interfaces between the polymer binder and the energetic particles. The proposed framework has been demonstrated to identify the most consequential material and morphological parameters under vibrational and impact loads.

Co-Optimization of CO 2-EOR and Storage Processes in Mature Oil Reservoirs

DOE PAGES

Ampomah, William; Balch, Robert S.; Grigg, Reid B.; ...

2016-08-02

This article presents an optimization methodology for CO 2 enhanced oil recovery in partially depleted reservoirs. A field-scale compositional reservoir flow model was developed for assessing the performance history of an active CO 2 flood and for optimizing both oil production and CO 2 storage in the Farnsworth Unit (FWU), Ochiltree County, Texas. A geological framework model constructed from geophysical, geological, and engineering data acquired from the FWU was the basis for all reservoir simulations and the optimization method. An equation of state was calibrated with laboratory fluid analyses and subsequently used to predict the thermodynamic minimum miscible pressure (MMP).more » Initial history calibrations of primary, secondary and tertiary recovery were conducted as the basis for the study. After a good match was achieved, an optimization approach consisting of a proxy or surrogate model was constructed with a polynomial response surface method (PRSM). The PRSM utilized an objective function that maximized both oil recovery and CO 2 storage. Experimental design was used to link uncertain parameters to the objective function. Control variables considered in this study included: water alternating gas cycle and ratio, production rates and bottom-hole pressure of injectors and producers. Other key parameters considered in the modeling process were CO 2 purchase, gas recycle and addition of infill wells and/or patterns. The PRSM proxy model was ‘trained’ or calibrated with a series of training simulations. This involved an iterative process until the surrogate model reached a specific validation criterion. A sensitivity analysis was first conducted to ascertain which of these control variables to retain in the surrogate model. A genetic algorithm with a mixed-integer capability optimization approach was employed to determine the optimum developmental strategy to maximize both oil recovery and CO 2 storage. The proxy model reduced the computational cost significantly. The validation criteria of the reduced order model ensured accuracy in the dynamic modeling results. The prediction outcome suggested robustness and reliability of the genetic algorithm for optimizing both oil recovery and CO 2 storage. The reservoir modeling approach used in this study illustrates an improved approach to optimizing oil production and CO 2 storage within partially depleted oil reservoirs such as FWU. Lastly, this study may serve as a benchmark for potential CO 2–EOR projects in the Anadarko basin and/or geologically similar basins throughout the world.« less

Co-Optimization of CO 2-EOR and Storage Processes in Mature Oil Reservoirs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ampomah, William; Balch, Robert S.; Grigg, Reid B.

This article presents an optimization methodology for CO 2 enhanced oil recovery in partially depleted reservoirs. A field-scale compositional reservoir flow model was developed for assessing the performance history of an active CO 2 flood and for optimizing both oil production and CO 2 storage in the Farnsworth Unit (FWU), Ochiltree County, Texas. A geological framework model constructed from geophysical, geological, and engineering data acquired from the FWU was the basis for all reservoir simulations and the optimization method. An equation of state was calibrated with laboratory fluid analyses and subsequently used to predict the thermodynamic minimum miscible pressure (MMP).more » Initial history calibrations of primary, secondary and tertiary recovery were conducted as the basis for the study. After a good match was achieved, an optimization approach consisting of a proxy or surrogate model was constructed with a polynomial response surface method (PRSM). The PRSM utilized an objective function that maximized both oil recovery and CO 2 storage. Experimental design was used to link uncertain parameters to the objective function. Control variables considered in this study included: water alternating gas cycle and ratio, production rates and bottom-hole pressure of injectors and producers. Other key parameters considered in the modeling process were CO 2 purchase, gas recycle and addition of infill wells and/or patterns. The PRSM proxy model was ‘trained’ or calibrated with a series of training simulations. This involved an iterative process until the surrogate model reached a specific validation criterion. A sensitivity analysis was first conducted to ascertain which of these control variables to retain in the surrogate model. A genetic algorithm with a mixed-integer capability optimization approach was employed to determine the optimum developmental strategy to maximize both oil recovery and CO 2 storage. The proxy model reduced the computational cost significantly. The validation criteria of the reduced order model ensured accuracy in the dynamic modeling results. The prediction outcome suggested robustness and reliability of the genetic algorithm for optimizing both oil recovery and CO 2 storage. The reservoir modeling approach used in this study illustrates an improved approach to optimizing oil production and CO 2 storage within partially depleted oil reservoirs such as FWU. Lastly, this study may serve as a benchmark for potential CO 2–EOR projects in the Anadarko basin and/or geologically similar basins throughout the world.« less

Progression-free survival/time to progression as a potential surrogate for overall survival in HR+, HER2- metastatic breast cancer.

PubMed

Forsythe, Anna; Chandiwana, David; Barth, Janina; Thabane, Marroon; Baeck, Johan; Tremblay, Gabriel

2018-01-01

Several recent randomized controlled trials (RCTs) in hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) metastatic breast cancer (MBC) have demonstrated significant improvements in progression-free survival (PFS); however, few have reported improvement in overall survival (OS). The surrogacy of PFS or time to progression (TTP) for OS has not been formally investigated in HR+, HER2- MBC. A systematic literature review of RCTs in HR+, HER2- MBC was conducted to identify studies that reported both median PFS/TTP and OS. The correlation between PFS/TTP and OS was evaluated using Pearson's product-moment correlation and Spearman's rank correlation. Subgroup analyses were performed to explore possible reasons for heterogeneity. Errors-in-variables weighted least squares regression (LSR) was used to model incremental OS months as a function of incremental PFS/TTP months. An exploratory analysis investigated the impact of three covariates (chemotherapy vs hormonal/targeted therapy, PFS vs TTP, and first-line therapy vs second-line therapy or greater) on OS prediction. The lower 95% prediction band was used to determine the minimum incremental PFS/TTP months required to predict OS benefit (surrogate threshold effect [STE]). Forty studies were identified. There was a statistically significant correlation between median PFS/TTP and OS (Pearson =0.741, P =0.000; Spearman =0.650, P =0.000). These results proved consistent for chemotherapy and hormonal/targeted therapy. Univariate LSR analysis yielded an R 2 of 0.354 with 1 incremental PFS/TTP month corresponding to 1.13 incremental OS months. Controlling the type of treatment (chemotherapy vs hormonal/targeted therapy), line of therapy (first vs subsequent), and progression measure (PFS vs TTP) led to an improved R 2 of 0.569 with 1 PFS/TTP month corresponding to 0.78 OS months. The STE for OS benefit was 5-6 months of incremental PFS/TTP. We demonstrated a significant association between PFS/TTP and OS, which may justify the use of PFS/TTP as a surrogate for OS benefit in HR+, HER2- MBC.

Surrogate outcomes: experiences at the Common Drug Review

PubMed Central

2013-01-01

Background Surrogate outcomes are a significant challenge in drug evaluation for health technology assessment (HTA) agencies. The research objectives were to: identify factors associated with surrogate use and acceptability in Canada’s Common Drug Review (CDR) recommendations, and compare the CDR with other HTA or regulatory agencies regarding surrogate concerns. Methods Final recommendations were identified from CDR inception (September 2003) to December 31, 2010. Recommendations were classified by type of outcome (surrogate, final, other) and acceptability of surrogates (determined by the presence/absence of statements of concern regarding surrogates). Descriptive and statistical analyses examined factors related to surrogate use and acceptability. For thirteen surrogate-based submissions, recommendations from international HTA and regulatory agencies were reviewed for statements about surrogate acceptability. Results Of 156 final recommendations, 68 (44%) involved surrogates. The overall ‘do not list’ (DNL) rate was 48%; the DNL rate for surrogates was 41% (p = 0.175). The DNL rate was 64% for non-accepted surrogates (n = 28) versus 25% for accepted surrogates (odds ratio 5.4, p = 0.002). Clinical uncertainty, use of economic evidence over price alone, and a premium price were significantly associated with non-accepted surrogates. Surrogates were used most commonly for HIV, diabetes, rare diseases, cardiovascular disease and cancer. For the subset of drugs studied, other HTA agencies did not express concerns for most recommendations, while regulatory agencies frequently stated surrogate acceptance. Conclusions The majority of surrogates were accepted at the CDR. Non-accepted surrogates were significantly associated with clinical uncertainty and a DNL recommendation. There was inconsistency of surrogate acceptability across several international agencies. Stakeholders should consider collaboratively establishing guidelines on the use, validation, and acceptability of surrogates. PMID:24341379

Runoff load estimation of particulate and dissolved nitrogen in Lake Inba watershed using continuous monitoring data on turbidity and electric conductivity.

PubMed

Kim, J; Nagano, Y; Furumai, H

2012-01-01

Easy-to-measure surrogate parameters for water quality indicators are needed for real time monitoring as well as for generating data for model calibration and validation. In this study, a novel linear regression model for estimating total nitrogen (TN) based on two surrogate parameters is proposed based on evaluation of pollutant loads flowing into a eutrophic lake. Based on their runoff characteristics during wet weather, electric conductivity (EC) and turbidity were selected as surrogates for particulate nitrogen (PN) and dissolved nitrogen (DN), respectively. Strong linear relationships were established between PN and turbidity and DN and EC, and both models subsequently combined for estimation of TN. This model was evaluated by comparison of estimated and observed TN runoff loads during rainfall events. This analysis showed that turbidity and EC are viable surrogates for PN and DN, respectively, and that the linear regression model for TN concentration was successful in estimating TN runoff loads during rainfall events and also under dry weather conditions.

Increasing consistency of disease biomarker prediction across datasets.

PubMed

Chikina, Maria D; Sealfon, Stuart C

2014-01-01

Microarray studies with human subjects often have limited sample sizes which hampers the ability to detect reliable biomarkers associated with disease and motivates the need to aggregate data across studies. However, human gene expression measurements may be influenced by many non-random factors such as genetics, sample preparations, and tissue heterogeneity. These factors can contribute to a lack of agreement among related studies, limiting the utility of their aggregation. We show that it is feasible to carry out an automatic correction of individual datasets to reduce the effect of such 'latent variables' (without prior knowledge of the variables) in such a way that datasets addressing the same condition show better agreement once each is corrected. We build our approach on the method of surrogate variable analysis but we demonstrate that the original algorithm is unsuitable for the analysis of human tissue samples that are mixtures of different cell types. We propose a modification to SVA that is crucial to obtaining the improvement in agreement that we observe. We develop our method on a compendium of multiple sclerosis data and verify it on an independent compendium of Parkinson's disease datasets. In both cases, we show that our method is able to improve agreement across varying study designs, platforms, and tissues. This approach has the potential for wide applicability to any field where lack of inter-study agreement has been a concern.

Continuous Metabolic Syndrome Scores for Children Using Salivary Biomarkers.

PubMed

Shi, Ping; Goodson, J Max; Hartman, Mor-Li; Hasturk, Hatice; Yaskell, Tina; Vargas, Jorel; Cugini, Maryann; Barake, Roula; Alsmadi, Osama; Al-Mutawa, Sabiha; Ariga, Jitendra; Soparkar, Pramod; Behbehani, Jawad; Behbehani, Kazem; Welty, Francine

2015-01-01

Binary definitions of the metabolic syndrome based on the presence of a particular number of individual risk factors are limited, particularly in the pediatric population. To address this limitation, we aimed at constructing composite and continuous metabolic syndrome scores (cmetS) to represent an overall measure of metabolic syndrome (MetS) in a large cohort of metabolically at-risk children, focusing on the use of the usual clinical parameters (waist circumference (WC) and systolic blood pressure (SBP), supplemented with two salivary surrogate variables (glucose and high density lipoprotein cholesterol (HDLC). Two different approaches used to create the scores were evaluated in comparison. Data from 8,112 Kuwaiti children (10.00 ± 0.67 years) were used to construct two cmetS for each subject. The first cmetS (cmetS-Z) was created by summing standardized residuals of each variable regressed on age and gender; and the second cmetS (cmetS-PCA) was defined as the first principal component from gender-specific principal component analysis based on the four variables. There was a graded relationship between both scores and the number of adverse risk factors. The areas under the curve using cmetS-Z and cmetS-PCA as predictors for severe metabolic syndrome (defined as the presence of ≥3 metabolic risk factors) were 0.935 and 0.912, respectively. cmetS-Z was positively associated with WC, SBP, and glucose, but inversely associated with HDLC. Except for the lack of association with glucose, cmetS-PCA was similar to cmetS-Z in boys, but had minimum loading on HDLC in girls. Analysis using quantile regression showed an inverse association of fitness level with cmetS-PCA (p = 0.001 for boys; p = 0.002 for girls), and comparison of cmetS-Z and cmetS-PCA suggested that WC and SBP were main contributory components. Significant alterations in the relationship between cmetS and salivary adipocytokines were demonstrated in overweight and obese children as compared to underweight and normal-weight children. We have derived continuous summary scores for MetS from a large-scale pediatric study using two different approaches, incorporating salivary measures as surrogate for plasma measures. The derived scores were viable expressions of metabolic risk, and can be utilized to study the relationships of MetS with various aspects of the metabolic disease process.

Comparison of HRV parameters derived from photoplethysmography and electrocardiography signals.

PubMed

Jeyhani, Vala; Mahdiani, Shadi; Peltokangas, Mikko; Vehkaoja, Antti

2015-01-01

Heart rate variability (HRV) has become a useful tool in analysis of cardiovascular system in both research and clinical fields. HRV has been also used in other applications such as stress level estimation in wearable devices. HRV is normally obtained from ECG as the time interval of two successive R waves. Recently PPG has been proposed as an alternative for ECG in HRV analysis to overcome some difficulties in measurement of ECG. In addition, PPG-HRV is also used in some commercial devices such as modern optical wrist-worn heart rate monitors. However, some researches have shown that PPG is not a surrogate for heart rate variability analysis. In this work, HRV analysis was applied on beat-to-beat intervals obtained from ECG and PPG in 19 healthy male subjects. Some important HRV parameters were calculated from PPG-HRV and ECG-HRV. Maximum of PPG and its second derivative were considered as two methods for obtaining the beat-to-beat signals from PPG and the results were compared with those achieved from ECG-HRV. Our results show that the smallest error happens in SDNN and SD2 with relative error of 2.46% and 2%, respectively. The most affected parameter is pNN50 with relative error of 29.89%. In addition, in our trial, using the maximum of PPG gave better results than its second derivative.

Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition.

PubMed

Gilbert, Peter B; Gabriel, Erin E; Huang, Ying; Chan, Ivan S F

2015-09-01

A common problem of interest within a randomized clinical trial is the evaluation of an inexpensive response endpoint as a valid surrogate endpoint for a clinical endpoint, where a chief purpose of a valid surrogate is to provide a way to make correct inferences on clinical treatment effects in future studies without needing to collect the clinical endpoint data. Within the principal stratification framework for addressing this problem based on data from a single randomized clinical efficacy trial, a variety of definitions and criteria for a good surrogate endpoint have been proposed, all based on or closely related to the "principal effects" or "causal effect predictiveness (CEP)" surface. We discuss CEP-based criteria for a useful surrogate endpoint, including (1) the meaning and relative importance of proposed criteria including average causal necessity (ACN), average causal sufficiency (ACS), and large clinical effect modification; (2) the relationship between these criteria and the Prentice definition of a valid surrogate endpoint; and (3) the relationship between these criteria and the consistency criterion (i.e., assurance against the "surrogate paradox"). This includes the result that ACN plus a strong version of ACS generally do not imply the Prentice definition nor the consistency criterion, but they do have these implications in special cases. Moreover, the converse does not hold except in a special case with a binary candidate surrogate. The results highlight that assumptions about the treatment effect on the clinical endpoint before the candidate surrogate is measured are influential for the ability to draw conclusions about the Prentice definition or consistency. In addition, we emphasize that in some scenarios that occur commonly in practice, the principal strata sub-populations for inference are identifiable from the observable data, in which cases the principal stratification framework has relatively high utility for the purpose of effect modification analysis, and is closely connected to the treatment marker selection problem. The results are illustrated with application to a vaccine efficacy trial, where ACN and ACS for an antibody marker are found to be consistent with the data and hence support the Prentice definition and consistency.

Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition

PubMed Central

Gilbert, Peter B.; Gabriel, Erin E.; Huang, Ying; Chan, Ivan S.F.

2015-01-01

A common problem of interest within a randomized clinical trial is the evaluation of an inexpensive response endpoint as a valid surrogate endpoint for a clinical endpoint, where a chief purpose of a valid surrogate is to provide a way to make correct inferences on clinical treatment effects in future studies without needing to collect the clinical endpoint data. Within the principal stratification framework for addressing this problem based on data from a single randomized clinical efficacy trial, a variety of definitions and criteria for a good surrogate endpoint have been proposed, all based on or closely related to the “principal effects” or “causal effect predictiveness (CEP)” surface. We discuss CEP-based criteria for a useful surrogate endpoint, including (1) the meaning and relative importance of proposed criteria including average causal necessity (ACN), average causal sufficiency (ACS), and large clinical effect modification; (2) the relationship between these criteria and the Prentice definition of a valid surrogate endpoint; and (3) the relationship between these criteria and the consistency criterion (i.e., assurance against the “surrogate paradox”). This includes the result that ACN plus a strong version of ACS generally do not imply the Prentice definition nor the consistency criterion, but they do have these implications in special cases. Moreover, the converse does not hold except in a special case with a binary candidate surrogate. The results highlight that assumptions about the treatment effect on the clinical endpoint before the candidate surrogate is measured are influential for the ability to draw conclusions about the Prentice definition or consistency. In addition, we emphasize that in some scenarios that occur commonly in practice, the principal strata sub-populations for inference are identifiable from the observable data, in which cases the principal stratification framework has relatively high utility for the purpose of effect modification analysis, and is closely connected to the treatment marker selection problem. The results are illustrated with application to a vaccine efficacy trial, where ACN and ACS for an antibody marker are found to be consistent with the data and hence support the Prentice definition and consistency. PMID:26722639

Nonconvex Nonsmooth Low Rank Minimization via Iteratively Reweighted Nuclear Norm.

PubMed

Lu, Canyi; Tang, Jinhui; Yan, Shuicheng; Lin, Zhouchen

2016-02-01

The nuclear norm is widely used as a convex surrogate of the rank function in compressive sensing for low rank matrix recovery with its applications in image recovery and signal processing. However, solving the nuclear norm-based relaxed convex problem usually leads to a suboptimal solution of the original rank minimization problem. In this paper, we propose to use a family of nonconvex surrogates of L0-norm on the singular values of a matrix to approximate the rank function. This leads to a nonconvex nonsmooth minimization problem. Then, we propose to solve the problem by an iteratively re-weighted nuclear norm (IRNN) algorithm. IRNN iteratively solves a weighted singular value thresholding problem, which has a closed form solution due to the special properties of the nonconvex surrogate functions. We also extend IRNN to solve the nonconvex problem with two or more blocks of variables. In theory, we prove that the IRNN decreases the objective function value monotonically, and any limit point is a stationary point. Extensive experiments on both synthesized data and real images demonstrate that IRNN enhances the low rank matrix recovery compared with the state-of-the-art convex algorithms.

Estimation of k-ε parameters using surrogate models and jet-in-crossflow data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lefantzi, Sophia; Ray, Jaideep; Arunajatesan, Srinivasan

2014-11-01

We demonstrate a Bayesian method that can be used to calibrate computationally expensive 3D RANS (Reynolds Av- eraged Navier Stokes) models with complex response surfaces. Such calibrations, conditioned on experimental data, can yield turbulence model parameters as probability density functions (PDF), concisely capturing the uncertainty in the parameter estimates. Methods such as Markov chain Monte Carlo (MCMC) estimate the PDF by sampling, with each sample requiring a run of the RANS model. Consequently a quick-running surrogate is used instead to the RANS simulator. The surrogate can be very difficult to design if the model's response i.e., the dependence of themore » calibration variable (the observable) on the parameter being estimated is complex. We show how the training data used to construct the surrogate can be employed to isolate a promising and physically realistic part of the parameter space, within which the response is well-behaved and easily modeled. We design a classifier, based on treed linear models, to model the "well-behaved region". This classifier serves as a prior in a Bayesian calibration study aimed at estimating 3 k - ε parameters ( C μ, C ε2 , C ε1 ) from experimental data of a transonic jet-in-crossflow interaction. The robustness of the calibration is investigated by checking its predictions of variables not included in the cal- ibration data. We also check the limit of applicability of the calibration by testing at off-calibration flow regimes. We find that calibration yield turbulence model parameters which predict the flowfield far better than when the nomi- nal values of the parameters are used. Substantial improvements are still obtained when we use the calibrated RANS model to predict jet-in-crossflow at Mach numbers and jet strengths quite different from those used to generate the ex- perimental (calibration) data. Thus the primary reason for poor predictive skill of RANS, when using nominal values of the turbulence model parameters, was parametric uncertainty, which was rectified by calibration. Post-calibration, the dominant contribution to model inaccuraries are due to the structural errors in RANS.« less

Validation of surrogate endpoints in advanced solid tumors: systematic review of statistical methods, results, and implications for policy makers.

PubMed

Ciani, Oriana; Davis, Sarah; Tappenden, Paul; Garside, Ruth; Stein, Ken; Cantrell, Anna; Saad, Everardo D; Buyse, Marc; Taylor, Rod S

2014-07-01

Licensing of, and coverage decisions on, new therapies should rely on evidence from patient-relevant endpoints such as overall survival (OS). Nevertheless, evidence from surrogate endpoints may also be useful, as it may not only expedite the regulatory approval of new therapies but also inform coverage decisions. It is, therefore, essential that candidate surrogate endpoints be properly validated. However, there is no consensus on statistical methods for such validation and on how the evidence thus derived should be applied by policy makers. We review current statistical approaches to surrogate-endpoint validation based on meta-analysis in various advanced-tumor settings. We assessed the suitability of two surrogates (progression-free survival [PFS] and time-to-progression [TTP]) using three current validation frameworks: Elston and Taylor's framework, the German Institute of Quality and Efficiency in Health Care's (IQWiG) framework and the Biomarker-Surrogacy Evaluation Schema (BSES3). A wide variety of statistical methods have been used to assess surrogacy. The strength of the association between the two surrogates and OS was generally low. The level of evidence (observation-level versus treatment-level) available varied considerably by cancer type, by evaluation tools and was not always consistent even within one specific cancer type. Not in all solid tumors the treatment-level association between PFS or TTP and OS has been investigated. According to IQWiG's framework, only PFS achieved acceptable evidence of surrogacy in metastatic colorectal and ovarian cancer treated with cytotoxic agents. Our study emphasizes the challenges of surrogate-endpoint validation and the importance of building consensus on the development of evaluation frameworks.

Reduced cost mission design using surrogate models

NASA Astrophysics Data System (ADS)

Feldhacker, Juliana D.; Jones, Brandon A.; Doostan, Alireza; Hampton, Jerrad

2016-01-01

This paper uses surrogate models to reduce the computational cost associated with spacecraft mission design in three-body dynamical systems. Sampling-based least squares regression is used to project the system response onto a set of orthogonal bases, providing a representation of the ΔV required for rendezvous as a reduced-order surrogate model. Models are presented for mid-field rendezvous of spacecraft in orbits in the Earth-Moon circular restricted three-body problem, including a halo orbit about the Earth-Moon L2 libration point (EML-2) and a distant retrograde orbit (DRO) about the Moon. In each case, the initial position of the spacecraft, the time of flight, and the separation between the chaser and the target vehicles are all considered as design inputs. The results show that sample sizes on the order of 102 are sufficient to produce accurate surrogates, with RMS errors reaching 0.2 m/s for the halo orbit and falling below 0.01 m/s for the DRO. A single function call to the resulting surrogate is up to two orders of magnitude faster than computing the same solution using full fidelity propagators. The expansion coefficients solved for in the surrogates are then used to conduct a global sensitivity analysis of the ΔV on each of the input parameters, which identifies the separation between the spacecraft as the primary contributor to the ΔV cost. Finally, the models are demonstrated to be useful for cheap evaluation of the cost function in constrained optimization problems seeking to minimize the ΔV required for rendezvous. These surrogate models show significant advantages for mission design in three-body systems, in terms of both computational cost and capabilities, over traditional Monte Carlo methods.

Sequential experimental design based generalised ANOVA

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2016-07-01

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

Sequential experimental design based generalised ANOVA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakraborty, Souvik, E-mail: csouvik41@gmail.com; Chowdhury, Rajib, E-mail: rajibfce@iitr.ac.in

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover,more » generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.« less

4D tumor centroid tracking using orthogonal 2D dynamic MRI: Implications for radiotherapy planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tryggestad, Erik; Flammang, Aaron; Shea, Steven M.

2013-09-15

Purpose: Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited “snapshot” in time. Heretofore, long-duration, 4D motion characterization for radiotherapy planning, margin optimization, and validation have been impractical for safety reasons, requiring invasive markers imaged under x-ray fluoroscopy. To characterize 3D tumor motion and associated variability over durations more consistent with treatments, the authors have developed a practical dynamic MRI (dMRI) technique employing two orthogonal planes acquired in a continuous, interleaved fashion.Methods: 2D balanced steady-state free precession MRI was acquired continuously over 9–14 min at approximately 4 Hz in three healthy volunteersmore » using a commercial 1.5 T system; alternating orthogonal imaging planes (sagittal, coronal, sagittal, etc.) were employed. The 2D in-plane pixel resolution was 2 × 2 mm{sup 2} with a 5 mm slice profile. Simultaneous with image acquisition, the authors monitored a 1D surrogate respiratory signal using a device available with the MRI system. 2D template matching-based anatomic feature registration, or tracking, was performed independently in each orientation. 4D feature tracking at the raw frame rate was derived using spline interpolation.Results: Tracking vascular features in the lung for two volunteers and pancreatic features in one volunteer, the authors have successfully demonstrated this method. Registration error, defined here as the difference between the sagittal and coronal tracking result in the SI direction, ranged from 0.7 to 1.6 mm (1σ) which was less than the acquired image resolution. Although the healthy volunteers were instructed to relax and breathe normally, significantly variable respiration was observed. To demonstrate potential applications of this technique, the authors subsequently explored the intrafraction stability of hypothetical tumoral internal target volumes and 3D spatial probability distribution functions. The surrogate respiratory information allowed the authors to show how this technique can be used to study correlations between internal and external (surrogate) information over these prolonged durations. However, compared against the gold standard of the time stamps in the dMRI frames, the temporal synchronization of the surrogate 1D respiratory information was shown to be likely unreliable.Conclusions: The authors have established viability of a novel and practical pretreatment, 4D tumor centroid tracking method employing a commercially available dynamic MRI sequence. Further developments from the vendor are likely needed to provide a reliably synchronized surrogate 1D respiratory signal, which will likely broaden the utility of this method in the pretreatment radiotherapy planning context.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Kunkun, E-mail: ktg@illinois.edu; Inria Bordeaux – Sud-Ouest, Team Cardamom, 200 avenue de la Vieille Tour, 33405 Talence; Congedo, Pietro M.

The Polynomial Dimensional Decomposition (PDD) is employed in this work for the global sensitivity analysis and uncertainty quantification (UQ) of stochastic systems subject to a moderate to large number of input random variables. Due to the intimate connection between the PDD and the Analysis of Variance (ANOVA) approaches, PDD is able to provide a simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to the Polynomial Chaos expansion (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of standard methods unaffordable formore » real engineering applications. In order to address the problem of the curse of dimensionality, this work proposes essentially variance-based adaptive strategies aiming to build a cheap meta-model (i.e. surrogate model) by employing the sparse PDD approach with its coefficients computed by regression. Three levels of adaptivity are carried out in this paper: 1) the truncated dimensionality for ANOVA component functions, 2) the active dimension technique especially for second- and higher-order parameter interactions, and 3) the stepwise regression approach designed to retain only the most influential polynomials in the PDD expansion. During this adaptive procedure featuring stepwise regressions, the surrogate model representation keeps containing few terms, so that the cost to resolve repeatedly the linear systems of the least-squares regression problem is negligible. The size of the finally obtained sparse PDD representation is much smaller than the one of the full expansion, since only significant terms are eventually retained. Consequently, a much smaller number of calls to the deterministic model is required to compute the final PDD coefficients.« less

A Response Surface Methodology for Bi-Level Integrated System Synthesis (BLISS)

NASA Technical Reports Server (NTRS)

Altus, Troy David; Sobieski, Jaroslaw (Technical Monitor)

2002-01-01

The report describes a new method for optimization of engineering systems such as aerospace vehicles whose design must harmonize a number of subsystems and various physical phenomena, each represented by a separate computer code, e.g., aerodynamics, structures, propulsion, performance, etc. To represent the system internal couplings, the codes receive output from other codes as part of their inputs. The system analysis and optimization task is decomposed into subtasks that can be executed concurrently, each subtask conducted using local state and design variables and holding constant a set of the system-level design variables. The subtasks results are stored in form of the Response Surfaces (RS) fitted in the space of the system-level variables to be used as the subtask surrogates in a system-level optimization whose purpose is to optimize the system objective(s) and to reconcile the system internal couplings. By virtue of decomposition and execution concurrency, the method enables a broad workfront in organization of an engineering project involving a number of specialty groups that might be geographically dispersed, and it exploits the contemporary computing technology of massively concurrent and distributed processing. The report includes a demonstration test case of supersonic business jet design.

Conservative strategy-based ensemble surrogate model for optimal groundwater remediation design at DNAPLs-contaminated sites

NASA Astrophysics Data System (ADS)

Ouyang, Qi; Lu, Wenxi; Lin, Jin; Deng, Wenbing; Cheng, Weiguo

2017-08-01

The surrogate-based simulation-optimization techniques are frequently used for optimal groundwater remediation design. When this technique is used, surrogate errors caused by surrogate-modeling uncertainty may lead to generation of infeasible designs. In this paper, a conservative strategy that pushes the optimal design into the feasible region was used to address surrogate-modeling uncertainty. In addition, chance-constrained programming (CCP) was adopted to compare with the conservative strategy in addressing this uncertainty. Three methods, multi-gene genetic programming (MGGP), Kriging (KRG) and support vector regression (SVR), were used to construct surrogate models for a time-consuming multi-phase flow model. To improve the performance of the surrogate model, ensemble surrogates were constructed based on combinations of different stand-alone surrogate models. The results show that: (1) the surrogate-modeling uncertainty was successfully addressed by the conservative strategy, which means that this method is promising for addressing surrogate-modeling uncertainty. (2) The ensemble surrogate model that combines MGGP with KRG showed the most favorable performance, which indicates that this ensemble surrogate can utilize both stand-alone surrogate models to improve the performance of the surrogate model.

Mimicking Retention and Transport of Rotavirus and Adenovirus in Sand Media Using DNA-labeled, Protein-coated Silica Nanoparticles

NASA Astrophysics Data System (ADS)

Pang, Liping; Farkas, Kata; Bennett, Grant; Varsani, Arvind; Easingwood, Richard; Tilley, Richard; Nowostawska, Urszula; Lin, Susan

2014-05-01

Rotavirus (RoV) and adenovirus (AdV) are important viral pathogens for the risk analysis of drinking water. Despite this, little is known about their retention and transport behaviors in porous media (e.g. sand filtered used for water treatment and groundwater aquifers due to a lack of representative surrogates. In this study, we developed RoV and AdV surrogates by covalently coating 70-nm sized silica nanoparticles with specific proteins and a DNA marker for sensitive detection. Filtration experiments using beach sand columns demonstrated the similarity of the surrogates' concentrations, attachment, and filtration efficiencies to the target viruses. The surrogates showed the same magnitude of concentration reduction as the viruses. Conversely, MS2 phage (a traditional virus model) over predicted concentrations of AdV and RoV by 1- and 2-orders of magnitude, respectively. The surrogates remained stable in size, surface charge and DNA concentration for at least one year. They can be easily and rapidly detected at concentrations down to one particle per PCR reaction and are readily detectable in natural waters and even in effluent. With up-scaling validation in pilot trials, the surrogates can be a useful cost-effective new tool for studying virus retention and transport in porous media, e.g. for assessing filter efficiency in water and wastewater treatment, tracking virus migration in groundwater after effluent land disposal, and establishing safe setback distances for groundwater protection.

Validity of ambient levels of fine particles as surrogate for personal exposure to outdoor air pollution--results of the European EXPOLIS-EAS Study (Swiss Center Basel).

PubMed

Oglesby, L; Künzli, N; Röösli, M; Braun-Fahrländer, C; Mathys, P; Stern, W; Jantunen, M; Kousa, A

2000-07-01

To evaluate the validity of fixed-site fine particle levels as exposure surrogates in air pollution epidemiology, we considered four indicator groups: (1) PM2.5 total mass concentrations, (2) sulfur and potassium for regional air pollution, (3) lead and bromine for traffic-related particles, and (4) calcium for crustal particles. Using data from the European EXPOLIS (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) study, we assessed the associations between 48-hr personal exposures and home outdoor levels of the indicators. Furthermore, within-city variability of fine particle levels was evaluated. Personal exposures to PM2.5 mass were not correlated to corresponding home outdoor levels (n = 44, rSpearman (Sp) = 0.07). In the group reporting neither relevant indoor sources nor relevant activities, personal exposures and home outdoor levels of sulfur were highly correlated (n = 40, rSp = 0.85). In contrast, the associations were weaker for traffic (Pb: n = 44, rSp = 0.53; Br: n = 44, rSp = 0.21) and crustal (Ca: n = 44, rSp = 0.12) indicators. This contrast is consistent with spatially homogeneous regional pollution and higher spatial variability of traffic and crustal indicators observed in Basel, Switzerland. We conclude that for regional air pollution, fixed-site fine particle levels are valid exposure surrogates. For source-specific exposures, however, fixed-site data are probably not the optimal measure. Still, in air pollution epidemiology, ambient PM2.5 levels may be more appropriate exposure estimates than total personal PM2.5 exposure, since the latter reflects a mixture of indoor and outdoor sources.

Validity of Ambient Levels of Fine Particles as Surrogate for Personal Exposure to Outdoor Air Pollution-Results of the European EXPOLIS-EAS Study (Swiss Center Basel).

PubMed

Oglesby, Lucy; Künzli, Nino; Röösli, Martin; Braun-Fahrländer, Charlotte; Mathys, Patrick; Stern, Willem; Jantunen, Matti; Kousa, Anu

2000-07-01

To evaluate the validity of fixed-site fine particle levels as exposure surrogates in air pollution epidemiology, we considered four indicator groups: (1) PM 25 total mass concentrations, (2) sulfur and potassium for regional air pollution, (3) lead and bromine for traffic-related particles, and (4) calcium for crustal particles. Using data from the European EXPOLIS (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) study, we assessed the associations between 48-hr personal exposures and home outdoor levels of the indicators. Furthermore, within-city variability of fine particle levels was evaluated. Personal exposures to PM 2.5 mass were not correlated to corresponding home outdoor levels (n = 44, r S (S) =r o v ' Spearman (Sp) 0.07). In the group reporting neither relevant indoor sources nor relevant activities, personal exposures and home outdoor levels of sulfur were highly correlated (n = 40, r Sp = 0.85). In contrast, the associations were weaker for traffic (Pb: n = 44, r Sp = 0.53; Br: n = 44, r Sp = 0.21) and crustal (Ca: n = 44, r Sp = 0.12) indicators. This contrast is consistent with spatially homogeneous regional pollution and higher spatial variability of traffic and crustal indicators observed in Basel, Switzerland. We conclude that for regional air pollution, fixed-site fine particle levels are valid exposure surrogates. For source-specific exposures, however, fixed-site data are probably not the optimal measure. Still, in air pollution epidemiology, ambient PM 2.5 levels may be more appropriate exposure estimates than total personal PM 2.5 exposure, since the latter reflects a mixture of indoor and outdoor sources.

Coastal habitats as surrogates for taxonomic, functional and trophic structures of benthic faunal communities.

PubMed

Törnroos, Anna; Nordström, Marie C; Bonsdorff, Erik

2013-01-01

Due to human impact, there is extensive degradation and loss of marine habitats, which calls for measures that incorporate taxonomic as well as functional and trophic aspects of biodiversity. Since such data is less easily quantifiable in nature, the use of habitats as surrogates or proxies for biodiversity is on the rise in marine conservation and management. However, there is a critical gap in knowledge of whether pre-defined habitat units adequately represent the functional and trophic structure of communities. We also lack comparisons of different measures of community structure in terms of both between- (β) and within-habitat (α) variability when accounting for species densities. Thus, we evaluated a priori defined coastal habitats as surrogates for traditional taxonomic, functional and trophic zoobenthic community structure. We focused on four habitats (bare sand, canopy-forming algae, seagrass above- and belowground), all easily delineated in nature and defined through classification systems. We analyzed uni- and multivariate data on species and trait diversity as well as stable isotope ratios of benthic macrofauna. A good fit between habitat types and taxonomic and functional structure was found, although habitats were more similar functionally. This was attributed to within-habitat heterogeneity so when habitat divisions matched the taxonomic structure, only bare sand was functionally distinct. The pre-defined habitats did not meet the variability of trophic structure, which also proved to differentiate on a smaller spatial scale. The quantification of trophic structure using species density only identified an epi- and an infaunal unit. To summarize the results we present a conceptual model illustrating the match between pre-defined habitat types and the taxonomic, functional and trophic community structure. Our results show the importance of including functional and trophic aspects more comprehensively in marine management and spatial planning.

Testing Surrogacy Assumptions: Can Threatened and Endangered Plants Be Grouped by Biological Similarity and Abundances?

PubMed Central

Che-Castaldo, Judy P.; Neel, Maile C.

2012-01-01

There is renewed interest in implementing surrogate species approaches in conservation planning due to the large number of species in need of management but limited resources and data. One type of surrogate approach involves selection of one or a few species to represent a larger group of species requiring similar management actions, so that protection and persistence of the selected species would result in conservation of the group of species. However, among the criticisms of surrogate approaches is the need to test underlying assumptions, which remain rarely examined. In this study, we tested one of the fundamental assumptions underlying use of surrogate species in recovery planning: that there exist groups of threatened and endangered species that are sufficiently similar to warrant similar management or recovery criteria. Using a comprehensive database of all plant species listed under the U.S. Endangered Species Act and tree-based random forest analysis, we found no evidence of species groups based on a set of distributional and biological traits or by abundances and patterns of decline. Our results suggested that application of surrogate approaches for endangered species recovery would be unjustified. Thus, conservation planning focused on individual species and their patterns of decline will likely be required to recover listed species. PMID:23240051

Testing surrogacy assumptions: can threatened and endangered plants be grouped by biological similarity and abundances?

PubMed

Che-Castaldo, Judy P; Neel, Maile C

2012-01-01

There is renewed interest in implementing surrogate species approaches in conservation planning due to the large number of species in need of management but limited resources and data. One type of surrogate approach involves selection of one or a few species to represent a larger group of species requiring similar management actions, so that protection and persistence of the selected species would result in conservation of the group of species. However, among the criticisms of surrogate approaches is the need to test underlying assumptions, which remain rarely examined. In this study, we tested one of the fundamental assumptions underlying use of surrogate species in recovery planning: that there exist groups of threatened and endangered species that are sufficiently similar to warrant similar management or recovery criteria. Using a comprehensive database of all plant species listed under the U.S. Endangered Species Act and tree-based random forest analysis, we found no evidence of species groups based on a set of distributional and biological traits or by abundances and patterns of decline. Our results suggested that application of surrogate approaches for endangered species recovery would be unjustified. Thus, conservation planning focused on individual species and their patterns of decline will likely be required to recover listed species.

The oral disposition index is a strong predictor of incident diabetes in Asian Indian prediabetic men.

PubMed

Ram, Jagannathan; Snehalatha, Chamukuttan; Selvam, Sundaram; Nanditha, Arun; Shetty, Ananth Samith; Godsland, Ian F; Johnston, Desmond G; Ramachandran, Ambady

2015-08-01

In this analysis, we sought to examine the prospective association of the disposition index (DIo) derived from oral glucose tolerance test with incident diabetes in Asian Indian men with impaired glucose tolerance (IGT). These post hoc analyses used data from a 2-year prospective study in primary prevention of diabetes using lifestyle intervention among 517 men with IGT. All the participants received standard lifestyle advice at baseline. The surrogate insulin sensitivity and insulin secretion measures were tested for their hyperbolic relationship. Predictive associations of various surrogate measures with incident diabetes were determined using receiver operating characteristic curves. The combination of total area under the curve of insulin-to-glucose ratio (AUCinsulin/glucose) and Matsuda's insulin sensitivity index was the best equation to depict DIo [β: -0.954 (95 % CI -1.015 to -0.893)] compared to other measures tested in this cohort. There was an inverse association between change in DIo at the final follow-up and development of incident diabetes. Among the surrogate insulin measures studied, DIo [AUC (0.717 (95 % CI 0.675-0.756))] as a composite measure was superior than other surrogate indices. Among the surrogate indices studied, DIo was the best measure associated with incident diabetes.

Early analysis of surrogate endpoints for metastatic melanoma in immune checkpoint inhibitor trials.

PubMed

Petrelli, Fausto; Coinu, Andrea; Cabiddu, Mary; Borgonovo, Karen; Ghilardi, Mara; Lonati, Veronica; Barni, Sandro

2016-06-01

Recent major phase III trials led to the approval of immune checkpoint inhibitors (ipilimumab, pembrolizumab, and nivolumab) in metastatic malignant melanoma (MM). We aim to assess whether median progression-free survival, and 1 and 2-year overall survival (OS) rates are reliable surrogate endpoints for median OS through a meta-analysis of published trials involving immunotherapy. A systematic literature search in PubMed, EMBASE, Web of Science, and SCOPUS of published phase II to III trials with immunotherapy as the treatment for MM was conducted. Adjusted weighted linear regression was used to calculate Pearson correlations (R) between surrogates and median OS, and between treatment effects on surrogates and median OS. A total of 13 studies involving 3373 patients with MM were identified. The correlation of progression-free survival with OS was not significant (R = 0.45, P = .11). Conversely, the correlation between 1-year OS and median OS was very strong (R = 0.93, 95% confidence interval [CI] 0.84-0.96, P < .00001), as was the correlation between 2-year OS and OS (R = 0.79, 95% CI 0.51-0.91, P = .0001). The correlation between the treatment effects on 1-year OS and OS was also significant (R = -0.86, 95% CI -0.3 to 0.97, P = .01). Similar results were obtained for 2-year OS. According to the available study data, 1-year OS rate could be regarded as a potential surrogate for median OS in novel immunotherapy trials of metastatic MM. Waiting for ongoing studies (e.g., pembrolizumab), we suggest that this intermediate endpoint could be considered as a potential primary endpoint in future clinical trials.

Commercialization, Altruism, Clinical Practice: Seeking Explanation for Similarities and Differences in Californian and Canadian Gestational Surrogacy Outcomes.

PubMed

White, Pamela M

Surrogacy is growing worldwide. Although recently some countries have sought to ban it, between 2010 and 2014 the number of babies born to gestational surrogates having in vitro fertilization treatment in California doubled, and in Canada it grew by 35%. This work seeks to fill identified knowledge gaps about the similarities and differences in the practices and outcomes of gestational surrogacy, which in California operates on a commercial basis, whereas in Canada it is illegal to pay a surrogate. The paper focusses on the period from 2010 to 2014, for which comparable American and Canadian national assisted reproduction technology information exist. A retrospective data analysis was performed using information on gestational surrogate multiple births obtained from the Centers for Disease Control and Prevention National Assisted Reproductive Technology Surveillance System (NASS) and Canada's Assisted Reproduction Registry-Better Outcomes Registry and Network (CARTR-BORN). Multiple birth rates and transfers of multiple embryos were compared using relative risk analysis. Adherence to voluntary American Society for Reproductive Medicine-Society for Assisted Reproductive Technology and Canadian Fertility and Andrology Society embryo transfer guidelines was modelled. Among gestational surrogates, when donor ova embryos obtained from women aged less than 35 years were used, embryo transfer guideline adherence was 42% in California and 48% in Canada. Regardless of where on the commercial/noncommercial boundary North American surrogates reside, they are more likely to receive more donor ova embryos per in vitro fertilization transfer than other in vitro fertilization patients. An altruistic desire to assist childless couples and individuals create families along with clinic practices seem to play major roles in treatment decisions privileging the transfer two or more embryos. Copyright © 2018 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

The Use of Surrogate Data in Demographic Population Viability Analysis: A Case Study of California Sea Lions

PubMed Central

2015-01-01

Reliable data necessary to parameterize population models are seldom available for imperiled species. As an alternative, data from populations of the same species or from ecologically similar species have been used to construct models. In this study, we evaluated the use of demographic data collected at one California sea lion colony (Los Islotes) to predict the population dynamics of the same species from two other colonies (San Jorge and Granito) in the Gulf of California, Mexico, for which demographic data are lacking. To do so, we developed a stochastic demographic age-structured matrix model and conducted a population viability analysis for each colony. For the Los Islotes colony we used site-specific pup, juvenile, and adult survival probabilities, as well as birth rates for older females. For the other colonies, we used site-specific pup and juvenile survival probabilities, but used surrogate data from Los Islotes for adult survival probabilities and birth rates. We assessed these models by comparing simulated retrospective population trajectories to observed population trends based on count data. The projected population trajectories approximated the observed trends when surrogate data were used for one colony but failed to match for a second colony. Our results indicate that species-specific and even region-specific surrogate data may lead to erroneous conservation decisions. These results highlight the importance of using population-specific demographic data in assessing extinction risk. When vital rates are not available and immediate management actions must be taken, in particular for imperiled species, we recommend the use of surrogate data only when the populations appear to have similar population trends. PMID:26413746

Structure of diffusion flames from a vertical burner

Treesearch

Mark A. Finney; Dan Jimenez; Jack D. Cohen; Isaac C. Grenfell; Cyle Wold

2010-01-01

Non-steady and turbulent flames are commonly observed to produce flame contacts with adjacent fuels during fire spread in a wide range of fuel bed depths. A stationary gas-fired burner (flame wall) was developed to begin study of flame edge variability along an analagous vertical fuel source. This flame wall is surrogate for a combustion interface at the edge of a deep...

Quantifying sampling noise and parametric uncertainty in atomistic-to-continuum simulations using surrogate models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salloum, Maher N.; Sargsyan, Khachik; Jones, Reese E.

2015-08-11

We present a methodology to assess the predictive fidelity of multiscale simulations by incorporating uncertainty in the information exchanged between the components of an atomistic-to-continuum simulation. We account for both the uncertainty due to finite sampling in molecular dynamics (MD) simulations and the uncertainty in the physical parameters of the model. Using Bayesian inference, we represent the expensive atomistic component by a surrogate model that relates the long-term output of the atomistic simulation to its uncertain inputs. We then present algorithms to solve for the variables exchanged across the atomistic-continuum interface in terms of polynomial chaos expansions (PCEs). We alsomore » consider a simple Couette flow where velocities are exchanged between the atomistic and continuum components, while accounting for uncertainty in the atomistic model parameters and the continuum boundary conditions. Results show convergence of the coupling algorithm at a reasonable number of iterations. As a result, the uncertainty in the obtained variables significantly depends on the amount of data sampled from the MD simulations and on the width of the time averaging window used in the MD simulations.« less

Surrogate markers of visceral fat and response to anti-depressive treatment in patients with major depressive disorder: a prospective exploratory analysis.

PubMed

Tønning, Morten; Petersen, Dorthe; Steglich-Petersen, Marie; Csillag, Claudio

2017-02-01

Body mass index (BMI) and body weight have been shown to be associated to treatment outcome in patients with major depressive disorder, but this relationship is not clear. Visceral fat might be an underlying mechanism explaining this relationship. The aim of this study was to prospectively investigate whether visceral fat, as measured by hip-to-waist ratio and waist circumference, affects treatment outcome in patients with major depressive disorder in patients attending a hospital psychiatric care unit in Denmark. The study was conducted as an observational prospective study including 33 patients with major depressive disorder. Assessments were made at enrolment and after 8 weeks. Primary variables were hip-to-waist ratio and waist circumference. Outcome were remission or response of depressive symptoms measured with the Hamilton Depression Rating Scale (HAM-D 17 ) interviews and HAM-D 6 self-rating questionnaires. No differences were found in outcome between groups of patients with high vs low visceral fat in this population. The lack of association was evident for all surrogate markers of visceral fat, and suggests that visceral fat has no impact on outcomes of depressive symptoms. However, study limitations might have contributed to this lack of association, especially sample size and considerable variations on multiple parameters including treatment received during the 8 weeks of follow-up.

Evaluation of multiple-frequency, active and passive acoustics as surrogates for bedload transport

USGS Publications Warehouse

Wood, Molly S.; Fosness, Ryan L.; Pachman, Gregory; Lorang, Mark; Tonolla, Diego

2015-01-01

The use of multiple-frequency, active acoustics through deployment of acoustic Doppler current profilers (ADCPs) shows potential for estimating bedload in selected grain size categories. The U.S. Geological Survey (USGS), in cooperation with the University of Montana (UM), evaluated the use of multiple-frequency, active and passive acoustics as surrogates for bedload transport during a pilot study on the Kootenai River, Idaho, May 17-18, 2012. Four ADCPs with frequencies ranging from 600 to 2000 kHz were used to measure apparent moving bed velocities at 20 stations across the river in conjunction with physical bedload samples. Additionally, UM scientists measured the sound frequencies of moving particles with two hydrophones, considered passive acoustics, along longitudinal transects in the study reach. Some patterns emerged in the preliminary analysis which show promise for future studies. Statistically significant relations were successfully developed between apparent moving bed velocities measured by ADCPs with frequencies 1000 and 1200 kHz and bedload in 0.5 to 2.0 mm grain size categories. The 600 kHz ADCP seemed somewhat sensitive to the movement of gravel bedload in the size range 8.0 to 31.5 mm, but the relation was not statistically significant. The passive hydrophone surveys corroborated the sample results and could be used to map spatial variability in bedload transport and to select a measurement cross-section with moving bedload for active acoustic surveys and physical samples.

Real-time tumor motion estimation using respiratory surrogate via memory-based learning

NASA Astrophysics Data System (ADS)

Li, Ruijiang; Lewis, John H.; Berbeco, Ross I.; Xing, Lei

2012-08-01

Respiratory tumor motion is a major challenge in radiation therapy for thoracic and abdominal cancers. Effective motion management requires an accurate knowledge of the real-time tumor motion. External respiration monitoring devices (optical, etc) provide a noninvasive, non-ionizing, low-cost and practical approach to obtain the respiratory signal. Due to the highly complex and nonlinear relations between tumor and surrogate motion, its ultimate success hinges on the ability to accurately infer the tumor motion from respiratory surrogates. Given their widespread use in the clinic, such a method is critically needed. We propose to use a powerful memory-based learning method to find the complex relations between tumor motion and respiratory surrogates. The method first stores the training data in memory and then finds relevant data to answer a particular query. Nearby data points are assigned high relevance (or weights) and conversely distant data are assigned low relevance. By fitting relatively simple models to local patches instead of fitting one single global model, it is able to capture highly nonlinear and complex relations between the internal tumor motion and external surrogates accurately. Due to the local nature of weighting functions, the method is inherently robust to outliers in the training data. Moreover, both training and adapting to new data are performed almost instantaneously with memory-based learning, making it suitable for dynamically following variable internal/external relations. We evaluated the method using respiratory motion data from 11 patients. The data set consists of simultaneous measurement of 3D tumor motion and 1D abdominal surface (used as the surrogate signal in this study). There are a total of 171 respiratory traces, with an average peak-to-peak amplitude of ∼15 mm and average duration of ∼115 s per trace. Given only 5 s (roughly one breath) pretreatment training data, the method achieved an average 3D error of 1.5 mm and 95th percentile error of 3.4 mm on unseen test data. The average 3D error was further reduced to 1.4 mm when the model was tuned to its optimal setting for each respiratory trace. In one trace where a few outliers are present in the training data, the proposed method achieved an error reduction of as much as ∼50% compared with the best linear model (1.0 mm versus 2.1 mm). The memory-based learning technique is able to accurately capture the highly complex and nonlinear relations between tumor and surrogate motion in an efficient manner (a few milliseconds per estimate). Furthermore, the algorithm is particularly suitable to handle situations where the training data are contaminated by large errors or outliers. These desirable properties make it an ideal candidate for accurate and robust tumor gating/tracking using respiratory surrogates.

Evaluating surrogate endpoints, prognostic markers, and predictive markers: Some simple themes.

PubMed

Baker, Stuart G; Kramer, Barnett S

2015-08-01

A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. We organized our discussion around a different theme for each topic. "Fundamentally an extrapolation" refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. "Decision analysis to the rescue" refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. "The appeal of simplicity" refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. © The Author(s) 2014.

Surrogacy: The experience of Greek commissioning women.

PubMed

Papaligoura, Zaira; Papadatou, Danai; Bellali, Thalia

2015-12-01

Available studies on surrogacy are extremely limited. Findings suggest that surrogacy is experienced as problem free, with a significant number of commissioning mothers maintaining contact with the surrogates over time. To explore the experiences of Greek commissioning women regarding the surrogacy arrangement and birth of a child through surrogacy. The data of this study were collected from 7 intended mothers who had either a long history of infertility or serious health problems. Interviews were tape-recorded, transcribed and analysed employing content analysis. The analysis of the women's accounts revealed three themes: (a) a shared journey, (b) the birth of a long-awaited child, and (c) the surrogacy disclosure. The surrogacy process became the women's affairs, with their partners offering backstage support. A very close bond was developed with the surrogates, characterised by daily contacts and care-giving behaviours. While this bond was abruptly discontinued after the child's birth, it was interiorised with all participants being grateful to their surrogate. The timing and content of the surrogacy disclosure to family and child(ren) were carefully chosen by participants, who avoided providing information when egg donation was involved. Findings are reassuring for women who want to parent a child through a surrogate arrangement, and suggest that the availability of counselling services may help intended mothers to cope with disclosure issues. Copyright © 2015 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

Can PPG be used for HRV analysis?

PubMed

Pinheiro, N; Couceiro, R; Henriques, J; Muehlsteff, J; Quintal, I; Goncalves, L; Carvalho, P

2016-08-01

Heart rate variability (HRV) represents one of the most promising markers of the autonomic nervous system (ANS) regulation. However, it requires the acquisition of the ECG signal in order to reliably detect the RR intervals, which is not always easily and comfortably available in personal health applications. Additionally, due to progress in single spot optical sensors, photoplethysmography (PPG) is an interesting alternative for heartbeat interval measurements, since it is a more convenient and a less intrusive measurement technique. Driven by the technological advances in such sensors, wrist-worn devices are becoming a commodity, and the interest in the assessment of HRV indexes from the PPG analysis (pulse rate variability - PRV) is rising. In this study, we investigate the hypothesis of using PRV features as surrogates for HRV indexes, in three different contexts: healthy subjects at rest, healthy subjects after physical exercise and subjects with cardiovascular diseases (CVD). Additionally, we also evaluate which are the characteristic points better suited for PRV analysis in these contexts, i.e. the PPG waveform characteristic points leading to the PRV features that present the best estimates of HRV (correlation and error analysis). The achieved results suggest that the PRV can be often used as an alternative for HRV analysis in healthy subjects, with significant correlations above 82%, for both time and frequency features. Contrarily, in the post-exercise and CVD subjects, time and (most importantly) frequency domain features shall be used with caution (mean correlations ranging from 68% to 88%).

Surrogate clinical endpoints to predict overall survival in non-small cell lung cancer trials-are we in a new era?

PubMed

Clarke, Jeffrey M; Wang, Xiaofei; Ready, Neal E

2015-12-01

Surrogate endpoints for clinical trials in oncology offer an alternative metric for measuring clinical benefit, allowing for shorter trial duration, smaller patient cohorts, and single arm design. The correlation of surrogate endpoints with overall survival (OS) in therapeutic studies is a central consideration to their validity. The Food and Drug Administration (FDA) recently published an analysis of fourteen clinical trials in advanced non-small cell lung cancer (NSCLC), and discovered a strong association between response rate and progression free survival. Furthermore, a correlation between response rate and OS is demonstrated when analyzing the experimental treatment arm separately, minimizing bias from patient crossover. We also highlight multiple, important considerations when using response as an endpoint in clinical trials involving NSCLC patients.

Uncertainty quantification in capacitive RF MEMS switches

NASA Astrophysics Data System (ADS)

Pax, Benjamin J.

Development of radio frequency micro electrical-mechanical systems (RF MEMS) has led to novel approaches to implement electrical circuitry. The introduction of capacitive MEMS switches, in particular, has shown promise in low-loss, low-power devices. However, the promise of MEMS switches has not yet been completely realized. RF-MEMS switches are known to fail after only a few months of operation, and nominally similar designs show wide variability in lifetime. Modeling switch operation using nominal or as-designed parameters cannot predict the statistical spread in the number of cycles to failure, and probabilistic methods are necessary. A Bayesian framework for calibration, validation and prediction offers an integrated approach to quantifying the uncertainty in predictions of MEMS switch performance. The objective of this thesis is to use the Bayesian framework to predict the creep-related deflection of the PRISM RF-MEMS switch over several thousand hours of operation. The PRISM switch used in this thesis is the focus of research at Purdue's PRISM center, and is a capacitive contacting RF-MEMS switch. It employs a fixed-fixed nickel membrane which is electrostatically actuated by applying voltage between the membrane and a pull-down electrode. Creep plays a central role in the reliability of this switch. The focus of this thesis is on the creep model, which is calibrated against experimental data measured for a frog-leg varactor fabricated and characterized at Purdue University. Creep plasticity is modeled using plate element theory with electrostatic forces being generated using either parallel plate approximations where appropriate, or solving for the full 3D potential field. For the latter, structure-electrostatics interaction is determined through immersed boundary method. A probabilistic framework using generalized polynomial chaos (gPC) is used to create surrogate models to mitigate the costly full physics simulations, and Bayesian calibration and forward propagation of uncertainty are performed using this surrogate model. The first step in the analysis is Bayesian calibration of the creep related parameters. A computational model of the frog-leg varactor is created, and the computed creep deflection of the device over 800 hours is used to generate a surrogate model using a polynomial chaos expansion in Hermite polynomials. Parameters related to the creep phenomenon are calibrated using Bayesian calibration with experimental deflection data from the frog-leg device. The calibrated input distributions are subsequently propagated through a surrogate gPC model for the PRISM MEMS switch to produce probability density functions of the maximum membrane deflection of the membrane over several thousand hours. The assumptions related to the Bayesian calibration and forward propagation are analyzed to determine the sensitivity to these assumptions of the calibrated input distributions and propagated output distributions of the PRISM device. The work is an early step in understanding the role of geometric variability, model uncertainty, numerical errors and experimental uncertainties in the long-term performance of RF-MEMS.

Surrogate decision making: do we have to trade off accuracy and procedural satisfaction?

PubMed

Frey, Renato; Hertwig, Ralph; Herzog, Stefan M

2014-02-01

Making surrogate decisions on behalf of incapacitated patients can raise difficult questions for relatives, physicians, and society. Previous research has focused on the accuracy of surrogate decisions (i.e., the proportion of correctly inferred preferences). Less attention has been paid to the procedural satisfaction that patients' surrogates and patients attribute to specific approaches to making surrogate decisions. The objective was to investigate hypothetical patients' and surrogates' procedural satisfaction with specific approaches to making surrogate decisions and whether implementing these preferences would lead to tradeoffs between procedural satisfaction and accuracy. Study 1 investigated procedural satisfaction by assigning participants (618 in a mixed-age but relatively young online sample and 50 in an older offline sample) to the roles of hypothetical surrogates or patients. Study 2 (involving 64 real multigenerational families with a total of 253 participants) investigated accuracy using 24 medical scenarios. Hypothetical patients and surrogates had closely aligned preferences: Procedural satisfaction was highest with a patient-designated surrogate, followed by shared surrogate decision-making approaches and legally assigned surrogates. These approaches did not differ substantially in accuracy. Limitations are that participants' preferences regarding existing and novel approaches to making surrogate decisions can only be elicited under hypothetical conditions. Next to decision making by patient-designated surrogates, shared surrogate decision making is the preferred approach among patients and surrogates alike. This approach appears to impose no tradeoff between procedural satisfaction and accuracy. Therefore, shared decision making should be further studied in representative samples of the general population, and if people's preferences prove to be robust, they deserve to be weighted more strongly in legal frameworks in addition to patient-designated surrogates.

Informed consent in medical decision-making in commercial gestational surrogacy: a mixed methods study in New Delhi, India.

PubMed

Tanderup, Malene; Reddy, Sunita; Patel, Tulsi; Nielsen, Birgitte Bruun

2015-05-01

To investigate ethical issues in informed consent for decisions regarding embryo transfer and fetal reduction in commercial gestational surrogacy. Mixed methods study employing observations, an interview-guide and semi-structured interviews. Fertility clinics and agencies in Delhi, India, between December 2011 and December 2012. Doctors providing conceptive technologies to commissioning couples and carrying out surrogacy procedures; surrogate mothers; agents functioning as links for surrogacy. Interviews using semi-structured interview guides were carried out among 20 doctors in 18 fertility clinics, five agents from four agencies and 14 surrogate mothers. Surrogate mothers were interviewed both individually and in the presence of doctors and agents. Data on socio-economic context and experiences among and between various actors in the surrogacy process were coded to identify categories of ethical concern. Numerical and grounded theory-oriented analyses were used. Informed consent, number of embryos transferred, fetal reduction, conflict of interest among the involved parties. None of the 14 surrogate mothers were able to explain the risks involved in embryo transfer and fetal reduction. The majority of the doctors took unilateral decisions about embryo transfer and fetal reduction. The commissioning parents were usually only indirectly involved. In the qualitative analysis, difficulties in explaining procedures, autonomy, self-payment of fertility treatment and conflicts of interest were the main themes. Clinical procedural decisions were primarily made by the doctors. Surrogate mothers were not adequately informed. There is a need for regulation on decision-making procedures to safeguard the interests of surrogate mothers. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

Which factors influence the resort to surrogate consent in stroke trials, and what are the patient outcomes in this context?

PubMed

Mendyk, Anne-Marie; Labreuche, Julien; Henon, Hilde; Girot, Marie; Cordonnier, Charlotte; Duhamel, Alain; Leys, Didier; Bordet, Régis

2015-04-24

The provision of informed consent is a prerequisite for inclusion of a patient in a clinical research project. In some countries, the legislation on clinical research authorizes a third person to provide informed consent if the patient is unable to do so directly (i.e. surrogate consent). This is the case during acute stroke, when the symptoms may prevent the patient from providing informed consent and thus require a third party to be approached. Identification of factors associated with the medical team's decision to resort to surrogate consent may (i) help the care team during the inclusion process and (ii) enable the patient's family circle to be better informed (and thus feel less guilty) about providing surrogate consent. Patients included in the BIOSTROKE cohort (initially dedicated to the analysis of factors influencing stroke severity) were divided into two groups: those having provided informed consent directly and those for whom a third party (such as a family member) had provided surrogate consent. We compared the groups in terms of the initial clinical characteristics (age, gender, type of stroke, severity on the National Institutes of Health Stroke Scale (NIHSS), pre-stroke cognitive status according to the Informant Questionnaire on Cognitive Decline in the Elderly, and the stroke's aetiology) and the functional and cognitive impairments (according to the NIHSS, the modified Rankin score (mRS) and the Mini Mental State Examination) on post-stroke days 8 and 90. Three hundred and ninety five patients were included (mean ± SD age: 67 ± 15 years; 53% males). Surrogate consent had been obtained in 228 cases, and 167 patients had provided consent themselves. The patients included with surrogate consent were likely to be older and more aphasic, with a pre-existing cognitive disorder and more severe stroke (relative to the patients having provided consent). In terms of recovery, the patients included with surrogate consent had a worse functional prognosis (day 90 mRS ≥3: 57.6%, compared with 16.8% in patients having provided consent themselves; p < 0.0001) and a worse cognitive prognosis (day 90 MMS < 24: 15.4% and 4.8%, respectively; p < 0.002). The mortality rate was significantly higher in the surrogate consent group. We found that in addition to age, aphasia and stroke severity, pre-stroke cognitive status is a factor that should prompt the care team to consider requesting surrogate consent for participation in a clinical study. Given that the unfavourable outcome in patients with surrogate consent is often due to their initial clinical state (rather than inclusion in a trial per se), the issue of the family's feelings of guilt (and how to avoid these feelings) should be further addressed.

Predicting Individual Tree and Shrub Species Distributions with Empirically Derived Microclimate Surfaces in a Complex Mountain Ecosystem in Northern Idaho, USA

NASA Astrophysics Data System (ADS)

Holden, Z.; Cushman, S.; Evans, J.; Littell, J. S.

2009-12-01

The resolution of current climate interpolation models limits our ability to adequately account for temperature variability in complex mountainous terrain. We empirically derive 30 meter resolution models of June-October day and nighttime temperature and April nighttime Vapor Pressure Deficit (VPD) using hourly data from 53 Hobo dataloggers stratified by topographic setting in mixed conifer forests near Bonners Ferry, ID. 66%, of the variability in average June-October daytime temperature is explained by 3 variables (elevation, relative slope position and topographic roughness) derived from 30 meter digital elevation models. 69% of the variability in nighttime temperatures among stations is explained by elevation, relative slope position and topographic dissection (450 meter window). 54% of variability in April nighttime VPD is explained by elevation, soil wetness and the NDVIc derived from Landsat. We extract temperature and VPD predictions at 411 intensified Forest Inventory and Analysis plots (FIA). We use these variables with soil wetness and solar radiation indices derived from a 30 meter DEM to predict the presence and absence of 10 common forest tree species and 25 shrub species. Classification accuracies range from 87% for Pinus ponderosa , to > 97% for most other tree species. Shrub model accuracies are also high with greater than 90% accuracy for the majority of species. Species distribution models based on the physical variables that drive species occurrence, rather than their topographic surrogates, will eventually allow us to predict potential future distributions of these species with warming climate at fine spatial scales.

Experimental injury study of children seated behind collapsing front seats in rear impacts.

PubMed

Saczalski, Kenneth J; Sances, Anthony; Kumaresan, Srirangam; Burton, Joseph L; Lewis, Paul R

2003-01-01

In the mid 1990's the U.S. Department of Transportation made recommendations to place children and infants into the rear seating areas of motor vehicles to avoid front seat airbag induced injuries and fatalities. In most rear-impacts, however, the adult occupied front seats will collapse into the rear occupant area and pose another potentially serious injury hazard to the rear-seated children. Since rear-impacts involve a wide range of speeds, impact severity, and various sizes of adults in collapsing front seats, a multi-variable experimental method was employed in conjunction with a multi-level "factorial analysis" technique to study injury potential of rear-seated children. Various sizes of Hybrid III adult surrogates, seated in a "typical" average strength collapsing type of front seat, and a three-year-old Hybrid III child surrogate, seated on a built-in booster seat located directly behind the front adult occupant, were tested at various impact severity levels in a popular "minivan" sled-buck test set up. A total of five test configurations were utilized in this study. Three levels of velocity changes ranging from 22.5 to 42.5 kph were used. The average of peak accelerations on the sled-buck tests ranged from approximately 8.2 G's up to about 11.1 G's, with absolute peak values of just over 14 G's at the higher velocity change. The parameters of the test configuration enabled the experimental data to be combined into a polynomial "injury" function of the two primary independent variables (i.e. front seat adult occupant weight and velocity change) so that the "likelihood" of rear child "injury potential" could be determined over a wide range of the key parameters. The experimentally derived head injury data was used to obtain a preliminary HIC (Head Injury Criteria) polynomial fit at the 900 level for the rear-seated child. Several actual accident cases were compared with the preliminary polynomial fit. This study provides a test efficient, multi-variable, method to compare the injury biomechanical data with actual accident cases.

Surrogate models for efficient stability analysis of brake systems

NASA Astrophysics Data System (ADS)

Nechak, Lyes; Gillot, Frédéric; Besset, Sébastien; Sinou, Jean-Jacques

2015-07-01

This study assesses capacities of the global sensitivity analysis combined together with the kriging formalism to be useful in the robust stability analysis of brake systems, which is too costly when performed with the classical complex eigenvalues analysis (CEA) based on finite element models (FEMs). By considering a simplified brake system, the global sensitivity analysis is first shown very helpful for understanding the effects of design parameters on the brake system's stability. This is allowed by the so-called Sobol indices which discriminate design parameters with respect to their influence on the stability. Consequently, only uncertainty of influent parameters is taken into account in the following step, namely, the surrogate modelling based on kriging. The latter is then demonstrated to be an interesting alternative to FEMs since it allowed, with a lower cost, an accurate estimation of the system's proportions of instability corresponding to the influent parameters.

Surrogate Structures for Computationally Expensive Optimization Problems With CPU-Time Correlated Functions

DTIC Science & Technology

2007-06-01

xc)−∇2g(x̃c)](x− xc). The second transformation is a space mapping function P that handles the change in variable dimensions (see Bandler et al. [11...17(2):188–217, 2004. 11. Bandler, J. W., Q. Cheng, S. Dakroury, A. S. Mohamed, M.H. Bakr, K. Madsen, J. Søndergaard. “ Space Mapping : The State of

Using BEHAVEPlus for predicting fire behavior in southern Appalachian hardwood stands subjected to fuel reduction treatments

Treesearch

Helen H. Mohr; Thomas A. Waldrop; Dean M. Simon

2010-01-01

There is a crucial need for fuel reduction in United States forests due to decades of fuel accumulation resulting from fire exclusion. The National Fire and Fire Surrogate Study (FFS) addresses this issue by examining the effects of three fuel reduction treatments on numerous response variables. At an FFS site in the southern Appalachian Mountains, fuels were altered...

Two Decades of Cardiovascular Trials With Primary Surrogate Endpoints: 1990-2011.

PubMed

Bikdeli, Behnood; Punnanithinont, Natdanai; Akram, Yasir; Lee, Ike; Desai, Nihar R; Ross, Joseph S; Krumholz, Harlan M

2017-03-21

Surrogate endpoint trials test strategies more efficiently but are accompanied by uncertainty about the relationship between changes in surrogate markers and clinical outcomes. We identified cardiovascular trials with primary surrogate endpoints published in the New England Journal of Medicine , Lancet , and JAMA: Journal of the American Medical Association from 1990 to 2011 and determined the trends in publication of surrogate endpoint trials and the success of the trials in meeting their primary endpoints. We tracked for publication of clinical outcome trials on the interventions tested in surrogate trials. We screened 3016 articles and identified 220 surrogate endpoint trials. From the total of 220 surrogate trials, 157 (71.4%) were positive for their primary endpoint. Only 59 (26.8%) surrogate trials had a subsequent clinical outcomes trial. Among these 59 trials, 24 outcomes trial results validated the positive surrogates, whereas 20 subsequent outcome trials were negative following positive results on a surrogate. We identified only 3 examples in which the surrogate trial was negative but a subsequent outcomes trial was conducted and showed benefit. Findings were consistent in a sample cohort of 383 screened articles inclusive of 37 surrogate endpoint trials from 6 other high-impact journals. Although cardiovascular surrogate outcomes trials frequently show superiority of the tested intervention, they are infrequently followed by a prominent outcomes trial. When there was a high-profile clinical outcomes study, nearly half of the positive surrogate trials were not validated. Cardiovascular surrogate outcome trials may be more appropriate for excluding benefit from the patient perspective than for identifying it. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Chemically and size-resolved particulate matter dry deposition on stone and surrogate surfaces inside and outside the low emission zone of Milan: application of a newly developed "Deposition Box".

PubMed

Ferrero, Luca; Casati, Marco; Nobili, Lara; D'Angelo, Luca; Rovelli, Grazia; Sangiorgi, Giorgia; Rizzi, Cristiana; Perrone, Maria Grazia; Sansonetti, Antonio; Conti, Claudia; Bolzacchini, Ezio; Bernardi, Elena; Vassura, Ivano

2018-04-01

The collection of atmospheric particles on not-filtering substrates via dry deposition, and the subsequent study of the particle-induced material decay, is trivial due to the high number of variables simultaneously acting on the investigated surface. This work reports seasonally resolved data of chemical composition and size distribution of particulate matter deposed on stone and surrogate surfaces obtained using a new method, especially developed at this purpose. A "Deposition Box" was designed allowing the particulate matter dry deposition to occur selectively removing, at the same time, variables that can mask the effect of airborne particles on material decay. A pitched roof avoided rainfall and wind variability; a standardised gentle air exchange rate ensured a continuous "sampling" of ambient air leaving unchanged the sampled particle size distribution and, at the same time, leaving quite calm condition inside the box, allowing the deposition to occur. Thus, the "Deposition Box" represents an affordable tool that can be used complementary to traditional exposure systems. With this system, several exposure campaigns, involving investigated stone materials (ISMs) (Carrara Marble, Botticino limestone, Noto calcarenite and Granite) and surrogate (Quartz, PTFE, and Aluminium) substrates, have been performed in two different sites placed in Milan (Italy) inside and outside the low emission zone. Deposition rates (30-90 μg cm -2  month -1 ) showed significant differences between sites and seasons, becoming less evident considering long-period exposures due to a positive feedback on the deposition induced by the deposited particles. Similarly, different stone substrates influenced the deposition rates too. The collected deposits have been observed with optical and scanning electron microscopes and analysed by ion chromatography. Ion deposition rates were similar in the two sites during winter, whereas it was greater outside the low emission zone during summer and considering the long-period exposure. The dimensional distribution of the collected deposits showed a significant presence of fine particles in agreement with deposition rate of the ionic fraction. The obtained results allowed to point out the role of the fine particles fraction and the importance of making seasonal studies.

Isotope Inversion Experiment evaluating the suitability of calibration in surrogate matrix for quantification via LC-MS/MS-Exemplary application for a steroid multi-method.

PubMed

Suhr, Anna Catharina; Vogeser, Michael; Grimm, Stefanie H

2016-05-30

For quotable quantitative analysis of endogenous analytes in complex biological samples by isotope dilution LC-MS/MS, the creation of appropriate calibrators is a challenge, since analyte-free authentic material is in general not available. Thus, surrogate matrices are often used to prepare calibrators and controls. However, currently employed validation protocols do not include specific experiments to verify the suitability of a surrogate matrix calibration for quantification of authentic matrix samples. The aim of the study was the development of a novel validation experiment to test whether surrogate matrix based calibrators enable correct quantification of authentic matrix samples. The key element of the novel validation experiment is the inversion of nonlabelled analytes and their stable isotope labelled (SIL) counterparts in respect to their functions, i.e. SIL compound is the analyte and nonlabelled substance is employed as internal standard. As a consequence, both surrogate and authentic matrix are analyte-free regarding SIL analytes, which allows a comparison of both matrices. We called this approach Isotope Inversion Experiment. As figure of merit we defined the accuracy of inverse quality controls in authentic matrix quantified by means of a surrogate matrix calibration curve. As a proof-of-concept application a LC-MS/MS assay addressing six corticosteroids (cortisol, cortisone, corticosterone, 11-deoxycortisol, 11-deoxycorticosterone, and 17-OH-progesterone) was chosen. The integration of the Isotope Inversion Experiment in the validation protocol for the steroid assay was successfully realized. The accuracy results of the inverse quality controls were all in all very satisfying. As a consequence the suitability of a surrogate matrix calibration for quantification of the targeted steroids in human serum as authentic matrix could be successfully demonstrated. The Isotope Inversion Experiment fills a gap in the validation process for LC-MS/MS assays quantifying endogenous analytes. We consider it a valuable and convenient tool to evaluate the correct quantification of authentic matrix samples based on a calibration curve in surrogate matrix. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of chronic lymphotic leukemia transcriptomic profile: differences between molecular subgroups.

PubMed

Jantus Lewintre, Eloisa; Reinoso Martín, Cristina; Montaner, David; Marín, Miguel; José Terol, María; Farrás, Rosa; Benet, Isabel; Calvete, Juan J; Dopazo, Joaquín; García-Conde, Javier

2009-01-01

B cell chronic lymphocytic leukemia (CLL) is a lymphoproliferative disorder with a variable clinical course. Patients with unmutated IgV(H) gene show a shorter progression-free and overall survival than patients with immunoglobulin heavy chain variable regions (IgV(H)) gene mutated. In addition, BCL6 mutations identify a subgroup of patients with high risk of progression. Gene expression was analysed in 36 early-stage patients using high-density microarrays. Around 150 genes differentially expressed were found according to IgV(H) mutations, whereas no difference was found according to BCL6 mutations. Functional profiling methods allowed us to distinguish KEGG and gene ontology terms showing coordinated gene expression changes across subgroups of CLL. We validated a set of differentially expressed genes according to IgV(H) status, scoring them as putative prognostic markers in CLL. Among them, CRY1, LPL, CD82 and DUSP22 are the ones with at least equal or superior performance to ZAP70 which is actually the most used surrogate marker of IgV(H) status.

A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning.

PubMed

Zhang, H H; Gao, S; Chen, W; Shi, L; D'Souza, W D; Meyer, R R

2013-03-21

An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equallyspaced beams (eplans), we have developed a global search metaheuristic process based on the nested partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are of superior quality.

A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning

PubMed Central

Zhang, H H; Gao, S; Chen, W; Shi, L; D’Souza, W D; Meyer, R R

2013-01-01

An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equally-spaced beams (eplans), we have developed a global search metaheuristic process based on the Nested Partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are superior quality. PMID:23459411

Low-rank separated representation surrogates of high-dimensional stochastic functions: Application in Bayesian inference

NASA Astrophysics Data System (ADS)

Validi, AbdoulAhad

2014-03-01

This study introduces a non-intrusive approach in the context of low-rank separated representation to construct a surrogate of high-dimensional stochastic functions, e.g., PDEs/ODEs, in order to decrease the computational cost of Markov Chain Monte Carlo simulations in Bayesian inference. The surrogate model is constructed via a regularized alternative least-square regression with Tikhonov regularization using a roughening matrix computing the gradient of the solution, in conjunction with a perturbation-based error indicator to detect optimal model complexities. The model approximates a vector of a continuous solution at discrete values of a physical variable. The required number of random realizations to achieve a successful approximation linearly depends on the function dimensionality. The computational cost of the model construction is quadratic in the number of random inputs, which potentially tackles the curse of dimensionality in high-dimensional stochastic functions. Furthermore, this vector-valued separated representation-based model, in comparison to the available scalar-valued case, leads to a significant reduction in the cost of approximation by an order of magnitude equal to the vector size. The performance of the method is studied through its application to three numerical examples including a 41-dimensional elliptic PDE and a 21-dimensional cavity flow.

Active Learning to Understand Infectious Disease Models and Improve Policy Making

PubMed Central

Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-01-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings. PMID:24743387

Active learning to understand infectious disease models and improve policy making.

PubMed

Willem, Lander; Stijven, Sean; Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-04-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings.

Protocol biopsies in renal transplantation: prognostic value of structural monitoring.

PubMed

Serón, D; Moreso, F

2007-09-01

The natural history of renal allograft damage has been characterized in serial protocol biopsies. The prevalence of subclinical rejection (SCR) is maximal during the first months and it is associated with the progression of interstitial fibrosis/tubular atrophy (IF/TA) and a decreased graft survival. IF/TA rapidly progress during the first months and constitutes an independent predictor of graft survival. IF/TA associated with transplant vasculopathy, SCR, or transplant glomerulopathy implies a poorer prognosis than IF/TA without additional lesions. These observations suggest that protocol biopsies could be considered a surrogate of graft survival. Preliminary data suggest that the predictive value of protocol biopsies is not inferior to acute rejection or renal function. Additionally, protocol biopsies have been employed as a secondary efficacy variable in clinical trials. This strategy has been useful to demonstrate a decrease in the progression of IF/TA in some calcineurin-free regimens. Quantification of renal damage is associated with graft survival suggesting that quantitative parameters might improve the predictive value of protocol biopsies. Validation of protocol biopsies as a surrogate of graft survival is actively pursued, as the utility of classical surrogates of graft outcome such as acute rejection has become less useful because of its decreased prevalence with actual immunosuppression.

Family Matters: Effects of Birth Order, Culture, and Family Dynamics on Surrogate Decision Making

PubMed Central

Su, Christopher T.; McMahan, Ryan D.; Williams, Brie A.; Sharma, Rashmi K.; Sudore, Rebecca L.

2014-01-01

Cultural attitudes about medical decision making and filial expectations may lead some surrogates to experience stress and family conflict. Thirteen focus groups with racially and ethnically diverse English- and Spanish-speakers from county and Veterans hospitals, senior centers, and cancer support groups were conducted to describe participants’ experiences making serious or end-of-life decisions for others. Filial expectations and family dynamics related to birth order and surrogate decision making were explored using qualitative, thematic content analysis and overarching themes from focus group transcripts were identified. The mean age of the 69 participants was 69 years ± 14 and 29% were African American, 26% were White, 26% were Asian/Pacific Islander, and 19% were Latino. Seventy percent of participants engaged in unprompted discussions about birth order and family dynamics. Six subthemes were identified within 3 overarching categories of communication, emotion, and conflict: Communication – (1) unspoken expectations and (2) discussion of death as taboo; Emotion – (3) emotional stress and (4) feelings of loneliness; and Conflict – (5) family conflict and (6) potential solutions to prevent conflict. These findings suggest that birth order and family dynamics can have profound effects on surrogate stress and coping. Clinicians should be aware of potential unspoken filial expectations for firstborns and help facilitate communication between the patient, surrogate, and extended family to reduce stress and conflict. PMID:24383459

Suitability of Organic Matter Surrogates to Predict Trihalomethane Formation in Drinking Water Sources

PubMed Central

Pifer, Ashley D.; Fairey, Julian L.

2014-01-01

Abstract Broadly applicable disinfection by-product (DBP) precursor surrogate parameters could be leveraged at drinking water treatment plants (DWTPs) to curb formation of regulated DBPs, such as trihalomethanes (THMs). In this study, dissolved organic carbon (DOC), ultraviolet absorbance at 254 nm (UV254), fluorescence excitation/emission wavelength pairs (IEx/Em), and the maximum fluorescence intensities (FMAX) of components from parallel factor (PARAFAC) analysis were evaluated as total THM formation potential (TTHMFP) precursor surrogate parameters. A diverse set of source waters from eleven DWTPs located within watersheds underlain by six different soil orders were coagulated with alum at pH 6, 7, and 8, resulting in 44 sample waters. DOC, UV254, IEx/Em, and FMAX values were measured to characterize dissolved organic matter in raw and treated waters and THMs were quantified following formation potential tests with free chlorine. For the 44 sample waters, the linear TTHMFP correlation with UV254 was stronger (r2=0.89) than I240/562 (r2=0.81, the strongest surrogate parameter from excitation/emission matrix pair picking), FMAX from a humic/fulvic acid-like PARAFAC component (r2=0.78), and DOC (r2=0.75). Results indicate that UV254 was the most accurate TTHMFP precursor surrogate parameter assessed for a diverse group of raw and alum-coagulated waters. PMID:24669183

Potential surrogate endpoints for overall survival in locoregionally advanced nasopharyngeal carcinoma: an analysis of a phase III randomized trial

PubMed Central

Chen, Yu-Pei; Chen, Yong; Zhang, Wen-Na; Liang, Shao-Bo; Zong, Jing-Feng; Chen, Lei; Mao, Yan-Ping; Tang, Ling-Long; Li, Wen-Fei; Liu, Xu; Guo, Ying; Lin, Ai-Hua; Liu, Meng-Zhong; Sun, Ying; Ma, Jun

2015-01-01

The gold standard endpoint in trials of locoregionally advanced nasopharyngeal carcinoma (NPC) is overall survival (OS). Using data from a phase III randomized trial, we evaluated whether progression-free survival (PFS), failure-free survival (FFS), distant failure-free survival (D-FFS) or locoregional failure-free survival (LR-FFS) could be reliable surrogate endpoints for OS. Between July 2002 and September 2005, 316 eligible patients with stage III-IVB NPC were randomly assigned to receive either radiotherapy alone or chemoradiotherapy. 2- and 3-year PFS, FFS, D-FFS, and LR-FFS were tested as surrogate endpoints for 5-year OS using Prentice’s four criteria. The Spearman’s rank correlation coefficient was calculated to assess the strength of the associations. After a median follow-up time of 5.8 years, 2- and 3-year D-FFS and LR-FFS were not significantly different between treatment arms, in rejection of Prentice’s second criterion. Being consistent with all Prentice’s criteria, 2- and 3-year PFS and FFS were valid surrogate endpoints for 5-year OS; the rank correlation coefficient was highest (0.84) between 3-year PFS and 5-year OS. In conclusion, PFS and FFS at 2 and 3 years may be candidate surrogate endpoints for OS at 5 years; 3-year PFS may be more appropriate for early assessment of long-term survival. PMID:26219568

Potential surrogate endpoints for overall survival in locoregionally advanced nasopharyngeal carcinoma: an analysis of a phase III randomized trial.

PubMed

Chen, Yu-Pei; Chen, Yong; Zhang, Wen-Na; Liang, Shao-Bo; Zong, Jing-Feng; Chen, Lei; Mao, Yan-Ping; Tang, Ling-Long; Li, Wen-Fei; Liu, Xu; Guo, Ying; Lin, Ai-Hua; Liu, Meng-Zhong; Sun, Ying; Ma, Jun

2015-07-29

The gold standard endpoint in trials of locoregionally advanced nasopharyngeal carcinoma (NPC) is overall survival (OS). Using data from a phase III randomized trial, we evaluated whether progression-free survival (PFS), failure-free survival (FFS), distant failure-free survival (D-FFS) or locoregional failure-free survival (LR-FFS) could be reliable surrogate endpoints for OS. Between July 2002 and September 2005, 316 eligible patients with stage III-IVB NPC were randomly assigned to receive either radiotherapy alone or chemoradiotherapy. 2- and 3-year PFS, FFS, D-FFS, and LR-FFS were tested as surrogate endpoints for 5-year OS using Prentice's four criteria. The Spearman's rank correlation coefficient was calculated to assess the strength of the associations. After a median follow-up time of 5.8 years, 2- and 3-year D-FFS and LR-FFS were not significantly different between treatment arms, in rejection of Prentice's second criterion. Being consistent with all Prentice's criteria, 2- and 3-year PFS and FFS were valid surrogate endpoints for 5-year OS; the rank correlation coefficient was highest (0.84) between 3-year PFS and 5-year OS. In conclusion, PFS and FFS at 2 and 3 years may be candidate surrogate endpoints for OS at 5 years; 3-year PFS may be more appropriate for early assessment of long-term survival.

Identification of surrogate endpoints in patients with locoregionally advanced nasopharyngeal carcinoma receiving neoadjuvant chemotherapy plus concurrent chemoradiotherapy versus concurrent chemoradiotherapy alone.

PubMed

Chen, Yu-Pei; Zhang, Wen-Na; Tang, Ling-Long; Mao, Yan-Ping; Liu, Xu; Chen, Lei; Zhou, Guan-Qun; Mai, Hai-Qiang; Shao, Jian-Yong; Jia, Wei-Hua; Kang, Tie-Bang; Zeng, Mu-Sheng; Sun, Ying; Ma, Jun

2015-11-24

In the era of intensity-modulated radiotherapy (IMRT), the efficacy of additional neoadjuvant chemotherapy (NACT) to concurrent chemoradiotherapy (CCRT) in locoregionally advanced nasopharyngeal carcinoma (NPC) is currently being investigated in ongoing trials. Overall survival (OS) is the gold standard endpoint in NPC trials. We performed this analysis to identify surrogate endpoints for OS, which could shorten follow-up duration and speed up assessment of treatment effects. We retrospectively analysed 208 matched-pair patients with locoregionally advanced NPC receiving NACT+CCRT or CCRT. Progression-free survival (PFS), failure-free survival (FFS), distant failure-free survival (D-FFS) and locoregional failure-free survival (LR-FFS) at 2 and 3 years were assessed as surrogates for 5-year OS according to Prentice's criteria. The strength of the associations were assessed using Spearman's rank correlation coefficient. No significant differences were observed between treatment arms for any surrogate endpoint at 2 years, which rejected Prentice's second criterion. In contrast, 3-year LR-FFS, PFS, FFS and D-FFS were consistent with all four of Prentice's criteria; the rank correlation coefficient (0.730) between 3-year PFS and 5-year OS was highest. 3-year PFS, FFS and D-FFS could be valid surrogate endpoints for 5-year OS; 3-year PFS may be the most accurate.

Family matters: effects of birth order, culture, and family dynamics on surrogate decision-making.

PubMed

Su, Christopher T; McMahan, Ryan D; Williams, Brie A; Sharma, Rashmi K; Sudore, Rebecca L

2014-01-01

Cultural attitudes about medical decision-making and filial expectations may lead some surrogates to experience stress and family conflict. Thirteen focus groups with racially and ethnically diverse English and Spanish speakers from county and Veterans Affairs hospitals, senior centers, and cancer support groups were conducted to describe participants' experiences making serious or end-of-life decisions for others. Filial expectations and family dynamics related to birth order and surrogate decision-making were explored using qualitative, thematic content analysis, and overarching themes from focus group transcripts were identified. The mean age of the 69 participants was 69 ± 14, and 29% were African American, 26% were white, 26% were Asian or Pacific Islander, and 19% were Latino. Seventy percent of participants engaged in unprompted discussions about birth order and family dynamics. Six subthemes were identified within three overarching categories: communication (unspoken expectations and discussion of death as taboo), emotion (emotional stress and feelings of loneliness), and conflict (family conflict and potential solutions to prevent conflict). These findings suggest that birth order and family dynamics can have profound effects on surrogate stress and coping. Clinicians should be aware of potential unspoken filial expectations for firstborns and help facilitate communication between the patient, surrogate, and extended family to reduce stress and conflict. © Published 2013. This article is a U.S. Government work and is in the public domain in the U.S.A.

A toxin-free enzyme-linked immunosorbent assay for the analysis of aflatoxins based on a VHH surrogate standard.

PubMed

Wang, Yanru; Li, Peiwu; Zhang, Qi; Hu, Xiaofeng; Zhang, Wen

2016-09-01

A toxin-free enzyme-linked immunosorbent assay (ELISA) for aflatoxins was developed using an anti-idiotype nanobody VHH 2-5 as surrogate standard. Anti-idiotype nanobody VHH 2-5 was generated by immunizing an alpaca with anti-aflatoxin monoclonal antibody 1C11. This assay was used to detect aflatoxins in agro-products after a simple extraction with 75 % methanol/H2O. Aflatoxin concentration was calculated by a two-step approach: the concentration of VHH 2-5 was first obtained by a four-parameter logistic regression from the detected absorbance value at 450 nm, and then converted to aflatoxin concentration by a linear equation. The assay exhibits a limit of detection (LOD) of 0.015 ng mL(-1), which is better than or comparable with conventional immunoassays. The performance of our VHH surrogate-based ELISA was further validated with a high-performance liquid chromatography (HPLC) method for total aflatoxins determination in 20 naturally contaminated peanut samples, displaying a good correlation (R (2) = 0.988). In conclusion, the proposed assay represents a first example applying an anti-idiotype VHH antibody as a standard surrogate in ELISA. With the advantages of high stability and ease of production, the VHH antibody-based standard surrogate can be extended in the future to immunoassays for other highly toxic compounds. Graphical Abstract ᅟ.

Predicting temporal variation in zooplankton beta diversity is challenging

PubMed Central

Castelo Branco, Christina W.; Kozlowsky-Suzuki, Betina; Sousa-Filho, Izidro F.; Souza, Leonardo Coimbra e; Bini, Luis Mauricio

2017-01-01

Beta diversity, the spatial variation in species composition, has been related to different explanatory variables, including environmental heterogeneity, productivity and connectivity. Using a long-term time series of zooplankton data collected over 62 months in a tropical reservoir (Ribeirão das Lajes Reservoir, Rio de Janeiro State, Brazil), we tested whether beta diversity (as measured across six sites distributed along the main axis of the reservoir) was correlated with environmental heterogeneity (spatial environmental variation in a given month), chlorophyll-a concentration (a surrogate for productivity) and water level. We did not found evidence for the role of these predictors, suggesting the need to reevaluate predictions or at least to search for better surrogates of the processes that hypothetically control beta diversity variation. However, beta diversity declined over time, which is consistent with the process of biotic homogenization, a worldwide cause of concern. PMID:29095892

Indoor radon, geogenic radon surrogates and geology - Investigations on their correlation.

PubMed

Friedmann, H; Baumgartner, A; Bernreiter, M; Gräser, J; Gruber, V; Kabrt, F; Kaineder, H; Maringer, F J; Ringer, W; Seidel, C; Wurm, G

2017-01-01

The indoor radon concentration was measured in most houses in a couple of municipalities in Austria. At the same time the activity concentration of radium in soil, the soil gas radon concentration, the permeability of the ground and the ambient dose equivalent rate were also measured and the geological situations (geological units) were recorded too. From the indoor radon concentration and different house and living parameters a radon potential (Austrian radon potential) was derived which should represent the radon concentration in a standard room. Another radon potential (Neznal radon potential) was calculated from the soil gas radon concentration and the permeability. The aim of the investigation was to correlate all the different variables and to test if the use of surrogate data (e.g. geological information, ambient dose equivalent rate, etc.) can be used to judge the radon risk for an area without performing numerous indoor measurements. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting temporal variation in zooplankton beta diversity is challenging.

PubMed

Lopes, Vanessa Guimarães; Castelo Branco, Christina W; Kozlowsky-Suzuki, Betina; Sousa-Filho, Izidro F; Souza, Leonardo Coimbra E; Bini, Luis Mauricio

2017-01-01

Beta diversity, the spatial variation in species composition, has been related to different explanatory variables, including environmental heterogeneity, productivity and connectivity. Using a long-term time series of zooplankton data collected over 62 months in a tropical reservoir (Ribeirão das Lajes Reservoir, Rio de Janeiro State, Brazil), we tested whether beta diversity (as measured across six sites distributed along the main axis of the reservoir) was correlated with environmental heterogeneity (spatial environmental variation in a given month), chlorophyll-a concentration (a surrogate for productivity) and water level. We did not found evidence for the role of these predictors, suggesting the need to reevaluate predictions or at least to search for better surrogates of the processes that hypothetically control beta diversity variation. However, beta diversity declined over time, which is consistent with the process of biotic homogenization, a worldwide cause of concern.

Coral reef habitats as surrogates of species, ecological functions, and ecosystem services.

PubMed

Mumby, Peter J; Broad, Kenneth; Brumbaugh, Daniel R; Dahlgren, Craig P; Harborne, Alastair R; Hastings, Alan; Holmes, Katherine E; Kappel, Carrie V; Micheli, Fiorenza; Sanchirico, James N

2008-08-01

Habitat maps are often the core spatially consistent data set on which marine reserve networks are designed, but their efficacy as surrogates for species richness and applicability to other conservation measures is poorly understood. Combining an analysis of field survey data, literature review, and expert assessment by a multidisciplinary working group, we examined the degree to which Caribbean coastal habitats provide useful planning information on 4 conservation measures: species richness, the ecological functions of fish species, ecosystem processes, and ecosystem services. Approximately one-quarter to one-third of benthic invertebrate species and fish species (disaggregated by life phase; hereafter fish species) occurred in a single habitat, and Montastraea-dominated forereefs consistently had the highest richness of all species, processes, and services. All 11 habitats were needed to represent all 277 fish species in the seascape, although reducing the conservation target to 95% of species approximately halved the number of habitats required to ensure representation. Species accumulation indices (SAIs) were used to compare the efficacy of surrogates and revealed that fish species were a more appropriate surrogate of benthic species (SAI = 71%) than benthic species were for fishes (SAI = 42%). Species of reef fishes were also distributed more widely across the seascape than invertebrates and therefore their use as a surrogate simultaneously included mangroves, sea grass, and coral reef habitats. Functional classes of fishes served as effective surrogates of fish and benthic species which, given their ease to survey, makes them a particularly useful measure for conservation planning. Ecosystem processes and services exhibited great redundancy among habitats and were ineffective as surrogates of species. Therefore, processes and services in this case were generally unsuitable for a complementarity-based approach to reserve design. In contrast, the representation of species or functional classes ensured inclusion of all processes and services in the reserve network.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zawisza, I; Yan, H; Yin, F

Purpose: To assure that tumor motion is within the radiation field during high-dose and high-precision radiosurgery, real-time imaging and surrogate monitoring are employed. These methods are useful in providing real-time tumor/surrogate motion but no future information is available. In order to anticipate future tumor/surrogate motion and track target location precisely, an algorithm is developed and investigated for estimating surrogate motion multiple-steps ahead. Methods: The study utilized a one-dimensional surrogate motion signal divided into three components: (a) training component containing the primary data including the first frame to the beginning of the input subsequence; (b) input subsequence component of the surrogatemore » signal used as input to the prediction algorithm: (c) output subsequence component is the remaining signal used as the known output of the prediction algorithm for validation. The prediction algorithm consists of three major steps: (1) extracting subsequences from training component which best-match the input subsequence according to given criterion; (2) calculating weighting factors from these best-matched subsequence; (3) collecting the proceeding parts of the subsequences and combining them together with assigned weighting factors to form output. The prediction algorithm was examined for several patients, and its performance is assessed based on the correlation between prediction and known output. Results: Respiratory motion data was collected for 20 patients using the RPM system. The output subsequence is the last 50 samples (∼2 seconds) of a surrogate signal, and the input subsequence was 100 (∼3 seconds) frames prior to the output subsequence. Based on the analysis of correlation coefficient between predicted and known output subsequence, the average correlation is 0.9644±0.0394 and 0.9789±0.0239 for equal-weighting and relative-weighting strategies, respectively. Conclusion: Preliminary results indicate that the prediction algorithm is effective in estimating surrogate motion multiple-steps in advance. Relative-weighting method shows better prediction accuracy than equal-weighting method. More parameters of this algorithm are under investigation.« less

Simultaneous tumor and surrogate motion tracking with dynamic MRI for radiation therapy planning

NASA Astrophysics Data System (ADS)

Park, Seyoun; Farah, Rana; Shea, Steven M.; Tryggestad, Erik; Hales, Russell; Lee, Junghoon

2018-01-01

Respiration-induced tumor motion is a major obstacle for achieving high-precision radiotherapy of cancers in the thoracic and abdominal regions. Surrogate-based estimation and tracking methods are commonly used in radiotherapy, but with limited understanding of quantified correlation to tumor motion. In this study, we propose a method to simultaneously track the lung tumor and external surrogates to evaluate their spatial correlation in a quantitative way using dynamic MRI, which allows real-time acquisition without ionizing radiation exposure. To capture the lung and whole tumor, four MRI-compatible fiducials are placed on the patient’s chest and upper abdomen. Two different types of acquisitions are performed in the sagittal orientation including multi-slice 2D cine MRIs to reconstruct 4D-MRI and two-slice 2D cine MRIs to simultaneously track the tumor and fiducials. A phase-binned 4D-MRI is first reconstructed from multi-slice MR images using body area as a respiratory surrogate and groupwise registration. The 4D-MRI provides 3D template volumes for different breathing phases. 3D tumor position is calculated by 3D-2D template matching in which 3D tumor templates in the 4D-MRI reconstruction and the 2D cine MRIs from the two-slice tracking dataset are registered. 3D trajectories of the external surrogates are derived via matching a 3D geometrical model of the fiducials to their segmentations on the 2D cine MRIs. We tested our method on ten lung cancer patients. Using a correlation analysis, the 3D tumor trajectory demonstrates a noticeable phase mismatch and significant cycle-to-cycle motion variation, while the external surrogate was not sensitive enough to capture such variations. Additionally, there was significant phase mismatch between surrogate signals obtained from the fiducials at different locations.

Integrating surrogate models into subsurface simulation framework allows computation of complex reactive transport scenarios

NASA Astrophysics Data System (ADS)

De Lucia, Marco; Kempka, Thomas; Jatnieks, Janis; Kühn, Michael

2017-04-01

Reactive transport simulations - where geochemical reactions are coupled with hydrodynamic transport of reactants - are extremely time consuming and suffer from significant numerical issues. Given the high uncertainties inherently associated with the geochemical models, which also constitute the major computational bottleneck, such requirements may seem inappropriate and probably constitute the main limitation for their wide application. A promising way to ease and speed-up such coupled simulations is achievable employing statistical surrogates instead of "full-physics" geochemical models [1]. Data-driven surrogates are reduced models obtained on a set of pre-calculated "full physics" simulations, capturing their principal features while being extremely fast to compute. Model reduction of course comes at price of a precision loss; however, this appears justified in presence of large uncertainties regarding the parametrization of geochemical processes. This contribution illustrates the integration of surrogates into the flexible simulation framework currently being developed by the authors' research group [2]. The high level language of choice for obtaining and dealing with surrogate models is R, which profits from state-of-the-art methods for statistical analysis of large simulations ensembles. A stand-alone advective mass transport module was furthermore developed in order to add such capability to any multiphase finite volume hydrodynamic simulator within the simulation framework. We present 2D and 3D case studies benchmarking the performance of surrogates and "full physics" chemistry in scenarios pertaining the assessment of geological subsurface utilization. [1] Jatnieks, J., De Lucia, M., Dransch, D., Sips, M.: "Data-driven surrogate model approach for improving the performance of reactive transport simulations.", Energy Procedia 97, 2016, p. 447-453. [2] Kempka, T., Nakaten, B., De Lucia, M., Nakaten, N., Otto, C., Pohl, M., Chabab [Tillner], E., Kühn, M.: "Flexible Simulation Framework to Couple Processes in Complex 3D Models for Subsurface Utilization Assessment.", Energy Procedia, 97, 2016 p. 494-501.

Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature

PubMed Central

Cayuela, Luis; González-Caro, Sebastián; Aldana, Ana M.; Stevenson, Pablo R.; Phillips, Oliver; Cogollo, Álvaro; Peñuela, Maria C.; von Hildebrand, Patricio; Jiménez, Eliana; Melo, Omar; Londoño-Vega, Ana Catalina; Mendoza, Irina; Velásquez, Oswaldo; Fernández, Fernando; Serna, Marcela; Velázquez-Rua, Cesar; Benítez, Doris; Rey-Benayas, José M.

2017-01-01

Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage. PMID:28301482

Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature.

PubMed

Álvarez-Dávila, Esteban; Cayuela, Luis; González-Caro, Sebastián; Aldana, Ana M; Stevenson, Pablo R; Phillips, Oliver; Cogollo, Álvaro; Peñuela, Maria C; von Hildebrand, Patricio; Jiménez, Eliana; Melo, Omar; Londoño-Vega, Ana Catalina; Mendoza, Irina; Velásquez, Oswaldo; Fernández, Fernando; Serna, Marcela; Velázquez-Rua, Cesar; Benítez, Doris; Rey-Benayas, José M

2017-01-01

Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage.

Multiple scaling behaviour and nonlinear traits in music scores

PubMed Central

Larralde, Hernán; Martínez-Mekler, Gustavo; Müller, Markus

2017-01-01

We present a statistical analysis of music scores from different composers using detrended fluctuation analysis (DFA). We find different fluctuation profiles that correspond to distinct autocorrelation structures of the musical pieces. Further, we reveal evidence for the presence of nonlinear autocorrelations by estimating the DFA of the magnitude series, a result validated by a corresponding study of appropriate surrogate data. The amount and the character of nonlinear correlations vary from one composer to another. Finally, we performed a simple experiment in order to evaluate the pleasantness of the musical surrogate pieces in comparison with the original music and find that nonlinear correlations could play an important role in the aesthetic perception of a musical piece. PMID:29308256

Multiple scaling behaviour and nonlinear traits in music scores

NASA Astrophysics Data System (ADS)

González-Espinoza, Alfredo; Larralde, Hernán; Martínez-Mekler, Gustavo; Müller, Markus

2017-12-01

We present a statistical analysis of music scores from different composers using detrended fluctuation analysis (DFA). We find different fluctuation profiles that correspond to distinct autocorrelation structures of the musical pieces. Further, we reveal evidence for the presence of nonlinear autocorrelations by estimating the DFA of the magnitude series, a result validated by a corresponding study of appropriate surrogate data. The amount and the character of nonlinear correlations vary from one composer to another. Finally, we performed a simple experiment in order to evaluate the pleasantness of the musical surrogate pieces in comparison with the original music and find that nonlinear correlations could play an important role in the aesthetic perception of a musical piece.

Variability of Urinary Phthalate Metabolite and Bisphenol A Concentrations before and during Pregnancy

PubMed Central

Braun, Joe M.; Smith, Kristen W.; Williams, Paige L.; Calafat, Antonia M.; Berry, Katharine; Ehrlich, Shelley

2012-01-01

Background: Gestational phthalate and bisphenol A (BPA) exposure may increase the risk of adverse maternal/child health outcomes, but there are few data on the variability of urinary biomarkers before and during pregnancy. Objective: We characterized the variability of urinary phthalate metabolite and BPA concentrations before and during pregnancy and the ability of a single spot urine sample to classify average gestational exposure. Methods: We collected 1,001 urine samples before and during pregnancy from 137 women who were partners in couples attending a Boston fertility clinic and who had a live birth. Women provided spot urine samples before (n ≥ 2) and during (n ≥ 2) pregnancy. We measured urinary concentrations of monoethyl phthalate (MEP), mono-n-butyl phthalate (MBP), mono-iso-butyl phthalate, monobenzyl phthalate (MBzP), four metabolites of di-(2-ethylhexyl) phthalate (DEHP), and BPA. After adjusting for specific gravity, we characterized biomarker variability using intraclass correlation coefficients (ICCs) and conducted several surrogate category analyses to determine whether a single spot urine sample could adequately classify average gestational exposure. Results: Absolute concentrations of phthalate metabolites and BPA were similar before and during pregnancy. Variability was higher during pregnancy than before pregnancy for BPA and MBzP, but similar during and before pregnancy for MBP, MEP, and ΣDEHP. During pregnancy, MEP (ICC = 0.50) and MBP (ICC = 0.45) were less variable than BPA (ICC = 0.12), MBzP (ICC = 0.25), and ΣDEHP metabolites (ICC = 0.08). Surrogate analyses suggested that a single spot urine sample may reasonably classify MEP and MBP concentrations during pregnancy, but more than one sample may be necessary for MBzP, DEHP, and BPA. Conclusions: Urinary phthalate metabolites and BPA concentrations were variable before and during pregnancy, but the magnitude of variability was biomarker specific. A single spot urine sample adequately classified MBP and MEP concentrations during pregnancy. The present results may be related to unique features of the women studied, and replication in other pregnancy cohorts is recommended. PMID:22262702

A new algorithm combining geostatistics with the surrogate data approach to increase the accuracy of comparisons of point radiation measurements with cloud measurements

NASA Astrophysics Data System (ADS)

Venema, V. K. C.; Lindau, R.; Varnai, T.; Simmer, C.

2009-04-01

Two main groups of statistical methods used in the Earth sciences are geostatistics and stochastic modelling. Geostatistical methods, such as various kriging algorithms, aim at estimating the mean value for every point as well as possible. In case of sparse measurements, such fields have less variability at small scales and a narrower distribution as the true field. This can lead to biases if a nonlinear process is simulated on such a kriged field. Stochastic modelling aims at reproducing the structure of the data. One of the stochastic modelling methods, the so-called surrogate data approach, replicates the value distribution and power spectrum of a certain data set. However, while stochastic methods reproduce the statistical properties of the data, the location of the measurement is not considered. Because radiative transfer through clouds is a highly nonlinear process it is essential to model the distribution (e.g. of optical depth, extinction, liquid water content or liquid water path) accurately as well as the correlations in the cloud field because of horizontal photon transport. This explains the success of surrogate cloud fields for use in 3D radiative transfer studies. However, up to now we could only achieve good results for the radiative properties averaged over the field, but not for a radiation measurement located at a certain position. Therefore we have developed a new algorithm that combines the accuracy of stochastic (surrogate) modelling with the positioning capabilities of kriging. In this way, we can automatically profit from the large geostatistical literature and software. The algorithm is tested on cloud fields from large eddy simulations (LES). On these clouds a measurement is simulated. From the pseudo-measurement we estimated the distribution and power spectrum. Furthermore, the pseudo-measurement is kriged to a field the size of the final surrogate cloud. The distribution, spectrum and the kriged field are the inputs to the algorithm. This algorithm is similar to the standard iterative amplitude adjusted Fourier transform (IAAFT) algorithm, but has an additional iterative step in which the surrogate field is nudged towards the kriged field. The nudging strength is gradually reduced to zero. We work with four types of pseudo-measurements: one zenith pointing measurement (which together with the wind produces a line measurement), five zenith pointing measurements, a slow and a fast azimuth scan (which together with the wind produce spirals). Because we work with LES clouds and the truth is known, we can validate the algorithm by performing 3D radiative transfer calculations on the original LES clouds and on the new surrogate clouds. For comparison also the radiative properties of the kriged fields and standard surrogate fields are computed. Preliminary results already show that these new surrogate clouds reproduce the structure of the original clouds very well and the minima and maxima are located where the pseudo-measurements sees them. The main limitation seems to be the amount of data, which is especially very limited in case of just one zenith pointing measurement.

Prediction of survival benefits from progression-free survival benefits in advanced non-small-cell lung cancer: evidence from a meta-analysis of 2334 patients from 5 randomised trials

PubMed Central

Laporte, Silvy; Squifflet, Pierre; Baroux, Noémie; Fossella, Frank; Georgoulias, Vassilis; Pujol, Jean-Louis; Douillard, Jean-Yves; Kudoh, Shinzohy; Pignon, Jean-Pierre; Quinaux, Emmanuel; Buyse, Marc

2013-01-01

Objectives To investigate whether progression-free survival (PFS) can be considered a surrogate endpoint for overall survival (OS) in advanced non-small-cell lung cancer (NSCLC). Design Meta-analysis of individual patient data from randomised trials. Setting Five randomised controlled trials comparing docetaxel-based chemotherapy with vinorelbine-based chemotherapy for the first-line treatment of NSCLC. Participants 2331 patients with advanced NSCLC. Primary and secondary outcome measures Surrogacy of PFS for OS was assessed through the association between these endpoints and between the treatment effects on these endpoints. The surrogate threshold effect was the minimum treatment effect on PFS required to predict a non-zero treatment effect on OS. Results The median follow-up of patients still alive was 23.4 months. Median OS was 10 months and median PFS was 5.5 months. The treatment effects on PFS and OS were correlated, whether using centres (R²=0.62, 95% CI 0.52 to 0.72) or prognostic strata (R²=0.72, 95% CI 0.60 to 0.84) as units of analysis. The surrogate threshold effect was a PFS hazard ratio (HR) of 0.49 using centres or 0.53 using prognostic strata. Conclusions These analyses provide only modest support for considering PFS as an acceptable surrogate for OS in patients with advanced NSCLC. Only treatments that have a major impact on PFS (risk reduction of at least 50%) would be expected to also have a significant effect on OS. Whether these results also apply to targeted therapies is an open question that requires independent evaluation. PMID:23485717

Quality-by-design case study: investigation of the role of poloxamer in immediate-release tablets by experimental design and multivariate data analysis.

PubMed

Kaul, Goldi; Huang, Jun; Chatlapalli, Ramarao; Ghosh, Krishnendu; Nagi, Arwinder

2011-12-01

The role of poloxamer 188, water and binder addition rate, on retarding dissolution in immediate-release tablets of a model drug from BCS class II was investigated by means of multivariate data analysis (MVDA) combined with design of experiments (DOE). While the DOE analysis yielded important clues into the cause-and-effect relationship between the responses and design factors, multivariate data analysis of the 40+ variables provided additional information on slowdown in tablet dissolution. A steep dependence of both tablet dissolution and disintegration on the poloxamer and less so on other design variables was observed. Poloxamer was found to increase dissolution rates in granules as expected of surfactants in general but retard dissolution in tablets. The unexpected effect of poloxamer in tablets was accompanied by an increase in tablet-disintegration-time-mediated slowdown of tablet dissolution and by a surrogate binding effect of poloxamer at higher concentrations. It was additionally realized through MVDA that poloxamer in tablets either acts as a binder by itself or promotes binder action of the binder povidone resulting in increased intragranular cohesion. Additionally, poloxamer was found to mediate tablet dissolution on stability as well. In contrast to tablet dissolution at release (time zero), poloxamer appeared to increase tablet dissolution in a concentration-dependent manner on accelerated open-dish stability. Substituting polysorbate 80 as an alternate surfactant in place of poloxamer in the formulation was found to stabilize tablet dissolution.

Instrumented gait analysis: a measure of gait improvement by a wheeled walker in hospitalized geriatric patients.

PubMed

Schülein, Samuel; Barth, Jens; Rampp, Alexander; Rupprecht, Roland; Eskofier, Björn M; Winkler, Jürgen; Gaßmann, Karl-Günter; Klucken, Jochen

2017-02-27

In an increasing aging society, reduced mobility is one of the most important factors limiting activities of daily living and overall quality of life. The ability to walk independently contributes to the mobility, but is increasingly restricted by numerous diseases that impair gait and balance. The aim of this cross-sectional observation study was to examine whether spatio-temporal gait parameters derived from mobile instrumented gait analysis can be used to measure the gait stabilizing effects of a wheeled walker (WW) and whether these gait parameters may serve as surrogate marker in hospitalized patients with multifactorial gait and balance impairment. One hundred six patients (ages 68-95) wearing inertial sensor equipped shoes passed an instrumented walkway with and without gait support from a WW. The walkway assessed the risk of falling associated gait parameters velocity, swing time, stride length, stride time- and double support time variability. Inertial sensor-equipped shoes measured heel strike and toe off angles, and foot clearance. The use of a WW improved the risk of spatio-temporal parameters velocity, swing time, stride length and the sagittal plane associated parameters heel strike and toe off angles in all patients. First-time users (FTUs) showed similar gait parameter improvement patterns as frequent WW users (FUs). However, FUs with higher levels of gait impairment improved more in velocity, stride length and toe off angle compared to the FTUs. The impact of a WW can be quantified objectively by instrumented gait assessment. Thus, objective gait parameters may serve as surrogate markers for the use of walking aids in patients with gait and balance impairments.

Effect of laser irradiance and wavelength on the analysis of gold- and silver-bearing minerals with laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Díaz, Daniel; Molina, Alejandro; Hahn, David

2018-07-01

The influence of laser irradiance and wavelength on the analysis of gold and silver in ore and surrogate samples with laser-induced breakdown spectroscopy (LIBS) was evaluated. Gold-doped mineral samples (surrogates) and ore samples containing naturally-occurring gold and silver were analyzed with LIBS using 1064 and 355 nm laser wavelengths at irradiances from 0.36 × 109 to 19.9 × 109 W/cm2 and 0.97 × 109 to 4.3 × 109 W/cm2, respectively. The LIBS net, background and signal-to-background signals were analyzed. For all irradiances, wavelengths, samples and analytes the calibration curves behaved linearly for concentrations from 1 to 9 μg/g gold (surrogate samples) and 0.7 to 47.0 μg/g silver (ore samples). However, it was not possible to prepare calibration curves for gold-bearing ore samples (at any concentration) nor for gold-doped surrogate samples with gold concentrations below 1 μg/g. Calibration curve parameters for gold-doped surrogate samples were statistically invariant at 1064 and 355 nm. Contrary, the Ag-ore analyte showed higher emission intensity at 1064 nm, but the signal-to-background normalization reduced the effect of laser wavelength of silver calibration plots. The gold-doped calibration curve metrics improved at higher laser irradiance, but that did not translate into lower limits of detection. While coefficients of determination (R2) and limits of detection did not vary significantly with laser wavelength, the LIBS repeatability at 355 nm improved up to a 50% with respect to that at 1064 nm. Plasma diagnostics by the Boltzmann and Stark broadening methods showed that the plasma temperature and electron density did not follow a specific trend as the wavelength changed for the delay and gate times used. This research presents supporting evidence that the LIBS discrete sampling features combined with the discrete and random distribution of gold in minerals hinder gold analysis by LIBS in ore samples; however, the use of higher laser irradiances at 1064 nm increased the probability of sampling and detecting naturally-occurring gold.

Evaluating surrogate endpoints, prognostic markers, and predictive markers — some simple themes

PubMed Central

Baker, Stuart G.; Kramer, Barnett S.

2014-01-01

Background A surrogate endpoint is an endpoint observed earlier than the true endpoint (a health outcome) that is used to draw conclusions about the effect of treatment on the unobserved true endpoint. A prognostic marker is a marker for predicting the risk of an event given a control treatment; it informs treatment decisions when there is information on anticipated benefits and harms of a new treatment applied to persons at high risk. A predictive marker is a marker for predicting the effect of treatment on outcome in a subgroup of patients or study participants; it provides more rigorous information for treatment selection than a prognostic marker when it is based on estimated treatment effects in a randomized trial. Methods We organized our discussion around a different theme for each topic. Results “Fundamentally an extrapolation” refers to the non-statistical considerations and assumptions needed when using surrogate endpoints to evaluate a new treatment. “Decision analysis to the rescue” refers to use the use of decision analysis to evaluate an additional prognostic marker because it is not possible to choose between purely statistical measures of marker performance. “The appeal of simplicity” refers to a straightforward and efficient use of a single randomized trial to evaluate overall treatment effect and treatment effect within subgroups using predictive markers. Conclusion The simple themes provide a general guideline for evaluation of surrogate endpoints, prognostic markers, and predictive markers. PMID:25385934

Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection: a systematic review and meta-analysis

PubMed Central

Smith, Jeffrey D.; MacDougall, Colin C.; Johnstone, Jennie; Copes, Ray A.; Schwartz, Brian; Garber, Gary E.

2016-01-01

Background: Conflicting recommendations exist related to which facial protection should be used by health care workers to prevent transmission of acute respiratory infections, including pandemic influenza. We performed a systematic review of both clinical and surrogate exposure data comparing N95 respirators and surgical masks for the prevention of transmissible acute respiratory infections. Methods: We searched various electronic databases and the grey literature for relevant studies published from January 1990 to December 2014. Randomized controlled trials (RCTs), cohort studies and case–control studies that included data on health care workers wearing N95 respirators and surgical masks to prevent acute respiratory infections were included in the meta-analysis. Surrogate exposure studies comparing N95 respirators and surgical masks using manikins or adult volunteers under simulated conditions were summarized separately. Outcomes from clinical studies were laboratory-confirmed respiratory infection, influenza-like illness and workplace absenteeism. Outcomes from surrogate exposure studies were filter penetration, face-seal leakage and total inward leakage. Results: We identified 6 clinical studies (3 RCTs, 1 cohort study and 2 case–control studies) and 23 surrogate exposure studies. In the meta-analysis of the clinical studies, we found no significant difference between N95 respirators and surgical masks in associated risk of (a) laboratory-confirmed respiratory infection (RCTs: odds ratio [OR] 0.89, 95% confidence interval [CI] 0.64–1.24; cohort study: OR 0.43, 95% CI 0.03–6.41; case–control studies: OR 0.91, 95% CI 0.25–3.36); (b) influenza-like illness (RCTs: OR 0.51, 95% CI 0.19–1.41); or (c) reported workplace absenteeism (RCT: OR 0.92, 95% CI 0.57–1.50). In the surrogate exposure studies, N95 respirators were associated with less filter penetration, less face-seal leakage and less total inward leakage under laboratory experimental conditions, compared with surgical masks. Interpretation: Although N95 respirators appeared to have a protective advantage over surgical masks in laboratory settings, our meta-analysis showed that there were insufficient data to determine definitively whether N95 respirators are superior to surgical masks in protecting health care workers against transmissible acute respiratory infections in clinical settings. PMID:26952529

Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection: a systematic review and meta-analysis.

PubMed

Smith, Jeffrey D; MacDougall, Colin C; Johnstone, Jennie; Copes, Ray A; Schwartz, Brian; Garber, Gary E

2016-05-17

Conflicting recommendations exist related to which facial protection should be used by health care workers to prevent transmission of acute respiratory infections, including pandemic influenza. We performed a systematic review of both clinical and surrogate exposure data comparing N95 respirators and surgical masks for the prevention of transmissible acute respiratory infections. We searched various electronic databases and the grey literature for relevant studies published from January 1990 to December 2014. Randomized controlled trials (RCTs), cohort studies and case-control studies that included data on health care workers wearing N95 respirators and surgical masks to prevent acute respiratory infections were included in the meta-analysis. Surrogate exposure studies comparing N95 respirators and surgical masks using manikins or adult volunteers under simulated conditions were summarized separately. Outcomes from clinical studies were laboratory-confirmed respiratory infection, influenza-like illness and workplace absenteeism. Outcomes from surrogate exposure studies were filter penetration, face-seal leakage and total inward leakage. We identified 6 clinical studies (3 RCTs, 1 cohort study and 2 case-control studies) and 23 surrogate exposure studies. In the meta-analysis of the clinical studies, we found no significant difference between N95 respirators and surgical masks in associated risk of (a) laboratory-confirmed respiratory infection (RCTs: odds ratio [OR] 0.89, 95% confidence interval [CI] 0.64-1.24; cohort study: OR 0.43, 95% CI 0.03-6.41; case-control studies: OR 0.91, 95% CI 0.25-3.36); (b) influenza-like illness (RCTs: OR 0.51, 95% CI 0.19-1.41); or (c) reported workplace absenteeism (RCT: OR 0.92, 95% CI 0.57-1.50). In the surrogate exposure studies, N95 respirators were associated with less filter penetration, less face-seal leakage and less total inward leakage under laboratory experimental conditions, compared with surgical masks. Although N95 respirators appeared to have a protective advantage over surgical masks in laboratory settings, our meta-analysis showed that there were insufficient data to determine definitively whether N95 respirators are superior to surgical masks in protecting health care workers against transmissible acute respiratory infections in clinical settings. © 2016 Canadian Medical Association or its licensors.

Exploring total cardiac variability in healthy and pathophysiological subjects using improved refined multiscale entropy.

PubMed

Marwaha, Puneeta; Sunkaria, Ramesh Kumar

2017-02-01

Multiscale entropy (MSE) and refined multiscale entropy (RMSE) techniques are being widely used to evaluate the complexity of a time series across multiple time scales 't'. Both these techniques, at certain time scales (sometimes for the entire time scales, in the case of RMSE), assign higher entropy to the HRV time series of certain pathologies than that of healthy subjects, and to their corresponding randomized surrogate time series. This incorrect assessment of signal complexity may be due to the fact that these techniques suffer from the following limitations: (1) threshold value 'r' is updated as a function of long-term standard deviation and hence unable to explore the short-term variability as well as substantial variability inherited in beat-to-beat fluctuations of long-term HRV time series. (2) In RMSE, entropy values assigned to different filtered scaled time series are the result of changes in variance, but do not completely reflect the real structural organization inherited in original time series. In the present work, we propose an improved RMSE (I-RMSE) technique by introducing a new procedure to set the threshold value by taking into account the period-to-period variability inherited in a signal and evaluated it on simulated and real HRV database. The proposed I-RMSE assigns higher entropy to the age-matched healthy subjects than that of patients suffering from atrial fibrillation, congestive heart failure, sudden cardiac death and diabetes mellitus, for the entire time scales. The results strongly support the reduction in complexity of HRV time series in female group, old-aged, patients suffering from severe cardiovascular and non-cardiovascular diseases, and in their corresponding surrogate time series.

Surrogate assisted multidisciplinary design optimization for an all-electric GEO satellite

NASA Astrophysics Data System (ADS)

Shi, Renhe; Liu, Li; Long, Teng; Liu, Jian; Yuan, Bin

2017-09-01

State-of-the-art all-electric geostationary earth orbit (GEO) satellites use electric thrusters to execute all propulsive duties, which significantly differ from the traditional all-chemical ones in orbit-raising, station-keeping, radiation damage protection, and power budget, etc. Design optimization task of an all-electric GEO satellite is therefore a complex multidisciplinary design optimization (MDO) problem involving unique design considerations. However, solving the all-electric GEO satellite MDO problem faces big challenges in disciplinary modeling techniques and efficient optimization strategy. To address these challenges, we presents a surrogate assisted MDO framework consisting of several modules, i.e., MDO problem definition, multidisciplinary modeling, multidisciplinary analysis (MDA), and surrogate assisted optimizer. Based on the proposed framework, the all-electric GEO satellite MDO problem is formulated to minimize the total mass of the satellite system under a number of practical constraints. Then considerable efforts are spent on multidisciplinary modeling involving geosynchronous transfer, GEO station-keeping, power, thermal control, attitude control, and structure disciplines. Since orbit dynamics models and finite element structural model are computationally expensive, an adaptive response surface surrogate based optimizer is incorporated in the proposed framework to solve the satellite MDO problem with moderate computational cost, where a response surface surrogate is gradually refined to represent the computationally expensive MDA process. After optimization, the total mass of the studied GEO satellite is decreased by 185.3 kg (i.e., 7.3% of the total mass). Finally, the optimal design is further discussed to demonstrate the effectiveness of our proposed framework to cope with the all-electric GEO satellite system design optimization problems. This proposed surrogate assisted MDO framework can also provide valuable references for other all-electric spacecraft system design.

Four-dimensional MRI using an internal respiratory surrogate derived by dimensionality reduction

NASA Astrophysics Data System (ADS)

Uh, Jinsoo; Ayaz Khan, M.; Hua, Chiaho

2016-11-01

This study aimed to develop a practical and accurate 4-dimensional (4D) magnetic resonance imaging (MRI) method using a non-navigator, image-based internal respiratory surrogate derived by dimensionality reduction (DR). The use of DR has been previously suggested but not implemented for reconstructing 4D MRI, despite its practical advantages. We compared multiple image-acquisition schemes and refined a retrospective-sorting process to optimally implement a DR-derived surrogate. The comparison included an unconventional scheme that acquires paired slices alternately to mitigate the internal surrogate’s dependency on a specific slice location. We introduced ‘target-oriented sorting’, as opposed to conventional binning, to quantify the coherence in retrospectively sorted images, thereby determining the minimal scan time needed for sufficient coherence. This study focused on evaluating the proposed method using digital phantoms which provided unequivocal gold standard. The evaluation indicated that the DR-based respiratory surrogate is highly accurate: the error in amplitude percentile of the surrogate signal was less than 5% with the optimal scheme. Acquiring alternating paired slices was superior to the conventional scheme of acquiring individual slices; the advantage of the unconventional scheme was more pronounced when a substantial phase shift occurred across slice locations. The analysis of coherence across sorted images confirmed the advantage of higher sampling efficiencies in non-navigator respiratory surrogates. We determined that a scan time of 20 s per imaging slice was sufficient to achieve a mean coherence error of less than 1% for the tested respiratory patterns. The clinical applicability of the proposed 4D MRI has been demonstrated with volunteers and patients. The diaphragm motion in 4D MRI was consistent with that in dynamic 2D imaging which was regarded as the gold standard (difference within 1.8 mm on average).

Racial Differences in Outcomes of an Advance Care Planning Intervention for Dialysis Patients and Their Surrogates.

PubMed

Song, Mi-Kyung; Ward, Sandra E; Lin, Feng-Chang; Hamilton, Jill B; Hanson, Laura C; Hladik, Gerald A; Fine, Jason P

2016-02-01

African Americans' beliefs about end-of-life care may differ from those of whites, but racial differences in advance care planning (ACP) outcomes are unknown. The aim of this study was to compare the efficacy of an ACP intervention on preparation for end-of-life decision making and post-bereavement outcomes for African Americans and whites on dialysis. A secondary analysis of data from a randomized trial comparing an ACP intervention (Sharing Patient's Illness Representations to Increase Trust [SPIRIT]) with usual care was conducted. There were 420 participants, 210 patient-surrogate dyads (67.4% African Americans), recruited from 20 dialysis centers in North Carolina. The outcomes of preparation for end-of-life decision making included dyad congruence on goals of care, surrogate decision-making confidence, a composite of the two, and patient decisional conflict assessed at 2, 6, and 12 months post-intervention. Surrogate bereavement outcomes included anxiety, depression, and post-traumatic distress symptoms assessed at 2 weeks, and at 3 and 6 months after the patient's death. SPIRIT was superior to usual care in improving dyad congruence (odds ration [OR] = 2.31, p = 0.018), surrogate decision-making confidence (β = 0.18, p = 0.021), and the composite (OR = 2.19, p = 0.028) 2 months post-intervention, but only for African Americans. SPIRIT reduced patient decisional conflict at 6 months for whites and at 12 months for African Americans. Finally, SPIRIT was superior to usual care in reducing surrogates' bereavement depressive symptoms for African Americans but not for whites (β = -3.49, p = 0.003). SPIRIT was effective in improving preparation for end-of-life decision-making and post-bereavement outcomes in African Americans.

Regression with Small Data Sets: A Case Study using Code Surrogates in Additive Manufacturing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamath, C.; Fan, Y. J.

There has been an increasing interest in recent years in the mining of massive data sets whose sizes are measured in terabytes. While it is easy to collect such large data sets in some application domains, there are others where collecting even a single data point can be very expensive, so the resulting data sets have only tens or hundreds of samples. For example, when complex computer simulations are used to understand a scientific phenomenon, we want to run the simulation for many different values of the input parameters and analyze the resulting output. The data set relating the simulationmore » inputs and outputs is typically quite small, especially when each run of the simulation is expensive. However, regression techniques can still be used on such data sets to build an inexpensive \\surrogate" that could provide an approximate output for a given set of inputs. A good surrogate can be very useful in sensitivity analysis, uncertainty analysis, and in designing experiments. In this paper, we compare different regression techniques to determine how well they predict melt-pool characteristics in the problem domain of additive manufacturing. Our analysis indicates that some of the commonly used regression methods do perform quite well even on small data sets.« less

Technical Note: Radiological properties of tissue surrogates used in a multimodality deformable pelvic phantom for MR-guided radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niebuhr, Nina I., E-mail: n.niebuhr@dkfz.de; Johnen, Wibke; Güldaglar, Timur

Purpose: Phantom surrogates were developed to allow multimodal [computed tomography (CT), magnetic resonance imaging (MRI), and teletherapy] and anthropomorphic tissue simulation as well as materials and methods to construct deformable organ shapes and anthropomorphic bone models. Methods: Agarose gels of variable concentrations and loadings were investigated to simulate various soft tissue types. Oils, fats, and Vaseline were investigated as surrogates for adipose tissue and bone marrow. Anthropomorphic shapes of bone and organs were realized using 3D-printing techniques based on segmentations of patient CT-scans. All materials were characterized in dual energy CT and MRI to adapt CT numbers, electron density, effectivemore » atomic number, as well as T1- and T2-relaxation times to patient and literature values. Results: Soft tissue simulation could be achieved with agarose gels in combination with a gadolinium-based contrast agent and NaF to simulate muscle, prostate, and tumor tissues. Vegetable oils were shown to be a good representation for adipose tissue in all modalities. Inner bone was realized using a mixture of Vaseline and K{sub 2}HPO{sub 4}, resulting in both a fatty bone marrow signal in MRI and inhomogeneous areas of low and high attenuation in CT. The high attenuation of outer bone was additionally adapted by applying gypsum bandages to the 3D-printed hollow bone case with values up to 1200 HU. Deformable hollow organs were manufactured using silicone. Signal loss in the MR images based on the conductivity of the gels needs to be further investigated. Conclusions: The presented surrogates and techniques allow the customized construction of multimodality, anthropomorphic, and deformable phantoms as exemplarily shown for a pelvic phantom, which is intended to study adaptive treatment scenarios in MR-guided radiation therapy.« less

Umbrellas can work under water: Using threatened species as indicator and management surrogates can improve coastal conservation

NASA Astrophysics Data System (ADS)

Gilby, Ben L.; Olds, Andrew D.; Connolly, Rod M.; Yabsley, Nicholas A.; Maxwell, Paul S.; Tibbetts, Ian R.; Schoeman, David S.; Schlacher, Thomas A.

2017-12-01

Species surrogates, the use of particular species to index habitat condition or to represent ecological assemblages are commonly identified in many ecosystems, but are less tested, and therefore less employed in estuaries. Estuaries provide important ecosystem goods (e.g. harvestable species) and services (e.g. carbon processing, coastal armouring), but require protection from multiple human activities, meaning that finding surrogates for estuarine condition or faunal assemblages is a significant knowledge gap. In this study, we test the efficacy of the threatened estuary ray Hemitrygon fluviorum, as a suitable indicator of ecosystem condition and management umbrella surrogate species for conservation prioritisation and monitoring purposes within estuaries. We surveyed fish assemblages and ray presence at ten sites within each of 22 estuaries in southeast Queensland, Australia, using one hour deployments of baited video arrays. We then tested for correlations between ray presence, a series of environmental variables considered important to ecosystem management within estuaries (i.e. testing rays as indicator species), and the co-occurring fish species (i.e. testing rays as umbrella species). Estuary rays function as both umbrella species and ecological indicators of habitat status in subtropical Australian estuaries. As umbrellas, ray occurrence concords with elevated species richness. As ecological indicators, ray distribution concords with habitats of good water quality (especially low turbidity) and more natural vegetation remaining in the catchment. These results highlight the potential for other threatened aquatic vertebrates that are both readily detectable and that are reliable proxies for ecosystems status to be become useful management tools in estuaries. The protection of such large, threatened species in coastal seascapes allows managers to address multiple targets for conservation, especially; (1) protecting species of conservation concern; (2) maintaining diversity; and (3) protecting optimal habitats by better placing reserves.

Technical Note: Radiological properties of tissue surrogates used in a multimodality deformable pelvic phantom for MR-guided radiotherapy.

PubMed

Niebuhr, Nina I; Johnen, Wibke; Güldaglar, Timur; Runz, Armin; Echner, Gernot; Mann, Philipp; Möhler, Christian; Pfaffenberger, Asja; Jäkel, Oliver; Greilich, Steffen

2016-02-01

Phantom surrogates were developed to allow multimodal [computed tomography (CT), magnetic resonance imaging (MRI), and teletherapy] and anthropomorphic tissue simulation as well as materials and methods to construct deformable organ shapes and anthropomorphic bone models. Agarose gels of variable concentrations and loadings were investigated to simulate various soft tissue types. Oils, fats, and Vaseline were investigated as surrogates for adipose tissue and bone marrow. Anthropomorphic shapes of bone and organs were realized using 3D-printing techniques based on segmentations of patient CT-scans. All materials were characterized in dual energy CT and MRI to adapt CT numbers, electron density, effective atomic number, as well as T1- and T2-relaxation times to patient and literature values. Soft tissue simulation could be achieved with agarose gels in combination with a gadolinium-based contrast agent and NaF to simulate muscle, prostate, and tumor tissues. Vegetable oils were shown to be a good representation for adipose tissue in all modalities. Inner bone was realized using a mixture of Vaseline and K2HPO4, resulting in both a fatty bone marrow signal in MRI and inhomogeneous areas of low and high attenuation in CT. The high attenuation of outer bone was additionally adapted by applying gypsum bandages to the 3D-printed hollow bone case with values up to 1200 HU. Deformable hollow organs were manufactured using silicone. Signal loss in the MR images based on the conductivity of the gels needs to be further investigated. The presented surrogates and techniques allow the customized construction of multimodality, anthropomorphic, and deformable phantoms as exemplarily shown for a pelvic phantom, which is intended to study adaptive treatment scenarios in MR-guided radiation therapy.

A Surrogate Approach to the Experimental Optimization of Multielement Airfoils

NASA Technical Reports Server (NTRS)

Otto, John C.; Landman, Drew; Patera, Anthony T.

1996-01-01

The incorporation of experimental test data into the optimization process is accomplished through the use of Bayesian-validated surrogates. In the surrogate approach, a surrogate for the experiment (e.g., a response surface) serves in the optimization process. The validation step of the framework provides a qualitative assessment of the surrogate quality, and bounds the surrogate-for-experiment error on designs "near" surrogate-predicted optimal designs. The utility of the framework is demonstrated through its application to the experimental selection of the trailing edge ap position to achieve a design lift coefficient for a three-element airfoil.

The psychological well-being and prenatal bonding of gestational surrogates.

PubMed

Lamba, N; Jadva, V; Kadam, K; Golombok, S

2018-02-23

How does the psychological well-being and prenatal bonding of Indian surrogates differ from a comparison group of mothers? Surrogates had higher levels of depression during pregnancy and post-birth, displayed lower emotional connection with the unborn baby, and greater care towards the healthy growth of the foetus, than the comparison group of mothers. Studies in the West have found that surrogates do not suffer long-term psychological harm. One study has shown that surrogates bond less with the foetus than expectant mothers. This study uses a prospective, longitudinal and cross-sectional design. Surrogates and a matched group of expectant mothers were seen twice, during 4-9 months of pregnancy and 4-6 months after the birth. Semi-structured interviews and standardized questionnaires were administered to 50 surrogates and 69 expectant mothers during pregnancy and 45 surrogates and 49 expectant mothers post-birth. All gestational surrogates were hosting pregnancies for international intended parents. Surrogates had higher levels of depression compared to the comparison group of mothers, during pregnancy and post-birth (P < 0.02). Low social support during pregnancy, hiding surrogacy and criticism from others were found to be predictive of higher depression in surrogates post-birth (P < 0.05). Regarding prenatal bonding, surrogates interacted less with and thought less about the foetus but adopted better eating habits and were more likely to avoid unhealthy practices during pregnancy, than expectant mothers (P < 0.05). No associations were found between greater prenatal bonding and greater psychological distress during pregnancy or after relinquishment. All surrogates were recruited from one clinic in Mumbai, and thus the representativeness of this sample is not known. Also, the possibility of socially desirable responding from surrogates cannot be ruled out. As this is the first study of the psychological well-being of surrogates in low-income countries, the findings have important policy implications. Providing support and counselling to surrogates, especially during pregnancy, may alleviate some of the psychological problems faced by surrogates. This study was supported by the Wellcome Trust [097857/Z/11/Z] and Nehru Trust, Cambridge. K.K. is the Medical Director of Corion Fertility Clinic. All other authors have no conflict of interest to declare.

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

NASA Technical Reports Server (NTRS)

Zwack, Mathew R.; Dees, Patrick D.; Holt, James B.

2016-01-01

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases [1]. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission [2]. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions.

Documenting the Regional and local distribution of Kalmia latifolia and Rosa multiflora in West Virginia, Ohio, and Pennsylvania Forests along a soil fertility gradient

Treesearch

Cynthia D. Huebner; Todd Hutchinson; Todd Ristau; Alejandro Royo; James Steinman

2012-01-01

Use of environmental variables as predictors of vegetation distribution patterns has long been a focus of ecology. However, the effect of edaphic factors on vegetation pattern is often measured using surrogates such as topography, because accurate measures of soil fertility and nutrients are unavailable or rare (Marage and Gégout 2009). Kalmia latifolia...

Health Risk Assessments of Waste Combustion Emissions Using Surrogate Analyte Models

DTIC Science & Technology

2013-03-01

pulmonary disease (Abraham et al., 2012; Rose et al., 2012). Among burn pit emissions, PM with diameter ≤ 2.5 µm (PM2.5) has been correlated with...various health effects, such as myocardial infarctions, pulmonary inflammation, and cancer (Polichetti et al., 2009; Pope et al., 2002). An...infarction, atherosclerosis, heart rate variability, and pulmonary inflammation (Polichetti et al., 2009; Avakian et al., 2002). Further, ultrafine

Optimization on the impeller of a low-specific-speed centrifugal pump for hydraulic performance improvement

NASA Astrophysics Data System (ADS)

Pei, Ji; Wang, Wenjie; Yuan, Shouqi; Zhang, Jinfeng

2016-09-01

In order to widen the high-efficiency operating range of a low-specific-speed centrifugal pump, an optimization process for considering efficiencies under 1.0 Q d and 1.4 Q d is proposed. Three parameters, namely, the blade outlet width b 2, blade outlet angle β 2, and blade wrap angle φ, are selected as design variables. Impellers are generated using the optimal Latin hypercube sampling method. The pump efficiencies are calculated using the software CFX 14.5 at two operating points selected as objectives. Surrogate models are also constructed to analyze the relationship between the objectives and the design variables. Finally, the particle swarm optimization algorithm is applied to calculate the surrogate model to determine the best combination of the impeller parameters. The results show that the performance curve predicted by numerical simulation has a good agreement with the experimental results. Compared with the efficiencies of the original impeller, the hydraulic efficiencies of the optimized impeller are increased by 4.18% and 0.62% under 1.0 Q d and 1.4Qd, respectively. The comparison of inner flow between the original pump and optimized one illustrates the improvement of performance. The optimization process can provide a useful reference on performance improvement of other pumps, even on reduction of pressure fluctuations.

Effect of particulate air pollution and passive smoking on surrogate biomarkers of endothelial dysfunction in healthy children.

PubMed

Kelishadi, Roya; Hashemi, Mohammad; Javanmard, Shaghayegh Haghjooy; Mansourian, Marjan; Afshani, Mohammadreza; Poursafa, Parinaz; Sadeghian, Babak; Fakhri, Maryam

2014-08-01

This study aimed to determine the association of ambient particulate matter (PM) on surrogate markers of endothelial function and inflammation in healthy children with or without exposure to second-hand smoke. This cross-sectional study was conducted in 2011 in Isfahan, which is the second largest and second most air-polluted city in Iran. The areas of the city with lowest and highest air pollution were determined, and in each area, 25 pre-pubescent boys with or without exposure to daily tobacco smoke at home were selected, i.e. 100 children were studied in total. Serum levels of C-reactive protein (CRP) and nitric oxide (NO) were measured. Mean (SD) NO concentration was 7·87 (2·18) and 7·75 (2·04) μmol/L for participants not exposed and exposed to passive smoking, respectively, which is not statistically significant. The corresponding figures for CRP concentrations were 1·69 (0·89) and 2·13 (1·19) μg/ml (P = 0·04). Mean (SD) CRP concentration was significantly higher in children living in the highly polluted area than in those in the area of low pollution [2·11 (1·91) vs 1·60 (1·43) μg/ml, respectively, P = 0·02]. This difference was not significant for NO concentration. The regression analysis that examined the association between PM concentration (as independent variable) and CRP and NO levels (as dependent variables) in children not exposed to passive smoking demonstrated that increased PM was associated with a decrease in NO and an increase in CRP concentration. This finding shows that, regardless of passive smoking, PM10 concentration has a significant independent association with serum CRP and is inversely associated with NO levels. The findings suggest that in healthy children PM concentration has a significant independent association with biomarkers of endothelial dysfunction and inflammation.

Optimization and uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality

NASA Astrophysics Data System (ADS)

Keating, Elizabeth H.; Doherty, John; Vrugt, Jasper A.; Kang, Qinjun

2010-10-01

Highly parameterized and CPU-intensive groundwater models are increasingly being used to understand and predict flow and transport through aquifers. Despite their frequent use, these models pose significant challenges for parameter estimation and predictive uncertainty analysis algorithms, particularly global methods which usually require very large numbers of forward runs. Here we present a general methodology for parameter estimation and uncertainty analysis that can be utilized in these situations. Our proposed method includes extraction of a surrogate model that mimics key characteristics of a full process model, followed by testing and implementation of a pragmatic uncertainty analysis technique, called null-space Monte Carlo (NSMC), that merges the strengths of gradient-based search and parameter dimensionality reduction. As part of the surrogate model analysis, the results of NSMC are compared with a formal Bayesian approach using the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. Such a comparison has never been accomplished before, especially in the context of high parameter dimensionality. Despite the highly nonlinear nature of the inverse problem, the existence of multiple local minima, and the relatively large parameter dimensionality, both methods performed well and results compare favorably with each other. Experiences gained from the surrogate model analysis are then transferred to calibrate the full highly parameterized and CPU intensive groundwater model and to explore predictive uncertainty of predictions made by that model. The methodology presented here is generally applicable to any highly parameterized and CPU-intensive environmental model, where efficient methods such as NSMC provide the only practical means for conducting predictive uncertainty analysis.

Surrogacy of progression-free survival (PFS) for overall survival (OS) in esophageal cancer trials with preoperative therapy: Literature-based meta-analysis.

PubMed

Kataoka, K; Nakamura, K; Mizusawa, J; Kato, K; Eba, J; Katayama, H; Shibata, T; Fukuda, H

2017-10-01

There have been no reports evaluating progression-free survival (PFS) as a surrogate endpoint in resectable esophageal cancer. This study was conducted to evaluate the trial level correlations between PFS and overall survival (OS) in resectable esophageal cancer with preoperative therapy and to explore the potential benefit of PFS as a surrogate endpoint for OS. A systematic literature search of randomized trials with preoperative chemotherapy or preoperative chemoradiotherapy for esophageal cancer reported from January 1990 to September 2014 was conducted using PubMed and the Cochrane Library. Weighted linear regression using sample size of each trial as a weight was used to estimate coefficient of determination (R 2 ) within PFS and OS. The primary analysis included trials in which the HR for both PFS and OS was reported. The sensitivity analysis included trials in which either HR or median survival time of PFS and OS was reported. In the sensitivity analysis, HR was estimated from the median survival time of PFS and OS, assuming exponential distribution. Of 614 articles, 10 trials were selected for the primary analysis and 15 for the sensitivity analysis. The primary analysis did not show a correlation between treatment effects on PFS and OS (R 2 0.283, 95% CI [0.00-0.90]). The sensitivity analysis did not show an association between PFS and OS (R 2 0.084, 95% CI [0.00-0.70]). Although the number of randomized controlled trials evaluating preoperative therapy for esophageal cancer is limited at the moment, PFS is not suitable for primary endpoint as a surrogate endpoint for OS. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Time-varying spectral analysis for comparison of HRV and PPG variability during tilt table test.

PubMed

Gil, Eduardo; Orini, Michele; Bailon, Raquel; Vergara, Jose Maria; Mainardi, Luca; Laguna, Pablo

2010-01-01

In this work we assessed the possibility of using the pulse rate variability (PRV) extracted from photoplethysmography signal as an alternative measurement of the HRV signal in non-stationary conditions. The study is based on the analysis of the changes observed during tilt table test in the heart rate modulation of 17 young subjects. Time-varying spectral properties of both signals were compared by time-frequency (TF) and TF coherence analysis. In addition, the effect of replacing PRV with HRV in the assessment of the changes of the autonomic modulation of the heart rate was considered. Time-frequency analysis revealed that: the TF spectra of both signals were highly correlated (0.99 ± 0.01); the difference between the instantaneous power, in LF and HF bands, obtained from HRV and PRV was small (, 10(-3) s(-2)) and their temporal patterns were highly correlated (0.98 ± 0.04 and 0.95 ± 0.06 in LF and HF bands respectively); TF coherence in LF and HF bands was high (0.97 ± 0.04 and 0.89 ± 0.08, respectively). Finally, the instantaneous power in LF band was observed to significantly increase during head-up tilt by both HRV and PRV analysis. These results suggest that, although some small differences in the time-varying spectral indices extracted from HRV and PRV exist, mainly in the HF band associated with respiration, PRV could be used as an acceptable surrogate of HRV during non-stationary conditions, at least during tilt table test.

Skeletal Mechanism Generation of Surrogate Jet Fuels for Aeropropulsion Modeling

NASA Astrophysics Data System (ADS)

Sung, Chih-Jen; Niemeyer, Kyle E.

2010-05-01

A novel implementation for the skeletal reduction of large detailed reaction mechanisms using the directed relation graph with error propagation and sensitivity analysis (DRGEPSA) is developed and presented with skeletal reductions of two important hydrocarbon components, n-heptane and n-decane, relevant to surrogate jet fuel development. DRGEPSA integrates two previously developed methods, directed relation graph-aided sensitivity analysis (DRGASA) and directed relation graph with error propagation (DRGEP), by first applying DRGEP to efficiently remove many unimportant species prior to sensitivity analysis to further remove unimportant species, producing an optimally small skeletal mechanism for a given error limit. It is illustrated that the combination of the DRGEP and DRGASA methods allows the DRGEPSA approach to overcome the weaknesses of each previous method, specifically that DRGEP cannot identify all unimportant species and that DRGASA shields unimportant species from removal.

Occupant kinematics of the Hybrid III, THOR-M, and postmortem human surrogates under various restraint conditions in full-scale frontal sled tests.

PubMed

Albert, Devon L; Beeman, Stephanie M; Kemper, Andrew R

2018-02-28

The objective of this research was to compare the occupant kinematics of the Hybrid III (HIII), THOR-M, and postmortem human surrogates (PMHS) during full-scale frontal sled tests under 3 safety restraint conditions: knee bolster (KB), knee bolster and steering wheel airbag (KB/SWAB), and knee bolster airbag and steering wheel airbag (KBAB/SWAB). A total of 20 frontal sled tests were performed with at least 2 tests performed per restraint condition per surrogate. The tests were designed to match the 2012 Toyota Camry New Car Assessment Program (NCAP) full-scale crash test. Rigid polyurethane foam surrogates with compressive strength ratings of 65 and 19 psi were used to simulate the KB and KBAB, respectively. The excursions of the head, shoulders, hips, knees, and ankles were collected using motion capture. Linear acceleration and angular velocity data were also collected from the head, thorax, and pelvis of each surrogate. Time histories were compared between surrogates and restraint conditions using ISO/TS 18571. All surrogates showed some degree of sensitivity to changes in restraint condition. For example, the use of a KBAB decreased the pelvis accelerations and the forward excursions of the knees and hips for all surrogates. However, these trends were not observed for the thorax, shoulders, and head, which showed more sensitivity to the presence of a SWAB. The average scores computed using ISO/TS 18571 for the HIII/PMHS and THOR-M/PMHS comparisons were 0.527 and 0.518, respectively. The HIII had slightly higher scores than the THOR-M for the excursions (HIII average = 0.574; THOR average = 0.520). However, the THOR-M had slightly higher scores for the accelerations and angular rates (HIII average = 0.471; THOR average = 0.516). The data from the current study showed that both KBABs and SWABs affected the kinematics of all surrogates during frontal sled tests. The results of the objective rating analysis indicated that the HIII and THOR-M had comparable overall biofidelity scores. The THOR-M slightly outperformed the HIII for the acceleration and angular velocity data. However, the HIII scored slightly better than the THOR-M for the excursion data. The most notable difference in biofidelity was for the knee excursions, where the HIII had a much higher average ISO score. Only the biofidelity of the HIII and THOR-M with regard to occupant kinematics was evaluated in this study; therefore, future work will evaluate the biofidelity of the ATDs in terms of lower extremity loading, thoracic response, and neck loading.

Will higher traffic flow lead to more traffic conflicts? A crash surrogate metric based analysis

PubMed Central

Kuang, Yan; Yan, Yadan

2017-01-01

In this paper, we aim to examine the relationship between traffic flow and potential conflict risks by using crash surrogate metrics. It has been widely recognized that one traffic flow corresponds to two distinct traffic states with different speeds and densities. In view of this, instead of simply aggregating traffic conditions with the same traffic volume, we represent potential conflict risks at a traffic flow fundamental diagram. Two crash surrogate metrics, namely, Aggregated Crash Index and Time to Collision, are used in this study to represent the potential conflict risks with respect to different traffic conditions. Furthermore, Beijing North Ring III and Next Generation SIMulation Interstate 80 datasets are utilized to carry out case studies. By using the proposed procedure, both datasets generate similar trends, which demonstrate the applicability of the proposed methodology and the transferability of our conclusions. PMID:28787022

Overview of selected surrogate technologies for high-temporal resolution suspended-sediment monitoring

USGS Publications Warehouse

Gray, John R.; Gartner, Jeffrey W.

2010-01-01

Traditional methods for characterizing selected properties of suspended sediments in rivers are being augmented and in some cases replaced by cost-effective surrogate instruments and methods that produce a temporally dense time series of quantifiably accurate data for use primarily in sediment-flux computations. Turbidity is the most common such surrogate technology, and the first to be sanctioned by the U.S. Geological Survey for use in producing data used in concert with water-discharge data to compute sediment concentrations and fluxes for storage in the National Water Information System. Other technologies, including laser-diffraction, digital photo-optic, acoustic-attenuation and backscatter, and pressure-difference techniques are being evaluated for producing reliable sediment concentration and, in some cases, particle-size distribution data. Each technology addresses a niche for sediment monitoring. Their performances range from compelling to disappointing. Some of these technologies have the potential to revolutionize fluvial-sediment data collection, analysis, and availability.

Will higher traffic flow lead to more traffic conflicts? A crash surrogate metric based analysis.

PubMed

Kuang, Yan; Qu, Xiaobo; Yan, Yadan

2017-01-01

In this paper, we aim to examine the relationship between traffic flow and potential conflict risks by using crash surrogate metrics. It has been widely recognized that one traffic flow corresponds to two distinct traffic states with different speeds and densities. In view of this, instead of simply aggregating traffic conditions with the same traffic volume, we represent potential conflict risks at a traffic flow fundamental diagram. Two crash surrogate metrics, namely, Aggregated Crash Index and Time to Collision, are used in this study to represent the potential conflict risks with respect to different traffic conditions. Furthermore, Beijing North Ring III and Next Generation SIMulation Interstate 80 datasets are utilized to carry out case studies. By using the proposed procedure, both datasets generate similar trends, which demonstrate the applicability of the proposed methodology and the transferability of our conclusions.

A rank test for bivariate time-to-event outcomes when one event is a surrogate

PubMed Central

Shaw, Pamela A.; Fay, Michael P.

2016-01-01

In many clinical settings, improving patient survival is of interest but a practical surrogate, such as time to disease progression, is instead used as a clinical trial’s primary endpoint. A time-to-first endpoint (e.g. death or disease progression) is commonly analyzed but may not be adequate to summarize patient outcomes if a subsequent event contains important additional information. We consider a surrogate outcome very generally, as one correlated with the true endpoint of interest. Settings of interest include those where the surrogate indicates a beneficial outcome so that the usual time-to-first endpoint of death or surrogate event is nonsensical. We present a new two-sample test for bivariate, interval-censored time-to-event data, where one endpoint is a surrogate for the second, less frequently observed endpoint of true interest. This test examines whether patient groups have equal clinical severity. If the true endpoint rarely occurs, the proposed test acts like a weighted logrank test on the surrogate; if it occurs for most individuals, then our test acts like a weighted logrank test on the true endpoint. If the surrogate is a useful statistical surrogate, our test can have better power than tests based on the surrogate that naively handle the true endpoint. In settings where the surrogate is not valid (treatment affects the surrogate but not the true endpoint), our test incorporates the information regarding the lack of treatment effect from the observed true endpoints and hence is expected to have a dampened treatment effect compared to tests based on the surrogate alone. PMID:27059817

Surrogate outcomes in health technology assessment: an international comparison.

PubMed

Velasco Garrido, Marcial; Mangiapane, Sandra

2009-07-01

Our aim was to review the recommendations given by health technology assessment (HTA) institutions in their methodological guidelines concerning the use of surrogate outcomes in their assessments. In a second step, we aimed at quantifying the role surrogate parameters take in assessment reports. We analyzed methodological papers and guidelines from HTA agencies with International Network of Agencies for Health Technology Assessment membership as well as from institutions related to pharmaceutical regulation (i.e., reimbursement, pricing). We analyzed the use of surrogate outcomes in a sample of HTA reports randomly drawn from the HTA database. We checked methods, results (including evidence tables), and conclusions sections and extracted the outcomes reported. We report descriptive statistics on the presence of surrogate outcomes in the reports. We identified thirty-four methodological guidelines, twenty of them addressing the issue of outcome parameter choice and the problematic of surrogate outcomes. Overall HTA agencies call on caution regarding the reliance on surrogate outcomes. None of the agencies has provided a list or catalog of acceptable and validated surrogate outcomes. We extracted the outcome parameter of 140 HTA reports. Only around half of the reports determined the outcomes for the assessment prospectively. Surrogate outcomes had been used in 62 percent of the reports. However, only 3.6 percent were based upon surrogate outcomes exclusively. All of them assessed diagnostic or screening technologies and the surrogate outcomes were predominantly test characteristics. HTA institutions seem to agree on a cautious approach to the use of surrogate outcomes in technology assessment. Thorough assessment of health technologies should not rely exclusively on surrogate outcomes.

Advanced topics in evidence-based urologic oncology: surrogate endpoints.

PubMed

Lavallée, Luke T; Montori, Victor M; Canfield, Stephen E; Breau, Rodney H

2011-01-01

Clinical trials often report surrogate endpoint data. A surrogate endpoint is a biological marker or clinical sign that can be substituted for a patient-important outcome. Using surrogate endpoints correctly may facilitate and expedite clinical trials and may improve medical decisions. However, rigorous criteria must be met for an endpoint to be considered a valid surrogate. The purpose of this article is to review the topic of surrogate endpoints in the context of a urologic encounter. Copyright © 2011 Elsevier Inc. All rights reserved.

Effects of urbanization on benthic macroinvertebrate communities in streams, Anchorage, Alaska

USGS Publications Warehouse

Ourso, Robert T.

2001-01-01

The effect of urbanization on stream macroinvertebrate communities was examined by using data gathered during a 1999 reconnaissance of 14 sites in the Municipality of Anchorage, Alaska. Data collected included macroinvertebrate abundance, water chemistry, and trace elements in bed sediments. Macroinvertebrate relative-abundance data were edited and used in metric and index calculations. Population density was used as a surrogate for urbanization. Cluster analysis (unweighted-paired-grouping method) using arithmetic means of macroinvertebrate presence-absence data showed a well-defined separation between urbanized and nonurbanized sites as well as extracted sites that did not cleanly fall into either category. Water quality in Anchorage generally declined with increasing urbanization (population density). Of 59 variables examined, 31 correlated with urbanization. Local regression analysis extracted 11 variables that showed a significant impairment threshold response and 6 that showed a significant linear response. Significant biological variables for determining the impairment threshold in this study were the Margalef diversity index, Ephemeroptera-Plecoptera-Trichoptera taxa richness, and total taxa richness. Significant thresholds were observed in the water-chemistry variables conductivity, dissolved organic carbon, potassium, and total dissolved solids. Significant thresholds in trace elements in bed sediments included arsenic, iron, manganese, and lead. Results suggest that sites in Anchorage that have ratios of population density to road density greater than 70, storm-drain densities greater than 0.45 miles per square mile, road densities greater than 4 miles per square mile, or population densities greater than 125-150 persons per square mile may require further monitoring to determine if the stream has become impaired. This population density is far less than the 1,000 persons per square mile used by the U.S. Census Bureau to define an urban area.

Mass diffusion coefficient measurement for vitreous humor using FEM and MRI

NASA Astrophysics Data System (ADS)

Rattanakijsuntorn, Komsan; Penkova, Anita; Sadha, Satwindar S.

2018-01-01

In early studies, the ‘contour method’ for determining the diffusion coefficient of the vitreous humor was developed. This technique relied on careful injection of an MRI contrast agent (surrogate drug) into the vitreous humor of fresh bovine eyes, and tracking the contours of the contrast agent in time. In addition, an analytical solution was developed for the theoretical contours built on point source model for the injected surrogate drug. The match between theoretical and experimental contours as a least square fit, while floating the diffusion coefficient, led to the value of the diffusion coefficient. This method had its limitation that the initial injection of the surrogate had to be spherical or ellipsoidal because of the analytical result based on the point-source model. With a new finite element model for the analysis in this study, the technique is much less restrictive and handles irregular shapes of the initial bolus. The fresh bovine eyes were used for drug diffusion study in the vitreous and three contrast agents of different molecular masses: gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA, 938 Da), non-ionic gadoteridol (Prohance, 559 Da), and bovine albumin conjugated with gadolinium (Galbumin, 74 kDa) were used as drug surrogates to visualize the diffusion process by MRI. The 3D finite element model was developed to determine the diffusion coefficients of these surrogates with the images from MRI. This method can be used for other types of bioporous media provided the concentration profile can be visualized (by methods such as MRI or fluorescence).

Audiovisual biofeedback improves the correlation between internal/external surrogate motion and lung tumor motion.

PubMed

Lee, Danny; Greer, Peter B; Paganelli, Chiara; Ludbrook, Joanna Jane; Kim, Taeho; Keall, Paul

2018-03-01

Breathing management can reduce breath-to-breath (intrafraction) and day-by-day (interfraction) variability in breathing motion while utilizing the respiratory motion of internal and external surrogates for respiratory guidance. Audiovisual (AV) biofeedback, an interactive personalized breathing motion management system, has been developed to improve reproducibility of intra- and interfraction breathing motion. However, the assumption of the correlation of respiratory motion between surrogates and tumors is not always verified during medical imaging and radiation treatment. Therefore, the aim of the study was to test the hypothesis that the correlation of respiratory motion between surrogates and tumors is the same under free breathing without guidance (FB) and with AV biofeedback guidance for voluntary motion management. For 13 lung cancer patients receiving radiotherapy, 2D coronal and sagittal cine-MR images were acquired across two MRI sessions (pre- and mid-treatment) with two breathing conditions: (a) FB and (b) AV biofeedback, totaling 88 patient measurements. Simultaneously, the external respiratory motion of the abdomen was measured. The internal respiratory motion of the diaphragm and lung tumor was retrospectively measured from 2D coronal and sagittal cine-MR images. The correlation of respiratory motion between surrogates and tumors was calculated using Pearson's correlation coefficient for: (a) abdomen to tumor (abdomen-tumor) and (b) diaphragm to tumor (diaphragm-tumor). The correlations were compared between FB and AV biofeedback using several metrics: abdomen-tumor and diaphragm-tumor correlations with/without ≥5 mm tumor motion range and with/without adjusting for phase shifts between the signals. Compared to FB, AV biofeedback improved abdomen-tumor correlation by 11% (p = 0.12) from 0.53 to 0.59 and diaphragm-tumor correlation by 13% (p = 0.02) from 0.55 to 0.62. Compared to FB, AV biofeedback improved abdomen-tumor correlation by 17% (p = 0.01) and diaphragm-tumor correlation by 15% (p < 0.01) while correcting 0.3 s (p = 0.54) and 0.2 s (p = 0.19) phase shifts, respectively. In addition, AV biofeedback with ≥5 mm tumor motion range, compared to FB improved abdomen-tumor correlation by 14% (p = 0.18) and diaphragm-tumor correlation by 17% (p = 0.01). The highest abdomen-tumor and diaphragm-tumor correlations were found using ≥5 mm tumor motion range and phase shifts, resulting in a 12% improvement in AV biofeedback. Our results demonstrated that AV biofeedback improves the correlation of respiratory motion between surrogates and the tumor. This suggests a need for AV biofeedback for respiratory guidance utilizing respiratory surrogates during image-guided and MRI-guided radiotherapy in thoracic regions. © 2018 American Association of Physicists in Medicine.

Perioperative Near-Infrared Spectroscopy Monitoring in Neonates With Congenital Heart Disease: Relationship of Cerebral Tissue Oxygenation Index Variability With Neurodevelopmental Outcome.

PubMed

Spaeder, Michael C; Klugman, Darren; Skurow-Todd, Kami; Glass, Penny; Jonas, Richard A; Donofrio, Mary T

2017-03-01

To evaluate the value of perioperative cerebral near-infrared spectroscopy monitoring using variability analysis in the prediction of neurodevelopmental outcomes in neonates undergoing surgery for congenital heart disease. Retrospective cohort study. Urban, academic, tertiary-care children's hospital. Neonates undergoing surgery with cardiopulmonary bypass for congenital heart disease. Perioperative monitoring of continuous cerebral tissue oxygenation index by near-infrared spectroscopy and subsequent neurodevelopmental testing at 6, 15, and 21 months of age. We developed a new measure, cerebral tissue oxygenation index variability, using the root mean of successive squared differences of averaged 1-minute cerebral tissue oxygenation index values for both the intraoperative and first 24-hours postoperative phases of monitoring. There were 62 neonates who underwent cerebral tissue oxygenation index monitoring during surgery for congenital heart disease and 44 underwent subsequent neurodevelopmental testing (12 did not survive until testing and six were lost to follow-up). Among the 44 monitored patients who underwent neurodevelopmental testing, 20 (45%) had abnormal neurodevelopmental indices. Patients with abnormal neurodevelopmental indices had lower postoperative cerebral tissue oxygenation index variability when compared with patients with normal indices (p = 0.01). Adjusting for class of congenital heart disease and duration of deep hypothermic circulatory arrest, lower postoperative cerebral tissue oxygenation index variability was associated with poor neurodevelopmental outcome (p = 0.02). We found reduced postoperative cerebral tissue oxygenation index variability in neonatal survivors of congenital heart disease surgery with poor neurodevelopmental outcomes. We hypothesize that reduced cerebral tissue oxygenation index variability may be a surrogate for impaired cerebral metabolic autoregulation in the immediate postoperative period. Further research is needed to investigate clinical implications of this finding and opportunities for using this measure to drive therapeutic interventions.

Nonspinning numerical relativity waveform surrogates: assessing the model

NASA Astrophysics Data System (ADS)

Field, Scott; Blackman, Jonathan; Galley, Chad; Scheel, Mark; Szilagyi, Bela; Tiglio, Manuel

2015-04-01

Recently, multi-modal gravitational waveform surrogate models have been built directly from data numerically generated by the Spectral Einstein Code (SpEC). I will describe ways in which the surrogate model error can be quantified. This task, in turn, requires (i) characterizing differences between waveforms computed by SpEC with those predicted by the surrogate model and (ii) estimating errors associated with the SpEC waveforms from which the surrogate is built. Both pieces can have numerous sources of numerical and systematic errors. We make an attempt to study the most dominant error sources and, ultimately, the surrogate model's fidelity. These investigations yield information about the surrogate model's uncertainty as a function of time (or frequency) and parameter, and could be useful in parameter estimation studies which seek to incorporate model error. Finally, I will conclude by comparing the numerical relativity surrogate model to other inspiral-merger-ringdown models. A companion talk will cover the building of multi-modal surrogate models.

Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations?

NASA Astrophysics Data System (ADS)

Lerma, Claudia; Echeverría, Juan C.; Infante, Oscar; Pérez-Grovas, Héctor; González-Gómez, Hortensia

2017-09-01

The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α1) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α1sign) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α1 and α1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α1magn) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α1magn > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α1 and α1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.

Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations?

PubMed

Lerma, Claudia; Echeverría, Juan C; Infante, Oscar; Pérez-Grovas, Héctor; González-Gómez, Hortensia

2017-09-01

The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α 1 ) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α 1sign ) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α 1 and α 1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α 1magn ) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α 1magn  > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α 1 and α 1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.

Surrogate endpoints and emerging surrogate endpoints for risk reduction of cardiovascular disease.

PubMed

Rasnake, Crystal M; Trumbo, Paula R; Heinonen, Therese M

2008-02-01

This article reviews surrogate endpoints and emerging biomarkers that were discussed at the annual "Cardiovascular Biomarkers and Surrogate Endpoints" symposium cosponsored by the US Food and Drug Administration (FDA) and the Montreal Heart Institute. The FDA's Center for Food Safety and Applied Nutrition (CFSAN) uses surrogate endpoints in its scientific review of a substance/disease relationship for a health claim. CFSAN currently recognizes three validated surrogate endpoints: blood pressure, blood total cholesterol, and blood low-density lipoprotein (LDL) concentration in its review of a health claim for cardiovascular disease (CVD). Numerous potential surrogate endpoints of CVD are being evaluated as the pathophysiology of heart disease is becoming better understood. However, these emerging biomarkers need to be validated as surrogate endpoints before they are used by CFSAN in the evaluation of a CVD health claim.

Surrogate end points in clinical research: hazardous to your health.

PubMed

Grimes, David A; Schulz, Kenneth F

2005-05-01

Surrogate end points in clinical research pose real danger. A surrogate end point is an outcome measure, commonly a laboratory test, that substitutes for a clinical event of true importance. Resistance to activated protein C, for example, has been used as a surrogate for venous thrombosis in women using oral contraceptives. Other examples of inappropriate surrogate end points in contraception include the postcoital test instead of pregnancy to evaluate new spermicides, breakage and slippage instead of pregnancy to evaluate condoms, and bone mineral density instead of fracture to assess the safety of depo-medroxyprogesterone acetate. None of these markers captures the effect of the treatment on the true outcome. A valid surrogate end point must both correlate with and accurately predict the outcome of interest. Although many surrogate markers correlate with an outcome, few have been shown to capture the effect of a treatment (for example, oral contraceptives) on the outcome (venous thrombosis). As a result, thousands of useless and misleading reports on surrogate end points litter the medical literature. New drugs have been shown to benefit a surrogate marker, but, paradoxically, triple the risk of death. Thousands of patients have died needlessly because of reliance on invalid surrogate markers. Researchers should avoid surrogate end points unless they have been validated; that requires at least one well done trial using both the surrogate and true outcome. The clinical maxim that "a difference to be a difference must make a difference" applies to research as well. Clinical research should focus on outcomes that matter.

Quality-control results for ground-water and surface-water data, Sacramento River Basin, California, National Water-Quality Assessment, 1996-1998

USGS Publications Warehouse

Munday, Cathy; Domagalski, Joseph L.

2003-01-01

Evaluating the extent that bias and variability affect the interpretation of ground- and surface-water data is necessary to meet the objectives of the National Water-Quality Assessment (NAWQA) Program. Quality-control samples used to evaluate the bias and variability include annual equipment blanks, field blanks, field matrix spikes, surrogates, and replicates. This report contains quality-control results for the constituents critical to the ground- and surface-water components of the Sacramento River Basin study unit of the NAWQA Program. A critical constituent is one that was detected frequently (more than 50 percent of the time in blank samples), was detected at amounts exceeding water-quality standards or goals, or was important for the interpretation of water-quality data. Quality-control samples were collected along with ground- and surface-water samples during the high intensity phase (cycle 1) of the Sacramento River Basin NAWQA beginning early in 1996 and ending in 1998. Ground-water field blanks indicated contamination of varying levels of significance when compared with concentrations detected in environmental ground-water samples for ammonia, dissolved organic carbon, aluminum, and copper. Concentrations of aluminum in surface-water field blanks were significant when compared with environmental samples. Field blank samples collected for pesticide and volatile organic compound analyses revealed no contamination in either ground- or surface-water samples that would effect the interpretation of environmental data, with the possible exception of the volatile organic compound trichloromethane (chloroform) in ground water. Replicate samples for ground water and surface water indicate that variability resulting from sample collection, processing, and analysis was generally low. Some of the larger maximum relative percentage differences calculated for replicate samples occurred between samples having lowest absolute concentration differences and(or) values near the reporting limit. Surrogate recoveries for pesticides analyzed by gas chromatography/mass spectrometry (GC/MS), pesticides analyzed by high performance liquid chromatography (HPLC), and volatile organic compounds in ground- and surface-water samples were within the acceptable limits of 70 to 130 percent and median recovery values between 82 and 113 percent. The recovery percentages for surrogate compounds analyzed by HPLC had the highest standard deviation, 20 percent for ground-water samples and 16 percent for surface-water samples, and the lowest median values, 82 percent for ground-water samples and 91 percent for surface-water samples. Results were consistent with the recovery results described for the analytical methods. Field matrix spike recoveries for pesticide compounds analyzed using GC/MS in ground- and surface-water samples were comparable with published recovery data. Recoveries of carbofuran, a critical constituent in ground- and surface-water studies, and desethyl atrazine, a critical constituent in the ground-water study, could not be calculated because of problems with the analytical method. Recoveries of pesticides analyzed using HPLC in ground- and surface-water samples were generally low and comparable with published recovery data. Other methodological problems for HPLC analytes included nondetection of the spike compounds and estimated values of spike concentrations. Recovery of field matrix spikes for volatile organic compounds generally were within the acceptable range, 70 and 130 percent for both ground- and surface-water samples, and median recoveries from 62 to 127 percent. High or low recoveries could be related to errors in the field, such as double spiking or using spike solution past its expiration date, rather than problems during analysis. The methodological changes in the field spike protocol during the course of the Sacramento River Basin study, which included decreasing the amount of spike solu

A polynomial chaos expansion based molecular dynamics study for probabilistic strength analysis of nano-twinned copper

NASA Astrophysics Data System (ADS)

Mahata, Avik; Mukhopadhyay, Tanmoy; Adhikari, Sondipon

2016-03-01

Nano-twinned structures are mechanically stronger, ductile and stable than its non-twinned form. We have investigated the effect of varying twin spacing and twin boundary width (TBW) on the yield strength of the nano-twinned copper in a probabilistic framework. An efficient surrogate modelling approach based on polynomial chaos expansion has been proposed for the analysis. Effectively utilising 15 sets of expensive molecular dynamics simulations, thousands of outputs have been obtained corresponding to different sets of twin spacing and twin width using virtual experiments based on the surrogates. One of the major outcomes of this work is that there exists an optimal combination of twin boundary spacing and twin width until which the strength can be increased and after that critical point the nanowires weaken. This study also reveals that the yield strength of nano-twinned copper is more sensitive to TBW than twin spacing. Such robust inferences have been possible to be drawn only because of applying the surrogate modelling approach, which makes it feasible to obtain results corresponding to 40 000 combinations of different twin boundary spacing and twin width in a computationally efficient framework.

Regenerating time series from ordinal networks.

PubMed

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

Regenerating time series from ordinal networks

NASA Astrophysics Data System (ADS)

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

Surrogacy: outcomes for surrogate mothers, children and the resulting families-a systematic review.

PubMed

Söderström-Anttila, Viveca; Wennerholm, Ulla-Britt; Loft, Anne; Pinborg, Anja; Aittomäki, Kristiina; Romundstad, Liv Bente; Bergh, Christina

2016-01-01

Surrogacy is a highly debated method mainly used for treating women with infertility caused by uterine factors. This systematic review summarizes current levels of knowledge of the obstetric, medical and psychological outcomes for the surrogate mothers, the intended parents and children born as a result of surrogacy. PubMed, Cochrane and Embase databases up to February 2015 were searched. Cohort studies and case series were included. Original studies published in English and the Scandinavian languages were included. In case of double publications, the latest study was included. Abstracts only and case reports were excluded. Studies with a control group and case series (more than three cases) were included. Cohort studies, but not case series, were assessed for methodological quality, in terms of risk of bias. We examined a variety of main outcomes for the surrogate mothers, children and intended mothers, including obstetric outcome, relationship between surrogate mother and intended couple, surrogate's experiences after relinquishing the child, preterm birth, low birthweight, birth defects, perinatal mortality, child psychological development, parent-child relationship, and disclosure to the child. The search returned 1795 articles of which 55 met the inclusion criteria. The medical outcome for the children was satisfactory and comparable to previous results for children conceived after fresh IVF and oocyte donation. The rate of multiple pregnancies was 2.6-75.0%. Preterm birth rate in singletons varied between 0 and 11.5% and low birthweight occurred in between 0 and 11.1% of cases. At the age of 10 years there were no major psychological differences between children born after surrogacy and children born after other types of assisted reproductive technology (ART) or after natural conception. The obstetric outcomes for the surrogate mothers were mainly reported from case series. Hypertensive disorders in pregnancy were reported in between 3.2 and 10% of cases and placenta praevia/placental abruption in 4.9%. Cases with hysterectomies have also been reported. Most surrogate mothers scored within the normal range on personality tests. Most psychosocial variables were satisfactory, although difficulties related to handing over the child did occur. The psychological well-being of children whose mother had been a surrogate mother between 5 and 15 years earlier was found to be good. No major differences in psychological state were found between intended mothers, mothers who conceived after other types of ART and mothers whose pregnancies were the result of natural conception. Most studies reporting on surrogacy have serious methodological limitations. According to these studies, most surrogacy arrangements are successfully implemented and most surrogate mothers are well-motivated and have little difficulty separating from the children born as a result of the arrangement. The perinatal outcome of the children is comparable to standard IVF and oocyte donation and there is no evidence of harm to the children born as a result of surrogacy. However, these conclusions should be interpreted with caution. To date, there are no studies on children born after cross-border surrogacy or growing up with gay fathers. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The representation of healthcare end users' perspectives by surrogates in healthcare decisions: a literature review.

PubMed

Shah, Syed Ghulam Sarwar; Farrow, Alexandra; Robinson, Ian

2009-12-01

The representation of end users' perspectives in healthcare decisions requires involvement of their surrogates when the end users, i.e. certain patients, elderly people, children and people with disabilities, are unable to present their views. To review critical issues, and the advantages and disadvantages of involving surrogates in representing end users' perspectives in healthcare decisions. A systematic review of literature published in peer-reviewed journals from 1990 to 2005. Findings show that surrogates are used widely in health care and that they are necessary to represent end users' perspectives in healthcare decisions when the latter are unable to do so themselves. Critical issues in using surrogates include key ethical, social, cultural, legal and medico-technological factors; ascertaining the best interest of end users; potential conflict of interest; possible biased decisions and the burden on surrogates. The key advantage of surrogate involvement in healthcare decisions is their ability to represent end users' needs, values and wishes. The main disadvantages include potential discrepancies between the decisions and conclusions of surrogates and end users; the failure of surrogates to predict end users' preferences accurately and the lack of certainty that useful information will be obtained through the surrogacy process. This systematic review has revealed that the involvement of surrogates is an additional vital way to represent end users' perspectives in healthcare decisions where for a range of reasons their opinions are unable to be effectively ascertained. However, because of the heterogeneity of surrogates and end users, the selection of appropriate surrogates and deploying surrogate decisions require particularly careful consideration of their value in individual cases; thus, subsequent decision-making must be reviewed on a case-to-case basis to seek to ensure that the best interests, needs and wishes of the end user are fully and accurately represented.

The Trial of Ascertaining Individual Preferences for Loved Ones' Role in End-of-Life Decisions (TAILORED) Study: A Randomized Controlled Trial to Improve Surrogate Decision Making.

PubMed

Sulmasy, Daniel P; Hughes, Mark T; Yenokyan, Gayane; Kub, Joan; Terry, Peter B; Astrow, Alan B; Johnson, Julie A; Ho, Grace; Nolan, Marie T

2017-10-01

Patients with terminal illnesses often require surrogate decision makers. Prior research has demonstrated high surrogate stress, and that despite standards promoting substituted judgment, most patients do not want their surrogates to make pure substituted judgments for them. It is not known how best to help loved ones fulfill the surrogate role. To test the effectiveness of an intervention to help surrogate decision makers. One hundred sixty-six patients (41% with amyotrophic lateral sclerosis and 59% with gastrointestinal cancers) and their surrogates at two university medical centers were randomized to an intensive nurse-directed discussion of the end-of-life decision control preferences of the patient (TAILORED) or a discussion of nutrition (CONTROL); 163 completed baseline interviews and underwent the intervention. Twelve patients died during follow-up and 137 dyads completed the study. Post-intervention, using all available data, TAILORED patients and surrogates became more likely to endorse mutual surrogate decision making, that is, a balance of their own wishes and what the surrogate thinks best (adjusted odds compared with baseline for patients = 1.78, P = 0.04; adjusted odds for surrogates = 2.05, P = 0.03). CONTROL patients became 40% less likely to endorse mutual surrogate decision making (P = 0.08), and CONTROL surrogates did not change significantly from baseline (adjusted odds = 1.44, P = 0.28). Stress levels decreased for TAILORED surrogates (impact of events scale = 23.1 ± 14.6 baseline, 20.8 ± 15.3 f/u, P = 0.046), but not for CONTROL (P = 0.85), and post-intervention stress was lower for TAILORED than CONTROL (P = 0.04). Surrogates' confidence was uniformly high at baseline and did not change. Caregiver burden (Zarit) increased from 12.5 ± 6.5 to 14.7 ± 8.1 for TAILORED (P < 0.01), while not changing for CONTROL, yet satisfaction with involvement in decision making was higher at follow-up for TAILORED than for CONTROL (71% vs. 52%, P = 0.03). TAILORED patients and surrogates who completed the study adopted a more mutual decision-making style, balancing their own wishes with what the surrogate thinks would be best for them. Surrogates reported less stress and more satisfaction. Confidence was high at baseline and did not change. There was a modest increase in caregiver burden. These findings suggest that interventions like TAILORED might positively impact surrogate decision making. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Meta-analysis of avian and small-mammal response to fire severity and fire surrogate treatments in U.S. fire-prone forests.

PubMed

Fontaine, Joseph B; Kennedy, Patricia L

2012-07-01

Management in fire-prone ecosystems relies widely upon application of prescribed fire and/or fire surrogate (e.g., forest thinning) treatments to maintain biodiversity and ecosystem function. Recently, published literature examining wildlife response to fire and fire management has increased rapidly. However, none of this literature has been synthesized quantitatively, precluding assessment of consistent patterns of wildlife response among treatment types. Using meta-analysis, we examined the scientific literature on vertebrate demographic responses to burn severity (low/moderate, high), fire surrogates (forest thinning), and fire and fire surrogate combined treatments in the most extensively studied fire-prone, forested biome (forests of the United States). Effect sizes (magnitude of response) and their 95% confidence limits (response consistency) were estimated for each species-by-treatment combination with two or more observations. We found 41 studies of 119 bird and 17 small-mammal species that examined short-term responses (< or =4 years) to thinning, low/moderate- and high-severity fire, and thinning plus prescribed fire; data on other taxa and at longer time scales were too sparse to permit quantitative assessment. At the stand scale (<50 ha), thinning and low/moderate-severity fire demonstrated similar response patterns in these forests. Combined thinning plus prescribed fire produced a higher percentage of positive responses. High-severity fire provoked stronger responses, with a majority of species possessing higher or lower effect sizes relative to fires of lower severity. In the short term and at fine spatial scales, fire surrogate forest-thinning treatments appear to effectively mimic low/moderate-severity fire, whereas low/moderate-severity fire is not a substitute for high-severity fire. The varied response of taxa to each of the four conditions considered makes it clear that the full range of fire-based disturbances (or their surrogates) is necessary to maintain a full complement of vertebrate species, including fire-sensitive taxa. This is especially true for high-severity fire, where positive responses from many avian taxa suggest that this disturbance (either as wildfire or prescribed fire) should be included in management plans where it is consistent with historic fire regimes and where maintenance of regional vertebrate biodiversity is a goal.

A perfect correlate does not a surrogate make

PubMed Central

Baker, Stuart G; Kramer, Barnett S

2003-01-01

Background There is common belief among some medical researchers that if a potential surrogate endpoint is highly correlated with a true endpoint, then a positive (or negative) difference in potential surrogate endpoints between randomization groups would imply a positive (or negative) difference in unobserved true endpoints between randomization groups. We investigate this belief when the potential surrogate and unobserved true endpoints are perfectly correlated within each randomization group. Methods We use a graphical approach. The vertical axis is the unobserved true endpoint and the horizontal axis is the potential surrogate endpoint. Perfect correlation within each randomization group implies that, for each randomization group, potential surrogate and true endpoints are related by a straight line. In this scenario the investigator does not know the slopes or intercepts. We consider a plausible example where the slope of the line is higher for the experimental group than for the control group. Results In our example with unknown lines, a decrease in mean potential surrogate endpoints from control to experimental groups corresponds to an increase in mean true endpoint from control to experimental groups. Thus the potential surrogate endpoints give the wrong inference. Similar results hold for binary potential surrogate and true outcomes (although the notion of correlation does not apply). The potential surrogate endpointwould give the correct inference if either (i) the unknown lines for the two group coincided, which means that the distribution of true endpoint conditional on potential surrogate endpoint does not depend on treatment group, which is called the Prentice Criterion or (ii) if one could accurately predict the lines based on data from prior studies. Conclusion Perfect correlation between potential surrogate and unobserved true outcomes within randomized groups does not guarantee correct inference based on a potential surrogate endpoint. Even in early phase trials, investigators should not base conclusions on potential surrogate endpoints in which the only validation is high correlation with the true endpoint within a group. PMID:12962545

Toward a Psychology of Surrogate Decision Making.

PubMed

Tunney, Richard J; Ziegler, Fenja V

2015-11-01

In everyday life, many of the decisions that we make are made on behalf of other people. A growing body of research suggests that we often, but not always, make different decisions on behalf of other people than the other person would choose. This is problematic in the practical case of legally designated surrogate decision makers, who may not meet the substituted judgment standard. Here, we review evidence from studies of surrogate decision making and examine the extent to which surrogate decision making accurately predicts the recipient's wishes, or if it is an incomplete or distorted application of the surrogate's own decision-making processes. We find no existing domain-general model of surrogate decision making. We propose a framework by which surrogate decision making can be assessed and a novel domain-general theory as a unifying explanatory concept for surrogate decisions. © The Author(s) 2015.

[Definition of low threshold volumes for quality assurance: conceptual and methodological issues involved in the definition and evaluation of thresholds for volume outcome relations in clinical care].

PubMed

Wetzel, Hermann

2006-01-01

In a large number of mostly retrospective association studies, a statistical relationship between volume and quality of health care has been reported. However, the relevance of these results is frequently limited by methodological shortcomings. In this article, criteria for the evidence and definition of thresholds for volume-outcome relations are proposed, e.g. the specification of relevant outcomes for quality indicators, analysis of volume as a continuous variable with an adequate case-mix and risk adjustment, accounting for cluster effects and considering mathematical models for the derivation of cut-off values. Moreover, volume thresholds are regarded as surrogate parameters for the indirect classification of the quality of care, whose diagnostic validity and effectiveness in improving health care quality need to be evaluated in prospective studies.

Comparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.

PubMed

Gabriel, Erin E; Sachs, Michael C; Gilbert, Peter B

2015-02-10

Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd.

Ratio of mean platelet volume to platelet count is a potential surrogate marker predicting liver cirrhosis.

PubMed

Iida, Hiroya; Kaibori, Masaki; Matsui, Kosuke; Ishizaki, Morihiko; Kon, Masanori

2018-01-27

To provide a simple surrogate marker predictive of liver cirrhosis (LC). Specimens from 302 patients who underwent resection for hepatocellular carcinoma between January 2006 and December 2012 were retrospectively analyzed. Based on pathologic findings, patients were divided into groups based on whether or not they had LC. Parameters associated with hepatic functional reserve were compared in these two groups using Mann-Whitney U -test for univariate analysis. Factors differing significantly in univariate analyses were entered into multivariate logistic regression analysis. There were significant differences between the LC group ( n = 100) and non-LC group ( n = 202) in prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin, albumin, cholinesterase, type IV collagen, hyaluronic acid, indocyanine green retention rate at 15 min, maximal removal rate of technitium-99m diethylene triamine penta-acetic acid-galactosyl human serum albumin and ratio of mean platelet volume to platelet count (MPV/PLT). Multivariate analysis showed that prothrombin activity, concentrations of alanine aminotransferase, aspartate aminotransferase, total bilirubin and hyaluronic acid, and MPV/PLT ratio were factors independently predictive of LC. The area under the curve value for MPV/PLT was 0.78, with a 0.8 cutoff value having a sensitivity of 65% and a specificity of 78%. The MPV/PLT ratio, which can be determined simply from the complete blood count, may be a simple surrogate marker predicting LC.

The psychological well-being and prenatal bonding of gestational surrogates

PubMed Central

Lamba, N; Jadva, V; Kadam, K; Golombok, S

2018-01-01

Abstract STUDY QUESTION How does the psychological well-being and prenatal bonding of Indian surrogates differ from a comparison group of mothers? SUMMARY ANSWER Surrogates had higher levels of depression during pregnancy and post-birth, displayed lower emotional connection with the unborn baby, and greater care towards the healthy growth of the foetus, than the comparison group of mothers. WHAT IS ALREADY KNOWN Studies in the West have found that surrogates do not suffer long-term psychological harm. One study has shown that surrogates bond less with the foetus than expectant mothers. STUDY, DESIGN, SIZE, DURATION This study uses a prospective, longitudinal and cross-sectional design. Surrogates and a matched group of expectant mothers were seen twice, during 4–9 months of pregnancy and 4–6 months after the birth. PARTICIPANTS/MATERIALS, SETTING, METHODS Semi-structured interviews and standardized questionnaires were administered to 50 surrogates and 69 expectant mothers during pregnancy and 45 surrogates and 49 expectant mothers post-birth. All gestational surrogates were hosting pregnancies for international intended parents. MAIN RESULTS AND THE ROLE OF CHANCE Surrogates had higher levels of depression compared to the comparison group of mothers, during pregnancy and post-birth (P < 0.02). Low social support during pregnancy, hiding surrogacy and criticism from others were found to be predictive of higher depression in surrogates post-birth (P < 0.05). Regarding prenatal bonding, surrogates interacted less with and thought less about the foetus but adopted better eating habits and were more likely to avoid unhealthy practices during pregnancy, than expectant mothers (P < 0.05). No associations were found between greater prenatal bonding and greater psychological distress during pregnancy or after relinquishment. LIMITATIONS, REASONS FOR CAUTION All surrogates were recruited from one clinic in Mumbai, and thus the representativeness of this sample is not known. Also, the possibility of socially desirable responding from surrogates cannot be ruled out. WIDER IMPLICATIONS OF THE FINDINGS As this is the first study of the psychological well-being of surrogates in low-income countries, the findings have important policy implications. Providing support and counselling to surrogates, especially during pregnancy, may alleviate some of the psychological problems faced by surrogates. STUDY FUNDING/COMPETING INTEREST(S) This study was supported by the Wellcome Trust [097857/Z/11/Z] and Nehru Trust, Cambridge. K.K. is the Medical Director of Corion Fertility Clinic. All other authors have no conflict of interest to declare. PMID:29566176

Individual progression of carotid intima media thickness as a surrogate for vascular risk (PROG-IMT): Rationale and design of a meta-analysis project

PubMed Central

Lorenz, Matthias W.; Bickel, Horst; Bots, Michiel L.; Breteler, Monique M.B.; Catapano, Alberico L.; Desvarieux, Moise; Hedblad, Bo; Iglseder, Bernhard; Johnsen, Stein Harald; Juraska, Michal; Kiechl, Stefan; Mathiesen, Ellisiv B.; Norata, Giuseppe D.; Grigore, Liliana; Polak, Joseph; Poppert, Holger; Rosvall, Maria; Rundek, Tatjana; Sacco, Ralph L.; Sander, Dirk; Sitzer, Matthias; Steinmetz, Helmuth; Stensland, Eva; Willeit, Johann; Witteman, Jacqueline; Yanez, David; Thompson, Simon G.

2013-01-01

Carotid intima media thickness (IMT) progression is increasingly used as a surrogate for vascular risk. This use is supported by data from a few clinical trials investigating statins, but established criteria of surrogacy are only partially fulfilled. To provide a valid basis for the use of IMT progression as a study end point, we are performing a 3-step meta-analysis project based on individual participant data. Objectives of the 3 successive stages are to investigate (1) whether IMT progression prospectively predicts myocardial infarction, stroke, or death in population-based samples; (2) whether it does so in prevalent disease cohorts; and (3) whether interventions affecting IMT progression predict a therapeutic effect on clinical end points. Recruitment strategies, inclusion criteria, and estimates of the expected numbers of eligible studies are presented along with a detailed analysis plan. PMID:20435179

Generalized sample entropy analysis for traffic signals based on similarity measure

NASA Astrophysics Data System (ADS)

Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.

Probabilistic Fatigue Damage Prognosis Using a Surrogate Model Trained Via 3D Finite Element Analysis

NASA Technical Reports Server (NTRS)

Leser, Patrick E.; Hochhalter, Jacob D.; Newman, John A.; Leser, William P.; Warner, James E.; Wawrzynek, Paul A.; Yuan, Fuh-Gwo

2015-01-01

Utilizing inverse uncertainty quantification techniques, structural health monitoring can be integrated with damage progression models to form probabilistic predictions of a structure's remaining useful life. However, damage evolution in realistic structures is physically complex. Accurately representing this behavior requires high-fidelity models which are typically computationally prohibitive. In the present work, a high-fidelity finite element model is represented by a surrogate model, reducing computation times. The new approach is used with damage diagnosis data to form a probabilistic prediction of remaining useful life for a test specimen under mixed-mode conditions.

Surrogate Agreement in Tzotzil.

ERIC Educational Resources Information Center

Aissen, Judith L.

This study investigates whether other relationships in sentence structure besides the "brother-in-law" relation sanction surrogate agreement in Zinacanteco Tzotzil (Mayan). Surrogate agreement refers to cases in which an element that lies outside the class of regular agreement controllers in a language (the surrogate) controls…

Surrogate endpoints in randomized cardiovascular clinical trials.

PubMed

Domanski, Michael; Pocock, Stuart; Bernaud, Corine; Borer, Jeffrey; Geller, Nancy; Revkin, James; Zannad, Faiez

2011-08-01

Surrogate endpoints predict the occurrence and timing of a clinical endpoint of interest (CEI). Substitution of a surrogate endpoint for a CEI can dramatically reduce the time and cost necessary to complete a Phase III clinical trial. However, assurance that use of a surrogate endpoint will result in a correct conclusion regarding treatment effect on a CEI requires prior rigorous validation of the surrogate. Surrogate endpoints can also be of substantial use in Phase I and II studies to assess whether the intended therapeutic pathway is operative, thus providing assurance regarding the reasonableness of proceeding to a Phase III trial. This paper discusses the uses and validation of surrogate endpoints. © 2010 The Authors Fundamental and Clinical Pharmacology © 2010 Société Française de Pharmacologie et de Thérapeutique.

Advances in shock timing experiments on the National Ignition Facility

NASA Astrophysics Data System (ADS)

Robey, H. F.; Celliers, P. M.; Moody, J. D.; Sater, J.; Parham, T.; Kozioziemski, B.; Dylla-Spears, R.; Ross, J. S.; LePape, S.; Ralph, J. E.; Hohenberger, M.; Dewald, E. L.; Berzak Hopkins, L.; Kroll, J. J.; Yoxall, B. E.; Hamza, A. V.; Boehly, T. R.; Nikroo, A.; Landen, O. L.; Edwards, M. J.

2016-03-01

Recent advances in shock timing experiments and analysis techniques now enable shock measurements to be performed in cryogenic deuterium-tritium (DT) ice layered capsule implosions on the National Ignition Facility (NIF). Previous measurements of shock timing in inertial confinement fusion (ICF) implosions were performed in surrogate targets, where the solid DT ice shell and central DT gas were replaced with a continuous liquid deuterium (D2) fill. These previous experiments pose two surrogacy issues: a material surrogacy due to the difference of species (D2 vs. DT) and densities of the materials used and a geometric surrogacy due to presence of an additional interface (ice/gas) previously absent in the liquid-filled targets. This report presents experimental data and a new analysis method for validating the assumptions underlying this surrogate technique.

Surrogacy families 10 years on: relationship with the surrogate, decisions over disclosure and children's understanding of their surrogacy origins

PubMed Central

Jadva, V.; Blake, L.; Casey, P.; Golombok, S.

2012-01-01

BACKGROUND This study aimed to prospectively examine families created using surrogacy over a 10-year period in the UK with respect to intending parents' and children's relationship with the surrogate mother, parents' decisions over disclosure and children's understanding of the nature of their conception. METHODS Semi-structured interviews were administered by trained researchers to intending mothers, intending fathers and children on four occasions over a 10-year period. Forty-two families (19 with a genetic surrogate mother) participated when the child was 1-year old and by age 10 years, 33 families remained in the study. Data were collected on the frequency of contact with the surrogate mother, relationship with the surrogate, disclosure of surrogacy to the child and the child's understanding of their surrogacy birth. RESULTS Frequency of contact between surrogacy families and their surrogate mother decreased over time, particularly for families whose surrogate was a previously unknown genetic carrier (P < 0.001) (i.e. where they had met through a third party and the surrogate mother's egg was used to conceive the child). Most families reported harmonious relationships with their surrogate mother. At age 10 years, 19 (90%) children who had been informed of the nature of their conception had a good understanding of this and 13 of the 14 children who were in contact with their surrogate reported that they liked her. CONCLUSIONS Surrogacy families maintained good relationships with the surrogate mother over time. Children felt positive about their surrogate mother and their surrogacy birth. The sample size of this study was small and further, larger investigations are needed before firm conclusions can be drawn. PMID:22814484

Surrogate endpoints in oncology: when are they acceptable for regulatory and clinical decisions, and are they currently overused?

PubMed

Kemp, Robert; Prasad, Vinay

2017-07-21

Surrogate outcomes are not intrinsically beneficial to patients, but are designed to be easier and faster to measure than clinically meaningful outcomes. The use of surrogates as an endpoint in clinical trials and basis for regulatory approval is common, and frequently exceeds the guidance given by regulatory bodies. In this article, we demonstrate that the use of surrogates in oncology is widespread and increasing. At the same time, the strength of association between the surrogates used and clinically meaningful outcomes is often unknown or weak. Attempts to validate surrogates are rarely undertaken. When this is done, validation relies on only a fraction of available data, and often concludes that the surrogate is poor. Post-marketing studies, designed to ensure drugs have meaningful benefits, are often not performed. Alternatively, if a drug fails to improve quality of life or overall survival, market authorization is rarely revoked. We suggest this reliance on surrogates, and the imprecision surrounding their acceptable use, means that numerous drugs are now approved based on small yet statistically significant increases in surrogates of questionable reliability. In turn, this means the benefits of many approved drugs are uncertain. This is an unacceptable situation for patients and professionals, as prior experience has shown that such uncertainty can be associated with significant harm. The use of surrogate outcomes should be limited to situations where a surrogate has demonstrated robust ability to predict meaningful benefits, or where cases are dire, rare or with few treatment options. In both cases, surrogates must be used only when continuing studies examining hard endpoints have been fully recruited.

Surrogacy families 10 years on: relationship with the surrogate, decisions over disclosure and children's understanding of their surrogacy origins.

PubMed

Jadva, V; Blake, L; Casey, P; Golombok, S

2012-10-01

This study aimed to prospectively examine families created using surrogacy over a 10-year period in the UK with respect to intending parents' and children's relationship with the surrogate mother, parents' decisions over disclosure and children's understanding of the nature of their conception. Semi-structured interviews were administered by trained researchers to intending mothers, intending fathers and children on four occasions over a 10-year period. Forty-two families (19 with a genetic surrogate mother) participated when the child was 1-year old and by age 10 years, 33 families remained in the study. Data were collected on the frequency of contact with the surrogate mother, relationship with the surrogate, disclosure of surrogacy to the child and the child's understanding of their surrogacy birth. Frequency of contact between surrogacy families and their surrogate mother decreased over time, particularly for families whose surrogate was a previously unknown genetic carrier (P < 0.001) (i.e. where they had met through a third party and the surrogate mother's egg was used to conceive the child). Most families reported harmonious relationships with their surrogate mother. At age 10 years, 19 (90%) children who had been informed of the nature of their conception had a good understanding of this and 13 of the 14 children who were in contact with their surrogate reported that they liked her. Surrogacy families maintained good relationships with the surrogate mother over time. Children felt positive about their surrogate mother and their surrogacy birth. The sample size of this study was small and further, larger investigations are needed before firm conclusions can be drawn.

Use of aerobic spores as a surrogate for cryptosporidium oocysts in drinking water supplies.

PubMed

Headd, Brendan; Bradford, Scott A

2016-03-01

Waterborne illnesses are a growing concern among health and regulatory agencies worldwide. The United States Environmental Protection Agency has established several rules to combat the contamination of water supplies by cryptosporidium oocysts, however, the detection and study of cryptosporidium oocysts is hampered by methodological and financial constraints. As a result, numerous surrogates for cryptosporidium oocysts have been proposed by the scientific community and efforts are underway to evaluate many of the proposed surrogates. The purpose of this review is to evaluate the suitability of aerobic bacterial spores to serve as a surrogate for cryptosporidium oocysts in identifying contaminated drinking waters. To accomplish this we present a comparison of the biology and life cycles of aerobic spores and oocysts and compare their physical properties. An analysis of their surface properties is presented along with a review of the literature in regards to the transport, survival, and prevalence of aerobic spores and oocysts in the saturated subsurface environment. Aerobic spores and oocysts share many commonalities with regard to biology and survivability, and the environmental prevalence and ease of detection make aerobic spores a promising surrogate for cryptosporidium oocysts in surface and groundwater. However, the long-term transport and release of aerobic spores still needs to be further studied, and compared with available oocyst information. In addition, the surface properties and environmental interactions of spores are known to be highly dependent on the spore taxa and purification procedures, and additional research is needed to address these issues in the context of transport. Published by Elsevier Ltd.

Real-time surrogate analysis for potential oil and gas contamination of drinking water resources

NASA Astrophysics Data System (ADS)

Son, Ji-Hee; Carlson, Kenneth H.

2015-09-01

Public concerns related to the fast-growing shale oil and gas industry have increased during recent years. The major concern regarding shale gas production is the potential of fracturing fluids being injected into the well or produced fluids flowing out of the well to contaminate drinking water resources such as surface water and groundwater. Fracturing fluids contain high total dissolved solids (TDS); thus, changes in TDS concentrations in groundwater might indicate influences of fracturing fluids. An increase of methane concentrations in groundwater could also potentially be due to hydraulic fracturing activities. To understand the possible contamination of groundwater by fracturing activities, real-time groundwater monitoring is being implemented in the Denver-Julesburg basin of northeast Colorado. A strategy of monitoring of surrogate parameters was chosen instead of measuring potential contaminants directly, an approach that is not cost effective or operationally practical. Contaminant surrogates of TDS and dissolved methane were proposed in this study, and were tested for correlation and data distribution with laboratory experiments. Correlations between TDS and electrical conductivity (EC), and between methane contamination and oxidation-reduction potential (ORP) were strong at low concentrations of contaminants (1 mg/L TDS and 0.3 mg/L CH4). Dissolved oxygen (DO) was only an effective surrogate at higher methane concentrations (≥2.5 mg/L). The results indicated that EC and ORP are effective surrogates for detecting concentration changes of TDS and methane, respectively, and that a strategy of monitoring for easy to measure parameters can be effective detecting real-time, anomalous behavior relative to a predetermined baseline.

Processes in scientific workflows for information seeking related to physical sample materials

NASA Astrophysics Data System (ADS)

Ramdeen, S.

2014-12-01

The majority of State Geological Surveys have repositories containing cores, cuttings, fossils or other physical sample material. State surveys maintain these collections to support their own research as well as the research conducted by external users from other organizations. This includes organizations such as government agencies (state and federal), academia, industry and the public. The preliminary results presented in this paper will look at the research processes of these external users. In particular: how they discover, access and use digital surrogates, which they use to evaluate and access physical items in these collections. Data such as physical samples are materials that cannot be completely replaced with digital surrogates. Digital surrogates may be represented as metadata, which enable discovery and ultimately access to these samples. These surrogates may be found in records, databases, publications, etc. But surrogates do not completely prevent the need for access to the physical item as they cannot be subjected to chemical testing and/or other similar analysis. The goal of this research is to document the various processes external users perform in order to access physical materials. Data for this study will be collected by conducting interviews with these external users. During the interviews, participants will be asked to describe the workflow that lead them to interact with state survey repositories, and what steps they took afterward. High level processes/categories of behavior will be identified. These processes will be used in the development of an information seeking behavior model. This model may be used to facilitate the development of management tools and other aspects of cyberinfrastructure related to physical samples.

Quantitative analysis of the growth of Salmonella stanley during alfalfa sprouting and evaluation of Enterobacter aerogenes as its surrogate.

PubMed

Liu, Bin; Schaffner, Donald W

2007-02-01

Raw seed sprouts have been implicated in several food poisoning outbreaks in the last 10 years. Few studies have included investigations of factors influencing the effectiveness of testing spent irrigation water, and in no studies to date has a nonpathogenic surrogate been identified as suitable for large-scale irrigation water testing trials. Alfalfa seeds were inoculated with Salmonella Stanley or its presumptive surrogate (nalidixic acid-resistant Enterobacter aerogenes) at three concentrations (-3, -30, and -300 CFU/g) and were then transferred into either flasks or a bench top-scale sprouting chamber. Microbial concentrations were determined in seeds, sprouts, and irrigation water at various times during a 4-day sprouting process. Data were fit to logistic regression models, and growth rates and maximum concentrations were compared using the generalized linear model procedure of SAS. No significant differences in growth rates were observed among samples taken from flasks or the chamber. Microbial concentrations in irrigation water were not significantly different from concentrations in sprout samples obtaihed at the same time. E. aerogenes concentrations were similar to those of Salmonella Stanley at corresponding time points for all three inoculum concentrations. Growth rates were also constant regardless of inoculum concentration or strain, except that lower inoculum concentrations resulted in lower final concentrations proportional to their initial concentrations. This research demonstrated that a nonpathogenic easy-to-isolate surrogate (nalidixic acid-resistant E. aerogenes) provides results similar to those obtained with Salmonella Stanley, supporting the use of this surrogate in future large-scale experiments.

Surrogate endpoints for overall survival in lung cancer trials: a review.

PubMed

Fiteni, Frédéric; Westeel, Virginie; Bonnetain, Franck

2017-05-01

Intermediate endpoints are often used as primary endpoints instead of overall survival (OS) in lung cancer trials but they are not systematically validated as surrogate endpoints for OS. Areas covered: The aim of the study was to review the studies which assessed potential surrogate endpoints for OS in lung cancer trials. Expert commentary: Twenty studies were identified. In operable non-small cell lung cancer (NSCLC) (adjuvant trials) and locally advanced NSCLC (radiotherapy trials), one individual-patient data meta-analysis found a high correlation of disease-free survival (DFS) and progression-free survival (PFS) with OS at patient and trial level. In trials of adjuvant chemotherapy, correlation between disease-free survival DFS and OS were 0.83 at the individual level (95% CI 0.83-0.83) and 0.92 at trial level (95% CI 0.88-0.95). In locally advanced disease, correlation between PFS and OS was 0.77 to 0.85 at the individual level, and 0.89 to 0.97 at trial level. This study provides a 'proof' of the surrogacy of PFS and DFS on OS according to the IQWiG framework and the surrogacy of PFS and DFS on OS was classified level 2 according to Fleming hierarchy. In all the other setting, no endpoint was judged to be valid surrogate for OS.

Does synchronization reflect a true interaction in the cardiorespiratory system?

PubMed

Toledo, E; Akselrod, S; Pinhas, I; Aravot, D

2002-01-01

Cardiorespiratory synchronization, studied within the framework of phase synchronization, has recently raised interest as one of the interactions in the cardiorespiratory system. In this work, we present a quantitative approach to the analysis of this nonlinear phenomenon. Our primary aim is to determine whether synchronization between HR and respiration rate is a real phenomenon or a random one. First, we developed an algorithm, which detects epochs of synchronization automatically and objectively. The algorithm was applied to recordings of respiration and HR obtained from 13 normal subjects and 13 heart transplant patients. Surrogate data sets were constructed from the original recordings, specifically lacking the coupling between HR and respiration. The statistical properties of synchronization in the two data sets and in their surrogates were compared. Synchronization was observed in all groups: in normal subjects, in the heart transplant patients and in the surrogates. Interestingly, synchronization was less abundant in normal subjects than in the transplant patients, indicating that the unique physiological condition of the latter promote cardiorespiratory synchronization. The duration of synchronization epochs was significantly shorter in the surrogate data of both data sets, suggesting that at least some of the synchronization epochs are real. In view of those results, cardiorespiratory synchronization, although not a major feature of cardiorespiratory interaction, seems to be a real phenomenon rather than an artifact.

A speech pronunciation practice system for speech-impaired children: A study to measure its success.

PubMed

Salim, Siti Salwah; Mustafa, Mumtaz Begum Binti Peer; Asemi, Adeleh; Ahmad, Azila; Mohamed, Noraini; Ghazali, Kamila Binti

2016-09-01

The speech pronunciation practice (SPP) system enables children with speech impairments to practise and improve their speech pronunciation. However, little is known about the surrogate measures of the SPP system. This research aims to measure the success and effectiveness of the SPP system using three surrogate measures: usage (frequency of use), performance (recognition accuracy) and satisfaction (children's subjective reactions), and how these measures are aligned with the success of the SPP system, as well as to each other. We have measured the absolute change in the word error rate (WER) between the pre- and post-training, using the ANOVA test. Correlation co-efficiency (CC) analysis was conducted to test the relation between the surrogate measures, while a Structural Equation Model (SEM) was used to investigate the causal relations between the measures. The CC test results indicate a positive correlation between the surrogate measures. The SEM supports all the proposed gtheses. The ANOVA results indicate that SPP is effective in reducing the WER of impaired speech. The SPP system is an effective assistive tool, especially for high levels of severity. We found that performance is a mediator of the relation between "usage" and "satisfaction". Copyright © 2016 Elsevier Ltd. All rights reserved.

A general framework to learn surrogate relevance criterion for atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-09-01

Multi-atlas based image segmentation sees great opportunities in the big data era but also faces unprecedented challenges in identifying positive contributors from extensive heterogeneous data. To assess data relevance, image similarity criteria based on various image features widely serve as surrogates for the inaccessible geometric agreement criteria. This paper proposes a general framework to learn image based surrogate relevance criteria to better mimic the behaviors of segmentation based oracle geometric relevance. The validity of its general rationale is verified in the specific context of fusion set selection for image segmentation. More specifically, we first present a unified formulation for surrogate relevance criteria and model the neighborhood relationship among atlases based on the oracle relevance knowledge. Surrogates are then trained to be small for geometrically relevant neighbors and large for irrelevant remotes to the given targets. The proposed surrogate learning framework is verified in corpus callosum segmentation. The learned surrogates demonstrate superiority in inferring the underlying oracle value and selecting relevant fusion set, compared to benchmark surrogates.

Surrogacy: the experiences of surrogate mothers.

PubMed

Jadva, Vasanti; Murray, Clare; Lycett, Emma; MacCallum, Fiona; Golombok, Susan

2003-10-01

This study examined the motivations, experiences and psychological consequences of surrogacy for surrogate mothers. Thirty-four women who had given birth to a surrogate child approximately 1 year previously were interviewed by trained researchers, and the data rated using standardized coding criteria. Information was obtained on: (i) reasons for the woman's decision to become a surrogate mother; (ii) her retrospective view of the relationship with the commissioning couple before the pregnancy, during the pregnancy, and after the birth; (iii) her experiences during and after relinquishing the child; and (iv) how others reacted to her decision to become a surrogate mother. It was found that surrogate mothers do not generally experience major problems in their relationship with the commissioning couple, in handing over the baby, or from the reactions of those around them. The emotional problems experienced by some surrogate mothers in the weeks following the birth appeared to lessen over time. Surrogate mothers do not appear to experience psychological problems as a result of the surrogacy arrangement.

The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions.

PubMed

Bognar, Katalin; Romley, John A; Bae, Jay P; Murray, James; Chou, Jacquelyn W; Lakdawalla, Darius N

2017-01-01

Approval of new drugs is increasingly reliant on "surrogate endpoints," which correlate with but imperfectly predict clinical benefits. Proponents argue surrogate endpoints allow for faster approval, but critics charge they provide inadequate evidence. We develop an economic framework that addresses the value of improvement in the predictive power, or "quality," of surrogate endpoints, and clarifies how quality can influence decisions by regulators, payers, and manufacturers. For example, the framework shows how lower-quality surrogates lead to greater misalignment of incentives between payers and regulators, resulting in more drugs that are approved for use but not covered by payers. Efficient price-negotiation in the marketplace can help align payer incentives for granting access based on surrogates. Higher-quality surrogates increase manufacturer profits and social surplus from early access to new drugs. Since the return on better quality is shared between manufacturers and payers, private incentives to invest in higher-quality surrogates are inefficiently low. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Sensitivity of temporal heart rate variability in Poincaré plot to changes in parasympathetic nervous system activity.

PubMed

Karmakar, Chandan K; Khandoker, Ahsan H; Voss, Andreas; Palaniswami, Marimuthu

2011-03-03

A novel descriptor (Complex Correlation Measure (CCM)) for measuring the variability in the temporal structure of Poincaré plot has been developed to characterize or distinguish between Poincaré plots with similar shapes. This study was designed to assess the changes in temporal structure of the Poincaré plot using CCM during atropine infusion, 70° head-up tilt and scopolamine administration in healthy human subjects. CCM quantifies the point-to-point variation of the signal rather than gross description of the Poincaré plot. The physiological relevance of CCM was demonstrated by comparing the changes in CCM values with autonomic perturbation during all phases of the experiment. The sensitivities of short term variability (SD1), long term variability (SD2) and variability in temporal structure (CCM) were analyzed by changing the temporal structure by shuffling the sequences of points of the Poincaré plot. Surrogate analysis was used to show CCM as a measure of changes in temporal structure rather than random noise and sensitivity of CCM with changes in parasympathetic activity. CCM was found to be most sensitive to changes in temporal structure of the Poincaré plot as compared to SD1 and SD2. The values of all descriptors decreased with decrease in parasympathetic activity during atropine infusion and 70° head-up tilt phase. In contrast, values of all descriptors increased with increase in parasympathetic activity during scopolamine administration. The concordant reduction and enhancement in CCM values with parasympathetic activity indicates that the temporal variability of Poincaré plot is modulated by the parasympathetic activity which correlates with changes in CCM values. CCM is more sensitive than SD1 and SD2 to changes of parasympathetic activity.

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

Palus, Milan; Jajcay, Nikola; Hartman, David; Hlinka, Jaroslav

2015-04-01

Multitude of scales characteristic of the climate system variability requires innovative approaches in analysis of instrumental time series. We present a methodology which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited band-with, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. In particular, an information-theoretic formulation of the generalized, nonlinear Granger causality is applied together with surrogate data testing methods [1]. The method [2] uncovers causal influence (in the Granger sense) and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of daily mean surface air temperature from various European locations an information transfer from larger to smaller scales has been observed as the influence of the phase of slow oscillatory phenomena with periods around 7-8 years on amplitudes of the variability characterized by smaller temporal scales from a few months to annual and quasi-biennial scales [3]. In sea surface temperature data from the tropical Pacific area an influence of quasi-oscillatory phenomena with periods around 4-6 years on the variability on and near the annual scale has been observed. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [2] M. Palus, Entropy 16(10), 5263-5289 (2014) [3] M. Palus, Phys. Rev. Lett. 112, 078702 (2014)

Predicting laser weld reliability with stochastic reduced-order models. Predicting laser weld reliability

DOE PAGES

Emery, John M.; Field, Richard V.; Foulk, James W.; ...

2015-05-26

Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not bemore » efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.« less

Time-Frequency Learning Machines for Nonstationarity Detection Using Surrogates

NASA Astrophysics Data System (ADS)

Borgnat, Pierre; Flandrin, Patrick; Richard, Cédric; Ferrari, André; Amoud, Hassan; Honeine, Paul

2012-03-01

Time-frequency representations provide a powerful tool for nonstationary signal analysis and classification, supporting a wide range of applications [12]. As opposed to conventional Fourier analysis, these techniques reveal the evolution in time of the spectral content of signals. In Ref. [7,38], time-frequency analysis is used to test stationarity of any signal. The proposed method consists of a comparison between global and local time-frequency features. The originality is to make use of a family of stationary surrogate signals for defining the null hypothesis of stationarity and, based upon this information, to derive statistical tests. An open question remains, however, about how to choose relevant time-frequency features. Over the last decade, a number of new pattern recognition methods based on reproducing kernels have been introduced. These learning machines have gained popularity due to their conceptual simplicity and their outstanding performance [30]. Initiated by Vapnik’s support vector machines (SVM) [35], they offer now a wide class of supervised and unsupervised learning algorithms. In Ref. [17-19], the authors have shown how the most effective and innovative learning machines can be tuned to operate in the time-frequency domain. This chapter follows this line of research by taking advantage of learning machines to test and quantify stationarity. Based on one-class SVM, our approach uses the entire time-frequency representation and does not require arbitrary feature extraction. Applied to a set of surrogates, it provides the domain boundary that includes most of these stationarized signals. This allows us to test the stationarity of the signal under investigation. This chapter is organized as follows. In Section 22.2, we introduce the surrogate data method to generate stationarized signals, namely, the null hypothesis of stationarity. The concept of time-frequency learning machines is presented in Section 22.3, and applied to one-class SVM in order to derive a stationarity test in Section 22.4. The relevance of the latter is illustrated by simulation results in Section 22.5.

Performance test results of noninvasive characterization of Resource Conservation and Recovery Act surrogate waste by prompt gamma neutron activation analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gehrke, R.J.; Streier, G.G.

1997-03-01

During FY-96, a performance test was carried out with funding from the Mixed Waste Focus Area (MWFA) of the Department of Energy (DOE) to determine the noninvasive elemental assay capabilities of commercial companies for Resource Conservation and Recovery Act (RCRA) metals present in 8-gal drums containing surrogate waste. Commercial companies were required to be experienced in the use of prompt gamma neutron activation analysis (PGNAA) techniques and to have a prototype assay system with which to conduct the test assays. Potential participants were identified through responses to a call for proposals advertised in the Commerce Business Daily and through personalmore » contacts. Six companies were originally identified. Two of these six were willing and able to participate in the performance test, as described in the test plan, with some subsidizing from the DOE MWFA. The tests were conducted with surrogate sludge waste because (1) a large volume of this type of waste awaits final disposition and (2) sludge tends to be somewhat homogeneous. The surrogate concentrations of the above RCRA metals ranged from {approximately} 300 ppm to {approximately} 20,000 ppm. The lower limit was chosen as an estimate of the expected sensitivity of detection required by noninvasive, pretreatment elemental assay systems to be of value for operational and compliance purposes and to still be achievable with state-of-the-art methods of analysis. The upper limit of {approximately} 20,000 ppm was chosen because it is the opinion of the author that assay above this concentration level is within current state-of-the-art methods for most RCRA constituents. This report is organized into three parts: Part 1, Test Plan to Evaluate the Technical Status of Noninvasive Elemental Assay Techniques for Hazardous Waste; Part 2, Participants` Results; and Part 3, Evaluation of and Comments on Participants` Results.« less

Experimental and computational study of methane counterflow diffusion flames perturbed by trace amounts of either jet fuel or a 6-component surrogate under non-sooting conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bufferand, H.; Tosatto, L.; La Mantia, B.

2009-08-15

The chemical structure of a methane counterflow diffusion flame and of the same flame doped with 1000 ppm (molar) of either jet fuel or a 6-component jet fuel surrogate was analyzed experimentally, by gas sampling via quartz microprobes and subsequent GC/MS analysis, and computationally using a semi-detailed kinetic mechanism for the surrogate blend. Conditions were chosen to ensure that all three flames were non-sooting, with identical temperature profiles and stoichiometric mixture fraction, through a judicious selection of feed stream composition and strain rate. The experimental dataset provides a glimpse of the pyrolysis and oxidation behavior of jet fuel in amore » diffusion flame. The jet fuel initial oxidation is consistent with anticipated chemical kinetic behavior, based on thermal decomposition of large alkanes to smaller and smaller fragments and the survival of ring-stabilized aromatics at higher temperatures. The 6-component surrogate captures the same trend correctly, but the agreement is not quantitative with respect to some of the aromatics such as benzene and toluene. Various alkanes, alkenes and aromatics among the jet fuel components are either only qualitatively characterized or could not be identified, because of the presence of many isomers and overlapping spectra in the chromatogram, leaving 80% of the carbon from the jet fuel unaccounted for in the early pyrolysis history of the parent fuel. Computationally, the one-dimensional code adopted a semi-detailed kinetic mechanism for the surrogate blend that is based on an existing hierarchically constructed kinetic model for alkanes and simple aromatics, extended to account for the presence of tetralin and methylcyclohexane as reference fuels. The computational results are in reasonably good agreement with the experimental ones for the surrogate behavior, with the greatest discrepancy in the concentrations of aromatics and ethylene. (author)« less

Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

PubMed Central

Samu, David; Seth, Anil K.; Nowotny, Thomas

2014-01-01

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. PMID:24699277

An adaptive sparse-grid high-order stochastic collocation method for Bayesian inference in groundwater reactive transport modeling

NASA Astrophysics Data System (ADS)

Zhang, Guannan; Lu, Dan; Ye, Ming; Gunzburger, Max; Webster, Clayton

2013-10-01

Bayesian analysis has become vital to uncertainty quantification in groundwater modeling, but its application has been hindered by the computational cost associated with numerous model executions required by exploring the posterior probability density function (PPDF) of model parameters. This is particularly the case when the PPDF is estimated using Markov Chain Monte Carlo (MCMC) sampling. In this study, a new approach is developed to improve the computational efficiency of Bayesian inference by constructing a surrogate of the PPDF, using an adaptive sparse-grid high-order stochastic collocation (aSG-hSC) method. Unlike previous works using first-order hierarchical basis, this paper utilizes a compactly supported higher-order hierarchical basis to construct the surrogate system, resulting in a significant reduction in the number of required model executions. In addition, using the hierarchical surplus as an error indicator allows locally adaptive refinement of sparse grids in the parameter space, which further improves computational efficiency. To efficiently build the surrogate system for the PPDF with multiple significant modes, optimization techniques are used to identify the modes, for which high-probability regions are defined and components of the aSG-hSC approximation are constructed. After the surrogate is determined, the PPDF can be evaluated by sampling the surrogate system directly without model execution, resulting in improved efficiency of the surrogate-based MCMC compared with conventional MCMC. The developed method is evaluated using two synthetic groundwater reactive transport models. The first example involves coupled linear reactions and demonstrates the accuracy of our high-order hierarchical basis approach in approximating high-dimensional posteriori distribution. The second example is highly nonlinear because of the reactions of uranium surface complexation, and demonstrates how the iterative aSG-hSC method is able to capture multimodal and non-Gaussian features of PPDF caused by model nonlinearity. Both experiments show that aSG-hSC is an effective and efficient tool for Bayesian inference.

Comparison of task-based exposure metrics for an epidemiologic study of isocyanate inhalation exposures among autobody shop workers.

PubMed

Woskie, Susan R; Bello, Dhimiter; Gore, Rebecca J; Stowe, Meredith H; Eisen, Ellen A; Liu, Youcheng; Sparer, Judy A; Redlich, Carrie A; Cullen, Mark R

2008-09-01

Because many occupational epidemiologic studies use exposure surrogates rather than quantitative exposure metrics, the UMass Lowell and Yale study of autobody shop workers provided an opportunity to evaluate the relative utility of surrogates and quantitative exposure metrics in an exposure response analysis of cross-week change in respiratory function. A task-based exposure assessment was used to develop several metrics of inhalation exposure to isocyanates. The metrics included the surrogates, job title, counts of spray painting events during the day, counts of spray and bystander exposure events, and a quantitative exposure metric that incorporated exposure determinant models based on task sampling and a personal workplace protection factor for respirator use, combined with a daily task checklist. The result of the quantitative exposure algorithm was an estimate of the daily time-weighted average respirator-corrected total NCO exposure (microg/m(3)). In general, these four metrics were found to be variable in agreement using measures such as weighted kappa and Spearman correlation. A logistic model for 10% drop in FEV(1) from Monday morning to Thursday morning was used to evaluate the utility of each exposure metric. The quantitative exposure metric was the most favorable, producing the best model fit, as well as the greatest strength and magnitude of association. This finding supports the reports of others that reducing exposure misclassification can improve risk estimates that otherwise would be biased toward the null. Although detailed and quantitative exposure assessment can be more time consuming and costly, it can improve exposure-disease evaluations and is more useful for risk assessment purposes. The task-based exposure modeling method successfully produced estimates of daily time-weighted average exposures in the complex and changing autobody shop work environment. The ambient TWA exposures of all of the office workers and technicians and 57% of the painters were found to be below the current U.K. Health and Safety Executive occupational exposure limit (OEL) for total NCO of 20 microg/m(3). When respirator use was incorporated, all personal daily exposures were below the U.K. OEL.

Incorporating approximation error in surrogate based Bayesian inversion

NASA Astrophysics Data System (ADS)

Zhang, J.; Zeng, L.; Li, W.; Wu, L.

2015-12-01

There are increasing interests in applying surrogates for inverse Bayesian modeling to reduce repetitive evaluations of original model. In this way, the computational cost is expected to be saved. However, the approximation error of surrogate model is usually overlooked. This is partly because that it is difficult to evaluate the approximation error for many surrogates. Previous studies have shown that, the direct combination of surrogates and Bayesian methods (e.g., Markov Chain Monte Carlo, MCMC) may lead to biased estimations when the surrogate cannot emulate the highly nonlinear original system. This problem can be alleviated by implementing MCMC in a two-stage manner. However, the computational cost is still high since a relatively large number of original model simulations are required. In this study, we illustrate the importance of incorporating approximation error in inverse Bayesian modeling. Gaussian process (GP) is chosen to construct the surrogate for its convenience in approximation error evaluation. Numerical cases of Bayesian experimental design and parameter estimation for contaminant source identification are used to illustrate this idea. It is shown that, once the surrogate approximation error is well incorporated into Bayesian framework, promising results can be obtained even when the surrogate is directly used, and no further original model simulations are required.

Systematic review: the effect on surrogates of making treatment decisions for others.

PubMed

Wendler, David; Rid, Annette

2011-03-01

Clinical practice relies on surrogates to make or help to make treatment decisions for incapacitated adults; however, the effect of this practice on surrogates has not been evaluated. To assess the effect on surrogates of making treatment decisions for adults who cannot make their own decisions. Empirical studies published in English and listed in MEDLINE, EMBASE, CINAHL, BIOETHICSLINE, PsycINFO, or Scopus before 1 July 2010. Eligible studies provided quantitative or qualitative empirical data, by evaluating surrogates, regarding the effect on surrogates of making treatment decisions for an incapacitated adult. Information on study location, number and type of surrogates, timing of data collection, type of decisions, patient setting, methods, main findings, and limitations. 40 studies, 29 using qualitative and 11 using quantitative methods, provided data on 2854 surrogates, more than one half of whom were family members of the patient. Most surrogates were surveyed several months to years after making treatment decisions, the majority of which were end-of-life decisions. The quantitative studies found that at least one third of surrogates experienced a negative emotional burden as the result of making treatment decisions. The qualitative studies reported that many or most surrogates experienced negative emotional burden. The negative effects on surrogates were often substantial and typically lasted months or, in some cases, years. The most common negative effects cited by surrogates were stress, guilt over the decisions they made, and doubt regarding whether they had made the right decisions. Nine of the 40 studies also reported beneficial effects on a few surrogates, the most common of which were supporting the patient and feeling a sense of satisfaction. Knowing which treatment is consistent with the patient's preferences was frequently cited as reducing the negative effect on surrogates. Thirty-two of the 40 articles reported data collected in the United States. Because the study populations were relatively homogenous, it is unclear whether the findings apply to other groups. In some cases, the effect of making treatment decisions could not be isolated from that of other stressors, such as grief or prognostic uncertainty. Nine of the studies had a response rate less than 50%, and 9 did not report a response rate. Many of the studies had a substantial interval between the treatment decisions and data collection. Making treatment decisions has a negative emotional effect on at least one third of surrogates, which is often substantial and typically lasts months (or sometimes years). Future research should evaluate ways to reduce this burden, including methods to identify which treatment options are consistent with the patient's preferences. National Institutes of Health.

Scramjet Fuel Injection Array Optimization Utilizing Mixed Variable Pattern Search With Kriging Surrogates

DTIC Science & Technology

2008-03-01

injector con- figurations for Scramjet applications.” International Journal of Heat and Mass Transfer 49: 3634–3644 (2006). 8. Anderson, C.D...Experimental Attainment of Optimal Conditions,” Journal of the Royal Statistical Society, B(13): 1–38, 1951. 19. Brewer, K.M. Exergy Methods for the Mission...second applies mvps to a new scramjet design in support of the Hypersonic International Flight Re- search Experimentation (hifire). The results

BECon: a tool for interpreting DNA methylation findings from blood in the context of brain.

PubMed

Edgar, R D; Jones, M J; Meaney, M J; Turecki, G; Kobor, M S

2017-08-01

Tissue differences are one of the largest contributors to variability in the human DNA methylome. Despite the tissue-specific nature of DNA methylation, the inaccessibility of human brain samples necessitates the frequent use of surrogate tissues such as blood, in studies of associations between DNA methylation and brain function and health. Results from studies of surrogate tissues in humans are difficult to interpret in this context, as the connection between blood-brain DNA methylation is tenuous and not well-documented. Here, we aimed to provide a resource to the community to aid interpretation of blood-based DNA methylation results in the context of brain tissue. We used paired samples from 16 individuals from three brain regions and whole blood, run on the Illumina 450 K Human Methylation Array to quantify the concordance of DNA methylation between tissues. From these data, we have made available metrics on: the variability of cytosine-phosphate-guanine dinucleotides (CpGs) in our blood and brain samples, the concordance of CpGs between blood and brain, and estimations of how strongly a CpG is affected by cell composition in both blood and brain through the web application BECon (Blood-Brain Epigenetic Concordance; https://redgar598.shinyapps.io/BECon/). We anticipate that BECon will enable biological interpretation of blood-based human DNA methylation results, in the context of brain.

Approximate entropy of human respiratory movement during eye-closed waking and different sleep stages.

PubMed

Burioka, Naoto; Cornélissen, Germaine; Halberg, Franz; Kaplan, Daniel T; Suyama, Hisashi; Sako, Takanori; Shimizu, Eiji

2003-01-01

The breath-to-breath variability of respiratory parameters changes with sleep stage. This study investigates any alteration in the approximate entropy (ApEn) of respiratory movement as a gauge of complexity in respiration, by stage of consciousness, in the light of putative brain interactions. Eight healthy men, who were between the ages of 23 and 29 years, were investigated. The signals of chest wall movement and EEG were recorded from 10:30 PM to 6:00 AM. After analog-to-digital conversion, the ApEn of respiratory movement (3 min) and EEG (20 s) were computed. Surrogate data were tested for nonlinearity in the original time series. The most impressive reduction in the ApEn of respiratory movement was associated with stage IV sleep, when the ApEn of the EEG was also statistically significantly decreased. A statistically significant linear relation is found between the ApEn of both variables. Surrogate data indicated that respiratory movement had nonlinear properties during all stages of consciousness that were investigated. Respiratory movement and EEG signals are more regular during stage IV sleep than during other stages of consciousness. The change in complexity described by the ApEn of respiration depends in part on the ApEn of the EEG, suggesting the involvement of nonlinear dynamic processes in the coordination between brain and lungs.

Uncertainty Quantification in CO 2 Sequestration Using Surrogate Models from Polynomial Chaos Expansion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yan; Sahinidis, Nikolaos V.

2013-03-06

In this paper, surrogate models are iteratively built using polynomial chaos expansion (PCE) and detailed numerical simulations of a carbon sequestration system. Output variables from a numerical simulator are approximated as polynomial functions of uncertain parameters. Once generated, PCE representations can be used in place of the numerical simulator and often decrease simulation times by several orders of magnitude. However, PCE models are expensive to derive unless the number of terms in the expansion is moderate, which requires a relatively small number of uncertain variables and a low degree of expansion. To cope with this limitation, instead of using amore » classical full expansion at each step of an iterative PCE construction method, we introduce a mixed-integer programming (MIP) formulation to identify the best subset of basis terms in the expansion. This approach makes it possible to keep the number of terms small in the expansion. Monte Carlo (MC) simulation is then performed by substituting the values of the uncertain parameters into the closed-form polynomial functions. Based on the results of MC simulation, the uncertainties of injecting CO{sub 2} underground are quantified for a saline aquifer. Moreover, based on the PCE model, we formulate an optimization problem to determine the optimal CO{sub 2} injection rate so as to maximize the gas saturation (residual trapping) during injection, and thereby minimize the chance of leakage.« less

Oxygen diffusion and consumption in extracellular matrix gels: implications for designing three-dimensional cultures.

PubMed

Colom, Adai; Galgoczy, Roland; Almendros, Isaac; Xaubet, Antonio; Farré, Ramon; Alcaraz, Jordi

2014-08-01

Three-dimensional (3D) cultures are increasingly used as tissue surrogates to study many physiopathological processes. However, to what extent current 3D culture protocols provide physiologic oxygen tension conditions remains ill defined. To address this limitation, oxygen tension was measured in a panel of acellular or cellularized extracellular matrix (ECM) gels with A549 cells, and analyzed in terms of oxygen diffusion and consumption. Gels included reconstituted basement membrane, fibrin and collagen. Oxygen diffusivity in acellular gels was up to 40% smaller than that of water, and the lower values were observed in the denser gels. In 3D cultures, physiologic oxygen tension was achieved after 2 days in dense (≥3 mg/mL) but not sparse gels, revealing that the latter gels are not suitable tissue surrogates in terms of oxygen distribution. In dense gels, we observed a dominant effect of ECM composition over density in oxygen consumption. All diffusion and consumption data were used in a simple model to estimate ranges for gel thickness, seeding density and time-window that may support physiologic oxygen tension. Thus, we identified critical variables for oxygen tension in ECM gels, and introduced a model to assess initial values of these variables, which may short-cut the optimization step of 3D culture studies. © 2013 Wiley Periodicals, Inc.

Challenge of surrogate endpoints.

PubMed

Furgerson, James L; Hannah, William N; Thompson, Jennifer C

2012-03-01

Surrogate endpoints are biomarkers that are intended to substitute for clinical endpoints. They have been used to find novel therapeutic targets, improve the statistical power and shorten the duration of clinical trials, and control the cost of conducting research studies. The more generalized use of surrogate endpoints in clinical decision making can be hazardous and should be undertaken with great caution. This article reviews prior work with surrogate endpoints and highlights caveats and lessons learned from studies using surrogate endpoints.

Statistical evaluation of surrogate endpoints with examples from cancer clinical trials.

PubMed

Buyse, Marc; Molenberghs, Geert; Paoletti, Xavier; Oba, Koji; Alonso, Ariel; Van der Elst, Wim; Burzykowski, Tomasz

2016-01-01

A surrogate endpoint is intended to replace a clinical endpoint for the evaluation of new treatments when it can be measured more cheaply, more conveniently, more frequently, or earlier than that clinical endpoint. A surrogate endpoint is expected to predict clinical benefit, harm, or lack of these. Besides the biological plausibility of a surrogate, a quantitative assessment of the strength of evidence for surrogacy requires the demonstration of the prognostic value of the surrogate for the clinical outcome, and evidence that treatment effects on the surrogate reliably predict treatment effects on the clinical outcome. We focus on these two conditions, and outline the statistical approaches that have been proposed to assess the extent to which these conditions are fulfilled. When data are available from a single trial, one can assess the "individual level association" between the surrogate and the true endpoint. When data are available from several trials, one can additionally assess the "trial level association" between the treatment effect on the surrogate and the treatment effect on the true endpoint. In the latter case, the "surrogate threshold effect" can be estimated as the minimum effect on the surrogate endpoint that predicts a statistically significant effect on the clinical endpoint. All these concepts are discussed in the context of randomized clinical trials in oncology, and illustrated with two meta-analyses in gastric cancer. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The long-term experiences of surrogates: relationships and contact with surrogacy families in genetic and gestational surrogacy arrangements.

PubMed

Imrie, Susan; Jadva, Vasanti

2014-10-01

This study examined the contact arrangements and relationships between surrogates and surrogacy families and whether these outcomes differed according to the type of surrogacy undertaken. Surrogates' motivations for carrying out multiple surrogacy arrangements were also examined, and surrogates' psychological health was assessed. Semi-structured interviews were administered to 34 women who had given birth to a child conceived through surrogacy approximately 7 years prior to interview. Some surrogates had carried out multiple surrogacy arrangements, and data were collected on the frequency, type of contact, and surrogate's feelings about the level of contact in each surrogacy arrangement, the surrogate's relationship with each child and parent, and her experience of, and motivation for, each surrogacy. Questionnaire measures of psychological health were administered. Surrogates had completed a total of 102 surrogacy arrangements and remained in contact with the majority of families, and reported positive relationships in most cases. Surrogates were happy with their level of contact in the majority of arrangements and most were viewed as positive experiences. Few differences were found according to surrogacy type. The primary motivation given for multiple surrogacy arrangements was to help couples have a sibling for an existing child. Most surrogates showed no psychological health problems at the time of data collection. Copyright © 2014 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

The Limits of Surrogates' Moral Authority and Physician Professionalism: Can the Paradigm of Palliative Sedation Be Instructive?

PubMed

Berger, Jeffrey T

2017-01-01

With narrow exception, physicians' treatment of incapacitated patients requires the consent of health surrogates. Although the decision-making authority of surrogates is appropriately broad, their moral authority is not without limits. Discerning these bounds is particularly germane to ethically complex treatments and has important implications for the welfare of patients, for the professional integrity of clinicians, and, in fact, for the welfare of surrogates. Palliative sedation is one such complex treatment; as such, it provides a valuable model for analyzing the scope of surrogates' moral authority. Guidelines for palliative sedation that present it as a "last-resort" treatment for severe and intractable suffering yet require surrogate consent in order to offer it are ethically untenable, precisely because the moral limits of surrogate authority have not been considered. © 2017 The Hastings Center.

Bayesian Adaptive Trial Design for a Newly Validated Surrogate Endpoint

PubMed Central

Renfro, Lindsay A.; Carlin, Bradley P.; Sargent, Daniel J.

2011-01-01

Summary The evaluation of surrogate endpoints for primary use in future clinical trials is an increasingly important research area, due to demands for more efficient trials coupled with recent regulatory acceptance of some surrogates as ‘valid.’ However, little consideration has been given to how a trial which utilizes a newly-validated surrogate endpoint as its primary endpoint might be appropriately designed. We propose a novel Bayesian adaptive trial design that allows the new surrogate endpoint to play a dominant role in assessing the effect of an intervention, while remaining realistically cautious about its use. By incorporating multi-trial historical information on the validated relationship between the surrogate and clinical endpoints, then subsequently evaluating accumulating data against this relationship as the new trial progresses, we adaptively guard against an erroneous assessment of treatment based upon a truly invalid surrogate. When the joint outcomes in the new trial seem plausible given similar historical trials, we proceed with the surrogate endpoint as the primary endpoint, and do so adaptively–perhaps stopping the trial for early success or inferiority of the experimental treatment, or for futility. Otherwise, we discard the surrogate and switch adaptive determinations to the original primary endpoint. We use simulation to test the operating characteristics of this new design compared to a standard O’Brien-Fleming approach, as well as the ability of our design to discriminate trustworthy from untrustworthy surrogates in hypothetical future trials. Furthermore, we investigate possible benefits using patient-level data from 18 adjuvant therapy trials in colon cancer, where disease-free survival is considered a newly-validated surrogate endpoint for overall survival. PMID:21838811

A multi-fidelity framework for physics based rotor blade simulation and optimization

NASA Astrophysics Data System (ADS)

Collins, Kyle Brian

New helicopter rotor designs are desired that offer increased efficiency, reduced vibration, and reduced noise. Rotor Designers in industry need methods that allow them to use the most accurate simulation tools available to search for these optimal designs. Computer based rotor analysis and optimization have been advanced by the development of industry standard codes known as "comprehensive" rotorcraft analysis tools. These tools typically use table look-up aerodynamics, simplified inflow models and perform aeroelastic analysis using Computational Structural Dynamics (CSD). Due to the simplified aerodynamics, most design studies are performed varying structural related design variables like sectional mass and stiffness. The optimization of shape related variables in forward flight using these tools is complicated and results are viewed with skepticism because rotor blade loads are not accurately predicted. The most accurate methods of rotor simulation utilize Computational Fluid Dynamics (CFD) but have historically been considered too computationally intensive to be used in computer based optimization, where numerous simulations are required. An approach is needed where high fidelity CFD rotor analysis can be utilized in a shape variable optimization problem with multiple objectives. Any approach should be capable of working in forward flight in addition to hover. An alternative is proposed and founded on the idea that efficient hybrid CFD methods of rotor analysis are ready to be used in preliminary design. In addition, the proposed approach recognizes the usefulness of lower fidelity physics based analysis and surrogate modeling. Together, they are used with high fidelity analysis in an intelligent process of surrogate model building of parameters in the high fidelity domain. Closing the loop between high and low fidelity analysis is a key aspect of the proposed approach. This is done by using information from higher fidelity analysis to improve predictions made with lower fidelity models. This thesis documents the development of automated low and high fidelity physics based rotor simulation frameworks. The low fidelity framework uses a comprehensive code with simplified aerodynamics. The high fidelity model uses a parallel processor capable CFD/CSD methodology. Both low and high fidelity frameworks include an aeroacoustic simulation for prediction of noise. A synergistic process is developed that uses both the low and high fidelity frameworks together to build approximate models of important high fidelity metrics as functions of certain design variables. To test the process, a 4-bladed hingeless rotor model is used as a baseline. The design variables investigated include tip geometry and spanwise twist distribution. Approximation models are built for metrics related to rotor efficiency and vibration using the results from 60+ high fidelity (CFD/CSD) experiments and 400+ low fidelity experiments. Optimization using the approximation models found the Pareto Frontier anchor points, or the design having maximum rotor efficiency and the design having minimum vibration. Various Pareto generation methods are used to find designs on the frontier between these two anchor designs. When tested in the high fidelity framework, the Pareto anchor designs are shown to be very good designs when compared with other designs from the high fidelity database. This provides evidence that the process proposed has merit. Ultimately, this process can be utilized by industry rotor designers with their existing tools to bring high fidelity analysis into the preliminary design stage of rotors. In conclusion, the methods developed and documented in this thesis have made several novel contributions. First, an automated high fidelity CFD based forward flight simulation framework has been built for use in preliminary design optimization. The framework was built around an integrated, parallel processor capable CFD/CSD/AA process. Second, a novel method of building approximate models of high fidelity parameters has been developed. The method uses a combination of low and high fidelity results and combines Design of Experiments, statistical effects analysis, and aspects of approximation model management. And third, the determination of rotor blade shape variables through optimization using CFD based analysis in forward flight has been performed. This was done using the high fidelity CFD/CSD/AA framework and method mentioned above. While the low and high fidelity predictions methods used in the work still have inaccuracies that can affect the absolute levels of the results, a framework has been successfully developed and demonstrated that allows for an efficient process to improve rotor blade designs in terms of a selected choice of objective function(s). Using engineering judgment, this methodology could be applied today to investigate opportunities to improve existing designs. With improvements in the low and high fidelity prediction components that will certainly occur, this framework could become a powerful tool for future rotorcraft design work. (Abstract shortened by UMI.)

Surrogate Plant Data Base : Volume 1. Introduction, Appendix A : The Development of Surrogate Plant Data ; Appendix B : Application of the Surrogate .

DOT National Transportation Integrated Search

1983-03-01

This four volume report consists of a data base describing "surrogate" automobile and truck manufacturing plants developed as part of a methodology for evaluating capital investment requirements in new manufacturing facilities to build new fleets of ...

26 CFR 1.7874-2T - Surrogate foreign corporation (temporary).

Code of Federal Regulations, 2012 CFR

2012-04-01

... 26 Internal Revenue 13 2012-04-01 2012-04-01 false Surrogate foreign corporation (temporary). 1... Surrogate foreign corporation (temporary). (a) Scope. This section provides rules for determining whether a foreign corporation shall be treated as a surrogate foreign corporation under section 7874(a)(2)(B...

26 CFR 1.7874-2T - Surrogate foreign corporation (temporary).

Code of Federal Regulations, 2011 CFR

2011-04-01

... 26 Internal Revenue 13 2011-04-01 2011-04-01 false Surrogate foreign corporation (temporary). 1... Surrogate foreign corporation (temporary). (a) Scope. This section provides rules for determining whether a foreign corporation shall be treated as a surrogate foreign corporation under section 7874(a)(2)(B...

34 CFR 300.519 - Surrogate parents.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) Surrogate parent responsibilities. The surrogate parent may represent the child in all matters relating to... DISABILITIES Procedural Safeguards Due Process Procedures for Parents and Children § 300.519 Surrogate parents..., cannot locate a parent; (3) The child is a ward of the State under the laws of that State; or (4) The...

34 CFR 300.519 - Surrogate parents.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) Surrogate parent responsibilities. The surrogate parent may represent the child in all matters relating to... DISABILITIES Procedural Safeguards Due Process Procedures for Parents and Children § 300.519 Surrogate parents..., cannot locate a parent; (3) The child is a ward of the State under the laws of that State; or (4) The...

34 CFR 300.519 - Surrogate parents.

Code of Federal Regulations, 2012 CFR

2012-07-01

...) Surrogate parent responsibilities. The surrogate parent may represent the child in all matters relating to... DISABILITIES Procedural Safeguards Due Process Procedures for Parents and Children § 300.519 Surrogate parents..., cannot locate a parent; (3) The child is a ward of the State under the laws of that State; or (4) The...

34 CFR 300.519 - Surrogate parents.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) Surrogate parent responsibilities. The surrogate parent may represent the child in all matters relating to... DISABILITIES Procedural Safeguards Due Process Procedures for Parents and Children § 300.519 Surrogate parents..., cannot locate a parent; (3) The child is a ward of the State under the laws of that State; or (4) The...

34 CFR 300.519 - Surrogate parents.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) Surrogate parent responsibilities. The surrogate parent may represent the child in all matters relating to... DISABILITIES Procedural Safeguards Due Process Procedures for Parents and Children § 300.519 Surrogate parents..., cannot locate a parent; (3) The child is a ward of the State under the laws of that State; or (4) The...

Performance evaluation of contrast-detail in full field digital mammography systems using ideal (Hotelling) observer vs. conventional automated analysis of CDMAM images for quality control of contrast-detail characteristics.

PubMed

Delakis, Ioannis; Wise, Robert; Morris, Lauren; Kulama, Eugenia

2015-11-01

The purpose of this work was to evaluate the contrast-detail performance of full field digital mammography (FFDM) systems using ideal (Hotelling) observer Signal-to-Noise Ratio (SNR) methodology and ascertain whether it can be considered an alternative to the conventional, automated analysis of CDMAM phantom images. Five FFDM units currently used in the national breast screening programme were evaluated, which differed with respect to age, detector, Automatic Exposure Control (AEC) and target/filter combination. Contrast-detail performance was analysed using CDMAM and ideal observer SNR methodology. The ideal observer SNR was calculated for input signal originating from gold discs of varying thicknesses and diameters, and then used to estimate the threshold gold thickness for each diameter as per CDMAM analysis. The variability of both methods and the dependence of CDMAM analysis on phantom manufacturing discrepancies also investigated. Results from both CDMAM and ideal observer methodologies were informative differentiators of FFDM systems' contrast-detail performance, displaying comparable patterns with respect to the FFDM systems' type and age. CDMAM results suggested higher threshold gold thickness values compared with the ideal observer methodology, especially for small-diameter details, which can be attributed to the behaviour of the CDMAM phantom used in this study. In addition, ideal observer methodology results showed lower variability than CDMAM results. The Ideal observer SNR methodology can provide a useful metric of the FFDM systems' contrast detail characteristics and could be considered a surrogate for conventional, automated analysis of CDMAM images. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Are outcomes reported in surgical randomized trials patient-important? A systematic review and meta-analysis

PubMed Central

Adie, Sam; Harris, Ian A.; Naylor, Justine M.; Mittal, Rajat

2017-01-01

Background The dangers of using surrogate outcomes are well documented. They may have little or no association with their patient-important correlates, leading to the approval and use of interventions that lack efficacy. We sought to assess whether primary outcomes in surgical randomized controlled trials (RCTs) are more likely to be patient-important outcomes than surrogate or laboratory-based outcomes. Methods We reviewed RCTs assessing an operative intervention published in 2008 and 2009 and indexed in MEDLINE, EMBASE or the Cochrane Central Register of Controlled Trials. After a pilot of the selection criteria, 1 reviewer selected trials and another reviewer checked the selection. We extracted information on outcome characteristics (patient-important, surrogate, or laboratory-based outcome) and whether they were primary or secondary outcomes. We calculated odds ratios (OR) and pooled in random-effects meta-analysis to obtain an overall estimate of the association between patient importance and primary outcome specification. Results In 350 included RCTs, a total of 8258 outcomes were reported (median 18 per trial. The mean proportion (per trial) of patient-important outcomes was 60%, and 66% of trials specified a patient-important primary outcome. The most commonly reported patient-important primary outcomes were morbid events (41%), intervention outcomes (11%), function (11%) and pain (9%). Surrogate and laboratory-based primary outcomes were reported in 33% and 8% of trials, respectively. Patient-important outcomes were not associated with primary outcome status (OR 0.82, 95% confidence interval 0.63–1.1, I2 = 21%). Conclusion A substantial proportion of surgical RCTs specify primary outcomes that are not patient-important. Authors, journals and trial funders should insist that patient-important outcomes are the focus of study. PMID:28234219

From the closest observers of patient care: a thematic analysis of online narrative reviews of hospitals.

PubMed

Bardach, Naomi S; Lyndon, Audrey; Asteria-Peñaloza, Renée; Goldman, L Elizabeth; Lin, Grace A; Dudley, R Adams

2016-11-01

Patient-centred care has become a priority in many countries. It is unknown whether current tools capture aspects of care patients and their surrogates consider important. We investigated whether online narrative reviews from patients and surrogates reflect domains in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) and we described additional potential domains. We used thematic analysis to assess online narrative reviews for reference to HCAHPS domains and salient non-HCAHPS domains and compared results by reviewer type (patient vs surrogate). We identified hospitals for review from the American Hospital Association database using a stratified random sampling approach. This approach ensured inclusion of reviews of a diverse set of hospitals. We searched online in February 2013 for narrative reviews from any source for each hospital. We included up to two narrative reviews for each hospital. Outpatient or emergency department reviews, reviews from self-identified hospital employees, or reviews of <10 words. 50.0% (n=122) of reviews (N=244) were from patients and 38.1% (n=93) from friends or family members. Only 57.0% (n=139) of reviews mentioned any HCAHPS domain. Additional salient domains were: Financing, including unexpected out-of-pocket costs and difficult interactions with billing departments; system-centred care; and perceptions of safety. These domains were mentioned in 51.2% (n=125) of reviews. Friends and family members commented on perceptions of safety more frequently than patients. A substantial proportion of consumer reviews do not mention HCAHPS domains. Surrogates appear to observe care differently than patients, particularly around safety. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Use of habitats as surrogates of biodiversity for efficient coral reef conservation planning in Pacific Ocean islands.

PubMed

Dalleau, Mayeul; Andréfouët, Serge; Wabnitz, Colette C C; Payri, Claude; Wantiez, Laurent; Pichon, Michel; Friedman, Kim; Vigliola, Laurent; Benzoni, Francesca

2010-04-01

Marine protected areas (MPAs) have been highlighted as a means toward effective conservation of coral reefs. New strategies are required to more effectively select MPA locations and increase the pace of their implementation. Many criteria exist to design MPA networks, but generally, it is recommended that networks conserve a diversity of species selected for, among other attributes, their representativeness, rarity, or endemicity. Because knowledge of species' spatial distribution remains scarce, efficient surrogates are urgently needed. We used five different levels of habitat maps and six spatial scales of analysis to identify under which circumstances habitat data used to design MPA networks for Wallis Island provided better representation of species than random choice alone. Protected-area site selections were derived from a rarity-complementarity algorithm. Habitat surrogacy was tested for commercial fish species, all fish species, commercially harvested invertebrates, corals, and algae species. Efficiency of habitat surrogacy varied by species group, type of habitat map, and spatial scale of analysis. Maps with the highest habitat thematic complexity provided better surrogates than simpler maps and were more robust to changes in spatial scales. Surrogates were most efficient for commercial fishes, corals, and algae but not for commercial invertebrates. Conversely, other measurements of species-habitat associations, such as richness congruence and composition similarities provided weak results. We provide, in part, a habitat-mapping methodology for designation of MPAs for Pacific Ocean islands that are characterized by habitat zonations similar to Wallis. Given the increasing availability and affordability of space-borne imagery to map habitats, our approach could appreciably facilitate and improve current approaches to coral reef conservation and enhance MPA implementation.

Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints.

PubMed

Renfro, Lindsay A; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J

2014-10-01

Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer.

Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints

PubMed Central

Renfro, Lindsay A.; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J.

2014-01-01

Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer. PMID:25061255

An imprecise probability approach for squeal instability analysis based on evidence theory

NASA Astrophysics Data System (ADS)

Lü, Hui; Shangguan, Wen-Bin; Yu, Dejie

2017-01-01

An imprecise probability approach based on evidence theory is proposed for squeal instability analysis of uncertain disc brakes in this paper. First, the squeal instability of the finite element (FE) model of a disc brake is investigated and its dominant unstable eigenvalue is detected by running two typical numerical simulations, i.e., complex eigenvalue analysis (CEA) and transient dynamical analysis. Next, the uncertainty mainly caused by contact and friction is taken into account and some key parameters of the brake are described as uncertain parameters. All these uncertain parameters are usually involved with imprecise data such as incomplete information and conflict information. Finally, a squeal instability analysis model considering imprecise uncertainty is established by integrating evidence theory, Taylor expansion, subinterval analysis and surrogate model. In the proposed analysis model, the uncertain parameters with imprecise data are treated as evidence variables, and the belief measure and plausibility measure are employed to evaluate system squeal instability. The effectiveness of the proposed approach is demonstrated by numerical examples and some interesting observations and conclusions are summarized from the analyses and discussions. The proposed approach is generally limited to the squeal problems without too many investigated parameters. It can be considered as a potential method for squeal instability analysis, which will act as the first step to reduce squeal noise of uncertain brakes with imprecise information.

Approximation of personal exposure to fine particulate matters (PM2.5) during cooking using solid biomass fuels in the kitchens of rural West Bengal, India.

PubMed

Nayek, Sukanta; Padhy, Pratap Kumar

2018-06-01

More than 85% of the rural Indian households use traditional solid biofuels (SBFs) for daily cooking. Burning of the easily available unprocessed solid fuels in inefficient earthen cooking stoves produce large quantities of particulate matters. Smaller particulates, especially with aerodynamic diameter of 2.5 μm or less (PM 2.5 ), largely generated during cooking, are considered to be health damaging in nature. In the present study, kitchen level exposure of women cooks to fine particulate matters during lunch preparation was assessed considering kitchen openness as surrogate to the ventilation condition. Two-way ANCOVA analysis considering meal quantity as a covariate revealed no significant interaction between the openness and the seasons explaining the variability of the personal exposure to the fine particulate matters in rural kitchen during cooking. Multiple linear regression analysis revealed the openness as the only significant predictor for personal exposure to the fine particulate matters. In the present study, the annual average fine particulate matter exposure concentration was found to be 974 μg m -3 .

Eutrophication risk assessment in coastal embayments using simple statistical models.

PubMed

Arhonditsis, G; Eleftheriadou, M; Karydis, M; Tsirtsis, G

2003-09-01

A statistical methodology is proposed for assessing the risk of eutrophication in marine coastal embayments. The procedure followed was the development of regression models relating the levels of chlorophyll a (Chl) with the concentration of the limiting nutrient--usually nitrogen--and the renewal rate of the systems. The method was applied in the Gulf of Gera, Island of Lesvos, Aegean Sea and a surrogate for renewal rate was created using the Canberra metric as a measure of the resemblance between the Gulf and the oligotrophic waters of the open sea in terms of their physical, chemical and biological properties. The Chl-total dissolved nitrogen-renewal rate regression model was the most significant, accounting for 60% of the variation observed in Chl. Predicted distributions of Chl for various combinations of the independent variables, based on Bayesian analysis of the models, enabled comparison of the outcomes of specific scenarios of interest as well as further analysis of the system dynamics. The present statistical approach can be used as a methodological tool for testing the resilience of coastal ecosystems under alternative managerial schemes and levels of exogenous nutrient loading.