WorldWideScience

Sample records for survival models adjusting

  1. Modelling survival

    DEFF Research Database (Denmark)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight

    2016-01-01

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test...

  2. A comparative evaluation of risk-adjustment models for benchmarking amputation-free survival after lower extremity bypass.

    Science.gov (United States)

    Simons, Jessica P; Goodney, Philip P; Flahive, Julie; Hoel, Andrew W; Hallett, John W; Kraiss, Larry W; Schanzer, Andres

    2016-04-01

    Providing patients and payers with publicly reported risk-adjusted quality metrics for the purpose of benchmarking physicians and institutions has become a national priority. Several prediction models have been developed to estimate outcomes after lower extremity revascularization for critical limb ischemia, but the optimal model to use in contemporary practice has not been defined. We sought to identify the highest-performing risk-adjustment model for amputation-free survival (AFS) at 1 year after lower extremity bypass (LEB). We used the national Society for Vascular Surgery Vascular Quality Initiative (VQI) database (2003-2012) to assess the performance of three previously validated risk-adjustment models for AFS. The Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL), Finland National Vascular (FINNVASC) registry, and the modified Project of Ex-vivo vein graft Engineering via Transfection III (PREVENT III [mPIII]) risk scores were applied to the VQI cohort. A novel model for 1-year AFS was also derived using the VQI data set and externally validated using the PIII data set. The relative discrimination (Harrell c-index) and calibration (Hosmer-May goodness-of-fit test) of each model were compared. Among 7754 patients in the VQI who underwent LEB for critical limb ischemia, the AFS was 74% at 1 year. Each of the previously published models for AFS demonstrated similar discriminative performance: c-indices for BASIL, FINNVASC, mPIII were 0.66, 0.60, and 0.64, respectively. The novel VQI-derived model had improved discriminative ability with a c-index of 0.71 and appropriate generalizability on external validation with a c-index of 0.68. The model was well calibrated in both the VQI and PIII data sets (goodness of fit P = not significant). Currently available prediction models for AFS after LEB perform modestly when applied to national contemporary VQI data. Moreover, the performance of each model was inferior to that of the novel VQI-derived model

  3. Covariate-adjusted measures of discrimination for survival data

    DEFF Research Database (Denmark)

    White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth

    2015-01-01

    by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...... statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators......, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were...

  4. Convexity Adjustments for ATS Models

    DEFF Research Database (Denmark)

    Murgoci, Agatha; Gaspar, Raquel M.

    . As a result we classify convexity adjustments into forward adjustments and swaps adjustments. We, then, focus on affine term structure (ATS) models and, in this context, conjecture convexity adjustments should be related of affine functionals. In the case of forward adjustments, we show how to obtain exact...

  5. Radiobilogical cell survival models

    International Nuclear Information System (INIS)

    Zackrisson, B.

    1992-01-01

    A central issue in clinical radiobiological research is the prediction of responses to different radiation qualities. The choice of cell survival and dose-response model greatly influences the results. In this context the relationship between theory and model is emphasized. Generally, the interpretations of experimental data depend on the model. Cell survival models are systematized with respect to their relations to radiobiological theories of cell kill. The growing knowlegde of biological, physical, and chemical mechanisms is reflected in the formulation of new models. The present overview shows that recent modelling has been more oriented towards the stochastic fluctuations connected to radiation energy deposition. This implies that the traditional cell surivival models ought to be complemented by models of stochastic energy deposition processes and repair processes at the intracellular level. (orig.)

  6. Adjustment Criterion and Algorithm in Adjustment Model with Uncertain

    Directory of Open Access Journals (Sweden)

    SONG Yingchun

    2015-02-01

    Full Text Available Uncertainty often exists in the process of obtaining measurement data, which affects the reliability of parameter estimation. This paper establishes a new adjustment model in which uncertainty is incorporated into the function model as a parameter. A new adjustment criterion and its iterative algorithm are given based on uncertainty propagation law in the residual error, in which the maximum possible uncertainty is minimized. This paper also analyzes, with examples, the different adjustment criteria and features of optimal solutions about the least-squares adjustment, the uncertainty adjustment and total least-squares adjustment. Existing error theory is extended with new observational data processing method about uncertainty.

  7. Risk-adjusted survival after tissue versus mechanical aortic valve replacement: a 23-year assessment.

    Science.gov (United States)

    Gaca, Jeffrey G; Clare, Robert M; Rankin, J Scott; Daneshmand, Mani A; Milano, Carmelo A; Hughes, G Chad; Wolfe, Walter G; Glower, Donald D; Smith, Peter K

    2013-11-01

    Detailed analyses of risk-adjusted outcomes after mitral valve surgery have documented significant survival decrements with tissue valves at any age. Several recent studies of prosthetic aortic valve replacement (AVR) also have suggested a poorer performance of tissue valves, although analyses have been limited to small matched series. The study aim was to test the hypothesis that AVR with tissue valves is associated with a lower risk-adjusted survival, as compared to mechanical valves. Between 1986 and 2009, primary isolated AVR, with or without coronary artery bypass grafting (CABG), was performed with currently available valve types in 2148 patients (1108 tissue valves, 1040 mechanical). Patients were selected for tissue valves to be used primarily in the elderly. Baseline and operative characteristics were documented prospectively with a consistent variable set over the entire 23-year period. Follow up was obtained with mailed questionnaires, supplemented by National Death Index searches. The average time to death or follow up was seven years, and follow up for survival was 96.2% complete. Risk-adjusted survival characteristics for the two groups were evaluated using a Cox proportional hazards model with stepwise selection of candidate variables. Differences in baseline characteristics between groups were (tissue versus mechanical): median age 73 versus 61 years; non-elective surgery 32% versus 28%; CABG 45% versus 35%; median ejection fraction 55% versus 55%; renal failure 6% versus 1%; diabetes 18% versus 7% (pvalves; however, after risk adjustment for the adverse profiles of tissue valve patients, no significant difference was observed in survival after tissue or mechanical AVR. Thus, the hypothesis did not hold, and risk-adjusted survival was equivalent, of course qualified by the fact that selection bias was evident. With selection criteria that employed tissue AVR more frequently in elderly patients, tissue and mechanical valves achieved similar survival

  8. Survival analysis models and applications

    CERN Document Server

    Liu, Xian

    2012-01-01

    Survival analysis concerns sequential occurrences of events governed by probabilistic laws.  Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis.Assumes only a minimal knowledge of SAS whilst enablin

  9. Probabilistic Survivability Versus Time Modeling

    Science.gov (United States)

    Joyner, James J., Sr.

    2016-01-01

    This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.

  10. Adjustment or updating of models

    Indian Academy of Sciences (India)

    25, Part 3, June 2000, pp. 235±245 ... While the model is defined in terms of these spatial parameters, ... discussed in terms of `model order' with concern focused on whether or not the ..... In other words, it is not easy to justify what the required.

  11. Adjustment model of thermoluminescence experimental data

    International Nuclear Information System (INIS)

    Moreno y Moreno, A.; Moreno B, A.

    2002-01-01

    This model adjusts the experimental results for thermoluminescence according to the equation: I (T) = I (a i * exp (-1/b i * (T-C i )) where: a i , b i , c i are the i-Th peak adjusted to a gaussian curve. The adjustments of the curve can be operated manual or analytically using the macro function and the solver.xla complement installed previously in the computational system. In this work it is shown: 1. The information of experimental data from a LiF curve obtained from the Physics Institute of UNAM which the data adjustment model is operated in the macro type. 2. A LiF curve of four peaks obtained from Harshaw information simulated in Microsoft Excel, discussed in previous works, as a reference not in macro. (Author)

  12. Extendable linearised adjustment model for deformation analysis

    NARCIS (Netherlands)

    Hiddo Velsink

    2015-01-01

    Author supplied: "This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices

  13. Extendable linearised adjustment model for deformation analysis

    NARCIS (Netherlands)

    Velsink, H.

    2015-01-01

    This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices and correlation

  14. Long-Term Survival, Quality of Life, and Quality-Adjusted Survival in Critically Ill Patients With Cancer.

    Science.gov (United States)

    Normilio-Silva, Karina; de Figueiredo, Adelaide Cristina; Pedroso-de-Lima, Antonio Carlos; Tunes-da-Silva, Gisela; Nunes da Silva, Adriana; Delgado Dias Levites, Andresa; de-Simone, Ana Tereza; Lopes Safra, Patrícia; Zancani, Roberta; Tonini, Paula Camilla; Vasconcelos de Andrade E Silva, Ulysses; Buosi Silva, Thiago; Martins Giorgi, Juliana; Eluf-Neto, José; Costa, Anderson; Abrahão Hajjar, Ludhmila; Biasi Cavalcanti, Alexandre

    2016-07-01

    To assess the long-term survival, health-related quality of life, and quality-adjusted life years of cancer patients admitted to ICUs. Prospective cohort. Two cancer specialized ICUs in Brazil. A total of 792 participants. None. The health-related quality of life before ICU admission; at 15 days; and at 3, 6, 12, and 18 months was assessed with the EQ-5D-3L. In addition, the vital status was assessed at 24 months. The mean age of the subjects was 61.6 ± 14.3 years, 42.5% were female subjects and half were admitted after elective surgery. The mean Simplified Acute Physiology Score 3 was 47.4 ± 15.6. Survival at 12 and 18 months was 42.4% and 38.1%, respectively. The mean EQ-5D-3L utility measure before admission to the ICU was 0.47 ± 0.43, at 15 days it was 0.41 ± 0.44, at 90 days 0.56 ± 0.42, at 6 months 0.60 ± 0.41, at 12 months 0.67 ± 0.35, and at 18 months 0.67 ± 0.35. The probabilities for attaining 12 and 18 months of quality-adjusted survival were 30.1% and 19.1%, respectively. There were statistically significant differences in survival time and quality-adjusted life years according to all assessed baseline characteristics (ICU admission after elective surgery, emergency surgery, or medical admission; Simplified Acute Physiology Score 3; cancer extension; cancer status; previous surgery; previous chemotherapy; previous radiotherapy; performance status; and previous health-related quality of life). Only the previous health-related quality of life and performance status were associated with the health-related quality of life during the 18-month follow-up. Long-term survival, health-related quality of life, and quality-adjusted life year expectancy of cancer patients admitted to the ICU are limited. Nevertheless, these clinical outcomes exhibit wide variability among patients and are associated with simple characteristics present at the time of ICU admission, which may help healthcare professionals estimate patients

  15. Premium adjustment: actuarial analysis on epidemiological models ...

    African Journals Online (AJOL)

    In this paper, we analyse insurance premium adjustment in the context of an epidemiological model where the insurer's future financial liability is greater than the premium from patients. In this situation, it becomes extremely difficult for the insurer since a negative reserve would severely increase its risk of insolvency, ...

  16. Life-Cycle Models for Survivable Systems

    National Research Council Canada - National Science Library

    Linger, Richard

    2002-01-01

    .... Current software development life-cycle models are not focused on creating survivable systems, and exhibit shortcomings when the goal is to develop systems with a high degree of assurance of survivability...

  17. OPEC model : adjustment or new model

    International Nuclear Information System (INIS)

    Ayoub, A.

    1994-01-01

    Since the early eighties, the international oil industry went through major changes : new financial markets, reintegration, opening of the upstream, liberalization of investments, privatization. This article provides answers to two major questions : what are the reasons for these changes ? ; do these changes announce the replacement of OPEC model by a new model in which state intervention is weaker and national companies more autonomous. This would imply a profound change of political and institutional systems of oil producing countries. (Author)

  18. Survivability Assessment: Modeling A Recovery Process

    OpenAIRE

    Paputungan, Irving Vitra; Abdullah, Azween

    2009-01-01

    Survivability is the ability of a system to continue operating, in a timely manner, in the presence ofattacks, failures, or accidents. Recovery in survivability is a process of a system to heal or recover from damageas early as possible to fulfill its mission as condition permit. In this paper, we show a preliminary recoverymodel to enhance the system survivability. The model focuses on how we preserve the system and resumes itscritical service under attacks as soon as possible.Keywords: surv...

  19. Player Modeling for Intelligent Difficulty Adjustment

    Science.gov (United States)

    Missura, Olana; Gärtner, Thomas

    In this paper we aim at automatically adjusting the difficulty of computer games by clustering players into different types and supervised prediction of the type from short traces of gameplay. An important ingredient of video games is to challenge players by providing them with tasks of appropriate and increasing difficulty. How this difficulty should be chosen and increase over time strongly depends on the ability, experience, perception and learning curve of each individual player. It is a subjective parameter that is very difficult to set. Wrong choices can easily lead to players stopping to play the game as they get bored (if underburdened) or frustrated (if overburdened). An ideal game should be able to adjust its difficulty dynamically governed by the player’s performance. Modern video games utilise a game-testing process to investigate among other factors the perceived difficulty for a multitude of players. In this paper, we investigate how machine learning techniques can be used for automatic difficulty adjustment. Our experiments confirm the potential of machine learning in this application.

  20. On adjustment for auxiliary covariates in additive hazard models for the analysis of randomized experiments

    DEFF Research Database (Denmark)

    Vansteelandt, S.; Martinussen, Torben; Tchetgen, E. J Tchetgen

    2014-01-01

    We consider additive hazard models (Aalen, 1989) for the effect of a randomized treatment on a survival outcome, adjusting for auxiliary baseline covariates. We demonstrate that the Aalen least-squares estimator of the treatment effect parameter is asymptotically unbiased, even when the hazard...... that, in view of its robustness against model misspecification, Aalen least-squares estimation is attractive for evaluating treatment effects on a survival outcome in randomized experiments, and the primary reasons to consider baseline covariate adjustment in such settings could be interest in subgroup......'s dependence on time or on the auxiliary covariates is misspecified, and even away from the null hypothesis of no treatment effect. We furthermore show that adjustment for auxiliary baseline covariates does not change the asymptotic variance of the estimator of the effect of a randomized treatment. We conclude...

  1. Methodological aspects of journaling a dynamic adjusting entry model

    Directory of Open Access Journals (Sweden)

    Vlasta Kašparovská

    2011-01-01

    Full Text Available This paper expands the discussion of the importance and function of adjusting entries for loan receivables. Discussion of the cyclical development of adjusting entries, their negative impact on the business cycle and potential solutions has intensified during the financial crisis. These discussions are still ongoing and continue to be relevant to members of the professional public, banking regulators and representatives of international accounting institutions. The objective of this paper is to evaluate a method of journaling dynamic adjusting entries under current accounting law. It also expresses the authors’ opinions on the potential for consistently implementing basic accounting principles in journaling adjusting entries for loan receivables under a dynamic model.

  2. A generalized additive regression model for survival times

    DEFF Research Database (Denmark)

    Scheike, Thomas H.

    2001-01-01

    Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models......Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models...

  3. Revealing the equivalence of two clonal survival models by principal component analysis

    International Nuclear Information System (INIS)

    Lachet, Bernard; Dufour, Jacques

    1976-01-01

    The principal component analysis of 21 chlorella cell survival curves, adjusted by one-hit and two-hit target models, lead to quite similar projections on the principal plan: the homologous parameters of these models are linearly correlated; the reason for the statistical equivalence of these two models, in the present state of experimental inaccuracy, is revealed [fr

  4. Repair models of cell survival and corresponding computer program for survival curve fitting

    International Nuclear Information System (INIS)

    Shen Xun; Hu Yiwei

    1992-01-01

    Some basic concepts and formulations of two repair models of survival, the incomplete repair (IR) model and the lethal-potentially lethal (LPL) model, are introduced. An IBM-PC computer program for survival curve fitting with these models was developed and applied to fit the survivals of human melanoma cells HX118 irradiated at different dose rates. Comparison was made between the repair models and two non-repair models, the multitar get-single hit model and the linear-quadratic model, in the fitting and analysis of the survival-dose curves. It was shown that either IR model or LPL model can fit a set of survival curves of different dose rates with same parameters and provide information on the repair capacity of cells. These two mathematical models could be very useful in quantitative study on the radiosensitivity and repair capacity of cells

  5. Adjusting survival time estimates to account for treatment switching in randomized controlled trials--an economic evaluation context: methods, limitations, and recommendations.

    Science.gov (United States)

    Latimer, Nicholas R; Abrams, Keith R; Lambert, Paul C; Crowther, Michael J; Wailoo, Allan J; Morden, James P; Akehurst, Ron L; Campbell, Michael J

    2014-04-01

    Treatment switching commonly occurs in clinical trials of novel interventions in the advanced or metastatic cancer setting. However, methods to adjust for switching have been used inconsistently and potentially inappropriately in health technology assessments (HTAs). We present recommendations on the use of methods to adjust survival estimates in the presence of treatment switching in the context of economic evaluations. We provide background on the treatment switching issue and summarize methods used to adjust for it in HTAs. We discuss the assumptions and limitations associated with adjustment methods and draw on results of a simulation study to make recommendations on their use. We demonstrate that methods used to adjust for treatment switching have important limitations and often produce bias in realistic scenarios. We present an analysis framework that aims to increase the probability that suitable adjustment methods can be identified on a case-by-case basis. We recommend that the characteristics of clinical trials, and the treatment switching mechanism observed within them, should be considered alongside the key assumptions of the adjustment methods. Key assumptions include the "no unmeasured confounders" assumption associated with the inverse probability of censoring weights (IPCW) method and the "common treatment effect" assumption associated with the rank preserving structural failure time model (RPSFTM). The limitations associated with switching adjustment methods such as the RPSFTM and IPCW mean that they are appropriate in different scenarios. In some scenarios, both methods may be prone to bias; "2-stage" methods should be considered, and intention-to-treat analyses may sometimes produce the least bias. The data requirements of adjustment methods also have important implications for clinical trialists.

  6. Storm Water Management Model Climate Adjustment Tool (SWMM-CAT)

    Science.gov (United States)

    The US EPA’s newest tool, the Stormwater Management Model (SWMM) – Climate Adjustment Tool (CAT) is meant to help municipal stormwater utilities better address potential climate change impacts affecting their operations. SWMM, first released in 1971, models hydrology and hydrauli...

  7. R.M. Solow Adjusted Model of Economic Growth

    Directory of Open Access Journals (Sweden)

    Ion Gh. Rosca

    2007-05-01

    Full Text Available Besides the models of M. Keynes, R.F. Harrod, E. Domar, D. Romer, Ramsey-Cass-Koopmans etc., the R.M. Solow model is part of the category which characterizes the economic growth. The paper proposes the study of the R.M. Solow adjusted model of economic growth, while the adjustment consisting in the model adaptation to the Romanian economic characteristics. The article is the first one from a three paper series dedicated to the macroeconomic modelling theme, using the R.M. Solow model, such as: “Measurement of the economic growth and extensions of the R.M. Solow adjusted model” and “Evolution scenarios at the Romanian economy level using the R.M. Solow adjusted model”. The analysis part of the model is based on the study of the equilibrium to the continuous case with some interpretations of the discreet one, by using the state diagram. The optimization problem at the economic level is also used; it is built up of a specified number of representative consumers and firms in order to reveal the interaction between these elements.

  8. Standard model group: Survival of the fittest

    Science.gov (United States)

    Nielsen, H. B.; Brene, N.

    1983-09-01

    The essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some "world (gauge) group". We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapses is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property.

  9. Standard model group: survival of the fittest

    Energy Technology Data Exchange (ETDEWEB)

    Nielsen, H.B. (Niels Bohr Inst., Copenhagen (Denmark); Nordisk Inst. for Teoretisk Atomfysik, Copenhagen (Denmark)); Brene, N. (Niels Bohr Inst., Copenhagen (Denmark))

    1983-09-19

    The essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapse is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property.

  10. Standard model group: survival of the fittest

    International Nuclear Information System (INIS)

    Nielsen, H.B.; Brene, N.

    1983-01-01

    Th essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapse is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property. (orig.)

  11. Standard model group survival of the fittest

    International Nuclear Information System (INIS)

    Nielsen, H.B.; Brene, N.

    1983-02-01

    The essential content of this note is related to random dynamics. The authors speculate that the world seen through a sub Planck scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some ''world (gauge) group''. It is seen that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. It is further argued that the subgroup which survives as the end product of a possible chain of collapses is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property. (Auth.)

  12. Parenting Stress, Mental Health, Dyadic Adjustment: A Structural Equation Model

    Directory of Open Access Journals (Sweden)

    Luca Rollè

    2017-05-01

    Full Text Available Objective: In the 1st year of the post-partum period, parenting stress, mental health, and dyadic adjustment are important for the wellbeing of both parents and the child. However, there are few studies that analyze the relationship among these three dimensions. The aim of this study is to investigate the relationships between parenting stress, mental health (depressive and anxiety symptoms, and dyadic adjustment among first-time parents.Method: We studied 268 parents (134 couples of healthy babies. At 12 months post-partum, both parents filled out, in a counterbalanced order, the Parenting Stress Index-Short Form, the Edinburgh Post-natal Depression Scale, the State-Trait Anxiety Inventory, and the Dyadic Adjustment Scale. Structural equation modeling was used to analyze the potential mediating effects of mental health on the relationship between parenting stress and dyadic adjustment.Results: Results showed the full mediation effect of mental health between parenting stress and dyadic adjustment. A multi-group analysis further found that the paths did not differ across mothers and fathers.Discussion: The results suggest that mental health is an important dimension that mediates the relationship between parenting stress and dyadic adjustment in the transition to parenthood.

  13. Comparison of Cox and Gray's survival models in severe sepsis

    DEFF Research Database (Denmark)

    Kasal, Jan; Andersen, Zorana Jovanovic; Clermont, Gilles

    2004-01-01

    Although survival is traditionally modeled using Cox proportional hazards modeling, this approach may be inappropriate in sepsis, in which the proportional hazards assumption does not hold. Newer, more flexible models, such as Gray's model, may be more appropriate....

  14. Extensions and Applications of the Cox-Aalen Survival Model

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2003-01-01

    Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects......Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects...

  15. Predicting and Modelling of Survival Data when Cox's Regression Model does not hold

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...

  16. Aqua/Aura Updated Inclination Adjust Maneuver Performance Prediction Model

    Science.gov (United States)

    Boone, Spencer

    2017-01-01

    This presentation will discuss the updated Inclination Adjust Maneuver (IAM) performance prediction model that was developed for Aqua and Aura following the 2017 IAM series. This updated model uses statistical regression methods to identify potential long-term trends in maneuver parameters, yielding improved predictions when re-planning past maneuvers. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager.

  17. Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria

    Directory of Open Access Journals (Sweden)

    Kimmel Marek

    2011-05-01

    Full Text Available Abstract Background Volunteering participants in disease studies tend to be healthier than the general population partially due to specific enrollment criteria. Using modeling to accurately predict outcomes of cohort studies enrolling volunteers requires adjusting for the bias introduced in this way. Here we propose a new method to account for the effect of a specific form of healthy volunteer bias resulting from imposing disease status-related eligibility criteria, on disease-specific mortality, by explicitly modeling the length of the time interval between the moment when the subject becomes ineligible for the study, and the outcome. Methods Using survival time data from 1190 newly diagnosed lung cancer patients at MD Anderson Cancer Center, we model the time from clinical lung cancer diagnosis to death using an exponential distribution to approximate the length of this interval for a study where lung cancer death serves as the outcome. Incorporating this interval into our previously developed lung cancer risk model, we adjust for the effect of disease status-related eligibility criteria in predicting the number of lung cancer deaths in the control arm of CARET. The effect of the adjustment using the MD Anderson-derived approximation is compared to that based on SEER data. Results Using the adjustment developed in conjunction with our existing lung cancer model, we are able to accurately predict the number of lung cancer deaths observed in the control arm of CARET. Conclusions The resulting adjustment was accurate in predicting the lower rates of disease observed in the early years while still maintaining reasonable prediction ability in the later years of the trial. This method could be used to adjust for, or predict the duration and relative effect of any possible biases related to disease-specific eligibility criteria in modeling studies of volunteer-based cohorts.

  18. In-season retail sales forecasting using survival models

    African Journals Online (AJOL)

    Retail sales forecasting, survival analysis, time series analysis, Holt's smoothing .... where fx(t) is the probability density function of the future lifetime, Tx, of a .... Adjustments were made to the shape of the smoothed mortality rates in light of new.

  19. Modeling wind adjustment factor and midflame wind speed for Rothermel's surface fire spread model

    Science.gov (United States)

    Patricia L. Andrews

    2012-01-01

    Rothermel's surface fire spread model was developed to use a value for the wind speed that affects surface fire, called midflame wind speed. Models have been developed to adjust 20-ft wind speed to midflame wind speed for sheltered and unsheltered surface fuel. In this report, Wind Adjustment Factor (WAF) model equations are given, and the BehavePlus fire modeling...

  20. Stage-specific predictive models for breast cancer survivability.

    Science.gov (United States)

    Kate, Rohit J; Nadig, Ramya

    2017-01-01

    Survivability rates vary widely among various stages of breast cancer. Although machine learning models built in past to predict breast cancer survivability were given stage as one of the features, they were not trained or evaluated separately for each stage. To investigate whether there are differences in performance of machine learning models trained and evaluated across different stages for predicting breast cancer survivability. Using three different machine learning methods we built models to predict breast cancer survivability separately for each stage and compared them with the traditional joint models built for all the stages. We also evaluated the models separately for each stage and together for all the stages. Our results show that the most suitable model to predict survivability for a specific stage is the model trained for that particular stage. In our experiments, using additional examples of other stages during training did not help, in fact, it made it worse in some cases. The most important features for predicting survivability were also found to be different for different stages. By evaluating the models separately on different stages we found that the performance widely varied across them. We also demonstrate that evaluating predictive models for survivability on all the stages together, as was done in the past, is misleading because it overestimates performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  1. Risk-adjusted survival for adults following in-hospital cardiac arrest by day of week and time of day: observational cohort study

    Science.gov (United States)

    Robinson, Emily J; Power, Geraldine S; Nolan, Jerry; Soar, Jasmeet; Spearpoint, Ken; Gwinnutt, Carl; Rowan, Kathryn M

    2016-01-01

    Background Internationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events. Objective To describe IHCA demographics during three day/time periods—weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)—and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care. Methods We performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals. Results Risk-adjusted outcomes (OR (95% CI)) were worse (p20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses. Conclusions IHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during

  2. Risk-adjusted survival for adults following in-hospital cardiac arrest by day of week and time of day: observational cohort study.

    Science.gov (United States)

    Robinson, Emily J; Smith, Gary B; Power, Geraldine S; Harrison, David A; Nolan, Jerry; Soar, Jasmeet; Spearpoint, Ken; Gwinnutt, Carl; Rowan, Kathryn M

    2016-11-01

    Internationally, hospital survival is lower for patients admitted at weekends and at night. Data from the UK National Cardiac Arrest Audit (NCAA) indicate that crude hospital survival was worse after in-hospital cardiac arrest (IHCA) at night versus day, and at weekends versus weekdays, despite similar frequency of events. To describe IHCA demographics during three day/time periods-weekday daytime (Monday to Friday, 08:00 to 19:59), weekend daytime (Saturday and Sunday, 08:00 to 19:59) and night-time (Monday to Sunday, 20:00 to 07:59)-and to compare the associated rates of return of spontaneous circulation (ROSC) for >20 min (ROSC>20 min) and survival to hospital discharge, adjusted for risk using previously developed NCAA risk models. To consider whether any observed difference could be attributed to differences in the case mix of patients resident in hospital and/or the administered care. We performed a prospectively defined analysis of NCAA data from 27 700 patients aged ≥16 years receiving chest compressions and/or defibrillation and attended by a hospital-based resuscitation team in response to a resuscitation (2222) call in 146 UK acute hospitals. Risk-adjusted outcomes (OR (95% CI)) were worse (p20 min 0.88 (0.81 to 0.95); hospital survival 0.72 (0.64 to 0.80)), and night-time (ROSC>20 min 0.72 (0.68 to 0.76); hospital survival 0.58 (0.54 to 0.63)) compared with weekday daytime. The effects were stronger for non-shockable than shockable rhythms, but there was no significant interaction between day/time of arrest and age, or day/time of arrest and arrest location. While many daytime IHCAs involved procedures, restricting the analyses to IHCAs in medical admissions with an arrest location of ward produced results that are broadly in line with the primary analyses. IHCAs attended by the hospital-based resuscitation team during nights and weekends have substantially worse outcomes than during weekday daytimes. Organisational or care differences at

  3. Developing a scalable modeling architecture for studying survivability technologies

    Science.gov (United States)

    Mohammad, Syed; Bounker, Paul; Mason, James; Brister, Jason; Shady, Dan; Tucker, David

    2006-05-01

    To facilitate interoperability of models in a scalable environment, and provide a relevant virtual environment in which Survivability technologies can be evaluated, the US Army Research Development and Engineering Command (RDECOM) Modeling Architecture for Technology Research and Experimentation (MATREX) Science and Technology Objective (STO) program has initiated the Survivability Thread which will seek to address some of the many technical and programmatic challenges associated with the effort. In coordination with different Thread customers, such as the Survivability branches of various Army labs, a collaborative group has been formed to define the requirements for the simulation environment that would in turn provide them a value-added tool for assessing models and gauge system-level performance relevant to Future Combat Systems (FCS) and the Survivability requirements of other burgeoning programs. An initial set of customer requirements has been generated in coordination with the RDECOM Survivability IPT lead, through the Survivability Technology Area at RDECOM Tank-automotive Research Development and Engineering Center (TARDEC, Warren, MI). The results of this project are aimed at a culminating experiment and demonstration scheduled for September, 2006, which will include a multitude of components from within RDECOM and provide the framework for future experiments to support Survivability research. This paper details the components with which the MATREX Survivability Thread was created and executed, and provides insight into the capabilities currently demanded by the Survivability faculty within RDECOM.

  4. Estimating quality adjusted progression free survival of first-line treatments for EGFR mutation positive non small cell lung cancer patients in The Netherlands

    Directory of Open Access Journals (Sweden)

    Verduyn S

    2012-09-01

    Full Text Available Abstract Background Gefitinib, a tyrosine kinase inhibitor, is an effective treatment in advanced non-small cell lung cancer (NSCLC patients with an activating mutation in the epidermal growth factor receptor (EGFR. Randomised clinical trials showed a benefit in progression free survival for gefitinib versus doublet chemotherapy regimens in patients with an activated EGFR mutation (EGFR M+. From a patient perspective, progression free survival is important, but so is health-related quality of life. Therefore, this analysis evaluates the Quality Adjusted progression free survival of gefitinib versus three relevant doublet chemotherapies (gemcitabine/cisplatin (Gem/Cis; pemetrexed/cisplatin (Pem/Cis; paclitaxel/carboplatin (Pac/Carb in a Dutch health care setting in patients with EGFR M+ stage IIIB/IV NSCLC. This study uses progression free survival rather than overall survival for its time frame in order to better compare the treatments and to account for the influence that subsequent treatment lines would have on overall survival analysis. Methods Mean progression free survival for Pac/Carb was obtained by extrapolating the median progression free survival as reported in the Iressa-Pan-Asia Study (IPASS. Data from a network meta-analysis was used to estimate the mean progression free survival for therapies of interest relative to Pac/Carb. Adjustment for health-related quality of life was done by incorporating utilities for the Dutch population, obtained by converting FACT-L data (from IPASS to utility values and multiplying these with the mean progression free survival for each treatment arm to determine the Quality Adjusted progression free survival. Probabilistic sensitivity analysis was carried out to determine 95% credibility intervals. Results The Quality Adjusted progression free survival (PFS (mean, (95% credibility interval was 5.2 months (4.5; 5.8 for Gem/Cis, 5.3 months (4.6; 6.1 for Pem/Cis; 4.9 months (4.4; 5.5 for Pac/Carb and 8

  5. Efficient estimation of semiparametric copula models for bivariate survival data

    KAUST Repository

    Cheng, Guang

    2014-01-01

    A semiparametric copula model for bivariate survival data is characterized by a parametric copula model of dependence and nonparametric models of two marginal survival functions. Efficient estimation for the semiparametric copula model has been recently studied for the complete data case. When the survival data are censored, semiparametric efficient estimation has only been considered for some specific copula models such as the Gaussian copulas. In this paper, we obtain the semiparametric efficiency bound and efficient estimation for general semiparametric copula models for possibly censored data. We construct an approximate maximum likelihood estimator by approximating the log baseline hazard functions with spline functions. We show that our estimates of the copula dependence parameter and the survival functions are asymptotically normal and efficient. Simple consistent covariance estimators are also provided. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2013 Elsevier Inc.

  6. SEMI-COMPETING RISKS ON A TRIVARIATE WEIBULL SURVIVAL MODEL

    Directory of Open Access Journals (Sweden)

    Jenq-Daw Lee

    2008-07-01

    Full Text Available A setting of a trivairate survival function using semi-competing risks concept is proposed, in which a terminal event can only occur after other events. The Stanford Heart Transplant data is reanalyzed using a trivariate Weibull distribution model with the proposed survival function.

  7. Capital Structure: Target Adjustment Model and a Mediation Moderation Model with Capital Structure as Mediator

    OpenAIRE

    Abedmajid, Mohammed

    2015-01-01

    This study consists of two models. Model one is conducted to check if there is a target adjustment toward optimal capital structure, in the context of Turkish firm listed on the stock market, over the period 2003-2014. Model 2 captures the interaction between firm size, profitability, market value and capital structure using the moderation mediation model. The results of model 1 have shown that there is a partial adjustment of the capital structure to reach target levels. The results of...

  8. Model for Adjustment of Aggregate Forecasts using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Taracena–Sanz L. F.

    2010-07-01

    Full Text Available This research suggests a contribution in the implementation of forecasting models. The proposed model is developed with the aim to fit the projection of demand to surroundings of firms, and this is based on three considerations that cause that in many cases the forecasts of the demand are different from reality, such as: 1 one of the problems most difficult to model in the forecasts is the uncertainty related to the information available; 2 the methods traditionally used by firms for the projection of demand mainly are based on past behavior of the market (historical demand; and 3 these methods do not consider in their analysis the factors that are influencing so that the observed behaviour occurs. Therefore, the proposed model is based on the implementation of Fuzzy Logic, integrating the main variables that affect the behavior of market demand, and which are not considered in the classical statistical methods. The model was applied to a bottling of carbonated beverages, and with the adjustment of the projection of demand a more reliable forecast was obtained.

  9. A Unified Model of Geostrophic Adjustment and Frontogenesis

    Science.gov (United States)

    Taylor, John; Shakespeare, Callum

    2013-11-01

    Fronts, or regions with strong horizontal density gradients, are ubiquitous and dynamically important features of the ocean and atmosphere. In the ocean, fronts are associated with enhanced air-sea fluxes, turbulence, and biological productivity, while atmospheric fronts are associated with some of the most extreme weather events. Here, we describe a new mathematical framework for describing the formation of fronts, or frontogenesis. This framework unifies two classical problems in geophysical fluid dynamics, geostrophic adjustment and strain-driven frontogenesis, and provides a number of important extensions beyond previous efforts. The model solutions closely match numerical simulations during the early stages of frontogenesis, and provide a means to describe the development of turbulence at mature fronts.

  10. PERMINTAAN BERAS DI PROVINSI JAMBI (Penerapan Partial Adjustment Model

    Directory of Open Access Journals (Sweden)

    Wasi Riyanto

    2013-07-01

    Full Text Available The purpose of this study is to determine the effect of price of rice, flour prices, population, income of population and demand of rice for a year earlier on rice demand, demand rice elasticity and rice demand prediction in Jambi Province. This study uses secondary data, including time series data for 22 years from 1988 until 2009. The study used some variables, consist of rice demand (Qdt, the price of rice (Hb, the price of wheat flour (Hg, population (Jp, the income of the population (PDRB and demand for rice the previous year (Qdt-1. The make of this study are multiple regression and dynamic analysis a Partial Adjustment Model, where the demand for rice is the dependent variable and the price of rice, flour prices, population, income population and demand of rice last year was the independent variable. Partial Adjustment Model analysis results showed that the effect of changes in prices of rice and flour are not significant to changes in demand for rice. The population and demand of rice the previous year has positive and significant impact on demand for rice, while revenues have negative and significant population of rice demand. Variable price of rice, earning population and the price of flour is inelastic the demand of rice, because rice is not a normal good but as a necessity so that there is no substitution of goods (replacement of rice with other commodities in Jambi Province. Based on the analysis, it is recommended to the government to be able to control the rate of population increase given the variable number of people as one of the factors that affect demand for rice.It is expected that the government also began to socialize in a lifestyle of non-rice food consumption to control the increasing amount of demand for rice. Last suggestion, the government developed a diversification of staple foods other than rice.

  11. Age-adjusted Charlson comorbidity index score as predictor of survival of patients with digestive system cancer who have undergone surgical resection.

    Science.gov (United States)

    Tian, Yaohua; Jian, Zhong; Xu, Beibei; Liu, Hui

    2017-10-03

    Comorbidities have considerable effects on survival outcomes. The primary objective of this retrospective study was to examine the association between age-adjusted Charlson comorbidity index (ACCI) score and postoperative in-hospital mortality in patients with digestive system cancer who have undergone surgical resection of their cancers. Using electronic hospitalization summary reports, we identified 315,464 patients who had undergone surgery for digestive system cancer in top-rank (Grade 3A) hospitals in China between 2013 and 2015. The Cox proportional hazard regression model was applied to evaluate the effect of ACCI score on postoperative mortality, with adjustments for sex, type of resection, anesthesia methods, and caseload of each healthcare institution. The postoperative in-hospital mortality rate in the study cohort was 1.2% (3,631/315,464). ACCI score had a positive graded association with the risk of postoperative in-hospital mortality for all cancer subtypes. The adjusted HRs for postoperative in-hospital mortality scores ≥ 6 for esophagus, stomach, colorectum, pancreas, and liver and gallbladder cancer were 2.05 (95% CI: 1.45-2.92), 2.00 (95% CI: 1.60-2.49), 2.54 (95% CI: 2.02-3.21), 2.58 (95% CI: 1.68-3.97), and 4.57 (95% CI: 3.37-6.20), respectively, compared to scores of 0-1. These findings suggested that a high ACCI score is an independent predictor of postoperative in-hospital mortality in Chinese patients with digestive system cancer who have undergone surgical resection.

  12. Repair-misrepair model of cell survival

    International Nuclear Information System (INIS)

    Tobias, C.A.; Blakely, E.A.; Ngo, F.Q.H.

    1980-01-01

    During the last three years a new model, the repair-misrepair model (RMR) has been proposed, to interpret radiobiological experiments with heavy ions. In using the RMR model it became apparent that some of its features are suitable for handling the effects produced by a variety of environmental agents in addition to ionizing radiation. Two separate sequences of events are assumed to take place in an irradiated cell. The first sequence begins with an initial energy transfer consisting of ionizations and excitations, culminating via fast secondary physical and chemical processes in established macromolecular lesions in essential cell structures. The second sequence contains the responses of the cell to the lesions and consists of the processes of recognition and molecular repair. In normal cells there exists one repair process or at most a few enzymatic repair processes for each essential macromolecular lesion. The enzymatic repair processes may last for hours and minutes, and can be separated in time from the initial physicochemical and later genetic phases

  13. Permintaan Beras di Provinsi Jambi (Penerapan Partial Adjustment Model

    Directory of Open Access Journals (Sweden)

    Wasi Riyanto

    2013-07-01

    Full Text Available The purpose of this study is to determine the effect of price of rice, flour prices, population, income of population and demand of rice for a year earlier on rice demand, demand rice elasticity and rice demand prediction in Jambi Province. This study uses secondary data, including time series data for 22 years from 1988 until 2009. The study used some variables, consist of rice demand (Qdt, the price of rice (Hb, the price of wheat flour (Hg, population (Jp, the income of the population (PDRB and demand for rice the previous year (Qdt-1. The make of this study are multiple regression and dynamic analysis  a Partial Adjustment Model, where the demand for rice is the dependent variable and the price of rice, flour prices, population, income population and demand of rice last year was the independent variable. Partial Adjustment Model analysis results showed that the effect of changes in prices of rice  and flour are not significant  to  changes in demand for rice. The population and demand of rice the previous year has positive and significant impact on demand for rice, while revenues have negative and significant population of rice demand. Variable price of rice, earning population and the price of flour is inelastic the demand of rice, because rice is not a normal good but as a necessity so that there is no substitution of goods (replacement of rice with other commodities in Jambi Province. Based on the analysis, it is recommended to the government to be able to control the rate of population increase given the variable number of people as one of the factors that affect demand for rice.It is expected that the  government also began  to  socialize  in a lifestyle  of  non-rice food consumption to control the increasing amount of demand for rice. Last suggestion, the government developed a diversification of staple foods other than rice. Keywords: Demand, Rice, Income Population

  14. Adjusting the Adjusted X[superscript 2]/df Ratio Statistic for Dichotomous Item Response Theory Analyses: Does the Model Fit?

    Science.gov (United States)

    Tay, Louis; Drasgow, Fritz

    2012-01-01

    Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…

  15. Predictive model for survival in patients with gastric cancer.

    Science.gov (United States)

    Goshayeshi, Ladan; Hoseini, Benyamin; Yousefli, Zahra; Khooie, Alireza; Etminani, Kobra; Esmaeilzadeh, Abbas; Golabpour, Amin

    2017-12-01

    Gastric cancer is one of the most prevalent cancers in the world. Characterized by poor prognosis, it is a frequent cause of cancer in Iran. The aim of the study was to design a predictive model of survival time for patients suffering from gastric cancer. This was a historical cohort conducted between 2011 and 2016. Study population were 277 patients suffering from gastric cancer. Data were gathered from the Iranian Cancer Registry and the laboratory of Emam Reza Hospital in Mashhad, Iran. Patients or their relatives underwent interviews where it was needed. Missing values were imputed by data mining techniques. Fifteen factors were analyzed. Survival was addressed as a dependent variable. Then, the predictive model was designed by combining both genetic algorithm and logistic regression. Matlab 2014 software was used to combine them. Of the 277 patients, only survival of 80 patients was available whose data were used for designing the predictive model. Mean ?SD of missing values for each patient was 4.43?.41 combined predictive model achieved 72.57% accuracy. Sex, birth year, age at diagnosis time, age at diagnosis time of patients' family, family history of gastric cancer, and family history of other gastrointestinal cancers were six parameters associated with patient survival. The study revealed that imputing missing values by data mining techniques have a good accuracy. And it also revealed six parameters extracted by genetic algorithm effect on the survival of patients with gastric cancer. Our combined predictive model, with a good accuracy, is appropriate to forecast the survival of patients suffering from Gastric cancer. So, we suggest policy makers and specialists to apply it for prediction of patients' survival.

  16. Statistical models and methods for reliability and survival analysis

    CERN Document Server

    Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo

    2013-01-01

    Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical

  17. Modelling survival: exposure pattern, species sensitivity and uncertainty.

    Science.gov (United States)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

    2016-07-06

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

  18. Disaster Hits Home: A Model of Displaced Family Adjustment after Hurricane Katrina

    Science.gov (United States)

    Peek, Lori; Morrissey, Bridget; Marlatt, Holly

    2011-01-01

    The authors explored individual and family adjustment processes among parents (n = 30) and children (n = 55) who were displaced to Colorado after Hurricane Katrina. Drawing on in-depth interviews with 23 families, this article offers an inductive model of displaced family adjustment. Four stages of family adjustment are presented in the model: (a)…

  19. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    DEFF Research Database (Denmark)

    Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

    2014-01-01

    A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

  20. Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits

    DEFF Research Database (Denmark)

    Pimentel Maia, Rafael; Madsen, Per; Labouriau, Rodrigo

    2013-01-01

    A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented co...... applications. The methods presented are implemented in such a way that large and complex quantitative genetic data can be analyzed......A class of multivariate mixed survival models for continuous and discrete time with a complex covariance structure is introduced in a context of quantitative genetic applications. The methods introduced can be used in many applications in quantitative genetics although the discussion presented...... concentrates on longevity studies. The framework presented allows to combine models based on continuous time with models based on discrete time in a joint analysis. The continuous time models are approximations of the frailty model in which the hazard function will be assumed to be piece-wise constant...

  1. Capital adjustment cost and bias in income based dynamic panel models with fixed effects

    OpenAIRE

    Yoseph Yilma Getachew; Keshab Bhattarai; Parantap Basu

    2012-01-01

    The fixed effects (FE) estimator of "conditional convergence" in income based dynamic panel models could be biased downward when capital adjustment cost is present. Such a capital adjustment cost means a rising marginal cost of investment which could slow down the convergence. The standard FE regression fails to take into account of this capital adjustment cost and thus it could overestimate the rate of convergence. Using a Ramsey model with long-run adjustment cost of capital, we characteriz...

  2. Discrete dynamic modeling of T cell survival signaling networks

    Science.gov (United States)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  3. Adjustment costs in a two-capital growth model

    Czech Academy of Sciences Publication Activity Database

    Duczynski, Petr

    2002-01-01

    Roč. 26, č. 5 (2002), s. 837-850 ISSN 0165-1889 R&D Projects: GA AV ČR KSK9058117 Institutional research plan: CEZ:AV0Z7085904 Keywords : adjustment costs * capital mobility * convergence * human capital Subject RIV: AH - Economics Impact factor: 0.738, year: 2002

  4. Age adjusted hematopoietic stem cell transplant comorbidity index predicts survival in a T-cell depleted cohort.

    Science.gov (United States)

    Saeed, Hayder; Yalamanchi, Swati; Liu, Meng; Van Meter, Emily; Gul, Zartash; Monohan, Gregory; Howard, Dianna; Hildebrandt, Gerhard C; Herzig, Roger

    2018-02-01

    Allogeneic hematopoietic stem cell transplant (HCT) continues to evolve with the treatment in higher risk patient population. This practice mandates stringent update and validation of risk stratification prior to undergoing such a complex and potentially fatal procedure. We examined the adoption of the new comorbidity index (HCT-CI/Age) proposed by the Seattle group after the addition of age variable and compared it to the pre-transplant assessment of mortality (PAM) that already incorporates age as part of its evaluation criteria. A retrospective analysis of adult patients who underwent HCT at our institution from January 2010 through August 2014 was performed. Kaplan-Meier's curve, log-rank tests, Cox model and Pearson correlation was used in the analysis. Of the 114 patients that underwent allogeneic transplant in our institution, 75.4% were ≥40 years old. More than 58% had a DLCO ≤80%. Although scores were positively correlated (correlation coefficient 0.43, p < 0.001), HCT-CI/Age more accurately predicted 2-year overall survival (OS) and non-relapse mortality (NRM) in patients with lower (0-4) and higher (5-7) scores (52% and 36% versus 24% and 76%, p = 0.004, 0.003 respectively). PAM score did not reach statistical significance for difference in OS nor NRM between the low (<24) and high-risk (≥24) groups (p = 0.19 for both). Despite our small sample population, HCT-CI/Age was more discriminative to identify patients with poor outcome that might benefit from intensified management strategies or other therapeutic approaches rather than allogeneic HCT. Copyright © 2018. Published by Elsevier B.V.

  5. Parameter resolution in two models for cell survival after radiation

    International Nuclear Information System (INIS)

    Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.

    1989-01-01

    The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)

  6. Player Modeling Using HOSVD towards Dynamic Difficulty Adjustment in Videogames

    OpenAIRE

    Anagnostou , Kostas; Maragoudakis , Manolis

    2012-01-01

    Part 3: Second International Workshop on Computational Intelligence in Software Engineering (CISE 2012); International audience; In this work, we propose and evaluate a Higher Order Singular Value Decomposition (HOSVD) of a tensor as a means to classify player behavior and adjust game difficulty dynamically. Applying this method to player data collected during a plethora of game sessions resulted in a reduction of the dimensionality of the classification problem and a robust classification of...

  7. Survival prediction model for postoperative hepatocellular carcinoma patients.

    Science.gov (United States)

    Ren, Zhihui; He, Shasha; Fan, Xiaotang; He, Fangping; Sang, Wei; Bao, Yongxing; Ren, Weixin; Zhao, Jinming; Ji, Xuewen; Wen, Hao

    2017-09-01

    This study is to establish a predictive index (PI) model of 5-year survival rate for patients with hepatocellular carcinoma (HCC) after radical resection and to evaluate its prediction sensitivity, specificity, and accuracy.Patients underwent HCC surgical resection were enrolled and randomly divided into prediction model group (101 patients) and model evaluation group (100 patients). Cox regression model was used for univariate and multivariate survival analysis. A PI model was established based on multivariate analysis and receiver operating characteristic (ROC) curve was drawn accordingly. The area under ROC (AUROC) and PI cutoff value was identified.Multiple Cox regression analysis of prediction model group showed that neutrophil to lymphocyte ratio, histological grade, microvascular invasion, positive resection margin, number of tumor, and postoperative transcatheter arterial chemoembolization treatment were the independent predictors for the 5-year survival rate for HCC patients. The model was PI = 0.377 × NLR + 0.554 × HG + 0.927 × PRM + 0.778 × MVI + 0.740 × NT - 0.831 × transcatheter arterial chemoembolization (TACE). In the prediction model group, AUROC was 0.832 and the PI cutoff value was 3.38. The sensitivity, specificity, and accuracy were 78.0%, 80%, and 79.2%, respectively. In model evaluation group, AUROC was 0.822, and the PI cutoff value was well corresponded to the prediction model group with sensitivity, specificity, and accuracy of 85.0%, 83.3%, and 84.0%, respectively.The PI model can quantify the mortality risk of hepatitis B related HCC with high sensitivity, specificity, and accuracy.

  8. Structural Adjustment Policy Experiments: The Use of Philippine CGE Models

    OpenAIRE

    Cororaton, Caesar B.

    1994-01-01

    This paper reviews the general structure of the following general computable general equilibrium (CGE): the APEX model, Habito’s second version of the PhilCGE model, Cororaton’s CGE model and Bautista’s first CGE model. These models are chosen as they represent the range of recently constructed CGE models of the Philippine economy. They also represent two schools of thought in CGE modeling: the well defined neoclassical, Walrasian, general equilibrium school where the market-clearing variable...

  9. A structural model for stress, coping, and psychosocial adjustment: A multi-group analysis by stages of survivorship in Korean women with breast cancer.

    Science.gov (United States)

    Jang, Miyoung; Kim, Jiyoung

    2018-04-01

    Prospective studies have examined factors directly affecting psychosocial adjustment during breast cancer treatment. Survivorship stage may moderate a direct effect of stress on psychosocial adjustment. This study aimed to examine relationships between stress, social support, self-efficacy, coping, and psychosocial adjustment to construct a model of the effect pathways between those factors, and determine if survivorship stage moderates those effects. Six hundred people with breast cancer completed questionnaires. Examined stages of survivorship after treatment were as follows: acute (i.e., 5 years). Stress (Perceived Stress Scale), social support (Multidimensional Scale of Perceived Social Support), self-efficacy (New General Self Efficacy Scale), coping (Ways of Coping Checklist), and psychosocial adjustment (Psychosocial Adjustment to Illness Scale-Self-Report-Korean Version) were measured. Self-efficacy significantly correlated with psychosocial adjustment in the acute survival stage (γ = -0.37, P psychosocial adjustment was greater in the acute (γ = -0.42, P psychosocial adjustment was stronger in the lasting survival stage (β = 0.42, P psychosocial adjustment of female breast cancer patients. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. Improving Risk Adjustment for Mortality After Pediatric Cardiac Surgery: The UK PRAiS2 Model.

    Science.gov (United States)

    Rogers, Libby; Brown, Katherine L; Franklin, Rodney C; Ambler, Gareth; Anderson, David; Barron, David J; Crowe, Sonya; English, Kate; Stickley, John; Tibby, Shane; Tsang, Victor; Utley, Martin; Witter, Thomas; Pagel, Christina

    2017-07-01

    Partial Risk Adjustment in Surgery (PRAiS), a risk model for 30-day mortality after children's heart surgery, has been used by the UK National Congenital Heart Disease Audit to report expected risk-adjusted survival since 2013. This study aimed to improve the model by incorporating additional comorbidity and diagnostic information. The model development dataset was all procedures performed between 2009 and 2014 in all UK and Ireland congenital cardiac centers. The outcome measure was death within each 30-day surgical episode. Model development followed an iterative process of clinical discussion and development and assessment of models using logistic regression under 25 × 5 cross-validation. Performance was measured using Akaike information criterion, the area under the receiver-operating characteristic curve (AUC), and calibration. The final model was assessed in an external 2014 to 2015 validation dataset. The development dataset comprised 21,838 30-day surgical episodes, with 539 deaths (mortality, 2.5%). The validation dataset comprised 4,207 episodes, with 97 deaths (mortality, 2.3%). The updated risk model included 15 procedural, 11 diagnostic, and 4 comorbidity groupings, and nonlinear functions of age and weight. Performance under cross-validation was: median AUC of 0.83 (range, 0.82 to 0.83), median calibration slope and intercept of 0.92 (range, 0.64 to 1.25) and -0.23 (range, -1.08 to 0.85) respectively. In the validation dataset, the AUC was 0.86 (95% confidence interval [CI], 0.82 to 0.89), and the calibration slope and intercept were 1.01 (95% CI, 0.83 to 1.18) and 0.11 (95% CI, -0.45 to 0.67), respectively, showing excellent performance. A more sophisticated PRAiS2 risk model for UK use was developed with additional comorbidity and diagnostic information, alongside age and weight as nonlinear variables. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  11. Modeling of an Adjustable Beam Solid State Light

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal is for the development of a computational model of a prototype variable beam light source using optical modeling software, Zemax OpticStudio ®. The...

  12. Adjusting multistate capture-recapture models for misclassification bias: manatee breeding proportions

    Science.gov (United States)

    Kendall, W.L.; Hines, J.E.; Nichols, J.D.

    2003-01-01

    Matrix population models are important tools for research and management of populations. Estimating the parameters of these models is an important step in applying them to real populations. Multistate capture-recapture methods have provided a useful means for estimating survival and parameters of transition between locations or life history states but have mostly relied on the assumption that the state occupied by each detected animal is known with certainty. Nevertheless, in some cases animals can be misclassified. Using multiple capture sessions within each period of interest, we developed a method that adjusts estimates of transition probabilities for bias due to misclassification. We applied this method to 10 years of sighting data for a population of Florida manatees (Trichechus manatus latirostris) in order to estimate the annual probability of transition from nonbreeding to breeding status. Some sighted females were unequivocally classified as breeders because they were clearly accompanied by a first-year calf. The remainder were classified, sometimes erroneously, as nonbreeders because an attendant first-year calf was not observed or was classified as more than one year old. We estimated a conditional breeding probability of 0.31 + 0.04 (estimate + 1 SE) when we ignored misclassification bias, and 0.61 + 0.09 when we accounted for misclassification.

  13. Analyzing sickness absence with statistical models for survival data

    DEFF Research Database (Denmark)

    Christensen, Karl Bang; Andersen, Per Kragh; Smith-Hansen, Lars

    2007-01-01

    OBJECTIVES: Sickness absence is the outcome in many epidemiologic studies and is often based on summary measures such as the number of sickness absences per year. In this study the use of modern statistical methods was examined by making better use of the available information. Since sickness...... absence data deal with events occurring over time, the use of statistical models for survival data has been reviewed, and the use of frailty models has been proposed for the analysis of such data. METHODS: Three methods for analyzing data on sickness absences were compared using a simulation study...... involving the following: (i) Poisson regression using a single outcome variable (number of sickness absences), (ii) analysis of time to first event using the Cox proportional hazards model, and (iii) frailty models, which are random effects proportional hazards models. Data from a study of the relation...

  14. Machine learning models in breast cancer survival prediction.

    Science.gov (United States)

    Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

    2016-01-01

    Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

  15. Estimating true instead of apparent survival using spatial Cormack-Jolly-Seber models

    Science.gov (United States)

    Schaub, Michael; Royle, J. Andrew

    2014-01-01

    Survival is often estimated from capture–recapture data using Cormack–Jolly–Seber (CJS) models, where mortality and emigration cannot be distinguished, and the estimated apparent survival probability is the product of the probabilities of true survival and of study area fidelity. Consequently, apparent survival is lower than true survival unless study area fidelity equals one. Underestimation of true survival from capture–recapture data is a main limitation of the method.

  16. Husbands' perceptions of their wives' breast cancer coping efficacy: testing congruence models of adjustment.

    Science.gov (United States)

    Merluzzi, Thomas V; Martinez Sanchez, MaryAnn

    2018-01-01

    Recent reviews have reinforced the notion that having a supportive spouse can help with the process of coping with and adjusting to cancer. Congruence between spouses' perspectives has been proposed as one mechanism in that process, yet alternative models of congruence have not been examined closely. This study assessed alternative models of congruence in perceptions of coping and their mediating effects on adjustment to breast cancer. Seventy-two women in treatment for breast cancer and their husbands completed measures of marital adjustment, self-efficacy for coping, and adjustment to cancer. Karnofsky Performance Status was obtained from medical records. Wives completed a measure of self-efficacy for coping (wives' ratings of self-efficacy for coping [WSEC]) and husbands completed a measure of self-efficacy for coping (husbands' ratings of wives' self-efficacy for coping [HSEC]) based on their perceptions of their wives' coping efficacy. Interestingly, the correlation between WSEC and HSEC was only 0.207; thus, they are relatively independent perspectives. The following three models were tested to determine the nature of the relationship between WSEC and HSEC: discrepancy model (WSEC - HSEC), additive model (WSEC + HSEC), and multiplicative model (WSEC × HSEC). The discrepancy model was not related to wives' adjustment; however, the additive ( B =0.205, P <0.001) and multiplicative ( B =0.001, P <0.001) models were significantly related to wives' adjustment. Also, the additive model mediated the relationship between performance status and adjustment. Husbands' perception of their wives' coping efficacy contributed marginally to their wives' adjustment, and the combination of WSEC and HSEC mediated the relationship between functional status and wives' adjustment, thus positively impacting wives' adjustment to cancer. Future research is needed to determine the quality of the differences between HSEC and WSEC in order to develop interventions to optimize the

  17. Survival models for harvest management of mourning dove populations

    Science.gov (United States)

    Otis, D.L.

    2002-01-01

    Quantitative models of the relationship between annual survival and harvest rate of migratory game-bird populations are essential to science-based harvest management strategies. I used the best available band-recovery and harvest data for mourning doves (Zenaida macroura) to build a set of models based on different assumptions about compensatory harvest mortality. Although these models suffer from lack of contemporary data, they can be used in development of an initial set of population models that synthesize existing demographic data on a management-unit scale, and serve as a tool for prioritization of population demographic information needs. Credible harvest management plans for mourning dove populations will require a long-term commitment to population monitoring and iterative population analysis.

  18. An Adjusted Discount Rate Model for Fuel Cycle Cost Estimation

    Energy Technology Data Exchange (ETDEWEB)

    Kim, S. K.; Kang, G. B.; Ko, W. I. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    Owing to the diverse nuclear fuel cycle options available, including direct disposal, it is necessary to select the optimum nuclear fuel cycles in consideration of the political and social environments as well as the technical stability and economic efficiency of each country. Economic efficiency is therefore one of the significant evaluation standards. In particular, because nuclear fuel cycle cost may vary in each country, and the estimated cost usually prevails over the real cost, when evaluating the economic efficiency, any existing uncertainty needs to be removed when possible to produce reliable cost information. Many countries still do not have reprocessing facilities, and no globally commercialized HLW (High-level waste) repository is available. A nuclear fuel cycle cost estimation model is therefore inevitably subject to uncertainty. This paper analyzes the uncertainty arising out of a nuclear fuel cycle cost evaluation from the viewpoint of a cost estimation model. Compared to the same discount rate model, the nuclear fuel cycle cost of a different discount rate model is reduced because the generation quantity as denominator in Equation has been discounted. Namely, if the discount rate reduces in the back-end process of the nuclear fuel cycle, the nuclear fuel cycle cost is also reduced. Further, it was found that the cost of the same discount rate model is overestimated compared with the different discount rate model as a whole.

  19. An Adjusted Discount Rate Model for Fuel Cycle Cost Estimation

    International Nuclear Information System (INIS)

    Kim, S. K.; Kang, G. B.; Ko, W. I.

    2013-01-01

    Owing to the diverse nuclear fuel cycle options available, including direct disposal, it is necessary to select the optimum nuclear fuel cycles in consideration of the political and social environments as well as the technical stability and economic efficiency of each country. Economic efficiency is therefore one of the significant evaluation standards. In particular, because nuclear fuel cycle cost may vary in each country, and the estimated cost usually prevails over the real cost, when evaluating the economic efficiency, any existing uncertainty needs to be removed when possible to produce reliable cost information. Many countries still do not have reprocessing facilities, and no globally commercialized HLW (High-level waste) repository is available. A nuclear fuel cycle cost estimation model is therefore inevitably subject to uncertainty. This paper analyzes the uncertainty arising out of a nuclear fuel cycle cost evaluation from the viewpoint of a cost estimation model. Compared to the same discount rate model, the nuclear fuel cycle cost of a different discount rate model is reduced because the generation quantity as denominator in Equation has been discounted. Namely, if the discount rate reduces in the back-end process of the nuclear fuel cycle, the nuclear fuel cycle cost is also reduced. Further, it was found that the cost of the same discount rate model is overestimated compared with the different discount rate model as a whole

  20. Statistical study of clone survival curves after irradiation in one or two stages. Comparison and generalization of different models

    International Nuclear Information System (INIS)

    Lachet, Bernard.

    1975-01-01

    A statistical study was carried out on 208 survival curves for chlorella subjected to γ or particle radiations. The computing programmes used were written in Fortran. The different experimental causes contributing to the variance of a survival rate are analyzed and consequently the experiments can be planned. Each curve was fitted to four models by the weighted least squares method applied to non-linear functions. The validity of the fits obtained can be checked by the F test. It was possible to define the confidence and prediction zones around an adjusted curve by weighting of the residual variance, in spite of error on the doses delivered; the confidence limits can them be fixed for a dose estimated from an exact or measured survival. The four models adopted were compared for the precision of their fit (by a non-parametric simultaneous comparison test) and the scattering of their adjusted parameters: Wideroe's model gives a very good fit with the experimental points in return for a scattering of its parameters, which robs them of their presumed meaning. The principal component analysis showed the statistical equivalence of the 1 and 2 hit target models. Division of the irradiation into two doses, the first fixed by the investigator, leads to families of curves for which the equation was established from that of any basic model expressing the dose survival relationship in one-stage irradiation [fr

  1. PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

    Science.gov (United States)

    Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

    2010-01-01

    The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

  2. Spherical Model Integrating Academic Competence with Social Adjustment and Psychopathology.

    Science.gov (United States)

    Schaefer, Earl S.; And Others

    This study replicates and elaborates a three-dimensional, spherical model that integrates research findings concerning social and emotional behavior, psychopathology, and academic competence. Kindergarten teachers completed an extensive set of rating scales on 100 children, including the Classroom Behavior Inventory and the Child Adaptive Behavior…

  3. R.M. Solow Adjusted Model of Economic Growth

    Directory of Open Access Journals (Sweden)

    Ion Gh. Rosca

    2007-05-01

    The analysis part of the model is based on the study of the equilibrium to the continuous case with some interpretations of the discreet one, by using the state diagram. The optimization problem at the economic level is also used; it is built up of a specified number of representative consumers and firms in order to reveal the interaction between these elements.

  4. Connecting single-stock assessment models through correlated survival

    DEFF Research Database (Denmark)

    Albertsen, Christoffer Moesgaard; Nielsen, Anders; Thygesen, Uffe Høgsbro

    2017-01-01

    times. We propose a simple alternative. In three case studies each with two stocks, we improve the single-stock models, as measured by Akaike information criterion, by adding correlation in the cohort survival. To limit the number of parameters, the correlations are parameterized through...... the corresponding partial correlations. We consider six models where the partial correlation matrix between stocks follows a band structure ranging from independent assessments to complex correlation structures. Further, a simulation study illustrates the importance of handling correlated data sufficiently...... by investigating the coverage of confidence intervals for estimated fishing mortality. The results presented will allow managers to evaluate stock statuses based on a more accurate evaluation of model output uncertainty. The methods are directly implementable for stocks with an analytical assessment and do...

  5. Living donor risk model for predicting kidney allograft and patient survival in an emerging economy.

    Science.gov (United States)

    Zafar, Mirza Naqi; Wong, Germaine; Aziz, Tahir; Abbas, Khawar; Adibul Hasan Rizvi, S

    2018-03-01

    Living donor kidney is the main source of donor organs in low to middle income countries. We aimed to develop a living donor risk model that predicts graft and patient survival in an emerging economy. We used data from the Sindh Institute of Urology and Transplantation (SIUT) database (n = 2283 recipients and n = 2283 living kidney donors, transplanted between 1993 and 2009) and conducted Cox proportional hazard analyses to develop a composite score that predicts graft and patient survivals. Donor factors age, creatinine clearance, nephron dose (estimated by donor/recipient body weight ratio) and human leukocyte antigen (HLA) match were included in the living donor risk model. The adjusted hazard ratios (HRs) for graft failures among those who received a kidney with living donor scores (reference to donor score of zero) of 1, 2, 3 and 4 were 1.14 (95%CI: 0.94-1.39), 1.24 (95%CI:1.03-1.49), 1.25 (95%CI:1.03-1.51) and 1.36 (95%CI:1.08-1.72) (P-value for trend =0.05). Similar findings were observed for patient survival. Similar to findings in high income countries, our study suggests that donor characteristics such as age, nephron dose, creatinine clearance and HLA match are important factors that determine the long-term patient and graft survival in low income countries. However, other crucial but undefined factors may play a role in determining the overall risk of graft failure and mortality in living kidney donor transplant recipients. © 2016 Asian Pacific Society of Nephrology.

  6. Modeling of pathogen survival during simulated gastric digestion.

    Science.gov (United States)

    Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

    2011-02-01

    The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens.

  7. Modeling of Pathogen Survival during Simulated Gastric Digestion ▿

    Science.gov (United States)

    Koseki, Shige; Mizuno, Yasuko; Sotome, Itaru

    2011-01-01

    The objective of the present study was to develop a mathematical model of pathogenic bacterial inactivation kinetics in a gastric environment in order to further understand a part of the infectious dose-response mechanism. The major bacterial pathogens Listeria monocytogenes, Escherichia coli O157:H7, and Salmonella spp. were examined by using simulated gastric fluid adjusted to various pH values. To correspond to the various pHs in a stomach during digestion, a modified logistic differential equation model and the Weibull differential equation model were examined. The specific inactivation rate for each pathogen was successfully described by a square-root model as a function of pH. The square-root models were combined with the modified logistic differential equation to obtain a complete inactivation curve. Both the modified logistic and Weibull models provided a highly accurate fitting of the static pH conditions for every pathogen. However, while the residuals plots of the modified logistic model indicated no systematic bias and/or regional prediction problems, the residuals plots of the Weibull model showed a systematic bias. The modified logistic model appropriately predicted the pathogen behavior in the simulated gastric digestion process with actual food, including cut lettuce, minced tuna, hamburger, and scrambled egg. Although the developed model enabled us to predict pathogen inactivation during gastric digestion, its results also suggested that the ingested bacteria in the stomach would barely be inactivated in the real digestion process. The results of this study will provide important information on a part of the dose-response mechanism of bacterial pathogens. PMID:21131530

  8. Models for cell survival with low LET radiation

    International Nuclear Information System (INIS)

    Payne, M.G.; Garrett, W.R.

    1975-01-01

    A model for cell survival under low LET irradiation was developed in which the cell is considered to have N 0 -independent sensitive sites, each of which can exist in either an undamaged state (state A) or one of two damaged states. Radiation can change the sensitive sites from the undamaged state to either of two damaged states. The first damaged state (state B) can either be repaired or be promoted on the second damaged state (state C), which is irreparable. The promotion from the first damaged state to the second can occur due to any of the following: (1) further radiation damage, (2) an abortive attempt to repair the site, or (3) the arrival at a part of the cell cycle where the damage is ''fixed.'' Subject to the further assumptions that radiation damage can occur either indirectly (i.e., through radiation products) or due to direct interaction, and that repair of the first damaged state is a one-step process, expressions can be derived for P(N/sub A/, N/sub B/,t) = probability that after time t a cell will have N/sub A/ sites in state A and N/sub B/ in state B. The problem of determining P(N/sub A/, N/sub B/, t) is formulated for arbitrary time dependences of the radiation field and of all rate coefficients. A large family of cell-survival models can be described by interpreting the sensitive sites in different ways and by making different choices of rate coefficients and of the combinations of numbers of sites in different states that will lead to cell death. (U.S.)

  9. An evaluation of bias in propensity score-adjusted non-linear regression models.

    Science.gov (United States)

    Wan, Fei; Mitra, Nandita

    2018-03-01

    Propensity score methods are commonly used to adjust for observed confounding when estimating the conditional treatment effect in observational studies. One popular method, covariate adjustment of the propensity score in a regression model, has been empirically shown to be biased in non-linear models. However, no compelling underlying theoretical reason has been presented. We propose a new framework to investigate bias and consistency of propensity score-adjusted treatment effects in non-linear models that uses a simple geometric approach to forge a link between the consistency of the propensity score estimator and the collapsibility of non-linear models. Under this framework, we demonstrate that adjustment of the propensity score in an outcome model results in the decomposition of observed covariates into the propensity score and a remainder term. Omission of this remainder term from a non-collapsible regression model leads to biased estimates of the conditional odds ratio and conditional hazard ratio, but not for the conditional rate ratio. We further show, via simulation studies, that the bias in these propensity score-adjusted estimators increases with larger treatment effect size, larger covariate effects, and increasing dissimilarity between the coefficients of the covariates in the treatment model versus the outcome model.

  10. Adjusting the Stems Regional Forest Growth Model to Improve Local Predictions

    Science.gov (United States)

    W. Brad Smith

    1983-01-01

    A simple procedure using double sampling is described for adjusting growth in the STEMS regional forest growth model to compensate for subregional variations. Predictive accuracy of the STEMS model (a distance-independent, individual tree growth model for Lake States forests) was improved by using this procedure

  11. Modeling and Control of the Redundant Parallel Adjustment Mechanism on a Deployable Antenna Panel

    Directory of Open Access Journals (Sweden)

    Lili Tian

    2016-10-01

    Full Text Available With the aim of developing multiple input and multiple output (MIMO coupling systems with a redundant parallel adjustment mechanism on the deployable antenna panel, a structural control integrated design methodology is proposed in this paper. Firstly, the modal information from the finite element model of the structure of the antenna panel is extracted, and then the mathematical model is established with the Hamilton principle; Secondly, the discrete Linear Quadratic Regulator (LQR controller is added to the model in order to control the actuators and adjust the shape of the panel. Finally, the engineering practicality of the modeling and control method based on finite element analysis simulation is verified.

  12. A Log Logistic Survival Model Applied to Hypobaric Decompression Sickness

    Science.gov (United States)

    Conkin, Johnny

    2001-01-01

    Decompression sickness (DCS) is a complex, multivariable problem. A mathematical description or model of the likelihood of DCS requires a large amount of quality research data, ideas on how to define a decompression dose using physical and physiological variables, and an appropriate analytical approach. It also requires a high-performance computer with specialized software. I have used published DCS data to develop my decompression doses, which are variants of equilibrium expressions for evolved gas plus other explanatory variables. My analytical approach is survival analysis, where the time of DCS occurrence is modeled. My conclusions can be applied to simple hypobaric decompressions - ascents lasting from 5 to 30 minutes - and, after minutes to hours, to denitrogenation (prebreathing). They are also applicable to long or short exposures, and can be used whether the sufferer of DCS is at rest or exercising at altitude. Ultimately I would like my models to be applied to astronauts to reduce the risk of DCS during spacewalks, as well as to future spaceflight crews on the Moon and Mars.

  13. Partitioning of excess mortality in population-based cancer patient survival studies using flexible parametric survival models

    Directory of Open Access Journals (Sweden)

    Eloranta Sandra

    2012-06-01

    Full Text Available Abstract Background Relative survival is commonly used for studying survival of cancer patients as it captures both the direct and indirect contribution of a cancer diagnosis on mortality by comparing the observed survival of the patients to the expected survival in a comparable cancer-free population. However, existing methods do not allow estimation of the impact of isolated conditions (e.g., excess cardiovascular mortality on the total excess mortality. For this purpose we extend flexible parametric survival models for relative survival, which use restricted cubic splines for the baseline cumulative excess hazard and for any time-dependent effects. Methods In the extended model we partition the excess mortality associated with a diagnosis of cancer through estimating a separate baseline excess hazard function for the outcomes under investigation. This is done by incorporating mutually exclusive background mortality rates, stratified by the underlying causes of death reported in the Swedish population, and by introducing cause of death as a time-dependent effect in the extended model. This approach thereby enables modeling of temporal trends in e.g., excess cardiovascular mortality and remaining cancer excess mortality simultaneously. Furthermore, we illustrate how the results from the proposed model can be used to derive crude probabilities of death due to the component parts, i.e., probabilities estimated in the presence of competing causes of death. Results The method is illustrated with examples where the total excess mortality experienced by patients diagnosed with breast cancer is partitioned into excess cardiovascular mortality and remaining cancer excess mortality. Conclusions The proposed method can be used to simultaneously study disease patterns and temporal trends for various causes of cancer-consequent deaths. Such information should be of interest for patients and clinicians as one way of improving prognosis after cancer is

  14. Steps in the construction and verification of an explanatory model of psychosocial adjustment

    Directory of Open Access Journals (Sweden)

    Arantzazu Rodríguez-Fernández

    2016-06-01

    Full Text Available The aim of the present study was to empirically test an explanatory model of psychosocial adjustment during adolescence, with psychosocial adjustment during this stage being understood as a combination of school adjustment (or school engagement and subjective well-being. According to the hypothetic model, psychosocial adjustment depends on self-concept and resilience, which in turn act as mediators of the influence of perceived social support (from family, peers and teachers on this adjustment. Participants were 1250 secondary school students (638 girls and 612 boys aged between 12 and 15 years (Mean = 13.72; SD = 1.09. The results provided evidence of: (a the influence of all three types of perceived support on subject resilience and self-concept, with perceived family support being particularly important in this respect; (b the influence of the support received from teachers on school adjustment and support received from the family on psychological wellbeing; and (c the absence of any direct influence of peer support on psychosocial adjustment, although indirect influence was observed through the psychological variables studied. These results are discussed from an educational perspective and in terms of future research.

  15. Steps in the construction and verification of an explanatory model of psychosocial adjustment

    Directory of Open Access Journals (Sweden)

    Arantzazu Rodríguez-Fernández

    2016-06-01

    Full Text Available The aim of the present study was to empirically test an explanatory model of psychosocial adjustment during adolescence, with psychosocial adjustment during this stage being understood as a combination of school adjustment (or school engagement and subjective well-being. According to the hypothetic model, psychosocial adjustment depends on self-concept and resilience, which in turn act as mediators of the influence of perceived social support (from family, peers and teachers on this adjustment. Participants were 1250 secondary school students (638 girls and 612 boys aged between 12 and 15 years (Mean = 13.72; SD = 1.09. The results provided evidence of: (a the influence of all three types of perceived support on subject resilience and self-concept, with perceived family support being particularly important in this respect; (b the influence of the support received from teachers on school adjustment and support received from the family on psychological wellbeing; and (c the absence of any direct influence of peer support on psychosocial adjustment, although indirect influence was observed through the psychological variables studied. These results are discussed from an educational perspective and in terms of future research

  16. Implication of Mauk Nursing Rehabilitation Model on Adjustment of Stroke Patients

    Directory of Open Access Journals (Sweden)

    Zeinab Ebrahimpour mouziraji

    2014-12-01

    Full Text Available Objectives: Stroke is a neurological syndrome with sudden onset or gradual destruction of brain vessels, which may take 24 hours or more. Complications of stroke effect in the variation aspects of the individual. According to De Spulveda and Chang’s Studies, disability reduced the effective adjustment. This study aimed to overview the adjustment of stroke patients based on the main concepts of rehabilitation nursing Mauk model. Methods: In a quasi-experimental one group pre-posttest design study, data was collected in the neurology clinic of Imam Khomeini hospital and stroke patient rehabilitation centers in Tehran (Tabassom. Data collection included demographic and adjustment questionnaires of stroke patients. The intervention included seven sessions as Mauk model, each session with one hour training, for seven patients. Data analysis performed with SPSS software with paired t-test and was compared with previous results. Results: There were significant differences between the mean scores of patients with stroke adjustment questionnaire in the pre-test-post-test. But in the adjustment sub-scales, except for relationship with wife and Personal adjustment, in other areas, there is no statistically significant difference between the pre and posttest. Discussion: The results indicated that training has been affected on some aspects of adjustment of stroke patients in order to, as improving functions, complications and its limitations. Nurses can help then with implementing of plans such as patients education in this regard.

  17. High-dose chemotherapy for patients with high-risk breast cancer: a clinical and economic assessment using a quality-adjusted survival analysis.

    Science.gov (United States)

    Marino, Patricia; Roché, Henri; Moatti, Jean-Paul

    2008-04-01

    The benefit of high-dose chemotherapy (HDC) has not been clearly demonstrated. It may offer disease-free survival improvement at the expense of major toxicity and increasing cost. We evaluated the trade-offs between toxicity, relapse, and costs using a quality-adjusted time without symptoms or toxicity (Q-TWiST) analysis. The analysis was conducted in the context of a randomized trial (PEGASE 01) evaluating the benefit of HDC for 314 patients with high-risk breast cancer. A Q-TWiST analysis was first performed to compare HDC with standard chemotherapy. We then used the results of this Q-TWiST analysis to inform a cost per quality-adjusted life-year (QALY) comparison between treatments. Q-TWiST durations were in favor of HDC, whatever the weighting coefficients used for the analysis. This benefit was significant when the weighting coefficient related to the time spent after relapse was low (0.78), HDC offered no benefit. For intermediate values, the results depended on the weighting coefficient attributed to the toxicity period. The incremental cost per QALY ranged from 12,691euro/QALY to 26,439euro/QALY, according to the coefficients used to weight toxicity and relapse. The benefits of HDC outweigh the burdens of treatment for a wide range of utility coefficients. Economic impact is not a barrier to HDC diffusion in this situation. Nevertheless, no significant benefit was demonstrated for a certain range of utility values.

  18. Impact of censoring on learning Bayesian networks in survival modelling.

    Science.gov (United States)

    Stajduhar, Ivan; Dalbelo-Basić, Bojana; Bogunović, Nikola

    2009-11-01

    Bayesian networks are commonly used for presenting uncertainty and covariate interactions in an easily interpretable way. Because of their efficient inference and ability to represent causal relationships, they are an excellent choice for medical decision support systems in diagnosis, treatment, and prognosis. Although good procedures for learning Bayesian networks from data have been defined, their performance in learning from censored survival data has not been widely studied. In this paper, we explore how to use these procedures to learn about possible interactions between prognostic factors and their influence on the variate of interest. We study how censoring affects the probability of learning correct Bayesian network structures. Additionally, we analyse the potential usefulness of the learnt models for predicting the time-independent probability of an event of interest. We analysed the influence of censoring with a simulation on synthetic data sampled from randomly generated Bayesian networks. We used two well-known methods for learning Bayesian networks from data: a constraint-based method and a score-based method. We compared the performance of each method under different levels of censoring to those of the naive Bayes classifier and the proportional hazards model. We did additional experiments on several datasets from real-world medical domains. The machine-learning methods treated censored cases in the data as event-free. We report and compare results for several commonly used model evaluation metrics. On average, the proportional hazards method outperformed other methods in most censoring setups. As part of the simulation study, we also analysed structural similarities of the learnt networks. Heavy censoring, as opposed to no censoring, produces up to a 5% surplus and up to 10% missing total arcs. It also produces up to 50% missing arcs that should originally be connected to the variate of interest. Presented methods for learning Bayesian networks from

  19. Re-evaluating neonatal-age models for ungulates: does model choice affect survival estimates?

    Directory of Open Access Journals (Sweden)

    Troy W Grovenburg

    Full Text Available New-hoof growth is regarded as the most reliable metric for predicting age of newborn ungulates, but variation in estimated age among hoof-growth equations that have been developed may affect estimates of survival in staggered-entry models. We used known-age newborns to evaluate variation in age estimates among existing hoof-growth equations and to determine the consequences of that variation on survival estimates. During 2001-2009, we captured and radiocollared 174 newborn (≤24-hrs old ungulates: 76 white-tailed deer (Odocoileus virginianus in Minnesota and South Dakota, 61 mule deer (O. hemionus in California, and 37 pronghorn (Antilocapra americana in South Dakota. Estimated age of known-age newborns differed among hoof-growth models and varied by >15 days for white-tailed deer, >20 days for mule deer, and >10 days for pronghorn. Accuracy (i.e., the proportion of neonates assigned to the correct age in aging newborns using published equations ranged from 0.0% to 39.4% in white-tailed deer, 0.0% to 3.3% in mule deer, and was 0.0% for pronghorns. Results of survival modeling indicated that variability in estimates of age-at-capture affected short-term estimates of survival (i.e., 30 days for white-tailed deer and mule deer, and survival estimates over a longer time frame (i.e., 120 days for mule deer. Conversely, survival estimates for pronghorn were not affected by estimates of age. Our analyses indicate that modeling survival in daily intervals is too fine a temporal scale when age-at-capture is unknown given the potential inaccuracies among equations used to estimate age of neonates. Instead, weekly survival intervals are more appropriate because most models accurately predicted ages within 1 week of the known age. Variation among results of neonatal-age models on short- and long-term estimates of survival for known-age young emphasizes the importance of selecting an appropriate hoof-growth equation and appropriately defining intervals (i

  20. Modelling the joint distribution of competing risks survival times using copula functions

    OpenAIRE

    Kaishev, V. K.; Haberman, S.; Dimitrova, D. S.

    2005-01-01

    The problem of modelling the joint distribution of survival times in a competing risks model, using copula functions is considered. In order to evaluate this joint distribution and the related overall survival function, a system of non-linear differential equations is solved, which relates the crude and net survival functions of the modelled competing risks, through the copula. A similar approach to modelling dependent multiple decrements was applied by Carriere (1994) who used a Gaussian cop...

  1. Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco Use in the United States

    Science.gov (United States)

    Kaplan, Robert M.; Anderson, John P.; Kaplan, Cameron M.

    2007-01-01

    Purpose: To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method: We obtained estimates of tobacco consumption from 6 years of the National Health Interview…

  2. Evaluation of the Stress Adjustment and Adaptation Model among Families Reporting Economic Pressure

    Science.gov (United States)

    Vandsburger, Etty; Biggerstaff, Marilyn A.

    2004-01-01

    This research evaluates the Stress Adjustment and Adaptation Model (double ABCX model) examining the effects resiliency resources on family functioning when families experience economic pressure. Families (N = 128) with incomes at or below the poverty line from a rural area of a southern state completed measures of perceived economic pressure,…

  3. Emotional closeness to parents and grandparents: A moderated mediation model predicting adolescent adjustment.

    Science.gov (United States)

    Attar-Schwartz, Shalhevet

    2015-09-01

    Warm and emotionally close relationships with parents and grandparents have been found in previous studies to be linked with better adolescent adjustment. The present study, informed by Family Systems Theory and Intergenerational Solidarity Theory, uses a moderated mediation model analyzing the contribution of the dynamics of these intergenerational relationships to adolescent adjustment. Specifically, it examines the mediating role of emotional closeness to the closest grandparent in the relationship between emotional closeness to a parent (the offspring of the closest grandparent) and adolescent adjustment difficulties. The model also examines the moderating role of emotional closeness to parents in the relationship between emotional closeness to grandparents and adjustment difficulties. The study was based on a sample of 1,405 Jewish Israeli secondary school students (ages 12-18) who completed a structured questionnaire. It was found that emotional closeness to the closest grandparent was more strongly associated with reduced adjustment difficulties among adolescents with higher levels of emotional closeness to their parents. In addition, adolescent adjustment and emotional closeness to parents was partially mediated by emotional closeness to grandparents. Examining the family conditions under which adolescents' relationships with grandparents is stronger and more beneficial for them can help elucidate variations in grandparent-grandchild ties and expand our understanding of the mechanisms that shape child outcomes. (c) 2015 APA, all rights reserved).

  4. Risk adjustment models for short-term outcomes after surgical resection for oesophagogastric cancer.

    Science.gov (United States)

    Fischer, C; Lingsma, H; Hardwick, R; Cromwell, D A; Steyerberg, E; Groene, O

    2016-01-01

    Outcomes for oesophagogastric cancer surgery are compared with the aim of benchmarking quality of care. Adjusting for patient characteristics is crucial to avoid biased comparisons between providers. The study objective was to develop a case-mix adjustment model for comparing 30- and 90-day mortality and anastomotic leakage rates after oesophagogastric cancer resections. The study reviewed existing models, considered expert opinion and examined audit data in order to select predictors that were consequently used to develop a case-mix adjustment model for the National Oesophago-Gastric Cancer Audit, covering England and Wales. Models were developed on patients undergoing surgical resection between April 2011 and March 2013 using logistic regression. Model calibration and discrimination was quantified using a bootstrap procedure. Most existing risk models for oesophagogastric resections were methodologically weak, outdated or based on detailed laboratory data that are not generally available. In 4882 patients with oesophagogastric cancer used for model development, 30- and 90-day mortality rates were 2·3 and 4·4 per cent respectively, and 6·2 per cent of patients developed an anastomotic leak. The internally validated models, based on predictors selected from the literature, showed moderate discrimination (area under the receiver operating characteristic (ROC) curve 0·646 for 30-day mortality, 0·664 for 90-day mortality and 0·587 for anastomotic leakage) and good calibration. Based on available data, three case-mix adjustment models for postoperative outcomes in patients undergoing curative surgery for oesophagogastric cancer were developed. These models should be used for risk adjustment when assessing hospital performance in the National Health Service, and tested in other large health systems. © 2015 BJS Society Ltd Published by John Wiley & Sons Ltd.

  5. Conference Innovations in Derivatives Market : Fixed Income Modeling, Valuation Adjustments, Risk Management, and Regulation

    CERN Document Server

    Grbac, Zorana; Scherer, Matthias; Zagst, Rudi

    2016-01-01

    This book presents 20 peer-reviewed chapters on current aspects of derivatives markets and derivative pricing. The contributions, written by leading researchers in the field as well as experienced authors from the financial industry, present the state of the art in: • Modeling counterparty credit risk: credit valuation adjustment, debit valuation adjustment, funding valuation adjustment, and wrong way risk. • Pricing and hedging in fixed-income markets and multi-curve interest-rate modeling. • Recent developments concerning contingent convertible bonds, the measuring of basis spreads, and the modeling of implied correlations. The recent financial crisis has cast tremendous doubts on the classical view on derivative pricing. Now, counterparty credit risk and liquidity issues are integral aspects of a prudent valuation procedure and the reference interest rates are represented by a multitude of curves according to their different periods and maturities. A panel discussion included in the book (featuring D...

  6. NanOx, a new model to predict cell survival in the context of particle therapy

    Science.gov (United States)

    Cunha, M.; Monini, C.; Testa, E.; Beuve, M.

    2017-02-01

    Particle therapy is increasingly attractive for the treatment of tumors and the number of facilities offering it is rising worldwide. Due to the well-known enhanced effectiveness of ions, it is of utmost importance to plan treatments with great care to ensure tumor killing and healthy tissues sparing. Hence, the accurate quantification of the relative biological effectiveness (RBE) of ions, used in the calculation of the biological dose, is critical. Nevertheless, the RBE is a complex function of many parameters and its determination requires modeling. The approaches currently used have allowed particle therapy to thrive, but still show some shortcomings. We present herein a short description of a new theoretical framework, NanOx, to calculate cell survival in the context of particle therapy. It gathers principles from existing approaches, while addressing some of their weaknesses. NanOx is a multiscale model that takes the stochastic nature of radiation at nanometric and micrometric scales fully into account, integrating also the chemical aspects of radiation-matter interaction. The latter are included in the model by means of a chemical specific energy, determined from the production of reactive chemical species induced by irradiation. Such a production represents the accumulation of oxidative stress and sublethal damage in the cell, potentially generating non-local lethal events in NanOx. The complementary local lethal events occur in a very localized region and can, alone, lead to cell death. Both these classes of events contribute to cell death. The comparison between experimental data and model predictions for the V79 cell line show a good agreement. In particular, the dependence of the typical shoulders of cell survival curves on linear energy transfer are well described, but also the effectiveness of different ions, including the overkill effect. These results required the adjustment of a number of parameters compatible with the application of the model in

  7. Droop Control with an Adjustable Complex Virtual Impedance Loop based on Cloud Model Theory

    DEFF Research Database (Denmark)

    Li, Yan; Shuai, Zhikang; Xu, Qinming

    2016-01-01

    Droop control framework with an adjustable virtual impedance loop is proposed in this paper, which is based on the cloud model theory. The proposed virtual impedance loop includes two terms: a negative virtual resistor and an adjustable virtual inductance. The negative virtual resistor term...... sometimes. The cloud model theory is applied to get online the changing line impedance value, which relies on the relevance of the reactive power responding the changing line impedance. The verification of the proposed control strategy is done according to the simulation in a low voltage microgrid in Matlab....

  8. Contact angle adjustment in equation-of-state-based pseudopotential model.

    Science.gov (United States)

    Hu, Anjie; Li, Longjian; Uddin, Rizwan; Liu, Dong

    2016-05-01

    The single component pseudopotential lattice Boltzmann model has been widely applied in multiphase simulation due to its simplicity and stability. In many studies, it has been claimed that this model can be stable for density ratios larger than 1000. However, the application of the model is still limited to small density ratios when the contact angle is considered. The reason is that the original contact angle adjustment method influences the stability of the model. Moreover, simulation results in the present work show that, by applying the original contact angle adjustment method, the density distribution near the wall is artificially changed, and the contact angle is dependent on the surface tension. Hence, it is very inconvenient to apply this method with a fixed contact angle, and the accuracy of the model cannot be guaranteed. To solve these problems, a contact angle adjustment method based on the geometry analysis is proposed and numerically compared with the original method. Simulation results show that, with our contact angle adjustment method, the stability of the model is highly improved when the density ratio is relatively large, and it is independent of the surface tension.

  9. Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

    Science.gov (United States)

    Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

    2009-04-01

    Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

  10. Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

    Science.gov (United States)

    Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

    2012-01-01

    State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow

  11. Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

    Science.gov (United States)

    Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard

    2016-10-01

    In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

  12. Testing a social ecological model for relations between political violence and child adjustment in Northern Ireland.

    Science.gov (United States)

    Cummings, E Mark; Merrilees, Christine E; Schermerhorn, Alice C; Goeke-Morey, Marcie C; Shirlow, Peter; Cairns, Ed

    2010-05-01

    Relations between political violence and child adjustment are matters of international concern. Past research demonstrates the significance of community, family, and child psychological processes in child adjustment, supporting study of interrelations between multiple social ecological factors and child adjustment in contexts of political violence. Testing a social ecological model, 300 mothers and their children (M = 12.28 years, SD = 1.77) from Catholic and Protestant working class neighborhoods in Belfast, Northern Ireland, completed measures of community discord, family relations, and children's regulatory processes (i.e., emotional security) and outcomes. Historical political violence in neighborhoods based on objective records (i.e., politically motivated deaths) were related to family members' reports of current sectarian antisocial behavior and nonsectarian antisocial behavior. Interparental conflict and parental monitoring and children's emotional security about both the community and family contributed to explanatory pathways for relations between sectarian antisocial behavior in communities and children's adjustment problems. The discussion evaluates support for social ecological models for relations between political violence and child adjustment and its implications for understanding relations in other parts of the world.

  13. A Threshold Model of Social Support, Adjustment, and Distress after Breast Cancer Treatment

    Science.gov (United States)

    Mallinckrodt, Brent; Armer, Jane M.; Heppner, P. Paul

    2012-01-01

    This study examined a threshold model that proposes that social support exhibits a curvilinear association with adjustment and distress, such that support in excess of a critical threshold level has decreasing incremental benefits. Women diagnosed with a first occurrence of breast cancer (N = 154) completed survey measures of perceived support…

  14. Development of a model for case-mix adjustment of pressure ulcer prevalence rates.

    NARCIS (Netherlands)

    Bours, G.J.J.W.; Halfens, J.; Berger, M.P.; Abu-Saad, H.H.; Grol, R.P.T.M.

    2003-01-01

    BACKGROUND: Acute care hospitals participating in the Dutch national pressure ulcer prevalence survey use the results of this survey to compare their outcomes and assess their quality of care regarding pressure ulcer prevention. The development of a model for case-mix adjustment is essential for the

  15. 10 km running performance predicted by a multiple linear regression model with allometrically adjusted variables.

    Science.gov (United States)

    Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O

    2016-06-01

    The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.

  16. Towards an Integrated Conceptual Model of International Student Adjustment and Adaptation

    Science.gov (United States)

    Schartner, Alina; Young, Tony Johnstone

    2016-01-01

    Despite a burgeoning body of empirical research on "the international student experience", the area remains under-theorized. The literature to date lacks a guiding conceptual model that captures the adjustment and adaptation trajectories of this unique, growing, and important sojourner group. In this paper, we therefore put forward a…

  17. A Four-Part Model of Autonomy during Emerging Adulthood: Associations with Adjustment

    Science.gov (United States)

    Lamborn, Susie D.; Groh, Kelly

    2009-01-01

    We found support for a four-part model of autonomy that links connectedness, separation, detachment, and agency to adjustment during emerging adulthood. Based on self-report surveys of 285 American college students, expected associations among the autonomy variables were found. In addition, agency, as measured by self-reliance, predicted lower…

  18. Testing an Attachment Model of Latina/o College Students' Psychological Adjustment

    Science.gov (United States)

    Garriott, Patton O.; Love, Keisha M.; Tyler, Kenneth M.; Thomas, Deneia M.; Roan-Belle, Clarissa R.; Brown, Carrie L.

    2010-01-01

    The present study examined the influence of attachment relationships on the psychological adjustment of Latina/o university students (N = 80) attending predominantly White institutions of higher education. A path analysis conducted to test a hypothesized model of parent and peer attachment, self-esteem, and psychological distress indicated that…

  19. Rational Multi-curve Models with Counterparty-risk Valuation Adjustments

    DEFF Research Database (Denmark)

    Crépey, Stéphane; Macrina, Andrea; Nguyen, Tuyet Mai

    2016-01-01

    We develop a multi-curve term structure set-up in which the modelling ingredients are expressed by rational functionals of Markov processes. We calibrate to London Interbank Offer Rate swaptions data and show that a rational two-factor log-normal multi-curve model is sufficient to match market da...... with regulatory obligations. In order to compute counterparty-risk valuation adjustments, such as credit valuation adjustment, we show how default intensity processes with rational form can be derived. We flesh out our study by applying the results to a basis swap contract....... with accuracy. We elucidate the relationship between the models developed and calibrated under a risk-neutral measure Q and their consistent equivalence class under the real-world probability measure P. The consistent P-pricing models are applied to compute the risk exposures which may be required to comply...

  20. Adjustment modes in the trajectory of progressive multiple sclerosis: a qualitative study and conceptual model.

    Science.gov (United States)

    Bogosian, Angeliki; Morgan, Myfanwy; Bishop, Felicity L; Day, Fern; Moss-Morris, Rona

    2017-03-01

    We examined cognitive and behavioural challenges and adaptations for people with progressive multiple sclerosis (MS) and developed a preliminary conceptual model of changes in adjustment over time. Using theoretical sampling, 34 semi-structured interviews were conducted with people with MS. Participants were between 41 and 77 years of age. Thirteen were diagnosed with primary progressive MS and 21 with secondary progressive MS. Data were analysed using a grounded theory approach. Participants described initially bracketing the illness off and carrying on their usual activities but this became problematic as the condition progressed and they employed different adjustment modes to cope with increased disabilities. Some scaled back their activities to live a more comfortable life, others identified new activities or adapted old ones, whereas at times, people disengaged from the adjustment process altogether and resigned to their condition. Relationships with partners, emotional reactions, environment and perception of the environment influenced adjustment, while people were often flexible and shifted among modes. Adjusting to a progressive condition is a fluid process. Future interventions can be tailored to address modifiable factors at different stages of the condition and may involve addressing emotional reactions concealing/revealing the condition and perceptions of the environment.

  1. Evolution Scenarios at the Romanian Economy Level, Using the R.M. Solow Adjusted Model

    Directory of Open Access Journals (Sweden)

    Stelian Stancu

    2008-06-01

    Full Text Available Besides the models of M. Keynes, R.F. Harrod, E. Domar, D. Romer, Ramsey-Cass-Koopmans model etc., the R.M. Solow model is part of the category which characterizes the economic growth. The paper proposes the presentation of the R.M. Solow adjusted model with specific simulation characteristics and economic growth scenario. Considering these aspects, there are presented the values obtained at the economy level, behind the simulations, about the ratio Capital on the output volume, Output volume on employee, equal with the current labour efficiency, as well as the Labour efficiency value.

  2. Estimation and model selection of semiparametric multivariate survival functions under general censorship.

    Science.gov (United States)

    Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

    2010-07-01

    We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root- n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

  3. Modeling survival: application of the Andersen-Gill model to Yellowstone grizzly bears

    Science.gov (United States)

    Johnson, Christopher J.; Boyce, Mark S.; Schwartz, Charles C.; Haroldson, Mark A.

    2004-01-01

     Wildlife ecologists often use the Kaplan-Meier procedure or Cox proportional hazards model to estimate survival rates, distributions, and magnitude of risk factors. The Andersen-Gill formulation (A-G) of the Cox proportional hazards model has seen limited application to mark-resight data but has a number of advantages, including the ability to accommodate left-censored data, time-varying covariates, multiple events, and discontinuous intervals of risks. We introduce the A-G model including structure of data, interpretation of results, and assessment of assumptions. We then apply the model to 22 years of radiotelemetry data for grizzly bears (Ursus arctos) of the Greater Yellowstone Grizzly Bear Recovery Zone in Montana, Idaho, and Wyoming, USA. We used Akaike's Information Criterion (AICc) and multi-model inference to assess a number of potentially useful predictive models relative to explanatory covariates for demography, human disturbance, and habitat. Using the most parsimonious models, we generated risk ratios, hypothetical survival curves, and a map of the spatial distribution of high-risk areas across the recovery zone. Our results were in agreement with past studies of mortality factors for Yellowstone grizzly bears. Holding other covariates constant, mortality was highest for bears that were subjected to repeated management actions and inhabited areas with high road densities outside Yellowstone National Park. Hazard models developed with covariates descriptive of foraging habitats were not the most parsimonious, but they suggested that high-elevation areas offered lower risks of mortality when compared to agricultural areas.

  4. Price adjustment for traditional Chinese medicine procedures: Based on a standardized value parity model.

    Science.gov (United States)

    Wang, Haiyin; Jin, Chunlin; Jiang, Qingwu

    2017-11-20

    Traditional Chinese medicine (TCM) is an important part of China's medical system. Due to the prolonged low price of TCM procedures and the lack of an effective mechanism for dynamic price adjustment, the development of TCM has markedly lagged behind Western medicine. The World Health Organization (WHO) has emphasized the need to enhance the development of alternative and traditional medicine when creating national health care systems. The establishment of scientific and appropriate mechanisms to adjust the price of medical procedures in TCM is crucial to promoting the development of TCM. This study has examined incorporating value indicators and data on basic manpower expended, time spent, technical difficulty, and the degree of risk in the latest standards for the price of medical procedures in China, and this study also offers a price adjustment model with the relative price ratio as a key index. This study examined 144 TCM procedures and found that prices of TCM procedures were mainly based on the value of medical care provided; on average, medical care provided accounted for 89% of the price. Current price levels were generally low and the current price accounted for 56% of the standardized value of a procedure, on average. Current price levels accounted for a markedly lower standardized value of acupuncture, moxibustion, special treatment with TCM, and comprehensive TCM procedures. This study selected a total of 79 procedures and adjusted them by priority. The relationship between the price of TCM procedures and the suggested price was significantly optimized (p based on a standardized value parity model is a scientific and suitable method of price adjustment that can serve as a reference for other provinces and municipalities in China and other countries and regions that mainly have fee-for-service (FFS) medical care.

  5. Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes

    Science.gov (United States)

    2012-11-01

    2012 4. TITLE AND SUBTITLE Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes 5a. CONTRACT NUMBER 5b. GRANT ...may be used to construct spatially varying wind fields for the GOM region (e.g., Thompson and Cardone [12]), but this requires using a complicated...Storm Damage Reduc- tion, and Dredging Operations and Environmental Research (DOER). The USACE Headquarters granted permission to publish this paper

  6. Radar adjusted data versus modelled precipitation: a case study over Cyprus

    Directory of Open Access Journals (Sweden)

    M. Casaioli

    2006-01-01

    Full Text Available In the framework of the European VOLTAIRE project (Fifth Framework Programme, simulations of relatively heavy precipitation events, which occurred over the island of Cyprus, by means of numerical atmospheric models were performed. One of the aims of the project was indeed the comparison of modelled rainfall fields with multi-sensor observations. Thus, for the 5 March 2003 event, the 24-h accumulated precipitation BOlogna Limited Area Model (BOLAM forecast was compared with the available observations reconstructed from ground-based radar data and estimated by rain gauge data. Since radar data may be affected by errors depending on the distance from the radar, these data could be range-adjusted by using other sensors. In this case, the Precipitation Radar aboard the Tropical Rainfall Measuring Mission (TRMM satellite was used to adjust the ground-based radar data with a two-parameter scheme. Thus, in this work, two observational fields were employed: the rain gauge gridded analysis and the observational analysis obtained by merging the range-adjusted radar and rain gauge fields. In order to verify the modelled precipitation, both non-parametric skill scores and the contiguous rain area (CRA analysis were applied. Skill score results show some differences when using the two observational fields. CRA results are instead quite in agreement, showing that in general a 0.27° eastward shift optimizes the forecast with respect to the two observational analyses. This result is also supported by a subjective inspection of the shifted forecast field, whose gross features agree with the analysis pattern more than the non-shifted forecast one. However, some open questions, especially regarding the effect of other range adjustment techniques, remain open and need to be addressed in future works.

  7. Risk-adjusted Outcomes of Clinically Relevant Pancreatic Fistula Following Pancreatoduodenectomy: A Model for Performance Evaluation.

    Science.gov (United States)

    McMillan, Matthew T; Soi, Sameer; Asbun, Horacio J; Ball, Chad G; Bassi, Claudio; Beane, Joal D; Behrman, Stephen W; Berger, Adam C; Bloomston, Mark; Callery, Mark P; Christein, John D; Dixon, Elijah; Drebin, Jeffrey A; Castillo, Carlos Fernandez-Del; Fisher, William E; Fong, Zhi Ven; House, Michael G; Hughes, Steven J; Kent, Tara S; Kunstman, John W; Malleo, Giuseppe; Miller, Benjamin C; Salem, Ronald R; Soares, Kevin; Valero, Vicente; Wolfgang, Christopher L; Vollmer, Charles M

    2016-08-01

    To evaluate surgical performance in pancreatoduodenectomy using clinically relevant postoperative pancreatic fistula (CR-POPF) occurrence as a quality indicator. Accurate assessment of surgeon and institutional performance requires (1) standardized definitions for the outcome of interest and (2) a comprehensive risk-adjustment process to control for differences in patient risk. This multinational, retrospective study of 4301 pancreatoduodenectomies involved 55 surgeons at 15 institutions. Risk for CR-POPF was assessed using the previously validated Fistula Risk Score, and pancreatic fistulas were stratified by International Study Group criteria. CR-POPF variability was evaluated and hierarchical regression analysis assessed individual surgeon and institutional performance. There was considerable variability in both CR-POPF risk and occurrence. Factors increasing the risk for CR-POPF development included increasing Fistula Risk Score (odds ratio 1.49 per point, P ratio 3.30, P performance outliers were identified at the surgeon and institutional levels. Of the top 10 surgeons (≥15 cases) for nonrisk-adjusted performance, only 6 remained in this high-performing category following risk adjustment. This analysis of pancreatic fistulas following pancreatoduodenectomy demonstrates considerable variability in both the risk and occurrence of CR-POPF among surgeons and institutions. Disparities in patient risk between providers reinforce the need for comprehensive, risk-adjusted modeling when assessing performance based on procedure-specific complications. Furthermore, beyond inherent patient risk factors, surgical decision-making influences fistula outcomes.

  8. Economic analysis of coal price-electricity price adjustment in China based on the CGE model

    International Nuclear Information System (INIS)

    He, Y.X.; Zhang, S.L.; Yang, L.Y.; Wang, Y.J.; Wang, J.

    2010-01-01

    In recent years, coal price has risen rapidly, which has also brought a sharp increase in the expenditures of thermal power plants in China. Meantime, the power production price and power retail price have not been adjusted accordingly and a large number of thermal power plants have incurred losses. The power industry is a key industry in the national economy. As such, a thorough analysis and evaluation of the economic influence of the electricity price should be conducted before electricity price adjustment is carried out. This paper analyses the influence of coal price adjustment on the electric power industry, and the influence of electricity price adjustment on the macroeconomy in China based on computable general equilibrium models. The conclusions are as follows: (1) a coal price increase causes a rise in the cost of the electric power industry, but the influence gradually descends with increase in coal price; and (2) an electricity price increase has an adverse influence on the total output, Gross Domestic Product (GDP), and the Consumer Price Index (CPI). Electricity price increases have a contractionary effect on economic development and, consequently, electricity price policy making must consequently consider all factors to minimize their adverse influence.

  9. A metallic solution model with adjustable parameter for describing ternary thermodynamic properties from its binary constituents

    International Nuclear Information System (INIS)

    Fang Zheng; Qiu Guanzhou

    2007-01-01

    A metallic solution model with adjustable parameter k has been developed to predict thermodynamic properties of ternary systems from those of its constituent three binaries. In the present model, the excess Gibbs free energy for a ternary mixture is expressed as a weighted probability sum of those of binaries and the k value is determined based on an assumption that the ternary interaction generally strengthens the mixing effects for metallic solutions with weak interaction, making the Gibbs free energy of mixing of the ternary system more negative than that before considering the interaction. This point is never considered in the models currently reported, where the only difference in a geometrical definition of molar values of components is considered that do not involve thermodynamic principles but are completely empirical. The current model describes the results of experiments very well, and by adjusting the k value also agrees with those from models used widely in the literature. Three ternary systems, Mg-Cu-Ni, Zn-In-Cd, and Cd-Bi-Pb are recalculated to demonstrate the method of determining k and the precision of the model. The results of the calculations, especially those in Mg-Cu-Ni system, are better than those predicted by the current models in the literature

  10. Conceptual Model for Simulating the Adjustments of Bankfull Characteristics in the Lower Yellow River, China

    Directory of Open Access Journals (Sweden)

    Yuanjian Wang

    2014-01-01

    Full Text Available We present a conceptual model for simulating the temporal adjustments in the banks of the Lower Yellow River (LYR. Basic conservation equations for mass, friction, and sediment transport capacity and the Exner equation were adopted to simulate the hydrodynamics underlying fluvial processes. The relationship between changing rates in bankfull width and depth, derived from quasiuniversal hydraulic geometries, was used as a closure for the hydrodynamic equations. On inputting the daily flow discharge and sediment load, the conceptual model successfully simulated the 30-year adjustments in the bankfull geometries of typical reaches of the LYR. The square of the correlating coefficient reached 0.74 for Huayuankou Station in the multiple-thread reach and exceeded 0.90 for Lijin Station in the meandering reach. This proposed model allows multiple dependent variables and the input of daily hydrological data for long-term simulations. This links the hydrodynamic and geomorphic processes in a fluvial river and has potential applicability to fluvial rivers undergoing significant adjustments.

  11. Risk-adjusted performance evaluation in three academic thoracic surgery units using the Eurolung risk models.

    Science.gov (United States)

    Pompili, Cecilia; Shargall, Yaron; Decaluwe, Herbert; Moons, Johnny; Chari, Madhu; Brunelli, Alessandro

    2018-01-03

    The objective of this study was to evaluate the performance of 3 thoracic surgery centres using the Eurolung risk models for morbidity and mortality. This was a retrospective analysis performed on data collected from 3 academic centres (2014-2016). Seven hundred and twenty-one patients in Centre 1, 857 patients in Centre 2 and 433 patients in Centre 3 who underwent anatomical lung resections were analysed. The Eurolung1 and Eurolung2 models were used to predict risk-adjusted cardiopulmonary morbidity and 30-day mortality rates. Observed and risk-adjusted outcomes were compared within each centre. The observed morbidity of Centre 1 was in line with the predicted morbidity (observed 21.1% vs predicted 22.7%, P = 0.31). Centre 2 performed better than expected (observed morbidity 20.2% vs predicted 26.7%, P models were successfully used as risk-adjusting instruments to internally audit the outcomes of 3 different centres, showing their applicability for future quality improvement initiatives. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  12. Ensemble of cell survival experiments after ion irradiation for validation of RBE models

    Energy Technology Data Exchange (ETDEWEB)

    Friedrich, Thomas; Scholz, Uwe; Scholz, Michael [GSI Helmholtzzentrum fuer Schwerionenforschung, Darmstadt (Germany); Durante, Marco [GSI Helmholtzzentrum fuer Schwerionenforschung, Darmstadt (Germany); Institut fuer Festkoerperphysik, TU Darmstadt, Darmstadt (Germany)

    2012-07-01

    There is persistent interest in understanding the systematics of the relative biological effectiveness (RBE). Models such as the Local Effect Model (LEM) or the Microdosimetric Kinetic Model have the goal to predict the RBE. For the validation of these models a collection of many in-vitro cell survival experiments is most appropriate. The set-up of an ensemble of in-vitro cell survival data comprising about 850 survival experiments after both ion and photon irradiation is reported. The survival curves have been taken out from publications. The experiments encompass survival curves obtained in different labs, using different ion species from protons to uranium, varying irradiation modalities (shaped or monoenergetic beam), various energies and linear energy transfers, and a whole variety of cell types (human or rodent; normal, mutagenic or tumor; radioresistant or -sensitive). Each cell survival curve has been parameterized by the linear-quadratic model. The photon parameters have been added to the data base to allow to calculate the experimental RBE to any survival level. We report on experimental trends found within the data ensemble. The data will serve as a testing ground for RBE models such as the LEM. Finally, a roadmap for further validation and first model results using the data base in combination with the LEM are presented.

  13. Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment.

    Science.gov (United States)

    Qiao, Hong; Xi, Xuanyang; Li, Yinlin; Wu, Wei; Li, Fengfu

    2015-11-01

    Recently, many computational models have been proposed to simulate visual cognition process. For example, the hierarchical Max-Pooling (HMAX) model was proposed according to the hierarchical and bottom-up structure of V1 to V4 in the ventral pathway of primate visual cortex, which could achieve position- and scale-tolerant recognition. In our previous work, we have introduced memory and association into the HMAX model to simulate visual cognition process. In this paper, we improve our theoretical framework by mimicking a more elaborate structure and function of the primate visual cortex. We will mainly focus on the new formation of memory and association in visual processing under different circumstances as well as preliminary cognition and active adjustment in the inferior temporal cortex, which are absent in the HMAX model. The main contributions of this paper are: 1) in the memory and association part, we apply deep convolutional neural networks to extract various episodic features of the objects since people use different features for object recognition. Moreover, to achieve a fast and robust recognition in the retrieval and association process, different types of features are stored in separated clusters and the feature binding of the same object is stimulated in a loop discharge manner and 2) in the preliminary cognition and active adjustment part, we introduce preliminary cognition to classify different types of objects since distinct neural circuits in a human brain are used for identification of various types of objects. Furthermore, active cognition adjustment of occlusion and orientation is implemented to the model to mimic the top-down effect in human cognition process. Finally, our model is evaluated on two face databases CAS-PEAL-R1 and AR. The results demonstrate that our model exhibits its efficiency on visual recognition process with much lower memory storage requirement and a better performance compared with the traditional purely computational

  14. Estimation of group means when adjusting for covariates in generalized linear models.

    Science.gov (United States)

    Qu, Yongming; Luo, Junxiang

    2015-01-01

    Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.

  15. Using Green's Functions to initialize and adjust a global, eddying ocean biogeochemistry general circulation model

    Science.gov (United States)

    Brix, H.; Menemenlis, D.; Hill, C.; Dutkiewicz, S.; Jahn, O.; Wang, D.; Bowman, K.; Zhang, H.

    2015-11-01

    The NASA Carbon Monitoring System (CMS) Flux Project aims to attribute changes in the atmospheric accumulation of carbon dioxide to spatially resolved fluxes by utilizing the full suite of NASA data, models, and assimilation capabilities. For the oceanic part of this project, we introduce ECCO2-Darwin, a new ocean biogeochemistry general circulation model based on combining the following pre-existing components: (i) a full-depth, eddying, global-ocean configuration of the Massachusetts Institute of Technology general circulation model (MITgcm), (ii) an adjoint-method-based estimate of ocean circulation from the Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) project, (iii) the MIT ecosystem model "Darwin", and (iv) a marine carbon chemistry model. Air-sea gas exchange coefficients and initial conditions of dissolved inorganic carbon, alkalinity, and oxygen are adjusted using a Green's Functions approach in order to optimize modeled air-sea CO2 fluxes. Data constraints include observations of carbon dioxide partial pressure (pCO2) for 2009-2010, global air-sea CO2 flux estimates, and the seasonal cycle of the Takahashi et al. (2009) Atlas. The model sensitivity experiments (or Green's Functions) include simulations that start from different initial conditions as well as experiments that perturb air-sea gas exchange parameters and the ratio of particulate inorganic to organic carbon. The Green's Functions approach yields a linear combination of these sensitivity experiments that minimizes model-data differences. The resulting initial conditions and gas exchange coefficients are then used to integrate the ECCO2-Darwin model forward. Despite the small number (six) of control parameters, the adjusted simulation is significantly closer to the data constraints (37% cost function reduction, i.e., reduction in the model-data difference, relative to the baseline simulation) and to independent observations (e.g., alkalinity). The adjusted air-sea gas

  16. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    Science.gov (United States)

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

  17. Electromagnetic structure of pion in the framework of adjusted VMD model with elastic cut

    International Nuclear Information System (INIS)

    Dubnicka, S.; Furdik, I.; Meshcheryakov, V.A.

    1987-01-01

    The vector dominance model (VMD) parametrization of pion form factor is transformed into the pion c.m. momentum variable. Then the corresponding VMD poles are shifted by means of the nonzero widths of vector mesons from the real axis into the complex region of the second sheet of Riemann surface generated by the square-root two-pion-threshold branchpoint. A realistic description of all existing data is achieved in the framework of this adjusted VMD model and the presence of ρ'(1250) and ρ''(1600) mesons in e + e - →π + π - is confirmed by determination of their parameters directly from the fit of data

  18. Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

    Science.gov (United States)

    White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

    2017-12-01

    As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

  19. A survivability model for ejection of green compacts in powder metallurgy technology

    Directory of Open Access Journals (Sweden)

    Payman Ahi

    2012-01-01

    Full Text Available Reliability and quality assurance have become major considerations in the design and manufacture of today’s parts and products. Survivability of green compact using powder metallurgy technology is considered as one of the major quality attributes in manufacturing systems today. During powder metallurgy (PM production, the compaction conditions and behavior of the metal powder dictate the stress and density distribution in the green compact prior to sintering. These parameters greatly influence the mechanical properties and overall strength of the final component. In order to improve these properties, higher compaction pressures are usually employed, which make unloading and ejection of green compacts more challenging, especially for the powder-compacted parts with relatively complicated shapes. This study looked at a mathematical survivability model concerning green compact characteristics in PM technology and the stress-strength failure model in reliability engineering. This model depicts the relationship between mechanical loads (stress during ejection, experimentally determined green strength and survivability of green compact. The resulting survivability is the probability that a green compact survives during and after ejection. This survivability model can be used as an efficient tool for selecting the appropriate parameters for the process planning stage in PM technology. A case study is presented here in order to demonstrate the application of the proposed survivability model.

  20. Remote Sensing-based Methodologies for Snow Model Adjustments in Operational Streamflow Prediction

    Science.gov (United States)

    Bender, S.; Miller, W. P.; Bernard, B.; Stokes, M.; Oaida, C. M.; Painter, T. H.

    2015-12-01

    Water management agencies rely on hydrologic forecasts issued by operational agencies such as NOAA's Colorado Basin River Forecast Center (CBRFC). The CBRFC has partnered with the Jet Propulsion Laboratory (JPL) under funding from NASA to incorporate research-oriented, remotely-sensed snow data into CBRFC operations and to improve the accuracy of CBRFC forecasts. The partnership has yielded valuable analysis of snow surface albedo as represented in JPL's MODIS Dust Radiative Forcing in Snow (MODDRFS) data, across the CBRFC's area of responsibility. When dust layers within a snowpack emerge, reducing the snow surface albedo, the snowmelt rate may accelerate. The CBRFC operational snow model (SNOW17) is a temperature-index model that lacks explicit representation of snowpack surface albedo. CBRFC forecasters monitor MODDRFS data for emerging dust layers and may manually adjust SNOW17 melt rates. A technique was needed for efficient and objective incorporation of the MODDRFS data into SNOW17. Initial development focused in Colorado, where dust-on-snow events frequently occur. CBRFC forecasters used retrospective JPL-CBRFC analysis and developed a quantitative relationship between MODDRFS data and mean areal temperature (MAT) data. The relationship was used to generate adjusted, MODDRFS-informed input for SNOW17. Impacts of the MODDRFS-SNOW17 MAT adjustment method on snowmelt-driven streamflow prediction varied spatially and with characteristics of the dust deposition events. The largest improvements occurred in southwestern Colorado, in years with intense dust deposition events. Application of the method in other regions of Colorado and in "low dust" years resulted in minimal impact. The MODDRFS-SNOW17 MAT technique will be implemented in CBRFC operations in late 2015, prior to spring 2016 runoff. Collaborative investigation of remote sensing-based adjustment methods for the CBRFC operational hydrologic forecasting environment will continue over the next several years.

  1. Dynamically adjustable foot-ground contact model to estimate ground reaction force during walking and running.

    Science.gov (United States)

    Jung, Yihwan; Jung, Moonki; Ryu, Jiseon; Yoon, Sukhoon; Park, Sang-Kyoon; Koo, Seungbum

    2016-03-01

    Human dynamic models have been used to estimate joint kinetics during various activities. Kinetics estimation is in demand in sports and clinical applications where data on external forces, such as the ground reaction force (GRF), are not available. The purpose of this study was to estimate the GRF during gait by utilizing distance- and velocity-dependent force models between the foot and ground in an inverse-dynamics-based optimization. Ten males were tested as they walked at four different speeds on a force plate-embedded treadmill system. The full-GRF model whose foot-ground reaction elements were dynamically adjusted according to vertical displacement and anterior-posterior speed between the foot and ground was implemented in a full-body skeletal model. The model estimated the vertical and shear forces of the GRF from body kinematics. The shear-GRF model with dynamically adjustable shear reaction elements according to the input vertical force was also implemented in the foot of a full-body skeletal model. Shear forces of the GRF were estimated from body kinematics, vertical GRF, and center of pressure. The estimated full GRF had the lowest root mean square (RMS) errors at the slow walking speed (1.0m/s) with 4.2, 1.3, and 5.7% BW for anterior-posterior, medial-lateral, and vertical forces, respectively. The estimated shear forces were not significantly different between the full-GRF and shear-GRF models, but the RMS errors of the estimated knee joint kinetics were significantly lower for the shear-GRF model. Providing COP and vertical GRF with sensors, such as an insole-type pressure mat, can help estimate shear forces of the GRF and increase accuracy for estimation of joint kinetics. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Utilizing Visual Effects Software for Efficient and Flexible Isostatic Adjustment Modelling

    Science.gov (United States)

    Meldgaard, A.; Nielsen, L.; Iaffaldano, G.

    2017-12-01

    The isostatic adjustment signal generated by transient ice sheet loading is an important indicator of past ice sheet extent and the rheological constitution of the interior of the Earth. Finite element modelling has proved to be a very useful tool in these studies. We present a simple numerical model for 3D visco elastic Earth deformation and a new approach to the design of such models utilizing visual effects software designed for the film and game industry. The software package Houdini offers an assortment of optimized tools and libraries which greatly facilitate the creation of efficient numerical algorithms. In particular, we make use of Houdini's procedural work flow, the SIMD programming language VEX, Houdini's sparse matrix creation and inversion libraries, an inbuilt tetrahedralizer for grid creation, and the user interface, which facilitates effortless manipulation of 3D geometry. We mitigate many of the time consuming steps associated with the authoring of efficient algorithms from scratch while still keeping the flexibility that may be lost with the use of commercial dedicated finite element programs. We test the efficiency of the algorithm by comparing simulation times with off-the-shelf solutions from the Abaqus software package. The algorithm is tailored for the study of local isostatic adjustment patterns, in close vicinity to present ice sheet margins. In particular, we wish to examine possible causes for the considerable spatial differences in the uplift magnitude which are apparent from field observations in these areas. Such features, with spatial scales of tens of kilometres, are not resolvable with current global isostatic adjustment models, and may require the inclusion of local topographic features. We use the presented algorithm to study a near field area where field observations are abundant, namely, Disko Bay in West Greenland with the intention of constraining Earth parameters and ice thickness. In addition, we assess how local

  3. Hepatic retransplantation in New England--a regional experience and survival model.

    Science.gov (United States)

    Powelson, J A; Cosimi, A B; Lewis, W D; Rohrer, R J; Freeman, R B; Vacanti, J P; Jonas, M; Lorber, M I; Marks, W H; Bradley, J

    1993-04-01

    Hepatic retransplantation (reTx) offers the only alternative to death for patients who have failed primary hepatic transplantation (PTx). Assuming a finite number of donor organs, reTx also denies the chance of survival for some patients awaiting PTx. The impact of reTx on overall survival (i.e., the survival of all candidates for transplantation) must therefore be clarified. Between 1983 and 1991, 651 patients from the New England Organ Bank underwent liver transplantation, and 73 reTx were performed in 71 patients (11% reTx rate). The 1-year actuarial survival for reTx (48%) was significantly less than for PTx (70%, P 365 days, 83%). Patients on the regional waiting list had an 18% mortality rate while awaiting transplantation. These results were incorporated into a mathematical model describing survival as a function of reTx rate, assuming a limited supply of donor livers. ReTx improves the 1-year survival rate for patients undergoing PTx but decreases overall survival (survival of all candidates) for liver transplantation. In the current era of persistently insufficient donor numbers, strategies based on minimizing the use of reTx, especially in the case of patients in whom chances of success are minimal, will result in the best overall rate of patient survival.

  4. Family support and acceptance, gay male identity formation, and psychological adjustment: a path model.

    Science.gov (United States)

    Elizur, Y; Ziv, M

    2001-01-01

    While heterosexist family undermining has been demonstrated to be a developmental risk factor in the life of persons with same-gender orientation, the issue of protective family factors is both controversial and relatively neglected. In this study of Israeli gay males (N = 114), we focused on the interrelations of family support, family acceptance and family knowledge of gay orientation, and gay male identity formation, and their effects on mental health and self-esteem. A path model was proposed based on the hypotheses that family support, family acceptance, family knowledge, and gay identity formation have an impact on psychological adjustment, and that family support has an effect on gay identity formation that is mediated by family acceptance. The assessment of gay identity formation was based on an established stage model that was streamlined for cross-cultural practice by defining three basic processes of same-gender identity formation: self-definition, self-acceptance, and disclosure (Elizur & Mintzer, 2001). The testing of our conceptual path model demonstrated an excellent fit with the data. An alternative model that hypothesized effects of gay male identity on family acceptance and family knowledge did not fit the data. Interpreting these results, we propose that the main effect of family support/acceptance on gay identity is related to the process of disclosure, and that both general family support and family acceptance of same-gender orientation play a significant role in the psychological adjustment of gay men.

  5. Fluid Survival Tool: A Model Checker for Hybrid Petri Nets

    NARCIS (Netherlands)

    Postema, Björn Frits; Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Ghasemieh, Hamed

    2014-01-01

    Recently, algorithms for model checking Stochastic Time Logic (STL) on Hybrid Petri nets with a single general one-shot transition (HPNG) have been introduced. This paper presents a tool for model checking HPNG models against STL formulas. A graphical user interface (GUI) not only helps to

  6. Parametric and semiparametric models with applications to reliability, survival analysis, and quality of life

    CERN Document Server

    Nikulin, M; Mesbah, M; Limnios, N

    2004-01-01

    Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.

  7. Analisis Portofolio Optimum Saham Syariah Menggunakan Liquidity Adjusted Capital Asset Pricing Model (LCAPM

    Directory of Open Access Journals (Sweden)

    Nila Cahyati

    2015-04-01

    Full Text Available Investasi mempunyai karakteristik antara return dan resiko. Pembentukan portofolio optimal digunakan untuk memaksimalkan keuntungan dan meminimumkan resiko. Liquidity Adjusted Capital Asset Pricing Model (LCAPM merupakan metode pengembangan baru dari CAPM yang dipengaruhi likuiditas. Indikator likuiditas apabila digabungkan dengan metode CAPM dapat membantu memaksimalkan return dan meminimumkan resiko. Tujuan penelitian adalah membandingkan expected retun dan resiko saham serta mengetahui proporsi pada portofolio optimal. Sampel yang digunakan merupakan saham JII (Jakarta Islamic Index  periode Januari 2013 – November 2014. Hasil penelitian menunjukkan bahwa expected return portofolio LCAPM sebesar 0,0956 dengan resiko 0,0043 yang membentuk proporsi saham AALI (55,19% dan saham PGAS (44,81%.

  8. An Efficient Bundle Adjustment Model Based on Parallax Parametrization for Environmental Monitoring

    Science.gov (United States)

    Chen, R.; Sun, Y. Y.; Lei, Y.

    2017-12-01

    With the rapid development of Unmanned Aircraft Systems (UAS), more and more research fields have been successfully equipped with this mature technology, among which is environmental monitoring. One difficult task is how to acquire accurate position of ground object in order to reconstruct the scene more accurate. To handle this problem, we combine bundle adjustment method from Photogrammetry with parallax parametrization from Computer Vision to create a new method call APCP (aerial polar-coordinate photogrammetry). One impressive advantage of this method compared with traditional method is that the 3-dimensional point in space is represented using three angles (elevation angle, azimuth angle and parallax angle) rather than the XYZ value. As the basis for APCP, bundle adjustment could be used to optimize the UAS sensors' pose accurately, reconstruct the 3D models of environment, thus serving as the criterion of accurate position for monitoring. To verity the effectiveness of the proposed method, we test on several UAV dataset obtained by non-metric digital cameras with large attitude angles, and we find that our methods could achieve 1 or 2 times better efficiency with no loss of accuracy than traditional ones. For the classical nonlinear optimization of bundle adjustment model based on the rectangular coordinate, it suffers the problem of being seriously dependent on the initial values, making it unable to converge fast or converge to a stable state. On the contrary, APCP method could deal with quite complex condition of UAS when conducting monitoring as it represent the points in space with angles, including the condition that the sequential images focusing on one object have zero parallax angle. In brief, this paper presents the parameterization of 3D feature points based on APCP, and derives a full bundle adjustment model and the corresponding nonlinear optimization problems based on this method. In addition, we analyze the influence of convergence and

  9. Predicting water main failures using Bayesian model averaging and survival modelling approach

    International Nuclear Information System (INIS)

    Kabir, Golam; Tesfamariam, Solomon; Sadiq, Rehan

    2015-01-01

    To develop an effective preventive or proactive repair and replacement action plan, water utilities often rely on water main failure prediction models. However, in predicting the failure of water mains, uncertainty is inherent regardless of the quality and quantity of data used in the model. To improve the understanding of water main failure, a Bayesian framework is developed for predicting the failure of water mains considering uncertainties. In this study, Bayesian model averaging method (BMA) is presented to identify the influential pipe-dependent and time-dependent covariates considering model uncertainties whereas Bayesian Weibull Proportional Hazard Model (BWPHM) is applied to develop the survival curves and to predict the failure rates of water mains. To accredit the proposed framework, it is implemented to predict the failure of cast iron (CI) and ductile iron (DI) pipes of the water distribution network of the City of Calgary, Alberta, Canada. Results indicate that the predicted 95% uncertainty bounds of the proposed BWPHMs capture effectively the observed breaks for both CI and DI water mains. Moreover, the performance of the proposed BWPHMs are better compare to the Cox-Proportional Hazard Model (Cox-PHM) for considering Weibull distribution for the baseline hazard function and model uncertainties. - Highlights: • Prioritize rehabilitation and replacements (R/R) strategies of water mains. • Consider the uncertainties for the failure prediction. • Improve the prediction capability of the water mains failure models. • Identify the influential and appropriate covariates for different models. • Determine the effects of the covariates on failure

  10. Empiric model for mean generation time adjustment factor for classic point kinetics equations

    Energy Technology Data Exchange (ETDEWEB)

    Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C., E-mail: david.goes@poli.ufrj.br, E-mail: aquilino@lmp.ufrj.br, E-mail: alessandro@con.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear

    2017-11-01

    Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

  11. Empiric model for mean generation time adjustment factor for classic point kinetics equations

    International Nuclear Information System (INIS)

    Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C.

    2017-01-01

    Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)

  12. PACE and the Medicare+Choice risk-adjusted payment model.

    Science.gov (United States)

    Temkin-Greener, H; Meiners, M R; Gruenberg, L

    2001-01-01

    This paper investigates the impact of the Medicare principal inpatient diagnostic cost group (PIP-DCG) payment model on the Program of All-Inclusive Care for the Elderly (PACE). Currently, more than 6,000 Medicare beneficiaries who are nursing home certifiable receive care from PACE, a program poised for expansion under the Balanced Budget Act of 1997. Overall, our analysis suggests that the application of the PIP-DCG model to the PACE program would reduce Medicare payments to PACE, on average, by 38%. The PIP-DCG payment model bases its risk adjustment on inpatient diagnoses and does not capture adequately the risk of caring for a population with functional impairments.

  13. Modeling the airborne survival of influenza virus in a residential setting: the impacts of home humidification

    Science.gov (United States)

    2010-01-01

    Background Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH) conditions. Further analysis has shown that absolute humidity (AH) may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. Methods A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US) using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. Results The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. Conclusion This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity indoors. PMID:20815876

  14. Modeling the airborne survival of influenza virus in a residential setting: the impacts of home humidification

    Directory of Open Access Journals (Sweden)

    Myatt Theodore A

    2010-09-01

    Full Text Available Abstract Background Laboratory research studies indicate that aerosolized influenza viruses survive for longer periods at low relative humidity (RH conditions. Further analysis has shown that absolute humidity (AH may be an improved predictor of virus survival in the environment. Maintaining airborne moisture levels that reduce survival of the virus in the air and on surfaces could be another tool for managing public health risks of influenza. Methods A multi-zone indoor air quality model was used to evaluate the ability of portable humidifiers to control moisture content of the air and the potential related benefit of decreasing survival of influenza viruses in single-family residences. We modeled indoor AH and influenza virus concentrations during winter months (Northeast US using the CONTAM multi-zone indoor air quality model. A two-story residential template was used under two different ventilation conditions - forced hot air and radiant heating. Humidity was evaluated on a room-specific and whole house basis. Estimates of emission rates for influenza virus were particle-size specific and derived from published studies and included emissions during both tidal breathing and coughing events. The survival of the influenza virus was determined based on the established relationship between AH and virus survival. Results The presence of a portable humidifier with an output of 0.16 kg water per hour in the bedroom resulted in an increase in median sleeping hours AH/RH levels of 11 to 19% compared to periods without a humidifier present. The associated percent decrease in influenza virus survival was 17.5 - 31.6%. Distribution of water vapor through a residence was estimated to yield 3 to 12% increases in AH/RH and 7.8-13.9% reductions in influenza virus survival. Conclusion This modeling analysis demonstrates the potential benefit of portable residential humidifiers in reducing the survival of aerosolized influenza virus by controlling humidity

  15. Automatic parameter estimation of multicompartmental neuron models via minimization of trace error with control adjustment.

    Science.gov (United States)

    Brookings, Ted; Goeritz, Marie L; Marder, Eve

    2014-11-01

    We describe a new technique to fit conductance-based neuron models to intracellular voltage traces from isolated biological neurons. The biological neurons are recorded in current-clamp with pink (1/f) noise injected to perturb the activity of the neuron. The new algorithm finds a set of parameters that allows a multicompartmental model neuron to match the recorded voltage trace. Attempting to match a recorded voltage trace directly has a well-known problem: mismatch in the timing of action potentials between biological and model neuron is inevitable and results in poor phenomenological match between the model and data. Our approach avoids this by applying a weak control adjustment to the model to promote alignment during the fitting procedure. This approach is closely related to the control theoretic concept of a Luenberger observer. We tested this approach on synthetic data and on data recorded from an anterior gastric receptor neuron from the stomatogastric ganglion of the crab Cancer borealis. To test the flexibility of this approach, the synthetic data were constructed with conductance models that were different from the ones used in the fitting model. For both synthetic and biological data, the resultant models had good spike-timing accuracy. Copyright © 2014 the American Physiological Society.

  16. Modeling the effects of binary mixtures on survival in time.

    NARCIS (Netherlands)

    Baas, J.; van Houte, B.P.P.; van Gestel, C.A.M.; Kooijman, S.A.L.M.

    2007-01-01

    In general, effects of mixtures are difficult to describe, and most of the models in use are descriptive in nature and lack a strong mechanistic basis. The aim of this experiment was to develop a process-based model for the interpretation of mixture toxicity measurements, with effects of binary

  17. Asymmetric adjustment

    NARCIS (Netherlands)

    2010-01-01

    A method of adjusting a signal processing parameter for a first hearing aid and a second hearing aid forming parts of a binaural hearing aid system to be worn by a user is provided. The binaural hearing aid system comprises a user specific model representing a desired asymmetry between a first ear

  18. A hands-on approach for fitting long-term survival models under the GAMLSS framework.

    Science.gov (United States)

    de Castro, Mário; Cancho, Vicente G; Rodrigues, Josemar

    2010-02-01

    In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. In this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

  19. Modelling Tradescantia fluminensis to assess long term survival

    Directory of Open Access Journals (Sweden)

    Alex James

    2015-06-01

    Full Text Available We present a simple Poisson process model for the growth of Tradescantia fluminensis, an invasive plant species that inhibits the regeneration of native forest remnants in New Zealand. The model was parameterised with data derived from field experiments in New Zealand and then verified with independent data. The model gave good predictions which showed that its underlying assumptions are sound. However, this simple model had less predictive power for outputs based on variance suggesting that some assumptions were lacking. Therefore, we extended the model to include higher variability between plants thereby improving its predictions. This high variance model suggests that control measures that promote node death at the base of the plant or restrict the main stem growth rate will be more effective than those that reduce the number of branching events. The extended model forms a good basis for assessing the efficacy of various forms of control of this weed, including the recently-released leaf-feeding tradescantia leaf beetle (Neolema ogloblini.

  20. A Multiscale Survival Process for Modeling Human Activity Patterns.

    Science.gov (United States)

    Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

    2016-01-01

    Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

  1. Regression models for interval censored survival data: Application to HIV infection in Danish homosexual men

    DEFF Research Database (Denmark)

    Carstensen, Bendix

    1996-01-01

    This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men.......This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men....

  2. Modeling time-to-event (survival) data using classification tree analysis.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2017-12-01

    Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

  3. A new multivariate zero-adjusted Poisson model with applications to biomedicine.

    Science.gov (United States)

    Liu, Yin; Tian, Guo-Liang; Tang, Man-Lai; Yuen, Kam Chuen

    2018-05-25

    Recently, although advances were made on modeling multivariate count data, existing models really has several limitations: (i) The multivariate Poisson log-normal model (Aitchison and Ho, ) cannot be used to fit multivariate count data with excess zero-vectors; (ii) The multivariate zero-inflated Poisson (ZIP) distribution (Li et al., 1999) cannot be used to model zero-truncated/deflated count data and it is difficult to apply to high-dimensional cases; (iii) The Type I multivariate zero-adjusted Poisson (ZAP) distribution (Tian et al., 2017) could only model multivariate count data with a special correlation structure for random components that are all positive or negative. In this paper, we first introduce a new multivariate ZAP distribution, based on a multivariate Poisson distribution, which allows the correlations between components with a more flexible dependency structure, that is some of the correlation coefficients could be positive while others could be negative. We then develop its important distributional properties, and provide efficient statistical inference methods for multivariate ZAP model with or without covariates. Two real data examples in biomedicine are used to illustrate the proposed methods. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Risk-adjusted capitation funding models for chronic disease in Australia: alternatives to casemix funding.

    Science.gov (United States)

    Antioch, K M; Walsh, M K

    2002-01-01

    Under Australian casemix funding arrangements that use Diagnosis-Related Groups (DRGs) the average price is policy based, not benchmarked. Cost weights are too low for State-wide chronic disease services. Risk-adjusted Capitation Funding Models (RACFM) are feasible alternatives. A RACFM was developed for public patients with cystic fibrosis treated by an Australian Health Maintenance Organization (AHMO). Adverse selection is of limited concern since patients pay solidarity contributions via Medicare levy with no premium contributions to the AHMO. Sponsors paying premium subsidies are the State of Victoria and the Federal Government. Cost per patient is the dependent variable in the multiple regression. Data on DRG 173 (cystic fibrosis) patients were assessed for heteroskedasticity, multicollinearity, structural stability and functional form. Stepwise linear regression excluded non-significant variables. Significant variables were 'emergency' (1276.9), 'outlier' (6377.1), 'complexity' (3043.5), 'procedures' (317.4) and the constant (4492.7) (R(2)=0.21, SE=3598.3, F=14.39, Probpayment (constant). The model explained 21% of the variance in cost per patient. The payment rate is adjusted by a best practice annual admission rate per patient. The model is a blended RACFM for in-patient, out-patient, Hospital In The Home, Fee-For-Service Federal payments for drugs and medical services; lump sum lung transplant payments and risk sharing through cost (loss) outlier payments. State and Federally funded home and palliative services are 'carved out'. The model, which has national application via Coordinated Care Trials and by Australian States for RACFMs may be instructive for Germany, which plans to use Australian DRGs for casemix funding. The capitation alternative for chronic disease can improve equity, allocative efficiency and distributional justice. The use of Diagnostic Cost Groups (DCGs) is a promising alternative classification system for capitation arrangements.

  5. Survival analysis

    International Nuclear Information System (INIS)

    Badwe, R.A.

    1999-01-01

    The primary endpoint in the majority of the studies has been either disease recurrence or death. This kind of analysis requires a special method since all patients in the study experience the endpoint. The standard method for estimating such survival distribution is Kaplan Meier method. The survival function is defined as the proportion of individuals who survive beyond certain time. Multi-variate comparison for survival has been carried out with Cox's proportional hazard model

  6. Survival Analysis of a Nonautonomous Logistic Model with Stochastic Perturbation

    Directory of Open Access Journals (Sweden)

    Chun Lu

    2012-01-01

    Full Text Available Taking white noise into account, a stochastic nonautonomous logistic model is proposed and investigated. Sufficient conditions for extinction, nonpersistence in the mean, weak persistence, stochastic permanence, and global asymptotic stability are established. Moreover, the threshold between weak persistence and extinction is obtained. Finally, we introduce some numerical simulink graphics to illustrate our main results.

  7. Accounting for Uncertainty in Decision Analytic Models Using Rank Preserving Structural Failure Time Modeling: Application to Parametric Survival Models.

    Science.gov (United States)

    Bennett, Iain; Paracha, Noman; Abrams, Keith; Ray, Joshua

    2018-01-01

    Rank Preserving Structural Failure Time models are one of the most commonly used statistical methods to adjust for treatment switching in oncology clinical trials. The method is often applied in a decision analytic model without appropriately accounting for additional uncertainty when determining the allocation of health care resources. The aim of the study is to describe novel approaches to adequately account for uncertainty when using a Rank Preserving Structural Failure Time model in a decision analytic model. Using two examples, we tested and compared the performance of the novel Test-based method with the resampling bootstrap method and with the conventional approach of no adjustment. In the first example, we simulated life expectancy using a simple decision analytic model based on a hypothetical oncology trial with treatment switching. In the second example, we applied the adjustment method on published data when no individual patient data were available. Mean estimates of overall and incremental life expectancy were similar across methods. However, the bootstrapped and test-based estimates consistently produced greater estimates of uncertainty compared with the estimate without any adjustment applied. Similar results were observed when using the test based approach on a published data showing that failing to adjust for uncertainty led to smaller confidence intervals. Both the bootstrapping and test-based approaches provide a solution to appropriately incorporate uncertainty, with the benefit that the latter can implemented by researchers in the absence of individual patient data. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  8. Adjusting kinematics and kinetics in a feedback-controlled toe walking model

    Directory of Open Access Journals (Sweden)

    Olenšek Andrej

    2012-08-01

    Full Text Available Abstract Background In clinical gait assessment, the correct interpretation of gait kinematics and kinetics has a decisive impact on the success of the therapeutic programme. Due to the vast amount of information from which primary anomalies should be identified and separated from secondary compensatory changes, as well as the biomechanical complexity and redundancy of the human locomotion system, this task is considerably challenging and requires the attention of an experienced interdisciplinary team of experts. The ongoing research in the field of biomechanics suggests that mathematical modeling may facilitate this task. This paper explores the possibility of generating a family of toe walking gait patterns by systematically changing selected parameters of a feedback-controlled model. Methods From the selected clinical case of toe walking we identified typical toe walking characteristics and encoded them as a set of gait-oriented control objectives to be achieved in a feedback-controlled walking model. They were defined as fourth order polynomials and imposed via feedback control at the within-step control level. At the between-step control level, stance leg lengthening velocity at the end of the single support phase was adaptively adjusted after each step so as to facilitate gait velocity control. Each time the gait velocity settled at the desired value, selected intra-step gait characteristics were modified by adjusting the polynomials so as to mimic the effect of a typical therapeutical intervention - inhibitory casting. Results By systematically adjusting the set of control parameters we were able to generate a family of gait kinematic and kinetic patterns that exhibit similar principal toe walking characteristics, as they were recorded by means of an instrumented gait analysis system in the selected clinical case of toe walking. We further acknowledge that they to some extent follow similar improvement tendencies as those which one can

  9. Relevance of the c-statistic when evaluating risk-adjustment models in surgery.

    Science.gov (United States)

    Merkow, Ryan P; Hall, Bruce L; Cohen, Mark E; Dimick, Justin B; Wang, Edward; Chow, Warren B; Ko, Clifford Y; Bilimoria, Karl Y

    2012-05-01

    The measurement of hospital quality based on outcomes requires risk adjustment. The c-statistic is a popular tool used to judge model performance, but can be limited, particularly when evaluating specific operations in focused populations. Our objectives were to examine the interpretation and relevance of the c-statistic when used in models with increasingly similar case mix and to consider an alternative perspective on model calibration based on a graphical depiction of model fit. From the American College of Surgeons National Surgical Quality Improvement Program (2008-2009), patients were identified who underwent a general surgery procedure, and procedure groups were increasingly restricted: colorectal-all, colorectal-elective cases only, and colorectal-elective cancer cases only. Mortality and serious morbidity outcomes were evaluated using logistic regression-based risk adjustment, and model c-statistics and calibration curves were used to compare model performance. During the study period, 323,427 general, 47,605 colorectal-all, 39,860 colorectal-elective, and 21,680 colorectal cancer patients were studied. Mortality ranged from 1.0% in general surgery to 4.1% in the colorectal-all group, and serious morbidity ranged from 3.9% in general surgery to 12.4% in the colorectal-all procedural group. As case mix was restricted, c-statistics progressively declined from the general to the colorectal cancer surgery cohorts for both mortality and serious morbidity (mortality: 0.949 to 0.866; serious morbidity: 0.861 to 0.668). Calibration was evaluated graphically by examining predicted vs observed number of events over risk deciles. For both mortality and serious morbidity, there was no qualitative difference in calibration identified between the procedure groups. In the present study, we demonstrate how the c-statistic can become less informative and, in certain circumstances, can lead to incorrect model-based conclusions, as case mix is restricted and patients become

  10. Surviving the present: Modeling tools for organizational change

    International Nuclear Information System (INIS)

    Pangaro, P.

    1992-01-01

    The nuclear industry, like the rest of modern American business, is beset by a confluence of economic, technological, competitive, regulatory, and political pressures. For better or worse, business schools and management consultants have leapt to the rescue, offering the most modern conveniences that they can purvey. Recent advances in the study of organizations have led to new tools for their analysis, revision, and repair. There are two complementary tools that do not impose values or injunctions in themselves. One, called the organization modeler, captures the hierarchy of purposes that organizations and their subparts carry out. Any deficiency or pathology is quickly illuminated, and requirements for repair are made clear. The second, called THOUGHTSTICKER, is used to capture the semantic content of the conversations that occur across the interactions of parts of an organization. The distinctions and vocabulary in the language of an organization, and the relations within that domain, are elicited from the participants so that all three are available for debate and refinement. The product of the applications of these modeling tools is not the resulting models but rather the enhancement of the organization as a consequence of the process of constructing them

  11. Measurement of the Economic Growth and Add-on of the R.M. Solow Adjusted Model

    Directory of Open Access Journals (Sweden)

    Ion Gh. Rosca

    2007-08-01

    Full Text Available Besides the models of M. Keynes, R.F. Harrod, E. Domar, D. Romer, Ramsey-Cass-Koopmans model etc., the R.M. Solow model is part of the category which characterizes the economic growth.The paper aim is the economic growth measurement and add-on of the R.M. Solow adjusted model.

  12. A Comparative Study of CAPM and Seven Factors Risk Adjusted Return Model

    Directory of Open Access Journals (Sweden)

    Madiha Riaz Bhatti

    2014-12-01

    Full Text Available This study is a comparison and contrast of the predictive powers of two asset pricing models: CAPM and seven factor risk-return adjusted model, to explain the cross section of stock rate of returns in the financial sector listed at Karachi Stock Exchange (KSE. To test the models daily returns from January 2013 to February 2014 have been taken and the excess returns of portfolios are regressed on explanatory variables. The results of the tested models indicate that the models are valid and applicable in the financial market of Pakistan during the period under study, as the intercepts are not significantly different from zero. It is consequently established from the findings that all the explanatory variables explain the stock returns in the financial sector of KSE. In addition, the results of this study show that addition of more explanatory variables to the single factor CAPM results in reasonably high values of R2. These results provide substantial support to fund managers, investors and financial analysts in making investment decisions.

  13. Adjustment of automatic control systems of production facilities at coal processing plants using multivariant physico- mathematical models

    Science.gov (United States)

    Evtushenko, V. F.; Myshlyaev, L. P.; Makarov, G. V.; Ivushkin, K. A.; Burkova, E. V.

    2016-10-01

    The structure of multi-variant physical and mathematical models of control system is offered as well as its application for adjustment of automatic control system (ACS) of production facilities on the example of coal processing plant.

  14. An Analysis of Missile Systems Cost Growth and Implementation of Acquisition Reform Initiatives Using a Hybrid Adjusted Cost Growth Model

    National Research Council Canada - National Science Library

    Abate, Christopher

    2004-01-01

    ...) data with a hybrid adjusted cost growth (ACG) model. In addition, an analysis of acquisition reform initiatives during the treatment period was conducted to determine if reform efforts impacted missile system cost growth. A pre-reform...

  15. The New York Sepsis Severity Score: Development of a Risk-Adjusted Severity Model for Sepsis.

    Science.gov (United States)

    Phillips, Gary S; Osborn, Tiffany M; Terry, Kathleen M; Gesten, Foster; Levy, Mitchell M; Lemeshow, Stanley

    2018-05-01

    In accordance with Rory's Regulations, hospitals across New York State developed and implemented protocols for sepsis recognition and treatment to reduce variations in evidence informed care and preventable mortality. The New York Department of Health sought to develop a risk assessment model for accurate and standardized hospital mortality comparisons of adult septic patients across institutions using case-mix adjustment. Retrospective evaluation of prospectively collected data. Data from 43,204 severe sepsis and septic shock patients from 179 hospitals across New York State were evaluated. Prospective data were submitted to a database from January 1, 2015, to December 31, 2015. None. Maximum likelihood logistic regression was used to estimate model coefficients used in the New York State risk model. The mortality probability was estimated using a logistic regression model. Variables to be included in the model were determined as part of the model-building process. Interactions between variables were included if they made clinical sense and if their p values were less than 0.05. Model development used a random sample of 90% of available patients and was validated using the remaining 10%. Hosmer-Lemeshow goodness of fit p values were considerably greater than 0.05, suggesting good calibration. Areas under the receiver operator curve in the developmental and validation subsets were 0.770 (95% CI, 0.765-0.775) and 0.773 (95% CI, 0.758-0.787), respectively, indicating good discrimination. Development and validation datasets had similar distributions of estimated mortality probabilities. Mortality increased with rising age, comorbidities, and lactate. The New York Sepsis Severity Score accurately estimated the probability of hospital mortality in severe sepsis and septic shock patients. It performed well with respect to calibration and discrimination. This sepsis-specific model provides an accurate, comprehensive method for standardized mortality comparison of adult

  16. Using cure models for analyzing the influence of pathogens on salmon survival

    Science.gov (United States)

    Ray, Adam R; Perry, Russell W.; Som, Nicholas A.; Bartholomew, Jerri L

    2014-01-01

    Parasites and pathogens influence the size and stability of wildlife populations, yet many population models ignore the population-level effects of pathogens. Standard survival analysis methods (e.g., accelerated failure time models) are used to assess how survival rates are influenced by disease. However, they assume that each individual is equally susceptible and will eventually experience the event of interest; this assumption is not typically satisfied with regard to pathogens of wildlife populations. In contrast, mixture cure models, which comprise logistic regression and survival analysis components, allow for different covariates to be entered into each part of the model and provide better predictions of survival when a fraction of the population is expected to survive a disease outbreak. We fitted mixture cure models to the host–pathogen dynamics of Chinook Salmon Oncorhynchus tshawytscha and Coho Salmon O. kisutch and the myxozoan parasite Ceratomyxa shasta. Total parasite concentration, water temperature, and discharge were used as covariates to predict the observed parasite-induced mortality in juvenile salmonids collected as part of a long-term monitoring program in the Klamath River, California. The mixture cure models predicted the observed total mortality well, but some of the variability in observed mortality rates was not captured by the models. Parasite concentration and water temperature were positively associated with total mortality and the mortality rate of both Chinook Salmon and Coho Salmon. Discharge was positively associated with total mortality for both species but only affected the mortality rate for Coho Salmon. The mixture cure models provide insights into how daily survival rates change over time in Chinook Salmon and Coho Salmon after they become infected with C. shasta.

  17. Analyses adjusting for selective crossover show improved overall survival with adjuvant letrozole compared with tamoxifen in the BIG 1-98 study

    DEFF Research Database (Denmark)

    Colleoni, Marco; Giobbie-Hurder, Anita; Regan, Meredith M

    2011-01-01

    Among postmenopausal women with endocrine-responsive breast cancer, the aromatase inhibitor letrozole, when compared with tamoxifen, has been shown to significantly improve disease-free survival (DFS) and time to distant recurrence (TDR). We investigated whether letrozole monotherapy prolonged ov...

  18. A Survival Model for Shortleaf Pine Tress Growing in Uneven-Aged Stands

    Science.gov (United States)

    Thomas B. Lynch; Lawrence R. Gering; Michael M. Huebschmann; Paul A. Murphy

    1999-01-01

    A survival model for shortleaf pine (Pinus echinata Mill.) trees growing in uneven-aged stands was developed using data from permanently established plots maintained by an industrial forestry company in western Arkansas. Parameters were fitted to a logistic regression model with a Bernoulli dependent variable in which "0" represented...

  19. Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

    Science.gov (United States)

    Nikbakht, Roya; Bahrampour, Abbas

    2017-01-01

    Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

  20. ELECTRICAL CONDUCTIVITY OF SOYBEAN SEED CULTIVARS AND ADJUSTED MODELS OF LEAKAGE CURVES ALONG THE TIME

    Directory of Open Access Journals (Sweden)

    ADRIANA RITA SALINAS

    2010-01-01

    Full Text Available The objective of this work was to study the behavior of ten soybean [Glycine max (L. Merr.] cultivars using the electrical conductivity (EC test by the comparison of curves of the accumulative electrolyte leakage along the time and to establish the statistical model that allow the best adjust of the curves. Ten soybean cultivars were used and they were mechanically harvested in 2004 in the EEA Oliveros, Santa Fe, Argentina. Measurements of EC were made for 100 individual seeds of each cultivar during 20 hours of immersion at intervals of 1 hour using an equipment that permit an individual seed analysis (Seed Automatic Analyzer SAD 9000S. There were proposed two statistical models to study the EC along the time of the 10 cultivars studied using SAS Statistics Program, to select the model that better allow us to understand the EC behavior along the time. Model 1 allowed to make comparisons of EC along the time between cultivars and to study the influence of the production environment on the physiological quality of soybean seeds. The time to reach the stabilization of the EC must not be lower than 19 hours for the different cultivars.

  1. Family caregiver adjustment and stroke survivor impairment: A path analytic model.

    Science.gov (United States)

    Pendergrass, Anna; Hautzinger, Martin; Elliott, Timothy R; Schilling, Oliver; Becker, Clemens; Pfeiffer, Klaus

    2017-05-01

    Depressive symptoms are a common problem among family caregivers of stroke survivors. The purpose of this study was to examine the association between care recipient's impairment and caregiver depression, and determine the possible mediating effects of caregiver negative problem-orientation, mastery, and leisure time satisfaction. The evaluated model was derived from Pearlin's stress process model of caregiver adjustment. We analyzed baseline data from 122 strained family members who were assisting stroke survivors in Germany for a minimum of 6 months and who consented to participate in a randomized clinical trial. Depressive symptoms were measured with the Center for Epidemiological Studies Depression Scale. The cross-sectional data were analyzed using path analysis. The results show an adequate fit of the model to the data, χ2(1, N = 122) = 0.17, p = .68; comparative fit index = 1.00; root mean square error of approximation: p caregiver depressive symptoms. Results indicate that caregivers at risk for depression reported a negative problem orientation, low caregiving mastery, and low leisure time satisfaction. The situation is particularly affected by the frequency of stroke survivor problematic behavior, and by the degree of their impairments in activities of daily living. The findings provide empirical support for the Pearlin's stress model and emphasize how important it is to target these mediators in health promotion interventions for family caregivers of stroke survivors. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  2. Survival behavior in the cyclic Lotka-Volterra model with a randomly switching reaction rate

    Science.gov (United States)

    West, Robert; Mobilia, Mauro; Rucklidge, Alastair M.

    2018-02-01

    We study the influence of a randomly switching reproduction-predation rate on the survival behavior of the nonspatial cyclic Lotka-Volterra model, also known as the zero-sum rock-paper-scissors game, used to metaphorically describe the cyclic competition between three species. In large and finite populations, demographic fluctuations (internal noise) drive two species to extinction in a finite time, while the species with the smallest reproduction-predation rate is the most likely to be the surviving one (law of the weakest). Here we model environmental (external) noise by assuming that the reproduction-predation rate of the strongest species (the fastest to reproduce and predate) in a given static environment randomly switches between two values corresponding to more and less favorable external conditions. We study the joint effect of environmental and demographic noise on the species survival probabilities and on the mean extinction time. In particular, we investigate whether the survival probabilities follow the law of the weakest and analyze their dependence on the external noise intensity and switching rate. Remarkably, when, on average, there is a finite number of switches prior to extinction, the survival probability of the predator of the species whose reaction rate switches typically varies nonmonotonically with the external noise intensity (with optimal survival about a critical noise strength). We also outline the relationship with the case where all reaction rates switch on markedly different time scales.

  3. Survival behavior in the cyclic Lotka-Volterra model with a randomly switching reaction rate.

    Science.gov (United States)

    West, Robert; Mobilia, Mauro; Rucklidge, Alastair M

    2018-02-01

    We study the influence of a randomly switching reproduction-predation rate on the survival behavior of the nonspatial cyclic Lotka-Volterra model, also known as the zero-sum rock-paper-scissors game, used to metaphorically describe the cyclic competition between three species. In large and finite populations, demographic fluctuations (internal noise) drive two species to extinction in a finite time, while the species with the smallest reproduction-predation rate is the most likely to be the surviving one (law of the weakest). Here we model environmental (external) noise by assuming that the reproduction-predation rate of the strongest species (the fastest to reproduce and predate) in a given static environment randomly switches between two values corresponding to more and less favorable external conditions. We study the joint effect of environmental and demographic noise on the species survival probabilities and on the mean extinction time. In particular, we investigate whether the survival probabilities follow the law of the weakest and analyze their dependence on the external noise intensity and switching rate. Remarkably, when, on average, there is a finite number of switches prior to extinction, the survival probability of the predator of the species whose reaction rate switches typically varies nonmonotonically with the external noise intensity (with optimal survival about a critical noise strength). We also outline the relationship with the case where all reaction rates switch on markedly different time scales.

  4. Optimal Scheme Selection of Agricultural Production Structure Adjustment - Based on DEA Model; Punjab (Pakistan)

    Institute of Scientific and Technical Information of China (English)

    Zeeshan Ahmad; Meng Jun; Muhammad Abdullah; Mazhar Nadeem Ishaq; Majid Lateef; Imran Khan

    2015-01-01

    This paper used the modern evaluation method of DEA (Data Envelopment Analysis) to assess the comparative efficiency and then on the basis of this among multiple schemes chose the optimal scheme of agricultural production structure adjustment. Based on the results of DEA model, we dissected scale advantages of each discretionary scheme or plan. We examined scale advantages of each discretionary scheme, tested profoundly a definitive purpose behind not-DEA efficient, which elucidated the system and methodology to enhance these discretionary plans. At the end, another method had been proposed to rank and select the optimal scheme. The research was important to guide the practice if the modification of agricultural production industrial structure was carried on.

  5. Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

    Science.gov (United States)

    Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

    2016-01-01

    Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

  6. A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data

    DEFF Research Database (Denmark)

    He, Peng; Eriksson, Frank; Scheike, Thomas H.

    2016-01-01

    function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight......With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution...... and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight...

  7. Joint modelling of longitudinal CEA tumour marker progression and survival data on breast cancer

    Science.gov (United States)

    Borges, Ana; Sousa, Inês; Castro, Luis

    2017-06-01

    This work proposes the use of Biostatistics methods to study breast cancer in patients of Braga's Hospital Senology Unit, located in Portugal. The primary motivation is to contribute to the understanding of the progression of breast cancer, within the Portuguese population, using a more complex statistical model assumptions than the traditional analysis that take into account a possible existence of a serial correlation structure within a same subject observations. We aim to infer which risk factors aect the survival of Braga's Hospital patients, diagnosed with breast tumour. Whilst analysing risk factors that aect a tumour markers used on the surveillance of disease progression the Carcinoembryonic antigen (CEA). As survival and longitudinal processes may be associated, it is important to model these two processes together. Hence, a joint modelling of these two processes to infer on the association of these was conducted. A data set of 540 patients, along with 50 variables, was collected from medical records of the Hospital. A joint model approach was used to analyse these data. Two dierent joint models were applied to the same data set, with dierent parameterizations which give dierent interpretations to model parameters. These were used by convenience as the ones implemented in R software. Results from the two models were compared. Results from joint models, showed that the longitudinal CEA values were signicantly associated with the survival probability of these patients. A comparison between parameter estimates obtained in this analysis and previous independent survival[4] and longitudinal analysis[5][6], lead us to conclude that independent analysis brings up bias parameter estimates. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary. Results indicate that the longitudinal progression of CEA is signicantly associated with the probability of survival of these patients. Hence, an assumption of

  8. Short term load forecasting technique based on the seasonal exponential adjustment method and the regression model

    International Nuclear Information System (INIS)

    Wu, Jie; Wang, Jianzhou; Lu, Haiyan; Dong, Yao; Lu, Xiaoxiao

    2013-01-01

    Highlights: ► The seasonal and trend items of the data series are forecasted separately. ► Seasonal item in the data series is verified by the Kendall τ correlation testing. ► Different regression models are applied to the trend item forecasting. ► We examine the superiority of the combined models by the quartile value comparison. ► Paired-sample T test is utilized to confirm the superiority of the combined models. - Abstract: For an energy-limited economy system, it is crucial to forecast load demand accurately. This paper devotes to 1-week-ahead daily load forecasting approach in which load demand series are predicted by employing the information of days before being similar to that of the forecast day. As well as in many nonlinear systems, seasonal item and trend item are coexisting in load demand datasets. In this paper, the existing of the seasonal item in the load demand data series is firstly verified according to the Kendall τ correlation testing method. Then in the belief of the separate forecasting to the seasonal item and the trend item would improve the forecasting accuracy, hybrid models by combining seasonal exponential adjustment method (SEAM) with the regression methods are proposed in this paper, where SEAM and the regression models are employed to seasonal and trend items forecasting respectively. Comparisons of the quartile values as well as the mean absolute percentage error values demonstrate this forecasting technique can significantly improve the accuracy though models applied to the trend item forecasting are eleven different ones. This superior performance of this separate forecasting technique is further confirmed by the paired-sample T tests

  9. Monitoring risk-adjusted outcomes in congenital heart surgery: does the appropriateness of a risk model change with time?

    Science.gov (United States)

    Tsang, Victor T; Brown, Katherine L; Synnergren, Mats Johanssen; Kang, Nicholas; de Leval, Marc R; Gallivan, Steve; Utley, Martin

    2009-02-01

    Risk adjustment of outcomes in pediatric congenital heart surgery is challenging due to the great diversity in diagnoses and procedures. We have previously shown that variable life-adjusted display (VLAD) charts provide an effective graphic display of risk-adjusted outcomes in this specialty. A question arises as to whether the risk model used remains appropriate over time. We used a recently developed graphic technique to evaluate the performance of an existing risk model among those patients at a single center during 2000 to 2003 originally used in model development. We then compared the distribution of predicted risk among these patients with that among patients in 2004 to 2006. Finally, we constructed a VLAD chart of risk-adjusted outcomes for the latter period. Among 1083 patients between April 2000 and March 2003, the risk model performed well at predicted risks above 3%, underestimated mortality at 2% to 3% predicted risk, and overestimated mortality below 2% predicted risk. There was little difference in the distribution of predicted risk among these patients and among 903 patients between June 2004 and October 2006. Outcomes for the more recent period were appreciably better than those expected according to the risk model. This finding cannot be explained by any apparent bias in the risk model combined with changes in case-mix. Risk models can, and hopefully do, become out of date. There is scope for complacency in the risk-adjusted audit if the risk model used is not regularly recalibrated to reflect changing standards and expectations.

  10. ADJUSTMENT OF MORPHOMETRIC PARAMETERS OF WATER BASINS BASED ON DIGITAL TERRAIN MODELS

    Directory of Open Access Journals (Sweden)

    Krasil'nikov Vitaliy Mikhaylovich

    2012-10-01

    Full Text Available The authors argue that effective use of water resources requires accurate morphometric characteristics of water basins. Accurate parameters are needed to analyze their condition, and to assure their appropriate control and operation. Today multiple water basins need their morphometric characteristics to be adjusted and properly stored. The procedure employed so far is based on plane geometric horizontals depicted onto topographic maps. It is described in the procedural guidelines issued in respect of the «Application of water resource regulations governing the operation of waterworks facilities of power plants». The technology described there is obsolete due to the availability of specialized software. The computer technique is based on a digital terrain model. The authors provide an overview of the technique implemented at Rybinsk and Gorkiy water basins in this article. Thus, the digital terrain model generated on the basis of the field data is used at Gorkiy water basin, while the model based on maps and charts is applied at Rybinsk water basin. The authors believe that the software technique can be applied to any other water basin on the basis of the analysis and comparison of morphometric characteristics of the two water basins.

  11. Dose-rate dependent stochastic effects in radiation cell-survival models

    International Nuclear Information System (INIS)

    Sachs, R.K.; Hlatky, L.R.

    1990-01-01

    When cells are subjected to ionizing radiation the specific energy rate (microscopic analog of dose-rate) varies from cell to cell. Within one cell, this rate fluctuates during the course of time; a crossing of a sensitive cellular site by a high energy charged particle produces many ionizations almost simultaneously, but during the interval between events no ionizations occur. In any cell-survival model one can incorporate the effect of such fluctuations without changing the basic biological assumptions. Using stochastic differential equations and Monte Carlo methods to take into account stochastic effects we calculated the dose-survival rfelationships in a number of current cell survival models. Some of the models assume quadratic misrepair; others assume saturable repair enzyme systems. It was found that a significant effect of random fluctuations is to decrease the theoretically predicted amount of dose-rate sparing. In the limit of low dose-rates neglecting the stochastic nature of specific energy rates often leads to qualitatively misleading results by overestimating the surviving fraction drastically. In the opposite limit of acute irradiation, analyzing the fluctuations in rates merely amounts to analyzing fluctuations in total specific energy via the usual microdosimetric specific energy distribution function, and neglecting fluctuations usually underestimates the surviving fraction. The Monte Carlo methods interpolate systematically between the low dose-rate and high dose-rate limits. As in other approaches, the slope of the survival curve at low dose-rates is virtually independent of dose and equals the initial slope of the survival curve for acute radiation. (orig.)

  12. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

    Science.gov (United States)

    Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

    2016-01-01

    Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  13. Ice loading model for Glacial Isostatic Adjustment in the Barents Sea constrained by GRACE gravity observations

    Science.gov (United States)

    Root, Bart; Tarasov, Lev; van der Wal, Wouter

    2014-05-01

    The global ice budget is still under discussion because the observed 120-130 m eustatic sea level equivalent since the Last Glacial Maximum (LGM) can not be explained by the current knowledge of land-ice melt after the LGM. One possible location for the missing ice is the Barents Sea Region, which was completely covered with ice during the LGM. This is deduced from relative sea level observations on Svalbard, Novaya Zemlya and the North coast of Scandinavia. However, there are no observations in the middle of the Barents Sea that capture the post-glacial uplift. With increased precision and longer time series of monthly gravity observations of the GRACE satellite mission it is possible to constrain Glacial Isostatic Adjustment in the center of the Barents Sea. This study investigates the extra constraint provided by GRACE data for modeling the past ice geometry in the Barents Sea. We use CSR release 5 data from February 2003 to July 2013. The GRACE data is corrected for the past 10 years of secular decline of glacier ice on Svalbard, Novaya Zemlya and Frans Joseph Land. With numerical GIA models for a radially symmetric Earth, we model the expected gravity changes and compare these with the GRACE observations after smoothing with a 250 km Gaussian filter. The comparisons show that for the viscosity profile VM5a, ICE-5G has too strong a gravity signal compared to GRACE. The regional calibrated ice sheet model (GLAC) of Tarasov appears to fit the amplitude of the GRACE signal. However, the GRACE data are very sensitive to the ice-melt correction, especially for Novaya Zemlya. Furthermore, the ice mass should be more concentrated to the middle of the Barents Sea. Alternative viscosity models confirm these conclusions.

  14. Direct risk standardisation: a new method for comparing casemix adjusted event rates using complex models.

    Science.gov (United States)

    Nicholl, Jon; Jacques, Richard M; Campbell, Michael J

    2013-10-29

    Comparison of outcomes between populations or centres may be confounded by any casemix differences and standardisation is carried out to avoid this. However, when the casemix adjustment models are large and complex, direct standardisation has been described as "practically impossible", and indirect standardisation may lead to unfair comparisons. We propose a new method of directly standardising for risk rather than standardising for casemix which overcomes these problems. Using a casemix model which is the same model as would be used in indirect standardisation, the risk in individuals is estimated. Risk categories are defined, and event rates in each category for each centre to be compared are calculated. A weighted sum of the risk category specific event rates is then calculated. We have illustrated this method using data on 6 million admissions to 146 hospitals in England in 2007/8 and an existing model with over 5000 casemix combinations, and a second dataset of 18,668 adult emergency admissions to 9 centres in the UK and overseas and a published model with over 20,000 casemix combinations and a continuous covariate. Substantial differences between conventional directly casemix standardised rates and rates from direct risk standardisation (DRS) were found. Results based on DRS were very similar to Standardised Mortality Ratios (SMRs) obtained from indirect standardisation, with similar standard errors. Direct risk standardisation using our proposed method is as straightforward as using conventional direct or indirect standardisation, always enables fair comparisons of performance to be made, can use continuous casemix covariates, and was found in our examples to have similar standard errors to the SMR. It should be preferred when there is a risk that conventional direct or indirect standardisation will lead to unfair comparisons.

  15. Comparison of six different models describing survival of mammalian cells after irradiation

    International Nuclear Information System (INIS)

    Sontag, W.

    1990-01-01

    Six different cell-survival models have been compared. All models are based on the similar assumption that irradiated cells are able to exist in one of three states. S A is the state of a totally repaired cell, in state S C the cell contains lethal lesions and in state S b the cell contains potentially lethal lesions i.e. those which either can be repaired or converted into lethal lesions. The differences between the six models lie in the different mathematical relationships between the three states. To test the six models, six different sets of experimental data were used which describe cell survival at different repair times after irradiation with sparsely ionizing irradiation. In order to compare the models, a goodness-of-fit function was used. The differences between the six models were tested by use of the nonparametric Mann-Whitney two sample test. Based on the 95% confidence limit, this required separation into three groups. (orig.)

  16. Location memory for dots in polygons versus cities in regions: evaluating the category adjustment model.

    Science.gov (United States)

    Friedman, Alinda; Montello, Daniel R; Burte, Heather

    2012-09-01

    We conducted 3 experiments to examine the category adjustment model (Huttenlocher, Hedges, & Duncan, 1991) in circumstances in which the category boundaries were irregular schematized polygons made from outlines of maps. For the first time, accuracy was tested when only perceptual and/or existing long-term memory information about identical locations was cued. Participants from Alberta, Canada and California received 1 of 3 conditions: dots-only, in which a dot appeared within the polygon, and after a 4-s dynamic mask the empty polygon appeared and the participant indicated where the dot had been; dots-and-names, in which participants were told that the first polygon represented Alberta/California and that each dot was in the correct location for the city whose name appeared outside the polygon; and names-only, in which there was no first polygon, and participants clicked on the city locations from extant memory alone. Location recall in the dots-only and dots-and-names conditions did not differ from each other and had small but significant directional errors that pointed away from the centroids of the polygons. In contrast, the names-only condition had large and significant directional errors that pointed toward the centroids. Experiments 2 and 3 eliminated the distribution of stimuli and overall screen position as causal factors. The data suggest that in the "classic" category adjustment paradigm, it is difficult to determine a priori when Bayesian cue combination is applicable, making Bayesian analysis less useful as a theoretical approach to location estimation. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  17. Positive Adjustment Among American Repatriated Prisoners of the Vietnam War: Modeling the Long-Term Effects of Captivity.

    Science.gov (United States)

    King, Daniel W; King, Lynda A; Park, Crystal L; Lee, Lewina O; Kaiser, Anica Pless; Spiro, Avron; Moore, Jeffrey L; Kaloupek, Danny G; Keane, Terence M

    2015-11-01

    A longitudinal lifespan model of factors contributing to later-life positive adjustment was tested on 567 American repatriated prisoners from the Vietnam War. This model encompassed demographics at time of capture and attributes assessed after return to the U.S. (reports of torture and mental distress) and approximately 3 decades later (later-life stressors, perceived social support, positive appraisal of military experiences, and positive adjustment). Age and education at time of capture and physical torture were associated with repatriation mental distress, which directly predicted poorer adjustment 30 years later. Physical torture also had a salutary effect, enhancing later-life positive appraisals of military experiences. Later-life events were directly and indirectly (through concerns about retirement) associated with positive adjustment. Results suggest that the personal resources of older age and more education and early-life adverse experiences can have cascading effects over the lifespan to impact well-being in both positive and negative ways.

  18. [Construction and validation of a multidimensional model of students' adjustment to college context].

    Science.gov (United States)

    Soares, Ana Paula; Guisande, M Adelina; Diniz, António M; Almeida, Leandro S

    2006-05-01

    This article presents a model of interaction of personal and contextual variables in the prediction of academic performance and psychosocial development of Portuguese college students. The sample consists of 560 first-year college students of the University of Minho. The path analysis results suggest that initial expectations of the students' involvement in academic life constituted an effective predictor of their involvement during their first year; as well as the social climate of the classroom influenced their involvement, well-being and levels of satisfaction obtained. However, these relationships were not strong enough to influence the criterion variables integrated in the model (academic performance and psychosocial development). Academic performance was predicted by the high school grades and college entrance examination scores, and the level of psychosocial development was determined by the level of development showed at the time they entered college. Though more research is needed, these results point to the importance of students' pre-college characteristics when we are considering the quality of their college adjustment process.

  19. On the analysis of clonogenic survival data: Statistical alternatives to the linear-quadratic model

    International Nuclear Information System (INIS)

    Unkel, Steffen; Belka, Claus; Lauber, Kirsten

    2016-01-01

    The most frequently used method to quantitatively describe the response to ionizing irradiation in terms of clonogenic survival is the linear-quadratic (LQ) model. In the LQ model, the logarithm of the surviving fraction is regressed linearly on the radiation dose by means of a second-degree polynomial. The ratio of the estimated parameters for the linear and quadratic term, respectively, represents the dose at which both terms have the same weight in the abrogation of clonogenic survival. This ratio is known as the α/β ratio. However, there are plausible scenarios in which the α/β ratio fails to sufficiently reflect differences between dose-response curves, for example when curves with similar α/β ratio but different overall steepness are being compared. In such situations, the interpretation of the LQ model is severely limited. Colony formation assays were performed in order to measure the clonogenic survival of nine human pancreatic cancer cell lines and immortalized human pancreatic ductal epithelial cells upon irradiation at 0-10 Gy. The resulting dataset was subjected to LQ regression and non-linear log-logistic regression. Dimensionality reduction of the data was performed by cluster analysis and principal component analysis. Both the LQ model and the non-linear log-logistic regression model resulted in accurate approximations of the observed dose-response relationships in the dataset of clonogenic survival. However, in contrast to the LQ model the non-linear regression model allowed the discrimination of curves with different overall steepness but similar α/β ratio and revealed an improved goodness-of-fit. Additionally, the estimated parameters in the non-linear model exhibit a more direct interpretation than the α/β ratio. Dimensionality reduction of clonogenic survival data by means of cluster analysis was shown to be a useful tool for classifying radioresistant and sensitive cell lines. More quantitatively, principal component analysis allowed

  20. Estimating the average treatment effect on survival based on observational data and using partly conditional modeling.

    Science.gov (United States)

    Gong, Qi; Schaubel, Douglas E

    2017-03-01

    Treatments are frequently evaluated in terms of their effect on patient survival. In settings where randomization of treatment is not feasible, observational data are employed, necessitating correction for covariate imbalances. Treatments are usually compared using a hazard ratio. Most existing methods which quantify the treatment effect through the survival function are applicable to treatments assigned at time 0. In the data structure of our interest, subjects typically begin follow-up untreated; time-until-treatment, and the pretreatment death hazard are both heavily influenced by longitudinal covariates; and subjects may experience periods of treatment ineligibility. We propose semiparametric methods for estimating the average difference in restricted mean survival time attributable to a time-dependent treatment, the average effect of treatment among the treated, under current treatment assignment patterns. The pre- and posttreatment models are partly conditional, in that they use the covariate history up to the time of treatment. The pre-treatment model is estimated through recently developed landmark analysis methods. For each treated patient, fitted pre- and posttreatment survival curves are projected out, then averaged in a manner which accounts for the censoring of treatment times. Asymptotic properties are derived and evaluated through simulation. The proposed methods are applied to liver transplant data in order to estimate the effect of liver transplantation on survival among transplant recipients under current practice patterns. © 2016, The International Biometric Society.

  1. Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

    Science.gov (United States)

    Liu, Gang; Dong, Chuanpeng; Wang, Xing; Hou, Guojun; Zheng, Yu; Xu, Huilin; Zhan, Xiaohui; Liu, Lei

    2017-11-17

    Clinical and pathological indicators are inadequate for prognosis of stage II and III colorectal carcinoma (CRC). In this study, we utilized the activity of regulatory factors, univariate Cox regression and random forest for variable selection and developed a multivariate Cox model to predict the overall survival of Stage II/III colorectal carcinoma in GSE39582 datasets (469 samples). Patients in low-risk group showed a significant longer overall survival and recurrence-free survival time than those in high-risk group. This finding was further validated in five other independent datasets (GSE14333, GSE17536, GSE17537, GSE33113, and GSE37892). Besides, associations between clinicopathological information and risk score were analyzed. A nomogram including risk score was plotted to facilitate the utilization of risk score. The risk score model is also demonstrated to be effective on predicting both overall and recurrence-free survival of chemotherapy received patients. After performing Gene Set Enrichment Analysis (GSEA) between high and low risk groups, we found that several cell-cell interaction KEGG pathways were identified. Funnel plot results showed that there was no publication bias in these datasets. In summary, by utilizing the regulatory activity in stage II and III colorectal carcinoma, the risk score successfully predicts the survival of 1021 stage II/III CRC patients in six independent datasets.

  2. Models of traumatic experiences and children's psychological adjustment: the roles of perceived parenting and the children's own resources and activity.

    Science.gov (United States)

    Punamäki, R L; Qouta, S; el Sarraj, E

    1997-08-01

    The relations between traumatic events, perceived parenting styles, children's resources, political activity, and psychological adjustment were examined among 108 Palestinian boys and girls of 11-12 years of age. The results showed that exposure to traumatic events increased psychological adjustment problems directly and via 2 mediating paths. First, the more traumatic events children had experienced, the more negative parenting they experienced. And, the poorer they perceived parenting, the more they suffered from high neuroticism and low self-esteem. Second, the more traumatic events children had experienced, the more political activity they showed, and the more active they were, the more they suffered from psychological adjustment problems. Good perceived parenting protected children's psychological adjustment by making them less vulnerable in two ways. First, traumatic events decreased their intellectual, creative, and cognitive resources, and a lack of resources predicted many psychological adjustment problems in a model excluding perceived parenting. Second, political activity increased psychological adjustment problems in the same model, but not in the model including good parenting.

  3. Effects of temperature on development, survival and reproduction of insects: Experimental design, data analysis and modeling

    Science.gov (United States)

    Jacques Regniere; James Powell; Barbara Bentz; Vincent Nealis

    2012-01-01

    The developmental response of insects to temperature is important in understanding the ecology of insect life histories. Temperature-dependent phenology models permit examination of the impacts of temperature on the geographical distributions, population dynamics and management of insects. The measurement of insect developmental, survival and reproductive responses to...

  4. Exploring location influences on firm survival rates using parametric duration models

    NARCIS (Netherlands)

    Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.; Timmermans, H.J.P.; Vries, de B.

    2010-01-01

    Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and

  5. Exploring location influences on firm survival rates using parametric duration models

    NARCIS (Netherlands)

    Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.

    2011-01-01

    Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and

  6. Exploration of location influences on firm survival rates using parametric duration models

    NARCIS (Netherlands)

    Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.

    2011-01-01

    This study explored the influences of location on business firm survival rates with the use of parametric duration models applied to a data set. Of the variables included, those found to be the most significant were accessibility to infrastructure supply, regional effects, demographic and economic

  7. Inference for shared-frailty survival models with left-truncated data

    NARCIS (Netherlands)

    van den Berg, G.J.; Drepper, B.

    2016-01-01

    Shared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with left-truncated

  8. Assessing climate change effects on long-term forest development: adjusting growth, phenology, and seed production in a gap model

    NARCIS (Netherlands)

    Meer, van der P.J.; Jorritsma, I.T.M.; Kramer, K.

    2002-01-01

    The sensitivity of forest development to climate change is assessed using a gap model. Process descriptions in the gap model of growth, phenology, and seed production were adjusted for climate change effects using a detailed process-based growth modeland a regression analysis. Simulation runs over

  9. Predictive modelling of Lactobacillus casei KN291 survival in fermented soy beverage.

    Science.gov (United States)

    Zielińska, Dorota; Dorota, Zielińska; Kołożyn-Krajewska, Danuta; Danuta, Kołożyn-Krajewska; Goryl, Antoni; Antoni, Goryl; Motyl, Ilona

    2014-02-01

    The aim of the study was to construct and verify predictive growth and survival models of a potentially probiotic bacteria in fermented soy beverage. The research material included natural soy beverage (Polgrunt, Poland) and the strain of lactic acid bacteria (LAB) - Lactobacillus casei KN291. To construct predictive models for the growth and survival of L. casei KN291 bacteria in the fermented soy beverage we design an experiment which allowed the collection of CFU data. Fermented soy beverage samples were stored at various temperature conditions (5, 10, 15, and 20°C) for 28 days. On the basis of obtained data concerning the survival of L. casei KN291 bacteria in soy beverage at different temperature and time conditions, two non-linear models (r(2)= 0.68-0.93) and two surface models (r(2)=0.76-0.79) were constructed; these models described the behaviour of the bacteria in the product to a satisfactory extent. Verification of the surface models was carried out utilizing the validation data - at 7°C during 28 days. It was found that applied models were well fitted and charged with small systematic errors, which is evidenced by accuracy factor - Af, bias factor - Bf and mean squared error - MSE. The constructed microbiological growth and survival models of L. casei KN291 in fermented soy beverage enable the estimation of products shelf life period, which in this case is defined by the requirement for the level of the bacteria to be above 10(6) CFU/cm(3). The constructed models may be useful as a tool for the manufacture of probiotic foods to estimate of their shelf life period.

  10. Comparison of Two Foreign Body Retrieval Devices with Adjustable Loops in a Swine Model

    International Nuclear Information System (INIS)

    Konya, Andras

    2006-01-01

    The purpose of the study was to compare two similar foreign body retrieval devices, the Texan TM (TX) and the Texan LONGhorn TM (TX-LG), in a swine model. Both devices feature a ≤30-mm adjustable loop. Capture times and total procedure times for retrieving foreign bodies from the infrarenal aorta, inferior vena cava, and stomach were compared. All attempts with both devices (TX, n = 15; TX-LG, n = 14) were successful. Foreign bodies in the vasculature were captured quickly using both devices (mean ± SD, 88 ± 106 sec for TX vs 67 ± 42 sec for TX-LG) with no significant difference between them. The TX-LG, however, allowed significantly better capture times than the TX in the stomach (p = 0.022), Overall, capture times for the TX-LG were significantly better than for the TX (p = 0.029). There was no significant difference between the total procedure times in any anatomic region. TX-LG performed significantly better than the TX in the stomach and therefore overall. The better torque control and maneuverability of TX-LG resulted in better performance in large anatomic spaces

  11. Modeling and Dynamic Simulation of the Adjust and Control System Mechanism for Reactor CAREM-25

    International Nuclear Information System (INIS)

    Larreteguy, A.E; Mazufri, C.M

    2000-01-01

    The adjust and control system mechanism, MSAC, is an advanced, and in some senses unique, hydromechanical device.The efforts in modeling this mechanism are aimed to: Get a deep understanding of the physical phenomena involved,Identify the set of parameters relevant to the dynamics of the system,Allow the numerical simulation of the system,Predict the behavior of the mechanism in conditions other than that obtainable within the range of operation of the experimental setup (CEM), and Help in defining the design of the CAPEM (loop for testing the mechanism under high pressure/high temperature conditions).Thanks to the close interaction between the mechanics, the experimenters, and the modelists that compose the MSAC task force, it has been possible to suggest improvements, not only in the design of the mechanism, but also in the design and the operation of the pulse generator (GDP) and the rest of the CEM.This effort has led to a design mature enough so as to be tested in a high-pressure loop

  12. Homoclinic connections and subcritical Neimark bifurcation in a duopoly model with adaptively adjusted productions

    International Nuclear Information System (INIS)

    Agliari, Anna

    2006-01-01

    In this paper we study some global bifurcations arising in the Puu's oligopoly model when we assume that the producers do not adjust to the best reply but use an adaptive process to obtain at each step the new production. Such bifurcations cause the appearance of a pair of closed invariant curves, one attracting and one repelling, this latter being involved in the subcritical Neimark bifurcation of the Cournot equilibrium point. The aim of the paper is to highlight the relationship between the global bifurcations causing the appearance/disappearance of two invariant closed curves and the homoclinic connections of some saddle cycle, already conjectured in [Agliari A, Gardini L, Puu T. Some global bifurcations related to the appearance of closed invariant curves. Comput Math Simul 2005;68:201-19]. We refine the results obtained in such a paper, showing that the appearance/disappearance of closed invariant curves is not necessarily related to the existence of an attracting cycle. The characterization of the periodicity tongues (i.e. a region of the parameter space in which an attracting cycle exists) associated with a subcritical Neimark bifurcation is also discussed

  13. Learning Survival Models with On-Line Simulation Activities in the Actuarial Science Degree

    Directory of Open Access Journals (Sweden)

    Antonio Fernandez-Morales

    2011-03-01

    Full Text Available The aim of this paper is to describe an on-line survival laboratory designed to enhance teaching and learning in the Statistics courses of the Actuarial Science Degree of the Uni-versity of Málaga. The objective of the on-line survival lab is to help students through a guided program of simulation activities with the understanding of the most important statistical concepts of the stochastic modeling of human survival, from an Actuarial point of view. The graphical interactive simulator is implemented as Java applets for the web version, and as a Javascript animation for a lite iPhone/iPod touch version. Finally, the results of a survey carried out at the end of the course are discussed to have a preliminary assessment of the students’ satisfaction with the resources, and their perception about the usefulness for their learning process.

  14. Statistical modelling of survival data with random effects h-likelihood approach

    CERN Document Server

    Ha, Il Do; Lee, Youngjo

    2017-01-01

    This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to research...

  15. An approach to the drone fleet survivability assessment based on a stochastic continues-time model

    Science.gov (United States)

    Kharchenko, Vyacheslav; Fesenko, Herman; Doukas, Nikos

    2017-09-01

    An approach and the algorithm to the drone fleet survivability assessment based on a stochastic continues-time model are proposed. The input data are the number of the drones, the drone fleet redundancy coefficient, the drone stability and restoration rate, the limit deviation from the norms of the drone fleet recovery, the drone fleet operational availability coefficient, the probability of the drone failure-free operation, time needed for performing the required tasks by the drone fleet. The ways for improving the recoverable drone fleet survivability taking into account amazing factors of system accident are suggested. Dependencies of the drone fleet survivability rate both on the drone stability and the number of the drones are analysed.

  16. Factors associated with supermarket and convenience store closure: a discrete time spatial survival modelling approach.

    Science.gov (United States)

    Warren, Joshua L; Gordon-Larsen, Penny

    2018-06-01

    While there is a literature on the distribution of food stores across geographic and social space, much of this research uses cross-sectional data. Analyses attempting to understand whether the availability of stores across neighborhoods is associated with diet and/or health outcomes are limited by a lack of understanding of factors that shape the emergence of new stores and the closure of others. We used quarterly data on supermarket and convenience store locations spanning seven years (2006-2012) and tract-level census data in four US cities: Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; San Francisco, California. A spatial discrete-time survival model was used to identify factors associated with an earlier and/or later closure time of a store. Sales volume was typically the strongest indicator of store survival. We identified heterogeneity in the association between tract-level poverty and racial composition with respect to store survival. Stores in high poverty, non-White tracts were often at a disadvantage in terms of survival length. The observed patterns of store survival varied by some of the same neighborhood sociodemographic factors associated with lifestyle and health outcomes, which could lead to confusion in interpretation in studies of the estimated effects of introduction of food stores into neighborhoods on health.

  17. Combined treatment with atorvastatin and imipenem improves survival and vascular functions in mouse model of sepsis.

    Science.gov (United States)

    Choudhury, Soumen; Kannan, Kandasamy; Pule Addison, M; Darzi, Sazad A; Singh, Vishakha; Singh, Thakur Uttam; Thangamalai, Ramasamy; Dash, Jeevan Ranjan; Parida, Subhashree; Debroy, Biplab; Paul, Avishek; Mishra, Santosh Kumar

    2015-08-01

    We have recently reported that pre-treatment, but not the post-treatment with atorvastatin showed survival benefit and improved hemodynamic functions in cecal ligation and puncture (CLP) model of sepsis in mice. Here we examined whether combined treatment with atorvastatin and imipenem after onset of sepsis can prolong survival and improve vascular functions. At 6 and 18h after sepsis induction, treatment with atorvastatin plus imipenem, atorvastatin or imipenem alone or placebo was initiated. Ex vivo experiments were done on mouse aorta to examine the vascular reactivity to nor-adrenaline and acetylcholine and mRNA expressions of α1D AR, GRK2 and eNOS. Atorvastatin plus imipenem extended the survival time to 56.00±4.62h from 20.00±1.66h observed in CLP mice. The survival time with atorvastatin or imipenem alone was 20.50±1.89h and 27.00±4.09h, respectively. The combined treatment reversed the hyporeactivity to nor-adrenaline through preservation of α1D AR mRNA/protein expression and reversal of α1D AR desensitization mediated by GRK2/Gβγ pathway. The treatment also restored endothelium-dependent relaxation to ACh through restoration of aortic eNOS mRNA expression and NO availability. In conclusion, combined treatment with atorvastatin and imipenem exhibited survival benefit and improved vascular functions in septic mice. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Genetic Determinants Associated With in Vivo Survival of Burkholderia cenocepacia in the Caenorhabditis elegans Model

    KAUST Repository

    Wong, Yee-Chin

    2018-05-29

    A Burkholderia cenocepacia infection usually leads to reduced survival and fatal cepacia syndrome in cystic fibrosis patients. The identification of B. cenocepacia essential genes for in vivo survival is key to designing new anti-infectives therapies. We used the Transposon-Directed Insertion Sequencing (TraDIS) approach to identify genes required for B. cenocepacia survival in the model infection host, Caenorhabditis elegans. A B. cenocepacia J2315 transposon pool of ∼500,000 mutants was used to infect C. elegans. We identified 178 genes as crucial for B. cenocepacia survival in the infected nematode. The majority of these genes code for proteins of unknown function, many of which are encoded by the genomic island BcenGI13, while other gene products are involved in nutrient acquisition, general stress responses and LPS O-antigen biosynthesis. Deletion of the glycosyltransferase gene wbxB and a histone-like nucleoid structuring (H-NS) protein-encoding gene (BCAL0154) reduced bacterial accumulation and attenuated virulence in C. elegans. Further analysis using quantitative RT-PCR indicated that BCAL0154 modulates B. cenocepacia pathogenesis via transcriptional regulation of motility-associated genes including fliC, fliG, flhD, and cheB1. This screen has successfully identified genes required for B. cenocepacia survival within the host-associated environment, many of which are potential targets for developing new antimicrobials.

  19. Genetic Determinants Associated With in Vivo Survival of Burkholderia cenocepacia in the Caenorhabditis elegans Model

    KAUST Repository

    Wong, Yee-Chin; Abd El Ghany, Moataz; Ghazzali, Raeece N. M.; Yap, Soon-Joo; Hoh, Chee-Choong; Pain, Arnab; Nathan, Sheila

    2018-01-01

    A Burkholderia cenocepacia infection usually leads to reduced survival and fatal cepacia syndrome in cystic fibrosis patients. The identification of B. cenocepacia essential genes for in vivo survival is key to designing new anti-infectives therapies. We used the Transposon-Directed Insertion Sequencing (TraDIS) approach to identify genes required for B. cenocepacia survival in the model infection host, Caenorhabditis elegans. A B. cenocepacia J2315 transposon pool of ∼500,000 mutants was used to infect C. elegans. We identified 178 genes as crucial for B. cenocepacia survival in the infected nematode. The majority of these genes code for proteins of unknown function, many of which are encoded by the genomic island BcenGI13, while other gene products are involved in nutrient acquisition, general stress responses and LPS O-antigen biosynthesis. Deletion of the glycosyltransferase gene wbxB and a histone-like nucleoid structuring (H-NS) protein-encoding gene (BCAL0154) reduced bacterial accumulation and attenuated virulence in C. elegans. Further analysis using quantitative RT-PCR indicated that BCAL0154 modulates B. cenocepacia pathogenesis via transcriptional regulation of motility-associated genes including fliC, fliG, flhD, and cheB1. This screen has successfully identified genes required for B. cenocepacia survival within the host-associated environment, many of which are potential targets for developing new antimicrobials.

  20. Adjustments of the TaD electron density reconstruction model with GNSS-TEC parameters for operational application purposes

    Directory of Open Access Journals (Sweden)

    Belehaki Anna

    2012-12-01

    Full Text Available Validation results on the latest version of TaD model (TaDv2 show realistic reconstruction of the electron density profiles (EDPs with an average error of 3 TECU, similar to the error obtained from GNSS-TEC calculated paremeters. The work presented here has the aim to further improve the accuracy of the TaD topside reconstruction, adjusting the TEC parameter calculated from TaD model with the TEC parameter calculated by GNSS transmitting RINEX files provided by receivers co-located with the Digisondes. The performance of the new version is tested during a storm period demonstrating further improvements in respect to the previous version. Statistical comparison of modeled and observed TEC confirms the validity of the proposed adjustment. A significant benefit of the proposed upgrade is that it facilitates the real-time implementation of TaD. The model needs a reliable measure of the scale height at the peak height, which is supposed to be provided by Digisondes. Oftenly, the automatic scaling software fails to correctly calculate the scale height at the peak, Hm, due to interferences in the receiving signal. Consequently the model estimated topside scale height is wrongly calculated leading to unrealistic results for the modeled EDP. The proposed TEC adjustment forces the model to correctly reproduce the topside scale height, despite the inaccurate values of Hm. This adjustment is very important for the application of TaD in an operational environment.

  1. Health economic modeling of the potential cost saving effects of Neurally Adjusted Ventilator Assist.

    Science.gov (United States)

    Hjelmgren, Jonas; Bruce Wirta, Sara; Huetson, Pernilla; Myrén, Karl-Johan; Göthberg, Sylvia

    2016-02-01

    Asynchrony between patient and ventilator breaths is associated with increased duration of mechanical ventilation (MV). Neurally Adjusted Ventilatory Assist (NAVA) controls MV through an esophageal reading of diaphragm electrical activity via a nasogastric tube mounted with electrode rings. NAVA has been shown to decrease asynchrony in comparison to pressure support ventilation (PSV). The objective of this study was to conduct a health economic evaluation of NAVA compared with PSV. We developed a model based on an indirect link between improved synchrony with NAVA versus PSV and fewer days spent on MV in synchronous patients. Unit costs for MV were obtained from the Swedish intensive care unit register, and used in the model along with NAVA-specific costs. The importance of each parameter (proportion of asynchronous patients, costs, and average MV duration) for the overall results was evaluated through sensitivity analyses. Base case results showed that 21% of patients ventilated with NAVA were asynchronous versus 52% of patients receiving PSV. This equals an absolute difference of 31% and an average of 1.7 days less on MV and a total cost saving of US$7886 (including NAVA catheter costs). A breakeven analysis suggested that NAVA was cost effective compared with PSV given an absolute difference in the proportion of asynchronous patients greater than 2.5% (49.5% versus 52% asynchronous patients with NAVA and PSV, respectively). The base case results were stable to changes in parameters, such as difference in asynchrony, duration of ventilation and daily intensive care unit costs. This study showed economically favorable results for NAVA versus PSV. Our results show that only a minor decrease in the proportion of asynchronous patients with NAVA is needed for investments to pay off and generate savings. Future studies need to confirm this result by directly relating improved synchrony to the number of days on MV. © The Author(s), 2015.

  2. [Adjustment of the Andersen's model to the Mexican context: access to prenatal care].

    Science.gov (United States)

    Tamez-González, Silvia; Valle-Arcos, Rosa Irene; Eibenschutz-Hartman, Catalina; Méndez-Ramírez, Ignacio

    2006-01-01

    The aim of this work was to propose an adjustment to the Model of Andersen who answers better to the social inequality of the population in the Mexico City and allows to evaluate the effect of socioeconomic factors in the access to the prenatal care of a sample stratified according to degree of marginalization. The data come from a study of 663 women, randomly selected from a framework sample of 21,421 homes in Mexico City. This work collects information about factors that affect utilization of health services, as well as predisposing factors (age and socioeconomic level), as enabling factors (education, social support, entitlement, pay out of pocket and opinion of health services), and need factors. The sample was ranked according to exclusion variables into three stratums. The data were analyzed through the technique of path analysis. The results indicate that socioeconomic level takes part like predisposed variable for utilization of prenatal care services into three stratums. Otherwise, education and social support were the most important enabling variables for utilization of prenatal care services in the same three groups. In regard to low stratum, the most important enabling variables were education and entitlement. For high stratum the principal enabling variables were pay out of pocket and social support. The medium stratum shows atypical behavior which it was difficult to explain and understand. There was not mediating role with need variable in three models. This indicated absence of equality in all stratums. However, the most correlations in high stratum perhaps indicate less inequitable conditions regarding other stratums.

  3. Opportunities for Improving Army Modeling and Simulation Development: Making Fundamental Adjustments and Borrowing Commercial Business Practices

    National Research Council Canada - National Science Library

    Lee, John

    2000-01-01

    ...; requirements which span the conflict spectrum. The Army's current staff training simulation development process could better support all possible scenarios by making some fundamental adjustments and borrowing commercial business practices...

  4. Using Multilevel Modeling to Assess Case-Mix Adjusters in Consumer Experience Surveys in Health Care

    NARCIS (Netherlands)

    Damman, Olga C.; Stubbe, Janine H.; Hendriks, Michelle; Arah, Onyebuchi A.; Spreeuwenberg, Peter; Delnoij, Diana M. J.; Groenewegen, Peter P.

    2009-01-01

    Background: Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for

  5. Effect of the spray volume adjustment model on the efficiency of fungicides and residues in processing tomato

    Energy Technology Data Exchange (ETDEWEB)

    Ratajkiewicz, H.; Kierzek, R.; Raczkowski, M.; Hołodyńska-Kulas, A.; Łacka, A.; Wójtowicz, A.; Wachowiak, M.

    2016-11-01

    This study compared the effects of a proportionate spray volume (PSV) adjustment model and a fixed model (300 L/ha) on the infestation of processing tomato with potato late blight (Phytophthora infestans (Mont.) de Bary) (PLB) and azoxystrobin and chlorothalonil residues in fruits in three consecutive seasons. The fungicides were applied in alternating system with or without two spreader adjuvants. The proportionate spray volume adjustment model was based on the number of leaves on plants and spray volume index. The modified Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method was optimized and validated for extraction of azoxystrobin and chlorothalonil residue. Gas chromatography with a nitrogen and phosphorus detector and an electron capture detector were used for the analysis of fungicides. The results showed that higher fungicidal residues were connected with lower infestation of tomato with PLB. PSV adjustment model resulted in lower infestation of tomato than the fixed model (300 L/ha) when fungicides were applied at half the dose without adjuvants. Higher expected spray interception into the tomato canopy with the PSV system was recognized as the reasons of better control of PLB. The spreader adjuvants did not have positive effect on the biological efficacy of spray volume application systems. The results suggest that PSV adjustment model can be used to determine the spray volume for fungicide application for processing tomato crop. (Author)

  6. Effect of the spray volume adjustment model on the efficiency of fungicides and residues in processing tomato

    Directory of Open Access Journals (Sweden)

    Henryk Ratajkiewicz

    2016-08-01

    Full Text Available This study compared the effects of a proportionate spray volume (PSV adjustment model and a fixed model (300 L/ha on the infestation of processing tomato with potato late blight (Phytophthora infestans (Mont. de Bary (PLB and azoxystrobin and chlorothalonil residues in fruits in three consecutive seasons. The fungicides were applied in alternating system with or without two spreader adjuvants. The proportionate spray volume adjustment model was based on the number of leaves on plants and spray volume index. The modified Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS method was optimized and validated for extraction of azoxystrobin and chlorothalonil residue. Gas chromatography with a nitrogen and phosphorus detector and an electron capture detector were used for the analysis of fungicides. The results showed that higher fungicidal residues were connected with lower infestation of tomato with PLB. PSV adjustment model resulted in lower infestation of tomato than the fixed model (300 L/ha when fungicides were applied at half the dose without adjuvants. Higher expected spray interception into the tomato canopy with the PSV system was recognized as the reasons of better control of PLB. The spreader adjuvants did not have positive effect on the biological efficacy of spray volume application systems. The results suggest that PSV adjustment model can be used to determine the spray volume for fungicide application for processing tomato crop.

  7. Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

    Science.gov (United States)

    Bernhardt, Paul W; Wang, Huixia Judy; Zhang, Daowen

    2014-01-01

    Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

  8. Application of accelerated failure time models for breast cancer patients' survival in Kurdistan Province of Iran.

    Science.gov (United States)

    Karimi, Asrin; Delpisheh, Ali; Sayehmiri, Kourosh

    2016-01-01

    Breast cancer is the most common cancer and the second common cause of cancer-induced mortalities in Iranian women. There has been a rapid development in hazard models and survival analysis in the last decade. The aim of this study was to evaluate the prognostic factors of overall survival (OS) in breast cancer patients using accelerated failure time models (AFT). This was a retrospective-analytic cohort study. About 313 women with a pathologically proven diagnosis of breast cancer who had been treated during a 7-year period (since January 2006 until March 2014) in Sanandaj City, Kurdistan Province of Iran were recruited. Performance among AFT was assessed using the goodness of fit methods. Discrimination among the exponential, Weibull, generalized gamma, log-logistic, and log-normal distributions was done using Akaik information criteria and maximum likelihood. The 5 years OS was 75% (95% CI = 74.57-75.43). The main results in terms of survival were found for the different categories of the clinical stage covariate, tumor metastasis, and relapse of cancer. Survival time in breast cancer patients without tumor metastasis and relapse were 4, 2-fold longer than other patients with metastasis and relapse, respectively. One of the most important undermining prognostic factors in breast cancer is metastasis; hence, knowledge of the mechanisms of metastasis is necessary to prevent it so occurrence and treatment of metastatic breast cancer and ultimately extend the lifetime of patients.

  9. Modeling the kinetics of survival of Staphylococcus aureus in regional yogurt from goat's milk.

    Science.gov (United States)

    Bednarko-Młynarczyk, E; Szteyn, J; Białobrzewski, I; Wiszniewska-Łaszczych, A; Liedtke, K

    2015-01-01

    The aim of this study was to determine the kinetics of the survival of the test strain of Staphylococcus aureus in the product investigated. Yogurt samples were contaminated with S. aure to an initial level of 10(3)-10(4) cfu/g. The samples were then stored at four temperatures: 4, 6, 20, 22°C. During storage, the number of S. aureus forming colonies in a gram of yogurt was determined every two hours. Based on the results of the analysis culture the curves of survival were plotted. Three primary models were selected to describe the kinetics of changes in the count of bacteria: Cole's model, a modified model of Gompertz and the model of Baranyi and Roberts. Analysis of the model fit carried out based on the average values of Pearson's correlation coefficient, between the modeled and measured values, showed that the Cole's model had the worst fit. The modified Gompertz model showed the count of S. aureus as a negative value. These drawbacks were not observed in the model of Baranyi and Roberts. For this reason, this model best reflects the kinetics of changes in the number of staphylococci in yogurt.

  10. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

    Science.gov (United States)

    Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

    2016-01-01

    Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

  11. Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models

    Directory of Open Access Journals (Sweden)

    Lois A Gelfand

    2016-03-01

    Full Text Available Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH and fully parametric accelerated failure time (AFT approaches for illustration.Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively under varied data conditions, some including censoring. A simulated data set illustrates the findings.Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome – underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  12. A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic

    International Nuclear Information System (INIS)

    Chow, Edward; Fung, KinWah; Panzarella, Tony; Bezjak, Andrea; Danjoux, Cyril; Tannock, Ian

    2002-01-01

    Purpose: To develop a predictive model for survival from the time of presentation in an outpatient palliative radiotherapy clinic. Methods and Materials: Sixteen factors were analyzed prospectively in 395 patients seen in a dedicated palliative radiotherapy clinic in a large tertiary cancer center using Cox's proportional hazards regression model. Results: Six prognostic factors had a statistically significant impact on survival, as follows: primary cancer site, site of metastases, Karnofsky performance score (KPS), and fatigue, appetite, and shortness of breath scores from the modified Edmonton Symptom Assessment Scale. Risk group stratification was performed (1) by assigning weights to the prognostic factors based on their levels of significance, and (2) by the number of risk factors present. The weighting method provided a Survival Prediction Score (SPS), ranging from 0 to 32. The survival probability at 3, 6, and 12 months was 83%, 70%, and 51%, respectively, for patients with SPS ≤13 (n=133); 67%, 41%, and 20% for patients with SPS 14-19 (n=129); and 36%, 18%, and 4% for patients with SPS ≥20 (n=133) (p<0.0001). Corresponding survival probabilities based on number of risk factors were as follows: 85%, 72%, and 52% (≤3 risk factors) (n=98); 68%, 47%, and 24% (4 risk factors) (n=117); and 46%, 24%, and 11% (≥5 factors) (n=180) (p<0.0001). Conclusion: Clinical prognostic factors can be used to predict prognosis among patients attending a palliative radiotherapy clinic. If validated in an independent series of patients, the model can be used to guide clinical decisions, plan supportive services, and allocate resource use

  13. Analysis of survival in breast cancer patients by using different parametric models

    Science.gov (United States)

    Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

    2017-09-01

    In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

  14. Developing and Validating a Survival Prediction Model for NSCLC Patients Through Distributed Learning Across 3 Countries.

    Science.gov (United States)

    Jochems, Arthur; Deist, Timo M; El Naqa, Issam; Kessler, Marc; Mayo, Chuck; Reeves, Jackson; Jolly, Shruti; Matuszak, Martha; Ten Haken, Randall; van Soest, Johan; Oberije, Cary; Faivre-Finn, Corinne; Price, Gareth; de Ruysscher, Dirk; Lambin, Philippe; Dekker, Andre

    2017-10-01

    Tools for survival prediction for non-small cell lung cancer (NSCLC) patients treated with chemoradiation or radiation therapy are of limited quality. In this work, we developed a predictive model of survival at 2 years. The model is based on a large volume of historical patient data and serves as a proof of concept to demonstrate the distributed learning approach. Clinical data from 698 lung cancer patients, treated with curative intent with chemoradiation or radiation therapy alone, were collected and stored at 2 different cancer institutes (559 patients at Maastro clinic (Netherlands) and 139 at Michigan university [United States]). The model was further validated on 196 patients originating from The Christie (United Kingdon). A Bayesian network model was adapted for distributed learning (the animation can be viewed at https://www.youtube.com/watch?v=ZDJFOxpwqEA). Two-year posttreatment survival was chosen as the endpoint. The Maastro clinic cohort data are publicly available at https://www.cancerdata.org/publication/developing-and-validating-survival-prediction-model-nsclc-patients-through-distributed, and the developed models can be found at www.predictcancer.org. Variables included in the final model were T and N category, age, performance status, and total tumor dose. The model has an area under the curve (AUC) of 0.66 on the external validation set and an AUC of 0.62 on a 5-fold cross validation. A model based on the T and N category performed with an AUC of 0.47 on the validation set, significantly worse than our model (PLearning the model in a centralized or distributed fashion yields a minor difference on the probabilities of the conditional probability tables (0.6%); the discriminative performance of the models on the validation set is similar (P=.26). Distributed learning from federated databases allows learning of predictive models on data originating from multiple institutions while avoiding many of the data-sharing barriers. We believe that

  15. DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

    International Nuclear Information System (INIS)

    Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V.; Tkachenko, N. P.

    2015-01-01

    The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available

  16. DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

    Science.gov (United States)

    Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V.; Tkachenko, N. P.

    2015-12-01

    The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.

  17. DaMoScope and its internet graphics for the visual control of adjusting mathematical models describing experimental data

    Energy Technology Data Exchange (ETDEWEB)

    Belousov, V. I.; Ezhela, V. V.; Kuyanov, Yu. V., E-mail: Yu.Kuyanov@gmail.com; Tkachenko, N. P. [Institute for High Energy Physics, National Research Center Kurchatov Institute, COMPAS Group (Russian Federation)

    2015-12-15

    The experience of using the dynamic atlas of the experimental data and mathematical models of their description in the problems of adjusting parametric models of observable values depending on kinematic variables is presented. The functional possibilities of an image of a large number of experimental data and the models describing them are shown by examples of data and models of observable values determined by the amplitudes of elastic scattering of hadrons. The Internet implementation of an interactive tool DaMoScope and its interface with the experimental data and codes of adjusted parametric models with the parameters of the best description of data are schematically shown. The DaMoScope codes are freely available.

  18. Data Assimilation and Adjusted Spherical Harmonic Model of VTEC Map over Thailand

    Science.gov (United States)

    Klinngam, Somjai; Maruyama, Takashi; Tsugawa, Takuya; Ishii, Mamoru; Supnithi, Pornchai; Chiablaem, Athiwat

    2016-07-01

    The global navigation satellite system (GNSS) and high frequency (HF) communication are vulnerable to the ionospheric irregularities, especially when the signal travels through the low-latitude region and around the magnetic equator known as equatorial ionization anomaly (EIA) region. In order to study the ionospheric effects to the communications performance in this region, the regional map of the observed total electron content (TEC) can show the characteristic and irregularities of the ionosphere. In this work, we develop the two-dimensional (2D) map of vertical TEC (VTEC) over Thailand using the adjusted spherical harmonic model (ASHM) and the data assimilation technique. We calculate the VTEC from the receiver independent exchange (RINEX) files recorded by the dual-frequency global positioning system (GPS) receivers on July 8th, 2012 (quiet day) at 12 stations around Thailand: 0° to 25°E and 95°N to 110°N. These stations are managed by Department of Public Works and Town & Country Planning (DPT), Thailand, and the South East Asia Low-latitude ionospheric Network (SEALION) project operated by National Institute of Information and Communications Technology (NICT), Japan, and King Mongkut's Institute of Technology Ladkrabang (KMITL). We compute the median observed VTEC (OBS-VTEC) in the grids with the spatial resolution of 2.5°x5° in latitude and longitude and time resolution of 2 hours. We assimilate the OBS-VTEC with the estimated VTEC from the International Reference Ionosphere model (IRI-VTEC) as well as the ionosphere map exchange (IONEX) files provided by the International GNSS Service (IGS-VTEC). The results show that the estimation of the 15-degree ASHM can be improved when both of IRI-VTEC and IGS-VTEC are weighted by the latitude-dependent factors before assimilating with the OBS-VTEC. However, the IRI-VTEC assimilation can improve the ASHM estimation more than the IGS-VTEC assimilation. Acknowledgment: This work is partially funded by the

  19. Validation of a Predictive Model for Survival in Metastatic Cancer Patients Attending an Outpatient Palliative Radiotherapy Clinic

    International Nuclear Information System (INIS)

    Chow, Edward; Abdolell, Mohamed; Panzarella, Tony; Harris, Kristin; Bezjak, Andrea; Warde, Padraig; Tannock, Ian

    2009-01-01

    Purpose: To validate a predictive model for survival of patients attending a palliative radiotherapy clinic. Methods and Materials: We described previously a model that had good predictive value for survival of patients referred during 1999 (1). The six prognostic factors (primary cancer site, site of metastases, Karnofsky performance score, and the fatigue, appetite and shortness-of-breath items from the Edmonton Symptom Assessment Scale) identified in this training set were extracted from the prospective database for the year 2000. We generated a partial score whereby each prognostic factor was assigned a value proportional to its prognostic weight. The sum of the partial scores for each patient was used to construct a survival prediction score (SPS). Patients were also grouped according to the number of these risk factors (NRF) that they possessed. The probability of survival at 3, 6, and 12 months was generated. The models were evaluated for their ability to predict survival in this validation set with appropriate statistical tests. Results: The median survival and survival probabilities of the training and validation sets were similar when separated into three groups using both SPS and NRF methods. There was no statistical difference in the performance of the SPS and NRF methods in survival prediction. Conclusion: Both the SPS and NRF models for predicting survival in patients referred for palliative radiotherapy have been validated. The NRF model is preferred because it is simpler and avoids the need to remember the weightings among the prognostic factors

  20. Adjustment of regional regression models of urban-runoff quality using data for Chattanooga, Knoxville, and Nashville, Tennessee

    Science.gov (United States)

    Hoos, Anne B.; Patel, Anant R.

    1996-01-01

    Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.

  1. Development and Validation of Perioperative Risk-Adjustment Models for Hip Fracture Repair, Total Hip Arthroplasty, and Total Knee Arthroplasty.

    Science.gov (United States)

    Schilling, Peter L; Bozic, Kevin J

    2016-01-06

    Comparing outcomes across providers requires risk-adjustment models that account for differences in case mix. The burden of data collection from the clinical record can make risk-adjusted outcomes difficult to measure. The purpose of this study was to develop risk-adjustment models for hip fracture repair (HFR), total hip arthroplasty (THA), and total knee arthroplasty (TKA) that weigh adequacy of risk adjustment against data-collection burden. We used data from the American College of Surgeons National Surgical Quality Improvement Program to create derivation cohorts for HFR (n = 7000), THA (n = 17,336), and TKA (n = 28,661). We developed logistic regression models for each procedure using age, sex, American Society of Anesthesiologists (ASA) physical status classification, comorbidities, laboratory values, and vital signs-based comorbidities as covariates, and validated the models with use of data from 2012. The derivation models' C-statistics for mortality were 80%, 81%, 75%, and 92% and for adverse events were 68%, 68%, 60%, and 70% for HFR, THA, TKA, and combined procedure cohorts. Age, sex, and ASA classification accounted for a large share of the explained variation in mortality (50%, 58%, 70%, and 67%) and adverse events (43%, 45%, 46%, and 68%). For THA and TKA, these three variables were nearly as predictive as models utilizing all covariates. HFR model discrimination improved with the addition of comorbidities and laboratory values; among the important covariates were functional status, low albumin, high creatinine, disseminated cancer, dyspnea, and body mass index. Model performance was similar in validation cohorts. Risk-adjustment models using data from health records demonstrated good discrimination and calibration for HFR, THA, and TKA. It is possible to provide adequate risk adjustment using only the most predictive variables commonly available within the clinical record. This finding helps to inform the trade-off between model performance and data

  2. Adolescent Sibling Relationship Quality and Adjustment: Sibling Trustworthiness and Modeling, as Factors Directly and Indirectly Influencing These Associations

    Science.gov (United States)

    Gamble, Wendy C.; Yu, Jeong Jin; Kuehn, Emily D.

    2011-01-01

    The main goal of this study was to examine the direct and moderating effects of trustworthiness and modeling on adolescent siblings' adjustment. Data were collected from 438 families including a mother, a younger sibling in fifth, sixth, or seventh grade (M = 11.6 years), and an older sibling (M = 14.3 years). Respondents completed Web-based…

  3. Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

    Science.gov (United States)

    Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

    2016-01-01

    Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

  4. Cell survival in carbon beams - comparison of amorphous track model predictions

    DEFF Research Database (Denmark)

    Grzanka, L.; Greilich, S.; Korcyl, M.

    Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under i....... Amorphous track modelling of luminescence detector efficiency in proton and carbon beams. 4.Tsuruoka C, Suzuki M, Kanai T, et al. LET and ion species dependence for cell killing in normal human skin fibroblasts. Radiat Res. 2005;163:494-500.......Introduction: Predictions of the radiobiological effectiveness (RBE) play an essential role in treatment planning with heavy charged particles. Amorphous track models ( [1] , [2] , also referred to as track structure models) provide currently the most suitable description of cell survival under ion....... [2] . In addition, a new approach based on microdosimetric distributions is presented and investigated [3] . Material and methods: A suitable software library embrasing the mentioned amorphous track models including numerous submodels with respect to delta-electron range models, radial dose...

  5. Convexity Adjustments

    DEFF Research Database (Denmark)

    M. Gaspar, Raquel; Murgoci, Agatha

    2010-01-01

    A convexity adjustment (or convexity correction) in fixed income markets arises when one uses prices of standard (plain vanilla) products plus an adjustment to price nonstandard products. We explain the basic and appealing idea behind the use of convexity adjustments and focus on the situations...

  6. A Key Challenge in Global HRM: Adding New Insights to Existing Expatriate Spouse Adjustment Models

    Science.gov (United States)

    Gupta, Ritu; Banerjee, Pratyush; Gaur, Jighyasu

    2012-01-01

    This study is an attempt to strengthen the existing knowledge about factors affecting the adjustment process of the trailing expatriate spouse and the subsequent impact of any maladjustment or expatriate failure. We conducted a qualitative enquiry using grounded theory methodology with 26 Indian spouses who had to deal with their partner's…

  7. Using multilevel modelling to assess case-mix adjusters in consumers experience surveys in health care

    NARCIS (Netherlands)

    Damman, O.C.; Stubbe, J.H.; Hendriks, M.; Arah, O.A.; Spreeuwenberg, P.; Delnoij, D.M.J.; Groenewegen, P.P.

    2009-01-01

    Background: Ratings on the quality of healthcare from the consumer’s perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for

  8. Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

    NARCIS (Netherlands)

    Damman, O.C.; Stubbe, J.H.; Hendriks, M.; Arah, O.A.; Spreeuwenberg, P.; Delnoij, D.M.J.; Groenewegen, P.P.

    2009-01-01

    Background: Ratings on the quality of healthcare from the consumer’s perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for

  9. A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients

    Energy Technology Data Exchange (ETDEWEB)

    Oberije, Cary, E-mail: cary.oberije@maastro.nl [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); De Ruysscher, Dirk [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Universitaire Ziekenhuizen Leuven, KU Leuven (Belgium); Houben, Ruud [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands); Heuvel, Michel van de; Uyterlinde, Wilma [Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Deasy, Joseph O. [Memorial Sloan Kettering Cancer Center, New York (United States); Belderbos, Jose [Department of Radiation Oncology, Netherlands Cancer Institute, Amsterdam (Netherlands); Dingemans, Anne-Marie C. [Department of Pulmonology, University Hospital Maastricht, Research Institute GROW of Oncology, Maastricht (Netherlands); Rimner, Andreas; Din, Shaun [Memorial Sloan Kettering Cancer Center, New York (United States); Lambin, Philippe [Radiation Oncology, Research Institute GROW of Oncology, Maastricht University Medical Center, Maastricht (Netherlands)

    2015-07-15

    Purpose: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient. Methods and Materials: Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130). Results: The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability ( (www.predictcancer.org)). The data set can be downloaded at (https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048). Conclusions: The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

  10. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    International Nuclear Information System (INIS)

    Taktak, Azzam F G; Fisher, Anthony C; Damato, Bertil E

    2004-01-01

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate

  11. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    Energy Technology Data Exchange (ETDEWEB)

    Taktak, Azzam F G [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Fisher, Anthony C [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Damato, Bertil E [Department of Ophthalmology, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom)

    2004-01-07

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate.

  12. Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic.

    Science.gov (United States)

    Wang, Ming; Long, Qi

    2016-09-01

    Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c-statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy is assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations. © 2016, The International Biometric Society.

  13. Economic evaluation of nivolumab for the treatment of second-line advanced squamous NSCLC in Canada: a comparison of modeling approaches to estimate and extrapolate survival outcomes.

    Science.gov (United States)

    Goeree, Ron; Villeneuve, Julie; Goeree, Jeff; Penrod, John R; Orsini, Lucinda; Tahami Monfared, Amir Abbas

    2016-06-01

    Background Lung cancer is the most common type of cancer in the world and is associated with significant mortality. Nivolumab demonstrated statistically significant improvements in progression-free survival (PFS) and overall survival (OS) for patients with advanced squamous non-small cell lung cancer (NSCLC) who were previously treated. The cost-effectiveness of nivolumab has not been assessed in Canada. A contentious component of projecting long-term cost and outcomes in cancer relates to the modeling approach adopted, with the two most common approaches being partitioned survival (PS) and Markov models. The objectives of this analysis were to estimate the cost-utility of nivolumab and to compare the results using these alternative modeling approaches. Methods Both PS and Markov models were developed using docetaxel and erlotinib as comparators. A three-health state model was used consisting of progression-free, progressed disease, and death. Disease progression and time to progression were estimated by identifying best-fitting survival curves from the clinical trial data for PFS and OS. Expected costs and health outcomes were calculated by combining health-state occupancy with medical resource use and quality-of-life assigned to each of the three health states. The health outcomes included in the model were survival and quality-adjusted-life-years (QALYs). Results Nivolumab was found to have the highest expected per-patient cost, but also improved per-patient life years (LYs) and QALYs. Nivolumab cost an additional $151,560 and $140,601 per QALY gained compared to docetaxel and erlotinib, respectively, using a PS model approach. The cost-utility estimates using a Markov model were very similar ($152,229 and $141,838, respectively, per QALY gained). Conclusions Nivolumab was found to involve a trade-off between improved patient survival and QALYs, and increased cost. It was found that the use of a PS or Markov model produced very similar estimates of expected cost

  14. Exact results for survival probability in the multistate Landau-Zener model

    International Nuclear Information System (INIS)

    Volkov, M V; Ostrovsky, V N

    2004-01-01

    An exact formula is derived for survival probability in the multistate Landau-Zener model in the special case where the initially populated state corresponds to the extremal (maximum or minimum) slope of a linear diabatic potential curve. The formula was originally guessed by S Brundobler and V Elzer (1993 J. Phys. A: Math. Gen. 26 1211) based on numerical calculations. It is a simple generalization of the expression for the probability of diabatic passage in the famous two-state Landau-Zener model. Our result is obtained via analysis and summation of the entire perturbation theory series

  15. Genetic evaluation of calf and heifer survival in Iranian Holstein cattle using linear and threshold models.

    Science.gov (United States)

    Forutan, M; Ansari Mahyari, S; Sargolzaei, M

    2015-02-01

    Calf and heifer survival are important traits in dairy cattle affecting profitability. This study was carried out to estimate genetic parameters of survival traits in female calves at different age periods, until nearly the first calving. Records of 49,583 female calves born during 1998 and 2009 were considered in five age periods as days 1-30, 31-180, 181-365, 366-760 and full period (day 1-760). Genetic components were estimated based on linear and threshold sire models and linear animal models. The models included both fixed effects (month of birth, dam's parity number, calving ease and twin/single) and random effects (herd-year, genetic effect of sire or animal and residual). Rates of death were 2.21, 3.37, 1.97, 4.14 and 12.4% for the above periods, respectively. Heritability estimates were very low ranging from 0.48 to 3.04, 0.62 to 3.51 and 0.50 to 4.24% for linear sire model, animal model and threshold sire model, respectively. Rank correlations between random effects of sires obtained with linear and threshold sire models and with linear animal and sire models were 0.82-0.95 and 0.61-0.83, respectively. The estimated genetic correlations between the five different periods were moderate and only significant for 31-180 and 181-365 (r(g) = 0.59), 31-180 and 366-760 (r(g) = 0.52), and 181-365 and 366-760 (r(g) = 0.42). The low genetic correlations in current study would suggest that survival at different periods may be affected by the same genes with different expression or by different genes. Even though the additive genetic variations of survival traits were small, it might be possible to improve these traits by traditional or genomic selection. © 2014 Blackwell Verlag GmbH.

  16. Modeling the survivability of brucella to exposure of Ultraviolet radiation and temperature

    Science.gov (United States)

    Howe, R.

    Accumulated summation of daily Ultra Violet-B (UV-B = 290? to 320 ? ) data? from The USDA Ultraviolet Radiation Monitoring Program show good correlation (R^2 = 77%) with daily temperature data during the five month period from February through June, 1998. Exposure of disease organisms, such as brucella to the effects of accumulated UV-B radiation, can be modeled for a 5 month period from February through June, 1998. Estimates of a lethal dosage for brucell of UV-B in the environment is dependent on minimum/maximum temperature and Solar Zenith Angle for the time period. The accumulated increase in temperature over this period also effects the decomposition of an aborted fetus containing brucella. Decomposition begins at some minimum daily temperature at 27 to 30 degrees C and peaks at 39 to 40C. It is useful to view the summation of temperature as a threshold for other bacteria growth, so that accumulated temperature greater than some value causes decomposition through competition with other bacteria and brucella die from the accumulated effects of UV-B, temperature and organism competition. Results of a study (Cook 1998) to determine survivability of brucellosis in the environment through exposure of aborted bovine fetuses show no one cause can be attributed to death of the disease agent. The combination of daily increase in temperature and accumulated UV-B radiation reveal an inverse correlation to survivability data and can be modeled as an indicator of brucella survivability in the environment in arid regions.

  17. A linear-quadratic model of cell survival considering both sublethal and potentially lethal radiation damage

    International Nuclear Information System (INIS)

    Rutz, H.P.; Coucke, P.A.; Mirimanoff, R.O.

    1991-01-01

    The authors assessed the dose-dependence of repair of potentially lethal damage in Chinese hamster ovary cells x-irradiated in vitro. The recovery ratio (RR) by which survival (SF) of the irradiated cells was enhanced increased exponentially with a linear and a quadratic component namely ζ and ψ: RR=exp(ζD+ψD 2 ). Survival of irradiated cells can thus be expressed by a combined linear-quadratic model considering 4 variables, namely α and β for the capacity of the cells to accumulate sublethal damage, and ζ and ψ for their capacity to repair potentially lethal damage: SF=exp((ζ-α)D+ (ψ-β)D 2 ). author. 26 refs.; 1 fig.; 1 tab

  18. Personal resilience, cognitive appraisals, and coping: an integrative model of adjustment to abortion.

    Science.gov (United States)

    Major, B; Richards, C; Cooper, M L; Cozzarelli, C; Zubek, J

    1998-03-01

    We hypothesized that the effects of personality (self-esteem, control, and optimism) on postabortion adaptation (distress, well-being, and decision satisfaction) would be fully mediated by preabortion cognitive appraisals (stress appraisals and self-efficacy appraisals) and postabortion coping. We further proposed that the effects of preabortion appraisals on adaptation would be fully mediated by postabortion coping. Results of a longitudinal study of 527 women who had first-trimester abortions supported our hypotheses. Women with more resilient personalities appraised their abortion as less stressful and had higher self-efficacy for coping with the abortion. More positive appraisals predicted greater acceptance/reframing coping and lesser avoidance/denial, venting, support seeking, and religious coping. Acceptance-reframing predicted better adjustment on all measures, whereas avoidance-denial and venting related to poorer adjustment on all measures. Greater support seeking was associated with reduced distress, and greater religious coping was associated with less decision satisfaction.

  19. An Optic Nerve Crush Injury Murine Model to Study Retinal Ganglion Cell Survival

    Science.gov (United States)

    Tang, Zhongshu; Zhang, Shuihua; Lee, Chunsik; Kumar, Anil; Arjunan, Pachiappan; Li, Yang; Zhang, Fan; Li, Xuri

    2011-01-01

    Injury to the optic nerve can lead to axonal degeneration, followed by a gradual death of retinal ganglion cells (RGCs), which results in irreversible vision loss. Examples of such diseases in human include traumatic optic neuropathy and optic nerve degeneration in glaucoma. It is characterized by typical changes in the optic nerve head, progressive optic nerve degeneration, and loss of retinal ganglion cells, if uncontrolled, leading to vision loss and blindness. The optic nerve crush (ONC) injury mouse model is an important experimental disease model for traumatic optic neuropathy, glaucoma, etc. In this model, the crush injury to the optic nerve leads to gradual retinal ganglion cells apoptosis. This disease model can be used to study the general processes and mechanisms of neuronal death and survival, which is essential for the development of therapeutic measures. In addition, pharmacological and molecular approaches can be used in this model to identify and test potential therapeutic reagents to treat different types of optic neuropathy. Here, we provide a step by step demonstration of (I) Baseline retrograde labeling of retinal ganglion cells (RGCs) at day 1, (II) Optic nerve crush injury at day 4, (III) Harvest the retinae and analyze RGC survival at day 11, and (IV) Representative result. PMID:21540827

  20. Overall survival in lower IPSS risk MDS by receipt of iron chelation therapy, adjusting for patient-related factors and measuring from time of first red blood cell transfusion dependence: an MDS-CAN analysis.

    Science.gov (United States)

    Leitch, Heather A; Parmar, Ambica; Wells, Richard A; Chodirker, Lisa; Zhu, Nancy; Nevill, Thomas J; Yee, Karen W L; Leber, Brian; Keating, Mary-Margaret; Sabloff, Mitchell; St Hilaire, Eve; Kumar, Rajat; Delage, Robert; Geddes, Michelle; Storring, John M; Kew, Andrea; Shamy, April; Elemary, Mohamed; Lenis, Martha; Mamedov, Alexandre; Ivo, Jessica; Francis, Janika; Zhang, Liying; Buckstein, Rena

    2017-10-01

    Analyses suggest iron overload in red blood cell (RBC) transfusion-dependent (TD) patients with myleodysplastic syndrome (MDS) portends inferior overall survival (OS) that is attenuated by iron chelation therapy (ICT) but may be biassed by unbalanced patient-related factors. The Canadian MDS Registry prospectively measures frailty, comorbidity and disability. We analysed OS by receipt of ICT, adjusting for these patient-related factors. TD International Prognostic Scoring System (IPSS) low and intermediate-1 risk MDS, at RBC TD, were included. Predictive factors for OS were determined. A matched pair analysis considering age, revised IPSS, TD severity, time from MDS diagnosis to TD, and receipt of disease-modifying agents was conducted. Of 239 patients, 83 received ICT; frailty, comorbidity and disability did not differ from non-ICT patients. Median OS from TD was superior in ICT patients (5·2 vs. 2·1 years; P MDS, adjusting for age, frailty, comorbidity, disability, revised IPSS, TD severity, time to TD and receiving disease-modifying agents. This provides additional evidence that ICT may confer clinical benefit. © 2017 John Wiley & Sons Ltd.

  1. Modelling lecturer performance index of private university in Tulungagung by using survival analysis with multivariate adaptive regression spline

    Science.gov (United States)

    Hasyim, M.; Prastyo, D. D.

    2018-03-01

    Survival analysis performs relationship between independent variables and survival time as dependent variable. In fact, not all survival data can be recorded completely by any reasons. In such situation, the data is called censored data. Moreover, several model for survival analysis requires assumptions. One of the approaches in survival analysis is nonparametric that gives more relax assumption. In this research, the nonparametric approach that is employed is Multivariate Regression Adaptive Spline (MARS). This study is aimed to measure the performance of private university’s lecturer. The survival time in this study is duration needed by lecturer to obtain their professional certificate. The results show that research activities is a significant factor along with developing courses material, good publication in international or national journal, and activities in research collaboration.

  2. DNA-mediated adjuvant immunotherapy extends survival in two different mouse models of myeloid malignancies.

    Science.gov (United States)

    Le Pogam, Carole; Patel, Satyananda; Gorombei, Petra; Guerenne, Laura; Krief, Patricia; Omidvar, Nader; Tekin, Nilgun; Bernasconi, Elena; Sicre, Flore; Schlageter, Marie-Helene; Chopin, Martine; Noguera, Maria-Elena; West, Robert; Abu, Ansu; Mathews, Vikram; Pla, Marika; Fenaux, Pierre; Chomienne, Christine; Padua, Rose Ann

    2015-10-20

    We have previously shown that a specific promyelocytic leukemia-retinoic acid receptor alpha (PML-RARA) DNA vaccine combined with all-trans retinoic acid (ATRA) increases the number of long term survivors with enhanced immune responses in a mouse model of acute promyelocytic leukemia (APL). This study reports the efficacy of a non-specific DNA vaccine, pVAX14Flipper (pVAX14), in both APL and high risk myelodysplastic syndrome (HR-MDS) models. PVAX14 is comprised of novel immunogenic DNA sequences inserted into the pVAX1 therapeutic plasmid. APL mice treated with pVAX14 combined with ATRA had increased survival comparable to that obtained with a specific PML-RARA vaccine. Moreover, the survival advantage correlated with decreased PML-RARA transcript levels and increase in anti-RARA antibody production. In HR-MDS mice, pVAX14 significantly improved survival and reduced biomarkers of leukemic transformation such as phosphorylated mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK) 1. In both preclinical models, pVAX14 vaccine significantly increased interferon gamma (IFNγ) production, memory T-cells (memT), reduced the number of colony forming units (CFU) and increased expression of the adapter molecule signalling to NF-κB, MyD88. These results demonstrate the adjuvant properties of pVAX14 providing thus new approaches to improve clinical outcome in two different models of myeloid malignancies, which may have potential for a broader applicability in other cancers.

  3. Mistral project: identification and parameter adjustment. Theoretical part; Projet Mistral: identification et recalage des modeles. Etude theorique

    Energy Technology Data Exchange (ETDEWEB)

    Faille, D.; Codrons, B.; Gevers, M.

    1996-03-01

    This document belongs to the methodological part of the project MISTRAL, which builds a library of power plant models. The model equations are generally obtained from the first principles. The parameters are actually not always easily calculable (at least accurately) from the dimension data. We are therefore investigating the possibility of automatically adjusting the value of those parameters from experimental data. To do that, we must master the optimization algorithms and the techniques that are analyzing the model structure, like the identifiability theory. (authors). 7 refs., 1 fig., 1 append.

  4. Impact of sentinel lymphadenectomy on survival in a murine model of melanoma.

    Science.gov (United States)

    Rebhun, Robert B; Lazar, Alexander J F; Fidler, Isaiah J; Gershenwald, Jeffrey E

    2008-01-01

    Lymphatic mapping and sentinel lymph node biopsy-also termed sentinel lymphadenectomy (SL)-has become a standard of care for patients with primary invasive cutaneous melanoma. This technique has been shown to provide accurate information about the disease status of the regional lymph node basins at risk for metastasis, provide prognostic information, and provide durable regional lymph node control. The potential survival benefit afforded to patients undergoing SL is controversial. Central to this controversy is whether metastasis to regional lymph nodes occurs independent of or prior to widespread hematogenous dissemination. A related area of uncertainty is whether tumor cells residing within regional lymph nodes have increased metastatic potential. We have used a murine model of primary invasive cutaneous melanoma based on injection of B16-BL6 melanoma cells into the pinna to address two questions: (1) does SL plus wide excision of the primary tumor result in a survival advantage over wide excision alone; and (2) do melanoma cells growing within lymph nodes produce a higher incidence of hematogenous metastases than do cells growing at the primary tumor site? We found that SL significantly improved the survival of mice with small primary tumors. We found no difference in the incidence of lung metastases produced by B16-BL6 melanoma cells growing exclusively within regional lymph nodes and cells growing within the pinna.

  5. Development of a likelihood of survival scoring system for hospitalized equine neonates using generalized boosted regression modeling.

    Directory of Open Access Journals (Sweden)

    Katarzyna A Dembek

    Full Text Available BACKGROUND: Medical management of critically ill equine neonates (foals can be expensive and labor intensive. Predicting the odds of foal survival using clinical information could facilitate the decision-making process for owners and clinicians. Numerous prognostic indicators and mathematical models to predict outcome in foals have been published; however, a validated scoring method to predict survival in sick foals has not been reported. The goal of this study was to develop and validate a scoring system that can be used by clinicians to predict likelihood of survival of equine neonates based on clinical data obtained on admission. METHODS AND RESULTS: Data from 339 hospitalized foals of less than four days of age admitted to three equine hospitals were included to develop the model. Thirty seven variables including historical information, physical examination and laboratory findings were analyzed by generalized boosted regression modeling (GBM to determine which ones would be included in the survival score. Of these, six variables were retained in the final model. The weight for each variable was calculated using a generalized linear model and the probability of survival for each total score was determined. The highest (7 and the lowest (0 scores represented 97% and 3% probability of survival, respectively. Accuracy of this survival score was validated in a prospective study on data from 283 hospitalized foals from the same three hospitals. Sensitivity, specificity, positive and negative predictive values for the survival score in the prospective population were 96%, 71%, 91%, and 85%, respectively. CONCLUSIONS: The survival score developed in our study was validated in a large number of foals with a wide range of diseases and can be easily implemented using data available in most equine hospitals. GBM was a useful tool to develop the survival score. Further evaluations of this scoring system in field conditions are needed.

  6. STI571 (Gleevec) improves tumor growth delay and survival in irradiated mouse models of glioblastoma

    International Nuclear Information System (INIS)

    Geng Ling; Shinohara, Eric T.; Kim, Dong; Tan Jiahuai; Osusky, Kate; Shyr, Yu; Hallahan, Dennis E.

    2006-01-01

    Purpose: Glioblastoma multiforme (GBM) is a devastating brain neoplasm that is essentially incurable. Although radiation therapy prolongs survival, GBMs progress within areas of irradiation. Recent studies in invertebrates have shown that STI571 (Gleevec; Novartis, East Hanover, NJ) enhances the cytotoxicity of ionizing radiation. In the present study, the effectiveness of STI571 in combination with radiation was studied in mouse models of GBM. Methods and Materials: Murine GL261 and human D54 GBM cell lines formed tumors in brains and hind limbs of C57BL6 and nude mice, respectively. GL261 and D54 cells were treated with 5 μmol/L of STI571 for 1 h and/or irradiated with 3 Gy. Protein was analyzed by Western immunoblots probed with antibodies to caspase 3, cleaved caspase 3, phospho-Akt, Akt, and platelet-derived growth factor receptor (PDGFR) α and β. Tumor volumes were assessed in mice bearing GL261 or D54 tumors treated with 21 Gy administered in seven fractionated doses. Histologic sections from STI571-treated mice were stained with phospho-Akt and phospho-PDGFR β antibodies. Kaplan-Meier survival curves were used to study the response of mice bearing intracranial implants of GL261. Results: STI571 penetrated the blood-brain barrier, which resulted in a reduction in phospho-PDGFR in GBM. STI571-induced apoptosis in GBM was significantly enhanced by irradiation. STI571 combined with irradiation induced caspase 3 cleavage in GBM cells. Glioblastoma multiforme response to therapy correlated with an increase in tumor growth delay and survival when STI571 was administered in conjunction with daily irradiation. Conclusion: These findings suggest that STI571 has the potential to augment radiotherapy and thereby improve median survival

  7. Survival of viral pathogens in animal feed ingredients under transboundary shipping models

    Science.gov (United States)

    Bauermann, Fernando V.; Niederwerder, Megan C.; Singrey, Aaron; Clement, Travis; de Lima, Marcelo; Long, Craig; Patterson, Gilbert; Sheahan, Maureen A.; Stoian, Ana M. M.; Petrovan, Vlad; Jones, Cassandra K.; De Jong, Jon; Ji, Ju; Spronk, Gordon D.; Minion, Luke; Christopher-Hennings, Jane; Zimmerman, Jeff J.; Rowland, Raymond R. R.; Nelson, Eric; Sundberg, Paul; Diel, Diego G.

    2018-01-01

    The goal of this study was to evaluate survival of important viral pathogens of livestock in animal feed ingredients imported daily into the United States under simulated transboundary conditions. Eleven viruses were selected based on global significance and impact to the livestock industry, including Foot and Mouth Disease Virus (FMDV), Classical Swine Fever Virus (CSFV), African Swine Fever Virus (ASFV), Influenza A Virus of Swine (IAV-S), Pseudorabies virus (PRV), Nipah Virus (NiV), Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), Swine Vesicular Disease Virus (SVDV), Vesicular Stomatitis Virus (VSV), Porcine Circovirus Type 2 (PCV2) and Vesicular Exanthema of Swine Virus (VESV). Surrogate viruses with similar genetic and physical properties were used for 6 viruses. Surrogates belonged to the same virus families as target pathogens, and included Senecavirus A (SVA) for FMDV, Bovine Viral Diarrhea Virus (BVDV) for CSFV, Bovine Herpesvirus Type 1 (BHV-1) for PRV, Canine Distemper Virus (CDV) for NiV, Porcine Sapelovirus (PSV) for SVDV and Feline Calicivirus (FCV) for VESV. For the remaining target viruses, actual pathogens were used. Virus survival was evaluated using Trans-Pacific or Trans-Atlantic transboundary models involving representative feed ingredients, transport times and environmental conditions, with samples tested by PCR, VI and/or swine bioassay. SVA (representing FMDV), FCV (representing VESV), BHV-1 (representing PRV), PRRSV, PSV (representing SVDV), ASFV and PCV2 maintained infectivity during transport, while BVDV (representing CSFV), VSV, CDV (representing NiV) and IAV-S did not. Notably, more viruses survived in conventional soybean meal, lysine hydrochloride, choline chloride, vitamin D and pork sausage casings. These results support published data on transboundary risk of PEDV in feed, demonstrate survival of certain viruses in specific feed ingredients (“high-risk combinations”) under conditions simulating transport between

  8. Resolution of a Rank-Deficient Adjustment Model Via an Isomorphic Geometrical Setup with Tensor Structure.

    Science.gov (United States)

    1987-03-01

    holds an economical advantage. We now formulate 1. from (65) in conjunction with (57): IH]T T I TI (4 L [I R)T(I + RR ) (L*4) where the positive...sizes of the matrices to be inverted, an economical edge of the analytical formulation hecomes apparent as well. Chapter 3 contains one such matrix of...the relat ions Sthat can tie iibta i ned via the tensor vers ion of adjustment quant it ies. Alt Iihut t . ho’ ) mpu it iona I merits of the CholeskI

  9. Modeling and Predicting the EUR/USD Exchange Rate: The Role of Nonlinear Adjustments to Purchasing Power Parity

    OpenAIRE

    Jesús Crespo Cuaresma; Anna Orthofer

    2010-01-01

    Reliable medium-term forecasts are essential for forward-looking monetary policy decisionmaking. Traditionally, predictions of the exchange rate tend to be linked to the equilibrium concept implied by the purchasing power parity (PPP) theory. In particular, the traditional benchmark for exchange rate models is based on a linear adjustment of the exchange rate to the level implied by PPP. In the presence of aggregation effects, transaction costs or uncertainty, however, economic theory predict...

  10. The adjustment of global and partial dry biomass models for Pinus pinaster in the North-East of Portugal

    OpenAIRE

    Lopes, Domingos; Almeida, L.R.; Castro, João Paulo; Aranha, José

    2005-01-01

    Ecosystems net primary production quantification can be done by means of allometric equations. Carbon sequestration studies also involve the quantification of growth dry biomass, knowing the carbon percentage of dry biomass. Fieldwork complexity to collect these kind of data are often limitative for obtaining these mathematical models. Allometric equations were adjusted to estimate dry biomass of individual Pinus pinaster trees, using data from 30 trees. Statisticals form the final equatio...

  11. An estimator of the survival function based on the semi-Markov model under dependent censorship.

    Science.gov (United States)

    Lee, Seung-Yeoun; Tsai, Wei-Yann

    2005-06-01

    Lee and Wolfe (Biometrics vol. 54 pp. 1176-1178, 1998) proposed the two-stage sampling design for testing the assumption of independent censoring, which involves further follow-up of a subset of lost-to-follow-up censored subjects. They also proposed an adjusted estimator for the survivor function for a proportional hazards model under the dependent censoring model. In this paper, a new estimator for the survivor function is proposed for the semi-Markov model under the dependent censorship on the basis of the two-stage sampling data. The consistency and the asymptotic distribution of the proposed estimator are derived. The estimation procedure is illustrated with an example of lung cancer clinical trial and simulation results are reported of the mean squared errors of estimators under a proportional hazards and two different nonproportional hazards models.

  12. A chip-level modeling approach for rail span collapse and survivability analyses

    International Nuclear Information System (INIS)

    Marvis, D.G.; Alexander, D.R.; Dinger, G.L.

    1989-01-01

    A general semiautomated analysis technique has been developed for analyzing rail span collapse and survivability of VLSI microcircuits in high ionizing dose rate radiation environments. Hierarchical macrocell modeling permits analyses at the chip level and interactive graphical postprocessing provides a rapid visualization of voltage, current and power distributions over an entire VLSIC. The technique is demonstrated for a 16k C MOS/SOI SRAM and a CMOS/SOS 8-bit multiplier. The authors also present an efficient method to treat memory arrays as well as a three-dimensional integration technique to compute sapphire photoconduction from the design layout

  13. Estimation of direct effects for survival data by using the Aalen additive hazards model

    DEFF Research Database (Denmark)

    Martinussen, Torben; Vansteelandt, Stijn; Gerster, Mette

    2011-01-01

    We extend the definition of the controlled direct effect of a point exposure on a survival outcome, other than through some given, time-fixed intermediate variable, to the additive hazard scale. We propose two-stage estimators for this effect when the exposure is dichotomous and randomly assigned...... Aalen's additive regression for the event time, given exposure, intermediate variable and confounders. The second stage involves applying Aalen's additive model, given the exposure alone, to a modified stochastic process (i.e. a modification of the observed counting process based on the first...

  14. An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan

    Directory of Open Access Journals (Sweden)

    Weiner Jonathan P

    2010-01-01

    Full Text Available Abstract Background Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. Methods A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234, while those in both 2002 and 2003 were included for prospective analyses (n = 164,562. Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. Results The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster. When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Conclusions Given the

  15. An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan.

    Science.gov (United States)

    Chang, Hsien-Yen; Weiner, Jonathan P

    2010-01-18

    Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI) programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG) case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234), while those in both 2002 and 2003 were included for prospective analyses (n = 164,562). Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group) model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster). When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Given the widespread availability of claims data and the superior explanatory

  16. Siblings' Perceptions of Differential Treatment, Fairness, and Jealousy and Adolescent Adjustment: A Moderated Indirect Effects Model.

    Science.gov (United States)

    Loeser, Meghan K; Whiteman, Shawn D; McHale, Susan M

    2016-08-01

    Youth's perception of parents' differential treatment (PDT) are associated with maladjustment during adolescence. Although the direct relations between PDT and youth's maladjustment have been well established, the mechanisms underlying these associations remain unclear. We addressed this gap by examining whether sibling jealousy accounted for the links between PDT and youth's depressive symptoms, self-worth, and risky behaviors. Additionally, we examined whether youth's perceptions of fairness regarding their treatment as well as the gender constellation of the dyad moderated these indirect relations (i.e., moderated-indirect effects). Participants were first- and second-born adolescent siblings ( M = 15.96, SD = .72 years for older siblings, M = 13.48, SD = 1.02 years for younger siblings) and their parents from 197 working and middle class European American families. Data were collected via home interviews. A series of Conditional Process Analyses revealed significant indirect effects of PDT through sibling jealousy to all three adjustment outcomes. Furthermore, perceptions of fairness moderated the relations between PDT and jealousy, such that the indirect effects were only significant at low (-1 SD ) and average levels of fairness. At high levels of fairness (+1 SD ) there was no association between PDT, jealousy, and youth adjustment. Taken together, results indicate that youth and parents would benefit from engaging in clear communication regarding the reasoning for the occurrence of differential treatment, likely maximizing youth and parent perceptions of that treatment as being fair, and in turn mitigating sibling jealousy and maladjustment.

  17. Siblings’ Perceptions of Differential Treatment, Fairness, and Jealousy and Adolescent Adjustment: A Moderated Indirect Effects Model

    Science.gov (United States)

    Loeser, Meghan K.; Whiteman, Shawn D.; McHale, Susan M.

    2016-01-01

    Youth's perception of parents’ differential treatment (PDT) are associated with maladjustment during adolescence. Although the direct relations between PDT and youth's maladjustment have been well established, the mechanisms underlying these associations remain unclear. We addressed this gap by examining whether sibling jealousy accounted for the links between PDT and youth's depressive symptoms, self-worth, and risky behaviors. Additionally, we examined whether youth's perceptions of fairness regarding their treatment as well as the gender constellation of the dyad moderated these indirect relations (i.e., moderated-indirect effects). Participants were first- and second-born adolescent siblings (M = 15.96, SD = .72 years for older siblings, M = 13.48, SD = 1.02 years for younger siblings) and their parents from 197 working and middle class European American families. Data were collected via home interviews. A series of Conditional Process Analyses revealed significant indirect effects of PDT through sibling jealousy to all three adjustment outcomes. Furthermore, perceptions of fairness moderated the relations between PDT and jealousy, such that the indirect effects were only significant at low (−1 SD) and average levels of fairness. At high levels of fairness (+1 SD) there was no association between PDT, jealousy, and youth adjustment. Taken together, results indicate that youth and parents would benefit from engaging in clear communication regarding the reasoning for the occurrence of differential treatment, likely maximizing youth and parent perceptions of that treatment as being fair, and in turn mitigating sibling jealousy and maladjustment. PMID:27867295

  18. The synthetic parasite-derived peptide GK1 increases survival in a preclinical mouse melanoma model.

    Science.gov (United States)

    Pérez-Torres, Armando; Vera-Aguilera, Jesús; Hernaiz-Leonardo, Juan Carlos; Moreno-Aguilera, Eduardo; Monteverde-Suarez, Diego; Vera-Aguilera, Carlos; Estrada-Bárcenas, Daniel

    2013-11-01

    The therapeutic efficacy of a synthetic parasite-derived peptide GK1, an immune response booster, was evaluated in a mouse melanoma model. This melanoma model correlates with human stage IIb melanoma, which is treated with wide surgical excision; a parallel study employing a surgical treatment was carried out as an instructive goal. C57BL/6 mice were injected subcutaneously in the flank with 2×10(5) B16-F10 murine melanoma cells. When the tumors reached 20 mm3, mice were separated into two different groups; the GK1 group, treated weekly with peritumoral injections of GK1 (10 μg/100 μL of sterile saline solution) and the control group, treated weekly with an antiseptic peritumoral injection of 100 μL of sterile saline solution without further intervention. All mice were monitored daily for clinical appearance, tumor size, and survival. Surgical treatment was performed in parallel when the tumor size was 20 mm3 (group A), 500 mm3 (group B), and >500 mm3 (group C). The GK1 peptide effectively increased the mean survival time by 9.05 days, corresponding to an increase of 42.58%, and significantly delayed tumor growth from day 3 to 12 of treatment. In addition, tumor necrosis was significantly increased (pcancers remains to be determined, and surgical removal remains a challenge for any new experimental treatment of melanoma in mouse models.

  19. Modelling survival and connectivity of Mnemiopsis leidyi in the south-western North Sea and Scheldt estuaries

    DEFF Research Database (Denmark)

    van der Molen, J.; van Beek, J.; Augustine, Starrlight

    2015-01-01

    Three different models were applied to study the reproduction, survival and dispersal of Mnemiopsis leidyi in the Scheldt estuaries and the southern North Sea: a high-resolution particle tracking model with passive particles, a low-resolution particle tracking model with a reproduction model coup...

  20. Improving breast cancer survival analysis through competition-based multidimensional modeling.

    Directory of Open Access Journals (Sweden)

    Erhan Bilal

    Full Text Available Breast cancer is the most common malignancy in women and is responsible for hundreds of thousands of deaths annually. As with most cancers, it is a heterogeneous disease and different breast cancer subtypes are treated differently. Understanding the difference in prognosis for breast cancer based on its molecular and phenotypic features is one avenue for improving treatment by matching the proper treatment with molecular subtypes of the disease. In this work, we employed a competition-based approach to modeling breast cancer prognosis using large datasets containing genomic and clinical information and an online real-time leaderboard program used to speed feedback to the modeling team and to encourage each modeler to work towards achieving a higher ranked submission. We find that machine learning methods combined with molecular features selected based on expert prior knowledge can improve survival predictions compared to current best-in-class methodologies and that ensemble models trained across multiple user submissions systematically outperform individual models within the ensemble. We also find that model scores are highly consistent across multiple independent evaluations. This study serves as the pilot phase of a much larger competition open to the whole research community, with the goal of understanding general strategies for model optimization using clinical and molecular profiling data and providing an objective, transparent system for assessing prognostic models.

  1. Differentiation of Self and Dyadic Adjustment in Couple Relationships: A Dyadic Analysis Using the Actor-Partner Interdependence Model.

    Science.gov (United States)

    Lampis, Jessica; Cataudella, Stefania; Agus, Mirian; Busonera, Alessandra; Skowron, Elizabeth A

    2018-06-10

    Bowen's multigenerational theory provides an account of how the internalization of experiences within the family of origin promotes development of the ability to maintain a distinct self whilst also making intimate connections with others. Differentiated people can maintain their I-position in intimate relationships. They can remain calm in conflictual relationships, resolve relational problems effectively, and reach compromises. Fusion with others, emotional cut-off, and emotional reactivity instead are common reactions to relational stress in undifferentiated people. Emotional reactivity is the tendency to react to stressors with irrational and intense emotional arousal. Fusion with others is an excessive emotional involvement in significant relationships, whilst emotional cut-off is the tendency to manage relationship anxiety through physical and emotional distance. This study is based on Bowen's theory, starting from the assumption that dyadic adjustment can be affected both by a member's differentiation of self (actor effect) and by his or her partner's differentiation of self (partner effect). We used the Actor-Partner Interdependence Model to study the relationship between differentiation of self and dyadic adjustment in a convenience sample of 137 heterosexual Italian couples (nonindependent, dyadic data). The couples completed the Differentiation of Self Inventory and the Dyadic Adjustment Scale. Men's dyadic adjustment depended only on their personal I-position, whereas women's dyadic adjustment was affected by their personal I-position and emotional cut-off as well as by their partner's I-position and emotional cut-off. The empirical and clinical implications of the results are discussed. © 2018 Family Process Institute.

  2. Selective histone deacetylase 6 inhibition prolongs survival in a lethal two-hit model.

    Science.gov (United States)

    Cheng, Xin; Liu, Zhengcai; Liu, Baoling; Zhao, Ting; Li, Yongqing; Alam, Hasan B

    2015-07-01

    Hemorrhagic shock (HS) followed by a subsequent insult ("second hit") often initiates an exaggerated systemic inflammatory response and multiple organ failure. We have previously demonstrated that valproic acid, a pan histone deacetylase inhibitor, could improve survival in a rodent "two-hit" model. In the present study, our goal was to determine whether selective inhibition of histone deacetylase 6 with Tubastatin A (Tub-A) could prolong survival in a two-hit model where HS was followed by sepsis from cecal ligation and puncture (CLP). C57Bl/6J mice were subjected to sublethal HS (30% blood loss) and then randomly divided into two groups (n = 13 per group) such as Tub-A group (treatment) and vehicle (VEH) group (control). The Tub-A group was given an intraperitoneal injection of Tub-A (70 mg/kg) dissolved in dimethyl sulfoxide (DMSO). The VEH group was injected with DMSO (1 μl/g body weight). After 24 h, all mice were subjected CLP followed immediately by another dose of Tub-A or DMSO. Survival was monitored for 10 d. In a parallel study, peritoneal irrigation fluid and liver tissue from Tub-A- or DMSO-treated mice were collected 3 h after CLP. Enzyme-linked immunosorbent assay was performed to quantify activity of the myeloperoxidase and concentrations of tumor necrosis factor-alpha (TNF-α) and interleukin 6 (IL-6) in the peritoneal irrigation fluid. RNA was isolated from the liver tissue, and real-time polymerase chain reaction was performed to measure relative messenger RNA levels of TNF-α and IL-6. Treatment with Tub-A significantly improved survival compared with that of the control (69.2% versus 15.4%). In addition, Tub-A significantly suppressed myeloperoxidase activity (169.9 ± 8.4 ng/mL versus 70.4 ± 17.4 ng/mL; P hit model. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Novel bifunctional anthracycline and nitrosourea chemotherapy for human bladder cancer: analysis in a preclinical survival model.

    Science.gov (United States)

    Glaves, D; Murray, M K; Raghavan, D

    1996-08-01

    A hybrid drug [N-2-chloroethylnitrosoureidodaunorubicin (AD312)] that combines structural and functional features of both anthracyclines and nitrosoureas was evaluated in a preclinical survival model of human bladder cancer. To measure the therapeutic activity of AD312, UCRU-BL13 transitional cell carcinoma cells were grown as xenografts in nude mice, and tumor growth rates were compared after i.v. administration of the drug at three dose levels. AD312 treatment at 45 and 60 mg/kg achieved 7-10-fold inhibition of tumor growth and increased host survival by 156 and 249%, respectively. Doses of 60 mg/kg showed optimal therapeutic efficacy, with sustained tumor growth inhibition, an over 2-fold increase in life span, and 40% of mice tumor free ("cured") at 120 days. Tumors were unresponsive to maximum tolerated doses of doxorubicin, a standard anthracycline used as a single agent and in combination therapies for bladder cancer. 1,3-Bis-[2-chloroethyl]-1-nitrosourea was used as a control for the apparently enhanced response of human tumors in murine hosts to nitrosoureas. 1, 3-Bis-[2-chloroethyl]-1-nitrosourea administered in three injections of 20 mg/kg did not cure mice but temporarily inhibited tumor growth by 70% and prolonged survival by 55%; its activity in this model suggests that it may be included in the repertoire of alkylating agents currently used for treatment of bladder cancers. AD312 showed increased antitumor activity with less toxicity than doxorubicin, and its bifunctional properties provide the opportunity for simultaneous treatment of individual cancer cells with two cytotoxic modalities as well as treatment of heterogeneous populations typical of bladder cancers. This novel cytotoxic drug cured doxorubicin-refractory disease and should be investigated for the clinical management of bladder cancer.

  4. Conditionally replicating adenovirus expressing TIMP2 increases survival in a mouse model of disseminated ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Sherry W Yang

    Full Text Available Ovarian cancer remains difficult to treat mainly due to presentation of the disease at an advanced stage. Conditionally-replicating adenoviruses (CRAds are promising anti-cancer agents that selectively kill the tumor cells. The present study evaluated the efficacy of a novel CRAd (Ad5/3-CXCR4-TIMP2 containing the CXCR4 promoter for selective viral replication in cancer cells together with TIMP2 as a therapeutic transgene, targeting the matrix metalloproteases (MMPs in a murine orthotopic model of disseminated ovarian cancer. An orthotopic model of ovarian cancer was established in athymic nude mice by intraperitonal injection of the human ovarian cancer cell line, SKOV3-Luc, expressing luciferase. Upon confirmation of peritoneal dissemination of the cells by non-invasive imaging, mice were randomly divided into four treatment groups: PBS, Ad-ΔE1-TIMP2, Ad5/3-CXCR4, and Ad5/3-CXCR4-TIMP2. All mice were imaged weekly to monitor tumor growth and were sacrificed upon reaching any of the predefined endpoints, including high tumor burden and significant weight loss along with clinical evidence of pain and distress. Survival analysis was performed using the Log-rank test. The median survival for the PBS cohort was 33 days; for Ad-ΔE1-TIMP2, 39 days; for Ad5/3-CXCR4, 52.5 days; and for Ad5/3-CXCR4-TIMP2, 63 days. The TIMP2-armed CRAd delayed tumor growth and significantly increased survival when compared to the unarmed CRAd. This therapeutic effect was confirmed to be mediated through inhibition of MMP9. Results of the in vivo study support the translational potential of Ad5/3-CXCR4-TIMP2 for treatment of human patients with advanced ovarian cancer.

  5. Rethinking plant functional types in Earth System Models: pan-tropical analysis of tree survival across environmental gradients

    Science.gov (United States)

    Johnson, D. J.; Needham, J.; Xu, C.; Davies, S. J.; Bunyavejchewin, S.; Giardina, C. P.; Condit, R.; Cordell, S.; Litton, C. M.; Hubbell, S.; Kassim, A. R. B.; Shawn, L. K. Y.; Nasardin, M. B.; Ong, P.; Ostertag, R.; Sack, L.; Tan, S. K. S.; Yap, S.; McDowell, N. G.; McMahon, S.

    2016-12-01

    Terrestrial carbon cycling is a function of the growth and survival of trees. Current model representations of tree growth and survival at a global scale rely on coarse plant functional traits that are parameterized very generally. In view of the large biodiversity in the tropical forests, it is important that we account for the functional diversity in order to better predict tropical forest responses to future climate changes. Several next generation Earth System Models are moving towards a size-structured, trait-based approach to modelling vegetation globally, but the challenge of which and how many traits are necessary to capture forest complexity remains. Additionally, the challenge of collecting sufficient trait data to describe the vast species richness of tropical forests is enormous. We propose a more fundamental approach to these problems by characterizing forests by their patterns of survival. We expect our approach to distill real-world tree survival into a reasonable number of functional types. Using 10 large-area tropical forest plots that span geographic, edaphic and climatic gradients, we model tree survival as a function of tree size for hundreds of species. We found surprisingly few categories of size-survival functions emerge. This indicates some fundamental strategies at play across diverse forests to constrain the range of possible size-survival functions. Initial cluster analysis indicates that four to eight functional forms are necessary to describe variation in size-survival relations. Temporal variation in size-survival functions can be related to local environmental variation, allowing us to parameterize how demographically similar groups of species respond to perturbations in the ecosystem. We believe this methodology will yield a synthetic approach to classifying forest systems that will greatly reduce uncertainty and complexity in global vegetation models.

  6. A survival model for fractionated radiotherapy with an application to prostate cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zaider, Marco [Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY (United States)]. E-mail: Zaiderm@mskcc.org; Zelefsky, Michael J.; Leibel, Steven A. [Department of Radiation Oncology, Memorial Sloan-Kettering Cancer Center, New York, NY (United States); Hanin, Leonid G. [Department of Mathematics, Idaho State University, Pocatello, ID (United States); Tsodikov, Alexander D.; Yakovlev, Andrei Y. [Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT (United States)

    2001-10-01

    This paper explores the applicability of a mechanistic survival model, based on the distribution of clonogens surviving a course of fractionated radiation therapy, to clinical data on patients with prostate cancer. The study was carried out using data on 1100 patients with clinically localized prostate cancer who were treated with three-dimensional conformal radiation therapy. The patients were stratified by radiation dose (group 1: <67.5 Gy; group 2: 67.5-72.5 Gy; group 3: 72.5-77.5 Gy; group 4: 77.5-87.5 Gy) and prognosis category (favourable, intermediate and unfavourable as defined by pre-treatment PSA and Gleason score). A relapse was recorded when tumour recurrence was diagnosed or when three successive prostate specific antigen (PSA) elevations were observed from a post-treatment nadir PSA level. PSA relapse-free survival was used as the primary end point. The model, which is based on an iterated Yule process, is specified in terms of three parameters: the mean number of tumour clonogens that survive the treatment, the mean of the progression time of post-treatment tumour development and its standard deviation. The model parameters were estimated by the maximum likelihood method. The fact that the proposed model provides an excellent description both of the survivor function and of the hazard rate is prima facie evidence of the validity of the model because closeness of the two survivor functions (empirical and model-based) does not generally imply closeness of the corresponding hazard rates. The estimated cure probabilities for the favourable group are 0.80, 0.74 and 0.87 (for dose groups 1-3, respectively); for the intermediate group: 0.25, 0.51, 0.58 and 0.78 (for dose groups 1-4, respectively) and for the unfavourable group: 0.0, 0.27, 0.33 and 0.64 (for dose groups 1-4, respectively). The distribution of progression time to tumour relapse was found to be independent of prognosis group but dependent on dose. As the dose increases the mean progression

  7. Risk adjustment model of credit life insurance using a genetic algorithm

    Science.gov (United States)

    Saputra, A.; Sukono; Rusyaman, E.

    2018-03-01

    In managing the risk of credit life insurance, insurance company should acknowledge the character of the risks to predict future losses. Risk characteristics can be learned in a claim distribution model. There are two standard approaches in designing the distribution model of claims over the insurance period i.e, collective risk model and individual risk model. In the collective risk model, the claim arises when risk occurs is called individual claim, accumulation of individual claim during a period of insurance is called an aggregate claim. The aggregate claim model may be formed by large model and a number of individual claims. How the measurement of insurance risk with the premium model approach and whether this approach is appropriate for estimating the potential losses occur in the future. In order to solve the problem Genetic Algorithm with Roulette Wheel Selection is used.

  8. Real time adjustment of slow changing flow components in distributed urban runoff models

    DEFF Research Database (Denmark)

    Borup, Morten; Grum, M.; Mikkelsen, Peter Steen

    2011-01-01

    In many urban runoff systems infiltrating water contributes with a substantial part of the total inflow and therefore most urban runoff modelling packages include hydrological models for simulating the infiltrating inflow. This paper presents a method for deterministic updating of the hydrological...... improvements for regular simulations as well as up to 10 hour forecasts. The updating method reduces the impact of non-representative precipitation estimates as well as model structural errors and leads to better overall modelling results....

  9. Alternative Payment Models Should Risk-Adjust for Conversion Total Hip Arthroplasty: A Propensity Score-Matched Study.

    Science.gov (United States)

    McLawhorn, Alexander S; Schairer, William W; Schwarzkopf, Ran; Halsey, David A; Iorio, Richard; Padgett, Douglas E

    2017-12-06

    For Medicare beneficiaries, hospital reimbursement for nonrevision hip arthroplasty is anchored to either diagnosis-related group code 469 or 470. Under alternative payment models, reimbursement for care episodes is not further risk-adjusted. This study's purpose was to compare outcomes of primary total hip arthroplasty (THA) vs conversion THA to explore the rationale for risk adjustment for conversion procedures. All primary and conversion THAs from 2007 to 2014, excluding acute hip fractures and cancer patients, were identified in the National Surgical Quality Improvement Program database. Conversion and primary THA patients were matched 1:1 using propensity scores, based on preoperative covariates. Multivariable logistic regressions evaluated associations between conversion THA and 30-day outcomes. A total of 2018 conversions were matched to 2018 primaries. There were no differences in preoperative covariates. Conversions had longer operative times (148 vs 95 minutes, P reimbursement models shift toward bundled payment paradigms, conversion THA appears to be a procedure for which risk adjustment is appropriate. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. A non-Gaussian generalisation of the Airline model for robust Seasonal Adjustment

    NARCIS (Netherlands)

    Aston, J.; Koopman, S.J.

    2006-01-01

    In their seminal book Time Series Analysis: Forecasting and Control, Box and Jenkins (1976) introduce the Airline model, which is still routinely used for the modelling of economic seasonal time series. The Airline model is for a differenced time series (in levels and seasons) and constitutes a

  11. THE INSTANTANEOUS SPEED OF ADJUSTMENT ASSUMPTION AND STABILITY OF ECONOMIC-MODELS

    NARCIS (Netherlands)

    SCHOONBEEK, L

    In order to simplify stability analysis of an economic model one can assume that one of the model variables moves infinitely fast towards equilibrium, given the values of the other slower variables. We present conditions such that stability of the simplified model implies, or is implied by,

  12. Modeling the effect of temperature on survival rate of Listeria monocytogenes in yogurt.

    Science.gov (United States)

    Szczawiński, J; Szczawińska, M E; Łobacz, A; Jackowska-Tracz, A

    2016-01-01

    The aim of the study was to (i) evaluate the behavior of Listeria monocytogenes in a commercially produced yogurt, (ii) determine the survival/inactivation rates of L. monocytogenes during cold storage of yogurt and (iii) to generate primary and secondary mathematical models to predict the behavior of these bacteria during storage at different temperatures. The samples of yogurt were inoculated with the mixture of three L. monocytogenes strains and stored at 3, 6, 9, 12 and 15°C for 16 days. The number of listeriae was determined after 0, 1, 2, 3, 5, 7, 9, 12, 14 and 16 days of storage. From each sample a series of decimal dilutions were prepared and plated onto ALOA agar (agar for Listeria according to Ottaviani and Agosti). It was found that applied temperature and storage time significantly influenced the survival rate of listeriae (pbacteria was found in the samples stored at 6°C (D-10 value = 243.9 h), whereas the highest reduction in the number of the bacteria was observed in the samples stored at 15°C (D-10 value = 87.0 h). The number of L. monocytogenes was correlated with the pH value of the samples (pyogurt stored under temperature range from 3 to 15°C, however, the polynomial model gave a better fit to the experimental data.

  13. Risk-adjusted econometric model to estimate postoperative costs: an additional instrument for monitoring performance after major lung resection.

    Science.gov (United States)

    Brunelli, Alessandro; Salati, Michele; Refai, Majed; Xiumé, Francesco; Rocco, Gaetano; Sabbatini, Armando

    2007-09-01

    The objectives of this study were to develop a risk-adjusted model to estimate individual postoperative costs after major lung resection and to use it for internal economic audit. Variable and fixed hospital costs were collected for 679 consecutive patients who underwent major lung resection from January 2000 through October 2006 at our unit. Several preoperative variables were used to develop a risk-adjusted econometric model from all patients operated on during the period 2000 through 2003 by a stepwise multiple regression analysis (validated by bootstrap). The model was then used to estimate the postoperative costs in the patients operated on during the 3 subsequent periods (years 2004, 2005, and 2006). Observed and predicted costs were then compared within each period by the Wilcoxon signed rank test. Multiple regression and bootstrap analysis yielded the following model predicting postoperative cost: 11,078 + 1340.3X (age > 70 years) + 1927.8X cardiac comorbidity - 95X ppoFEV1%. No differences between predicted and observed costs were noted in the first 2 periods analyzed (year 2004, $6188.40 vs $6241.40, P = .3; year 2005, $6308.60 vs $6483.60, P = .4), whereas in the most recent period (2006) observed costs were significantly lower than the predicted ones ($3457.30 vs $6162.70, P model may be used as a methodologic template for economic audit in our specialty and complement more traditional outcome measures in the assessment of performance.

  14. Estimation of emission adjustments from the application of four-dimensional data assimilation to photochemical air quality modeling

    International Nuclear Information System (INIS)

    Mendoza-Dominguez, A.; Russell, A.G.

    2001-01-01

    Four-dimensional data assimilation applied to photochemical air quality modeling is used to suggest adjustments to the emissions inventory of the Atlanta, Georgia metropolitan area. In this approach, a three-dimensional air quality model, coupled with direct sensitivity analysis, develops spatially and temporally varying concentration and sensitivity fields that account for chemical and physical processing, and receptor analysis is used to adjust source strengths. Proposed changes to domain-wide NO x , volatile organic compounds (VOCs) and CO emissions from anthropogenic sources and for VOC emissions from biogenic sources were estimated, as well as modifications to sources based on their spatial location (urban vs. rural areas). In general, domain-wide anthropogenic VOC emissions were increased approximately two times their base case level to best match observations, domain-wide anthropogenic NO x and biogenic VOC emissions (BEIS2 estimates) remained close to their base case value and domain-wide CO emissions were decreased. Adjustments for anthropogenic NO x emissions increased their level of uncertainty when adjustments were computed for mobile and area sources (or urban and rural sources) separately, due in part to the poor spatial resolution of the observation field of nitrogen-containing species. Estimated changes to CO emissions also suffer from poor spatial resolution of the measurements. Results suggest that rural anthropogenic VOC emissions appear to be severely underpredicted. The FDDA approach was also used to investigate the speciation profiles of VOC emissions, and results warrant revision of these profiles. In general, the results obtained here are consistent with what are viewed as the current deficiencies in emissions inventories as derived by other top-down techniques, such as tunnel studies and analysis of ambient measurements. (Author)

  15. Sodium caseinate induces increased survival in leukaemic mouse J774 model.

    Science.gov (United States)

    Córdova-Galaviz, Yolanda; Ledesma-Martínez, Edgar; Aguíñiga-Sánchez, Itzen; Soldevila-Melgarejo, Gloria; Soto-Cruz, Isabel; Weiss-Steider, Benny; Santiago-Osorio, Edelmiro

    2014-01-01

    Acute myeloid leukaemia is a neoplastic disease of haematopoietic stem cells. Although there have been recent advances regarding its treatment, mortality remains high. Consequently, therapeutic alternatives continue to be explored. In the present report, we present evidence that sodium caseinate (CasNa), a salt of the principal protein in milk, may possess important anti-leukaemic properties. J774 leukaemia macrophage-like cells were cultured with CasNa and proliferation, viability and differentiation were evaluated. These cells were also inoculated into BALB/c mice as a model of leukemia. We demonstrated that CasNa inhibits the in vitro proliferation and reduces viability of J774 cells, and leads to increased survival in vivo in a leukaemic mouse model. These data indicate that CasNa may be useful in leukaemia therapy. Copyright © 2014 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  16. Free Base Lysine Increases Survival and Reduces Metastasis in Prostate Cancer Model.

    Science.gov (United States)

    Ibrahim-Hashim, Arig; Wojtkowiak, Jonathan W; de Lourdes Coelho Ribeiro, Maria; Estrella, Veronica; Bailey, Kate M; Cornnell, Heather H; Gatenby, Robert A; Gillies, Robert J

    2011-11-19

    Malignant tumor cells typically metabolize glucose anaerobically to lactic acid even under normal oxygen tension, a phenomenon called aerobic glycolysis or the Warburg effect. This results in increased acid production and the acidification of the extracellular microenvironment in solid tumors. H + ions tend to flow along concentration gradients into peritumoral normal tissue causing extracellular matrix degradation and increased tumor cell motility thus promoting invasion and metastasis. We have shown that reducing this acidity with sodium bicarbonate buffer decreases the metastatic fitness of circulating tumor cells in prostate cancer and other cancer models. Mathematical models of the tumor-host dynamics predicted that buffers with a pka around 7 will be more effective in reducing intra- and peri-tumoral acidosis and, thus, and possibly more effective in inhibiting tumor metastasis than sodium bicarbonate which has a pKa around 6. Here we test this prediction the efficacy of free base lysine; a non-bicarbonate/non-volatile buffer with a higher pKa (~10), on prostate tumor metastases model. Oxygen consumption and acid production rate of PC3M prostate cancer cells and normal prostate cells were determined using the Seahorse Extracellular Flux (XF-96) analyzer. In vivo effect of 200 mM lysine started four days prior to inoculation on inhibition of metastasis was examined in PC3M-LUC-C6 prostate cancer model using SCID mice. Metastases were followed by bioluminescence imaging. PC3M prostate cancer cells are highly acidic in comparison to a normal prostate cell line indicating that reduction of intra- and perit-tumoral acidosis should inhibit metastases formation. In vivo administration of 200 mM free base lysine increased survival and reduced metastasis. PC3M prostate cancer cells are highly glycolytic and produce large amounts of acid when compared to normal prostate cells. Administration of non-volatile buffer decreased growth of metastases and improved survival

  17. Opportunities for Improving Army Modeling and Simulation Development: Making Fundamental Adjustments and Borrowing Commercial Business Practices

    National Research Council Canada - National Science Library

    Lee, John

    2000-01-01

    .... This paper briefly explores project management principles, leadership theory, and commercial business practices, suggesting improvements to the Army's modeling and simulation development process...

  18. Dynamic Modeling of Adjustable-Speed Pumped Storage Hydropower Plant: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Muljadi, E.; Singh, M.; Gevorgian, V.; Mohanpurkar, M.; Havsapian, R.; Koritarov, V.

    2015-04-06

    Hydropower is the largest producer of renewable energy in the U.S. More than 60% of the total renewable generation comes from hydropower. There is also approximately 22 GW of pumped storage hydropower (PSH). Conventional PSH uses a synchronous generator, and thus the rotational speed is constant at synchronous speed. This work details a hydrodynamic model and generator/power converter dynamic model. The optimization of the hydrodynamic model is executed by the hydro-turbine controller, and the electrical output real/reactive power is controlled by the power converter. All essential controllers to perform grid-interface functions and provide ancillary services are included in the model.

  19. Nutritional intra-amniotic therapy increases survival in a rabbit model of fetal growth restriction

    Science.gov (United States)

    Illa, Miriam; Pla, Laura; Zamora, Monica; Crispi, Fatima; Gratacos, Eduard

    2018-01-01

    Objective To evaluate the perinatal effects of a prenatal therapy based on intra-amniotic nutritional supplementation in a rabbit model of intrauterine growth restriction (IUGR). Methods IUGR was surgically induced in pregnant rabbits at gestational day 25 by ligating 40–50% of uteroplacental vessels of each gestational sac. At the same time, modified-parenteral nutrition solution (containing glucose, amino acids and electrolytes) was injected into the amniotic sac of nearly half of the IUGR fetuses (IUGR-T group n = 106), whereas sham injections were performed in the rest of fetuses (IUGR group n = 118). A control group without IUGR induction but sham injection was also included (n = 115). Five days after the ligation procedure, a cesarean section was performed to evaluate fetal cardiac function, survival and birth weight. Results Survival was significantly improved in the IUGR fetuses that were treated with intra-amniotic nutritional supplementation as compared to non-treated IUGR animals (survival rate: controls 71% vs. IUGR 44% p = 0.003 and IUGR-T 63% vs. IUGR 44% p = 0.02), whereas, birth weight (controls mean 43g ± SD 9 vs. IUGR 36g ± SD 9 vs. IUGR-T 35g ± SD 8, p = 0.001) and fetal cardiac function were similar among the IUGR groups. Conclusion Intra-amniotic injection of a modified-parenteral nutrient solution appears to be a promising therapy for reducing mortality among IUGR. These results provide an opportunity to develop new intra-amniotic nutritional strategies to reach the fetus by bypassing the placental insufficiency. PMID:29466434

  20. SURVIVAL OF MICROORGANISMS FROM MODERN PROBIOTICS IN MODEL CONDITIONS OF THE INTESTINE

    Directory of Open Access Journals (Sweden)

    Kabluchko TV

    2017-03-01

    Full Text Available Introduction. The staye of intestinal microflora affects the work of the whole organism. When composition of normal ibtestine microflora changes, its restoration is required. In our days a wide variety of probiotic drugs are available on the market which can be used to solve this problem. Most bacteria having probiotic properties represent the families Lactobacillus and Bifidobacterium, which have poor resistance to acidic content of the stomach and toxic effects of bile salts. Various studies have clearly shown that in a person with normal acidic and bile secretion, the lactobacilli and bifidobacteria are not detected after the passage through the duodenum, i.e., they perish before reaching the small intestines. In this study we compared the survival of different microorganisms which are contained in 9 probiotic drugs in a model of gastric and intestinal environments. Material and methods. In the laboratory of SI: “Mechnikov Institute Microbiology and Immunology, National Ukrainian Academy Medical Sciences" the in vitro experiments have been evaluated to test the ability of different probiotic bacteria which were contained in 9 probiotic drugs to survive the impact of the model environment of the stomach and duodenum. Bacillus coagulans persistence was evaluated under impact of simulated environment of the stomach and duodenum, it also was assessed by the quantity of CFU by incubation on culture medium. The following were studied: Lactobacillus acidophilus, Lactobacillus rhamnosus, Lactobacillus reuteri, Lactobacillus casei, Lactobacillus plantarum, Lactobacillus bulgaricus, Bifidobacterium bifidum, Bifidobacterium longum , Bifidobacterium breve, Bifidobacterium infantis, Bifidobacterium animalis subsp. Lactis BB-12, Saccharomyces boulardii, Bacillus coagulans, Bacillus clausii, Enterococcus faecium. Microorganisms were incubated for 3 hours in a model environment of the stomach (pepsin 3 g / l, hydrochloric acid of 160 mmol / l, pH 2

  1. Models of quality-adjusted life years when health varies over time

    DEFF Research Database (Denmark)

    Hansen, Kristian Schultz; Østerdal, Lars Peter Raahave

    2006-01-01

    Qualityadjusted life year (QALY) models are widely used for economic evaluation in the health care sector. In the first part of the paper, we establish an overview of QALY models where health varies over time and provide a theoretical analysis of model identification and parameter estimation from...... time tradeoff (TTO) and standard gamble (SG) scores. We investigate deterministic and probabilistic models and consider five different families of discounting functions in all. The second part of the paper discusses four issues recurrently debated in the literature. This discussion includes questioning...... of these two can be used to disentangle risk aversion from discounting. We find that caution must be taken when drawing conclusions from models with chronic health states to situations where health varies over time. One notable difference is that in the former case, risk aversion may be indistinguishable from...

  2. Linear identification and model adjustment of a PEM fuel cell stack

    Energy Technology Data Exchange (ETDEWEB)

    Kunusch, C; Puleston, P F; More, J J [LEICI, Departamento de Electrotecnia, Universidad Nacional de La Plata, calle 1 esq. 47 s/n, 1900 La Plata (Argentina); Consejo de Investigaciones Cientificas y Tecnicas (CONICET) (Argentina); Husar, A [Institut de Robotica i Informatica Industrial (CSIC-UPC), c/ Llorens i Artigas 4-6, 08028 Barcelona (Spain); Mayosky, M A [LEICI, Departamento de Electrotecnia, Universidad Nacional de La Plata, calle 1 esq. 47 s/n, 1900 La Plata (Argentina); Comision de Investigaciones Cientificas (CIC), Provincia de Buenos Aires (Argentina)

    2008-07-15

    In the context of fuel cell stack control a mayor challenge is modeling the interdependence of various complex subsystem dynamics. In many cases, the states interaction is usually modeled through several look-up tables, decision blocks and piecewise continuous functions. Many internal variables are inaccessible for measurement and cannot be used in control algorithms. To make significant contributions in this area, it is necessary to develop reliable models for control and design purposes. In this paper, a linear model based on experimental identification of a 7-cell stack was developed. The procedure followed to obtain a linear model of the system consisted in performing spectroscopy tests of four different single-input single-output subsystems. The considered inputs for the tests were the stack current and the cathode oxygen flow rate, while the measured outputs were the stack voltage and the cathode total pressure. The resulting model can be used either for model-based control design or for on-line analysis and errors detection. (author)

  3. A joint logistic regression and covariate-adjusted continuous-time Markov chain model.

    Science.gov (United States)

    Rubin, Maria Laura; Chan, Wenyaw; Yamal, Jose-Miguel; Robertson, Claudia Sue

    2017-12-10

    The use of longitudinal measurements to predict a categorical outcome is an increasingly common goal in research studies. Joint models are commonly used to describe two or more models simultaneously by considering the correlated nature of their outcomes and the random error present in the longitudinal measurements. However, there is limited research on joint models with longitudinal predictors and categorical cross-sectional outcomes. Perhaps the most challenging task is how to model the longitudinal predictor process such that it represents the true biological mechanism that dictates the association with the categorical response. We propose a joint logistic regression and Markov chain model to describe a binary cross-sectional response, where the unobserved transition rates of a two-state continuous-time Markov chain are included as covariates. We use the method of maximum likelihood to estimate the parameters of our model. In a simulation study, coverage probabilities of about 95%, standard deviations close to standard errors, and low biases for the parameter values show that our estimation method is adequate. We apply the proposed joint model to a dataset of patients with traumatic brain injury to describe and predict a 6-month outcome based on physiological data collected post-injury and admission characteristics. Our analysis indicates that the information provided by physiological changes over time may help improve prediction of long-term functional status of these severely ill subjects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  4. A model of survival following pre-hospital cardiac arrest based on the Victorian Ambulance Cardiac Arrest Register.

    Science.gov (United States)

    Fridman, Masha; Barnes, Vanessa; Whyman, Andrew; Currell, Alex; Bernard, Stephen; Walker, Tony; Smith, Karen L

    2007-11-01

    This study describes the epidemiology of sudden cardiac arrest patients in Victoria, Australia, as captured via the Victorian Ambulance Cardiac Arrest Register (VACAR). We used the VACAR data to construct a new model of out-of-hospital cardiac arrest (OHCA), which was specified in accordance with observed trends. All cases of cardiac arrest in Victoria that were attended by Victorian ambulance services during the period of 2002-2005. Overall survival to hospital discharge was 3.8% among 18,827 cases of OHCA. Survival was 15.7% among 1726 bystander witnessed, adult cardiac arrests of presumed cardiac aetiology, presenting in ventricular fibrillation or ventricular tachycardia (VF/VT), where resuscitation was attempted. In multivariate logistic regression analysis, bystander CPR, cardiac arrest (CA) location, response time, age and sex were predictors of VF/VT, which, in turn, was a strong predictor of survival. The same factors that affected VF/VT made an additional contribution to survival. However, for bystander CPR, CA location and response time this additional contribution was limited to VF/VT patients only. There was no detectable association between survival and age younger than 60 years or response time over 15min. The new model accounts for relationships among predictors of survival. These relationships indicate that interventions such as reduced response times and bystander CPR act in multiple ways to improve survival.

  5. Model for breast cancer survival: relative prognostic roles of axillary nodal status, TNM stage, estrogen receptor concentration, and tumor necrosis.

    Science.gov (United States)

    Shek, L L; Godolphin, W

    1988-10-01

    The independent prognostic effects of certain clinical and pathological variables measured at the time of primary diagnosis were assessed with Cox multivariate regression analysis. The 859 patients with primary breast cancer, on which the proportional hazards model was based, had a median follow-up of 60 months. Axillary nodal status (categorized as N0, N1-3 or N4+) was the most significant and independent factor in overall survival, but inclusion of TNM stage, estrogen receptor (ER) concentration and tumor necrosis significantly improved survival predictions. Predictions made with the model showed striking subset survival differences within stage: 5-year survival from 36% (N4+, loge[ER] = 0, marked necrosis) to 96% (N0, loge[ER] = 6, no necrosis) in TNM I, and from 0 to 70% for the same categories in TNM IV. Results of the model were used to classify patients into four distinct risk groups according to a derived hazard index. An 8-fold variation in survival was seen with the highest (greater than 3) to lowest index values (less than 1). Each hazard index level included patients with varied combinations of the above factors, but could be considered to denote the same degree of risk of breast cancer mortality. A model with ER concentration, nodal status, and tumor necrosis was found to best predict survival after disease recurrence in 369 patients, thus confirming the enduring biological significance of these factors.

  6. Cisplatin Resistant Spheroids Model Clinically Relevant Survival Mechanisms in Ovarian Tumors.

    Directory of Open Access Journals (Sweden)

    Winyoo Chowanadisai

    Full Text Available The majority of ovarian tumors eventually recur in a drug resistant form. Using cisplatin sensitive and resistant cell lines assembled into 3D spheroids we profiled gene expression and identified candidate mechanisms and biological pathways associated with cisplatin resistance. OVCAR-8 human ovarian carcinoma cells were exposed to sub-lethal concentrations of cisplatin to create a matched cisplatin-resistant cell line, OVCAR-8R. Genome-wide gene expression profiling of sensitive and resistant ovarian cancer spheroids identified 3,331 significantly differentially expressed probesets coding for 3,139 distinct protein-coding genes (Fc >2, FDR < 0.05 (S2 Table. Despite significant expression changes in some transporters including MDR1, cisplatin resistance was not associated with differences in intracellular cisplatin concentration. Cisplatin resistant cells were significantly enriched for a mesenchymal gene expression signature. OVCAR-8R resistance derived gene sets were significantly more biased to patients with shorter survival. From the most differentially expressed genes, we derived a 17-gene expression signature that identifies ovarian cancer patients with shorter overall survival in three independent datasets. We propose that the use of cisplatin resistant cell lines in 3D spheroid models is a viable approach to gain insight into resistance mechanisms relevant to ovarian tumors in patients. Our data support the emerging concept that ovarian cancers can acquire drug resistance through an epithelial-to-mesenchymal transition.

  7. Neuron-specific antioxidant OXR1 extends survival of a mouse model of amyotrophic lateral sclerosis.

    Science.gov (United States)

    Liu, Kevin X; Edwards, Benjamin; Lee, Sheena; Finelli, Mattéa J; Davies, Ben; Davies, Kay E; Oliver, Peter L

    2015-05-01

    Amyotrophic lateral sclerosis is a devastating neurodegenerative disorder characterized by the progressive loss of spinal motor neurons. While the aetiological mechanisms underlying the disease remain poorly understood, oxidative stress is a central component of amyotrophic lateral sclerosis and contributes to motor neuron injury. Recently, oxidation resistance 1 (OXR1) has emerged as a critical regulator of neuronal survival in response to oxidative stress, and is upregulated in the spinal cord of patients with amyotrophic lateral sclerosis. Here, we tested the hypothesis that OXR1 is a key neuroprotective factor during amyotrophic lateral sclerosis pathogenesis by crossing a new transgenic mouse line that overexpresses OXR1 in neurons with the SOD1(G93A) mouse model of amyotrophic lateral sclerosis. Interestingly, we report that overexpression of OXR1 significantly extends survival, improves motor deficits, and delays pathology in the spinal cord and in muscles of SOD1(G93A) mice. Furthermore, we find that overexpression of OXR1 in neurons significantly delays non-cell-autonomous neuroinflammatory response, classic complement system activation, and STAT3 activation through transcriptomic analysis of spinal cords of SOD1(G93A) mice. Taken together, these data identify OXR1 as the first neuron-specific antioxidant modulator of pathogenesis and disease progression in SOD1-mediated amyotrophic lateral sclerosis, and suggest that OXR1 may serve as a novel target for future therapeutic strategies. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

  8. Method for widespread microRNA-155 inhibition prolongs survival in ALS-model mice

    Science.gov (United States)

    Koval, Erica D.; Shaner, Carey; Zhang, Peter; du Maine, Xavier; Fischer, Kimberlee; Tay, Jia; Chau, B. Nelson; Wu, Gregory F.; Miller, Timothy M.

    2013-01-01

    microRNAs (miRNAs) are dysregulated in a variety of disease states, suggesting that this newly discovered class of gene expression repressors may be viable therapeutic targets. A microarray of miRNA changes in ALS-model superoxide dismutase 1 (SOD1)G93A rodents identified 12 miRNAs as significantly changed. Six miRNAs tested in human ALS tissues were confirmed increased. Specifically, miR-155 was increased 5-fold in mice and 2-fold in human spinal cords. To test miRNA inhibition in the central nervous system (CNS) as a potential novel therapeutic, we developed oligonucleotide-based miRNA inhibitors (anti-miRs) that could inhibit miRNAs throughout the CNS and in the periphery. Anti-miR-155 caused global derepression of targets in peritoneal macrophages and, following intraventricular delivery, demonstrated widespread functional distribution in the brain and spinal cord. After treating SOD1G93A mice with anti-miR-155, we significantly extended survival by 10 days and disease duration by 15 days (38%) while a scrambled control anti-miR did not significantly improve survival or disease duration. Therefore, antisense oligonucleotides may be used to successfully inhibit miRNAs throughout the brain and spinal cord, and miR-155 is a promising new therapeutic target for human ALS. PMID:23740943

  9. Bayesian Analysis for Dynamic Generalized Linear Latent Model with Application to Tree Survival Rate

    Directory of Open Access Journals (Sweden)

    Yu-sheng Cheng

    2014-01-01

    Full Text Available Logistic regression model is the most popular regression technique, available for modeling categorical data especially for dichotomous variables. Classic logistic regression model is typically used to interpret relationship between response variables and explanatory variables. However, in real applications, most data sets are collected in follow-up, which leads to the temporal correlation among the data. In order to characterize the different variables correlations, a new method about the latent variables is introduced in this study. At the same time, the latent variables about AR (1 model are used to depict time dependence. In the framework of Bayesian analysis, parameters estimates and statistical inferences are carried out via Gibbs sampler with Metropolis-Hastings (MH algorithm. Model comparison, based on the Bayes factor, and forecasting/smoothing of the survival rate of the tree are established. A simulation study is conducted to assess the performance of the proposed method and a pika data set is analyzed to illustrate the real application. Since Bayes factor approaches vary significantly, efficiency tests have been performed in order to decide which solution provides a better tool for the analysis of real relational data sets.

  10. Modeling the effect of temperature on survival rate of Salmonella Enteritidis in yogurt.

    Science.gov (United States)

    Szczawiński, J; Szczawińska, M E; Łobacz, A; Jackowska-Tracz, A

    2014-01-01

    The aim of the study was to determine the inactivation rates of Salmonella Enteritidis in commercially produced yogurt and to generate primary and secondary mathematical models to predict the behaviour of these bacteria during storage at different temperatures. The samples were inoculated with the mixture of three S. Enteritidis strains and stored at 5 degrees C, 10 degrees C, 15 degrees C, 20 degrees C and 25 degrees C for 24 h. The number of salmonellae was determined every two hours. It was found that the number of bacteria decreased linearly with storage time in all samples. Storage temperature and pH of yogurt significantly influenced survival rate of S. Enteritidis (p bacteria was the most dynamic. The natural logarithm of mean inactivation rates of Salmonella calculated from primary model was fitted to two secondary models: linear and polynomial. Equations obtained from both secondary models can be applied as a tool for prediction of inactivation rate of Salmonella in yogurt stored under temperature range from 5 to 25 degrees C; however, polynomial model gave the better fit to the experimental data.

  11. The combined geodetic network adjusted on the reference ellipsoid – a comparison of three functional models for GNSS observations

    Directory of Open Access Journals (Sweden)

    Kadaj Roman

    2016-12-01

    Full Text Available The adjustment problem of the so-called combined (hybrid, integrated network created with GNSS vectors and terrestrial observations has been the subject of many theoretical and applied works. The network adjustment in various mathematical spaces was considered: in the Cartesian geocentric system on a reference ellipsoid and on a mapping plane. For practical reasons, it often takes a geodetic coordinate system associated with the reference ellipsoid. In this case, the Cartesian GNSS vectors are converted, for example, into geodesic parameters (azimuth and length on the ellipsoid, but the simple form of converted pseudo-observations are the direct differences of the geodetic coordinates. Unfortunately, such an approach may be essentially distorted by a systematic error resulting from the position error of the GNSS vector, before its projection on the ellipsoid surface. In this paper, an analysis of the impact of this error on the determined measures of geometric ellipsoid elements, including the differences of geodetic coordinates or geodesic parameters is presented. Assuming that the adjustment of a combined network on the ellipsoid shows that the optimal functional approach in relation to the satellite observation, is to create the observational equations directly for the original GNSS Cartesian vector components, writing them directly as a function of the geodetic coordinates (in numerical applications, we use the linearized forms of observational equations with explicitly specified coefficients. While retaining the original character of the Cartesian vector, one avoids any systematic errors that may occur in the conversion of the original GNSS vectors to ellipsoid elements, for example the vector of the geodesic parameters. The problem is theoretically developed and numerically tested. An example of the adjustment of a subnet loaded from the database of reference stations of the ASG-EUPOS system was considered for the preferred functional

  12. Elasto-plastic hardening models adjustment to ferritic, austenitic and austenoferritic Rebar

    International Nuclear Information System (INIS)

    Hortigóna, B.; Gallardo, J.M.; Nieto-García, E.J.; López, J.A.

    2017-01-01

    The elastoplastic behaviour of steel used for structural member fabrication has received attention to facilitate a mechanical-resistant design. New Zealand and South African standards have adopted various theoretical approaches to describe such behaviour in stainless steels. With respect to the building industry, describing the tensile behaviour of steel rebar used to produce reinforced concrete structures is of interest. Differences compared with the homogenous material described in the above mentioned standards and related literatures are discussed in this paper. Specifically, the presence of ribs and the TEMPCORE® technology used to produce carbon steel rebar may alter the elastoplastic model. Carbon steel rebar is shown to fit a Hollomon model giving hardening exponent values on the order of 0.17. Austenitic stainless steel rebar behaviour is better described using a modified Rasmussen model with a free fitted exponent of 6. Duplex stainless steel shows a poor fit to any previous model. [es

  13. Modeling and simulation of M/M/c queuing pharmacy system with adjustable parameters

    Science.gov (United States)

    Rashida, A. R.; Fadzli, Mohammad; Ibrahim, Safwati; Goh, Siti Rohana

    2016-02-01

    This paper studies a discrete event simulation (DES) as a computer based modelling that imitates a real system of pharmacy unit. M/M/c queuing theo is used to model and analyse the characteristic of queuing system at the pharmacy unit of Hospital Tuanku Fauziah, Kangar in Perlis, Malaysia. The input of this model is based on statistical data collected for 20 working days in June 2014. Currently, patient waiting time of pharmacy unit is more than 15 minutes. The actual operation of the pharmacy unit is a mixed queuing server with M/M/2 queuing model where the pharmacist is referred as the server parameters. DES approach and ProModel simulation software is used to simulate the queuing model and to propose the improvement for queuing system at this pharmacy system. Waiting time for each server is analysed and found out that Counter 3 and 4 has the highest waiting time which is 16.98 and 16.73 minutes. Three scenarios; M/M/3, M/M/4 and M/M/5 are simulated and waiting time for actual queuing model and experimental queuing model are compared. The simulation results show that by adding the server (pharmacist), it will reduce patient waiting time to a reasonable improvement. Almost 50% average patient waiting time is reduced when one pharmacist is added to the counter. However, it is not necessary to fully utilize all counters because eventhough M/M/4 and M/M/5 produced more reduction in patient waiting time, but it is ineffective since Counter 5 is rarely used.

  14. Model-based Adjustment of Droplet Characteristic for 3D Electronic Printing

    Directory of Open Access Journals (Sweden)

    Lin Na

    2017-01-01

    Full Text Available The major challenge in 3D electronic printing is the print resolution and accuracy. In this paper, a typical mode - lumped element modeling method (LEM - is adopted to simulate the droplet jetting characteristic. This modeling method can quickly get the droplet velocity and volume with a high accuracy. Experimental results show that LEM has a simpler structure with the sufficient simulation and prediction accuracy.

  15. A comparative study of generalized linear mixed modelling and artificial neural network approach for the joint modelling of survival and incidence of Dengue patients in Sri Lanka

    Science.gov (United States)

    Hapugoda, J. C.; Sooriyarachchi, M. R.

    2017-09-01

    Survival time of patients with a disease and the incidence of that particular disease (count) is frequently observed in medical studies with the data of a clustered nature. In many cases, though, the survival times and the count can be correlated in a way that, diseases that occur rarely could have shorter survival times or vice versa. Due to this fact, joint modelling of these two variables will provide interesting and certainly improved results than modelling these separately. Authors have previously proposed a methodology using Generalized Linear Mixed Models (GLMM) by joining the Discrete Time Hazard model with the Poisson Regression model to jointly model survival and count model. As Aritificial Neural Network (ANN) has become a most powerful computational tool to model complex non-linear systems, it was proposed to develop a new joint model of survival and count of Dengue patients of Sri Lanka by using that approach. Thus, the objective of this study is to develop a model using ANN approach and compare the results with the previously developed GLMM model. As the response variables are continuous in nature, Generalized Regression Neural Network (GRNN) approach was adopted to model the data. To compare the model fit, measures such as root mean square error (RMSE), absolute mean error (AME) and correlation coefficient (R) were used. The measures indicate the GRNN model fits the data better than the GLMM model.

  16. A special case of reduced rank models for identification and modelling of time varying effects in survival analysis.

    Science.gov (United States)

    Perperoglou, Aris

    2016-12-10

    Flexible survival models are in need when modelling data from long term follow-up studies. In many cases, the assumption of proportionality imposed by a Cox model will not be valid. Instead, a model that can identify time varying effects of fixed covariates can be used. Although there are several approaches that deal with this problem, it is not always straightforward how to choose which covariates should be modelled having time varying effects and which not. At the same time, it is up to the researcher to define appropriate time functions that describe the dynamic pattern of the effects. In this work, we suggest a model that can deal with both fixed and time varying effects and uses simple hypotheses tests to distinguish which covariates do have dynamic effects. The model is an extension of the parsimonious reduced rank model of rank 1. As such, the number of parameters is kept low, and thus, a flexible set of time functions, such as b-splines, can be used. The basic theory is illustrated along with an efficient fitting algorithm. The proposed method is applied to a dataset of breast cancer patients and compared with a multivariate fractional polynomials approach for modelling time-varying effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  17. A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

    Science.gov (United States)

    Chai, Hua; Li, Zi-Na; Meng, De-Yu; Xia, Liang-Yong; Liang, Yong

    2017-10-12

    Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such information in the censored data, a semi-supervised learning framework (Cox-AFT model) combined with Cox proportional hazard (Cox) and accelerated failure time (AFT) model was used in cancer research, which has better performance than the single Cox or AFT model. This method, however, is easily affected by noise. To alleviate this problem, in this paper we combine the Cox-AFT model with self-paced learning (SPL) method to more effectively employ the information in the censored data in a self-learning way. SPL is a kind of reliable and stable learning mechanism, which is recently proposed for simulating the human learning process to help the AFT model automatically identify and include samples of high confidence into training, minimizing interference from high noise. Utilizing the SPL method produces two direct advantages: (1) The utilization of censored data is further promoted; (2) the noise delivered to the model is greatly decreased. The experimental results demonstrate the effectiveness of the proposed model compared to the traditional Cox-AFT model.

  18. Nest survival modelling using a multi-species approach in forests managed for timber and biofuel feedstock

    Science.gov (United States)

    Loman, Zachary G.; Monroe, Adrian; Riffell, Samuel K.; Miller, Darren A.; Vilella, Francisco; Wheat, Bradley R.; Rush, Scott A.; Martin, James A.

    2018-01-01

    Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA.We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.Synthesis and applications. Community models represent a viable

  19. Detection of superior genotype of fatty acid synthase in Korean native cattle by an environment-adjusted statistical model

    Directory of Open Access Journals (Sweden)

    Jea-Young Lee

    2017-06-01

    Full Text Available Objective This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score of Hanwoo. Methods To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms were excluded from the model. Results The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.

  20. Adjusting particle-size distributions to account for aggregation in tephra-deposit model forecasts

    Science.gov (United States)

    Mastin, Larry G.; Van Eaton, Alexa; Durant, A.J.

    2016-01-01

    Volcanic ash transport and dispersion (VATD) models are used to forecast tephra deposition during volcanic eruptions. Model accuracy is limited by the fact that fine-ash aggregates (clumps into clusters), thus altering patterns of deposition. In most models this is accounted for by ad hoc changes to model input, representing fine ash as aggregates with density ρagg, and a log-normal size distribution with median μagg and standard deviation σagg. Optimal values may vary between eruptions. To test the variance, we used the Ash3d tephra model to simulate four deposits: 18 May 1980 Mount St. Helens; 16–17 September 1992 Crater Peak (Mount Spurr); 17 June 1996 Ruapehu; and 23 March 2009 Mount Redoubt. In 192 simulations, we systematically varied μagg and σagg, holding ρagg constant at 600 kg m−3. We evaluated the fit using three indices that compare modeled versus measured (1) mass load at sample locations; (2) mass load versus distance along the dispersal axis; and (3) isomass area. For all deposits, under these inputs, the best-fit value of μagg ranged narrowly between  ∼  2.3 and 2.7φ (0.20–0.15 mm), despite large variations in erupted mass (0.25–50 Tg), plume height (8.5–25 km), mass fraction of fine ( discrete process that is insensitive to eruptive style or magnitude. This result offers the potential for a simple, computationally efficient parameterization scheme for use in operational model forecasts. Further research may indicate whether this narrow range also reflects physical constraints on processes in the evolving cloud.

  1. Experimental Robot Model Adjustments Based on Force–Torque Sensor Information

    Directory of Open Access Journals (Sweden)

    Santiago Martinez

    2018-03-01

    Full Text Available The computational complexity of humanoid robot balance control is reduced through the application of simplified kinematics and dynamics models. However, these simplifications lead to the introduction of errors that add to other inherent electro-mechanic inaccuracies and affect the robotic system. Linear control systems deal with these inaccuracies if they operate around a specific working point but are less precise if they do not. This work presents a model improvement based on the Linear Inverted Pendulum Model (LIPM to be applied in a non-linear control system. The aim is to minimize the control error and reduce robot oscillations for multiple working points. The new model, named the Dynamic LIPM (DLIPM, is used to plan the robot behavior with respect to changes in the balance status denoted by the zero moment point (ZMP. Thanks to the use of information from force–torque sensors, an experimental procedure has been applied to characterize the inaccuracies and introduce them into the new model. The experiments consist of balance perturbations similar to those of push-recovery trials, in which step-shaped ZMP variations are produced. The results show that the responses of the robot with respect to balance perturbations are more precise and the mechanical oscillations are reduced without comprising robot dynamics.

  2. A phased transition to a market adjustment of the pseudo model of Russian economy

    Directory of Open Access Journals (Sweden)

    N. Komkov

    2015-01-01

    Full Text Available We consider a phased reform of the economic model of Russia. In less than one century, Russia was in the extreme conditions of the model economy: the developed socialism (1917 and perfect capitalism (1991. Within each of them there was the instability of socio-economic development: economic recovery alternated recession and huge reserves of natural resources and to develop and use of land is not always effective. At each extremity of the selection was based largely on the current political aims and attitudes formed by various social groups. Russia achieved the economic situation and the prevailing socio-economic model of many subjected to fair criticism. To improve it proposes a phased approach to reform, when the main focus is on "how" to move to a new state. The approach is based on consideration of the scenario approach to the reform of the basic components of the economic model that involves the formation of a better scenario analysis and evaluation of the expert community the degree of closeness of planned versions of the model national development objectives of the country.

  3. Adjustment and Characterization of an Original Model of Chronic Ischemic Heart Failure in Pig

    Directory of Open Access Journals (Sweden)

    Laurent Barandon

    2010-01-01

    Full Text Available We present and characterize an original experimental model to create a chronic ischemic heart failure in pig. Two ameroid constrictors were placed around the LAD and the circumflex artery. Two months after surgery, pigs presented a poor LV function associated with a severe mitral valve insufficiency. Echocardiography analysis showed substantial anomalies in radial and circumferential deformations, both on the anterior and lateral surface of the heart. These anomalies in function were coupled with anomalies of perfusion observed in echocardiography after injection of contrast medium. No demonstration of myocardial infarction was observed with histological analysis. Our findings suggest that we were able to create and to stabilize a chronic ischemic heart failure model in the pig. This model represents a useful tool for the development of new medical or surgical treatment in this field.

  4. Psychosocial adjustment of children with chronic illness: an evaluation of three models.

    Science.gov (United States)

    Gartstein, M A; Short, A D; Vannatta, K; Noll, R B

    1999-06-01

    This study was designed to assess social, emotional, and behavioral functioning of children with chronic illness and to evaluate three models addressing the impact of chronic illness on psychosocial functioning: discrete disease, noncategorical, and mixed. Families of children with cancer, sickle cell disease, hemophilia, and juvenile rheumatoid arthritis participated, along with families of classroom comparison peers without a chronic illness who had the closest date of birth and were of the same race and gender (COMPs). Mothers, fathers, and children provided information regarding current functioning of the child with chronic illness or the COMP child. Child Behavior Checklist and Children's Depression Inventory scores were examined. Results provided support for the noncategorical model. Thus, the mixed model evaluated in this study requires modifications before its effectiveness as a classification system can be demonstrated.

  5. A statistical adjustment approach for climate projections of snow conditions in mountain regions using energy balance land surface models

    Science.gov (United States)

    Verfaillie, Deborah; Déqué, Michel; Morin, Samuel; Lafaysse, Matthieu

    2017-04-01

    Projections of future climate change have been increasingly called for lately, as the reality of climate change has been gradually accepted and societies and governments have started to plan upcoming mitigation and adaptation policies. In mountain regions such as the Alps or the Pyrenees, where winter tourism and hydropower production are large contributors to the regional revenue, particular attention is brought to current and future snow availability. The question of the vulnerability of mountain ecosystems as well as the occurrence of climate-related hazards such as avalanches and debris-flows is also under consideration. In order to generate projections of snow conditions, however, downscaling global climate models (GCMs) by using regional climate models (RCMs) is not sufficient to capture the fine-scale processes and thresholds at play. In particular, the altitudinal resolution matters, since the phase of precipitation is mainly controlled by the temperature which is altitude-dependent. Simulations from GCMs and RCMs moreover suffer from biases compared to local observations, due to their rather coarse spatial and altitudinal resolution, and often provide outputs at too coarse time resolution to drive impact models. RCM simulations must therefore be adjusted using empirical-statistical downscaling and error correction methods, before they can be used to drive specific models such as energy balance land surface models. In this study, time series of hourly temperature, precipitation, wind speed, humidity, and short- and longwave radiation were generated over the Pyrenees and the French Alps for the period 1950-2100, by using a new approach (named ADAMONT for ADjustment of RCM outputs to MOuNTain regions) based on quantile mapping applied to daily data, followed by time disaggregation accounting for weather patterns selection. We first introduce a thorough evaluation of the method using using model runs from the ALADIN RCM driven by a global reanalysis over the

  6. Adjustment of cast metal post/cores modeled with different acrylic resins

    OpenAIRE

    Gusmão, João Milton Rocha; Pereira, Renato Piai; Alves, Guilhermino Oliveira; Pithon, Matheus Melo; Moreira, David Costa

    2016-01-01

    Aim: Evaluate the performance of four commercially available chemically-activated acrylic resins (CAARs) by measuring the level of displacement of the cores following casting. Materials and Methods: Two devices were constructed to model the cores based on a natural tooth. Forty post/cores were modeled, 10 in each of the following CAARs: Duralay (Reliance Dental, Illinois, USA), Pattern Resin (GC, Tokyo, Japan), Dencrilay (Dencril, Sao Paulo, Brazil), and Jet (Clássico, Sao Paulo, Brazil). Two...

  7. The Linear Quadratic Adjustment Cost Model and the Demand for Labour

    DEFF Research Database (Denmark)

    Engsted, Tom; Haldrup, Niels

    1994-01-01

    Der udvikles en ny metode til estimation og test af den lineære kvadratiske tilpasningsomkostningsmodel når de underliggende tidsserier er ikke-stationære, og metoden anvendes til modellering af arbejdskraftefterspørgslen i danske industrisektorer.......Der udvikles en ny metode til estimation og test af den lineære kvadratiske tilpasningsomkostningsmodel når de underliggende tidsserier er ikke-stationære, og metoden anvendes til modellering af arbejdskraftefterspørgslen i danske industrisektorer....

  8. End-Tidal CO2-Guided Chest Compression Delivery Improves Survival in a Neonatal Asphyxial Cardiac Arrest Model.

    Science.gov (United States)

    Hamrick, Justin T; Hamrick, Jennifer L; Bhalala, Utpal; Armstrong, Jillian S; Lee, Jeong-Hoo; Kulikowicz, Ewa; Lee, Jennifer K; Kudchadkar, Sapna R; Koehler, Raymond C; Hunt, Elizabeth A; Shaffner, Donald H

    2017-11-01

    To determine whether end-tidal CO2-guided chest compression delivery improves survival over standard cardiopulmonary resuscitation after prolonged asphyxial arrest. Preclinical randomized controlled study. University animal research laboratory. 1-2-week-old swine. After undergoing a 20-minute asphyxial arrest, animals received either standard or end-tidal CO2-guided cardiopulmonary resuscitation. In the standard group, chest compression delivery was optimized by video and verbal feedback to maintain the rate, depth, and release within published guidelines. In the end-tidal CO2-guided group, chest compression rate and depth were adjusted to obtain a maximal end-tidal CO2 level without other feedback. Cardiopulmonary resuscitation included 10 minutes of basic life support followed by advanced life support for 10 minutes or until return of spontaneous circulation. Mean end-tidal CO2 at 10 minutes of cardiopulmonary resuscitation was 34 ± 8 torr in the end-tidal CO2 group (n = 14) and 19 ± 9 torr in the standard group (n = 14; p = 0.0001). The return of spontaneous circulation rate was 7 of 14 (50%) in the end-tidal CO2 group and 2 of 14 (14%) in the standard group (p = 0.04). The chest compression rate averaged 143 ± 10/min in the end-tidal CO2 group and 102 ± 2/min in the standard group (p tidal CO2-guided chest compression delivery. The response of the relaxation arterial pressure and cerebral perfusion pressure to the initial epinephrine administration was greater in the end-tidal CO2 group than in the standard group (p = 0.01 and p = 0.03, respectively). The prevalence of resuscitation-related injuries was similar between groups. End-tidal CO2-guided chest compression delivery is an effective resuscitation method that improves early survival after prolonged asphyxial arrest in this neonatal piglet model. Optimizing end-tidal CO2 levels during cardiopulmonary resuscitation required that chest compression delivery rate exceed current guidelines

  9. Modelling of the process of micromycetus survival in fruit and berry syrups

    Directory of Open Access Journals (Sweden)

    L. Osipova

    2017-06-01

    Full Text Available In order to develop methods for preserving fruit and berry syrup, which exclude the use of high-temperature sterilization and preservatives, the survival of spores of micromycetes (B. nivea molds in model media with different concentration of food osmotically active substances (sucrose, ethyl alcohol, citric acid at a certain concentration of lethal effects on microorganisms. It has been established that model media (juice based syrups from blueberries with a mass content of 4 % and 6 % alcohol, 50 % sucrose, 1 % and 2 % titrated acids, have a lethal effect on spores of B. nivea molds. The regression equation is obtained expressing the dependence of the amount of spores of B. nivea molds on the concentration of sucrose, acid, alcohol and the storage time of syrups. The form of the dependence and direction of the connection between the variables is established – a negative linear regression, which is expressed in the uniform decrease of the function. The estimation of quality of the received regression model is defined. The deviations of the calculated data from the data of the initial set are calculated. The proposed model has sufficient reliability, since the regression function is defined, interpreted and justified, and the estimation of the accuracy of the regression analysis meets the requirements.

  10. Repatriation Adjustment: Literature Review

    Directory of Open Access Journals (Sweden)

    Gamze Arman

    2009-12-01

    Full Text Available Expatriation is a widely studied area of research in work and organizational psychology. After expatriates accomplish their missions in host countries, they return to their countries and this process is called repatriation. Adjustment constitutes a crucial part in repatriation research. In the present literature review, research about repatriation adjustment was reviewed with the aim of defining the whole picture in this phenomenon. Present research was classified on the basis of a theoretical model of repatriation adjustment. Basic frame consisted of antecedents, adjustment, outcomes as main variables and personal characteristics/coping strategies and organizational strategies as moderating variables.

  11. Regression modeling strategies with applications to linear models, logistic and ordinal regression, and survival analysis

    CERN Document Server

    Harrell , Jr , Frank E

    2015-01-01

    This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for fitting nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap.  The reader will gain a keen understanding of predictive accuracy, and the harm of categorizing continuous predictors or outcomes.  This text realistically...

  12. Effect of Treatment Education Based on the Roy Adaptation Model on Adjustment of Hemodialysis Patients.

    Science.gov (United States)

    Kacaroglu Vicdan, Ayse; Gulseven Karabacak, Bilgi

    2016-01-01

    The Roy Adaptation Model examines the individual in 4 fields: physiological mode, self-concept mode, role function mode, and interdependence mode. Hemodialysis treatment is associated with the Roy Adaptation Model as it involves fields that might be needed by the individual with chronic renal disease. This research was conducted as randomized controlled experiment with the aim of determining the effect of the education given in accordance with the Roy Adaptation Model on physiological, psychological, and social adaptation of individuals undergoing hemodialysis treatment. This was a random controlled experimental study. The study was conducted at a dialysis center in Konya-Aksehir in Turkey between July 1 and December 31, 2012. The sample was composed of 82 individuals-41 experimental and 41 control. In the second interview, there was a decrease in the systolic blood pressures and body weights of the experimental group, an increase in the scores of functional performance and self-respect, and a decrease in the scores of psychosocial adaptation. In the control group, on the other hand, there was a decrease in the scores of self-respect and an increase in the scores of psychosocial adaptation. The 2 groups were compared in terms of adaptation variables and a difference was determined on behalf of the experimental group. The training that was provided and evaluated for individuals receiving hemodialysis according to 4 modes of the Roy Adaptation Model increased physical, psychological, and social adaptation.

  13. A Unified Model Exploring Parenting Practices as Mediators of Marital Conflict and Children's Adjustment

    Science.gov (United States)

    Coln, Kristen L.; Jordan, Sara S.; Mercer, Sterett H.

    2013-01-01

    We examined positive and negative parenting practices and psychological control as mediators of the relations between constructive and destructive marital conflict and children's internalizing and externalizing problems in a unified model. Married mothers of 121 children between the ages of 6 and 12 completed questionnaires measuring marital…

  14. Single-incision laparoscopic surgery in a survival animal model using a transabdominal magnetic anchoring system.

    Science.gov (United States)

    Cho, Yong Beom; Park, Chan Ho; Kim, Hee Cheol; Yun, Seong Hyeon; Lee, Woo Yong; Chun, Ho-Kyung

    2011-12-01

    Though single-incision laparoscopic surgery (SILS) can reduce operative scarring and facilitates postoperative recovery, it does have some limitations, such as reduction in instrument working, difficulty in triangulation, and collision of instruments. To overcome these limitations, development of new instruments is needed. The aim of this study is to evaluate the feasibility and safety of a magnetic anchoring system in performing SILS ileocecectomy. Experiments were performed in a living dog model. Five dogs (26.3-29.2 kg) underwent ileocecectomy using a multichannel single port (OCTO port; Darim, Seoul, Korea). The port was inserted at the umbilicus and maintained a CO(2) pneumoperitoneum. Two magnet-fixated vascular clips were attached to the colon using an endoclip applicator, and it was held together across the abdominal wall by using an external handheld magnet. The cecum was then retracted in an upward direction by moving the external handheld magnet, and the mesocolon was dissected with Ultracision(®). Extracorporeal functional end-to-end anastomosis was done using a linear stapler. All animals survived during the observational period of 2 weeks, and then re-exploration was performed under general anesthesia for evaluation of intra-abdominal healing and complications. Mean operation time was 70 min (range 55-100 min), with each subsequent case taking less time. The magnetic anchoring system was effective in achieving adequate exposure in all cases. All animals survived and convalesced normally without evidence of clinical complication during the observation period. At re-exploration, all anastomoses were completely healed and there were no complications such as abscess, bleeding or organ injury. SILS ileocecectomy using a magnetic anchoring system was safe and effective in a dog model. The development of magnetic anchoring systems may be beneficial for overcoming the limitations of SILS.

  15. Comparison of hypertabastic survival model with other unimodal hazard rate functions using a goodness-of-fit test.

    Science.gov (United States)

    Tahir, M Ramzan; Tran, Quang X; Nikulin, Mikhail S

    2017-05-30

    We studied the problem of testing a hypothesized distribution in survival regression models when the data is right censored and survival times are influenced by covariates. A modified chi-squared type test, known as Nikulin-Rao-Robson statistic, is applied for the comparison of accelerated failure time models. This statistic is used to test the goodness-of-fit for hypertabastic survival model and four other unimodal hazard rate functions. The results of simulation study showed that the hypertabastic distribution can be used as an alternative to log-logistic and log-normal distribution. In statistical modeling, because of its flexible shape of hazard functions, this distribution can also be used as a competitor of Birnbaum-Saunders and inverse Gaussian distributions. The results for the real data application are shown. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. Angle-adjustable density field formulation for the modeling of crystalline microstructure

    Science.gov (United States)

    Wang, Zi-Le; Liu, Zhirong; Huang, Zhi-Feng

    2018-05-01

    A continuum density field formulation with particle-scale resolution is constructed to simultaneously incorporate the orientation dependence of interparticle interactions and the rotational invariance of the system, a fundamental but challenging issue in modeling the structure and dynamics of a broad range of material systems across variable scales. This generalized phase field crystal-type approach is based upon the complete expansion of particle direct correlation functions and the concept of isotropic tensors. Through applications to the modeling of various two- and three-dimensional crystalline structures, our study demonstrates the capability of bond-angle control in this continuum field theory and its effects on the emergence of ordered phases, and provides a systematic way of performing tunable angle analyses for crystalline microstructures.

  17. Increased survival rate by local release of diclofenac in a murine model of recurrent oral carcinoma

    Directory of Open Access Journals (Sweden)

    Will OM

    2016-10-01

    Full Text Available Olga Maria Will,1,* Nicolai Purcz,2,* Athena Chalaris,3 Carola Heneweer,4,5 Susann Boretius,1 Larissa Purcz,2 Lila Nikkola,6 Nureddin Ashammakhi,6 Holger Kalthoff,7 Claus-Christian Glüer,1 Jörg Wiltfang,2 Yahya Açil,2 Sanjay Tiwari1 1Section Biomedical Imaging, Clinic for Radiology and Neuroradiology, MOIN CC, 2Department of Oral and Maxillofacial Surgery, University Hospital Schleswig-Holstein, 3Institute of Biochemistry, Christian-Albrechts-Universität zu Kiel, 4Clinic for Radiology and Neuroradiology, University Hospital Schleswig-Holstein, Kiel, 5Institute for Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany; 6Department of Biomedical Engineering, Tampere University of Technology, Tampere, Finland; 7Institute for Experimental Cancer Research, University Hospital Schleswig-Holstein, Kiel, Germany *These authors contributed equally to this work Abstract: Despite aggressive treatment with radiation and combination chemotherapy following tumor resection, the 5-year survival rate for patients with head and neck cancer is at best only 50%. In this study, we examined the therapeutic potential of localized release of diclofenac from electrospun nanofibers generated from poly(d,l-lactide-co-glycolide polymer. Diclofenac was chosen since anti-inflammatory agents that inhibit cyclooxygenase have shown great potential in their ability to directly inhibit tumor growth as well as suppress inflammation-mediated tumor growth. A mouse resection model of oral carcinoma was developed by establishing tumor growth in the oral cavity by ultrasound-guided injection of 1 million SCC-9 cells in the floor of the mouth. Following resection, mice were allocated into four groups with the following treatment: 1 no treatment, 2 implanted scaffolds without diclofenac, 3 implanted scaffolds loaded with diclofenac, and 4 diclofenac given orally. Small animal ultrasound and magnetic resonance imaging were utilized for longitudinal

  18. Aggregate Demand–Inflation Adjustment Model Applied to Southeast European Economies

    Directory of Open Access Journals (Sweden)

    Apostolov Mico

    2016-01-01

    Full Text Available Applying IS-MP-IA model and the Taylor rule to selected Southeast European economies (Albania, Bosnia and Herzegovina, Macedonia and Serbia we find that the change of effective exchange rate positively affects output, while the change of the world interest rate negatively affects output or it does not affect the output at all, and additional world output would help to increase output of the selected economies.

  19. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer

    NARCIS (Netherlands)

    Petersen, Japke F.; Stuiver, Martijn M.; Timmermans, Adriana J.; Chen, Amy; Zhang, Hongzhen; O'Neill, James P.; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T.; Koch, Wayne; van den Brekel, Michiel W. M.

    2017-01-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442

  20. A Generic Model for Relative Adjustment Between Optical Sensors Using Rigorous Orbit Mechanics

    Directory of Open Access Journals (Sweden)

    B. Islam

    2008-06-01

    Full Text Available The classical calibration or space resection is the fundamental task in photogrammetry. The lack of sufficient knowledge of interior and exterior orientation parameters lead to unreliable results in the photogrammetric process. One of the earliest in approaches using in photogrammetry was the plumb line calibration method. This method is suitable to recover the radial and decentering lens distortion coefficients, while the remaining interior(focal length and principal point coordinates and exterior orientation parameters have to be determined by a complimentary method. As the lens distortion remains very less it not considered as the interior orientation parameters, in the present rigorous sensor model. There are several other available methods based on the photogrammetric collinearity equations, which consider the determination of exterior orientation parameters, with no mention to the simultaneous determination of inner orientation parameters. Normal space resection methods solve the problem using control points, whose coordinates are known both in image and object reference systems. The non-linearity of the model and the problems, in point location in digital images and identifying the maximum GPS measured control points are the main drawbacks of the classical approaches. This paper addresses mathematical model based on the fundamental assumption of collineariy of three points of two Along-Track Stereo imagery sensors and independent object point. Assuming this condition it is possible to extract the exterior orientation (EO parameters for a long strip and single image together, without and with using the control points. Moreover, after extracting the EO parameters the accuracy for satellite data products are compared in with using single and with no control points.

  1. Constructing Quality Adjusted Price Indexes: a Comparison of Hedonic and Discrete Choice Models

    OpenAIRE

    N. Jonker

    2001-01-01

    The Boskin report (1996) concluded that the US consumer price index (CPI) overestimated the inflation by 1.1 percentage points. This was due to several measurement errors in the CPI. One of them is called quality change bias. In this paper two methods are compared which can be used to eliminate quality change bias, namely the hedonic method and a method based on the use of discrete choice models. The underlying micro-economic fundations of the two methods are compared as well as their empiric...

  2. Review and evaluation of performance measures for survival prediction models in external validation settings

    Directory of Open Access Journals (Sweden)

    M. Shafiqur Rahman

    2017-04-01

    Full Text Available Abstract Background When developing a prediction model for survival data it is essential to validate its performance in external validation settings using appropriate performance measures. Although a number of such measures have been proposed, there is only limited guidance regarding their use in the context of model validation. This paper reviewed and evaluated a wide range of performance measures to provide some guidelines for their use in practice. Methods An extensive simulation study based on two clinical datasets was conducted to investigate the performance of the measures in external validation settings. Measures were selected from categories that assess the overall performance, discrimination and calibration of a survival prediction model. Some of these have been modified to allow their use with validation data, and a case study is provided to describe how these measures can be estimated in practice. The measures were evaluated with respect to their robustness to censoring and ease of interpretation. All measures are implemented, or are straightforward to implement, in statistical software. Results Most of the performance measures were reasonably robust to moderate levels of censoring. One exception was Harrell’s concordance measure which tended to increase as censoring increased. Conclusions We recommend that Uno’s concordance measure is used to quantify concordance when there are moderate levels of censoring. Alternatively, Gönen and Heller’s measure could be considered, especially if censoring is very high, but we suggest that the prediction model is re-calibrated first. We also recommend that Royston’s D is routinely reported to assess discrimination since it has an appealing interpretation. The calibration slope is useful for both internal and external validation settings and recommended to report routinely. Our recommendation would be to use any of the predictive accuracy measures and provide the corresponding predictive

  3. Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

    DEFF Research Database (Denmark)

    Borup, Morten; Grum, Morten; Linde, Jens Jørgen

    2016-01-01

    estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable......Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling...... overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5–30 min of rain data recorded by multiple rain gauges and propagating the rainfall...

  4. Plants modify biological processes to ensure survival following carbon depletion: a Lolium perenne model.

    Directory of Open Access Journals (Sweden)

    Julia M Lee

    Full Text Available BACKGROUND: Plants, due to their immobility, have evolved mechanisms allowing them to adapt to multiple environmental and management conditions. Short-term undesirable conditions (e.g. moisture deficit, cold temperatures generally reduce photosynthetic carbon supply while increasing soluble carbohydrate accumulation. It is not known, however, what strategies plants may use in the long-term to adapt to situations resulting in net carbon depletion (i.e. reduced photosynthetic carbon supply and carbohydrate accumulation. In addition, many transcriptomic experiments have typically been undertaken under laboratory conditions; therefore, long-term acclimation strategies that plants use in natural environments are not well understood. METHODOLOGY/PRINCIPAL FINDINGS: Perennial ryegrass (Lolium perenne L. was used as a model plant to define whether plants adapt to repetitive carbon depletion and to further elucidate their long-term acclimation mechanisms. Transcriptome changes in both lamina and stubble tissues of field-grown plants with depleted carbon reserves were characterised using reverse transcription-quantitative polymerase chain reaction (RT-qPCR. The RT-qPCR data for select key genes indicated that plants reduced fructan degradation, and increased photosynthesis and fructan synthesis capacities following carbon depletion. This acclimatory response was not sufficient to prevent a reduction (P<0.001 in net biomass accumulation, but ensured that the plant survived. CONCLUSIONS: Adaptations of plants with depleted carbon reserves resulted in reduced post-defoliation carbon mobilization and earlier replenishment of carbon reserves, thereby ensuring survival and continued growth. These findings will help pave the way to improve plant biomass production, for either grazing livestock or biofuel purposes.

  5. An ice flow modeling perspective on bedrock adjustment patterns of the Greenland ice sheet

    Directory of Open Access Journals (Sweden)

    M. Olaizola

    2012-11-01

    Full Text Available Since the launch in 2002 of the Gravity Recovery and Climate Experiment (GRACE satellites, several estimates of the mass balance of the Greenland ice sheet (GrIS have been produced. To obtain ice mass changes, the GRACE data need to be corrected for the effect of deformation changes of the Earth's crust. Recently, a new method has been proposed where ice mass changes and bedrock changes are simultaneously solved. Results show bedrock subsidence over almost the entirety of Greenland in combination with ice mass loss which is only half of the currently standing estimates. This subsidence can be an elastic response, but it may however also be a delayed response to past changes. In this study we test whether these subsidence patterns are consistent with ice dynamical modeling results. We use a 3-D ice sheet–bedrock model with a surface mass balance forcing based on a mass balance gradient approach to study the pattern and magnitude of bedrock changes in Greenland. Different mass balance forcings are used. Simulations since the Last Glacial Maximum yield a bedrock delay with respect to the mass balance forcing of nearly 3000 yr and an average uplift at present of 0.3 mm yr−1. The spatial pattern of bedrock changes shows a small central subsidence as well as more intense uplift in the south. These results are not compatible with the gravity based reconstructions showing a subsidence with a maximum in central Greenland, thereby questioning whether the claim of halving of the ice mass change is justified.

  6. Modifying the baricity of local anesthetics for spinal anesthesia by temperature adjustment: model calculations.

    Science.gov (United States)

    Heller, Axel R; Zimmermann, Katrin; Seele, Kristin; Rössel, Thomas; Koch, Thea; Litz, Rainer J

    2006-08-01

    Although local anesthetics (LAs) are hyperbaric at room temperature, density drops within minutes after administration into the subarachnoid space. LAs become hypobaric and therefore may cranially ascend during spinal anesthesia in an uncontrolled manner. The authors hypothesized that temperature and density of LA solutions have a nonlinear relation that may be described by a polynomial equation, and that conversion of this equation may provide the temperature at which individual LAs are isobaric. Density of cerebrospinal fluid was measured using a vibrating tube densitometer. Temperature-dependent density data were obtained from all LAs commonly used for spinal anesthesia, at least in triplicate at 5 degrees, 20 degrees, 30 degrees, and 37 degrees C. The hypothesis was tested by fitting the obtained data into polynomial mathematical models allowing calculations of substance-specific isobaric temperatures. Cerebrospinal fluid at 37 degrees C had a density of 1.000646 +/- 0.000086 g/ml. Three groups of local anesthetics with similar temperature (T, degrees C)-dependent density (rho) characteristics were identified: articaine and mepivacaine, rho1(T) = 1.008-5.36 E-06 T2 (heavy LAs, isobaric at body temperature); L-bupivacaine, rho2(T) = 1.007-5.46 E-06 T2 (intermediate LA, less hypobaric than saline); bupivacaine, ropivacaine, prilocaine, and lidocaine, rho3(T) = 1.0063-5.0 E-06 T (light LAs, more hypobaric than saline). Isobaric temperatures (degrees C) were as follows: 5 mg/ml bupivacaine, 35.1; 5 mg/ml L-bupivacaine, 37.0; 5 mg/ml ropivacaine, 35.1; 20 mg/ml articaine, 39.4. Sophisticated measurements and mathematic models now allow calculation of the ideal injection temperature of LAs and, thus, even better control of LA distribution within the cerebrospinal fluid. The given formulae allow the adaptation on subpopulations with varying cerebrospinal fluid density.

  7. Flux balance modeling to predict bacterial survival during pulsed-activity events

    Science.gov (United States)

    Jose, Nicholas A.; Lau, Rebecca; Swenson, Tami L.; Klitgord, Niels; Garcia-Pichel, Ferran; Bowen, Benjamin P.; Baran, Richard; Northen, Trent R.

    2018-04-01

    Desert biological soil crusts (BSCs) are cyanobacteria-dominated surface soil microbial communities common to plant interspaces in arid environments. The capability to significantly dampen their metabolism allows them to exist for extended periods in a desiccated dormant state that is highly robust to environmental stresses. However, within minutes of wetting, metabolic functions reboot, maximizing activity during infrequent permissive periods. Microcoleus vaginatus, a primary producer within the crust ecosystem and an early colonizer, initiates crust formation by binding particles in the upper layer of soil via exopolysaccharides, making microbial dominated biological soil crusts highly dependent on the viability of this organism. Previous studies have suggested that biopolymers play a central role in the survival of this organism by powering resuscitation, rapidly forming compatible solutes, and fueling metabolic activity in dark, hydrated conditions. To elucidate the mechanism of this phenomenon and provide a basis for future modeling of BSCs, we developed a manually curated, genome-scale metabolic model of Microcoleus vaginatus (iNJ1153). To validate this model, gas chromatography-mass spectroscopy (GC-MS) and liquid chromatography-mass spectroscopy (LC-MS) were used to characterize the rate of biopolymer accumulation and depletion in in hydrated Microcoleus vaginatus under light and dark conditions. Constraint-based flux balance analysis showed agreement between model predictions and experimental reaction fluxes. A significant amount of consumed carbon and light energy is invested into storage molecules glycogen and polyphosphate, while β-polyhydroxybutyrate may function as a secondary resource. Pseudo-steady-state modeling suggests that glycogen, the primary carbon source with the fastest depletion rate, will be exhausted if M. vaginatus experiences dark wetting events 4 times longer than light wetting events.

  8. A novel survival model of cardioplegic arrest and cardiopulmonary bypass in rats: a methodology paper

    Directory of Open Access Journals (Sweden)

    Podgoreanu Mihai V

    2008-08-01

    Full Text Available Abstract Background Given the growing population of cardiac surgery patients with impaired preoperative cardiac function and rapidly expanding surgical techniques, continued efforts to improve myocardial protection strategies are warranted. Prior research is mostly limited to either large animal models or ex vivo preparations. We developed a new in vivo survival model that combines administration of antegrade cardioplegia with endoaortic crossclamping during cardiopulmonary bypass (CPB in the rat. Methods Sprague-Dawley rats were cannulated for CPB (n = 10. With ultrasound guidance, a 3.5 mm balloon angioplasty catheter was positioned via the right common carotid artery with its tip proximal to the aortic valve. To initiate cardioplegic arrest, the balloon was inflated and cardioplegia solution injected. After 30 min of cardioplegic arrest, the balloon was deflated, ventilation resumed, and rats were weaned from CPB and recovered. To rule out any evidence of cerebral ischemia due to right carotid artery ligation, animals were neurologically tested on postoperative day 14, and their brains histologically assessed. Results Thirty minutes of cardioplegic arrest was successfully established in all animals. Functional assessment revealed no neurologic deficits, and histology demonstrated no gross neuronal damage. Conclusion This novel small animal CPB model with cardioplegic arrest allows for both the study of myocardial ischemia-reperfusion injury as well as new cardioprotective strategies. Major advantages of this model include its overall feasibility and cost effectiveness. In future experiments long-term echocardiographic outcomes as well as enzymatic, genetic, and histologic characterization of myocardial injury can be assessed. In the field of myocardial protection, rodent models will be an important avenue of research.

  9. [The survival prediction model of advanced gallbladder cancer based on Bayesian network: a multi-institutional study].

    Science.gov (United States)

    Tang, Z H; Geng, Z M; Chen, C; Si, S B; Cai, Z Q; Song, T Q; Gong, P; Jiang, L; Qiu, Y H; He, Y; Zhai, W L; Li, S P; Zhang, Y C; Yang, Y

    2018-05-01

    Objective: To investigate the clinical value of Bayesian network in predicting survival of patients with advanced gallbladder cancer(GBC)who underwent curative intent surgery. Methods: The clinical data of patients with advanced GBC who underwent curative intent surgery in 9 institutions from January 2010 to December 2015 were analyzed retrospectively.A median survival time model based on a tree augmented naïve Bayes algorithm was established by Bayesia Lab software.The survival time, number of metastatic lymph nodes(NMLN), T stage, pathological grade, margin, jaundice, liver invasion, age, sex and tumor morphology were included in this model.Confusion matrix, the receiver operating characteristic curve and area under the curve were used to evaluate the accuracy of the model.A priori statistical analysis of these 10 variables and a posterior analysis(survival time as the target variable, the remaining factors as the attribute variables)was performed.The importance rankings of each variable was calculated with the polymorphic Birnbaum importance calculation based on the posterior analysis results.The survival probability forecast table was constructed based on the top 4 prognosis factors. The survival curve was drawn by the Kaplan-Meier method, and differences in survival curves were compared using the Log-rank test. Results: A total of 316 patients were enrolled, including 109 males and 207 females.The ratio of male to female was 1.0∶1.9, the age was (62.0±10.8)years.There was 298 cases(94.3%) R0 resection and 18 cases(5.7%) R1 resection.T staging: 287 cases(90.8%) T3 and 29 cases(9.2%) T4.The median survival time(MST) was 23.77 months, and the 1, 3, 5-year survival rates were 67.4%, 40.8%, 32.0%, respectively.For the Bayesian model, the number of correctly predicted cases was 121(≤23.77 months) and 115(>23.77 months) respectively, leading to a 74.86% accuracy of this model.The prior probability of survival time was 0.503 2(≤23.77 months) and 0.496 8

  10. Foundations for Survivable System Development: Service Traces, Intrusion Traces, and Evaluation Models

    National Research Council Canada - National Science Library

    Linger, Richard

    2001-01-01

    .... On the system side, survivability specifications can be defined by essential-service traces that map essential-service workflows, derived from user requirements, into system component dependencies...

  11. Fast Cloud Adjustment to Increasing CO2 in a Superparameterized Climate Model

    Directory of Open Access Journals (Sweden)

    Marat Khairoutdinov

    2012-05-01

    Full Text Available Two-year simulation experiments with a superparameterized climate model, SP-CAM, are performed to understand the fast tropical (30S-30N cloud response to an instantaneous quadrupling of CO2 concentration with SST held fixed at present-day values.The greenhouse effect of the CO2 perturbation quickly warms the tropical land surfaces by an average of 0.5 K. This shifts rising motion, surface precipitation, and cloud cover at all levels from the ocean to the land, with only small net tropical-mean cloud changes. There is a widespread average reduction of about 80 m in the depth of the trade inversion capping the marine boundary layer (MBL over the cooler subtropical oceans.One apparent contributing factor is CO2-enhanced downwelling longwave radiation, which reduces boundary-layer radiative cooling, a primary driver of turbulent entrainment through the trade inversion. A second contributor is a slight CO2-induced heating of the free troposphere above the MBL, which strengthens the trade inversion and also inhibits entrainment. There is a corresponding downward displacement of MBL clouds with a very slight decrease in mean cloud cover and albedo.Two-dimensional cloud-resolving model (CRM simulations of this MBL response are run to steady state using composite SP-CAM simulated thermodynamic and wind profiles from a representative cool subtropical ocean regime, for the control and 4xCO2 cases. Simulations with a CRM grid resolution equal to that of SP-CAM are compared with much finer resolution simulations. The coarse-resolution simulations maintain a cloud fraction and albedo comparable to SP-CAM, but the fine-resolution simulations have a much smaller cloud fraction. Nevertheless, both CRM configurations simulate a reduction in inversion height comparable to SP-CAM. The changes in low cloud cover and albedo in the CRM simulations are small, but both simulations predict a slight reduction in low cloud albedo as in SP-CAM.

  12. The comparison of proportional hazards and accelerated failure time models in analyzing the first birth interval survival data

    Science.gov (United States)

    Faruk, Alfensi

    2018-03-01

    Survival analysis is a branch of statistics, which is focussed on the analysis of time- to-event data. In multivariate survival analysis, the proportional hazards (PH) is the most popular model in order to analyze the effects of several covariates on the survival time. However, the assumption of constant hazards in PH model is not always satisfied by the data. The violation of the PH assumption leads to the misinterpretation of the estimation results and decreasing the power of the related statistical tests. On the other hand, the accelerated failure time (AFT) models do not assume the constant hazards in the survival data as in PH model. The AFT models, moreover, can be used as the alternative to PH model if the constant hazards assumption is violated. The objective of this research was to compare the performance of PH model and the AFT models in analyzing the significant factors affecting the first birth interval (FBI) data in Indonesia. In this work, the discussion was limited to three AFT models which were based on Weibull, exponential, and log-normal distribution. The analysis by using graphical approach and a statistical test showed that the non-proportional hazards exist in the FBI data set. Based on the Akaike information criterion (AIC), the log-normal AFT model was the most appropriate model among the other considered models. Results of the best fitted model (log-normal AFT model) showed that the covariates such as women’s educational level, husband’s educational level, contraceptive knowledge, access to mass media, wealth index, and employment status were among factors affecting the FBI in Indonesia.

  13. Advanced age negatively impacts survival in an experimental brain tumor model.

    Science.gov (United States)

    Ladomersky, Erik; Zhai, Lijie; Gritsina, Galina; Genet, Matthew; Lauing, Kristen L; Wu, Meijing; James, C David; Wainwright, Derek A

    2016-09-06

    Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with an average age of 64 years at the time of diagnosis. To study GBM, a number of mouse brain tumor models have been utilized. In these animal models, subjects tend to range from 6 to 12 weeks of age, which is analogous to that of a human teenager. Here, we examined the impact of age on host immunity and the gene expression associated with immune evasion in immunocompetent mice engrafted with syngeneic intracranial GL261. The data indicate that, in mice with brain tumors, youth conveys an advantage to survival. While age did not affect the tumor-infiltrating T cell phenotype or quantity, we discovered that old mice express higher levels of the immunoevasion enzyme, IDO1, which was decreased by the presence of brain tumor. Interestingly, other genes associated with promoting immunosuppression including CTLA-4, PD-L1 and FoxP3, were unaffected by age. These data highlight the possibility that IDO1 contributes to faster GBM outgrowth with advanced age, providing rationale for future investigation into immunotherapeutic targeting in the future. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  14. Simvastatin Treatment Improves Survival in a Murine Model of Burn Sepsis

    Science.gov (United States)

    Beffa, David C; Fischman, Alan J.; Fagan, Shawn P.; Hamrahi, Victoria F.; Kaneki, Masao; Yu, Yong-Ming; Tompkins, Ronald G.; Carter, Edward A.

    2014-01-01

    Infection is the most common and most serious complication of a major burn injury related to burn size. Despite improvements in antimicrobial therapies sepsis still accounts for 50–60% of deaths in burn patients. Given the acute onset and unpredictable nature of sepsis, primary prevention was rarely attempted in its management. However, recent studies have demonstrated that statin treatment can decrease mortality is a murine model of sepsis by preservation of cardiac function and reversal of inflammatory alterations. In addition, it has been shown that treatment with statins is associated with reduced incidence of sepsis in human patients. In the current study groups of CD1 male mice (n=12) were anesthetized and subjected to a dorsal 30% TBSA scald burn injury. Starting 2 hours post burn, the animals were divided into a treatment group receiving 0.2 µ/g simvastatin or a sham group receiving placebo. Simvastatin and placebo were administered by intraperitoneal injection with two dosing regimens; once daily and every 12 hours. On Post burn day 7 cecal ligation and puncture with a 21-gauge needle was performed under ketamine/xylazine anesthesia and the two different dosing schedules were continued. A simvastatin dose dependant improvement in survival was observed in the burn sepsis model. PMID:21145172

  15. Irreversible electroporation of the pancreas is feasible and safe in a porcine survival model.

    Science.gov (United States)

    Fritz, Stefan; Sommer, Christof M; Vollherbst, Dominik; Wachter, Miguel F; Longerich, Thomas; Sachsenmeier, Milena; Knapp, Jürgen; Radeleff, Boris A; Werner, Jens

    2015-07-01

    Use of thermal tumor ablation in the pancreatic parenchyma is limited because of the risk of pancreatitis, pancreatic fistula, or hemorrhage. This study aimed to evaluate the feasibility and safety of irreversible electroporation (IRE) in a porcine model. Ten pigs were divided into 2 study groups. In the first group, animals received IRE of the pancreatic tail and were killed after 60 minutes. In the second group, animals received IRE at the head of the pancreas and were followed up for 7 days. Clinical parameters, computed tomography imaging, laboratory results, and histology were obtained. All animals survived IRE ablation, and no cardiac adverse effects were noted. Sixty minutes after IRE, a hypodense lesion on computed tomography imaging indicated the ablation zone. None of the animals developed clinical signs of acute pancreatitis. Only small amounts of ascites fluid, with a transient increase in amylase and lipase levels, were observed, indicating that no pancreatic fistula occurred. This porcine model shows that IRE is feasible and safe in the pancreatic parenchyma. Computed tomography imaging reveals significant changes at 60 minutes after IRE and therefore might serve as an early indicator of therapeutic success. Clinical studies are needed to evaluate the efficacy of IRE in pancreatic cancer.

  16. Salary adjustments

    CERN Multimedia

    HR Department

    2008-01-01

    In accordance with decisions taken by the Finance Committee and Council in December 2007, salaries are adjusted with effect from 1 January 2008. Scale of basic salaries and scale of stipends paid to fellows (Annex R A 5 and R A 6 respectively): increased by 0.71% with effect from 1 January 2008. As a result of the stability of the Geneva consumer price index, following elements do not increase: a) Family Allowance, Child Allowance and Infant Allowance (Annex R A 3). b) Reimbursement of education fees: maximum amounts of reimbursement (Annex R A 4.01) for the academic year 2007/2008. Related adjustments will be implemented, wherever applicable, to Paid Associates and Students. As in the past, the actual percentage increase of each salary position may vary, due to the application of a constant step value and the rounding effects. Human Resources Department Tel. 73566

  17. Salary adjustments

    CERN Multimedia

    HR Department

    2008-01-01

    In accordance with decisions taken by the Finance Committee and Council in December 2007, salaries are adjusted with effect from 1 January 2008. Scale of basic salaries and scale of stipends paid to fellows (Annex R A 5 and R A 6 respectively): increased by 0.71% with effect from 1 January 2008. As a result of the stability of the Geneva consumer price index, the following elements do not increase: a)\tFamily Allowance, Child Allowance and Infant Allowance (Annex R A 3); b)\tReimbursement of education fees: maximum amounts of reimbursement (Annex R A 4.01) for the academic year 2007/2008. Related adjustments will be applied, wherever applicable, to Paid Associates and Students. As in the past, the actual percentage increase of each salary position may vary, due to the application of a constant step value and rounding effects. Human Resources Department Tel. 73566

  18. Shaft adjuster

    Science.gov (United States)

    Harry, Herbert H.

    1989-01-01

    Apparatus and method for the adjustment and alignment of shafts in high power devices. A plurality of adjacent rotatable angled cylinders are positioned between a base and the shaft to be aligned which when rotated introduce an axial offset. The apparatus is electrically conductive and constructed of a structurally rigid material. The angled cylinders allow the shaft such as the center conductor in a pulse line machine to be offset in any desired alignment position within the range of the apparatus.

  19. Adjustable collimator

    International Nuclear Information System (INIS)

    Carlson, R.W.; Covic, J.; Leininger, G.

    1981-01-01

    In a rotating fan beam tomographic scanner there is included an adjustable collimator and shutter assembly. The assembly includes a fan angle collimation cylinder having a plurality of different length slots through which the beam may pass for adjusting the fan angle of the beam. It also includes a beam thickness cylinder having a plurality of slots of different widths for adjusting the thickness of the beam. Further, some of the slots have filter materials mounted therein so that the operator may select from a plurality of filters. Also disclosed is a servo motor system which allows the operator to select the desired fan angle, beam thickness and filter from a remote location. An additional feature is a failsafe shutter assembly which includes a spring biased shutter cylinder mounted in the collimation cylinders. The servo motor control circuit checks several system conditions before the shutter is rendered openable. Further, the circuit cuts off the radiation if the shutter fails to open or close properly. A still further feature is a reference radiation intensity monitor which includes a tuning-fork shaped light conducting element having a scintillation crystal mounted on each tine. The monitor is placed adjacent the collimator between it and the source with the pair of crystals to either side of the fan beam

  20. Conceptualizing strategic business model innovation leadership for business survival and business model innovation excellence

    DEFF Research Database (Denmark)

    Lindgren, Peter; Abdullah, Maizura Ailin

    2013-01-01

    Too many businesses are being marginalized by blind "business model innovations (BMIs)" and simple "BMIs". As documented in previous research (Markides 2008, Lindgren 2012), most businesses perform BMIs at a reactive level i.e. perceiving what the market, customers and network partners might want...... rather than what they actually demand. Few businesses have the ability to proactively lead BMIs and on a strategic level lead BMIs to something that fits the business’s long term perspective (Hamel 2011). Apple, Ryanair, Facebook, Zappo are some businesses that have shown BMI Leadership (BMIL......) in a proactive way - and more importantly, as some examples of first level BMIL. The overall aim of the BMIL is to prevent businesses from being marginalized by the BMI and thereby to optimize the business’s total BMI investment. The literature research and case research we studied gave us some important...

  1. Clinical variables serve as prognostic factors in a model for survival from glioblastoma multiforme

    DEFF Research Database (Denmark)

    Michaelsen, Signe Regner; Christensen, Ib Jarle; Grunnet, Kirsten

    2013-01-01

    Although implementation of temozolomide (TMZ) as a part of primary therapy for glioblastoma multiforme (GBM) has resulted in improved patient survival, the disease is still incurable. Previous studies have correlated various parameters to survival, although no single parameter has yet been...

  2. Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

    Science.gov (United States)

    Astuti Thamrin, Sri; Taufik, Irfan

    2018-03-01

    Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

  3. A risk-adjusted financial model to estimate the cost of a video-assisted thoracoscopic surgery lobectomy programme.

    Science.gov (United States)

    Brunelli, Alessandro; Tentzeris, Vasileios; Sandri, Alberto; McKenna, Alexandra; Liew, Shan Liung; Milton, Richard; Chaudhuri, Nilanjan; Kefaloyannis, Emmanuel; Papagiannopoulos, Kostas

    2016-05-01

    To develop a clinically risk-adjusted financial model to estimate the cost associated with a video-assisted thoracoscopic surgery (VATS) lobectomy programme. Prospectively collected data of 236 VATS lobectomy patients (August 2012-December 2013) were analysed retrospectively. Fixed and variable intraoperative and postoperative costs were retrieved from the Hospital Accounting Department. Baseline and surgical variables were tested for a possible association with total cost using a multivariable linear regression and bootstrap analyses. Costs were calculated in GBP and expressed in Euros (EUR:GBP exchange rate 1.4). The average total cost of a VATS lobectomy was €11 368 (range €6992-€62 535). Average intraoperative (including surgical and anaesthetic time, overhead, disposable materials) and postoperative costs [including ward stay, high dependency unit (HDU) or intensive care unit (ICU) and variable costs associated with management of complications] were €8226 (range €5656-€13 296) and €3029 (range €529-€51 970), respectively. The following variables remained reliably associated with total costs after linear regression analysis and bootstrap: carbon monoxide lung diffusion capacity (DLCO) 0.05) in 86% of the samples. A hypothetical patient with COPD and DLCO less than 60% would cost €4270 more than a patient without COPD and with higher DLCO values (€14 793 vs €10 523). Risk-adjusting financial data can help estimate the total cost associated with VATS lobectomy based on clinical factors. This model can be used to audit the internal financial performance of a VATS lobectomy programme for budgeting, planning and for appropriate bundled payment reimbursements. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  4. SU-E-T-247: Multi-Leaf Collimator Model Adjustments Improve Small Field Dosimetry in VMAT Plans

    Energy Technology Data Exchange (ETDEWEB)

    Young, L; Yang, F [University of Washington, Seattle, WA (United States)

    2014-06-01

    Purpose: The Elekta beam modulator linac employs a 4-mm micro multileaf collimator (MLC) backed by a fixed jaw. Out-of-field dose discrepancies between treatment planning system (TPS) calculations and output water phantom measurements are caused by the 1-mm leaf gap required for all moving MLCs in a VMAT arc. In this study, MLC parameters are optimized to improve TPS out-of-field dose approximations. Methods: Static 2.4 cm square fields were created with a 1-mm leaf gap for MLCs that would normally park behind the jaw. Doses in the open field and leaf gap were measured with an A16 micro ion chamber and EDR2 film for comparison with corresponding point doses in the Pinnacle TPS. The MLC offset table and tip radius were adjusted until TPS point doses agreed with photon measurements. Improvements to the beam models were tested using static arcs consisting of square fields ranging from 1.6 to 14.0 cm, with 45° collimator rotation, and 1-mm leaf gap to replicate VMAT conditions. Gamma values for the 3-mm distance, 3% dose difference criteria were evaluated using standard QA procedures with a cylindrical detector array. Results: The best agreement in point doses within the leaf gap and open field was achieved by offsetting the default rounded leaf end table by 0.1 cm and adjusting the leaf tip radius to 13 cm. Improvements in TPS models for 6 and 10 MV photon beams were more significant for smaller field sizes 3.6 cm or less where the initial gamma factors progressively increased as field size decreased, i.e. for a 1.6cm field size, the Gamma increased from 56.1% to 98.8%. Conclusion: The MLC optimization techniques developed will achieve greater dosimetric accuracy in small field VMAT treatment plans for fixed jaw linear accelerators. Accurate predictions of dose to organs at risk may reduce adverse effects of radiotherapy.

  5. Evaluating a novel tiered scarcity adjusted water budget and pricing structure using a holistic systems modelling approach.

    Science.gov (United States)

    Sahin, Oz; Bertone, Edoardo; Beal, Cara; Stewart, Rodney A

    2018-06-01

    Population growth, coupled with declining water availability and changes in climatic conditions underline the need for sustainable and responsive water management instruments. Supply augmentation and demand management are the two main strategies used by water utilities. Water demand management has long been acknowledged as a least-cost strategy to maintain water security. This can be achieved in a variety of ways, including: i) educating consumers to limit their water use; ii) imposing restrictions/penalties; iii) using smart and/or efficient technologies; and iv) pricing mechanisms. Changing water consumption behaviours through pricing or restrictions is challenging as it introduces more social and political issues into the already complex water resources management process. This paper employs a participatory systems modelling approach for: (1) evaluating various forms of a proposed tiered scarcity adjusted water budget and pricing structure, and (2) comparing scenario outcomes against the traditional restriction policy regime. System dynamics modelling was applied since it can explicitly account for the feedbacks, interdependencies, and non-linear relations that inherently characterise the water tariff (price)-demand-revenue system. A combination of empirical water use data, billing data and customer feedback on future projected water bills facilitated the assessment of the suitability and likelihood of the adoption of scarcity-driven tariff options for a medium-sized city within Queensland, Australia. Results showed that the tiered scarcity adjusted water budget and pricing structure presented was preferable to restrictions since it could maintain water security more equitably with the lowest overall long-run marginal cost. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Modeling nest-survival data: a comparison of recently developed methods that can be implemented in MARK and SAS

    Directory of Open Access Journals (Sweden)

    Rotella, J. J.

    2004-06-01

    Full Text Available Estimating nest success and evaluating factors potentially related to the survival rates of nests are key aspects of many studies of avian populations. A strong interest in nest success has led to a rich literature detailing a variety of estimation methods for this vital rate. In recent years, modeling approaches have undergone especially rapid development. Despite these advances, most researchers still employ Mayfield’s ad-hoc method (Mayfield, 1961 or, in some cases, the maximum-likelihood estimator of Johnson (1979 and Bart & Robson (1982. Such methods permit analyses of stratified data but do not allow for more complex and realistic models of nest survival rate that include covariates that vary by individual, nest age, time, etc. and that may be continuous or categorical. Methods that allow researchers to rigorously assess the importance of a variety of biological factors that might affect nest survival rates can now be readily implemented in Program MARK and in SAS’s Proc GENMOD and Proc NLMIXED. Accordingly, use of Mayfield’s estimator without first evaluating the need for more complex models of nest survival rate cannot be justified. With the goal of increasing the use of more flexible methods, we first describe the likelihood used for these models and then consider the question of what the effective sample size is for computation of AICc. Next, we consider the advantages and disadvantages of these different programs in terms of ease of data input and model construction; utility/flexibility of generated estimates and predictions; ease of model selection; and ability to estimate variance components. An example data set is then analyzed using both MARK and SAS to demonstrate implementation of the methods with various models that contain nest-, group- (or block-, and time-specific covariates. Finally, we discuss improvements that would, if they became available, promote a better general understanding of nest survival rates.

  7. Generation of a convalescent model of virulent Francisella tularensis infection for assessment of host requirements for survival of tularemia.

    Directory of Open Access Journals (Sweden)

    Deborah D Crane

    Full Text Available Francisella tularensis is a facultative intracellular bacterium and the causative agent of tularemia. Development of novel vaccines and therapeutics for tularemia has been hampered by the lack of understanding of which immune components are required to survive infection. Defining these requirements for protection against virulent F. tularensis, such as strain SchuS4, has been difficult since experimentally infected animals typically die within 5 days after exposure to as few as 10 bacteria. Such a short mean time to death typically precludes development, and therefore assessment, of immune responses directed against virulent F. tularensis. To enable identification of the components of the immune system that are required for survival of virulent F. tularensis, we developed a convalescent model of tularemia in C57Bl/6 mice using low dose antibiotic therapy in which the host immune response is ultimately responsible for clearance of the bacterium. Using this model we demonstrate αβTCR(+ cells, γδTCR(+ cells, and B cells are necessary to survive primary SchuS4 infection. Analysis of mice deficient in specific soluble mediators shows that IL-12p40 and IL-12p35 are essential for survival of SchuS4 infection. We also show that IFN-γ is required for survival of SchuS4 infection since mice lacking IFN-γR succumb to disease during the course of antibiotic therapy. Finally, we found that both CD4(+ and CD8(+ cells are the primary producers of IFN-γand that γδTCR(+ cells and NK cells make a minimal contribution toward production of this cytokine throughout infection. Together these data provide a novel model that identifies key cells and cytokines required for survival or exacerbation of infection with virulent F. tularensis and provides evidence that this model will be a useful tool for better understanding the dynamics of tularemia infection.

  8. Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard.

    NARCIS (Netherlands)

    Möller, M.; Obleitner, F.; Reijmer, C.H.; Pohjola, V.A.; Glowacki, P.; Kohler, J.

    2016-01-01

    Large-scale modeling of glacier mass balance relies often on the output from regional climate models (RCMs). However, the limited accuracy and spatial resolution of RCM output pose limitations on mass balance simulations at subregional or local scales. Moreover, RCM output is still rarely available

  9. A clinical-molecular prognostic model to predict survival in patients with post polycythemia vera and post essential thrombocythemia myelofibrosis.

    Science.gov (United States)

    Passamonti, F; Giorgino, T; Mora, B; Guglielmelli, P; Rumi, E; Maffioli, M; Rambaldi, A; Caramella, M; Komrokji, R; Gotlib, J; Kiladjian, J J; Cervantes, F; Devos, T; Palandri, F; De Stefano, V; Ruggeri, M; Silver, R T; Benevolo, G; Albano, F; Caramazza, D; Merli, M; Pietra, D; Casalone, R; Rotunno, G; Barbui, T; Cazzola, M; Vannucchi, A M

    2017-12-01

    Polycythemia vera (PV) and essential thrombocythemia (ET) are myeloproliferative neoplasms with variable risk of evolution into post-PV and post-ET myelofibrosis, from now on referred to as secondary myelofibrosis (SMF). No specific tools have been defined for risk stratification in SMF. To develop a prognostic model for predicting survival, we studied 685 JAK2, CALR, and MPL annotated patients with SMF. Median survival of the whole cohort was 9.3 years (95% CI: 8-not reached-NR-). Through penalized Cox regressions we identified negative predictors of survival and according to beta risk coefficients we assigned 2 points to hemoglobin level <11 g/dl, to circulating blasts ⩾3%, and to CALR-unmutated genotype, 1 point to platelet count <150 × 10 9 /l and to constitutional symptoms, and 0.15 points to any year of age. Myelofibrosis Secondary to PV and ET-Prognostic Model (MYSEC-PM) allocated SMF patients into four risk categories with different survival (P<0.0001): low (median survival NR; 133 patients), intermediate-1 (9.3 years, 95% CI: 8.1-NR; 245 patients), intermediate-2 (4.4 years, 95% CI: 3.2-7.9; 126 patients), and high risk (2 years, 95% CI: 1.7-3.9; 75 patients). Finally, we found that the MYSEC-PM represents the most appropriate tool for SMF decision-making to be used in clinical and trial settings.

  10. The mass effect model of the survival rate's dose effect of organism irradiated with low energy ion beam

    International Nuclear Information System (INIS)

    Shao Chunlin; Gui Qifu; Yu Zengliang

    1995-01-01

    The main characteristic of the low energy ions mutation is its mass deposition effect. Basing on the theory of 'double strand breaking' and the 'mass deposition effect', the authors suggests that the mass deposition products can repair or further damage the double strand breaking of DNA. According to this consideration the dose effect model of the survival rate of organism irradiated by low energy of N + ion beam is deduced as: S exp{-p[αφ + βφ 2 -Rφ 2 exp(-kφ)-Lφ 3 exp(-kφ)]}, which can be called 'mass effect model'. In the low energy ion beam mutation, the dose effects of many survival rates that can not be imitated by previous models are successfully imitated by this model. The suitable application fields of the model are also discussed

  11. Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

    Science.gov (United States)

    Borup, Morten; Grum, Morten; Linde, Jens Jørgen; Mikkelsen, Peter Steen

    2016-08-01

    Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5-30 min of rain data recorded by multiple rain gauges and propagating the rainfall estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable, well defined, 64 ha urban catchment, for nine overflow generating rain events. The dynamically adjusted radar data perform best when the aggregation period is as small as 10-20 min, in which case it performs much better than static adjusted radar data and data from rain gauges situated 2-3 km away.

  12. SERPINB3 in the chicken model of ovarian cancer: a prognostic factor for platinum resistance and survival in patients with epithelial ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Whasun Lim

    Full Text Available Serine protease inhibitors (SERPINs appear to be ubiquitously expressed in a variety of species and play important roles in pivotal physiological processes such as angiogenesis, immune responses, blood coagulation and fibronolysis. Of these, squamous cell carcinoma antigen 1 (SCCA1, also known as a SERPINB3, was first identified in squamous cell carcinoma tissue from the cervix of women. However, there is little known about the SERPINB3 expression in human epithelial ovarian cancer (EOC. Therefore, in the present study, we investigated the functional role of SERPINB3 gene in human EOC using chickens, the most relevant animal model. In 136 chickens, EOC was found in 10 (7.4%. SERPINB3 mRNA was induced in cancerous, but not normal ovaries of chickens (P<0.01, and it was abundant only in the glandular epithelium of cancerous ovaries of chickens. Further, several microRNAs, specifically miR-101, miR-1668 and miR-1681 were discovered to influence SERPINB3 expression via its 3'-UTR which suggests that post-transcriptional regulation influences SERPINB3 expression in chickens. SERPINB3 protein was localized predominantly to the glandular epithelium in cancerous ovaries of chickens, and it was abundant in the nucleus of both chicken and human ovarian cancer cell lines. In 109 human patients with EOC, 15 (13.8%, 66 (60.6% and 28 (25.7% patients showed weak, moderate and strong expression of SERPINB3 protein, respectively. Strong expression of SERPINB3 protein was a prognostic factor for platinum resistance (adjusted OR; odds ratio, 5.94; 95% Confidence Limits, 1.21-29.15, and for poor progression-free survival (PFS; adjusted HR; hazard ratio, 2.07; 95% CI; confidence interval, 1.03-4.41. Therefore, SERPINB3 may play an important role in ovarian carcinogenesis and be a novel biomarker for predicting platinum resistance and a poor prognosis for survival in patients with EOC.

  13. A system dynamics model of China's electric power structure adjustment with constraints of PM10 emission reduction.

    Science.gov (United States)

    Guo, Xiaopeng; Ren, Dongfang; Guo, Xiaodan

    2018-06-01

    Recently, Chinese state environmental protection administration has brought out several PM10 reduction policies to control the coal consumption strictly and promote the adjustment of power structure. Under this new policy environment, a suitable analysis method is required to simulate the upcoming major shift of China's electric power structure. Firstly, a complete system dynamics model is built to simulate China's evolution path of power structure with constraints of PM10 reduction considering both technical and economical factors. Secondly, scenario analyses are conducted under different clean-power capacity growth rates to seek applicable policy guidance for PM10 reduction. The results suggest the following conclusions. (1) The proportion of thermal power installed capacity will decrease to 67% in 2018 with a dropping speed, and there will be an accelerated decline in 2023-2032. (2) The system dynamics model can effectively simulate the implementation of the policy, for example, the proportion of coal consumption in the forecast model is 63.3% (the accuracy rate is 95.2%), below policy target 65% in 2017. (3) China should promote clean power generation such as nuclear power to meet PM10 reduction target.

  14. Positive end-expiratory pressure improves survival in a rodent model of cardiopulmonary resuscitation using high-dose epinephrine.

    LENUS (Irish Health Repository)

    McCaul, Conán

    2009-10-01

    Multiple interventions have been tested in models of cardiopulmonary resuscitation (CPR) to optimize drug use, chest compressions, and ventilation. None has studied the effects of positive end-expiratory pressure (PEEP) on outcome. We hypothesized that because PEEP can reverse pulmonary atelectasis, lower pulmonary vascular resistance, and potentially improve cardiac output, its use during CPR would increase survival.

  15. Human immune cells' behavior and survival under bioenergetically restricted conditions in an in vitro fracture hematoma model

    Science.gov (United States)

    Hoff, Paula; Maschmeyer, Patrick; Gaber, Timo; Schütze, Tabea; Raue, Tobias; Schmidt-Bleek, Katharina; Dziurla, René; Schellmann, Saskia; Lohanatha, Ferenz Leonard; Röhner, Eric; Ode, Andrea; Burmester, Gerd-Rüdiger; Duda, Georg N; Perka, Carsten; Buttgereit, Frank

    2013-01-01

    The initial inflammatory phase of bone fracture healing represents a critical step for the outcome of the healing process. However, both the mechanisms initiating this inflammatory phase and the function of immune cells present at the fracture site are poorly understood. In order to study the early events within a fracture hematoma, we established an in vitro fracture hematoma model: we cultured hematomas forming during an osteotomy (artificial bone fracture) of the femur during total hip arthroplasty (THA) in vitro under bioenergetically controlled conditions. This model allowed us to monitor immune cell populations, cell survival and cytokine expression during the early phase following a fracture. Moreover, this model enabled us to change the bioenergetical conditions in order to mimic the in vivo situation, which is assumed to be characterized by hypoxia and restricted amounts of nutrients. Using this model, we found that immune cells adapt to hypoxia via the expression of angiogenic factors, chemoattractants and pro-inflammatory molecules. In addition, combined restriction of oxygen and nutrient supply enhanced the selective survival of lymphocytes in comparison with that of myeloid derived cells (i.e., neutrophils). Of note, non-restricted bioenergetical conditions did not show any similar effects regarding cytokine expression and/or different survival rates of immune cell subsets. In conclusion, we found that the bioenergetical conditions are among the crucial factors inducing the initial inflammatory phase of fracture healing and are thus a critical step for influencing survival and function of immune cells in the early fracture hematoma. PMID:23396474

  16. Mycobacterium tuberculosis PPE18 Protein Reduces Inflammation and Increases Survival in Animal Model of Sepsis.

    Science.gov (United States)

    Ahmed, Asma; Dolasia, Komal; Mukhopadhyay, Sangita

    2018-04-18

    Mycobacterium tuberculosis PPE18 is a member of the PPE family. Previous studies have shown that recombinant PPE18 (rPPE18) protein binds to TLR2 and triggers a signaling cascade which reduces levels of TNF-α and IL-12, and increases IL-10 in macrophages. Because TNF-α is a major mediator of the pathophysiology of sepsis and blocking inflammation is a possible line of therapy in such circumstances, we tested the efficacy of rPPE18 in reducing symptoms of sepsis in a mouse model of Escherichia coli- induced septic peritonitis. rPPE18 significantly decreased levels of serum TNF-α, IL-1β, IL-6, and IL-12 and reduced organ damage in mice injected i.p. with high doses of E. coli Peritoneal cells isolated from rPPE18-treated mice had characteristics of M2 macrophages which are protective in excessive inflammation. Additionally, rPPE18 inhibited disseminated intravascular coagulation, which can cause organ damage resulting in death. rPPE18 was able to reduce sepsis-induced mortality when given prophylactically or therapeutically. Additionally, in a mouse model of cecal ligation and puncture-induced sepsis, rPPE18 reduced TNF-α, alanine transaminase, and creatinine, attenuated organ damage, prevented depletion of monocytes and lymphocytes, and improved survival. Our studies show that rPPE18 has potent anti-inflammatory properties and can serve as a novel therapeutic to control sepsis. Copyright © 2018 by The American Association of Immunologists, Inc.

  17. A two-zone cosmic ray propagation model and its implication of the surviving fraction of radioactive cosmic ray isotopes

    International Nuclear Information System (INIS)

    Simon, M.; Scherzer, R.; Enge, W.

    1977-01-01

    In cosmic ray propagation calculations one can usually assume a homogeneous distribution of interstellar matter. The crucial astrophysical parameters in these models are: The path length distribution, the age of the cosmic ray particles and the interstellar matter density. These values are interrelated. The surviving fraction of radioactive cosmic ray isotopes is often used to determine a mean matter density of that region, where the cosmic ray particles may mainly reside. Using a Monte Carlo Propagation Program we calculated the change in the surviving fraction quantitatively assuming a region around the sources with higher matter density. (author)

  18. Development and internal validation of a prognostic model to predict recurrence free survival in patients with adult granulosa cell tumors of the ovary

    NARCIS (Netherlands)

    van Meurs, Hannah S.; Schuit, Ewoud; Horlings, Hugo M.; van der Velden, Jacobus; van Driel, Willemien J.; Mol, Ben Willem J.; Kenter, Gemma G.; Buist, Marrije R.

    2014-01-01

    Models to predict the probability of recurrence free survival exist for various types of malignancies, but a model for recurrence free survival in individuals with an adult granulosa cell tumor (GCT) of the ovary is lacking. We aimed to develop and internally validate such a prognostic model. We

  19. Modeling the decline of the Porcupine Caribou Herd, 1989-1998: the importance of survival vs. recruitment

    OpenAIRE

    Arthur, Stephen M.; Whitten, Kenneth R.; Mauer, Francis J.; Cooley, Dorothy

    2003-01-01

    The Porcupine caribou (Rangifer tarandus granti) herd increased from approximately 100 000 animals during the 1970s to 178 000 in 1989, then declined to 129 000 by 1998. Our objective was to model the dynamics of this herd and investigate the potential that lower calf recruitment, as was observed during 1991-1993, produced the observed population changes. A deterministic model was prepared using estimates of birth and survival rates that reproduced the pattern of population growth from 1971-1...

  20. NTCP modelling of lung toxicity after SBRT comparing the universal survival curve and the linear quadratic model for fractionation correction

    International Nuclear Information System (INIS)

    Wennberg, Berit M.; Baumann, Pia; Gagliardi, Giovanna

    2011-01-01

    Background. In SBRT of lung tumours no established relationship between dose-volume parameters and the incidence of lung toxicity is found. The aim of this study is to compare the LQ model and the universal survival curve (USC) to calculate biologically equivalent doses in SBRT to see if this will improve knowledge on this relationship. Material and methods. Toxicity data on radiation pneumonitis grade 2 or more (RP2+) from 57 patients were used, 10.5% were diagnosed with RP2+. The lung DVHs were corrected for fractionation (LQ and USC) and analysed with the Lyman- Kutcher-Burman (LKB) model. In the LQ-correction α/β = 3 Gy was used and the USC parameters used were: α/β = 3 Gy, D 0 = 1.0 Gy, n = 10, α 0.206 Gy-1 and d T = 5.8 Gy. In order to understand the relative contribution of different dose levels to the calculated NTCP the concept of fractional NTCP was used. This might give an insight to the questions of whether 'high doses to small volumes' or 'low doses to large volumes' are most important for lung toxicity. Results and Discussion. NTCP analysis with the LKB-model using parameters m = 0.4, D50 = 30 Gy resulted for the volume dependence parameter (n) with LQ correction n = 0.87 and with USC correction n = 0.71. Using parameters m = 0.3, D 50 = 20 Gy n = 0.93 with LQ correction and n 0.83 with USC correction. In SBRT of lung tumours, NTCP modelling of lung toxicity comparing models (LQ,USC) for fractionation correction, shows that low dose contribute less and high dose more to the NTCP when using the USC-model. Comparing NTCP modelling of SBRT data and data from breast cancer, lung cancer and whole lung irradiation implies that the response of the lung is treatment specific. More data are however needed in order to have a more reliable modelling

  1. Sodium nitroprusside enhanced cardiopulmonary resuscitation improves short term survival in a porcine model of ischemic refractory ventricular fibrillation.

    Science.gov (United States)

    Yannopoulos, Demetris; Bartos, Jason A; George, Stephen A; Sideris, George; Voicu, Sebastian; Oestreich, Brett; Matsuura, Timothy; Shekar, Kadambari; Rees, Jennifer; Aufderheide, Tom P

    2017-01-01

    Sodium nitroprusside (SNP) enhanced CPR (SNPeCPR) demonstrates increased vital organ blood flow and survival in multiple porcine models. We developed a new, coronary occlusion/ischemia model of prolonged resuscitation, mimicking the majority of out-of-hospital cardiac arrests presenting with shockable rhythms. SNPeCPR will increase short term (4-h) survival compared to standard 2015 Advanced Cardiac Life Support (ACLS) guidelines in an ischemic refractory ventricular fibrillation (VF), prolonged CPR model. Sixteen anesthetized pigs had the ostial left anterior descending artery occluded leading to ischemic VF arrest. VF was untreated for 5min. Basic life support was performed for 10min. At minute 10 (EMS arrival), animals received either SNPeCPR (n=8) or standard ACLS (n=8). Defibrillation (200J) occurred every 3min. CPR continued for a total of 45min, then the balloon was deflated simulating revascularization. CPR continued until return of spontaneous circulation (ROSC) or a total of 60min, if unsuccessful. SNPeCPR animals received 2mg of SNP at minute 10 followed by 1mg every 5min until ROSC. Standard ACLS animals received 0.5mg epinephrine every 5min until ROSC. Primary endpoints were ROSC and 4-h survival. All SNPeCPR animals (8/8) achieved sustained ROSC versus 2/8 standard ACLS animals within one hour of resuscitation (p=0.04). The 4-h survival was significantly improved with SNPeCPR compared to standard ACLS, 7/8 versus 1/8 respectively, p=0.0019. SNPeCPR significantly improved ROSC and 4-h survival compared with standard ACLS CPR in a porcine model of prolonged ischemic, refractory VF cardiac arrest. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  2. A prognostic scoring model for survival after locoregional therapy in de novo stage IV breast cancer.

    Science.gov (United States)

    Kommalapati, Anuhya; Tella, Sri Harsha; Goyal, Gaurav; Ganti, Apar Kishor; Krishnamurthy, Jairam; Tandra, Pavan Kumar

    2018-05-02

    The role of locoregional treatment (LRT) remains controversial in de novo stage IV breast cancer (BC). We sought to analyze the role of LRT and prognostic factors of overall survival (OS) in de novo stage IV BC patients treated with LRT utilizing the National Cancer Data Base (NCDB). The objective of the current study is to create and internally validate a prognostic scoring model to predict the long-term OS for de novo stage IV BC patients treated with LRT. We included de novo stage IV BC patients reported to NCDB between 2004 and 2015. Patients were divided into LRT and no-LRT subsets. We randomized LRT subset to training and validation cohorts. In the training cohort, a seventeen-point prognostic scoring system was developed based on the hazard ratios calculated using Cox-proportional method. We stratified both training and validation cohorts into two "groups" [group 1 (0-7 points) and group 2 (7-17 points)]. Kaplan-Meier method and log-rank test were used to compare OS between the two groups. Our prognostic score was validated internally by comparing the OS between the respective groups in both the training and validation cohorts. Among 67,978 patients, LRT subset (21,200) had better median OS as compared to that of no-LRT (45 vs. 24 months; p < 0.0001). The group 1 and group 2 in the training cohort showed a significant difference in the 3-year OS (p < 0.0001) (68 vs. 26%). On internal validation, comparable OS was seen between the respective groups in each cohort (p = 0.77). Our prognostic scoring system will help oncologists to predict the prognosis in de novo stage IV BC patients treated with LRT. Although firm treatment-related conclusions cannot be made due to the retrospective nature of the study, LRT appears to be associated with a better OS in specific subgroups.

  3. Development and external validation of a risk-prediction model to predict 5-year overall survival in advanced larynx cancer.

    Science.gov (United States)

    Petersen, Japke F; Stuiver, Martijn M; Timmermans, Adriana J; Chen, Amy; Zhang, Hongzhen; O'Neill, James P; Deady, Sandra; Vander Poorten, Vincent; Meulemans, Jeroen; Wennerberg, Johan; Skroder, Carl; Day, Andrew T; Koch, Wayne; van den Brekel, Michiel W M

    2018-05-01

    TNM-classification inadequately estimates patient-specific overall survival (OS). We aimed to improve this by developing a risk-prediction model for patients with advanced larynx cancer. Cohort study. We developed a risk prediction model to estimate the 5-year OS rate based on a cohort of 3,442 patients with T3T4N0N+M0 larynx cancer. The model was internally validated using bootstrapping samples and externally validated on patient data from five external centers (n = 770). The main outcome was performance of the model as tested by discrimination, calibration, and the ability to distinguish risk groups based on tertiles from the derivation dataset. The model performance was compared to a model based on T and N classification only. We included age, gender, T and N classification, and subsite as prognostic variables in the standard model. After external validation, the standard model had a significantly better fit than a model based on T and N classification alone (C statistic, 0.59 vs. 0.55, P statistic to 0.68. A risk prediction model for patients with advanced larynx cancer, consisting of readily available clinical variables, gives more accurate estimations of the estimated 5-year survival rate when compared to a model based on T and N classification alone. 2c. Laryngoscope, 128:1140-1145, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

  4. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data.

    Science.gov (United States)

    Nasejje, Justine B; Mwambi, Henry; Dheda, Keertan; Lesosky, Maia

    2017-07-28

    Random survival forest (RSF) models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (CIF) are known to correct the bias in RSF models by separating the procedure for the best covariate to split on from that of the best split point search for the selected covariate. In this study, we compare the random survival forest model to the conditional inference model (CIF) using twenty-two simulated time-to-event datasets. We also analysed two real time-to-event datasets. The first dataset is based on the survival of children under-five years of age in Uganda and it consists of categorical covariates with most of them having more than two levels (many split-points). The second dataset is based on the survival of patients with extremely drug resistant tuberculosis (XDR TB) which consists of mainly categorical covariates with two levels (few split-points). The study findings indicate that the conditional inference forest model is superior to random survival forest models in analysing time-to-event data that consists of covariates with many split-points based on the values of the bootstrap cross-validated estimates for integrated Brier scores. However, conditional inference forests perform comparably similar to random survival forests models in analysing time-to-event data consisting of covariates with fewer split-points. Although survival forests are promising methods in analysing time-to-event data, it is important to identify the best forest model for analysis based on the nature of covariates of the dataset in question.

  5. A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data

    Directory of Open Access Journals (Sweden)

    Justine B. Nasejje

    2017-07-01

    Full Text Available Abstract Background Random survival forest (RSF models have been identified as alternative methods to the Cox proportional hazards model in analysing time-to-event data. These methods, however, have been criticised for the bias that results from favouring covariates with many split-points and hence conditional inference forests for time-to-event data have been suggested. Conditional inference forests (CIF are known to correct the bias in RSF models by separating the procedure for the best covariate to split on from that of the best split point search for the selected covariate. Methods In this study, we compare the random survival forest model to the conditional inference model (CIF using twenty-two simulated time-to-event datasets. We also analysed two real time-to-event datasets. The first dataset is based on the survival of children under-five years of age in Uganda and it consists of categorical covariates with most of them having more than two levels (many split-points. The second dataset is based on the survival of patients with extremely drug resistant tuberculosis (XDR TB which consists of mainly categorical covariates with two levels (few split-points. Results The study findings indicate that the conditional inference forest model is superior to random survival forest models in analysing time-to-event data that consists of covariates with many split-points based on the values of the bootstrap cross-validated estimates for integrated Brier scores. However, conditional inference forests perform comparably similar to random survival forests models in analysing time-to-event data consisting of covariates with fewer split-points. Conclusion Although survival forests are promising methods in analysing time-to-event data, it is important to identify the best forest model for analysis based on the nature of covariates of the dataset in question.

  6. External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

    Directory of Open Access Journals (Sweden)

    Ping Yu

    Full Text Available A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke.The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient.The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82, and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84. Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, p<0.001; 0.927 for model B, p = 0.008.The case-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

  7. A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures

    Science.gov (United States)

    Kossieris, Panagiotis; Makropoulos, Christos; Onof, Christian; Koutsoyiannis, Demetris

    2018-01-01

    Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 min time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-min time scale. The applicability of the methodology was assessed on a 5-min rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

  8. Edaravone improves survival and neurological outcomes after CPR in a ventricular fibrillation model of rats.

    Science.gov (United States)

    Qin, Tao; Lei, Ling-Yan; Li, Nuo; Shi, Fangying Ruan; Chen, Meng-Hua; Xie, Lu

    2016-10-01

    Overproduction of free radicals is a main factor contributing to cerebral injury after cardiac arrest (CA)/cardiopulmonary resuscitation (CPR). We sought to evaluate the impact of edaravone on the survival and neurological outcomes after CA/CPR in rats. Rats were subjected to CA following CPR. For survival study, the rats with restoration of spontaneous circulation (ROSC) were randomly allocated to one of the two groups (edaravone and saline group, n=20/each group) to received Edaravone (3 mg/kg) or normal saline. Another 10 rats without experiencing CA and CPR served as the sham group. Survival was observed for 72 hours and the neurological deficit score (NDS) was calculated at 12, 24, 48, and 72 hours after ROSC. For the neurological biochemical analysis study, rats were subjected to the same experimental procedures. Then, edaravone group (n=24), saline group (n=24) and sham group (n=16) were further divided into 4 subgroups according to the different time intervals (12, 24, 48, and 72 hours following ROSC). Brain tissues were harvested at relative time intervals for evaluation of oxidative stress, TUNEL staining and apoptotic gene expression. Edaravone improved postresuscitative survival time and neurological deficit, decreased brain malonylaldehyde level, increased superoxide dismutase activities, decreased proapoptotic gene expression of capase-8, capase-3, and Bax, and increased antiapoptotic Bcl-2 expression at 12, 24, 48, and 72 hours after ROSC. Edaravone improves survival and neurological outcomes following CPR via antioxidative and antiapoptotic effects in rats. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Intrastriatal Grafting of Chromospheres: Survival and Functional Effects in the 6-OHDA Rat Model of Parkinson's Disease.

    Directory of Open Access Journals (Sweden)

    Alejandra Boronat-García

    Full Text Available Cell replacement therapy in Parkinson's disease (PD aims at re-establishing dopamine neurotransmission in the striatum by grafting dopamine-releasing cells. Chromaffin cell (CC grafts produce some transitory improvements of functional motor deficits in PD animal models, and have the advantage of allowing autologous transplantation. However, CC grafts have exhibited low survival, poor functional effects and dopamine release compared to other cell types. Recently, chromaffin progenitor-like cells were isolated from bovine and human adult adrenal medulla. Under low-attachment conditions, these cells aggregate and grow as spheres, named chromospheres. Here, we found that bovine-derived chromosphere-cell cultures exhibit a greater fraction of cells with a dopaminergic phenotype and higher dopamine release than CC. Chromospheres grafted in a rat model of PD survived in 57% of the total grafted animals. Behavioral tests showed that surviving chromosphere cells induce a reduction in motor alterations for at least 3 months after grafting. Finally, we found that compared with CC, chromosphere grafts survive more and produce more robust and consistent motor improvements. However, further experiments would be necessary to determine whether the functional benefits induced by chromosphere grafts can be improved, and also to elucidate the mechanisms underlying the functional effects of the grafts.

  10. Modeling the decline of the Porcupine Caribou Herd, 1989-1998: the importance of survival vs. recruitment

    Directory of Open Access Journals (Sweden)

    Stephen M. Arthur

    2003-04-01

    Full Text Available The Porcupine caribou (Rangifer tarandus granti herd increased from approximately 100 000 animals during the 1970s to 178 000 in 1989, then declined to 129 000 by 1998. Our objective was to model the dynamics of this herd and investigate the potential that lower calf recruitment, as was observed during 1991-1993, produced the observed population changes. A deterministic model was prepared using estimates of birth and survival rates that reproduced the pattern of population growth from 1971-1989. Then, parameters were changed to simulate effects of lower calf recruitment and adult survival. Reducing recruitment for 3 years caused an immediate reduction in population size, but the population began to recover in 5-6 years. Even a dramatic temporary reduction in recruitment did not explain the continuing decline after 1995. In contrast, a slight but persistent reduction in adult survival caused a decline that closely followed the observed pattern. This suggests that survival of adults, and perhaps calves, has declined since the late 1980s.

  11. Using simulation to interpret a discrete time survival model in a complex biological system: fertility and lameness in dairy cows.

    Directory of Open Access Journals (Sweden)

    Christopher D Hudson

    Full Text Available The ever-growing volume of data routinely collected and stored in everyday life presents researchers with a number of opportunities to gain insight and make predictions. This study aimed to demonstrate the usefulness in a specific clinical context of a simulation-based technique called probabilistic sensitivity analysis (PSA in interpreting the results of a discrete time survival model based on a large dataset of routinely collected dairy herd management data. Data from 12,515 dairy cows (from 39 herds were used to construct a multilevel discrete time survival model in which the outcome was the probability of a cow becoming pregnant during a given two day period of risk, and presence or absence of a recorded lameness event during various time frames relative to the risk period amongst the potential explanatory variables. A separate simulation model was then constructed to evaluate the wider clinical implications of the model results (i.e. the potential for a herd's incidence rate of lameness to influence its overall reproductive performance using PSA. Although the discrete time survival analysis revealed some relatively large associations between lameness events and risk of pregnancy (for example, occurrence of a lameness case within 14 days of a risk period was associated with a 25% reduction in the risk of the cow becoming pregnant during that risk period, PSA revealed that, when viewed in the context of a realistic clinical situation, a herd's lameness incidence rate is highly unlikely to influence its overall reproductive performance to a meaningful extent in the vast majority of situations. Construction of a simulation model within a PSA framework proved to be a very useful additional step to aid contextualisation of the results from a discrete time survival model, especially where the research is designed to guide on-farm management decisions at population (i.e. herd rather than individual level.

  12. External Validation of a Case-Mix Adjustment Model for the Standardized Reporting of 30-Day Stroke Mortality Rates in China.

    Science.gov (United States)

    Yu, Ping; Pan, Yuesong; Wang, Yongjun; Wang, Xianwei; Liu, Liping; Ji, Ruijun; Meng, Xia; Jing, Jing; Tong, Xu; Guo, Li; Wang, Yilong

    2016-01-01

    A case-mix adjustment model has been developed and externally validated, demonstrating promise. However, the model has not been thoroughly tested among populations in China. In our study, we evaluated the performance of the model in Chinese patients with acute stroke. The case-mix adjustment model A includes items on age, presence of atrial fibrillation on admission, National Institutes of Health Stroke Severity Scale (NIHSS) score on admission, and stroke type. Model B is similar to Model A but includes only the consciousness component of the NIHSS score. Both model A and B were evaluated to predict 30-day mortality rates in 13,948 patients with acute stroke from the China National Stroke Registry. The discrimination of the models was quantified by c-statistic. Calibration was assessed using Pearson's correlation coefficient. The c-statistic of model A in our external validation cohort was 0.80 (95% confidence interval, 0.79-0.82), and the c-statistic of model B was 0.82 (95% confidence interval, 0.81-0.84). Excellent calibration was reported in the two models with Pearson's correlation coefficient (0.892 for model A, pcase-mix adjustment model could be used to effectively predict 30-day mortality rates in Chinese patients with acute stroke.

  13. Applying the Transactional Stress and Coping Model to Sickle Cell Disorder and Insulin-Dependent Diabetes Mellitus: Identifying Psychosocial Variables Related to Adjustment and Intervention

    Science.gov (United States)

    Hocking, Matthew C.; Lochman, John E.

    2005-01-01

    This review paper examines the literature on psychosocial factors associated with adjustment to sickle cell disease and insulin-dependent diabetes mellitus in children through the framework of the transactional stress and coping (TSC) model. The transactional stress and coping model views adaptation to a childhood chronic illness as mediated by…

  14. Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

    Science.gov (United States)

    Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

    2017-10-01

    Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

  15. Kriging modeling and SPSA adjusting PID with KPWF compensator control of IPMC gripper for mm-sized objects

    Science.gov (United States)

    Chen, Yang; Hao, Lina; Yang, Hui; Gao, Jinhai

    2017-12-01

    Ionic polymer metal composite (IPMC) as a new smart material has been widely concerned in the micromanipulation field. In this paper, a novel two-finger gripper which contains an IPMC actuator and an ultrasensitive force sensor is proposed and fabricated. The IPMC as one finger of the gripper for mm-sized objects can achieve gripping and releasing motion, and the other finger works not only as a support finger but also as a force sensor. Because of the feedback signal of the force sensor, this integrated actuating and sensing gripper can complete gripping miniature objects in millimeter scale. The Kriging model is used to describe nonlinear characteristics of the IPMC for the first time, and then the control scheme called simultaneous perturbation stochastic approximation adjusting a proportion integration differentiation parameter controller with a Kriging predictor wavelet filter compensator is applied to track the gripping force of the gripper. The high precision force tracking in the foam ball manipulation process is obtained on a semi-physical experimental platform, which demonstrates that this gripper for mm-sized objects can work well in manipulation applications.

  16. A comparison of two-component and quadratic models to assess survival of irradiated stage-7 oocytes of Drosophila melanogaster

    International Nuclear Information System (INIS)

    Peres, C.A.; Koo, J.O.

    1981-01-01

    In this paper, the quadratic model to analyse data of this kind, i.e. S/S 0 = exp(-αD-bD 2 ), where S and Ssub(o) are defined as before is proposed is shown that the same biological interpretation can be given to the parameters α and A and to the parameters β and B. Furthermore it is shown that the quadratic model involves one probabilistic stage more than the two-component model, and therefore the quadratic model would perhaps be more appropriate as a dose-response model for survival of irradiated stage-7 oocytes of Drosophila melanogaster. In order to apply these results, the data presented by Sankaranarayanan and Sankaranarayanan and Volkers are reanalysed using the quadratic model. It is shown that the quadratic model fits better than the two-component model to the data in most situations. (orig./AJ)

  17. Neuregulin-1/erbB-activation improves cardiac function and survival in models of ischemic, dilated, and viral cardiomyopathy.

    Science.gov (United States)

    Liu, Xifu; Gu, Xinhua; Li, Zhaoming; Li, Xinyan; Li, Hui; Chang, Jianjie; Chen, Ping; Jin, Jing; Xi, Bing; Chen, Denghong; Lai, Donna; Graham, Robert M; Zhou, Mingdong

    2006-10-03

    We evaluated the therapeutic potential of a recombinant 61-residue neuregulin-1 (beta2a isoform) receptor-active peptide (rhNRG-1) in multiple animal models of heart disease. Activation of the erbB family of receptor tyrosine kinases by rhNRG-1 could provide a treatment option for heart failure, because neuregulin-stimulated erbB2/erbB4 heterodimerization is not only critical for myocardium formation in early heart development but prevents severe dysfunction of the adult heart and premature death. Disabled erbB-signaling is also implicated in the transition from compensatory hypertrophy to failure, whereas erbB receptor-activation promotes myocardial cell growth and survival and protects against anthracycline-induced cardiomyopathy. rhNRG-1 was administered IV to animal models of ischemic, dilated, and viral cardiomyopathy, and cardiac function and survival were evaluated. Short-term intravenous administration of rhNRG-1 to normal dogs and rats did not alter hemodynamics or cardiac contractility. In contrast, rhNRG-1 improved cardiac performance, attenuated pathological changes, and prolonged survival in rodent models of ischemic, dilated, and viral cardiomyopathy, with the survival benefits in the ischemic model being additive to those of angiotensin-converting enzyme inhibitor therapy. In addition, despite continued pacing, rhNRG-1 produced global improvements in cardiac function in a canine model of pacing-induced heart failure. These beneficial effects make rhNRG-1 promising as a broad-spectrum therapeutic for the treatment of heart failure due to a variety of common cardiac diseases.

  18. The use of simple reparameterizations to improve the efficiency of Markov chain Monte Carlo estimation for multilevel models with applications to discrete time survival models.

    Science.gov (United States)

    Browne, William J; Steele, Fiona; Golalizadeh, Mousa; Green, Martin J

    2009-06-01

    We consider the application of Markov chain Monte Carlo (MCMC) estimation methods to random-effects models and in particular the family of discrete time survival models. Survival models can be used in many situations in the medical and social sciences and we illustrate their use through two examples that differ in terms of both substantive area and data structure. A multilevel discrete time survival analysis involves expanding the data set so that the model can be cast as a standard multilevel binary response model. For such models it has been shown that MCMC methods have advantages in terms of reducing estimate bias. However, the data expansion results in very large data sets for which MCMC estimation is often slow and can produce chains that exhibit poor mixing. Any way of improving the mixing will result in both speeding up the methods and more confidence in the estimates that are produced. The MCMC methodological literature is full of alternative algorithms designed to improve mixing of chains and we describe three reparameterization techniques that are easy to implement in available software. We consider two examples of multilevel survival analysis: incidence of mastitis in dairy cattle and contraceptive use dynamics in Indonesia. For each application we show where the reparameterization techniques can be used and assess their performance.

  19. Modeling nest survival of cavity-nesting birds in relation to postfire salvage logging

    Science.gov (United States)

    Vicki Saab; Robin E. Russell; Jay Rotella; Jonathan G. Dudley

    2011-01-01

    Salvage logging practices in recently burned forests often have direct effects on species associated with dead trees, particularly cavity-nesting birds. As such, evaluation of postfire management practices on nest survival rates of cavity nesters is necessary for determining conservation strategies. We monitored 1,797 nests of 6 cavity-nesting bird species: Lewis'...

  20. Using the Q10 model to simulate E. coli survival in cowpats on grazing lands

    Science.gov (United States)

    Microbiological quality of surface waters can be affected by microbial load in runoff from grazing lands. This effect, with other factors, depends on the survival of microorganisms in animal waste deposited on pastures. Since temperature is a leading environmental parameter affec...

  1. The relationship between the C-statistic of a risk-adjustment model and the accuracy of hospital report cards: a Monte Carlo Study.

    Science.gov (United States)

    Austin, Peter C; Reeves, Mathew J

    2013-03-01

    Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk adjustment in hospital report cards. Many applied researchers use the c-statistic (equivalent to the area under the receiver operating characteristic curve) of the logistic regression model as a measure of the credibility and accuracy of hospital report cards. To determine the relationship between the c-statistic of a risk-adjustment model and the accuracy of hospital report cards. Monte Carlo simulations were used to examine this issue. We examined the influence of 3 factors on the accuracy of hospital report cards: the c-statistic of the logistic regression model used for risk adjustment, the number of hospitals, and the number of patients treated at each hospital. The parameters used to generate the simulated datasets came from analyses of patients hospitalized with a diagnosis of acute myocardial infarction in Ontario, Canada. The c-statistic of the risk-adjustment model had, at most, a very modest impact on the accuracy of hospital report cards, whereas the number of patients treated at each hospital had a much greater impact. The c-statistic of a risk-adjustment model should not be used to assess the accuracy of a hospital report card.

  2. Dimethylaminoparthenolide and gemcitabine: a survival study using a genetically engineered mouse model of pancreatic cancer

    International Nuclear Information System (INIS)

    Yip-Schneider, Michele T; Wu, Huangbing; Stantz, Keith; Agaram, Narasimhan; Crooks, Peter A; Schmidt, C Max

    2013-01-01

    Pancreatic cancer remains one of the deadliest cancers due to lack of early detection and absence of effective treatments. Gemcitabine, the current standard-of-care chemotherapy for pancreatic cancer, has limited clinical benefit. Treatment of pancreatic cancer cells with gemcitabine has been shown to induce the activity of the transcription factor nuclear factor-kappaB (NF-κB) which regulates the expression of genes involved in the inflammatory response and tumorigenesis. It has therefore been proposed that gemcitabine-induced NF-κB activation may result in chemoresistance. We hypothesize that NF-κB suppression by the novel inhibitor dimethylaminoparthenolide (DMAPT) may enhance the effect of gemcitabine in pancreatic cancer. The efficacy of DMAPT and gemcitabine was evaluated in a chemoprevention trial using the mutant Kras and p53-expressing LSL-Kras G12D/+ ; LSL-Trp53 R172H ; Pdx-1-Cre mouse model of pancreatic cancer. Mice were randomized to treatment groups (placebo, DMAPT [40 mg/kg/day], gemcitabine [50 mg/kg twice weekly], and the combination DMAPT/gemcitabine). Treatment was continued until mice showed signs of ill health at which time they were sacrificed. Plasma cytokine levels were determined using a Bio-Plex immunoassay. Statistical tests used included log-rank test, ANOVA with Dunnett’s post-test, Student’s t-test, and Fisher exact test. Gemcitabine or the combination DMAPT/gemcitabine significantly increased median survival and decreased the incidence and multiplicity of pancreatic adenocarcinomas. The DMAPT/gemcitabine combination also significantly decreased tumor size and the incidence of metastasis to the liver. No significant differences in the percentages of normal pancreatic ducts or premalignant pancreatic lesions were observed between the treatment groups. Pancreata in which no tumors formed were analyzed to determine the extent of pre-neoplasia; mostly normal ducts or low grade pancreatic lesions were observed, suggesting prevention

  3. Cost-effectiveness Analysis in R Using a Multi-state Modeling Survival Analysis Framework: A Tutorial.

    Science.gov (United States)

    Williams, Claire; Lewsey, James D; Briggs, Andrew H; Mackay, Daniel F

    2017-05-01

    This tutorial provides a step-by-step guide to performing cost-effectiveness analysis using a multi-state modeling approach. Alongside the tutorial, we provide easy-to-use functions in the statistics package R. We argue that this multi-state modeling approach using a package such as R has advantages over approaches where models are built in a spreadsheet package. In particular, using a syntax-based approach means there is a written record of what was done and the calculations are transparent. Reproducing the analysis is straightforward as the syntax just needs to be run again. The approach can be thought of as an alternative way to build a Markov decision-analytic model, which also has the option to use a state-arrival extended approach. In the state-arrival extended multi-state model, a covariate that represents patients' history is included, allowing the Markov property to be tested. We illustrate the building of multi-state survival models, making predictions from the models and assessing fits. We then proceed to perform a cost-effectiveness analysis, including deterministic and probabilistic sensitivity analyses. Finally, we show how to create 2 common methods of visualizing the results-namely, cost-effectiveness planes and cost-effectiveness acceptability curves. The analysis is implemented entirely within R. It is based on adaptions to functions in the existing R package mstate to accommodate parametric multi-state modeling that facilitates extrapolation of survival curves.

  4. Calculating the 30-day survival rate in acute myocardial infarction: should we use the treatment chain or the hospital catchment model?

    Directory of Open Access Journals (Sweden)

    Jan Norum

    2017-12-01

    Full Text Available Introduction: Acute myocardial infarction (AMI is a potentially deadly disease and significant efforts have been concentrated on improving hospital performance. A 30-day survival rate has become a key quality of care indicator. In Northern Norway, some patients undergoing AMI are directly transferred to the Regional Cardiac Intervention Center at the University Hospital of North Norway in Tromsø. Here, coronary angiography and percutaneous coronary intervention is performed. Consequently, local hospitals may be bypassed in the treatment chain, generating differences in case mix, and making the treatment chain model difficult to interpret. We aimed to compare the treatment chain model with an alternative based on patients’ place of living. Methods: Between 2013 and 2015, a total of 3,155 patients were registered in the Norwegian Patient Registry database. All patients were categorized according to their local hospital’s catchment area. The method of Guo-Romano, with an indifference interval of 0.02, was used to test whether a hospital was an outlier or not. We adjusted for age, sex, comorbidity, and number of prior hospitalizations. Conclusions: We revealed the 30-day AMI survival figure ranging between 88.0% and 93.5% (absolute difference 5.5% using the hospital catchment method. The treatment chain rate ranged between 86.0% and 94.0% (absolute difference 8.0%. The latter figure is the one published as the National Quality of Care Measure in Norway. Local hospitals may get negative attention even though their catchment area is well served. We recommend the hospital catchment method as the first choice when measuring equality of care.

  5. In search of laterally heterogeneous viscosity models of Glacial Isostatic Adjustment with the ICE-6G_C global ice history model

    Science.gov (United States)

    Li, Tanghua; Wu, Patrick; Steffen, Holger; Wang, Hansheng

    2018-05-01

    Most models of Glacial Isostatic Adjustment (GIA) assume that the Earth is laterally homogeneous. However, seismic and geological observations clearly show that the Earth's mantle is laterally heterogeneous. Previous studies of GIA with lateral heterogeneity mostly focused on its effect or sensitivity on GIA predictions, and it is not clear to what extent can lateral heterogeneity solve the misfits between GIA predictions and observations. Our aim is to search for the best 3D viscosity models that can simultaneously fit the global relative sea-level (RSL) data, the peak uplift rates (u-dot from GNSS) and peak gravity-rate-of-change (g-dot from the GRACE satellite mission) in Laurentia and Fennoscandia. However, the search is dependent on the ice and viscosity model inputs - the latter depends on the background viscosity and the seismic tomography models used. In this paper, the ICE-6G_C ice model, with Bunge & Grand's seismic tomography model and background viscosity models close to VM5 will be assumed. A Coupled Laplace-Finite Element Method is used to compute gravitationally self-consistent sea level change with time dependent coastlines and rotational feedback in addition to changes in deformation, gravity and the state of stress. Several laterally heterogeneous models are found to fit the global sea level data better than laterally homogeneous models. Two of these laterally heterogeneous models also fit the ICE-6G_C peak g-dot and u-dot rates observed in Laurentia simultaneously. However, even with the introduction of lateral heterogeneity, no model that is able to fit the present-day g-dot and uplift rate data in Fennoscandia has been found. Therefore, either the ice history of ICE-6G_C in Fennoscandia and Barent Sea needs some modifications, or the sub-lithospheric property/non-thermal effect underneath northern Europe must be different from that underneath Laurentia.

  6. Systemic administration of bevacizumab prolongs survival in an in vivo model of platinum pre-treated ovarian cancer

    Science.gov (United States)

    REIN, DANIEL T.; VOLKMER, ANNE KATHRIN; VOLKMER, JENS; BEYER, INES M.; JANNI, WOLFGANG; FLEISCH, MARKUS C.; WELTER, ANNE KATHRIN; BAUERSCHLAG, DIRK; SCHÖNDORF, THOMAS; BREIDENBACH, MARTINA

    2012-01-01

    Ovarian cancer patients often suffer from malignant ascites and pleural effusion. Apart from worsening the outcome, this condition frequently impairs the quality of life in patients who are already distressed by ovarian cancer. This study investigated whether single intraperitoneal administration of the anti-VEGF antibody bevacizumab is capable of reducing the ascites-related body surface and prolonging survival. The study was performed in an orthotopic murine model of peritoneal disseminated platin-resistant ovarian cancer. Mice were treated with bevacizumab and/or paclitaxel or buffer (control). Reduction of body surface and increased survival rates were assessed as therapeutic success. Survival of mice in all treatment groups was significantly enhanced when compared to the non-treatment control group. The combination of paclitaxel plus bevacizumab significantly improved body surface as well as overall survival in comparison to a treatment with only one of the drugs. Treatment of malignant effusion with a single dose of bevacizumab as an intraperitoneal application, with or without cytostatic co-medication, may be a powerful alternative to systemic treatment. PMID:22740945

  7. Survival of probiotic lactobacilli in the upper gastrointestinal tract using an in vitro gastric model of digestion.

    Science.gov (United States)

    Lo Curto, Alberto; Pitino, Iole; Mandalari, Giuseppina; Dainty, Jack Richard; Faulks, Richard Martin; John Wickham, Martin Sean

    2011-10-01

    The aim of this study was to investigate survival of three commercial probiotic strains (Lactobacillus casei subsp. shirota, L. casei subsp. immunitas, Lactobacillus acidophilus subsp. johnsonii) in the human upper gastrointestinal (GI) tract using a dynamic gastric model (DGM) of digestion followed by incubation under duodenal conditions. Water and milk were used as food matrices and survival was evaluated in both logarithmic and stationary phase. The % of recovery in logarithmic phase ranged from 1.0% to 43.8% in water for all tested strains, and from 80.5% to 197% in milk. Higher survival was observed in stationary phase for all strains. L. acidophilus subsp. johnsonii showed the highest survival rate in both water (93.9%) and milk (202.4%). Lactic acid production was higher in stationary phase, L. casei subsp. shirota producing the highest concentration (98.2 mM) after in vitro gastric plus duodenal digestion. Copyright © 2011 Elsevier Ltd. All rights reserved.

  8. Effect of Electroacupuncture at The Zusanli Point (Stomach-36) on Dorsal Random Pattern Skin Flap Survival in a Rat Model.

    Science.gov (United States)

    Wang, Li-Ren; Cai, Le-Yi; Lin, Ding-Sheng; Cao, Bin; Li, Zhi-Jie

    2017-10-01

    Random skin flaps are commonly used for wound repair and reconstruction. Electroacupuncture at The Zusanli point could enhance microcirculation and blood perfusion in random skin flaps. To determine whether electroacupuncture at The Zusanli point can improve the survival of random skin flaps in a rat model. Thirty-six male Sprague Dawley rats were randomly divided into 3 groups: control group (no electroacupuncture), Group A (electroacupuncture at a nonacupoint near The Zusanli point), and Group B (electroacupuncture at The Zusanli point). McFarlane flaps were established. On postoperative Day 2, malondialdehyde (MDA) and superoxide dismutase were detected. The flap survival rate was evaluated, inflammation was examined in hematoxylin and eosin-stained slices, and the expression of vascular endothelial growth factor (VEGF) was measured immunohistochemically on Day 7. The mean survival area of the flaps in Group B was significantly larger than that in the control group and Group A. Superoxide dismutase activity and VEGF expression level were significantly higher in Group B than those in the control group and Group A, whereas MDA and inflammation levels in Group B were significantly lower than those in the other 2 groups. Electroacupuncture at The Zusanli point can effectively improve the random flap survival.

  9. Assessing the effect of quantitative and qualitative predictors on gastric cancer individuals survival using hierarchical artificial neural network models.

    Science.gov (United States)

    Amiri, Zohreh; Mohammad, Kazem; Mahmoudi, Mahmood; Parsaeian, Mahbubeh; Zeraati, Hojjat

    2013-01-01

    There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models. This study was designed and conducted to examine the application of these models in order to determine the survival of gastric cancer patients, in comparison to the Cox proportional hazards model. We studied the postoperative survival of 330 gastric cancer patients who suffered surgery at a surgical unit of the Iran Cancer Institute over a five-year period. Covariates of age, gender, history of substance abuse, cancer site, type of pathology, presence of metastasis, stage, and number of complementary treatments were entered in the models, and survival probabilities were calculated at 6, 12, 18, 24, 36, 48, and 60 months using the Cox proportional hazards and neural network models. We estimated coefficients of the Cox model and the weights in the neural network (with 3, 5, and 7 nodes in the hidden layer) in the training group, and used them to derive predictions in the study group. Predictions with these two methods were compared with those of the Kaplan-Meier product limit estimator as the gold standard. Comparisons were performed with the Friedman and Kruskal-Wallis tests. Survival probabilities at different times were determined using the Cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the Kaplan-Meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between Cox and Kaplan-Meier (P neural network, and the neural network and the standard (Kaplan-Meier), as well as better accuracy for the neural network (with 3 nodes in the hidden layer

  10. Mammographic Density Reduction as a Prognostic Marker for Postmenopausal Breast Cancer: Results Using a Joint Longitudinal-Survival Modeling Approach.

    Science.gov (United States)

    Andersson, Therese M-L; Crowther, Michael J; Czene, Kamila; Hall, Per; Humphreys, Keith

    2017-11-01

    Previous studies have linked reductions in mammographic density after a breast cancer diagnosis to an improved prognosis. These studies focused on short-term change, using a 2-stage process, treating estimated change as a fixed covariate in a survival model. We propose the use of a joint longitudinal-survival model. This enables us to model long-term trends in density while accounting for dropout as well as for measurement error. We studied the change in mammographic density after a breast cancer diagnosis and its association with prognosis (measured by cause-specific mortality), overall and with respect to hormone replacement therapy and tamoxifen treatment. We included 1,740 women aged 50-74 years, diagnosed with breast cancer in Sweden during 1993-1995, with follow-up until 2008. They had a total of 6,317 mammographic density measures available from the first 5 years of follow-up, including baseline measures. We found that the impact of the withdrawal of hormone replacement therapy on density reduction was larger than that of tamoxifen treatment. Unlike previous studies, we found that there was an association between density reduction and survival, both for tamoxifen-treated women and women who were not treated with tamoxifen. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

  11. Adjustable, physiological ventricular restraint improves left ventricular mechanics and reduces dilatation in an ovine model of chronic heart failure.

    Science.gov (United States)

    Ghanta, Ravi K; Rangaraj, Aravind; Umakanthan, Ramanan; Lee, Lawrence; Laurence, Rita G; Fox, John A; Bolman, R Morton; Cohn, Lawrence H; Chen, Frederick Y

    2007-03-13

    Ventricular restraint is a nontransplantation surgical treatment for heart failure. The effect of varying restraint level on left ventricular (LV) mechanics and remodeling is not known. We hypothesized that restraint level may affect therapy efficacy. We studied the immediate effect of varying restraint levels in an ovine heart failure model. We then studied the long-term effect of restraint applied over a 2-month period. Restraint level was quantified by use of fluid-filled epicardial balloons placed around the ventricles and measurement of balloon luminal pressure at end diastole. At 4 different restraint levels (0, 3, 5, and 8 mm Hg), transmural myocardial pressure (P(tm)) and indices of myocardial oxygen consumption (MVO2) were determined in control (n=5) and ovine heart failure (n=5). Ventricular restraint therapy decreased P(tm) and MVO2, and improved mechanical efficiency. An optimal physiological restraint level of 3 mm Hg was identified to maximize improvement without an adverse affect on systemic hemodynamics. At this optimal level, end-diastolic P(tm) and MVO2 indices decreased by 27% and 20%, respectively. The serial longitudinal effects of optimized ventricular restraint were then evaluated in ovine heart failure with (n=3) and without (n=3) restraint over 2 months. Optimized ventricular restraint prevented and reversed pathological LV dilatation (130+/-22 mL to 91+/-18 mL) and improved LV ejection fraction (27+/-3% to 43+/-5%). Measured restraint level decreased over time as the LV became smaller, and reverse remodeling slowed. Ventricular restraint level affects the degree of decrease in P(tm), the degree of decrease in MVO2, and the rate of LV reverse remodeling. Periodic physiological adjustments of restraint level may be required for optimal restraint therapy efficacy.

  12. Cost Effectiveness of Childhood Cochlear Implantation and Deaf Education in Nicaragua: A Disability Adjusted Life Year Model.

    Science.gov (United States)

    Saunders, James E; Barrs, David M; Gong, Wenfeng; Wilson, Blake S; Mojica, Karen; Tucci, Debara L

    2015-09-01

    Cochlear implantation (CI) is a common intervention for severe-to-profound hearing loss in high-income countries, but is not commonly available to children in low resource environments. Owing in part to the device costs, CI has been assumed to be less economical than deaf education for low resource countries. The purpose of this study is to compare the cost effectiveness of the two interventions for children with severe-to-profound sensorineural hearing loss (SNHL) in a model using disability adjusted life years (DALYs). Cost estimates were derived from published data, expert opinion, and known costs of services in Nicaragua. Individual costs and lifetime DALY estimates with a 3% discounting rate were applied to both two interventions. Sensitivity analysis was implemented to evaluate the effect on the discounted cost of five key components: implant cost, audiology salary, speech therapy salary, number of children implanted per year, and device failure probability. The costs per DALY averted are $5,898 and $5,529 for CI and deaf education, respectively. Using standards set by the WHO, both interventions are cost effective. Sensitivity analysis shows that when all costs set to maximum estimates, CI is still cost effective. Using a conservative DALY analysis, both CI and deaf education are cost-effective treatment alternatives for severe-to-profound SNHL. CI intervention costs are not only influenced by the initial surgery and device costs but also by rehabilitation costs and the lifetime maintenance, device replacement, and battery costs. The major CI cost differences in this low resource setting were increased initial training and infrastructure costs, but lower medical personnel and surgery costs.

  13. Graft survival and cytokine production profile after limbal transplantation in the experimental mouse model

    Czech Academy of Sciences Publication Activity Database

    Lenčová, Anna; Pokorná, Kateřina; Zajícová, Alena; Krulová, Magdalena; Filipec, M.; Holáň, Vladimír

    2011-01-01

    Roč. 24, č. 3 (2011), s. 189-194 ISSN 0966-3274 R&D Projects: GA AV ČR KAN200520804; GA MŠk 1M0506; GA ČR GD310/08/H077 Institutional research plan: CEZ:AV0Z50520514 Keywords : limbal transplantation * graft survival * cytokine response Subject RIV: EC - Immunology Impact factor: 1.459, year: 2011

  14. Model description and evaluation of the mark-recapture survival model used to parameterize the 2012 status and threats analysis for the Florida manatee (Trichechus manatus latirostris)

    Science.gov (United States)

    Langtimm, Catherine A.; Kendall, William L.; Beck, Cathy A.; Kochman, Howard I.; Teague, Amy L.; Meigs-Friend, Gaia; Peñaloza, Claudia L.

    2016-11-30

    This report provides supporting details and evidence for the rationale, validity and efficacy of a new mark-recapture model, the Barker Robust Design, to estimate regional manatee survival rates used to parameterize several components of the 2012 version of the Manatee Core Biological Model (CBM) and Threats Analysis (TA).  The CBM and TA provide scientific analyses on population viability of the Florida manatee subspecies (Trichechus manatus latirostris) for U.S. Fish and Wildlife Service’s 5-year reviews of the status of the species as listed under the Endangered Species Act.  The model evaluation is presented in a standardized reporting framework, modified from the TRACE (TRAnsparent and Comprehensive model Evaluation) protocol first introduced for environmental threat analyses.  We identify this new protocol as TRACE-MANATEE SURVIVAL and this model evaluation specifically as TRACE-MANATEE SURVIVAL, Barker RD version 1. The longer-term objectives of the manatee standard reporting format are to (1) communicate to resource managers consistent evaluation information over sequential modeling efforts; (2) build understanding and expertise on the structure and function of the models; (3) document changes in model structures and applications in response to evolving management objectives, new biological and ecological knowledge, and new statistical advances; and (4) provide greater transparency for management and research review.

  15. Transoral endoscopic esophageal myotomy based on esophageal function testing in a survival porcine model.

    Science.gov (United States)

    Perretta, Silvana; Dallemagne, Bernard; Donatelli, Gianfranco; Diemunsch, Pierre; Marescaux, Jacques

    2011-01-01

    The most effective treatment of achalasia is Heller myotomy. To explore a submucosal endoscopic myotomy technique tailored on esophageal physiology testing and to compare it with the open technique. Prospective acute and survival comparative study in pigs (n = 12; 35 kg). University animal research center. Eight acute-4 open and 4 endoscopic-myotomies followed by 4 survival endoscopic procedures. Preoperative and postoperative manometry; esophagogastric junction (EGJ) distensibility before and after selective division of muscular fibers at the EGJ and after the myotomy was prolonged to a standard length by using the EndoFLIP Functional Lumen Imaging Probe (Crospon, Galway, Ireland). All procedures were successful, with no intraoperative and postoperative complications. In the survival group, the animals recovered promptly from surgery. Postoperative manometry demonstrated a 50% drop in mean lower esophageal sphincter pressure (LESp) in the endoscopic group (mean preoperative LESp, 22.2 ± 3.3 mm Hg; mean postoperative LESp, 11.34 ± 2.7 mm Hg; P open procedure group (mean preoperative LESp, 24.2 ± 3.2 mm Hg; mean postoperative LESp, 7.4 ± 4 mm Hg; P myotomy is feasible and safe. The lack of a significant difference in EGJ distensibility between the open and endoscopic procedure is very appealing. Were it to be perfected in a human population, this endoscopic approach could suggest a new strategy in the treatment of selected achalasia patients. Copyright © 2011 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

  16. Risk adjustment models for interhospital comparison of CS rates using Robson's ten group classification system and other socio-demographic and clinical variables.

    Science.gov (United States)

    Colais, Paola; Fantini, Maria P; Fusco, Danilo; Carretta, Elisa; Stivanello, Elisa; Lenzi, Jacopo; Pieri, Giulia; Perucci, Carlo A

    2012-06-21

    Caesarean section (CS) rate is a quality of health care indicator frequently used at national and international level. The aim of this study was to assess whether adjustment for Robson's Ten Group Classification System (TGCS), and clinical and socio-demographic variables of the mother and the fetus is necessary for inter-hospital comparisons of CS rates. The study population includes 64,423 deliveries in Emilia-Romagna between January 1, 2003 and December 31, 2004, classified according to theTGCS. Poisson regression was used to estimate crude and adjusted hospital relative risks of CS compared to a reference category. Analyses were carried out in the overall population and separately according to the Robson groups (groups I, II, III, IV and V-X combined). Adjusted relative risks (RR) of CS were estimated using two risk-adjustment models; the first (M1) including the TGCS group as the only adjustment factor; the second (M2) including in addition demographic and clinical confounders identified using a stepwise selection procedure. Percentage variations between crude and adjusted RRs by hospital were calculated to evaluate the confounding effect of covariates. The percentage variations from crude to adjusted RR proved to be similar in M1 and M2 model. However, stratified analyses by Robson's classification groups showed that residual confounding for clinical and demographic variables was present in groups I (nulliparous, single, cephalic, ≥37 weeks, spontaneous labour) and III (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, spontaneous labour) and IV (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, induced or CS before labour) and to a minor extent in groups II (nulliparous, single, cephalic, ≥37 weeks, induced or CS before labour) and IV (multiparous, excluding previous CS, single, cephalic, ≥37 weeks, induced or CS before labour). The TGCS classification is useful for inter-hospital comparison of CS section rates, but

  17. Cancer survival among Alaska Native people.

    Science.gov (United States)

    Nash, Sarah H; Meisner, Angela L W; Zimpelman, Garrett L; Barry, Marc; Wiggins, Charles L

    2018-03-26

    Recent cancer survival trends among American Indian and Alaska Native (AN) people are not well understood; survival has not been reported among AN people since 2001. This study examined cause-specific survival among AN cancer patients for lung, colorectal, female breast, prostate, and kidney cancers. It evaluated whether survival differed between cancers diagnosed in 1992-2002 (the earlier period) and cancers diagnosed in 2003-2013 (the later period) and by the age at diagnosis (<65 vs ≥65 years), stage at diagnosis (local or regional/distant/unknown), and sex. Kaplan-Meier and Cox proportional hazards models were used to estimate univariate and multivariate-adjusted cause-specific survival for each cancer. An improvement was observed in 5-year survival over time from lung cancer (hazard ratio [HR] for the later period vs the earlier period, 0.83; 95% confidence interval [CI], 0.72-0.97), and a marginally nonsignificant improvement was observed for colorectal cancer (HR, 0.81; 95% CI, 0.66-1.01). Site-specific differences in survival were observed by age and stage at diagnosis. This study presents the first data on cancer survival among AN people in almost 2 decades. During this time, AN people have experienced improvements in survival from lung and colorectal cancers. The reasons for these improvements may include increased access to care (including screening) as well as improvements in treatment. Improving cancer survival should be a priority for reducing the burden of cancer among AN people and eliminating cancer disparities. Cancer 2018. © 2018 American Cancer Society. © 2018 American Cancer Society.

  18. Iterative Bayesian Model Averaging: a method for the application of survival analysis to high-dimensional microarray data

    Directory of Open Access Journals (Sweden)

    Raftery Adrian E

    2009-02-01

    Full Text Available Abstract Background Microarray technology is increasingly used to identify potential biomarkers for cancer prognostics and diagnostics. Previously, we have developed the iterative Bayesian Model Averaging (BMA algorithm for use in classification. Here, we extend the iterative BMA algorithm for application to survival analysis on high-dimensional microarray data. The main goal in applying survival analysis to microarray data is to determine a highly predictive model of patients' time to event (such as death, relapse, or metastasis using a small number of selected genes. Our multivariate procedure combines the effectiveness of multiple contending models by calculating the weighted average of their posterior probability distributions. Our results demonstrate that our iterative BMA algorithm for survival analysis achieves high prediction accuracy while consistently selecting a small and cost-effective number of predictor genes. Results We applied the iterative BMA algorithm to two cancer datasets: breast cancer and diffuse large B-cell lymphoma (DLBCL data. On the breast cancer data, the algorithm selected a total of 15 predictor genes across 84 contending models from the training data. The maximum likelihood estimates of the selected genes and the posterior probabilities of the selected models from the training data were used to divide patients in the test (or validation dataset into high- and low-risk categories. Using the genes and models determined from the training data, we assigned patients from the test data into highly distinct risk groups (as indicated by a p-value of 7.26e-05 from the log-rank test. Moreover, we achieved comparable results using only the 5 top selected genes with 100% posterior probabilities. On the DLBCL data, our iterative BMA procedure selected a total of 25 genes across 3 contending models from the training data. Once again, we assigned the patients in the validation set to significantly distinct risk groups (p

  19. Biostatistics series module 9: Survival analysis

    Directory of Open Access Journals (Sweden)

    Avijit Hazra

    2017-01-01

    Full Text Available Survival analysis is concerned with “time to event“ data. Conventionally, it dealt with cancer death as the event in question, but it can handle any event occurring over a time frame, and this need not be always adverse in nature. When the outcome of a study is the time to an event, it is often not possible to wait until the event in question has happened to all the subjects, for example, until all are dead. In addition, subjects may leave the study prematurely. Such situations lead to what is called censored observations as complete information is not available for these subjects. The data set is thus an assemblage of times to the event in question and times after which no more information on the individual is available. Survival analysis methods are the only techniques capable of handling censored observations without treating them as missing data. They also make no assumption regarding normal distribution of time to event data. Descriptive methods for exploring survival times in a sample include life table and Kaplan–Meier techniques as well as various kinds of distribution fitting as advanced modeling techniques. The Kaplan–Meier cumulative survival probability over time plot has become the signature plot for biomedical survival analysis. Several techniques are available for comparing the survival experience in two or more groups – the log-rank test is popularly used. This test can also be used to produce an odds ratio as an estimate of risk of the event in the test group; this is called hazard ratio (HR. Limitations of the traditional log-rank test have led to various modifications and enhancements. Finally, survival analysis offers different regression models for estimating the impact of multiple predictors on survival. Cox's proportional hazard model is the most general of the regression methods that allows the hazard function to be modeled on a set of explanatory variables without making restrictive assumptions concerning the

  20. Growth, survival, and peptidolytic activity of Lactobacillus plantarum I91 in a hard-cheese model.

    Science.gov (United States)

    Bergamini, C V; Peralta, G H; Milesi, M M; Hynes, E R

    2013-09-01

    In this work, we studied the growth, survival, and peptidolytic activity of Lactobacillus plantarum I91 in a hard-cheese model consisting of a sterile extract of Reggianito cheese. To assess the influence of the primary starter and initial proteolysis level on these parameters, we prepared the extracts with cheeses that were produced using 2 different starter strains of Lactobacillus helveticus 138 or 209 (Lh138 or Lh209) at 3 ripening times: 3, 90, and 180 d. The experimental extracts were inoculated with Lb. plantarum I91; the control extracts were not inoculated and the blank extracts were heat-treated to inactivate enzymes and were not inoculated. All extracts were incubated at 34°C for 21 d, and then the pH, microbiological counts, and proteolysis profiles were determined. The basal proteolysis profiles in the extracts of young cheeses made with either strain tested were similar, but many differences between the proteolysis profiles of the extracts of the Lh138 and Lh209 cheeses were found when riper cheeses were used. The pH values in the blank and control extracts did not change, and no microbial growth was detected. In contrast, the pH value in experimental extracts decreased, and this decrease was more pronounced in extracts obtained from either of the young cheeses and from the Lh209 cheese at any stage of ripening. Lactobacillus plantarum I91 grew up to 8 log during the first days of incubation in all of the extracts, but then the number of viable cells decreased, the extent of which depended on the starter strain and the age of the cheese used for the extract. The decrease in the counts of Lb. plantarum I91 was observed mainly in the extracts in which the pH had diminished the most. In addition, the extracts that best supported the viability of Lb. plantarum I91 during incubation had the highest free amino acids content. The effect of Lb. plantarum I91 on the proteolysis profile of the extracts was marginal. Significant changes in the content of free

  1. Estimating survival of dental fillings on the basis of interval-censored data and multi-state models

    DEFF Research Database (Denmark)

    Joly, Pierre; Gerds, Thomas A; Qvist, Vibeke

    2012-01-01

    We aim to compare the life expectancy of a filling in a primary tooth between two types of treatments. We define the probabilities that a dental filling survives without complication until the permanent tooth erupts from beneath (exfoliation). We relate the time to exfoliation of the tooth...... with all these particularities, we propose to use a parametric four-state model with three random effects to take into account the hierarchical cluster structure. For inference, right and interval censoring as well as left truncation have to be dealt with. With the proposed approach, we can conclude...... that the estimated probability that a filling survives without complication until exfoliation is larger for one treatment than for the other, for all ages of the child at the time of treatment....

  2. EGFR inhibitor erlotinib delays disease progression but does not extend survival in the SOD1 mouse model of ALS.

    Directory of Open Access Journals (Sweden)

    Claire E Le Pichon

    Full Text Available Amyotrophic lateral sclerosis (ALS is a fatal neurodegenerative disease that causes progressive paralysis due to motor neuron death. Several lines of published evidence suggested that inhibition of epidermal growth factor receptor (EGFR signaling might protect neurons from degeneration. To test this hypothesis in vivo, we treated the SOD1 transgenic mouse model of ALS with erlotinib, an EGFR inhibitor clinically approved for oncology indications. Although erlotinib failed to extend ALS mouse survival it did provide a modest but significant delay in the onset of multiple behavioral measures of disease progression. However, given the lack of protection of motor neuron synapses and the lack of survival extension, the small benefits observed after erlotinib treatment appear purely symptomatic, with no modification of disease course.

  3. A Test of the Family Stress Model on Toddler-Aged Children's Adjustment among Hurricane Katrina Impacted and Nonimpacted Low-Income Families

    Science.gov (United States)

    Scaramella, Laura V.; Sohr-Preston, Sara L.; Callahan, Kristin L.; Mirabile, Scott P.

    2008-01-01

    Hurricane Katrina dramatically altered the level of social and environmental stressors for the residents of the New Orleans area. The Family Stress Model describes a process whereby felt financial strain undermines parents' mental health, the quality of family relationships, and child adjustment. Our study considered the extent to which the Family…

  4. Adjustments in the Almod 3W2 code models for reproducing the net load trip test in Angra I nuclear power plant

    International Nuclear Information System (INIS)

    Camargo, C.T.M.; Madeira, A.A.; Pontedeiro, A.C.; Dominguez, L.

    1986-09-01

    The recorded traces got from the net load trip test in Angra I NPP yelded the oportunity to make fine adjustments in the ALMOD 3W2 code models. The changes are described and the results are compared against plant real data. (Author) [pt

  5. Survival and Neurodevelopmental Outcomes among Periviable Infants.

    Science.gov (United States)

    Younge, Noelle; Goldstein, Ricki F; Bann, Carla M; Hintz, Susan R; Patel, Ravi M; Smith, P Brian; Bell, Edward F; Rysavy, Matthew A; Duncan, Andrea F; Vohr, Betty R; Das, Abhik; Goldberg, Ronald N; Higgins, Rosemary D; Cotten, C Michael

    2017-02-16

    Data reported during the past 5 years indicate that rates of survival have increased among infants born at the borderline of viability, but less is known about how increased rates of survival among these infants relate to early childhood neurodevelopmental outcomes. We compared survival and neurodevelopmental outcomes among infants born at 22 to 24 weeks of gestation, as assessed at 18 to 22 months of corrected age, across three consecutive birth-year epochs (2000-2003 [epoch 1], 2004-2007 [epoch 2], and 2008-2011 [epoch 3]). The infants were born at 11 centers that participated in the National Institute of Child Health and Human Development Neonatal Research Network. The primary outcome measure was a three-level outcome - survival without neurodevelopmental impairment, survival with neurodevelopmental impairment, or death. After accounting for differences in infant characteristics, including birth center, we used multinomial generalized logit models to compare the relative risk of survival without neurodevelopmental impairment, survival with neurodevelopmental impairment, and death. Data on the primary outcome were available for 4274 of 4458 infants (96%) born at the 11 centers. The percentage of infants who survived increased from 30% (424 of 1391 infants) in epoch 1 to 36% (487 of 1348 infants) in epoch 3 (Pneurodevelopmental impairment increased from 16% (217 of 1391) in epoch 1 to 20% (276 of 1348) in epoch 3 (P=0.001), whereas the percentage of infants who survived with neurodevelopmental impairment did not change significantly (15% [207 of 1391] in epoch 1 and 16% [211 of 1348] in epoch 3, P=0.29). After adjustment for changes in the baseline characteristics of the infants over time, both the rate of survival with neurodevelopmental impairment (as compared with death) and the rate of survival without neurodevelopmental impairment (as compared with death) increased over time (adjusted relative risks, 1.27 [95% confidence interval {CI}, 1.01 to 1.59] and 1

  6. Survival Old Model Tamping on Bugis House in Kampong of Bunne Regency of Soppeng South Sulawesi Indonesia

    Science.gov (United States)

    Abidah, Andi

    2017-10-01

    Tamping is space circulation from terrace to inside home and also as space for sitting space for low rank social community. Position tamping is one of side of main house. The floor of tamping slightly low than main house floor, this model has seldom found today which community more refer on new tamping model. The new model of tamping today, the same level on main house floor. Even new Bugis house model without tamping. Old model house use tamping but the tamping and watangpola ha the same floor level. This model consists of four modules which three modules on main house and one module tamping. In the past, old model of tamping is different level floor between watangpola and tamping floor now this tamping floor of old Bugis house model gone the same level of watangpola. While new model called eppa-eppa house, did not use tamping. Community in Kampung Bunne is till survive on old model of tamping on their house although several house has change its tamping like community applied now. This model is still found around 45 house of total number of house in the kampung. This study will explore applying old model of tamping of Bugis house in kampong Bunne Regency of Soppeng South Sulawesi. Qualitative research is used on this study. The study was developed base in sketch, photograph and interview.

  7. Inhibition of intestinal epithelial apoptosis improves survival in a murine model of radiation combined injury.

    Directory of Open Access Journals (Sweden)

    Enjae Jung

    Full Text Available World conditions place large populations at risk from ionizing radiation (IR from detonation of dirty bombs or nuclear devices. In a subgroup of patients, ionizing radiation exposure would be followed by a secondary infection. The effects of radiation combined injury are potentially more lethal than either insult in isolation. The purpose of this study was to determine mechanisms of mortality and possible therapeutic targets in radiation combined injury. Mice were exposed to IR with 2.5 Gray (Gy followed four days later by intratracheal methicillin-resistant Staphylococcus aureus (MRSA. While either IR or MRSA alone yielded 100% survival, animals with radiation combined injury had 53% survival (p = 0.01. Compared to IR or MRSA alone, mice with radiation combined injury had increased gut apoptosis, local and systemic bacterial burden, decreased splenic CD4 T cells, CD8 T cells, B cells, NK cells, and dendritic cells, and increased BAL and systemic IL-6 and G-CSF. In contrast, radiation combined injury did not alter lymphocyte apoptosis, pulmonary injury, or intestinal proliferation compared to IR or MRSA alone. In light of the synergistic increase in gut apoptosis following radiation combined injury, transgenic mice that overexpress Bcl-2 in their intestine and wild type mice were subjected to IR followed by MRSA. Bcl-2 mice had decreased gut apoptosis and improved survival compared to WT mice (92% vs. 42%; p<0.01. These data demonstrate that radiation combined injury results in significantly higher mortality than could be predicted based upon either IR or MRSA infection alone, and that preventing gut apoptosis may be a potential therapeutic target.

  8. Inhibition of intestinal epithelial apoptosis improves survival in a murine model of radiation combined injury.

    Science.gov (United States)

    Jung, Enjae; Perrone, Erin E; Brahmamdan, Pavan; McDonough, Jacquelyn S; Leathersich, Ann M; Dominguez, Jessica A; Clark, Andrew T; Fox, Amy C; Dunne, W Michael; Hotchkiss, Richard S; Coopersmith, Craig M

    2013-01-01

    World conditions place large populations at risk from ionizing radiation (IR) from detonation of dirty bombs or nuclear devices. In a subgroup of patients, ionizing radiation exposure would be followed by a secondary infection. The effects of radiation combined injury are potentially more lethal than either insult in isolation. The purpose of this study was to determine mechanisms of mortality and possible therapeutic targets in radiation combined injury. Mice were exposed to IR with 2.5 Gray (Gy) followed four days later by intratracheal methicillin-resistant Staphylococcus aureus (MRSA). While either IR or MRSA alone yielded 100% survival, animals with radiation combined injury had 53% survival (p = 0.01). Compared to IR or MRSA alone, mice with radiation combined injury had increased gut apoptosis, local and systemic bacterial burden, decreased splenic CD4 T cells, CD8 T cells, B cells, NK cells, and dendritic cells, and increased BAL and systemic IL-6 and G-CSF. In contrast, radiation combined injury did not alter lymphocyte apoptosis, pulmonary injury, or intestinal proliferation compared to IR or MRSA alone. In light of the synergistic increase in gut apoptosis following radiation combined injury, transgenic mice that overexpress Bcl-2 in their intestine and wild type mice were subjected to IR followed by MRSA. Bcl-2 mice had decreased gut apoptosis and improved survival compared to WT mice (92% vs. 42%; p<0.01). These data demonstrate that radiation combined injury results in significantly higher mortality than could be predicted based upon either IR or MRSA infection alone, and that preventing gut apoptosis may be a potential therapeutic target.

  9. Motor models and transient analysis for high-temperature, superconductor switch-based adjustable speed drive applications. Final report

    International Nuclear Information System (INIS)

    Bailey, J.M.

    1996-06-01

    New high-temperature superconductor (HTSC) technology may allow development of an energy-efficient power electronics switch for adjustable speed drive (ASD) applications involving variable-speed motors, superconducting magnetic energy storage systems, and other power conversion equipment. This project developed a motor simulation module for determining optimal applications of HTSC-based power switches in ASD systems

  10. Multivariable model development and internal validation for prostate cancer specific survival and overall survival after whole-gland salvage Iodine-125 prostate brachytherapy

    NARCIS (Netherlands)

    Peters, Max; van der Voort van Zyp, Jochem R N; Moerland, Marinus A; Hoekstra, Carel J; van de Pol, Sandrine; Westendorp, Hendrik; Maenhout, Metha; Kattevilder, Rob; Verkooijen, Helena M; van Rossum, Peter S N; Ahmed, Hashim U; Shah, Taimur T; Emberton, Mark; van Vulpen, Marco

    BACKGROUND: Whole-gland salvage Iodine-125-brachytherapy is a potentially curative treatment strategy for localised prostate cancer (PCa) recurrences after radiotherapy. Prognostic factors influencing PCa-specific and overall survival (PCaSS & OS) are not known. The objective of this study was to

  11. Intracranial AAV-IFN-β gene therapy eliminates invasive xenograft glioblastoma and improves survival in orthotopic syngeneic murine model.

    Science.gov (United States)

    GuhaSarkar, Dwijit; Neiswender, James; Su, Qin; Gao, Guangping; Sena-Esteves, Miguel

    2017-02-01

    The highly invasive property of glioblastoma (GBM) cells and genetic heterogeneity are largely responsible for tumor recurrence after the current standard-of-care treatment and thus a direct cause of death. Previously, we have shown that intracranial interferon-beta (IFN-β) gene therapy by locally administered adeno-associated viral vectors (AAV) successfully treats noninvasive orthotopic glioblastoma models. Here, we extend these findings by testing this approach in invasive human GBM xenograft and syngeneic mouse models. First, we show that a single intracranial injection of AAV encoding human IFN-β eliminates invasive human GBM8 tumors and promotes long-term survival. Next, we screened five AAV-IFN-β vectors with different promoters to drive safe expression of mouse IFN-β in the brain in the context of syngeneic GL261 tumors. Two AAV-IFN-β vectors were excluded due to safety concerns, but therapeutic studies with the other three vectors showed extensive tumor cell death, activation of microglia surrounding the tumors, and a 56% increase in median survival of the animals treated with AAV/P2-Int-mIFN-β vector. We also assessed the therapeutic effect of combining AAV-IFN-β therapy with temozolomide (TMZ). As TMZ affects DNA replication, an event that is crucial for second-strand DNA synthesis of single-stranded AAV vectors before active transcription, we tested two TMZ treatment regimens. Treatment with TMZ prior to AAV-IFN-β abrogated any benefit from the latter, while the reverse order of treatment doubled the median survival compared to controls. These studies demonstrate the therapeutic potential of intracranial AAV-IFN-β therapy in a highly migratory GBM model as well as in a syngeneic mouse model and that combination with TMZ is likely to enhance its antitumor potency. © 2016 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

  12. A comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling.

    Science.gov (United States)

    Leger, Stefan; Zwanenburg, Alex; Pilz, Karoline; Lohaus, Fabian; Linge, Annett; Zöphel, Klaus; Kotzerke, Jörg; Schreiber, Andreas; Tinhofer, Inge; Budach, Volker; Sak, Ali; Stuschke, Martin; Balermpas, Panagiotis; Rödel, Claus; Ganswindt, Ute; Belka, Claus; Pigorsch, Steffi; Combs, Stephanie E; Mönnich, David; Zips, Daniel; Krause, Mechthild; Baumann, Michael; Troost, Esther G C; Löck, Steffen; Richter, Christian

    2017-10-16

    Radiomics applies machine learning algorithms to quantitative imaging data to characterise the tumour phenotype and predict clinical outcome. For the development of radiomics risk models, a variety of different algorithms is available and it is not clear which one gives optimal results. Therefore, we assessed the performance of 11 machine learning algorithms combined with 12 feature selection methods by the concordance index (C-Index), to predict loco-regional tumour control (LRC) and overall survival for patients with head and neck squamous cell carcinoma. The considered algorithms are able to deal with continuous time-to-event survival data. Feature selection and model building were performed on a multicentre cohort (213 patients) and validated using an independent cohort (80 patients). We found several combinations of machine learning algorithms and feature selection methods which achieve similar results, e.g. C-Index = 0.71 and BT-COX: C-Index = 0.70 in combination with Spearman feature selection. Using the best performing models, patients were stratified into groups of low and high risk of recurrence. Significant differences in LRC were obtained between both groups on the validation cohort. Based on the presented analysis, we identified a subset of algorithms which should be considered in future radiomics studies to develop stable and clinically relevant predictive models for time-to-event endpoints.

  13. Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

    Directory of Open Access Journals (Sweden)

    Yun Shi

    2014-01-01

    Full Text Available Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM.

  14. Bronchus-associated lymphoid tissue (BALT and survival in a vaccine mouse model of tularemia.

    Directory of Open Access Journals (Sweden)

    Damiana Chiavolini

    2010-06-01

    Full Text Available Francisella tularensis causes severe pulmonary disease, and nasal vaccination could be the ideal measure to effectively prevent it. Nevertheless, the efficacy of this type of vaccine is influenced by the lack of an effective mucosal adjuvant.Mice were immunized via the nasal route with lipopolysaccharide isolated from F. tularensis and neisserial recombinant PorB as an adjuvant candidate. Then, mice were challenged via the same route with the F. tularensis attenuated live vaccine strain (LVS. Mouse survival and analysis of a number of immune parameters were conducted following intranasal challenge. Vaccination induced a systemic antibody response and 70% of mice were protected from challenge as showed by their improved survival and weight regain. Lungs from mice recovering from infection presented prominent lymphoid aggregates in peribronchial and perivascular areas, consistent with the location of bronchus-associated lymphoid tissue (BALT. BALT areas contained proliferating B and T cells, germinal centers, T cell infiltrates, dendritic cells (DCs. We also observed local production of antibody generating cells and homeostatic chemokines in BALT areas.These data indicate that PorB might be an optimal adjuvant candidate for improving the protective effect of F. tularensis antigens. The presence of BALT induced after intranasal challenge in vaccinated mice might play a role in regulation of local immunity and long-term protection, but more work is needed to elucidate mechanisms that lead to its formation.

  15. Adipose-derived stromal cells enhance auditory neuron survival in an animal model of sensory hearing loss.

    Science.gov (United States)

    Schendzielorz, Philipp; Vollmer, Maike; Rak, Kristen; Wiegner, Armin; Nada, Nashwa; Radeloff, Katrin; Hagen, Rudolf; Radeloff, Andreas

    2017-10-01

    A cochlear implant (CI) is an electronic prosthesis that can partially restore speech perception capabilities. Optimum information transfer from the cochlea to the central auditory system requires a proper functioning auditory nerve (AN) that is electrically stimulated by the device. In deafness, the lack of neurotrophic support, normally provided by the sensory cells of the inner ear, however, leads to gradual degeneration of auditory neurons with undesirable consequences for CI performance. We evaluated the potential of adipose-derived stromal cells (ASCs) that are known to produce neurotrophic factors to prevent neural degeneration in sensory hearing loss. For this, co-cultures of ASCs with auditory neurons have been studied, and autologous ASC transplantation has been performed in a guinea pig model of gentamicin-induced sensory hearing loss. In vitro ASCs were neuroprotective and considerably increased the neuritogenesis of auditory neurons. In vivo transplantation of ASCs into the scala tympani resulted in an enhanced survival of auditory neurons. Specifically, peripheral AN processes that are assumed to be the optimal activation site for CI stimulation and that are particularly vulnerable to hair cell loss showed a significantly higher survival rate in ASC-treated ears. ASC transplantation into the inner ear may restore neurotrophic support in sensory hearing loss and may help to improve CI performance by enhanced AN survival. Copyright © 2017 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

  16. Survival probability of Baltic larval cod in relation to spatial overlap patterns with their prey obtained from drift model studies

    DEFF Research Database (Denmark)

    Hinrichsen, H.H.; Schmidt, J.O.; Petereit, C.

    2005-01-01

    Temporal mismatch between the occurrence of larvae and their prey potentially affects the spatial overlap and thus the contact rates between predator and prey. This might have important consequences for growth and survival. We performed a case study investigating the influence of circulation......-prey overlap, dependent on the hatching time of cod larvae. By performing model runs for the years 1979-1998 investigated the intra- and interannual variability of potential spatial overlap between predator and prey. Assuming uniform prey distributions, we generally found the overlap to have decreased since...

  17. Instrumental variables estimation of exposure effects on a time-to-event endpoint using structural cumulative survival models.

    Science.gov (United States)

    Martinussen, Torben; Vansteelandt, Stijn; Tchetgen Tchetgen, Eric J; Zucker, David M

    2017-12-01

    The use of instrumental variables for estimating the effect of an exposure on an outcome is popular in econometrics, and increasingly so in epidemiology. This increasing popularity may be attributed to the natural occurrence of instrumental variables in observational studies that incorporate elements of randomization, either by design or by nature (e.g., random inheritance of genes). Instrumental variables estimation of exposure effects is well established for continuous outcomes and to some extent for binary outcomes. It is, however, largely lacking for time-to-event outcomes because of complications due to censoring and survivorship bias. In this article, we make a novel proposal under a class of structural cumulative survival models which parameterize time-varying effects of a point exposure directly on the scale of the survival function; these models are essentially equivalent with a semi-parametric variant of the instrumental variables additive hazards model. We propose a class of recursive instrumental variable estimators for these exposure effects, and derive their large sample properties along with inferential tools. We examine the performance of the proposed method in simulation studies and illustrate it in a Mendelian randomization study to evaluate the effect of diabetes on mortality using data from the Health and Retirement Study. We further use the proposed method to investigate potential benefit from breast cancer screening on subsequent breast cancer mortality based on the HIP-study. © 2017, The International Biometric Society.

  18. Post mortem Survival of Gallibacterium anatis in a Laying Hen Experimental Infection Model.

    Science.gov (United States)

    Wang, Chong; Pors, Susanne Elisabeth; Bojesen, Anders Miki

    2018-06-01

    To assess the survival of Gallibacterium anatis in dead laying hens, 21-wk-old laying hens were injected intraperitoneally with 0.5 ml brain hearth infusion broth containing 10 8 colony-forming units (CFU) of G. anatis 12656-12 liver ( n = 16), Escherichia coli ST141 ( n = 16), or a mix of G. anatis 12656-12 liver and E. coli ST141 ( n = 16), respectively. Birds were euthanatized 24 hr post injection. From each group eight dead birds were kept at 4 C and eight at room temperature. Swab samples were taken at different time points post euthanatization and streaked on blood agar plates. From the birds kept at 4 C, G. anatis was reisolated from the G. anatis and the G. anatis- E. coli co-injected groups at least 12 days post euthanization. From birds kept at room temperature, G. anatis was reisolated up to 2 days post euthanatization. When using the gyrB-based G. anatis-specific quantitative PCR (qPCR), G. anatis was detected within at least 5 days, and up to 5 days post euthanatization, from birds kept at room temperature and 4 C, respectively. Escherichia coli was reisolated from all the time points independent of how the birds were kept. No difference was observed between the reisolation rates for G. anatis or E. coli when comparing similar detection methods. For birds kept at 4 C, bacterial cultivation was a more sensitive method for detecting G. anatis ( P < 0.05), whereas for birds kept at room temperature, the G. anatis-specific qPCR outperformed bacterial culture ( P < 0.05). In conclusion, we demonstrated that G. anatis has a poorer survival rate than does E. coli in dead chickens kept at room temperature. That finding may affect the overall diagnostic sensitivity and lead to underdiagnosis of G. anatis in a normal production setting.

  19. The model of children's social adjustment under the gender-roles absence in single-parent families.

    Science.gov (United States)

    Chen, I-Jun; Zhang, Hailun; Wei, Bingsi; Guo, Zeyao

    2018-01-14

    This study aimed to evaluate the effects of the gender-role types and child-rearing gender-role attitude of the single-parents, as well as their children's gender role traits and family socio-economic status, on social adjustment. We recruited 458 pairs of single parents and their children aged 8-18 by purposive sampling. The research tools included the Family Socio-economic Status Questionnaire, Sex Role Scales, Parental Child-rearing Gender-role Attitude Scale and Social Adjustment Scale. The results indicated: (a) single mothers' and their daughters' feminine traits were both higher than their masculine traits, and sons' masculine traits were higher than their feminine traits; the majority gender-role type of single parents and their children was androgyny; significant differences were found between children's gender-role types depending on different raiser, the proportion of girls' masculine traits raised by single fathers was significantly higher than those who were raised by single mothers; (b) family socio-economic status and single parents' gender-role types positively influenced parental child-rearing gender-role attitude, which in turn, influenced the children's gender traits, and further affected children's social adjustment. © 2018 International Union of Psychological Science.

  20. On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

    Science.gov (United States)

    Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

    2017-10-01

    With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.

  1. Risk-adjustment models for heart failure patients' 30-day mortality and readmission rates: the incremental value of clinical data abstracted from medical charts beyond hospital discharge record.

    Science.gov (United States)

    Lenzi, Jacopo; Avaldi, Vera Maria; Hernandez-Boussard, Tina; Descovich, Carlo; Castaldini, Ilaria; Urbinati, Stefano; Di Pasquale, Giuseppe; Rucci, Paola; Fantini, Maria Pia

    2016-09-06

    Hospital discharge records (HDRs) are routinely used to assess outcomes of care and to compare hospital performance for heart failure. The advantages of using clinical data from medical charts to improve risk-adjustment models remain controversial. The aim of the present study was to evaluate the additional contribution of clinical variables to HDR-based 30-day mortality and readmission models in patients with heart failure. This retrospective observational study included all patients residing in the Local Healthcare Authority of Bologna (about 1 million inhabitants) who were discharged in 2012 from one of three hospitals in the area with a diagnosis of heart failure. For each study outcome, we compared the discrimination of the two risk-adjustment models (i.e., HDR-only model and HDR-clinical model) through the area under the ROC curve (AUC). A total of 1145 and 1025 patients were included in the mortality and readmission analyses, respectively. Adding clinical data significantly improved the discrimination of the mortality model (AUC = 0.84 vs. 0.73, p < 0.001), but not the discrimination of the readmission model (AUC = 0.65 vs. 0.63, p = 0.08). We identified clinical variables that significantly improved the discrimination of the HDR-only model for 30-day mortality following heart failure. By contrast, clinical variables made little contribution to the discrimination of the HDR-only model for 30-day readmission.

  2. Three Models of Anthrax Toxin Effects on the MAP-Kinase Pathway and Macrophage Survival

    National Research Council Canada - National Science Library

    Schneider, Daniel J

    2008-01-01

    .... This research modifies three published MAPK models to reflect this signal inhibition and to estimate a first-order reaction rate by fitting the models to published viability data for two macrophage...

  3. Modeling survival, yield, volume partitioning and their response to thinning for longleaf pine plantations

    Science.gov (United States)

    Carlos A. Gonzalez-Benecke; Salvador A. Gezan; Daniel J. Leduc; Timothy A. Martin; Wendell P. Cropper Jr; Lisa J Samuelson

    2012-01-01

    Longleaf pine (Pinus palustris Mill.) is an important tree species of the southeast U.S. Currently there is no comprehensive stand-level growth and yield model for the species. The model system described here estimates site index (SI) if dominant height (Hdom) and stand age are known (inversely, the model can project H

  4. Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

    Science.gov (United States)

    Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

    2015-01-01

    Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

  5. Long-Term Survival Prediction for Coronary Artery Bypass Grafting: Validation of the ASCERT Model Compared With The Society of Thoracic Surgeons Predicted Risk of Mortality.

    Science.gov (United States)

    Lancaster, Timothy S; Schill, Matthew R; Greenberg, Jason W; Ruaengsri, Chawannuch; Schuessler, Richard B; Lawton, Jennifer S; Maniar, Hersh S; Pasque, Michael K; Moon, Marc R; Damiano, Ralph J; Melby, Spencer J

    2018-05-01

    The recently developed American College of Cardiology Foundation-Society of Thoracic Surgeons (STS) Collaboration on the Comparative Effectiveness of Revascularization Strategy (ASCERT) Long-Term Survival Probability Calculator is a valuable addition to existing short-term risk-prediction tools for cardiac surgical procedures but has yet to be externally validated. Institutional data of 654 patients aged 65 years or older undergoing isolated coronary artery bypass grafting between 2005 and 2010 were reviewed. Predicted survival probabilities were calculated using the ASCERT model. Survival data were collected using the Social Security Death Index and institutional medical records. Model calibration and discrimination were assessed for the overall sample and for risk-stratified subgroups based on (1) ASCERT 7-year survival probability and (2) the predicted risk of mortality (PROM) from the STS Short-Term Risk Calculator. Logistic regression analysis was performed to evaluate additional perioperative variables contributing to death. Overall survival was 92.1% (569 of 597) at 1 year and 50.5% (164 of 325) at 7 years. Calibration assessment found no significant differences between predicted and actual survival curves for the overall sample or for the risk-stratified subgroups, whether stratified by predicted 7-year survival or by PROM. Discriminative performance was comparable between the ASCERT and PROM models for 7-year survival prediction (p validated for prediction of long-term survival after coronary artery bypass grafting in all risk groups. The widely used STS PROM performed comparably as a predictor of long-term survival. Both tools provide important information for preoperative decision making and patient counseling about potential outcomes after coronary artery bypass grafting. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  6. Survival of Five Strains of Shiga Toxigenic Escherichia coli in a Sausage Fermentation Model and Subsequent Sensitivity to Stress from Gastric Acid and Intestinal Fluid

    Directory of Open Access Journals (Sweden)

    Tone Mari Rode

    2017-01-01

    Full Text Available The ability of foodborne pathogens to exhibit adaptive responses to stressful conditions in foods may enhance their survival when passing through the gastrointestinal system. We aimed to determine whether Escherichia coli surviving stresses encountered during a model dry-fermented sausage (DFS production process exhibit enhanced tolerance and survival in an in vitro gastrointestinal model. Salami sausage batters spiked with five E. coli isolates, including enterohaemorrhagic E. coli strains isolated from different DFS outbreaks, were fermented in a model DFS process (20°C, 21 days. Control batters spiked with the same strains were stored at 4°C for the same period. Samples from matured model sausages and controls were thereafter exposed to an in vitro digestion challenge. Gastric exposure (pH 3 resulted in considerably reduced survival of the E. coli strains that had undergone the model DFS process. This reduction continued after entering intestinal challenge (pH 8, but growth resumed after 120 min. When subjected to gastric challenge for 120 min, E. coli that had undergone the DFS process showed about 2.3 log10⁡​ lower survival compared with those kept in sausage batter at 4°C. Our results indicated that E. coli strains surviving a model DFS process exhibited reduced tolerance to subsequent gastric challenge at low pH.

  7. Modeling and identification for the adjustable control of generation processes; Modelado e identificacion para el control autoajustable de procesos de generacion

    Energy Technology Data Exchange (ETDEWEB)

    Ricano Castillo, Juan Manuel; Palomares Gonzalez, Daniel [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1990-12-31

    The recursive technique of the method of minimum squares is employed to obtain a multivariable model of the self regressive mobile mean type, needed for the design of a multivariable, self-adjustable controller self adjustable multivariable. In this article the employed technique and the results obtained are described with the characterization of the model structure and the parametric estimation. The convergency velocity curves are observed towards the parameters` numerical values. [Espanol] La tecnica recursiva del metodo de los minimos cuadrados se emplea para obtener un modelo multivariable de tipo autorregresivo de promedio movil, necesario para el diseno de un controlador autoajustable muitivariable. En el articulo, se describe la tecnica empleada y los resultados obtenidos con la caracterizacion de la estructura del modelo y la estimacion parametrica. Se observan las curvas de la velocidad de convergencia hacia los valores numericos de los parametros.

  8. Modeling and identification for the adjustable control of generation processes; Modelado e identificacion para el control autoajustable de procesos de generacion

    Energy Technology Data Exchange (ETDEWEB)

    Ricano Castillo, Juan Manuel; Palomares Gonzalez, Daniel [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1989-12-31

    The recursive technique of the method of minimum squares is employed to obtain a multivariable model of the self regressive mobile mean type, needed for the design of a multivariable, self-adjustable controller self adjustable multivariable. In this article the employed technique and the results obtained are described with the characterization of the model structure and the parametric estimation. The convergency velocity curves are observed towards the parameters` numerical values. [Espanol] La tecnica recursiva del metodo de los minimos cuadrados se emplea para obtener un modelo multivariable de tipo autorregresivo de promedio movil, necesario para el diseno de un controlador autoajustable muitivariable. En el articulo, se describe la tecnica empleada y los resultados obtenidos con la caracterizacion de la estructura del modelo y la estimacion parametrica. Se observan las curvas de la velocidad de convergencia hacia los valores numericos de los parametros.

  9. A complete generalized adjustment criterion

    NARCIS (Netherlands)

    Perković, Emilija; Textor, Johannes; Kalisch, Markus; Maathuis, Marloes H.

    2015-01-01

    Covariate adjustment is a widely used approach to estimate total causal effects from observational data. Several graphical criteria have been developed in recent years to identify valid covariates for adjustment from graphical causal models. These criteria can handle multiple causes, latent

  10. Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

    Science.gov (United States)

    Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

    2016-03-01

    One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi

  11. MODELING OF THE HEAT PUMP STATION ADJUSTABLE LOOP OF AN INTERMEDIATE HEAT-TRANSFER AGENT (Part I

    Directory of Open Access Journals (Sweden)

    Sit B.

    2009-08-01

    Full Text Available There are examined equations of dynamics and statics of an adjustable intermediate loop of heat pump carbon dioxide station in this paper. Heat pump station is a part of the combined heat supply system. Control of transferred thermal capacity from the source of low potential heat source is realized by means of changing the speed of circulation of a liquid in the loop and changing the area of a heat-transmitting surface, both in the evaporator, and in the intermediate heat exchanger depending on the operating parameter, for example, external air temperature and wind speed.

  12. Suitability of a three-dimensional model to measure empathy and its relationship with social and normative adjustment in Spanish adolescents: a cross-sectional study.

    Science.gov (United States)

    Herrera-López, Mauricio; Gómez-Ortiz, Olga; Ortega-Ruiz, Rosario; Jolliffe, Darrick; Romera, Eva M

    2017-09-25

    (1) To examine the psychometric properties of the Basic Empathy Scale (BES) with Spanish adolescents, comparing a two and a three-dimensional structure;(2) To analyse the relationship between the three-dimensional empathy and social and normative adjustment in school. Transversal and ex post facto retrospective study. Confirmatory factorial analysis, multifactorial invariance analysis and structural equations models were used. 747 students (51.3% girls) from Cordoba, Spain, aged 12-17 years (M=13.8; SD=1.21). The original two-dimensional structure was confirmed (cognitive empathy, affective empathy), but a three-dimensional structure showed better psychometric properties, highlighting the good fit found in confirmatory factorial analysis and adequate internal consistent valued, measured with Cronbach's alpha and McDonald's omega. Composite reliability and average variance extracted showed better indices for a three-factor model. The research also showed evidence of measurement invariance across gender. All the factors of the final three-dimensional BES model were direct and significantly associated with social and normative adjustment, being most strongly related to cognitive empathy. This research supports the advances in neuroscience, developmental psychology and psychopathology through a three-dimensional version of the BES, which represents an improvement in the original two-factorial model. The organisation of empathy in three factors benefits the understanding of social and normative adjustment in adolescents, in which emotional disengagement favours adjusted peer relationships. Psychoeducational interventions aimed at improving the quality of social life in schools should target these components of empathy. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  13. The anchor-based minimal important change, based on receiver operating characteristic analysis or predictive modeling, may need to be adjusted for the proportion of improved patients.

    Science.gov (United States)

    Terluin, Berend; Eekhout, Iris; Terwee, Caroline B

    2017-03-01

    Patients have their individual minimal important changes (iMICs) as their personal benchmarks to determine whether a perceived health-related quality of life (HRQOL) change constitutes a (minimally) important change for them. We denote the mean iMIC in a group of patients as the "genuine MIC" (gMIC). The aims of this paper are (1) to examine the relationship between the gMIC and the anchor-based minimal important change (MIC), determined by receiver operating characteristic analysis or by predictive modeling; (2) to examine the impact of the proportion of improved patients on these MICs; and (3) to explore the possibility to adjust the MIC for the influence of the proportion of improved patients. Multiple simulations of patient samples involved in anchor-based MIC studies with different characteristics of HRQOL (change) scores and distributions of iMICs. In addition, a real data set is analyzed for illustration. The receiver operating characteristic-based and predictive modeling MICs equal the gMIC when the proportion of improved patients equals 0.5. The MIC is estimated higher than the gMIC when the proportion improved is greater than 0.5, and the MIC is estimated lower than the gMIC when the proportion improved is less than 0.5. Using an equation including the predictive modeling MIC, the log-odds of improvement, the standard deviation of the HRQOL change score, and the correlation between the HRQOL change score and the anchor results in an adjusted MIC reflecting the gMIC irrespective of the proportion of improved patients. Adjusting the predictive modeling MIC for the proportion of improved patients assures that the adjusted MIC reflects the gMIC. We assumed normal distributions and global perceived change scores that were independent on the follow-up score. Additionally, floor and ceiling effects were not taken into account. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. An Evaluation of the Adjusted DeLone and McLean Model of Information Systems Success; the case of financial information system in Ferdowsi University of Mashhad

    OpenAIRE

    Mohammad Lagzian; Shamsoddin Nazemi; Fatemeh Dadmand

    2012-01-01

    Assessing the success of information systems within organizations has been identified as one of the most critical subjects of information system management in both public and private organizations. It is therefore important to measure the success of information systems from the user's perspective. The purpose of the current study was to evaluate the degree of information system success by the adjusted DeLone and McLean’s model in the field financial information system (FIS) in an Iranian Univ...

  15. Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores.

    Science.gov (United States)

    Houthooft, Rein; Ruyssinck, Joeri; van der Herten, Joachim; Stijven, Sean; Couckuyt, Ivo; Gadeyne, Bram; Ongenae, Femke; Colpaert, Kirsten; Decruyenaere, Johan; Dhaene, Tom; De Turck, Filip

    2015-03-01

    The length of stay of critically ill patients in the intensive care unit (ICU) is an indication of patient ICU resource usage and varies considerably. Planning of postoperative ICU admissions is important as ICUs often have no nonoccupied beds available. Estimation of the ICU bed availability for the next coming days is entirely based on clinical judgement by intensivists and therefore too inaccurate. For this reason, predictive models have much potential for improving planning for ICU patient admission. Our goal is to develop and optimize models for patient survival and ICU length of stay (LOS) based on monitored ICU patient data. Furthermore, these models are compared on their use of sequential organ failure (SOFA) scores as well as underlying raw data as input features. Different machine learning techniques are trained, using a 14,480 patient dataset, both on SOFA scores as well as their underlying raw data values from the first five days after admission, in order to predict (i) the patient LOS, and (ii) the patient mortality. Furthermore, to help physicians in assessing the prediction credibility, a probabilistic model is tailored to the output of our best-performing model, assigning a belief to each patient status prediction. A two-by-two grid is built, using the classification outputs of the mortality and prolonged stay predictors to improve the patient LOS regression models. For predicting patient mortality and a prolonged stay, the best performing model is a support vector machine (SVM) with GA,D=65.9% (area under the curve (AUC) of 0.77) and GS,L=73.2% (AUC of 0.82). In terms of LOS regression, the best performing model is support vector regression, achieving a mean absolute error of 1.79 days and a median absolute error of 1.22 days for those patients surviving a nonprolonged stay. Using a classification grid based on the predicted patient mortality and prolonged stay, allows more accurate modeling of the patient LOS. The detailed models allow to support

  16. Modelling Anopheles gambiae s.s. Population Dynamics with Temperature- and Age-Dependent Survival

    Directory of Open Access Journals (Sweden)

    Céline Christiansen-Jucht

    2015-05-01

    Full Text Available Climate change and global warming are emerging as important threats to human health, particularly through the potential increase in vector- and water-borne diseases. Environmental variables are known to affect substantially the population dynamics and abundance of the poikilothermic vectors of disease, but the exact extent of this sensitivity is not well established. Focusing on malaria and its main vector in Africa, Anopheles gambiae sensu stricto, we present a set of novel mathematical models of climate-driven mosquito population dynamics motivated by experimental data suggesting that in An. gambiae, mortality is temperature and age dependent. We compared the performance of these models to that of a “standard” model ignoring age dependence. We used a longitudinal dataset of vector abundance over 36 months in sub-Saharan Africa for comparison between models that incorporate age dependence and one that does not, and observe that age-dependent models consistently fitted the data better than the reference model. This highlights that including age dependence in the vector component of mosquito-borne disease models may be important to predict more reliably disease transmission dynamics. Further data and studies are needed to enable improved fitting, leading to more accurate and informative model predictions for the An. gambiae malaria vector as well as for other disease vectors.

  17. A comparative study of two food model systems to test the survival of Campylobacter jejuni at -18 degrees C

    DEFF Research Database (Denmark)

    Birk, Tina; Rosenquist, Hanne; Brondsted, L.

    2006-01-01

    The survival of Campylobacter jejuni NCTC 11168 was tested at freezing conditions (-18 degrees C) over a period of 32 days in two food models that simulated either (i) the chicken skin surface (skin model) or (ii) the chicken juice in and around a broiler carcass (liquid model). In the skin model...... NCTC 11168 cells was slower when suspended in chicken juice than in BHIB. After freezing for 32 days, the reductions in the cell counts were 1.5 log CFU/ml in chicken juice and 3.5 log CFU/ml in BHIB. After the same time of freezing but when inoculated onto chicken skin, C. jejuni NCTC 11168...... was reduced by 2.2 log units when inoculated in chicken juice and 3.2 log units when inoculated into BHIB. For both models, the major decrease occurred within the first 24 h of freezing. The results obtained in the liquid model with chicken juice were comparable to the reductions of Campylobacter observed...

  18. VEGF as a Survival Factor in Ex Vivo Models of Early Diabetic Retinopathy.

    Science.gov (United States)

    Amato, Rosario; Biagioni, Martina; Cammalleri, Maurizio; Dal Monte, Massimo; Casini, Giovanni

    2016-06-01

    Growing evidence indicates neuroprotection as a therapeutic target in diabetic retinopathy (DR). We tested the hypothesis that VEGF is released and acts as a survival factor in the retina in early DR. Ex vivo mouse retinal explants were exposed to stressors similar to those characterizing DR, that is, high glucose (HG), oxidative stress (OS), or advanced glycation end-products (AGE). Neuroprotection was provided using octreotide (OCT), a somatostatin analog, and pituitary adenylate cyclase activating peptide (PACAP), two well-documented neuroprotectants. Data were obtained with real-time RT-PCR, Western blot, ELISA, and immunohistochemistry. Apoptosis was induced in the retinal explants by HG, OS, or AGE treatments. At the same time, explants also showed increased VEGF expression and release. The data revealed that VEGF is released shortly after exposure of the explants to stressors and before the level of cell death reaches its maximum. Retinal cell apoptosis was inhibited by OCT and PACAP. At the same time, OCT and PACAP also reduced VEGF expression and release. Vascular endothelial growth factor turned out to be a protective factor for the stressed retinal explants, because inhibiting VEGF with a VEGF trap further increased cell death. These data show that protecting retinal neurons from diabetic stress also reduces VEGF expression and release, while inhibiting VEGF leads to exacerbation of apoptosis. These observations suggest that the retina in early DR releases VEGF as a prosurvival factor. Neuroprotective agents may decrease the need of VEGF production by the retina, therefore limiting the risk, in the long term, of pathologic angiogenesis.

  19. Users' guide to system dynamics model describing Coho salmon survival in Olema Creek, Point Reyes National Seashore, Marin County, California

    Science.gov (United States)

    Woodward, Andrea; Torregrosa, Alicia; Madej, Mary Ann; Reichmuth, Michael; Fong, Darren

    2014-01-01

    The system dynamics model described in this report is the result of a collaboration between U.S. Geological Survey (USGS) scientists and National Park Service (NPS) San Francisco Bay Area Network (SFAN) staff, whose goal was to develop a methodology to integrate inventory and monitoring data to better understand ecosystem dynamics and trends using salmon in Olema Creek, Marin County, California, as an example case. The SFAN began monitoring multiple life stages of coho salmon (Oncorhynchus kisutch) in Olema Creek during 2003 (Carlisle and others, 2013), building on previous monitoring of spawning fish and redds. They initiated water-quality and habitat monitoring, and had access to flow and weather data from other sources. This system dynamics model of the freshwater portion of the coho salmon life cycle in Olema Creek integrated 8 years of existing monitoring data, literature values, and expert opinion to investigate potential factors limiting survival and production, identify data gaps, and improve monitoring and restoration prescriptions. A system dynamics model is particularly effective when (1) data are insufficient in time series length and/or measured parameters for a statistical or mechanistic model, and (2) the model must be easily accessible by users who are not modelers. These characteristics helped us meet the following overarching goals for this model: Summarize and synthesize NPS monitoring data with data and information from other sources to describe factors and processes affecting freshwater survival of coho salmon in Olema Creek. Provide a model that can be easily manipulated to experiment with alternative values of model parameters and novel scenarios of environmental drivers. Although the model describes the ecological dynamics of Olema Creek, these dynamics are structurally similar to numerous other coastal streams along the California coast that also contain anadromous fish populations. The model developed for Olema can be used, at least as a

  20. Positioning and number of nutritional levels in dose-response trials to estimate the optimal-level and the adjustment of the models

    Directory of Open Access Journals (Sweden)

    Fernando Augusto de Souza

    2014-07-01

    Full Text Available The aim of this research was to evaluate the influence of the number and position of nutrient levels used in dose-response trials in the estimation of the optimal-level (OL and the goodness of fit on the models: quadratic polynomial (QP, exponential (EXP, linear response plateau (LRP and quadratic response plateau (QRP. It was used data from dose-response trials realized in FCAV-Unesp Jaboticabal considering the homogeneity of variances and normal distribution. The fit of the models were evaluated considered the following statistics: adjusted coefficient of determination (R²adj, coefficient of variation (CV and the sum of the squares of deviations (SSD.It was verified in QP and EXP models that small changes on the placement and distribution of the levels caused great changes in the estimation of the OL. The LRP model was deeply influenced by the absence or presence of the level between the response and stabilization phases (change in the straight to plateau. The QRP needed more levels on the response phase and the last level on stabilization phase to estimate correctly the plateau. It was concluded that the OL and the adjust of the models are dependent on the positioning and the number of the levels and the specific characteristics of each model, but levels defined near to the true requirement and not so spaced are better to estimate the OL.

  1. Metabolic therapy with Deanna Protocol supplementation delays disease progression and extends survival in amyotrophic lateral sclerosis (ALS mouse model.

    Directory of Open Access Journals (Sweden)

    Csilla Ari

    Full Text Available Amyotrophic Lateral Sclerosis (ALS, also known as Lou Gehrig's disease, is a neurodegenerative disorder of motor neurons causing progressive muscle weakness, paralysis, and eventual death from respiratory failure. There is currently no cure or effective treatment for ALS. Besides motor neuron degeneration, ALS is associated with impaired energy metabolism, which is pathophysiologically linked to mitochondrial dysfunction and glutamate excitotoxicity. The Deanna Protocol (DP is a metabolic therapy that has been reported to alleviate symptoms in patients with ALS. In this study we hypothesized that alternative fuels in the form of TCA cycle intermediates, specifically arginine-alpha-ketoglutarate (AAKG, the main ingredient of the DP, and the ketogenic diet (KD, would increase motor function and survival in a mouse model of ALS (SOD1-G93A. ALS mice were fed standard rodent diet (SD, KD, or either diets containing a metabolic therapy of the primary ingredients of the DP consisting of AAKG, gamma-aminobutyric acid, Coenzyme Q10, and medium chain triglyceride high in caprylic triglyceride. Assessment of ALS-like pathology was performed using a pre-defined criteria for neurological score, accelerated rotarod test, paw grip endurance test, and grip strength test. Blood glucose, blood beta-hydroxybutyrate, and body weight were also monitored. SD+DP-fed mice exhibited improved neurological score from age 116 to 136 days compared to control mice. KD-fed mice exhibited better motor performance on all motor function tests at 15 and 16 weeks of age compared to controls. SD+DP and KD+DP therapies significantly extended survival time of SOD1-G93A mice by 7.5% (p = 0.001 and 4.2% (p = 0.006, respectively. Sixty-three percent of mice in the KD+DP and 72.7% of the SD+DP group lived past 125 days, while only 9% of the control animals survived past that point. Targeting energy metabolism with metabolic therapy produces a therapeutic effect in ALS mice which

  2. Metabolic therapy with Deanna Protocol supplementation delays disease progression and extends survival in amyotrophic lateral sclerosis (ALS) mouse model.

    Science.gov (United States)

    Ari, Csilla; Poff, Angela M; Held, Heather E; Landon, Carol S; Goldhagen, Craig R; Mavromates, Nicholas; D'Agostino, Dominic P

    2014-01-01

    Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig's disease, is a neurodegenerative disorder of motor neurons causing progressive muscle weakness, paralysis, and eventual death from respiratory failure. There is currently no cure or effective treatment for ALS. Besides motor neuron degeneration, ALS is associated with impaired energy metabolism, which is pathophysiologically linked to mitochondrial dysfunction and glutamate excitotoxicity. The Deanna Protocol (DP) is a metabolic therapy that has been reported to alleviate symptoms in patients with ALS. In this study we hypothesized that alternative fuels in the form of TCA cycle intermediates, specifically arginine-alpha-ketoglutarate (AAKG), the main ingredient of the DP, and the ketogenic diet (KD), would increase motor function and survival in a mouse model of ALS (SOD1-G93A). ALS mice were fed standard rodent diet (SD), KD, or either diets containing a metabolic therapy of the primary ingredients of the DP consisting of AAKG, gamma-aminobutyric acid, Coenzyme Q10, and medium chain triglyceride high in caprylic triglyceride. Assessment of ALS-like pathology was performed using a pre-defined criteria for neurological score, accelerated rotarod test, paw grip endurance test, and grip strength test. Blood glucose, blood beta-hydroxybutyrate, and body weight were also monitored. SD+DP-fed mice exhibited improved neurological score from age 116 to 136 days compared to control mice. KD-fed mice exhibited better motor performance on all motor function tests at 15 and 16 weeks of age compared to controls. SD+DP and KD+DP therapies significantly extended survival time of SOD1-G93A mice by 7.5% (p = 0.001) and 4.2% (p = 0.006), respectively. Sixty-three percent of mice in the KD+DP and 72.7% of the SD+DP group lived past 125 days, while only 9% of the control animals survived past that point. Targeting energy metabolism with metabolic therapy produces a therapeutic effect in ALS mice which may prolong

  3. A Novel Design for Adjustable Stiffness Artificial Tendon for the Ankle Joint of a Bipedal Robot: Modeling & Simulation

    Directory of Open Access Journals (Sweden)

    Aiman Omer

    2015-12-01

    Full Text Available Bipedal humanoid robots are expected to play a major role in the future. Performing bipedal locomotion requires high energy due to the high torque that needs to be provided by its legs’ joints. Taking the WABIAN-2R as an example, it uses harmonic gears in its joint to increase the torque. However, using such a mechanism increases the weight of the legs and therefore increases energy consumption. Therefore, the idea of developing a mechanism with adjustable stiffness to be connected to the leg joint is introduced here. The proposed mechanism would have the ability to provide passive and active motion. The mechanism would be attached to the ankle pitch joint as an artificial tendon. Using computer simulations, the dynamical performance of the mechanism is analytically evaluated.

  4. MEDI4893* Promotes Survival and Extends the Antibiotic Treatment Window in a Staphylococcus aureus Immunocompromised Pneumonia Model.

    Science.gov (United States)

    Hua, L; Cohen, T S; Shi, Y; Datta, V; Hilliard, J J; Tkaczyk, C; Suzich, J; Stover, C K; Sellman, B R

    2015-08-01

    Immunocompromised individuals are at increased risk of Staphylococcus aureus pneumonia. Neutralization of alpha-toxin (AT) with the monoclonal antibody (MAb) MEDI4893* protects normal mice from S. aureus pneumonia; however, the effects of the MAb in immunocompromised mice have not been reported. In this study, passive immunization with MEDI4893* increased survival rates and reduced bacterial numbers in the lungs in an immunocompromised murine S. aureus pneumonia model. Lungs from infected mice exhibited alveolar epithelial damage, protein leakage, and bacterial overgrowth, whereas lungs from mice passively immunized with MEDI4893* retained a healthy architecture, with an intact epithelial barrier. Adjunctive therapy or prophylaxis with a subtherapeutic MEDI4893* dose combined with subtherapeutic doses of vancomycin or linezolid improved survival rates, compared with the monotherapies. Furthermore, coadministration of MEDI4893* with vancomycin or linezolid extended the antibiotic treatment window. These data suggest that MAb-mediated neutralization of AT holds promise in strategies for prevention and adjunctive therapy among immunocompromised patients. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  5. Peptides modeled after the alpha-domain of metallothionein induce neurite outgrowth and promote survival of cerebellar granule neurons

    DEFF Research Database (Denmark)

    Asmussen, Johanne Wirenfeldt; Ambjørn, Malene; Bock, Elisabeth

    2009-01-01

    amino acids, as potent stimulators of neuronal differentiation and survival of primary neurons. In addition, we show that a peptide derived from the N-terminus of the MT beta-domain, EmtinBn, promotes neuronal survival. The neuritogenic and survival promoting effects of EmtinAc, similar to MT and Emtin...

  6. Growth and survival of larval and early juvenile lesser sandeel in patchy prey field in the North Sea: An examination using individual-based modelling

    DEFF Research Database (Denmark)

    Gürkan, Zeren; Christensen, Asbjørn; Deurs, Mikael van

    2012-01-01

    -stages in the North Sea. Simulations of patchiness related starvation mortality are able to explain observed patterns of variation in sandeel growth. Reduced prey densities within patches decrease growth and survival rate of larvae and match–mismatch affect growth and survival of larvae with different hatch time due...... by modeling copepod size spectra dynamics and patchiness based on particle count transects and Continuous Plankton Recorder time series data. The study analyzes the effects of larval hatching time, presence of zooplankton patchiness and within patch abundance on growth and survival of sandeel early life...

  7. The rise and fall of divorce - a sociological adjustment of becker’s model of the marriage market

    DEFF Research Database (Denmark)

    Andersen, Signe Hald; Hansen, Lars Gårn

    Despite the strong and persistent influence of Gary Becker’s marriage model, the model does not completely explain the observed correlation between married women’s labor market participation and overall divorce rates. In this paper we show how a simple sociologically inspired extension of the model...

  8. Adolescents of the U.S. National Longitudinal Lesbian Family Study: male role models, gender role traits, and psychological adjustment

    NARCIS (Netherlands)

    Bos, H.; Goldberg, N.; van Gelderen, L.; Gartrell, N.

    2012-01-01

    This article focuses on the influence of male role models on the lives of adolescents (N = 78) in the U.S. National Longitudinal Lesbian Family Study. Half of the adolescents had male role models; those with and those without male role models had similar scores on the feminine and masculine scales

  9. Immediate survival focus: synthesizing life history theory and dual process models to explain substance use.

    Science.gov (United States)

    Richardson, George B; Hardesty, Patrick

    2012-01-01

    Researchers have recently applied evolutionary life history theory to the understanding of behaviors often conceived of as prosocial or antisocial. In addition, researchers have applied cognitive science to the understanding of substance use and used dual process models, where explicit cognitive processes are modeled as relatively distinct from implicit cognitive processes, to explain and predict substance use behaviors. In this paper we synthesized these two theoretical perspectives to produce an adaptive and cognitive framework for explaining substance use. We contend that this framework provides new insights into the nature of substance use that may be valuable for both clinicians and researchers.

  10. Immediate Survival Focus: Synthesizing Life History Theory and Dual Process Models to Explain Substance Use

    Directory of Open Access Journals (Sweden)

    George B. Richardson

    2012-10-01

    Full Text Available Researchers have recently applied evolutionary life history theory to the understanding of behaviors often conceived of as prosocial or antisocial. In addition, researchers have applied cognitive science to the understanding of substance use and used dual process models, where explicit cognitive processes are modeled as relatively distinct from implicit cognitive processes, to explain and predict substance use behaviors. In this paper we synthesized these two theoretical perspectives to produce an adaptive and cognitive framework for explaining substance use. We contend that this framework provides new insights into the nature of substance use that may be valuable for both clinicians and researchers.

  11. A typology of interpartner conflict and maternal parenting practices in high-risk families: examining spillover and compensatory models and implications for child adjustment.

    Science.gov (United States)

    Sturge-Apple, Melissa L; Davies, Patrick T; Cicchetti, Dante; Fittoria, Michael G

    2014-11-01

    The present study incorporates a person-based approach to identify spillover and compartmentalization patterns of interpartner conflict and maternal parenting practices in an ethnically diverse sample of 192 2-year-old children and their mothers who had experienced higher levels of socioeconomic risk. In addition, we tested whether sociocontextual variables were differentially predictive of theses profiles and examined how interpartner-parenting profiles were associated with children's physiological and psychological adjustment over time. As expected, latent class analyses extracted three primary profiles of functioning: adequate functioning, spillover, and compartmentalizing families. Furthermore, interpartner-parenting profiles were differentially associated with both sociocontextual predictors and children's adjustment trajectories. The findings highlight the developmental utility of incorporating person-based approaches to models of interpartner conflict and maternal parenting practices.

  12. Genetic value of herd life adjusted for milk production.

    Science.gov (United States)

    Allaire, F R; Gibson, J P

    1992-05-01

    Cow herd life adjusted for lactational milk production was investigated as a genetic trait in the breeding objective. Under a simple model, the relative economic weight of milk to adjusted herd life on a per genetic standard deviation basis was equal to CVY/dCVL where CVY and CVL are the genetic coefficients of variation of milk production and adjusted herd life, respectively, and d is the depreciation per year per cow divided by the total fixed costs per year per cow. The relative economic value of milk to adjusted herd life at the prices and parameters for North America was about 3.2. An increase of 100-kg milk was equivalent to 2.2 mo of adjusted herd life. Three to 7% lower economic gain is expected when only improved milk production is sought compared with a breeding objective that included both production and adjusted herd life for relative value changed +/- 20%. A favorable economic gain to cost ratio probably exists for herd life used as a genetic trait to supplement milk in the breeding objective. Cow survival records are inexpensive, and herd life evaluations from such records may not extend the generation interval when such an evaluation is used in bull sire selection.

  13. Modulation of monocytic leukemia cell function and survival by highgradient magnetic fields and mathematical modeling studies

    Czech Academy of Sciences Publication Activity Database

    Zablotskyy, Vitaliy A.; Syrovets, T.; Schmidt, Z.W.; Dejneka, Alexandr; Simmet, T.

    2014-01-01

    Roč. 35, č. 10 (2014), s. 3164-3171 ISSN 0142-9612 Grant - others:AV ČR(CZ) M100101219 Institutional support: RVO:68378271 Keywords : magnetic field * cell proliferation * leukemia * apoptosis * modeling Subject RIV: BO - Biophysics Impact factor: 8.557, year: 2014

  14. Analyzing multivariate survival data using composite likelihood and flexible parametric modeling of the hazard functions

    DEFF Research Database (Denmark)

    Nielsen, Jan; Parner, Erik

    2010-01-01

    In this paper, we model multivariate time-to-event data by composite likelihood of pairwise frailty likelihoods and marginal hazards using natural cubic splines. Both right- and interval-censored data are considered. The suggested approach is applied on two types of family studies using the gamma...

  15. Model structure of the stream salmonid simulator (S3)—A dynamic model for simulating growth, movement, and survival of juvenile salmonids

    Science.gov (United States)

    Perry, Russell W.; Plumb, John M.; Jones, Edward C.; Som, Nicholas A.; Hetrick, Nicholas J.; Hardy, Thomas B.

    2018-04-06

    Fisheries and water managers often use population models to aid in understanding the effect of alternative water management or restoration actions on anadromous fish populations. We developed the Stream Salmonid Simulator (S3) to help resource managers evaluate the effect of management alternatives on juvenile salmonid populations. S3 is a deterministic stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and usable habitat area or carrying capacity. The physical characteristics of each habitat unit and the number of fish occupying each unit, in turn, drive survival and growth within each habitat unit and movement of fish among habitat units.The purpose of this report is to outline the underlying general structure of the S3 model that is common among different applications of the model. We have developed applications of the S3 model for juvenile fall Chinook salmon (Oncorhynchus tshawytscha) in the lower Klamath River. Thus, this report is a companion to current application of the S3 model to the Trinity River (in review). The general S3 model structure provides a biological and physical framework for the salmonid freshwater life cycle. This framework captures important demographics of juvenile salmonids aimed at translating management alternatives into simulated population responses. Although the S3 model is built on this common framework, the model has been constructed to allow much flexibility in application of the model to specific river systems. The ability for practitioners to include system-specific information for the

  16. Plant Survival and Mortality during Drought Can be Mediated by Co-occurring Species' Physiological and Morphological Traits: Results from a Model

    Science.gov (United States)

    Tai, X.; Mackay, D. S.

    2015-12-01

    Interactions among co-occurring species are mediated by plant physiology, morphology and environment. Without proper mechanisms to account for these factors, it remains difficult to predict plant mortality/survival under changing climate. A plant ecophysiological model, TREES, was extended to incorporate co-occurring species' belowground interaction for water. We used it to examine the interaction between two commonly co-occurring species during drought experiment, pine (Pinus edulis) and juniper (Juniperus monosperma), with contrasting physiological traits (vulnerability to cavitation and leaf water potential regulation). TREES was parameterized and validated using field-measured plant physiological traits. The root architecture (depth, profile, and root area to leaf area ratio) of juniper was adjusted to see how root morphology could affect the survival/mortality of its neighboring pine under both ambient and drought conditions. Drought suppressed plant water and carbon uptake, as well increased the average percentage loss of conductivity (PLC). Pine had 59% reduction in water uptake, 48% reduction in carbon uptake, and 38% increase in PLC, while juniper had 56% reduction in water uptake, 50% reduction in carbon and 29% increase in PLC, suggesting different vulnerability to drought as mediated by plant physiological traits. Variations in juniper root architecture further mediated drought stress on pine, from negative to positive. Different juniper root architecture caused variations in response of pine over drought (water uptake reduction ranged 0% ~63%, carbon uptake reduction ranged 0% ~ 70%, and PLC increase ranged 2% ~ 91%). Deeper or more uniformly distributed roots of juniper could effectively mitigate stress experienced by pine. In addition, the total water and carbon uptake tended to increase as the ratio of root area to leaf area increased while PLC showed non-monotonic response, suggesting the potential trade-off between maximizing resource uptake and

  17. Skin Stem Cell Hypotheses and Long Term Clone Survival – Explored Using Agent-based Modelling

    Science.gov (United States)

    Li, X.; Upadhyay, A. K.; Bullock, A. J.; Dicolandrea, T.; Xu, J.; Binder, R. L.; Robinson, M. K.; Finlay, D. R.; Mills, K. J.; Bascom, C. C.; Kelling, C. K.; Isfort, R. J.; Haycock, J. W.; MacNeil, S.; Smallwood, R. H.

    2013-01-01

    Epithelial renewal in skin is achieved by the constant turnover and differentiation of keratinocytes. Three popular hypotheses have been proposed to explain basal keratinocyte regeneration and epidermal homeostasis: 1) asymmetric division (stem-transit amplifying cell); 2) populational asymmetry (progenitor cell with stochastic fate); and 3) populational asymmetry with stem cells. In this study, we investigated lineage dynamics using these hypotheses with a 3D agent-based model of the epidermis. The model simulated the growth and maintenance of the epidermis over three years. The offspring of each proliferative cell was traced. While all lineages were preserved in asymmetric division, the vast majority were lost when assuming populational asymmetry. The third hypothesis provided the most reliable mechanism for self-renewal by preserving genetic heterogeneity in quiescent stem cells, and also inherent mechanisms for skin ageing and the accumulation of genetic mutation. PMID:23712735

  18. Skin stem cell hypotheses and long term clone survival--explored using agent-based modelling.

    Science.gov (United States)

    Li, X; Upadhyay, A K; Bullock, A J; Dicolandrea, T; Xu, J; Binder, R L; Robinson, M K; Finlay, D R; Mills, K J; Bascom, C C; Kelling, C K; Isfort, R J; Haycock, J W; MacNeil, S; Smallwood, R H

    2013-01-01

    Epithelial renewal in skin is achieved by the constant turnover and differentiation of keratinocytes. Three popular hypotheses have been proposed to explain basal keratinocyte regeneration and epidermal homeostasis: 1) asymmetric division (stem-transit amplifying cell); 2) populational asymmetry (progenitor cell with stochastic fate); and 3) populational asymmetry with stem cells. In this study, we investigated lineage dynamics using these hypotheses with a 3D agent-based model of t