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Sample records for prognostic modeling approach

  1. A Model-Based Prognostics Approach Applied to Pneumatic Valves

    Data.gov (United States)

    National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

  2. A Model-based Prognostics Approach Applied to Pneumatic Valves

    Data.gov (United States)

    National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

  3. Using prognostic models in CLL to personalize approach to clinical care: Are we there yet?

    Science.gov (United States)

    Mina, Alain; Sandoval Sus, Jose; Sleiman, Elsa; Pinilla-Ibarz, Javier; Awan, Farrukh T; Kharfan-Dabaja, Mohamed A

    2018-03-01

    Four decades ago, two staging systems were developed to help stratify CLL into different prognostic categories. These systems, the Rai and the Binet staging, depended entirely on abnormal exam findings and evidence of anemia and thrombocytopenia. Better understanding of biologic, genetic, and molecular characteristics of CLL have contributed to better appreciating its clinical heterogeneity. New prognostic models, the GCLLSG prognostic index and the CLL-IPI, emerged. They incorporate biologic and genetic information related to CLL and are capable of predicting survival outcomes and cases anticipated to need therapy earlier in the disease course. Accordingly, these newer models are helping develop better informed surveillance strategies and ultimately tailor treatment intensity according to presence (or lack thereof) of certain prognostic markers. This represents a step towards personalizing care of CLL patients. We anticipate that as more prognostic factors continue to be identified, the GCLLSG prognostic index and CLL-IPI models will undergo further revisions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. A model-based prognostic approach to predict interconnect failure using impedance analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Dae Il; Yoon, Jeong Ah [Dept. of System Design and Control Engineering. Ulsan National Institute of Science and Technology, Ulsan (Korea, Republic of)

    2016-10-15

    The reliability of electronic assemblies is largely affected by the health of interconnects, such as solder joints, which provide mechanical, electrical and thermal connections between circuit components. During field lifecycle conditions, interconnects are often subjected to a DC open circuit, one of the most common interconnect failure modes, due to cracking. An interconnect damaged by cracking is sometimes extremely hard to detect when it is a part of a daisy-chain structure, neighboring with other healthy interconnects that have not yet cracked. This cracked interconnect may seem to provide a good electrical contact due to the compressive load applied by the neighboring healthy interconnects, but it can cause the occasional loss of electrical continuity under operational and environmental loading conditions in field applications. Thus, cracked interconnects can lead to the intermittent failure of electronic assemblies and eventually to permanent failure of the product or the system. This paper introduces a model-based prognostic approach to quantitatively detect and predict interconnect failure using impedance analysis and particle filtering. Impedance analysis was previously reported as a sensitive means of detecting incipient changes at the surface of interconnects, such as cracking, based on the continuous monitoring of RF impedance. To predict the time to failure, particle filtering was used as a prognostic approach using the Paris model to address the fatigue crack growth. To validate this approach, mechanical fatigue tests were conducted with continuous monitoring of RF impedance while degrading the solder joints under test due to fatigue cracking. The test results showed the RF impedance consistently increased as the solder joints were degraded due to the growth of cracks, and particle filtering predicted the time to failure of the interconnects similarly to their actual timesto- failure based on the early sensitivity of RF impedance.

  5. Intercomparisons of Prognostic, Diagnostic, and Inversion Modeling Approaches for Estimation of Net Ecosystem Exchange over the Pacific Northwest Region

    Science.gov (United States)

    Turner, D. P.; Jacobson, A. R.; Nemani, R. R.

    2013-12-01

    The recent development of large spatially-explicit datasets for multiple variables relevant to monitoring terrestrial carbon flux offers the opportunity to estimate the terrestrial land flux using several alternative, potentially complimentary, approaches. Here we developed and compared regional estimates of net ecosystem exchange (NEE) over the Pacific Northwest region of the U.S. using three approaches. In the prognostic modeling approach, the process-based Biome-BGC model was driven by distributed meteorological station data and was informed by Landsat-based coverages of forest stand age and disturbance regime. In the diagnostic modeling approach, the quasi-mechanistic CFLUX model estimated net ecosystem production (NEP) by upscaling eddy covariance flux tower observations. The model was driven by distributed climate data and MODIS FPAR (the fraction of incident PAR that is absorbed by the vegetation canopy). It was informed by coarse resolution (1 km) data about forest stand age. In both the prognostic and diagnostic modeling approaches, emissions estimates for biomass burning, harvested products, and river/stream evasion were added to model-based NEP to get NEE. The inversion model (CarbonTracker) relied on observations of atmospheric CO2 concentration to optimize prior surface carbon flux estimates. The Pacific Northwest is heterogeneous with respect to land cover and forest management, and repeated surveys of forest inventory plots support the presence of a strong regional carbon sink. The diagnostic model suggested a stronger carbon sink than the prognostic model, and a much larger sink that the inversion model. The introduction of Landsat data on disturbance history served to reduce uncertainty with respect to regional NEE in the diagnostic and prognostic modeling approaches. The FPAR data was particularly helpful in capturing the seasonality of the carbon flux using the diagnostic modeling approach. The inversion approach took advantage of a global

  6. Modeling for Battery Prognostics

    Science.gov (United States)

    Kulkarni, Chetan S.; Goebel, Kai; Khasin, Michael; Hogge, Edward; Quach, Patrick

    2017-01-01

    For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient

  7. A Distributed Approach to System-Level Prognostics

    Science.gov (United States)

    Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, Indranil

    2012-01-01

    Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key technology for systems health management that leads to improved safety and reliability with reduced costs. The prognostics problem is often approached from a component-centric view. However, in most cases, it is not specifically component lifetimes that are important, but, rather, the lifetimes of the systems in which these components reside. The system-level prognostics problem can be quite difficult due to the increased scale and scope of the prognostics problem and the relative Jack of scalability and efficiency of typical prognostics approaches. In order to address these is ues, we develop a distributed solution to the system-level prognostics problem, based on the concept of structural model decomposition. The system model is decomposed into independent submodels. Independent local prognostics subproblems are then formed based on these local submodels, resul ting in a scalable, efficient, and flexible distributed approach to the system-level prognostics problem. We provide a formulation of the system-level prognostics problem and demonstrate the approach on a four-wheeled rover simulation testbed. The results show that the system-level prognostics problem can be accurately and efficiently solved in a distributed fashion.

  8. A novel approach towards fatigue damage prognostics of composite materials utilizing SHM data and stochastic degradation modeling

    NARCIS (Netherlands)

    Loutas, T.; Eleftheroglou, N.

    2016-01-01

    A prognostic framework is proposed in order to estimate the remaining useful life of composite materials under fatigue loading based on acoustic emission data and a sophisticated Non Homogenous Hidden Semi Markov Model. Bayesian neural networks are also utilized as an alternative machine learning

  9. A Distributed Approach to System-Level Prognostics

    Science.gov (United States)

    2012-09-01

    the end of (useful) life ( EOL ) and/or the remaining useful life (RUL) of components, subsystems, or systems. The prognostics problem itself can be...system state estimate, computes EOL and/or RUL. In this paper, we focus on a model-based prognostics approach (Orchard & Vachtse- vanos, 2009; Daigle...been focused on individual components, and determining their EOL and RUL, e.g., (Orchard & Vachtsevanos, 2009; Saha & Goebel, 2009; Daigle & Goebel

  10. Model-based Prognostics with Concurrent Damage Progression Processes

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics approaches rely on physics-based models that describe the behavior of systems and their components. These models must account for the several...

  11. Distributed Prognostics Based on Structural Model Decomposition

    Data.gov (United States)

    National Aeronautics and Space Administration — Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based...

  12. Physics-of-Failure Approach to Prognostics

    Science.gov (United States)

    Kulkarni, Chetan S.

    2017-01-01

    As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of the electrical components present in the system. In case of electric vehicles, computing remaining battery charge is safety-critical. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. In this presentation our approach to develop a system level health monitoring safety indicator for different electronic components is presented which runs estimation and prediction algorithms to determine state-of-charge and estimate remaining useful life of respective components. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making.

  13. Concordance for prognostic models with competing risks

    DEFF Research Database (Denmark)

    Wolbers, Marcel; Blanche, Paul; Koller, Michael T

    2014-01-01

    The concordance probability is a widely used measure to assess discrimination of prognostic models with binary and survival endpoints. We formally define the concordance probability for a prognostic model of the absolute risk of an event of interest in the presence of competing risks and relate i...

  14. State of the art and taxonomy of prognostics approaches, trends of prognostics applications and open issues towards maturity at different technology readiness levels

    Science.gov (United States)

    Javed, Kamran; Gouriveau, Rafael; Zerhouni, Noureddine

    2017-09-01

    Integrating prognostics to a real application requires a certain maturity level and for this reason there is a lack of success stories about development of a complete Prognostics and Health Management system. In fact, the maturity of prognostics is closely linked to data and domain specific entities like modeling. Basically, prognostics task aims at predicting the degradation of engineering assets. However, practically it is not possible to precisely predict the impending failure, which requires a thorough understanding to encounter different sources of uncertainty that affect prognostics. Therefore, different aspects crucial to the prognostics framework, i.e., from monitoring data to remaining useful life of equipment need to be addressed. To this aim, the paper contributes to state of the art and taxonomy of prognostics approaches and their application perspectives. In addition, factors for prognostics approach selection are identified, and new case studies from component-system level are discussed. Moreover, open challenges toward maturity of the prognostics under uncertainty are highlighted and scheme for an efficient prognostics approach is presented. Finally, the existing challenges for verification and validation of prognostics at different technology readiness levels are discussed with respect to open challenges.

  15. Physics based Degradation Modeling and Prognostics of Electrolytic Capacitors under Electrical Overstress Conditions

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper proposes a physics based degradation modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors are critical components in...

  16. Prognostics Health Management and Physics based failure Models for Electrolytic Capacitors

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors and MOSFETs are the two major...

  17. Prognostic modelling options for remaining useful life estimation by industry

    Science.gov (United States)

    Sikorska, J. Z.; Hodkiewicz, M.; Ma, L.

    2011-07-01

    Over recent years a significant amount of research has been undertaken to develop prognostic models that can be used to predict the remaining useful life of engineering assets. Implementations by industry have only had limited success. By design, models are subject to specific assumptions and approximations, some of which are mathematical, while others relate to practical implementation issues such as the amount of data required to validate and verify a proposed model. Therefore, appropriate model selection for successful practical implementation requires not only a mathematical understanding of each model type, but also an appreciation of how a particular business intends to utilise a model and its outputs. This paper discusses business issues that need to be considered when selecting an appropriate modelling approach for trial. It also presents classification tables and process flow diagrams to assist industry and research personnel select appropriate prognostic models for predicting the remaining useful life of engineering assets within their specific business environment. The paper then explores the strengths and weaknesses of the main prognostics model classes to establish what makes them better suited to certain applications than to others and summarises how each have been applied to engineering prognostics. Consequently, this paper should provide a starting point for young researchers first considering options for remaining useful life prediction. The models described in this paper are Knowledge-based (expert and fuzzy), Life expectancy (stochastic and statistical), Artificial Neural Networks, and Physical models.

  18. Investigating the Effect of Damage Progression Model Choice on Prognostics Performance

    Data.gov (United States)

    National Aeronautics and Space Administration — The success of model-based approaches to systems health management depends largely on the quality of the underly- ing models. In model-based prognostics, it is...

  19. A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Wen-An Yang

    2016-01-01

    Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

  20. A molecular prognostic model predicts esophageal squamous cell carcinoma prognosis.

    Directory of Open Access Journals (Sweden)

    Hui-Hui Cao

    Full Text Available Esophageal squamous cell carcinoma (ESCC has the highest mortality rates in China. The 5-year survival rate of ESCC remains dismal despite improvements in treatments such as surgical resection and adjuvant chemoradiation, and current clinical staging approaches are limited in their ability to effectively stratify patients for treatment options. The aim of the present study, therefore, was to develop an immunohistochemistry-based prognostic model to improve clinical risk assessment for patients with ESCC.We developed a molecular prognostic model based on the combined expression of axis of epidermal growth factor receptor (EGFR, phosphorylated Specificity protein 1 (p-Sp1, and Fascin proteins. The presence of this prognostic model and associated clinical outcomes were analyzed for 130 formalin-fixed, paraffin-embedded esophageal curative resection specimens (generation dataset and validated using an independent cohort of 185 specimens (validation dataset.The expression of these three genes at the protein level was used to build a molecular prognostic model that was highly predictive of ESCC survival in both generation and validation datasets (P = 0.001. Regression analysis showed that this molecular prognostic model was strongly and independently predictive of overall survival (hazard ratio = 2.358 [95% CI, 1.391-3.996], P = 0.001 in generation dataset; hazard ratio = 1.990 [95% CI, 1.256-3.154], P = 0.003 in validation dataset. Furthermore, the predictive ability of these 3 biomarkers in combination was more robust than that of each individual biomarker.This technically simple immunohistochemistry-based molecular model accurately predicts ESCC patient survival and thus could serve as a complement to current clinical risk stratification approaches.

  1. 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.

  2. Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

    Science.gov (United States)

    Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

    2018-05-02

    The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

  3. [A prognostic model of a cholera epidemic].

    Science.gov (United States)

    Boev, B V; Bondarenko, V M; Prokop'eva, N V; San Román, R T; Raygoza-Anaya, M; García de Alba, R

    1994-01-01

    A new model for the prognostication of cholera epidemic on the territory of a large city is proposed. This model reflects the characteristic feature of contacting infection by sensitive individuals due to the preservation of Vibrio cholerae in their water habitat. The mathematical model of the epidemic quantitatively reflects the processes of the spread of infection by kinetic equations describing the interaction of the streams of infected persons, the causative agents and susceptible persons. The functions and parameters of the model are linked with the distribution of individuals according to the duration of the incubation period and infectious process, as well as the period of asymptomatic carrier state. The computer realization of the model by means of IBM PC/AT made it possible to study the cholera epidemic which took place in Mexico in 1833. The verified model of the cholera epidemic was used for the prognostication of the possible spread of this infection in Guadalajara, taking into account changes in the epidemiological situation and the size of the population, as well as improvements in sanitary and hygienic conditions, in the city.

  4. Contemporary approach to neurologic prognostication of coma after cardiac arrest.

    Science.gov (United States)

    Ben-Hamouda, Nawfel; Taccone, Fabio S; Rossetti, Andrea O; Oddo, Mauro

    2014-11-01

    Coma after cardiac arrest (CA) is an important cause of admission to the ICU. Prognosis of post-CA coma has significantly improved over the past decade, particularly because of aggressive postresuscitation care and the use of therapeutic targeted temperature management (TTM). TTM and sedatives used to maintain controlled cooling might delay neurologic reflexes and reduce the accuracy of clinical examination. In the early ICU phase, patients' good recovery may often be indistinguishable (based on neurologic examination alone) from patients who eventually will have a poor prognosis. Prognostication of post-CA coma, therefore, has evolved toward a multimodal approach that combines neurologic examination with EEG and evoked potentials. Blood biomarkers (eg, neuron-specific enolase [NSE] and soluble 100-β protein) are useful complements for coma prognostication; however, results vary among commercial laboratory assays, and applying one single cutoff level (eg, > 33 μg/L for NSE) for poor prognostication is not recommended. Neuroimaging, mainly diffusion MRI, is emerging as a promising tool for prognostication, but its precise role needs further study before it can be widely used. This multimodal approach might reduce false-positive rates of poor prognosis, thereby providing optimal prognostication of comatose CA survivors. The aim of this review is to summarize studies and the principal tools presently available for outcome prediction and to describe a practical approach to the multimodal prognostication of coma after CA, with a particular focus on neuromonitoring tools. We also propose an algorithm for the optimal use of such multimodal tools during the early ICU phase of post-CA coma.

  5. Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics has received considerable attention recently as an emerging sub-discipline within SHM. Prognosis is here strictly defined as “predicting the time at...

  6. A framework for quantifying net benefits of alternative prognostic models

    NARCIS (Netherlands)

    Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Feskens, E.J.M.; Kromhout, D.

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit)

  7. Prognostics Approach for Power MOSFET Under Thermal-Stress

    Science.gov (United States)

    Galvan, Jose Ramon Celaya; Saxena, Abhinav; Kulkarni, Chetan S.; Saha, Sankalita; Goebel, Kai

    2012-01-01

    The prognostic technique for a power MOSFET presented in this paper is based on accelerated aging of MOSFET IRF520Npbf in a TO-220 package. The methodology utilizes thermal and power cycling to accelerate the life of the devices. The major failure mechanism for the stress conditions is dieattachment degradation, typical for discrete devices with leadfree solder die attachment. It has been determined that dieattach degradation results in an increase in ON-state resistance due to its dependence on junction temperature. Increasing resistance, thus, can be used as a precursor of failure for the die-attach failure mechanism under thermal stress. A feature based on normalized ON-resistance is computed from in-situ measurements of the electro-thermal response. An Extended Kalman filter is used as a model-based prognostics techniques based on the Bayesian tracking framework. The proposed prognostics technique reports on preliminary work that serves as a case study on the prediction of remaining life of power MOSFETs and builds upon the work presented in [1]. The algorithm considered in this study had been used as prognostics algorithm in different applications and is regarded as suitable candidate for component level prognostics. This work attempts to further the validation of such algorithm by presenting it with real degradation data including measurements from real sensors, which include all the complications (noise, bias, etc.) that are regularly not captured on simulated degradation data. The algorithm is developed and tested on the accelerated aging test timescale. In real world operation, the timescale of the degradation process and therefore the RUL predictions will be considerable larger. It is hypothesized that even though the timescale will be larger, it remains constant through the degradation process and the algorithm and model would still apply under the slower degradation process. By using accelerated aging data with actual device measurements and real

  8. On prognostic models, artificial intelligence and censored observations.

    Science.gov (United States)

    Anand, S S; Hamilton, P W; Hughes, J G; Bell, D A

    2001-03-01

    The development of prognostic models for assisting medical practitioners with decision making is not a trivial task. Models need to possess a number of desirable characteristics and few, if any, current modelling approaches based on statistical or artificial intelligence can produce models that display all these characteristics. The inability of modelling techniques to provide truly useful models has led to interest in these models being purely academic in nature. This in turn has resulted in only a very small percentage of models that have been developed being deployed in practice. On the other hand, new modelling paradigms are being proposed continuously within the machine learning and statistical community and claims, often based on inadequate evaluation, being made on their superiority over traditional modelling methods. We believe that for new modelling approaches to deliver true net benefits over traditional techniques, an evaluation centric approach to their development is essential. In this paper we present such an evaluation centric approach to developing extensions to the basic k-nearest neighbour (k-NN) paradigm. We use standard statistical techniques to enhance the distance metric used and a framework based on evidence theory to obtain a prediction for the target example from the outcome of the retrieved exemplars. We refer to this new k-NN algorithm as Censored k-NN (Ck-NN). This reflects the enhancements made to k-NN that are aimed at providing a means for handling censored observations within k-NN.

  9. Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions

    Science.gov (United States)

    2012-09-01

    make end of life ( EOL ) and remaining useful life (RUL) estimations. Model-based prognostics approaches perform these tasks with the help of first...in parameters Degradation Modeling Parameter estimation Prediction Thermal / Electrical Stress Experimental Data State Space model RUL EOL ...distribution at given single time point kP , and use this for multi-step predictions to EOL . There are several methods which exits for selecting the sigma

  10. Comparison of two prognostic models for acute pulmonary embolism

    Directory of Open Access Journals (Sweden)

    Abd-ElRahim Ibrahim Youssef

    2016-10-01

    Conclusion: (1 There is an agreement to great extent in risk stratification of APE patients by PESI and ESC prognostic models, where mortality rate is increased among high risk classes of both models, (2 ESC prognostic model is more accurate than PESI model in mortality prediction of APE patients especially in the high risk class, (3 echocardiographic evidence of RVD and elevated plasma BNP can help to identify APE patients at increased risk of adverse short-term outcome and (4 integration of RVD assessment by echocardiography and BNP to clinical findings improves the prognostic value of ESC model.

  11. Predictive and Prognostic Factors in Colorectal Cancer: A Personalized Approach

    Directory of Open Access Journals (Sweden)

    Timothy A. Rockall

    2011-03-01

    Full Text Available It is an exciting time for all those engaged in the treatment of colorectal cancer. The advent of new therapies presents the opportunity for a personalized approach to the patient. This approach considers the complex genetic mechanisms involved in tumorigenesis in addition to classical clinicopathological staging. The potential predictive and prognostic biomarkers which have stemmed from the study of the genetic basis of colorectal cancer and therapeutics are discussed with a focus on mismatch repair status, KRAS, BRAF, 18qLOH, CIMP and TGF-β.

  12. Model-based Prognostics under Limited Sensing

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics is crucial to providing reliable condition-based maintenance decisions. To obtain accurate predictions of component life, a variety of sensors are often...

  13. Diagnostic and Prognostic Models for Generator Step-Up Transformers

    Energy Technology Data Exchange (ETDEWEB)

    Vivek Agarwal; Nancy J. Lybeck; Binh T. Pham

    2014-09-01

    In 2014, the online monitoring (OLM) of active components project under the Light Water Reactor Sustainability program at Idaho National Laboratory (INL) focused on diagnostic and prognostic capabilities for generator step-up transformers. INL worked with subject matter experts from the Electric Power Research Institute (EPRI) to augment and revise the GSU fault signatures previously implemented in the Electric Power Research Institute’s (EPRI’s) Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. Two prognostic models were identified and implemented for GSUs in the FW-PHM Suite software. INL and EPRI demonstrated the use of prognostic capabilities for GSUs. The complete set of fault signatures developed for GSUs in the Asset Fault Signature Database of the FW-PHM Suite for GSUs is presented in this report. Two prognostic models are described for paper insulation: the Chendong model for degree of polymerization, and an IEEE model that uses a loading profile to calculates life consumption based on hot spot winding temperatures. Both models are life consumption models, which are examples of type II prognostic models. Use of the models in the FW-PHM Suite was successfully demonstrated at the 2014 August Utility Working Group Meeting, Idaho Falls, Idaho, to representatives from different utilities, EPRI, and the Halden Research Project.

  14. A Model-based Avionic Prognostic Reasoner (MAPR)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and...

  15. Model Adaptation for Prognostics in a Particle Filtering Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated....

  16. Model-based Prognostics with Fixed-lag Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics exploits domain knowl- edge of the system, its components, and how they fail by casting the underlying physical phenom- ena in a...

  17. A framework for quantifying net benefits of alternative prognostic models

    OpenAIRE

    Rapsomaniki, E.; White, I.R.; Wood, A.M.; Thompson, S.G.; Ford, I.

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measure...

  18. A framework for quantifying net benefits of alternative prognostic models

    DEFF Research Database (Denmark)

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M

    2012-01-01

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit......) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk...... reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple...

  19. Development and validation of logistic prognostic models by predefined SAS-macros

    Directory of Open Access Journals (Sweden)

    Ziegler, Christoph

    2006-02-01

    Full Text Available In medical decision making about therapies or diagnostic procedures in the treatment of patients the prognoses of the course or of the magnitude of diseases plays a relevant role. Beside of the subjective attitude of the clinician mathematical models can help in providing such prognoses. Such models are mostly multivariate regression models. In the case of a dichotomous outcome the logistic model will be applied as the standard model. In this paper we will describe SAS-macros for the development of such a model, for examination of the prognostic performance, and for model validation. The rational for this developmental approach of a prognostic modelling and the description of the macros can only given briefly in this paper. Much more details are given in. These 14 SAS-macros are a tool for setting up the whole process of deriving a prognostic model. Especially the possibility of validating the model by a standardized software tool gives an opportunity, which is not used in general in published prognostic models. Therefore, this can help to develop new models with good prognostic performance for use in medical applications.

  20. A Systems Engineering Approach to Electro-Mechanical Actuator Diagnostic and Prognostic Development

    Data.gov (United States)

    National Aeronautics and Space Administration — The authors have formulated a Comprehensive Systems Engineering approach to Electro-Mechanical Actuator (EMA) Prognostics and Health Management (PHM) system...

  1. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

    Directory of Open Access Journals (Sweden)

    Liu Yufeng

    2011-01-01

    Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

  2. Comparison of Two Probabilistic Fatigue Damage Assessment Approaches Using Prognostic Performance Metrics

    Directory of Open Access Journals (Sweden)

    Xuefei Guan

    2011-01-01

    Full Text Available In this paper, two probabilistic prognosis updating schemes are compared. One is based on the classical Bayesian approach and the other is based on newly developed maximum relative entropy (MRE approach. The algorithm performance of the two models is evaluated using a set of recently developed prognostics-based metrics. Various uncertainties from measurements, modeling, and parameter estimations are integrated into the prognosis framework as random input variables for fatigue damage of materials. Measures of response variables are then used to update the statistical distributions of random variables and the prognosis results are updated using posterior distributions. Markov Chain Monte Carlo (MCMC technique is employed to provide the posterior samples for model updating in the framework. Experimental data are used to demonstrate the operation of the proposed probabilistic prognosis methodology. A set of prognostics-based metrics are employed to quantitatively evaluate the prognosis performance and compare the proposed entropy method with the classical Bayesian updating algorithm. In particular, model accuracy, precision, robustness and convergence are rigorously evaluated in addition to the qualitative visual comparison. Following this, potential development and improvement for the prognostics-based metrics are discussed in detail.

  3. An Approach to Prognostic Decision Making in the Aerospace Domain

    Data.gov (United States)

    National Aeronautics and Space Administration — The field of Prognostic Health Management (PHM) has been undergoing rapid growth in recent years, with development of increasingly sophisticated techniques for...

  4. Prognostics for Steam Generator Tube Rupture using Markov Chain model

    International Nuclear Information System (INIS)

    Kim, Gibeom; Heo, Gyunyoung; Kim, Hyeonmin

    2016-01-01

    This paper will describe the prognostics method for evaluating and forecasting the ageing effect and demonstrate the procedure of prognostics for the Steam Generator Tube Rupture (SGTR) accident. Authors will propose the data-driven method so called MCMC (Markov Chain Monte Carlo) which is preferred to the physical-model method in terms of flexibility and availability. Degradation data is represented as growth of burst probability over time. Markov chain model is performed based on transition probability of state. And the state must be discrete variable. Therefore, burst probability that is continuous variable have to be changed into discrete variable to apply Markov chain model to the degradation data. The Markov chain model which is one of prognostics methods was described and the pilot demonstration for a SGTR accident was performed as a case study. The Markov chain model is strong since it is possible to be performed without physical models as long as enough data are available. However, in the case of the discrete Markov chain used in this study, there must be loss of information while the given data is discretized and assigned to the finite number of states. In this process, original information might not be reflected on prediction sufficiently. This should be noted as the limitation of discrete models. Now we will be studying on other prognostics methods such as GPM (General Path Model) which is also data-driven method as well as the particle filer which belongs to physical-model method and conducting comparison analysis

  5. Application of the Sensor Selection Approach in Polymer Electrolyte Membrane Fuel Cell Prognostics and Health Management

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    Lei Mao

    2017-09-01

    Full Text Available In this paper, the sensor selection approach is investigated with the aim of using fewer sensors to provide reliable fuel cell diagnostic and prognostic results. The sensitivity of sensors is firstly calculated with a developed fuel cell model. With sensor sensitivities to different fuel cell failure modes, the available sensors can be ranked. A sensor selection algorithm is used in the analysis, which considers both sensor sensitivity to fuel cell performance and resistance to noise. The performance of the selected sensors in polymer electrolyte membrane (PEM fuel cell prognostics is also evaluated with an adaptive neuro-fuzzy inference system (ANFIS, and results show that the fuel cell voltage can be predicted with good quality using the selected sensors. Furthermore, a fuel cell test is performed to investigate the effectiveness of selected sensors in fuel cell fault diagnosis. From the results, different fuel cell states can be distinguished with good quality using the selected sensors.

  6. Physics Based Modeling and Prognostics of Electrolytic Capacitors

    Science.gov (United States)

    Kulkarni, Chetan; Ceyla, Jose R.; Biswas, Gautam; Goebel, Kai

    2012-01-01

    This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors have become critical components in electronics systems in aeronautics and other domains. Degradations and faults in DC-DC converter unit propagates to the GPS and navigation subsystems and affects the overall solution. Capacitors and MOSFETs are the two major components, which cause degradations and failures in DC-DC converters. This type of capacitors are known for its low reliability and frequent breakdown on critical systems like power supplies of avionics equipment and electrical drivers of electromechanical actuators of control surfaces. Some of the more prevalent fault effects, such as a ripple voltage surge at the power supply output can cause glitches in the GPS position and velocity output, and this, in turn, if not corrected will propagate and distort the navigation solution. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

  7. A framework for quantifying net benefits of alternative prognostic models.

    Science.gov (United States)

    Rapsomaniki, Eleni; White, Ian R; Wood, Angela M; Thompson, Simon G

    2012-01-30

    New prognostic models are traditionally evaluated using measures of discrimination and risk reclassification, but these do not take full account of the clinical and health economic context. We propose a framework for comparing prognostic models by quantifying the public health impact (net benefit) of the treatment decisions they support, assuming a set of predetermined clinical treatment guidelines. The change in net benefit is more clinically interpretable than changes in traditional measures and can be used in full health economic evaluations of prognostic models used for screening and allocating risk reduction interventions. We extend previous work in this area by quantifying net benefits in life years, thus linking prognostic performance to health economic measures; by taking full account of the occurrence of events over time; and by considering estimation and cross-validation in a multiple-study setting. The method is illustrated in the context of cardiovascular disease risk prediction using an individual participant data meta-analysis. We estimate the number of cardiovascular-disease-free life years gained when statin treatment is allocated based on a risk prediction model with five established risk factors instead of a model with just age, gender and region. We explore methodological issues associated with the multistudy design and show that cost-effectiveness comparisons based on the proposed methodology are robust against a range of modelling assumptions, including adjusting for competing risks. Copyright © 2011 John Wiley & Sons, Ltd.

  8. Application of Prognostic Mesoscale Modeling in the Southeast United States

    International Nuclear Information System (INIS)

    Buckley, R.L.

    1999-01-01

    A prognostic model is being used to provide regional forecasts for a variety of applications at the Savannah River Site (SRS). Emergency response dispersion models available at SRS use the space and time-dependent meteorological data provided by this model to supplement local and regional observations. Output from the model is also used locally to aid in forecasting at SRS, and regionally in providing forecasts of the potential time and location of hurricane landfall within the southeast United States

  9. Risk factors and prognostic models for perinatal asphyxia at term

    NARCIS (Netherlands)

    Ensing, S.

    2015-01-01

    This thesis will focus on the risk factors and prognostic models for adverse perinatal outcome at term, with a special focus on perinatal asphyxia and obstetric interventions during labor to reduce adverse pregnancy outcomes. For the majority of the studies in this thesis we were allowed to use data

  10. A Distributed Approach to System-Level Prognostics

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key tech- nology for systems health management that leads...

  11. Systematic review of prognostic models in traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Roberts Ian

    2006-11-01

    Full Text Available Abstract Background Traumatic brain injury (TBI is a leading cause of death and disability world-wide. The ability to accurately predict patient outcome after TBI has an important role in clinical practice and research. Prognostic models are statistical models that combine two or more items of patient data to predict clinical outcome. They may improve predictions in TBI patients. Multiple prognostic models for TBI have accumulated for decades but none of them is widely used in clinical practice. The objective of this systematic review is to critically assess existing prognostic models for TBI Methods Studies that combine at least two variables to predict any outcome in patients with TBI were searched in PUBMED and EMBASE. Two reviewers independently examined titles, abstracts and assessed whether each met the pre-defined inclusion criteria. Results A total of 53 reports including 102 models were identified. Almost half (47% were derived from adult patients. Three quarters of the models included less than 500 patients. Most of the models (93% were from high income countries populations. Logistic regression was the most common analytical strategy to derived models (47%. In relation to the quality of the derivation models (n:66, only 15% reported less than 10% pf loss to follow-up, 68% did not justify the rationale to include the predictors, 11% conducted an external validation and only 19% of the logistic models presented the results in a clinically user-friendly way Conclusion Prognostic models are frequently published but they are developed from small samples of patients, their methodological quality is poor and they are rarely validated on external populations. Furthermore, they are not clinically practical as they are not presented to physicians in a user-friendly way. Finally because only a few are developed using populations from low and middle income countries, where most of trauma occurs, the generalizability to these setting is limited.

  12. Designing Data-Driven Battery Prognostic Approaches for Variable Loading Profiles: Some Lessons Learned

    Data.gov (United States)

    National Aeronautics and Space Administration — Among various approaches for implementing prognostic algorithms data-driven algorithms are popular in the industry due to their intuitive nature and relatively fast...

  13. Model Adaptation for Prognostics in a Particle Filtering Framework

    Directory of Open Access Journals (Sweden)

    Bhaskar Saha

    2011-01-01

    Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  14. Model Adaptation for Prognostics in a Particle Filtering Framework

    Science.gov (United States)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  15. A self-cognizant dynamic system approach for prognostics and health management

    Science.gov (United States)

    Bai, Guangxing; Wang, Pingfeng; Hu, Chao

    2015-03-01

    Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how and when a system will degrade its performance and lose its partial or whole functionality. Due to the complexity and invisibility of rules and states of most dynamic systems, developing an effective approach to track evolving system states becomes a major challenge. This paper presents a new self-cognizant dynamic system (SCDS) approach that incorporates artificial intelligence into dynamic system modeling for PHM. A feed-forward neural network (FFNN) is selected to approximate a complex system response which is challenging task in general due to inaccessible system physics. The trained FFNN model is then embedded into a dual extended Kalman filter algorithm to track down system dynamics. A recursive computation technique used to update the FFNN model using online measurements is also derived. To validate the proposed SCDS approach, a battery dynamic system is considered as an experimental application. After modeling the battery system by a FFNN model and a state-space model, the state-of-charge (SoC) and state-of-health (SoH) are estimated by updating the FFNN model using the proposed approach. Experimental results suggest that the proposed approach improves the efficiency and accuracy for battery health management.

  16. Electrochemistry-based Battery Modeling for Prognostics

    Science.gov (United States)

    Daigle, Matthew J.; Kulkarni, Chetan Shrikant

    2013-01-01

    Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.

  17. An Approach to Prognostic Decision Making in the Aerospace Domain

    Science.gov (United States)

    2012-09-01

    prediction of the Remaining Useful Life (RUL) and End of Life ( EOL ) as the goal of prognostics (Daigle & Goebel, 2010; Saxena et al., 2008). We believe...the drive). Either depletion of energy or com- plete component failure signify EOL . The goal of the PDM system is to reassess the original mission plan...either energy depletion or vehicle health deterioration resulted in EOL . PPG was allocated a limited number of utility function calls (UFC) to test

  18. A Physics-Based Modeling Framework for Prognostic Studies

    Science.gov (United States)

    Kulkarni, Chetan S.

    2014-01-01

    Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable

  19. Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

    Directory of Open Access Journals (Sweden)

    Sarah R. Haile

    2017-12-01

    Full Text Available Abstract Background Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them. Methods Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined. Results We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small. Conclusions We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties

  20. A Prognostic Model for Development of Profound Shock among Children Presenting with Dengue Shock Syndrome.

    Directory of Open Access Journals (Sweden)

    Phung Khanh Lam

    Full Text Available To identify risk factors and develop a prediction model for the development of profound and recurrent shock amongst children presenting with dengue shock syndrome (DSS.We analyzed data from a prospective cohort of children with DSS recruited at the Paediatric Intensive Care Unit of the Hospital for Tropical Disease in Ho Chi Minh City, Vietnam. The primary endpoint was "profound DSS", defined as ≥2 recurrent shock episodes (for subjects presenting in compensated shock, or ≥1 recurrent shock episodes (for subjects presenting initially with decompensated/hypotensive shock, and/or requirement for inotropic support. Recurrent shock was evaluated as a secondary endpoint. Risk factors were pre-defined clinical and laboratory variables collected at the time of presentation with shock. Prognostic model development was based on logistic regression and compared to several alternative approaches.The analysis population included 1207 children of whom 222 (18% progressed to "profound DSS" and 433 (36% had recurrent shock. Independent risk factors for both endpoints included younger age, earlier presentation, higher pulse rate, higher temperature, higher haematocrit and, for females, worse hemodynamic status at presentation. The final prognostic model for "profound DSS" showed acceptable discrimination (AUC=0.69 for internal validation and calibration and is presented as a simple score-chart.Several risk factors for development of profound or recurrent shock among children presenting with DSS were identified. The score-chart derived from the prognostic models should improve triage and management of children presenting with DSS in dengue-endemic areas.

  1. Prognostics for Microgrid Components

    Science.gov (United States)

    Saxena, Abhinav

    2012-01-01

    Prognostics is the science of predicting future performance and potential failures based on targeted condition monitoring. Moving away from the traditional reliability centric view, prognostics aims at detecting and quantifying the time to impending failures. This advance warning provides the opportunity to take actions that can preserve uptime, reduce cost of damage, or extend the life of the component. The talk will focus on the concepts and basics of prognostics from the viewpoint of condition-based systems health management. Differences with other techniques used in systems health management and philosophies of prognostics used in other domains will be shown. Examples relevant to micro grid systems and subsystems will be used to illustrate various types of prediction scenarios and the resources it take to set up a desired prognostic system. Specifically, the implementation results for power storage and power semiconductor components will demonstrate specific solution approaches of prognostics. The role of constituent elements of prognostics, such as model, prediction algorithms, failure threshold, run-to-failure data, requirements and specifications, and post-prognostic reasoning will be explained. A discussion on performance evaluation and performance metrics will conclude the technical discussion followed by general comments on open research problems and challenges in prognostics.

  2. A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Fernando Sánchez Lasheras

    2015-03-01

    Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

  3. Updating and prospective validation of a prognostic model for high sickness absence

    NARCIS (Netherlands)

    Roelen, C.A.M.; Heymans, M.W.; Twisk, J.W.R.; van Rhenen, W.; Pallesen, S.; Bjorvatn, B.; Moen, B.E.; Mageroy, N.

    2015-01-01

    Objectives To further develop and validate a Dutch prognostic model for high sickness absence (SA). Methods Three-wave longitudinal cohort study of 2,059 Norwegian nurses. The Dutch prognostic model was used to predict high SA among Norwegian nurses at wave 2. Subsequently, the model was updated by

  4. Unsupervised versus Supervised Identification of Prognostic Factors in Patients with Localized Retroperitoneal Sarcoma: A Data Clustering and Mahalanobis Distance Approach

    Directory of Open Access Journals (Sweden)

    Rita De Sanctis

    2018-01-01

    Full Text Available The aim of this report is to unveil specific prognostic factors for retroperitoneal sarcoma (RPS patients by univariate and multivariate statistical techniques. A phase I-II study on localized RPS treated with high-dose ifosfamide and radiotherapy followed by surgery (ISG-STS 0303 protocol demonstrated that chemo/radiotherapy was safe and increased the 3-year relapse-free survival (RFS with respect to historical controls. Of 70 patients, twenty-six developed local, 10 distant, and 5 combined relapse. Median disease-free interval (DFI was 29.47 months. According to a discriminant function analysis, DFI, histology, relapse pattern, and the first treatment approach at relapse had a statistically significant prognostic impact. Based on scientific literature and clinical expertise, clinicopathological data were analyzed using both a supervised and an unsupervised classification method to predict the prognosis, with similar sample sizes (66 and 65, resp., in casewise approach and 70 in mean-substitution one. This is the first attempt to predict patients’ prognosis by means of multivariate statistics, and in this light, it looks noticable that (i some clinical data have a well-defined prognostic value, (ii the unsupervised model produced comparable results with respect to the supervised one, and (iii the appropriate combination of both models appears fruitful and easily extensible to different clinical contexts.

  5. Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

    Science.gov (United States)

    Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

  6. Identifying prognostic features by bottom-up approach and correlating to drug repositioning.

    Directory of Open Access Journals (Sweden)

    Wei Li

    Full Text Available Traditionally top-down method was used to identify prognostic features in cancer research. That is to say, differentially expressed genes usually in cancer versus normal were identified to see if they possess survival prediction power. The problem is that prognostic features identified from one set of patient samples can rarely be transferred to other datasets. We apply bottom-up approach in this study: survival correlated or clinical stage correlated genes were selected first and prioritized by their network topology additionally, then a small set of features can be used as a prognostic signature.Gene expression profiles of a cohort of 221 hepatocellular carcinoma (HCC patients were used as a training set, 'bottom-up' approach was applied to discover gene-expression signatures associated with survival in both tumor and adjacent non-tumor tissues, and compared with 'top-down' approach. The results were validated in a second cohort of 82 patients which was used as a testing set.Two sets of gene signatures separately identified in tumor and adjacent non-tumor tissues by bottom-up approach were developed in the training cohort. These two signatures were associated with overall survival times of HCC patients and the robustness of each was validated in the testing set, and each predictive performance was better than gene expression signatures reported previously. Moreover, genes in these two prognosis signature gave some indications for drug-repositioning on HCC. Some approved drugs targeting these markers have the alternative indications on hepatocellular carcinoma.Using the bottom-up approach, we have developed two prognostic gene signatures with a limited number of genes that associated with overall survival times of patients with HCC. Furthermore, prognostic markers in these two signatures have the potential to be therapeutic targets.

  7. Measures to assess the prognostic ability of the stratified Cox proportional hazards model

    DEFF Research Database (Denmark)

    (Tybjaerg-Hansen, A.) The Fibrinogen Studies Collaboration.The Copenhagen City Heart Study; Tybjærg-Hansen, Anne

    2009-01-01

    Many measures have been proposed to summarize the prognostic ability of the Cox proportional hazards (CPH) survival model, although none is universally accepted for general use. By contrast, little work has been done to summarize the prognostic ability of the stratified CPH model; such measures...

  8. Simplified prognostic model for critically ill patients in resource limited settings in South Asia

    NARCIS (Netherlands)

    Haniffa, Rashan; Mukaka, Mavuto; Munasinghe, Sithum Bandara; de Silva, Ambepitiyawaduge Pubudu; Jayasinghe, Kosala Saroj Amarasiri; Beane, Abi; de Keizer, Nicolette; Dondorp, Arjen M.

    2017-01-01

    Background: Current critical care prognostic models are predominantly developed in high-income countries (HICs) and may not be feasible in intensive care units (ICUs) in lower-and middle-income countries (LMICs). Existing prognostic models cannot be applied without validation in LMICs as the

  9. A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

    Science.gov (United States)

    Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

  10. Prognostic factors in invasive bladder carcinoma treated by combined modality protocol (organ-sparing approach)

    International Nuclear Information System (INIS)

    Matos, Tadeja; Cufer, Tanja; Cervek, Jozica; Borstnar, Simona; Kragelj, Borut; Zumer-Pregelj, Mirjana

    2000-01-01

    Purpose: The results of bladder sparing approach for the treatment of muscle-invasive bladder cancer, using a combination of transurethral resection (TUR), chemotherapy, and radiotherapy, are encouraging. The survival of patients treated by this method is similar to the survival of patients treated by radical cystectomy. The aim of our study was to find out which pretreatment characteristics influence the survival of patients treated by organ sparing approach that would enable us to identify the patients most suitable for this type of treatment. Methods and Materials: The prognostic value of different factors, such as age, gender, performance status, hemoglobin level, clinical stage, histologic grade, presence of obstructive uropathy, and completeness of TUR, has been studied in 105 patients with invasive bladder cancer, who received a bladder sparing treatment in the period from 1988 to 1995. They were treated with a combination of TUR, followed by 2-4 cycles of methotrexate, cisplatinum, and vinblastine polychemotherapy. In complete responders the treatment was completed by radiotherapy (50 Gy to the bladder and 40 Gy to the regional lymph nodes), whereas nonresponders underwent cystectomy whenever feasible. Results: Our study has confirmed an independent prognostic value of performance status, histologic grade, and obstructive uropathy, for the disease-specific survival (DSS) of bladder cancer patients treated by a conservative approach. We believe that performance status best reflects the extent of disease and exerts significant influence on the extent and course of treatment, while obstructive uropathy is a good indicator of local spread of the disease, better than clinical T-stage. Our finding that histologic grade is one of the strongest prognostic factors shows that tumor biology also is a very important prognostic factor in patients treated by conservative approach. Conclusion: Patients with muscle-invasive bladder cancer who are most likely to benefit

  11. Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection.

    Science.gov (United States)

    Van Steen, Kristel; Curran, Desmond; Kramer, Jocelyn; Molenberghs, Geert; Van Vreckem, Ann; Bottomley, Andrew; Sylvester, Richard

    2002-12-30

    Clinical and quality of life (QL) variables from an EORTC clinical trial of first line chemotherapy in advanced breast cancer were used in a prognostic factor analysis of survival and response to chemotherapy. For response, different final multivariate models were obtained from forward and backward selection methods, suggesting a disconcerting instability. Quality of life was measured using the EORTC QLQ-C30 questionnaire completed by patients. Subscales on the questionnaire are known to be highly correlated, and therefore it was hypothesized that multicollinearity contributed to model instability. A correlation matrix indicated that global QL was highly correlated with 7 out of 11 variables. In a first attempt to explore multicollinearity, we used global QL as dependent variable in a regression model with other QL subscales as predictors. Afterwards, standard diagnostic tests for multicollinearity were performed. An exploratory principal components analysis and factor analysis of the QL subscales identified at most three important components and indicated that inclusion of global QL made minimal difference to the loadings on each component, suggesting that it is redundant in the model. In a second approach, we advocate a bootstrap technique to assess the stability of the models. Based on these analyses and since global QL exacerbates problems of multicollinearity, we therefore recommend that global QL be excluded from prognostic factor analyses using the QLQ-C30. The prognostic factor analysis was rerun without global QL in the model, and selected the same significant prognostic factors as before. Copyright 2002 John Wiley & Sons, Ltd.

  12. Improvement of PSA Models Using Monitoring and Prognostics

    Energy Technology Data Exchange (ETDEWEB)

    Heo, Gyun Young; Chang, Yoon Suk; Kim, Hyun Dae [Kyung Hee University, Yongin (Korea, Republic of)

    2014-08-15

    Probabilistic Safety Assessment (PSA) has performed a significant role for quantitative decision-making by finding design and operational vulnerability and evaluating cost-benefit in improving such weak points. Especially, it has been widely used as the core methodology for Risk-Informed Applications (RIAs). Even though the nature of PSA seeks realistic results, there are still 'conservative' aspects. The sources for the conservatism come from the assumption of safety analysis and the estimation of failure frequency. Surveillance, Diagnosis, and Prognosis (SDP) utilizing massive database and information technology is worthwhile to be highlighted in terms of the capability of alleviating the conservatism in the conventional PSA. This paper provides enabling techniques to concretize the method to provide time- and condition-dependent risk by integrating a conventional PSA model with condition monitoring and prognostics techniques. We will discuss how to integrate the results with frequency of initiating events (IEs) and failure probability of basic events (BEs). Two illustrative examples will be introduced: how the failure probability of a passive system can be evaluated under different plant conditions and how the IE frequency for Steam Generator Tube Rupture (SGTR) can be updated in terms of operating time. We expect that the proposed PSA model can take a role of annunciator to show the variation of Core Damage Frequency (CDF) in terms of time and operational conditions.

  13. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1994-01-01

    Most of today's general circulation models (GCMs) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, an urgent need for improvements in the treatment of clouds in GCMs has arisen, especially as the clouds relate to radiation. In this paper, we investigate the effects of introducing prognostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the longwave emissivity calculations. Results from several sensitivity simulations show that realistic water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds becomes stronger because of more realistic tropical convection

  14. Plaque Brachytherapy for Uveal Melanoma: A Vision Prognostication Model

    International Nuclear Information System (INIS)

    Khan, Niloufer; Khan, Mohammad K.; Bena, James; Macklis, Roger; Singh, Arun D.

    2012-01-01

    Purpose: To generate a vision prognostication model after plaque brachytherapy for uveal melanoma. Methods and Materials: All patients with primary single ciliary body or choroidal melanoma treated with iodine-125 or ruthenium-106 plaque brachytherapy between January 1, 2005, and June 30, 2010, were included. The primary endpoint was loss of visual acuity. Only patients with initial visual acuity better than or equal to 20/50 were used to evaluate visual acuity worse than 20/50 at the end of the study, and only patients with initial visual acuity better than or equal to 20/200 were used to evaluate visual acuity worse than 20/200 at the end of the study. Factors analyzed were sex, age, cataracts, diabetes, tumor size (basal dimension and apical height), tumor location, and radiation dose to the tumor apex, fovea, and optic disc. Univariate and multivariable Cox proportional hazards were used to determine the influence of baseline patient factors on vision loss. Kaplan-Meier curves (log rank analysis) were used to estimate freedom from vision loss. Results: Of 189 patients, 92% (174) were alive as of February 1, 2011. At presentation, visual acuity was better than or equal to 20/50 and better than or equal to 20/200 in 108 and 173 patients, respectively. Of these patients, 44.4% (48) had post-treatment visual acuity of worse than 20/50 and 25.4% (44) had post-treatment visual acuity worse than 20/200. By multivariable analysis, increased age (hazard ratio [HR] of 1.01 [1.00-1.03], P=.05), increase in tumor height (HR of 1.35 [1.22-1.48], P<.001), and a greater total dose to the fovea (HR of 1.01 [1.00-1.01], P<.001) were predictive of vision loss. This information was used to develop a nomogram predictive of vision loss. Conclusions: By providing a means to predict vision loss at 3 years after treatment, our vision prognostication model can be an important tool for patient selection and treatment counseling.

  15. Plaque Brachytherapy for Uveal Melanoma: A Vision Prognostication Model

    Energy Technology Data Exchange (ETDEWEB)

    Khan, Niloufer [Department of Radiation Oncology, Taussig Cancer Center, Cleveland Clinic, Cleveland, Ohio (United States); Khan, Mohammad K. [Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia (United States); Bena, James [Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio (United States); Macklis, Roger [Department of Radiation Oncology, Taussig Cancer Center, Cleveland Clinic, Cleveland, Ohio (United States); Singh, Arun D., E-mail: singha@ccf.org [Department of Ophthalmic Oncology, Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio (United States)

    2012-11-01

    Purpose: To generate a vision prognostication model after plaque brachytherapy for uveal melanoma. Methods and Materials: All patients with primary single ciliary body or choroidal melanoma treated with iodine-125 or ruthenium-106 plaque brachytherapy between January 1, 2005, and June 30, 2010, were included. The primary endpoint was loss of visual acuity. Only patients with initial visual acuity better than or equal to 20/50 were used to evaluate visual acuity worse than 20/50 at the end of the study, and only patients with initial visual acuity better than or equal to 20/200 were used to evaluate visual acuity worse than 20/200 at the end of the study. Factors analyzed were sex, age, cataracts, diabetes, tumor size (basal dimension and apical height), tumor location, and radiation dose to the tumor apex, fovea, and optic disc. Univariate and multivariable Cox proportional hazards were used to determine the influence of baseline patient factors on vision loss. Kaplan-Meier curves (log rank analysis) were used to estimate freedom from vision loss. Results: Of 189 patients, 92% (174) were alive as of February 1, 2011. At presentation, visual acuity was better than or equal to 20/50 and better than or equal to 20/200 in 108 and 173 patients, respectively. Of these patients, 44.4% (48) had post-treatment visual acuity of worse than 20/50 and 25.4% (44) had post-treatment visual acuity worse than 20/200. By multivariable analysis, increased age (hazard ratio [HR] of 1.01 [1.00-1.03], P=.05), increase in tumor height (HR of 1.35 [1.22-1.48], P<.001), and a greater total dose to the fovea (HR of 1.01 [1.00-1.01], P<.001) were predictive of vision loss. This information was used to develop a nomogram predictive of vision loss. Conclusions: By providing a means to predict vision loss at 3 years after treatment, our vision prognostication model can be an important tool for patient selection and treatment counseling.

  16. Expression of CD markers' in immune thrombocytopenic purpura: prognostic approaches.

    Science.gov (United States)

    Behzad, Masumeh Maleki; Asnafi, Ali Amin; Jaseb, Kaveh; Jalali Far, Mohammad Ali; Saki, Najmaldin

    2017-12-01

    Immune Thrombocytopenic Purpura (ITP) is a common autoimmune bleeding disorder characterized by a reduction in peripheral blood platelet counts. In this disease, autoantibodies (Auto-Abs) are produced against platelet GPIIb/GPIIIa by B cells, which require interaction with T cells. In this review, the importance of B and T lymphocytes in ITP prognosis has been studied. Relevant literature was identified by a PubMed search (1990-2016) of English-language papers using the terms B and T lymphocyte, platelet, CD markers and immune thrombocytopenic purpura. T and B lymphocytes are the main immune cells in the body. Defective function causes disrupted balance of different subgroups of lymphocytes, and abnormal expression of surface markers of these cells results in self-tolerance dysfunction, as well as induction of Auto-Abs against platelet glycoproteins (PG). Given the role of B and T cells in production of autoantibodies against PG, it can be stated that the detection of changes in CD markers' expression in these cells can be a good approach for assessing prognosis in ITP patients. © 2017 APMIS. Published by John Wiley & Sons Ltd.

  17. Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods.

    Science.gov (United States)

    Parkinson, Craig; Foley, Kieran; Whybra, Philip; Hills, Robert; Roberts, Ashley; Marshall, Chris; Staffurth, John; Spezi, Emiliano

    2018-04-11

    Prognosis in oesophageal cancer (OC) is poor. The 5-year overall survival (OS) rate is approximately 15%. Personalised medicine is hoped to increase the 5- and 10-year OS rates. Quantitative analysis of PET is gaining substantial interest in prognostic research but requires the accurate definition of the metabolic tumour volume. This study compares prognostic models developed in the same patient cohort using individual PET segmentation algorithms and assesses the impact on patient risk stratification. Consecutive patients (n = 427) with biopsy-proven OC were included in final analysis. All patients were staged with PET/CT between September 2010 and July 2016. Nine automatic PET segmentation methods were studied. All tumour contours were subjectively analysed for accuracy, and segmentation methods with segmentation methods studied, clustering means (KM2), general clustering means (GCM3), adaptive thresholding (AT) and watershed thresholding (WT) methods were included for analysis. Known clinical prognostic factors (age, treatment and staging) were significant in all of the developed prognostic models. AT and KM2 segmentation methods developed identical prognostic models. Patient risk stratification was dependent on the segmentation method used to develop the prognostic model with up to 73 patients (17.1%) changing risk stratification group. Prognostic models incorporating quantitative image features are dependent on the method used to delineate the primary tumour. This has a subsequent effect on risk stratification, with patients changing groups depending on the image segmentation method used.

  18. Degradations analysis and aging modeling for health assessment and prognostics of PEMFC

    International Nuclear Information System (INIS)

    Jouin, Marine; Gouriveau, Rafael; Hissel, Daniel; Péra, Marie-Cécile; Zerhouni, Noureddine

    2016-01-01

    Applying prognostics to Proton Exchange Membrane Fuel Cell (PEMFC) stacks is a good solution to help taking actions extending their lifetime. However, it requires a great understanding of the degradation mechanisms and failures occurring within the stack. This task is not simple when applied to a PEMFC due to the different levels (stack - cells - components), the different scales and the multiple causes that lead to degradation. To overcome this problem, this work proposes a methodology dedicated to the setting of a framework and a modeling of the aging for prognostics. This methodology is based on a deep literature review and degradation analyses of PEMFC stacks. This analysis allows defining a proper vocabulary dedicated to PEMFC's prognostics and health management and a clear limited framework to perform prognostics. Then the degradations review is used to select critical components within the stack, and to define their critical failure mechanisms thanks the proposal of new fault trees. The impact of these critical components and mechanisms on the power loss during aging is included to the model for prognostics. This model is finally validated on four datasets with different mission profiles both for health assessment and prognostics. - Highlights: • A proper framework to perform PHM, particularly prognostics, of PEMFC is proposed. • A degradation analysis is performed. • A completely new model of PEMFC degradation is proposed. • SOH estimation is performed with very high coefficients of determination.

  19. Enhancement of Physics-of-Failure Prognostic Models with System Level Features

    National Research Council Canada - National Science Library

    Kacprzynski, Gregory

    2002-01-01

    .... The novelty in the current prognostic tool development is that predictions are made through the fusion of stochastic physics-of-failure models, relevant system or component level health monitoring...

  20. Context-Dependent Prognostics and Health Assessment: A Condition-Based Maintenance Approach That Supports Mission Compliance

    Energy Technology Data Exchange (ETDEWEB)

    Allgood, G.O.; Kercel, S.W.

    1999-04-19

    In today's manufacturing environment, plants, systems, and equipment are being asked to perform at levels not thought possible a decade ago. The intent is to improve process operations and equipment reliability, availability, and maintainability without costly upgrades. Of course these gains must be achieved without impacting operational performance. Downsizing is also taking its toll on operations. Loss of personnel, particularly those who represent the corporate history, is depleting US industries of their valuable experiential base which has been relied on so heavily in the past. These realizations are causing companies to rethink their condition-based maintenance policies by moving away from reacting to equipment problems to taking a proactive approach by anticipating needs based on market and customer requirements. This paper describes a different approach to condition-based maintenance-context-dependent prognostics and health assessment. This diagnostic capability is developed around a context-dependent model that provides a capability to anticipate impending failures and determine machine performance over a protracted period of time. This prognostic capability links operational requirements to an economic performance model. In this context, a system may provide 100% operability with less than 100% functionality. This paradigm is used to facilitate optimal logistic supply and support.

  1. Prognostics and Condition-Based Maintenance: A New Approach to Precursive Metrics

    International Nuclear Information System (INIS)

    Jarrell, Donald B.; Sisk, Daniel R.; Bond, Leonard J.

    2004-01-01

    The assumptions used in the design basis of process equipment have always been as much art as science. The usually imprecise boundaries of the equipments' operational envelope provide opportunities for two major improvements in the operations and maintenance (O and M) of process machinery: (a) the actual versus intended machine environment can be understood and brought into much better alignment and (b) the end goal can define O and M strategies in terms of life cycle and economic management of plant assets.Scientists at the Pacific Northwest National Laboratory (PNNL) have performed experiments aimed at understanding and controlling aging of both safety-specific nuclear plant components and the infrastructure that supports essential plant processes. In this paper we examine the development of aging precursor metrics and their correlation with degradation rate and projected machinery failure.Degradation-specific correlations have been developed at PNNL that will allow accurate physics-based diagnostic and prognostic determinations to be derived from a new view of condition-based maintenance. This view, founded in root cause analysis, is focused on quantifying the primary stressor(s) responsible for degradation in the component of interest and formulating a deterministic relationship between the stressor intensity and the resulting degradation rate. This precursive relationship between the performance, degradation, and underlying stressor set is used to gain a first-principles approach to prognostic determinations. A holistic infrastructure approach, as applied through a conditions-based maintenance framework, will allow intelligent, automated diagnostic and prognostic programming to provide O and M practitioners with an understanding of the condition of their machinery today and an assurance of its operational state tomorrow

  2. Prognostics and Condition Based Maintenance: A New Approach to Precursive Metrics

    International Nuclear Information System (INIS)

    Jarrell, Donald B.; Sisk, Daniel R.; Bond, Leonard J.

    2002-01-01

    Scientists at the Pacific Northwest National Laboratory (PNNL) have examined the necessity for understanding and controlling the aging process of both safety-specific plant components and the infrastructure that supports these processes. In this paper we examine the preliminary development of aging precursor metrics and their correlation with degradation rate and projected machine failure. Degradation specific correlations are currently being developed at PNNL that will allow accurate physics-based diagnostic and prognostic determinations to be derived from a new view of condition based maintenance. This view, founded in root cause analysis, is focused on quantifying the primary stressor(s) responsible for degradation in the component of interest. The derivative relationship between the performance, degradation and the underlying stressor set is used to gain a first principles approach to prognostic determinations. The assumptions used for the design basis of process equipment have always been as much art as science and for this reason have been misused or relegated into obscurity in all but the nuclear industry. The ability to successfully link degradation and expected equipment life to stressor intensity level is valuable in that it quantifies the degree of machine stress for a given production level. This allows two major improvements in the O and M of process machinery: (1) the actual versus intended machine environment can be understood and brought into much better alignment, and (2) the end goal can define operations and maintenance strategies in terms of life cycle and economic management of plant assets. A holistic infrastructure approach, as applied through a CBM framework, will allow intelligent, automated diagnostic and prognostic programs to provide O and M practitioners with an understanding of the condition of their machinery today and an assurance of its operational state tomorrow

  3. An adaptive functional regression-based prognostic model for applications with missing data

    International Nuclear Information System (INIS)

    Fang, Xiaolei; Zhou, Rensheng; Gebraeel, Nagi

    2015-01-01

    Most prognostic degradation models rely on a relatively accurate and comprehensive database of historical degradation signals. Typically, these signals are used to identify suitable degradation trends that are useful for predicting lifetime. In many real-world applications, these degradation signals are usually incomplete, i.e., contain missing observations. Often the amount of missing data compromises the ability to identify a suitable parametric degradation model. This paper addresses this problem by developing a semi-parametric approach that can be used to predict the remaining lifetime of partially degraded systems. First, key signal features are identified by applying Functional Principal Components Analysis (FPCA) to the available historical data. Next, an adaptive functional regression model is used to model the extracted signal features and the corresponding times-to-failure. The model is then used to predict remaining lifetimes and to update these predictions using real-time signals observed from fielded components. Results show that the proposed approach is relatively robust to significant levels of missing data. The performance of the model is evaluated and shown to provide significantly accurate predictions of residual lifetime using two case studies. - Highlights: • We model degradation signals with missing data with the goal of predicting remaining lifetime. • We examine two types of signal characteristics, fragmented and sparse. • We provide framework that updates remaining life predictions by incorporating real-time signal observations. • For the missing data, we show that the proposed model outperforms other benchmark models. • For the complete data, we show that the proposed model performs at least as good as a benchmark model

  4. New prognostic model for extranodal natural killer/T cell lymphoma, nasal type.

    Science.gov (United States)

    Cai, Qingqing; Luo, Xiaolin; Zhang, Guanrong; Huang, Huiqiang; Huang, Hui; Lin, Tongyu; Jiang, Wenqi; Xia, Zhongjun; Young, Ken H

    2014-09-01

    Extranodal natural killer/T cell lymphoma, nasal type (ENKTL) is an aggressive disease with a poor prognosis, requiring risk stratification in affected patients. We designed a new prognostic model specifically for ENKTL to identify high-risk patients who need more aggressive therapy. We retrospectively reviewed 158 patients who were newly diagnosed with ENKTL. The estimated 5-year overall survival rate was 39.4 %. Independent prognostic factors included total protein (TP) 100 mg/dL, and Korean Prognostic Index (KPI) score ≥2. We constructed a new prognostic model by combining these prognostic factors: group 1 (64 cases (41.0 %)), no adverse factors; group 2 (58 cases (37.2 %)), one adverse factor; and group 3 (34 cases (21.8 %)), two or three adverse factors. The 5-year overall survival (OS) rates of these groups were 66.7, 23.0, and 5.9 %, respectively (p KPI model alone (p KPI model alone.

  5. Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.

    Science.gov (United States)

    Tadeo, Irene; Piqueras, Marta; Montaner, David; Villamón, Eva; Berbegall, Ana P; Cañete, Adela; Navarro, Samuel; Noguera, Rosa

    2014-02-01

    Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

  6. Prognostics of Power MOSFET

    Science.gov (United States)

    Celaya, Jose Ramon; Saxena, Abhinav; Vashchenko, Vladislay; Saha, Sankalita; Goebel, Kai Frank

    2011-01-01

    This paper demonstrates how to apply prognostics to power MOSFETs (metal oxide field effect transistor). The methodology uses thermal cycling to age devices and Gaussian process regression to perform prognostics. The approach is validated with experiments on 100V power MOSFETs. The failure mechanism for the stress conditions is determined to be die-attachment degradation. Change in ON-state resistance is used as a precursor of failure due to its dependence on junction temperature. The experimental data is augmented with a finite element analysis simulation that is based on a two-transistor model. The simulation assists in the interpretation of the degradation phenomena and SOA (safe operation area) change.

  7. An Integrated Cumulative Transformation and Feature Fusion Approach for Bearing Degradation Prognostics

    Directory of Open Access Journals (Sweden)

    Lixiang Duan

    2018-01-01

    Full Text Available Aimed at degradation prognostics of a rolling bearing, this paper proposed a novel cumulative transformation algorithm for data processing and a feature fusion technique for bearing degradation assessment. First, a cumulative transformation is presented to map the original features extracted from a vibration signal to their respective cumulative forms. The technique not only makes the extracted features show a monotonic trend but also reduces the fluctuation; such properties are more propitious to reflect the bearing degradation trend. Then, a new degradation index system is constructed, which fuses multidimensional cumulative features by kernel principal component analysis (KPCA. Finally, an extreme learning machine model based on phase space reconstruction is proposed to predict the degradation trend. The model performance is experimentally validated with a whole-life experiment of a rolling bearing. The results prove that the proposed method reflects the bearing degradation process clearly and achieves a good balance between model accuracy and complexity.

  8. Watershed modeling tools and data for prognostic and diagnostic

    Science.gov (United States)

    Chambel-Leitao, P.; Brito, D.; Neves, R.

    2009-04-01

    When eutrophication is considered an important process to control it can be accomplished reducing nitrogen and phosphorus losses from both point and nonpoint sources and helping to assess the effectiveness of the pollution reduction strategy. HARP-NUT guidelines (Guidelines on Harmonized Quantification and Reporting Procedures for Nutrients) (Borgvang & Selvik, 2000) are presented by OSPAR as the best common quantification and reporting procedures for calculating the reduction of nutrient inputs. In 2000, OSPAR HARP-NUT guidelines on a trial basis. They were intended to serve as a tool for OSPAR Contracting Parties to report, in a harmonized manner, their different commitments, present or future, with regard to nutrients under the OSPAR Convention, in particular the "Strategy to Combat Eutrophication". HARP-NUT Guidelines (Borgvang and Selvik, 2000; Schoumans, 2003) were developed to quantify and report on the individual sources of nitrogen and phosphorus discharges/losses to surface waters (Source Orientated Approach). These results can be compared to nitrogen and phosphorus figures with the total riverine loads measured at downstream monitoring points (Load Orientated Approach), as load reconciliation. Nitrogen and phosphorus retention in river systems represents the connecting link between the "Source Orientated Approach" and the "Load Orientated Approach". Both approaches are necessary for verification purposes and both may be needed for providing the information required for the various commitments. Guidelines 2,3,4,5 are mainly concerned with the sources estimation. They present a set of simple calculations that allow the estimation of the origin of loads. Guideline 6 is a particular case where the application of a model is advised, in order to estimate the sources of nutrients from diffuse sources associated with land use/land cover. The model chosen for this was SWAT (Arnold & Fohrer, 2005) model because it is suggested in the guideline 6 and because it

  9. Development and validation of a prognostic model for recurrent glioblastoma patients treated with bevacizumab and irinotecan

    DEFF Research Database (Denmark)

    Urup, Thomas; Dahlrot, Rikke Hedegaard; Grunnet, Kirsten

    2016-01-01

    Background Predictive markers and prognostic models are required in order to individualize treatment of recurrent glioblastoma (GBM) patients. Here, we sought to identify clinical factors able to predict response and survival in recurrent GBM patients treated with bevacizumab (BEV) and irinotecan....... Material and methods A total of 219 recurrent GBM patients treated with BEV plus irinotecan according to a previously published treatment protocol were included in the initial population. Prognostic models were generated by means of multivariate logistic and Cox regression analysis. Results In multivariate...

  10. Enhanced Prognostic Model for Lithium Ion Batteries Based on Particle Filter State Transition Model Modification

    Directory of Open Access Journals (Sweden)

    Buddhi Arachchige

    2017-11-01

    Full Text Available This paper focuses on predicting the End of Life and End of Discharge of Lithium ion batteries using a battery capacity fade model and a battery discharge model. The proposed framework will be able to estimate the Remaining Useful Life (RUL and the Remaining charge through capacity fade and discharge models. A particle filter is implemented that estimates the battery’s State of Charge (SOC and State of Life (SOL by utilizing the battery’s physical data such as voltage, temperature, and current measurements. The accuracy of the prognostic framework has been improved by enhancing the particle filter state transition model to incorporate different environmental and loading conditions without retuning the model parameters. The effect of capacity fade in the reduction of the EOD (End of Discharge time with cycling has also been included, integrating both EOL (End of Life and EOD prediction models in order to get more accuracy in the estimations.

  11. Aircraft Anomaly Prognostics, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Ridgetop Group will leverage its proven Electromechanical Actuator (EMA) prognostics methodology to develop an advanced model-based actuator prognostic reasoner...

  12. Prognostic model for chronic hypertension in women with a history of hypertensive pregnancy disorders at term

    NARCIS (Netherlands)

    van der Velde-Visser, S.D.; Hermes, W.; Twisk, J; Franx, A.; Pampus, M.G.; Koopmans, C.; Mol, B. W J; de Groot, J.C.M.J.

    2017-01-01

    Introduction The association between hypertensive pregnancy disorders and cardiovascular disease later in life is well described. In this study we aim to develop a prognostic model from patients characteristics known before, early in, during and after pregnancy to identify women at increased risk of

  13. Quantitative Assessment of Arrhythmia Using Non-linear Approach: A Non-invasive Prognostic Tool

    Science.gov (United States)

    Chakraborty, Monisha; Ghosh, Dipak

    2018-04-01

    Accurate prognostic tool to identify severity of Arrhythmia is yet to be investigated, owing to the complexity of the ECG signal. In this paper, we have shown that quantitative assessment of Arrhythmia is possible using non-linear technique based on "Hurst Rescaled Range Analysis". Although the concept of applying "non-linearity" for studying various cardiac dysfunctions is not entirely new, the novel objective of this paper is to identify the severity of the disease, monitoring of different medicine and their dose, and also to assess the efficiency of different medicine. The approach presented in this work is simple which in turn will help doctors in efficient disease management. In this work, Arrhythmia ECG time series are collected from MIT-BIH database. Normal ECG time series are acquired using POLYPARA system. Both time series are analyzed in thelight of non-linear approach following the method "Rescaled Range Analysis". The quantitative parameter, "Fractal Dimension" (D) is obtained from both types of time series. The major finding is that Arrhythmia ECG poses lower values of D as compared to normal. Further, this information can be used to access the severity of Arrhythmia quantitatively, which is a new direction of prognosis as well as adequate software may be developed for the use of medical practice.

  14. Large-scale external validation and comparison of prognostic models: an application to chronic obstructive pulmonary disease

    NARCIS (Netherlands)

    Guerra, Beniamino; Haile, Sarah R.; Lamprecht, Bernd; Ramírez, Ana S.; Martinez-Camblor, Pablo; Kaiser, Bernhard; Alfageme, Inmaculada; Almagro, Pere; Casanova, Ciro; Esteban-González, Cristóbal; Soler-Cataluña, Juan J.; de-Torres, Juan P.; Miravitlles, Marc; Celli, Bartolome R.; Marin, Jose M.; ter Riet, Gerben; Sobradillo, Patricia; Lange, Peter; Garcia-Aymerich, Judith; Antó, Josep M.; Turner, Alice M.; Han, MeiLan K.; Langhammer, Arnulf; Leivseth, Linda; Bakke, Per; Johannessen, Ane; Oga, Toru; Cosio, Borja; Ancochea-Bermúdez, Julio; Echazarreta, Andres; Roche, Nicolas; Burgel, Pierre-Régis; Sin, Don D.; Soriano, Joan B.; Puhan, Milo A.

    2018-01-01

    External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores

  15. Various approaches to the modelling of large scale 3-dimensional circulation in the Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Shaji, C.; Bahulayan, N.; Rao, A.D.; Dube, S.K.

    In this paper, the three different approaches to the modelling of large scale 3-dimensional flow in the ocean such as the diagnostic, semi-diagnostic (adaptation) and the prognostic are discussed in detail. Three-dimensional solutions are obtained...

  16. Updating and prospective validation of a prognostic model for high sickness absence.

    Science.gov (United States)

    Roelen, C A M; Heymans, M W; Twisk, J W R; van Rhenen, W; Pallesen, S; Bjorvatn, B; Moen, B E; Magerøy, N

    2015-01-01

    To further develop and validate a Dutch prognostic model for high sickness absence (SA). Three-wave longitudinal cohort study of 2,059 Norwegian nurses. The Dutch prognostic model was used to predict high SA among Norwegian nurses at wave 2. Subsequently, the model was updated by adding person-related (age, gender, marital status, children at home, and coping strategies), health-related (BMI, physical activity, smoking, and caffeine and alcohol intake), and work-related (job satisfaction, job demands, decision latitude, social support at work, and both work-to-family and family-to-work spillover) variables. The updated model was then prospectively validated for predictions at wave 3. 1,557 (77 %) nurses had complete data at wave 2 and 1,342 (65 %) at wave 3. The risk of high SA was under-estimated by the Dutch model, but discrimination between high-risk and low-risk nurses was fair after re-calibration to the Norwegian data. Gender, marital status, BMI, physical activity, smoking, alcohol intake, job satisfaction, job demands, decision latitude, support at the workplace, and work-to-family spillover were identified as potential predictors of high SA. However, these predictors did not improve the model's discriminative ability, which remained fair at wave 3. The prognostic model correctly identifies 73 % of Norwegian nurses at risk of high SA, although additional predictors are needed before the model can be used to screen working populations for risk of high SA.

  17. Evaluating Ice Nucleating Particle Concentrations From Prognostic Dust Minerals in an Earth System Model

    Science.gov (United States)

    Perlwitz, J. P.; Knopf, D. A.; Fridlind, A. M.; Miller, R. L.; Pérez García-Pando, C.; DeMott, P. J.

    2016-12-01

    The effect of aerosol particles on the radiative properties of clouds, the so-called, indirect effect of aerosols, is recognized as one of the largest sources of uncertainty in climate prediction. The distribution of water vapor, precipitation, and ice cloud formation are influenced by the atmospheric ice formation, thereby modulating cloud albedo and thus climate. It is well known that different particle types possess different ice formation propensities with mineral dust being a superior ice nucleating particle (INP) compared to soot particles. Furthermore, some dust mineral types are more proficient INP than others, depending on temperature and relative humidity.In recent work, we have presented an improved dust aerosol module in the NASA GISS Earth System ModelE2 with prognostic mineral composition of the dust aerosols. Thus, there are regional variations in dust composition. We evaluated the predicted mineral fractions of dust aerosols by comparing them to measurements from a compilation of about 60 published literature references. Additionally, the capability of the model to reproduce the elemental composition of the simulated dusthas been tested at Izana Observatory at Tenerife, Canary Islands, which is located off-shore of Africa and where frequent dust events are observed. We have been able to show that the new approach delivers a robust improvement of the predicted mineral fractions and elemental composition of dust.In the current study, we use three-dimensional dust mineral fields and thermodynamic conditions, which are simulated using GISS ModelE, to calculate offline the INP concentrations derived using different ice nucleation parameterizations that are currently discussed. We evaluate the calculated INP concentrations from the different parameterizations by comparing them to INP concentrations from field measurements.

  18. Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

    Directory of Open Access Journals (Sweden)

    Ghosh Debashis

    2004-12-01

    Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

  19. Multistream sensor fusion-based prognostics model for systems with single failure modes

    International Nuclear Information System (INIS)

    Fang, Xiaolei; Paynabar, Kamran; Gebraeel, Nagi

    2017-01-01

    Advances in sensor technology have facilitated the capability of monitoring the degradation of complex engineering systems through the analysis of multistream degradation signals. However, the varying levels of correlation with physical degradation process for different sensors, high-dimensionality of the degradation signals and cross-correlation among different signal streams pose significant challenges in monitoring and prognostics of such systems. To address the foregoing challenges, we develop a three-step multi-sensor prognostic methodology that utilizes multistream signals to predict residual useful lifetimes of partially degraded systems. We first identify the informative sensors via the penalized (log)-location-scale regression. Then, we fuse the degradation signals of the informative sensors using multivariate functional principal component analysis, which is capable of modeling the cross-correlation of signal streams. Finally, the third step focuses on utilizing the fused signal features for prognostics via adaptive penalized (log)-location-scale regression. We validate our multi-sensor prognostic methodology using simulation study as well as a case study of aircraft turbofan engines available from NASA repository.

  20. 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.

  1. Physics Based Electrolytic Capacitor Degradation Models for Prognostic Studies under Thermal Overstress

    Science.gov (United States)

    Kulkarni, Chetan S.; Celaya, Jose R.; Goebel, Kai; Biswas, Gautam

    2012-01-01

    Electrolytic capacitors are used in several applications ranging from power supplies on safety critical avionics equipment to power drivers for electro-mechanical actuators. This makes them good candidates for prognostics and health management research. Prognostics provides a way to assess remaining useful life of components or systems based on their current state of health and their anticipated future use and operational conditions. Past experiences show that capacitors tend to degrade and fail faster under high electrical and thermal stress conditions that they are often subjected to during operations. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

  2. Physical Modeling for Anomaly Diagnostics and Prognostics, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Ridgetop developed an innovative, model-driven anomaly diagnostic and fault characterization system for electromechanical actuator (EMA) systems to mitigate...

  3. 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.

  4. An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

    Science.gov (United States)

    Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

    2017-05-22

    PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age

  5. Towards A Model-based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

    Directory of Open Access Journals (Sweden)

    Gautam Biswas

    2012-12-01

    Full Text Available This paper presents a model-driven methodology for predict- ing the remaining useful life of electrolytic capacitors. This methodology adopts a Kalman filter approach in conjunction with an empirical state-based degradation model to predict the degradation of capacitor parameters through the life of the capacitor. Electrolytic capacitors are important components of systems that range from power supplies on critical avion- ics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their critical role in the system, they are good candidates for component level prognostics and health management. Prognostics provides a way to assess remain- ing useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. This paper proposes and empirical degradation model and discusses experimental results for an accelerated aging test performed on a set of identical capacitors subjected to electrical stress. The data forms the basis for developing the Kalman-filter based remaining life prediction algorithm.

  6. Improving Clinical Risk Stratification at Diagnosis in Primary Prostate Cancer: A Prognostic Modelling Study.

    Directory of Open Access Journals (Sweden)

    Vincent J Gnanapragasam

    2016-08-01

    Full Text Available Over 80% of the nearly 1 million men diagnosed with prostate cancer annually worldwide present with localised or locally advanced non-metastatic disease. Risk stratification is the cornerstone for clinical decision making and treatment selection for these men. The most widely applied stratification systems use presenting prostate-specific antigen (PSA concentration, biopsy Gleason grade, and clinical stage to classify patients as low, intermediate, or high risk. There is, however, significant heterogeneity in outcomes within these standard groupings. The International Society of Urological Pathology (ISUP has recently adopted a prognosis-based pathological classification that has yet to be included within a risk stratification system. Here we developed and tested a new stratification system based on the number of individual risk factors and incorporating the new ISUP prognostic score.Diagnostic clinicopathological data from 10,139 men with non-metastatic prostate cancer were available for this study from the Public Health England National Cancer Registration Service Eastern Office. This cohort was divided into a training set (n = 6,026; 1,557 total deaths, with 462 from prostate cancer and a testing set (n = 4,113; 1,053 total deaths, with 327 from prostate cancer. The median follow-up was 6.9 y, and the primary outcome measure was prostate-cancer-specific mortality (PCSM. An external validation cohort (n = 1,706 was also used. Patients were first categorised as low, intermediate, or high risk using the current three-stratum stratification system endorsed by the National Institute for Health and Care Excellence (NICE guidelines. The variables used to define the groups (PSA concentration, Gleason grading, and clinical stage were then used to sub-stratify within each risk category by testing the individual and then combined number of risk factors. In addition, we incorporated the new ISUP prognostic score as a discriminator. Using this approach, a

  7. Elements of a unified prognostic model for secondary air contamination by resuspension

    International Nuclear Information System (INIS)

    Besnus, F.; Garger, E.; Gordeev, S.; Hollaender, W.; Kashparov, V.; Martinez-Serrano, J.; Mironov, V.; Nicholson, K.; Tschiersch, J.; Vintersved, I.

    1996-01-01

    Based on results of several joint experimental campaigns and an extensive literature survey, a prognostic model was constructed capable of predicting airborne activity concentrations and size distributions as well as soil surface activity concentrations as a function of time and meteorological conditions. Example scenario calculations show that agricultural practices are of lesser importance to secondary air contamination than dust storms immediately after primary deposition and forest fires

  8. A prognostic pollen emissions model for climate models (PECM1.0

    Directory of Open Access Journals (Sweden)

    M. C. Wozniak

    2017-11-01

    Full Text Available We develop a prognostic model called Pollen Emissions for Climate Models (PECM for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus, evergreen needleleaf trees (Cupressaceae, Pinaceae, grasses (Poaceae; C3, C4, and ragweed (Ambrosia. This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4 over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1 a taxa-specific land cover database, phenology, and emission potential, and (2 a plant functional type (PFT land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions

  9. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

    The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...... monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution...

  10. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

    monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

  11. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud

    2017-01-01

    monitoring, fault detection and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

  12. The strong prognostic value of KELIM, a model-based parameter from CA 125 kinetics in ovarian cancer

    DEFF Research Database (Denmark)

    You, Benoit; Colomban, Olivier; Heywood, Mark

    2013-01-01

    Unexpected results were recently reported about the poor surrogacy of Gynecologic Cancer Intergroup (GCIG) defined CA-125 response in recurrent ovarian cancer (ROC) patients. Mathematical modeling may help describe CA-125 decline dynamically and discriminate prognostic kinetic parameters....

  13. Retrospective analysis of 104 histologically proven adult brainstem gliomas: clinical symptoms, therapeutic approaches and prognostic factors

    International Nuclear Information System (INIS)

    Reithmeier, Thomas; Kuzeawu, Aanyo; Hentschel, Bettina; Loeffler, Markus; Trippel, Michael; Nikkhah, Guido

    2014-01-01

    Adult brainstem gliomas are rare primary brain tumors (<2% of gliomas). The goal of this study was to analyze clinical, prognostic and therapeutic factors in a large series of histologically proven brainstem gliomas. Between 1997 and 2007, 104 patients with a histologically proven brainstem glioma were retrospectively analyzed. Data about clinical course of disease, neuropathological findings and therapeutic approaches were analyzed. The median age at diagnosis was 41 years (range 18-89 years), median KPS before any operative procedure was 80 (range 20-100) and median survival for the whole cohort was 18.8 months. Histopathological examinations revealed 16 grade I, 31 grade II, 42 grade III and 14 grade IV gliomas. Grading was not possible in 1 patient. Therapeutic concepts differed according to the histopathology of the disease. Median overall survival for grade II tumors was 26.4 months, for grade III tumors 12.9 months and for grade IV tumors 9.8 months. On multivariate analysis the relative risk to die increased with a KPS ≤ 70 by factor 6.7, with grade III/IV gliomas by the factor 1.8 and for age ≥ 40 by the factor 1.7. External beam radiation reduced the risk to die by factor 0.4. Adult brainstem gliomas present with a wide variety of neurological symptoms and postoperative radiation remains the cornerstone of therapy with no proven benefit of adding chemotherapy. Low KPS, age ≥ 40 and higher tumor grade have a negative impact on overall survival

  14. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1993-01-01

    Most of today's general circulation models (GCMS) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, there has arisen an urgent need for improvements in the treatment of clouds in GCMS, especially as the clouds relate to radiation. In the present paper, we investigate the effects of introducing pregnostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the long wave emissivity calculations. Results from several sensitivity simulations show that realistic cloud water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds become stronger, due to more realistic tropical convection

  15. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  16. Accounting for treatment use when validating a prognostic model: a simulation study.

    Science.gov (United States)

    Pajouheshnia, Romin; Peelen, Linda M; Moons, Karel G M; Reitsma, Johannes B; Groenwold, Rolf H H

    2017-07-14

    Prognostic models often show poor performance when applied to independent validation data sets. We illustrate how treatment use in a validation set can affect measures of model performance and present the uses and limitations of available analytical methods to account for this using simulated data. We outline how the use of risk-lowering treatments in a validation set can lead to an apparent overestimation of risk by a prognostic model that was developed in a treatment-naïve cohort to make predictions of risk without treatment. Potential methods to correct for the effects of treatment use when testing or validating a prognostic model are discussed from a theoretical perspective.. Subsequently, we assess, in simulated data sets, the impact of excluding treated individuals and the use of inverse probability weighting (IPW) on the estimated model discrimination (c-index) and calibration (observed:expected ratio and calibration plots) in scenarios with different patterns and effects of treatment use. Ignoring the use of effective treatments in a validation data set leads to poorer model discrimination and calibration than would be observed in the untreated target population for the model. Excluding treated individuals provided correct estimates of model performance only when treatment was randomly allocated, although this reduced the precision of the estimates. IPW followed by exclusion of the treated individuals provided correct estimates of model performance in data sets where treatment use was either random or moderately associated with an individual's risk when the assumptions of IPW were met, but yielded incorrect estimates in the presence of non-positivity or an unobserved confounder. When validating a prognostic model developed to make predictions of risk without treatment, treatment use in the validation set can bias estimates of the performance of the model in future targeted individuals, and should not be ignored. When treatment use is random, treated

  17. Accounting for treatment use when validating a prognostic model: a simulation study

    Directory of Open Access Journals (Sweden)

    Romin Pajouheshnia

    2017-07-01

    Full Text Available Abstract Background Prognostic models often show poor performance when applied to independent validation data sets. We illustrate how treatment use in a validation set can affect measures of model performance and present the uses and limitations of available analytical methods to account for this using simulated data. Methods We outline how the use of risk-lowering treatments in a validation set can lead to an apparent overestimation of risk by a prognostic model that was developed in a treatment-naïve cohort to make predictions of risk without treatment. Potential methods to correct for the effects of treatment use when testing or validating a prognostic model are discussed from a theoretical perspective.. Subsequently, we assess, in simulated data sets, the impact of excluding treated individuals and the use of inverse probability weighting (IPW on the estimated model discrimination (c-index and calibration (observed:expected ratio and calibration plots in scenarios with different patterns and effects of treatment use. Results Ignoring the use of effective treatments in a validation data set leads to poorer model discrimination and calibration than would be observed in the untreated target population for the model. Excluding treated individuals provided correct estimates of model performance only when treatment was randomly allocated, although this reduced the precision of the estimates. IPW followed by exclusion of the treated individuals provided correct estimates of model performance in data sets where treatment use was either random or moderately associated with an individual's risk when the assumptions of IPW were met, but yielded incorrect estimates in the presence of non-positivity or an unobserved confounder. Conclusions When validating a prognostic model developed to make predictions of risk without treatment, treatment use in the validation set can bias estimates of the performance of the model in future targeted individuals, and

  18. Moderate Traumatic Brain Injury: Clinical Characteristics and a Prognostic Model of 12-Month Outcome.

    Science.gov (United States)

    Einarsen, Cathrine Elisabeth; van der Naalt, Joukje; Jacobs, Bram; Follestad, Turid; Moen, Kent Gøran; Vik, Anne; Håberg, Asta Kristine; Skandsen, Toril

    2018-03-31

    Patients with moderate traumatic brain injury (TBI) often are studied together with patients with severe TBI, even though the expected outcome of the former is better. Therefore, we aimed to describe patient characteristics and 12-month outcomes, and to develop a prognostic model based on admission data, specifically for patients with moderate TBI. Patients with Glasgow Coma Scale scores of 9-13 and age ≥16 years were prospectively enrolled in 2 level I trauma centers in Europe. Glasgow Outcome Scale Extended (GOSE) score was assessed at 12 months. A prognostic model predicting moderate disability or worse (GOSE score ≤6), as opposed to a good recovery, was fitted by penalized regression. Model performance was evaluated by area under the curve of the receiver operating characteristics curves. Of the 395 enrolled patients, 81% had intracranial lesions on head computed tomography, and 71% were admitted to an intensive care unit. At 12 months, 44% were moderately disabled or worse (GOSE score ≤6), whereas 8% were severely disabled and 6% died (GOSE score ≤4). Older age, lower Glasgow Coma Scale score, no day-of-injury alcohol intoxication, presence of a subdural hematoma, occurrence of hypoxia and/or hypotension, and preinjury disability were significant predictors of GOSE score ≤6 (area under the curve = 0.80). Patients with moderate TBI exhibit characteristics of significant brain injury. Although few patients died or experienced severe disability, 44% did not experience good recovery, indicating that follow-up is needed. The model is a first step in development of prognostic models for moderate TBI that are valid across centers. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

  19. A hybrid prognostic model for multistep ahead prediction of machine condition

    Science.gov (United States)

    Roulias, D.; Loutas, T. H.; Kostopoulos, V.

    2012-05-01

    Prognostics are the future trend in condition based maintenance. In the current framework a data driven prognostic model is developed. The typical procedure of developing such a model comprises a) the selection of features which correlate well with the gradual degradation of the machine and b) the training of a mathematical tool. In this work the data are taken from a laboratory scale single stage gearbox under multi-sensor monitoring. Tests monitoring the condition of the gear pair from healthy state until total brake down following several days of continuous operation were conducted. After basic pre-processing of the derived data, an indicator that correlated well with the gearbox condition was obtained. Consecutively the time series is split in few distinguishable time regions via an intelligent data clustering scheme. Each operating region is modelled with a feed-forward artificial neural network (FFANN) scheme. The performance of the proposed model is tested by applying the system to predict the machine degradation level on unseen data. The results show the plausibility and effectiveness of the model in following the trend of the timeseries even in the case that a sudden change occurs. Moreover the model shows ability to generalise for application in similar mechanical assets.

  20. Prognostic stratification of patients with advanced renal cell carcinoma treated with sunitinib: comparison with the Memorial Sloan-Kettering prognostic factors model

    International Nuclear Information System (INIS)

    Bamias, Aristotelis; Anastasiou, Ioannis; Stravodimos, Kostas; Xanthakis, Ioannis; Skolarikos, Andreas; Christodoulou, Christos; Syrigos, Kostas; Papandreou, Christos; Razi, Evangelia; Dafni, Urania; Fountzilas, George; Karadimou, Alexandra; Dimopoulos, Meletios A; Lampaki, Sofia; Lainakis, George; Malettou, Lia; Timotheadou, Eleni; Papazisis, Kostas; Andreadis, Charalambos; Kontovinis, Loukas

    2010-01-01

    The treatment paradigm in advanced renal cell carcinoma (RCC) has changed in the recent years. Sunitinib has been established as a new standard for first-line therapy. We studied the prognostic significance of baseline characteristics and we compared the risk stratification with the established Memorial Sloan Kettering Cancer Center (MSKCC) model. This is a retrospective analysis of patients treated in six Greek Oncology Units of HECOG. Inclusion criteria were: advanced renal cell carcinoma not amenable to surgery and treatment with Sunitinib. Previous cytokine therapy but no targeted agents were allowed. Overall survival (OS) was the major end point. Significance of prognostic factors was evaluated with multivariate cox regression analysis. A model was developed to stratify patients according to risk. One hundred and nine patients were included. Median follow up has been 15.8 months and median OS 17.1 months (95% CI: 13.7-20.6). Time from diagnosis to the start of Sunitinib (<= 12 months vs. >12 months, p = 0.001), number of metastatic sites (1 vs. >1, p = 0.003) and performance status (PS) (<= 1 vs >1, p = 0.001) were independently associated with OS. Stratification in two risk groups ('low' risk: 0 or 1 risk factors; 'high' risk: 2 or 3 risk factors) resulted in distinctly different OS (median not reached [NR] vs. 10.8 [95% confidence interval (CI): 8.3-13.3], p < 0.001). The application of the MSKCC risk criteria resulted in stratification into 3 groups (low and intermediate and poor risk) with distinctly different prognosis underlying its validity. Nevertheless, MSKCC model did not show an improved prognostic performance over the model developed by this analysis. Studies on risk stratification of patients with advanced RCC treated with targeted therapies are warranted. Our results suggest that a simpler than the MSKCC model can be developed. Such models should be further validated

  1. HEDR modeling approach

    International Nuclear Information System (INIS)

    Shipler, D.B.; Napier, B.A.

    1992-07-01

    This report details the conceptual approaches to be used in calculating radiation doses to individuals throughout the various periods of operations at the Hanford Site. The report considers the major environmental transport pathways--atmospheric, surface water, and ground water--and projects and appropriate modeling technique for each. The modeling sequence chosen for each pathway depends on the available data on doses, the degree of confidence justified by such existing data, and the level of sophistication deemed appropriate for the particular pathway and time period being considered

  2. A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

    Directory of Open Access Journals (Sweden)

    Qihua Tan

    2009-01-01

    Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

  3. A probabilistic physics-of-failure model for prognostic health management of structures subject to pitting and corrosion-fatigue

    International Nuclear Information System (INIS)

    Chookah, M.; Nuhi, M.; Modarres, M.

    2011-01-01

    A combined probabilistic physics-of-failure-based model for pitting and corrosion-fatigue degradation mechanisms is proposed to estimate the reliability of structures and to perform prognosis and health management. A mechanistic superposition model for corrosion-fatigue mechanism was used as a benchmark model to propose the simple model. The proposed model describes the degradation of the structures as a function of physical and critical environmental stresses, such as amplitude and frequency of mechanical loads (for example caused by the internal piping pressure) and the concentration of corrosive chemical agents. The parameters of the proposed model are represented by the probability density functions and estimated through a Bayesian approach based on the data taken from the experiments performed as part of this research. For demonstrating applications, the proposed model provides prognostic information about the reliability of aging of structures and is helpful in developing inspection and replacement strategies. - Highlights: ► We model an inventory system under static–dynamic uncertainty strategy. ► The demand is stochastic and non-stationary. ► The optimal ordering policy is proven to be a base stock policy. ► A solution algorithm for finding an optimal solution is provided. ► Two heuristics developed produce high quality solutions and scale-up efficiently.

  4. External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study.

    Science.gov (United States)

    Lamain-de Ruiter, Marije; Kwee, Anneke; Naaktgeboren, Christiana A; de Groot, Inge; Evers, Inge M; Groenendaal, Floris; Hering, Yolanda R; Huisjes, Anjoke J M; Kirpestein, Cornel; Monincx, Wilma M; Siljee, Jacqueline E; Van 't Zelfde, Annewil; van Oirschot, Charlotte M; Vankan-Buitelaar, Simone A; Vonk, Mariska A A W; Wiegers, Therese A; Zwart, Joost J; Franx, Arie; Moons, Karel G M; Koster, Maria P H

    2016-08-30

     To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy.  External validation of all published prognostic models in large scale, prospective, multicentre cohort study.  31 independent midwifery practices and six hospitals in the Netherlands.  Women recruited in their first trimester (diabetes mellitus of any type were excluded.  Discrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots.  3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated. The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit.  In this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  5. Model-based prognostics for batteries which estimates useful life and uses a probability density function

    Science.gov (United States)

    Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor)

    2012-01-01

    This invention develops a mathematical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to the internal processes of the battery and validated using experimental data. Effects of temperature and load current have also been incorporated into the model. Subsequently, the model has been used in a Particle Filtering framework to make predictions of remaining useful life for individual discharge cycles as well as for cycle life. The prediction performance was found to be satisfactory as measured by performance metrics customized for prognostics for a sample case. The work presented here provides initial steps towards a comprehensive health management solution for energy storage devices.

  6. Prognostic and health management for engineering systems: a review of the data-driven approach and algorithms

    Directory of Open Access Journals (Sweden)

    Thamo Sutharssan

    2015-07-01

    Full Text Available Prognostics and health management (PHM has become an important component of many engineering systems and products, where algorithms are used to detect anomalies, diagnose faults and predict remaining useful lifetime (RUL. PHM can provide many advantages to users and maintainers. Although primary goals are to ensure the safety, provide state of the health and estimate RUL of the components and systems, there are also financial benefits such as operational and maintenance cost reductions and extended lifetime. This study aims at reviewing the current status of algorithms and methods used to underpin different existing PHM approaches. The focus is on providing a structured and comprehensive classification of the existing state-of-the-art PHM approaches, data-driven approaches and algorithms.

  7. Prognostic methods in medicine

    NARCIS (Netherlands)

    Lucas, P. J.; Abu-Hanna, A.

    1999-01-01

    Prognosis--the prediction of the course and outcome of disease processes--plays an important role in patient management tasks like diagnosis and treatment planning. As a result, prognostic models form an integral part of a number of systems supporting these tasks. Furthermore, prognostic models

  8. THE MODEL OF UNCLEAR EXPERT SYSTEM OF PROGNOSTICATION THE CONTENT OF EDUCATION

    Directory of Open Access Journals (Sweden)

    Ivan M. Tsidylo

    2012-12-01

    Full Text Available The article deals with the problem of development of the expert system of prognostication of the educational content by means of fuzzy logic. It was the model of making decision by the group of experts in accordance to meaningfulness of the theme in the educational programme on the base of the hierarchical system that combines in itself the use of both unclear and stochastic data. The structure of the unclear system, function and mechanisms of construction of separate blocks of the model are described. The surface of review of the unclear system represents dependence of estimation of the theme meaningfulness on the level of competence of group of experts and size to the point at the permanent value of level’s variation. The testing of the controller on a test selection proves the functional fitness of the developed model.

  9. Few promising multivariable prognostic models exist for recovery of people with non-specific neck pain in musculoskeletal primary care: A systematic review

    NARCIS (Netherlands)

    R.W. Wingbermühle (Roel); E. van Trijffel (Emiel); Nelissen, P.M. (Paul M.); B.W. Koes (Bart); A.P. Verhagen (Arianne)

    2017-01-01

    markdownabstractQuestion: Which multivariable prognostic model(s) for recovery in people with neck pain can be used in primary care? Design: Systematic review of studies evaluating multivariable prognostic models. Participants: People with non-specific neck pain presenting at primary care.

  10. A prognostic model for soft tissue sarcoma of the extremities and trunk wall based on size, vascular invasion, necrosis, and growth pattern

    DEFF Research Database (Denmark)

    Carneiro, Ana; Bendahl, Par-Ola; Engellau, Jacob

    2011-01-01

    type, necrosis, and grade. METHODS:: Whole-tumor sections from 239 soft tissue sarcomas of the extremities were reviewed for the following prognostic factors: size, vascular invasion, necrosis, and growth pattern. A new prognostic model, referred to as SING (Size, Invasion, Necrosis, Growth......), was established and compared with other clinically applied systems. RESULTS:: Size, vascular invasion, necrosis, and peripheral tumor growth pattern provided independent prognostic information with hazard ratios of 2.2-2.6 for development of metastases in multivariate analysis. When these factors were combined...... into the prognostic model SING, high risk of metastasis was predicted with a sensitivity of 74% and a specificity of 85%. Moreover, the prognostic performance of SING compared favorably with other widely used systems. CONCLUSIONS:: SING represents a promising prognostic model, and vascular invasion and tumor growth...

  11. Prognostic model for chronic hypertension in women with a history of hypertensive pregnancy disorders at term.

    Science.gov (United States)

    Visser, V S; Hermes, W; Twisk, J; Franx, A; van Pampus, M G; Koopmans, C; Mol, B W J; de Groot, C J M

    2017-10-01

    The association between hypertensive pregnancy disorders and cardiovascular disease later in life is well described. In this study we aim to develop a prognostic model from patients characteristics known before, early in, during and after pregnancy to identify women at increased risk of cardiovascular disease e.g. chronic hypertension years after pregnancy complicated by hypertension at term. We included women with a history of singleton pregnancy complicated by hypertension at term. Women using antihypertensive medication before pregnancy were excluded. We measured hypertension in these women more than 2years postpartum. Different patients characteristics before, early in, during and after pregnancy were considered to develop a prognostic model of chronic hypertension at 2-years. These included amongst others maternal age, blood pressure at pregnancy intake and blood pressure six weeks post-partum. Univariable analyses followed by a multivariable logistic regression analysis was performed to determine which combination of predictors best predicted chronic hypertension. Model performance was assessed by calibration (graphical plot) and discrimination (area under the receiver operating characteristic (AUC)). Of the 305 women in who blood pressure 2.5years after pregnancy was assessed, 105 women (34%) had chronic hypertension. The following patient characteristics were significant associated with chronic hypertension: higher maternal age, lower education, negative family history on hypertensive pregnancy disorders, higher BMI at booking, higher diastolic blood pressure at pregnancy intake, higher systolic blood pressure during pregnancy and higher diastolic blood pressure at six weeks post-partum. These characteristics were included in the prognostic model for chronic hypertension. Model performance was good as indicated by good calibration and good discrimination (AUC; 0.83 (95% CI 0.75 - 0.92). Chronic hypertension can be expected from patient characteristics

  12. Mayo Alliance Prognostic Model for Myelodysplastic Syndromes: Integration of Genetic and Clinical Information.

    Science.gov (United States)

    Tefferi, Ayalew; Gangat, Naseema; Mudireddy, Mythri; Lasho, Terra L; Finke, Christy; Begna, Kebede H; Elliott, Michelle A; Al-Kali, Aref; Litzow, Mark R; Hook, C Christopher; Wolanskyj, Alexandra P; Hogan, William J; Patnaik, Mrinal M; Pardanani, Animesh; Zblewski, Darci L; He, Rong; Viswanatha, David; Hanson, Curtis A; Ketterling, Rhett P; Tang, Jih-Luh; Chou, Wen-Chien; Lin, Chien-Chin; Tsai, Cheng-Hong; Tien, Hwei-Fang; Hou, Hsin-An

    2018-06-01

    To develop a new risk model for primary myelodysplastic syndromes (MDS) that integrates information on mutations, karyotype, and clinical variables. Patients with World Health Organization-defined primary MDS seen at Mayo Clinic (MC) from December 28, 1994, through December 19, 2017, constituted the core study group. The National Taiwan University Hospital (NTUH) provided the validation cohort. Model performance, compared with the revised International Prognostic Scoring System, was assessed by Akaike information criterion and area under the curve estimates. The study group consisted of 685 molecularly annotated patients from MC (357) and NTUH (328). Multivariate analysis of the MC cohort identified monosomal karyotype (hazard ratio [HR], 5.2; 95% CI, 3.1-8.6), "non-MK abnormalities other than single/double del(5q)" (HR, 1.8; 95% CI, 1.3-2.6), RUNX1 (HR, 2.0; 95% CI, 1.2-3.1) and ASXL1 (HR, 1.7; 95% CI, 1.2-2.3) mutations, absence of SF3B1 mutations (HR, 1.6; 95% CI, 1.1-2.4), age greater than 70 years (HR, 2.2; 95% CI, 1.6-3.1), hemoglobin level less than 8 g/dL in women or less than 9 g/dL in men (HR, 2.3; 95% CI, 1.7-3.1), platelet count less than 75 × 10 9 /L (HR, 1.5; 95% CI, 1.1-2.1), and 10% or more bone marrow blasts (HR, 1.7; 95% CI, 1.1-2.8) as predictors of inferior overall survival. Based on HR-weighted risk scores, a 4-tiered Mayo alliance prognostic model for MDS was devised: low (89 patients), intermediate-1 (104), intermediate-2 (95), and high (69); respective median survivals (5-year overall survival rates) were 85 (73%), 42 (34%), 22 (7%), and 9 months (0%). The Mayo alliance model was subsequently validated by using the external NTUH cohort and, compared with the revised International Prognostic Scoring System, displayed favorable Akaike information criterion (1865 vs 1943) and area under the curve (0.87 vs 0.76) values. We propose a simple and contemporary risk model for MDS that is based on a limited set of genetic and clinical variables

  13. A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures.

    Directory of Open Access Journals (Sweden)

    Maud H W Starmans

    Full Text Available BACKGROUND: Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures. PRINCIPAL FINDINGS: A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number. CONCLUSIONS: We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited.

  14. Prognostics-based qualification of high-power white LEDs using Lévy process approach

    Science.gov (United States)

    Yung, Kam-Chuen; Sun, Bo; Jiang, Xiaopeng

    2017-01-01

    Due to their versatility in a variety of applications and the growing market demand, high-power white light-emitting diodes (LEDs) have attracted considerable attention. Reliability qualification testing is an essential part of the product development process to ensure the reliability of a new LED product before its release. However, the widely used IES-TM-21 method does not provide comprehensive reliability information. For more accurate and effective qualification, this paper presents a novel method based on prognostics techniques. Prognostics is an engineering technology predicting the future reliability or determining the remaining useful lifetime (RUL) of a product by assessing the extent of deviation or degradation from its expected normal operating conditions. A Lévy subordinator of a mixed Gamma and compound Poisson process is used to describe the actual degradation process of LEDs characterized by random sporadic small jumps of degradation degree, and the reliability function is derived for qualification with different distribution forms of jump sizes. The IES LM-80 test results reported by different LED vendors are used to develop and validate the qualification methodology. This study will be helpful for LED manufacturers to reduce the total test time and cost required to qualify the reliability of an LED product.

  15. Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables

    NARCIS (Netherlands)

    Roelen, Corne A. M.; Stapelfeldt, Christina M.; Heymans, Martijn W.; van Rhenen, Willem; Labriola, Merete; Nielsen, Claus V.; Bultmann, Ute; Jensen, Chris

    Purpose To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models' risk discrimination was also investigated. Methods 2,562 municipal eldercare

  16. A prognostic model for temporal courses that combines temporal abstraction and case-based reasoning.

    Science.gov (United States)

    Schmidt, Rainer; Gierl, Lothar

    2005-03-01

    Since clinical management of patients and clinical research are essentially time-oriented endeavours, reasoning about time has become a hot topic in medical informatics. Here we present a method for prognosis of temporal courses, which combines temporal abstractions with case-based reasoning. It is useful for application domains where neither well-known standards, nor known periodicity, nor a complete domain theory exist. We have used our method in two prognostic applications. The first one deals with prognosis of the kidney function for intensive care patients. The idea is to elicit impairments on time, especially to warn against threatening kidney failures. Our second application deals with a completely different domain, namely geographical medicine. Its intention is to compute early warnings against approaching infectious diseases, which are characterised by irregular cyclic occurrences. So far, we have applied our program on influenza and bronchitis. In this paper, we focus on influenza forecast and show first experimental results.

  17. Optimization of a prognostic biosphere model for terrestrial biomass and atmospheric CO2 variability

    International Nuclear Information System (INIS)

    Saito, M.; Ito, A.; Maksyutov, S.

    2014-01-01

    This study investigates the capacity of a prognostic biosphere model to simulate global variability in atmospheric CO 2 concentrations and vegetation carbon dynamics under current environmental conditions. Global data sets of atmospheric CO 2 concentrations, above-ground biomass (AGB), and net primary productivity (NPP) in terrestrial vegetation were assimilated into the biosphere model using an inverse modeling method combined with an atmospheric transport model. In this process, the optimal physiological parameters of the biosphere model were estimated by minimizing the misfit between observed and modeled values, and parameters were generated to characterize various biome types. Results obtained using the model with the optimized parameters correspond to the observed seasonal variations in CO 2 concentration and their annual amplitudes in both the Northern and Southern Hemispheres. In simulating the mean annual AGB and NPP, the model shows improvements in estimating the mean magnitudes and probability distributions for each biome, as compared with results obtained using prior simulation parameters. However, the model is less efficient in its simulation of AGB for forest type biomes. This misfit suggests that more accurate values of input parameters, specifically, grid mean AGB values and seasonal variabilities in physiological parameters, are required to improve the performance of the simulation model. (authors)

  18. Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

    Science.gov (United States)

    Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

    2013-01-01

    In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

  19. External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study.

    NARCIS (Netherlands)

    Lamain-de Ruiter, M.; Kwee, A.; Naaktgeboren, C.A.; Groot, I. de; Evers, I.M.; Groenendaal, F.; Hering, Y.R.; Huisjes, A.J.M.; Kirpestein, C.; Monincx, W.M.; Siljee, J.E.; Zelfde, A. van't; Oirschot, C.M. van; Vankan-Buitelaar, S.A.; Vonk, M.A.A.W.; Wiegers, T.A.; Zwart, J.J.; Franx, A.; Moons, K.G.M.; Koster, M.P.H.

    2016-01-01

    Objective: To perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy. Design: External validation of all published prognostic models in

  20. Transitions in Prognostic Awareness Among Terminally Ill Cancer Patients in Their Last 6 Months of Life Examined by Multi-State Markov Modeling.

    Science.gov (United States)

    Hsiu Chen, Chen; Wen, Fur-Hsing; Hou, Ming-Mo; Hsieh, Chia-Hsun; Chou, Wen-Chi; Chen, Jen-Shi; Chang, Wen-Cheng; Tang, Siew Tzuh

    2017-09-01

    Developing accurate prognostic awareness, a cornerstone of preference-based end-of-life (EOL) care decision-making, is a dynamic process involving more prognostic-awareness states than knowing or not knowing. Understanding the transition probabilities and time spent in each prognostic-awareness state can help clinicians identify trigger points for facilitating transitions toward accurate prognostic awareness. We examined transition probabilities in distinct prognostic-awareness states between consecutive time points in 247 cancer patients' last 6 months and estimated the time spent in each state. Prognostic awareness was categorized into four states: (a) unknown and not wanting to know, state 1; (b) unknown but wanting to know, state 2; (c) inaccurate awareness, state 3; and (d) accurate awareness, state 4. Transitional probabilities were examined by multistate Markov modeling. Initially, 59.5% of patients had accurate prognostic awareness, whereas the probabilities of being in states 1-3 were 8.1%, 17.4%, and 15.0%, respectively. Patients' prognostic awareness generally remained unchanged (probabilities of remaining in the same state: 45.5%-92.9%). If prognostic awareness changed, it tended to shift toward higher prognostic-awareness states (probabilities of shifting to state 4 were 23.2%-36.6% for patients initially in states 1-3, followed by probabilities of shifting to state 3 for those in states 1 and 2 [9.8%-10.1%]). Patients were estimated to spend 1.29, 0.42, 0.68, and 3.61 months in states 1-4, respectively, in their last 6 months. Terminally ill cancer patients' prognostic awareness generally remained unchanged, with a tendency to become more aware of their prognosis. Health care professionals should facilitate patients' transitions toward accurate prognostic awareness in a timely manner to promote preference-based EOL decisions. Terminally ill Taiwanese cancer patients' prognostic awareness generally remained stable, with a tendency toward developing

  1. Predicting stabilizing treatment outcomes for complex posttraumatic stress disorder and dissociative identity disorder: an expertise-based prognostic model

    NARCIS (Netherlands)

    Baars, E.W.; van der Hart, O.; Nijenhuis, E.R.S.; Chu, J.A.; Glas, G.; Draaijer, N.

    2011-01-01

    The purpose of this study was to develop an expertise-based prognostic model for the treatment of complex posttraumatic stress disorder (PTSD) and dissociative identity disorder (DID).We developed a survey in 2 rounds: In the first round we surveyed 42 experienced therapists (22 DID and 20 complex

  2. Prognostic model for patients treated for colorectal adenomas with regard to development of recurrent adenomas and carcinoma

    DEFF Research Database (Denmark)

    Jensen, P; Krogsgaard, M R; Christiansen, J

    1996-01-01

    -80. INTERVENTIONS: All patients were followed up by rectoscopy and double contrast barium enema. The survival data were analysed by Cox's proportional hazards model. MAIN OUTCOME MEASURES: Variables of significant prognostic importance for recurrence of adenomas and the development of cancer were identified...

  3. Cross-National Validation of Prognostic Models Predicting Sickness Absence and the Added Value of Work Environment Variables

    NARCIS (Netherlands)

    Roelen, C.A.M.; Stapelfeldt, C.M.; Heijmans, M.W.; van Rhenen, W.; Labriola, M.; Nielsen, C.V.; Bultmann, U.; Jensen, C.

    2015-01-01

    Purpose To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models’ risk discrimination was also investigated. Methods 2,562 municipal eldercare

  4. Treatment-Related Predictive and Prognostic Factors in Trimodality Approach in Stage IIIA/N2 Non-Small Cell Lung Cancer.

    Science.gov (United States)

    Jeremić, Branislav; Casas, Francesc; Dubinsky, Pavol; Gomez-Caamano, Antonio; Čihorić, Nikola; Videtic, Gregory; Igrutinovic, Ivan

    2018-01-01

    While there are no established pretreatment predictive and prognostic factors in patients with stage IIIA/pN2 non-small cell lung cancer (NSCLC) indicating a benefit to surgery as a part of trimodality approach, little is known about treatment-related predictive and prognostic factors in this setting. A literature search was conducted to identify possible treatment-related predictive and prognostic factors for patients for whom trimodality approach was reported on. Overall survival was the primary endpoint of this study. Of 30 identified studies, there were two phase II studies, 5 "prospective" studies, and 23 retrospective studies. No study was found which specifically looked at treatment-related predictive factors of improved outcomes in trimodality treatment. Of potential treatment-related prognostic factors, the least frequently analyzed factors among 30 available studies were overall pathologic stage after preoperative treatment and UICC downstaging. Evaluation of treatment response before surgery and by pathologic tumor stage after induction therapy were analyzed in slightly more than 40% of studies and found not to influence survival. More frequently studied factors-resection status, degree of tumor regression, and pathologic nodal stage after induction therapy as well as the most frequently studied factor, the treatment (in almost 75% studies)-showed no discernible impact on survival, due to conflicting results. Currently, it is impossible to identify any treatment-related predictive or prognostic factors for selecting surgery in the treatment of patients with stage IIIA/pN2 NSCLC.

  5. Implementation of Remaining Useful Lifetime Transformer Models in the Fleet-Wide Prognostic and Health Management Suite

    International Nuclear Information System (INIS)

    Agarwal, Vivek; Lybeck, Nancy J.; Pham, Binh; Rusaw, Richard; Bickford, Randall

    2015-01-01

    Research and development efforts are required to address aging and reliability concerns of the existing fleet of nuclear power plants. As most plants continue to operate beyond the license life (i.e., towards 60 or 80 years), plant components are more likely to incur age-related degradation mechanisms. To assess and manage the health of aging plant assets across the nuclear industry, the Electric Power Research Institute has developed a web-based Fleet-Wide Prognostic and Health Management (FW-PHM) Suite for diagnosis and prognosis. FW-PHM is a set of web-based diagnostic and prognostic tools and databases, comprised of the Diagnostic Advisor, the Asset Fault Signature Database, the Remaining Useful Life Advisor, and the Remaining Useful Life Database, that serves as an integrated health monitoring architecture. The main focus of this paper is the implementation of prognostic models for generator step-up transformers in the FW-PHM Suite. One prognostic model discussed is based on the functional relationship between degree of polymerization, (the most commonly used metrics to assess the health of the winding insulation in a transformer) and furfural concentration in the insulating oil. The other model is based on thermal-induced degradation of the transformer insulation. By utilizing transformer loading information, established thermal models are used to estimate the hot spot temperature inside the transformer winding. Both models are implemented in the Remaining Useful Life Database of the FW-PHM Suite. The Remaining Useful Life Advisor utilizes the implemented prognostic models to estimate the remaining useful life of the paper winding insulation in the transformer based on actual oil testing and operational data.

  6. Prognostic model based on nailfold capillaroscopy for identifying Raynaud's phenomenon patients at high risk for the development of a scleroderma spectrum disorder: PRINCE (prognostic index for nailfold capillaroscopic examination).

    Science.gov (United States)

    Ingegnoli, Francesca; Boracchi, Patrizia; Gualtierotti, Roberta; Lubatti, Chiara; Meani, Laura; Zahalkova, Lenka; Zeni, Silvana; Fantini, Flavio

    2008-07-01

    To construct a prognostic index based on nailfold capillaroscopic examinations that is capable of predicting the 5-year transition from isolated Raynaud's phenomenon (RP) to RP secondary to scleroderma spectrum disorders (SSDs). The study involved 104 consecutive adult patients with a clinical history of isolated RP, and the index was externally validated in another cohort of 100 patients with the same characteristics. Both groups were followed up for 1-8 years. Six variables were examined because of their potential prognostic relevance (branching, enlarged and giant loops, capillary disorganization, microhemorrhages, and the number of capillaries). The only factors that played a significant prognostic role were the presence of giant loops (hazard ratio [HR] 2.64, P = 0.008) and microhemorrhages (HR 2.33, P = 0.01), and the number of capillaries (analyzed as a continuous variable). The adjusted prognostic role of these factors was evaluated by means of multivariate regression analysis, and the results were used to construct an algorithm-based prognostic index. The model was internally and externally validated. Our prognostic capillaroscopic index identifies RP patients in whom the risk of developing SSDs is high. This model is a weighted combination of different capillaroscopy parameters that allows physicians to stratify RP patients easily, using a relatively simple diagram to deduce the prognosis. Our results suggest that this index could be used in clinical practice, and its further inclusion in prospective studies will undoubtedly help in exploring its potential in predicting treatment response.

  7. Prognostic Modeling in Pathologic N1 Breast Cancer Without Elective Nodal Irradiation After Current Standard Systemic Management.

    Science.gov (United States)

    Yu, Jeong Il; Park, Won; Choi, Doo Ho; Huh, Seung Jae; Nam, Seok Jin; Kim, Seok Won; Lee, Jeong Eon; Kil, Won Ho; Im, Young-Hyuck; Ahn, Jin Seok; Park, Yeon Hee; Cho, Eun Yoon

    2015-08-01

    This study was conducted to establish a prognostic model in patients with pathologic N1 (pN1) breast cancer who have not undergone elective nodal irradiation (ENI) under the current standard management and to suggest possible indications for ENI. We performed a retrospective study with patients with pN1 breast cancer who received the standard local and preferred adjuvant chemotherapy treatment without neoadjuvant chemotherapy and ENI from January 2005 to June 2011. Most of the indicated patients received endocrine and trastuzumab therapy. In 735 enrolled patients, the median follow-up period was 58.4 months (range, 7.2-111.3 months). Overall, 55 recurrences (7.4%) developed, and locoregional recurrence was present in 27 patients (3.8%). Recurrence-free survival was significantly related to lymphovascular invasion (P = .04, hazard ratio [HR], 1.83; 95% confidence interval [CI], 1.03-2.88), histologic grade (P = .03, HR, 2.57; 95% CI, 1.05-6.26), and nonluminal A subtype (P = .02, HR, 3.04; 95% CI, 1.23-7.49) in multivariate analysis. The prognostic model was established by these 3 prognostic factors. Recurrence-free survival was less than 90% at 5 years in cases with 2 or 3 factors. The prognostic model has stratified risk groups in pN1 breast cancer without ENI. Patients with 2 or more factors should be considered for ENI. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Development Of A Multivariate Prognostic Model For Pain And Activity Limitation In People With Low Back Disorders Receiving Physiotherapy.

    Science.gov (United States)

    Ford, Jon J; Richards BPhysio, Matt C; Surkitt BPhysio, Luke D; Chan BPhysio, Alexander Yp; Slater, Sarah L; Taylor, Nicholas F; Hahne, Andrew J

    2018-05-28

    To identify predictors for back pain, leg pain and activity limitation in patients with early persistent low back disorders. Prospective inception cohort study; Setting: primary care private physiotherapy clinics in Melbourne, Australia. 300 adults aged 18-65 years with low back and/or referred leg pain of ≥6-weeks and ≤6-months duration. Not applicable. Numerical rating scales for back pain and leg pain as well as the Oswestry Disability Scale. Prognostic factors included sociodemographics, treatment related factors, subjective/physical examination, subgrouping factors and standardized questionnaires. Univariate analysis followed by generalized estimating equations were used to develop a multivariate prognostic model for back pain, leg pain and activity limitation. Fifty-eight prognostic factors progressed to the multivariate stage where 15 showed significant (pduration, high multifidus tone, clinically determined inflammation, higher back and leg pain severity, lower lifting capacity, lower work capacity and higher pain drawing percentage coverage). The preliminary model identifying predictors of low back disorders explained up to 37% of the variance in outcome. This study evaluated a comprehensive range of prognostic factors reflective of both the biomedical and psychosocial domains of low back disorders. The preliminary multivariate model requires further validation before being considered for clinical use. Copyright © 2018. Published by Elsevier Inc.

  9. Predicting stabilizing treatment outcomes for complex posttraumatic stress disorder and dissociative identity disorder: an expertise-based prognostic model.

    Science.gov (United States)

    Baars, Erik W; van der Hart, Onno; Nijenhuis, Ellert R S; Chu, James A; Glas, Gerrit; Draijer, Nel

    2011-01-01

    The purpose of this study was to develop an expertise-based prognostic model for the treatment of complex posttraumatic stress disorder (PTSD) and dissociative identity disorder (DID). We developed a survey in 2 rounds: In the first round we surveyed 42 experienced therapists (22 DID and 20 complex PTSD therapists), and in the second round we surveyed a subset of 22 of the 42 therapists (13 DID and 9 complex PTSD therapists). First, we drew on therapists' knowledge of prognostic factors for stabilization-oriented treatment of complex PTSD and DID. Second, therapists prioritized a list of prognostic factors by estimating the size of each variable's prognostic effect; we clustered these factors according to content and named the clusters. Next, concept mapping methodology and statistical analyses (including principal components analyses) were used to transform individual judgments into weighted group judgments for clusters of items. A prognostic model, based on consensually determined estimates of effect sizes, of 8 clusters containing 51 factors for both complex PTSD and DID was formed. It includes the clusters lack of motivation, lack of healthy relationships, lack of healthy therapeutic relationships, lack of other internal and external resources, serious Axis I comorbidity, serious Axis II comorbidity, poor attachment, and self-destruction. In addition, a set of 5 DID-specific items was constructed. The model is supportive of the current phase-oriented treatment model, emphasizing the strengthening of the therapeutic relationship and the patient's resources in the initial stabilization phase. Further research is needed to test the model's statistical and clinical validity.

  10. Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury.

    Science.gov (United States)

    Ritter, Anne C; Wagner, Amy K; Szaflarski, Jerzy P; Brooks, Maria M; Zafonte, Ross D; Pugh, Mary Jo V; Fabio, Anthony; Hammond, Flora M; Dreer, Laura E; Bushnik, Tamara; Walker, William C; Brown, Allen W; Johnson-Greene, Doug; Shea, Timothy; Krellman, Jason W; Rosenthal, Joseph A

    2016-09-01

    Posttraumatic seizures (PTS) are well-recognized acute and chronic complications of traumatic brain injury (TBI). Risk factors have been identified, but considerable variability in who develops PTS remains. Existing PTS prognostic models are not widely adopted for clinical use and do not reflect current trends in injury, diagnosis, or care. We aimed to develop and internally validate preliminary prognostic regression models to predict PTS during acute care hospitalization, and at year 1 and year 2 postinjury. Prognostic models predicting PTS during acute care hospitalization and year 1 and year 2 post-injury were developed using a recent (2011-2014) cohort from the TBI Model Systems National Database. Potential PTS predictors were selected based on previous literature and biologic plausibility. Bivariable logistic regression identified variables with a p-value models. Multivariable logistic regression modeling with backward-stepwise elimination was used to determine reduced prognostic models and to internally validate using 1,000 bootstrap samples. Fit statistics were calculated, correcting for overfitting (optimism). The prognostic models identified sex, craniotomy, contusion load, and pre-injury limitation in learning/remembering/concentrating as significant PTS predictors during acute hospitalization. Significant predictors of PTS at year 1 were subdural hematoma (SDH), contusion load, craniotomy, craniectomy, seizure during acute hospitalization, duration of posttraumatic amnesia, preinjury mental health treatment/psychiatric hospitalization, and preinjury incarceration. Year 2 significant predictors were similar to those of year 1: SDH, intraparenchymal fragment, craniotomy, craniectomy, seizure during acute hospitalization, and preinjury incarceration. Corrected concordance (C) statistics were 0.599, 0.747, and 0.716 for acute hospitalization, year 1, and year 2 models, respectively. The prognostic model for PTS during acute hospitalization did not

  11. Cross-national validation of prognostic models predicting sickness absence and the added value of work environment variables.

    Science.gov (United States)

    Roelen, Corné A M; Stapelfeldt, Christina M; Heymans, Martijn W; van Rhenen, Willem; Labriola, Merete; Nielsen, Claus V; Bültmann, Ute; Jensen, Chris

    2015-06-01

    To validate Dutch prognostic models including age, self-rated health and prior sickness absence (SA) for ability to predict high SA in Danish eldercare. The added value of work environment variables to the models' risk discrimination was also investigated. 2,562 municipal eldercare workers (95% women) participated in the Working in Eldercare Survey. Predictor variables were measured by questionnaire at baseline in 2005. Prognostic models were validated for predictions of high (≥30) SA days and high (≥3) SA episodes retrieved from employer records during 1-year follow-up. The accuracy of predictions was assessed by calibration graphs and the ability of the models to discriminate between high- and low-risk workers was investigated by ROC-analysis. The added value of work environment variables was measured with Integrated Discrimination Improvement (IDI). 1,930 workers had complete data for analysis. The models underestimated the risk of high SA in eldercare workers and the SA episodes model had to be re-calibrated to the Danish data. Discrimination was practically useful for the re-calibrated SA episodes model, but not the SA days model. Physical workload improved the SA days model (IDI = 0.40; 95% CI 0.19-0.60) and psychosocial work factors, particularly the quality of leadership (IDI = 0.70; 95% CI 053-0.86) improved the SA episodes model. The prognostic model predicting high SA days showed poor performance even after physical workload was added. The prognostic model predicting high SA episodes could be used to identify high-risk workers, especially when psychosocial work factors are added as predictor variables.

  12. Model for prognostication of population irradiation dose at the soil way of long-living radionuclides including in food chains

    International Nuclear Information System (INIS)

    Prister, B.S.; Vinogradskaya, V.D.

    2009-01-01

    On the basis of modern pictures of cesium and strontium ion absorption mechanisms a soil taking complex was build the kinetic model of radionuclide migration from soil to plants. Model parameter association with the agricultural chemistry properties of soil, represented by complex estimation of soil properties S e f. The example of model application for prognostication of population internal irradiation dose due to consumption of milk at the soil way of long-living radionuclides including in food chains

  13. Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

    International Nuclear Information System (INIS)

    Taghavifar, Hamid; Mardani, Aref

    2014-01-01

    This paper examines the prediction of energy efficiency indices of driven wheels (i.e. traction coefficient and tractive power efficiency) as affected by wheel load, slippage and forward velocity at three different levels with three replicates to form a total of 162 data points. The pertinent experiments were carried out in the soil bin testing facility. A feed-forward ANN (artificial neural network) with standard BP (back propagation) algorithm was practiced to construct a supervised representation to predict the energy efficiency indices of driven wheels. It was deduced, in view of the statistical performance criteria (i.e. MSE (mean squared error) and R 2 ), that a supervised ANN with 3-8-10-2 topology and Levenberg–Marquardt training algorithm represented the optimal model. Modeling implementations indicated that ANN is a powerful technique to prognosticate the stochastic energy efficiency indices as affected by soil-wheel interactions with MSE of 0.001194 and R 2 of 0.987 and 0.9772 for traction coefficient and tractive power efficiency. It was found that traction coefficient and tractive power efficiency increase with increased slippage. A similar trend is valid for the influence of wheel load on the objective parameters. Wherein increase of velocity led to an increment of tractive power efficiency, velocity had no significant effect on traction coefficient. - Highlights: • Energy efficiency indexes were assessed as affected by tire parameters. • ANN was applied for prognostication of the objective parameters. • A 3-8-10-2 ANN with MSE of 0.001194 and R 2 of 0.987 and 0.9772 was designated as optimal model. • Optimal values of learning rate and momentum were found 0.9 and 0.5, respectively

  14. Verification of a prognostic meteorological and air pollution model for year-long predictions in the Kwinana industrial region of Western Australia

    International Nuclear Information System (INIS)

    Hurley, P.J.; Blockley, A.; Rayner, K.

    2001-01-01

    A prognostic air pollution model (TAPM) has been used to predict meteorology and sulphur dioxide concentration in the Kwinana industrial region of Western Australia for 1997, with a view to verifying TAPM for use in environmental impact assessments and associated air pollution studies. The regulatory plume model, DISPMOD, developed for the Kwinana region has also been run using both an observationally based meteorological file (denoted DISPMOD-O) and using a TAPM-based meteorological file (denoted DISPMOD-T). TAPM predictions of the meteorology for 1997 compare well with the observed values at each of the five monitoring sites. Root mean square error and index of agreement values for temperature and winds indicate that TAPM performs well at predicting the meteorology, compared to the performance of similar models from other studies. The yearly average, 99.9 percentile, maximum and mean of the top 10 ground-level sulphur dioxide concentrations for 1997 were predicted well by all of the model runs, although DISPMOD-O and DISPMOD-T tended to overpredict extreme statistics at sites furthest from the sources. Overall, TAPM performed better than DISPMOD-O, which in turn performed better than DISPMOD-T, for all statistics considered, but we consider that all three sets of results are sufficiently accurate for regulatory applications. The mean of the top ten concentrations is generally considered to be a robust performance statistic for air pollution applications, and we show that compared to the site-averaged observed value of 95μgm -3 , TAPM predicted 94μgm -3 , DISPMOD-O predicted 111μgm -3 and DISPMOD-T predicted 125μgm -3 . The results indicate that the prognostic meteorological and air pollution approach to regulatory modelling used by TAPM, gives comparable or better results than the current regulatory approach used in the Kwinana region (DISPMOD), and also indicates that the approach of using a currently accepted regulatory model with a prognostically

  15. Experimental program for physics-of-failure modeling of electrolytic capacitors towards prognostics and health management

    International Nuclear Information System (INIS)

    Rana, Y.S.; Banerjee, Shantanab; Singh, Tej; Varde, P.V.

    2017-01-01

    Prognostics and Health Management (PHM) is a method used for predicting reliability of a component or system by assessing its current health and future operating conditions. A physics-of-failure (PoF)-based program on PHM for reliability prediction has been initiated at our institute. As part of the program, we aim at developing PoF-based models for degradation of electronic components and their experimental validation. In this direction, a database on existing PoF models for different electronic components has been prepared. We plan to experimentally determine the model constants and propose suitable methodology for PHM. Electrolytic capacitors are one of the most common passive components which find their applications in devices such as power supplies in aircrafts and printed circuit boards (PCBs) for regulation and protection of a nuclear reactor. Experimental studies have established that electrolytic capacitors degrade under electrical and thermal stress and tend to fail before their anticipated useful life at normal operating conditions. Equivalent series resistance (ESR) and capacitance (C) are the two main parameters used for monitoring health of such capacitors. In this paper, we present an experimental program for thermal and electrical overstress studies towards degradation models for electrolytic capacitors. (author)

  16. Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

    Science.gov (United States)

    Daigle, Matthew John; Goebel, Kai Frank

    2010-01-01

    Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

  17. Development and validation of prognostic models in metastatic breast cancer: a GOCS study.

    Science.gov (United States)

    Rabinovich, M; Vallejo, C; Bianco, A; Perez, J; Machiavelli, M; Leone, B; Romero, A; Rodriguez, R; Cuevas, M; Dansky, C

    1992-01-01

    The significance of several prognostic factors and the magnitude of their influence on response rate and survival were assessed by means of uni- and multivariate analyses in 362 patients with stage IV (UICC) breast carcinoma receiving combination chemotherapy as first systemic treatment over an 8-year period. Univariate analyses identified performance status and prior adjuvant radiotherapy as predictors of objective regression (OR), whereas the performance status, prior chemotherapy and radiotherapy (adjuvants), white blood cells count, SGOT and SGPT levels, and metastatic pattern were significantly correlated to survival. In multivariate analyses favorable characteristics associated to OR were prior adjuvant radiotherapy, no prior chemotherapy and postmenopausal status. Regarding survival, the performance status and visceral involvement were selected by the Cox model. The predictive accuracy of the logistic and the proportional hazards models was retrospectively tested in the training sample, and prospectively in a new population of 126 patients also receiving combined chemotherapy as first treatment for metastatic breast cancer. A certain overfitting to data in the training sample was observed with the regression model for response. However, the discriminative ability of the Cox model for survival was clearly confirmed.

  18. Cumulative Intracranial Tumor Volume Augments the Prognostic Value of Diagnosis-Specific Graded Prognostic Assessment Model for Survival in Patients with Melanoma Cerebral Metastases

    DEFF Research Database (Denmark)

    Hirshman, Brian R; Wilson, Bayard R; Ali, Mir Amaan

    2018-01-01

    BACKGROUND: The diagnosis-specific graded prognostic assessment scale (ds-GPA) for patients with melanoma brain metastasis (BM) utilizes only 2 key prognostic variables: Karnofsky performance status and the number of intracranial metastases. We wished to determine whether inclusion of cumulative ...

  19. A prognostic model for soft tissue sarcoma of the extremities and trunk wall based on size, vascular invasion, necrosis, and growth pattern

    DEFF Research Database (Denmark)

    Carneiro, Ana; Bendahl, Par-Ola; Engellau, Jacob

    2011-01-01

    type, necrosis, and grade. METHODS:: Whole-tumor sections from 239 soft tissue sarcomas of the extremities were reviewed for the following prognostic factors: size, vascular invasion, necrosis, and growth pattern. A new prognostic model, referred to as SING (Size, Invasion, Necrosis, Growth...

  20. Development of a prognostic model for predicting spontaneous singleton preterm birth.

    Science.gov (United States)

    Schaaf, Jelle M; Ravelli, Anita C J; Mol, Ben Willem J; Abu-Hanna, Ameen

    2012-10-01

    To develop and validate a prognostic model for prediction of spontaneous preterm birth. Prospective cohort study using data of the nationwide perinatal registry in The Netherlands. We studied 1,524,058 singleton pregnancies between 1999 and 2007. We developed a multiple logistic regression model to estimate the risk of spontaneous preterm birth based on maternal and pregnancy characteristics. We used bootstrapping techniques to internally validate our model. Discrimination (AUC), accuracy (Brier score) and calibration (calibration graphs and Hosmer-Lemeshow C-statistic) were used to assess the model's predictive performance. Our primary outcome measure was spontaneous preterm birth at model included 13 variables for predicting preterm birth. The predicted probabilities ranged from 0.01 to 0.71 (IQR 0.02-0.04). The model had an area under the receiver operator characteristic curve (AUC) of 0.63 (95% CI 0.63-0.63), the Brier score was 0.04 (95% CI 0.04-0.04) and the Hosmer Lemeshow C-statistic was significant (pvalues of predicted probability. The positive predictive value was 26% (95% CI 20-33%) for the 0.4 probability cut-off point. The model's discrimination was fair and it had modest calibration. Previous preterm birth, drug abuse and vaginal bleeding in the first half of pregnancy were the most important predictors for spontaneous preterm birth. Although not applicable in clinical practice yet, this model is a next step towards early prediction of spontaneous preterm birth that enables caregivers to start preventive therapy in women at higher risk. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  1. Analysis of acute myocardial infarction occurance in Saratov region using GIS-technologies and prognostic modeling

    Directory of Open Access Journals (Sweden)

    SokolovI.M.

    2012-09-01

    Full Text Available

     

    The research objective: To find estimation tools of incidence of acute myocardial infarction at the regional level and to optimize organization of medical assistance to patients with acute coronary pathology. Materials. With the use of statistics of territorial distribution of acute myocardial infarction incidence in the region and GIS-TECHNOLOGIES the statistical analysis and mathematical modelling of the spatially-organizational data has been carried out. Results. On the basis of the received results the prognostic model of development of acute coronary pathology has been generated. Measures on optimization of organization of medical assistance to patients with an acute coronary pathology have been stated. Conclusion. Methods of intellectual support of the doctor may become effective in formation of organizational structure of the system of stage-by-stage qualified and specialized aid to patients with acute coronary syndrome.

  2. A Modeling Framework for Prognostic Decision Making and its Application to UAV Mission Planning

    Data.gov (United States)

    National Aeronautics and Space Administration — The goal of prognostic decision making (PDM) is to utilize information on anticipated system health changes in selecting future actions. One of the key challenges in...

  3. Comparison of Two Probabilistic Fatigue Damage Assessment Approaches Using Prognostic Performance Metrics

    Data.gov (United States)

    National Aeronautics and Space Administration — A general framework for probabilistic prognosis using maximum entropy approach, MRE, is proposed in this paper to include all available information and uncertainties...

  4. Simple prognostic model for patients with advanced cancer based on performance status.

    Science.gov (United States)

    Jang, Raymond W; Caraiscos, Valerie B; Swami, Nadia; Banerjee, Subrata; Mak, Ernie; Kaya, Ebru; Rodin, Gary; Bryson, John; Ridley, Julia Z; Le, Lisa W; Zimmermann, Camilla

    2014-09-01

    Providing survival estimates is important for decision making in oncology care. The purpose of this study was to provide survival estimates for outpatients with advanced cancer, using the Eastern Cooperative Oncology Group (ECOG), Palliative Performance Scale (PPS), and Karnofsky Performance Status (KPS) scales, and to compare their ability to predict survival. ECOG, PPS, and KPS were completed by physicians for each new patient attending the Princess Margaret Cancer Centre outpatient Oncology Palliative Care Clinic (OPCC) from April 2007 to February 2010. Survival analysis was performed using the Kaplan-Meier method. The log-rank test for trend was employed to test for differences in survival curves for each level of performance status (PS), and the concordance index (C-statistic) was used to test the predictive discriminatory ability of each PS measure. Measures were completed for 1,655 patients. PS delineated survival well for all three scales according to the log-rank test for trend (P statistic was similar for all three scales and ranged from 0.63 to 0.64. We present a simple tool that uses PS alone to prognosticate in advanced cancer, and has similar discriminatory ability to more complex models. Copyright © 2014 by American Society of Clinical Oncology.

  5. Material Modelling - Composite Approach

    DEFF Research Database (Denmark)

    Nielsen, Lauge Fuglsang

    1997-01-01

    is successfully justified comparing predicted results with experimental data obtained in the HETEK-project on creep, relaxation, and shrinkage of very young concretes cured at a temperature of T = 20^o C and a relative humidity of RH = 100%. The model is also justified comparing predicted creep, shrinkage......, and internal stresses caused by drying shrinkage with experimental results reported in the literature on the mechanical behavior of mature concretes. It is then concluded that the model presented applied in general with respect to age at loading.From a stress analysis point of view the most important finding...... in this report is that cement paste and concrete behave practically as linear-viscoelastic materials from an age of approximately 10 hours. This is a significant age extension relative to earlier studies in the literature where linear-viscoelastic behavior is only demonstrated from ages of a few days. Thus...

  6. Validation of new prognostic and predictive scores by sequential testing approach

    International Nuclear Information System (INIS)

    Nieder, Carsten; Haukland, Ellinor; Pawinski, Adam; Dalhaug, Astrid

    2010-01-01

    Background and Purpose: For practitioners, the question arises how their own patient population differs from that used in large-scale analyses resulting in new scores and nomograms and whether such tools actually are valid at a local level and thus can be implemented. A recent article proposed an easy-to-use method for the in-clinic validation of new prediction tools with a limited number of patients, a so-called sequential testing approach. The present study evaluates this approach in scores related to radiation oncology. Material and Methods: Three different scores were used, each predicting short overall survival after palliative radiotherapy (bone metastases, brain metastases, metastatic spinal cord compression). For each scenario, a limited number of consecutive patients entered the sequential testing approach. The positive predictive value (PPV) was used for validation of the respective score and it was required that the PPV exceeded 80%. Results: For two scores, validity in the own local patient population could be confirmed after entering 13 and 17 patients, respectively. For the third score, no decision could be reached even after increasing the sample size to 30. Conclusion: In-clinic validation of new predictive tools with sequential testing approach should be preferred over uncritical adoption of tools which provide no significant benefit to local patient populations. Often the necessary number of patients can be reached within reasonable time frames even in small oncology practices. In addition, validation is performed continuously as the data are collected. (orig.)

  7. Validation of new prognostic and predictive scores by sequential testing approach

    Energy Technology Data Exchange (ETDEWEB)

    Nieder, Carsten [Radiation Oncology Unit, Nordland Hospital, Bodo (Norway); Inst. of Clinical Medicine, Univ. of Tromso (Norway); Haukland, Ellinor; Pawinski, Adam; Dalhaug, Astrid [Radiation Oncology Unit, Nordland Hospital, Bodo (Norway)

    2010-03-15

    Background and Purpose: For practitioners, the question arises how their own patient population differs from that used in large-scale analyses resulting in new scores and nomograms and whether such tools actually are valid at a local level and thus can be implemented. A recent article proposed an easy-to-use method for the in-clinic validation of new prediction tools with a limited number of patients, a so-called sequential testing approach. The present study evaluates this approach in scores related to radiation oncology. Material and Methods: Three different scores were used, each predicting short overall survival after palliative radiotherapy (bone metastases, brain metastases, metastatic spinal cord compression). For each scenario, a limited number of consecutive patients entered the sequential testing approach. The positive predictive value (PPV) was used for validation of the respective score and it was required that the PPV exceeded 80%. Results: For two scores, validity in the own local patient population could be confirmed after entering 13 and 17 patients, respectively. For the third score, no decision could be reached even after increasing the sample size to 30. Conclusion: In-clinic validation of new predictive tools with sequential testing approach should be preferred over uncritical adoption of tools which provide no significant benefit to local patient populations. Often the necessary number of patients can be reached within reasonable time frames even in small oncology practices. In addition, validation is performed continuously as the data are collected. (orig.)

  8. An internally validated prognostic model for success in revision stapes surgery for otosclerosis.

    Science.gov (United States)

    Wegner, Inge; Vincent, Robert; Derks, Laura S M; Rauh, Simone P; Heymans, Martijn W; Stegeman, Inge; Grolman, Wilko

    2018-03-09

    To develop a prediction model that can accurately predict the chance of success following revision stapes surgery in patients with recurrent or persistent otosclerosis at 2- to 6-months follow-up and to validate this model internally. A retrospective cohort study of prospectively gathered data in a tertiary referral center. The associations of 11 prognostic factors with treatment success were tested in 705 cases using multivariable logistic regression analysis with backward selection. Success was defined as a mean air-bone gap closure to 10 dB or less. The most relevant predictors were used to derive a clinical prediction rule to determine the probability of success. Internal validation by means of bootstrapping was performed. Model performance indices, including the Hosmer-Lemeshow test, the area under the receiver operating characteristics curve (AUC), and the explained variance were calculated. Success was achieved in 57.7% of cases at 2- to 6-months follow-up. Certain previous surgical techniques, primary causes of failure leading up to revision stapes surgery, and positions of the prosthesis placed during revision surgery were associated with higher success percentages. The clinical prediction rule performed moderately well in the original dataset (Hosmer-Lemeshow P = .78; AUC = 0.73; explained variance = 22%), which slightly decreased following internal validation by means of bootstrapping (AUC = 0.69; explained variance = 13%). Our study established the importance of previous surgical technique, primary cause of failure, and type of the prosthesis placed during the revision surgery in predicting the probability of success following stapes surgery at 2- to 6-months follow-up. 2b. Laryngoscope, 2018. © 2018 The American Laryngological, Rhinological and Otological Society, Inc.

  9. Incorporating Prognostic Marine Nitrogen Fixers and Related Bio-Physical Feedbacks in an Earth System Model

    Science.gov (United States)

    Paulsen, H.; Ilyina, T.; Six, K. D.

    2016-02-01

    Marine nitrogen fixers play a fundamental role in the oceanic nitrogen and carbon cycles by providing a major source of `new' nitrogen to the euphotic zone that supports biological carbon export and sequestration. Furthermore, nitrogen fixers may regionally have a direct impact on ocean physics and hence the climate system as they form extensive surface mats which can increase light absorption and surface albedo and reduce the momentum input by wind. Resulting alterations in temperature and stratification may feed back on nitrogen fixers' growth itself.We incorporate nitrogen fixers as a prognostic 3D tracer in the ocean biogeochemical component (HAMOCC) of the Max Planck Institute Earth system model and assess for the first time the impact of related bio-physical feedbacks on biogeochemistry and the climate system.The model successfully reproduces recent estimates of global nitrogen fixation rates, as well as the observed distribution of nitrogen fixers, covering large parts of the tropical and subtropical oceans. First results indicate that including bio-physical feedbacks has considerable effects on the upper ocean physics in this region. Light absorption by nitrogen fixers leads locally to surface heating, subsurface cooling, and mixed layer depth shoaling in the subtropical gyres. As a result, equatorial upwelling is increased, leading to surface cooling at the equator. This signal is damped by the effect of the reduced wind stress due to the presence of cyanobacteria mats, which causes a reduction in the wind-driven circulation, and hence a reduction in equatorial upwelling. The increase in surface albedo due to nitrogen fixers has only inconsiderable effects. The response of nitrogen fixers' growth to the alterations in temperature and stratification varies regionally. Simulations with the fully coupled Earth system model are in progress to assess the implications of the biologically induced changes in upper ocean physics for the global climate system.

  10. Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3)

    Science.gov (United States)

    Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike

    2018-04-01

    A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and raindrops. The unique aspect of the new scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice by a single category that predicts bulk particle properties (P3). This method has already been applied in a regional model and most recently also in the Community Atmosphere Model 5 (CAM5). A single cloud ice category does not rely on heuristic conversion rates from one category to another. Therefore, it is conceptually easier and closer to first principles. This work shows that a single category is a viable approach to describe cloud ice in climate models. Prognostic representation of sedimentation is achieved by a nested approach for sub-stepping the cloud microphysics scheme. This yields good results in terms of accuracy and performance as compared to simulations with high temporal resolution. Furthermore, the new scheme allows for a competition between various cloud processes and is thus able to unbiasedly represent the ice formation pathway from nucleation to growth by vapor deposition and collisions to sedimentation. Specific aspects of the P3 method are evaluated. We could not produce a purely stratiform cloud where rime growth dominates growth by vapor deposition and conclude that the lack of appropriate conditions renders the prognostic parameters associated with the rime properties unnecessary. Limitations inherent in a single category are examined.

  11. Generic Software Architecture for Prognostics (GSAP) User Guide

    Science.gov (United States)

    Teubert, Christopher Allen; Daigle, Matthew John; Watkins, Jason; Sankararaman, Shankar; Goebel, Kai

    2016-01-01

    The Generic Software Architecture for Prognostics (GSAP) is a framework for applying prognostics. It makes applying prognostics easier by implementing many of the common elements across prognostic applications. The standard interface enables reuse of prognostic algorithms and models across systems using the GSAP framework.

  12. VTE Risk assessment - a prognostic Model: BATER Cohort Study of young women.

    Science.gov (United States)

    Heinemann, Lothar Aj; Dominh, Thai; Assmann, Anita; Schramm, Wolfgang; Schürmann, Rolf; Hilpert, Jan; Spannagl, Michael

    2005-04-18

    BACKGROUND: Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE). There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. MATERIALS AND METHODS: A 10-year observation period of the Bavarian Thromboembolic Risk (BATER) study, a cohort study of 4337 women (18-55 years), was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993). The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. RESULTS: Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs). A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI) and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation). Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%), moderate risk (21.1%), high risk (6.0%), very high risk of future VTE (0.9%). In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. CONCLUSION: Our prognostic tool - containing clinical information (and if available also genetic data) - seems to be

  13. VTE Risk assessment – a prognostic Model: BATER Cohort Study of young women

    Directory of Open Access Journals (Sweden)

    Schürmann Rolf

    2005-04-01

    Full Text Available Abstract Background Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE. There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. Materials and methods A 10-year observation period of the Bavarian Thromboembolic Risk (BATER study, a cohort study of 4337 women (18–55 years, was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993. The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. Results Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs. A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation. Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%, moderate risk (21.1%, high risk (6.0%, very high risk of future VTE (0.9%. In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. Conclusion Our prognostic tool – containing clinical information (and if available also genetic data

  14. Glycolytic activity in breast cancer using 18F-FDG PET/CT as prognostic predictor: A molecular phenotype approach.

    Science.gov (United States)

    Garcia Vicente, A M; Soriano Castrejón, A; Amo-Salas, M; Lopez Fidalgo, J F; Muñoz Sanchez, M M; Alvarez Cabellos, R; Espinosa Aunion, R; Muñoz Madero, V

    2016-01-01

    To explore the relationship between basal (18)F-FDG uptake in breast tumors and survival in patients with breast cancer (BC) using a molecular phenotype approach. This prospective and multicentre study included 193 women diagnosed with BC. All patients underwent an (18)F-FDG PET/CT prior to treatment. Maximum standardized uptake value (SUVmax) in tumor (T), lymph nodes (N), and the N/T index was obtained in all the cases. Metabolic stage was established. As regards biological prognostic parameters, tumors were classified into molecular sub-types and risk categories. Overall survival (OS) and disease free survival (DFS) were obtained. An analysis was performed on the relationship between semi-quantitative metabolic parameters with molecular phenotypes and risk categories. The effect of molecular sub-type and risk categories in prognosis was analyzed using Kaplan-Meier and univariate and multivariate tests. Statistical differences were found in both SUVT and SUVN, according to the molecular sub-types and risk classifications, with higher semi-quantitative values in more biologically aggressive tumors. No statistical differences were observed with respect to the N/T index. Kaplan-Meier analysis revealed that risk categories were significantly related to DFS and OS. In the multivariate analysis, metabolic stage and risk phenotype showed a significant association with DFS. High-risk phenotype category showed a worst prognosis with respect to the other categories with higher SUVmax in primary tumor and lymph nodes. Copyright © 2015 Elsevier España, S.L.U. and SEMNIM. All rights reserved.

  15. Prognostics and health management of engineering systems an introduction

    CERN Document Server

    Kim, Nam-Ho; Choi, Joo-Ho

    2017-01-01

    This book introduces the methods for predicting the future behavior of a system’s health and the remaining useful life to determine an appropriate maintenance schedule. The authors introduce the history, industrial applications, algorithms, and benefits and challenges of PHM (Prognostics and Health Management) to help readers understand this highly interdisciplinary engineering approach that incorporates sensing technologies, physics of failure, machine learning, modern statistics, and reliability engineering. It is ideal for beginners because it introduces various prognostics algorithms and explains their attributes, pros and cons in terms of model definition, model parameter estimation, and ability to handle noise and bias in data, allowing readers to select the appropriate methods for their fields of application. Among the many topics discussed in-depth are: • Prognostics tutorials using least-squares • Bayesian inference and parameter estimation • Physics-based prognostics algorithms including non...

  16. Proposal of a clinical typing system and generation of a prognostic model in patients with nasopharyngeal carcinoma from Southern China.

    Science.gov (United States)

    Sun, Peng; Chen, Cui; Chen, Xin-Lin; Cheng, Yi-Kan; Zeng, Lei; Zeng, Zhi-Jian; Liu, Li-Zhi; Su, Yong; Gu, Mo-Fa

    2014-01-01

    To propose a novel clinical typing classification focusing on the distinct progression patterns of nasopharyngeal carcinoma (NPC), to supplement our knowledge of the clinical-biological behavior, to provide useful knowledge for treatment planning, and to contribute to basic research in NPC. 632 consecutive patients were retrospectively reviewed and analyzed according to the novel typing system. We considered that NPC can be divided into 5 types as follows: limited (L), ascending (A), descending (D) ascending- descending (mixed) (AD), and distant metastasis types (M). The distribution of these clinical types, their association with Epstein-Barr virus (EBV) serology and prognostic value were explored. 55 (8.70%), 59 (9.34%), 177 (28.01%), 321 (50.79%) and 20 (3.16%) patients were classified as Type L, A, D, AD and M, respectively. EBV (VCA)-IgA titers, EBV early antigen (EA)-IgA serum titers, and capsid antigen lg(EBV DNA) were positively associated with the clinical typing (pTypes L, A, D, AD and M were 100, 100, 95.10, 88.20 and 59.30%, respectively (ptype, which were independent predictors of OS (multivariate Cox proportional model). The prognostic model stratified patients into 4 risk subgroups. The 3-year OS rates of the low, intermediate, high and extremely high risk groups were 99.5, 90.0, 85.5 and 53.2%, respectively (ptyping system and prognostic model can supplement TNM classification, and may help design novel treatment strategies, evaluate risk stratification and investigate the varied biological characteristics of NPC.

  17. A first appraisal of prognostic ocean DMS models and prospects for their use in climate models

    NARCIS (Netherlands)

    Le Clainche, Yvonnick; Vezina, Alain; Levasseur, Maurice; Cropp, Roger A.; Gunson, Jim R.; Vallina, Sergio M.; Vogt, Meike; Lancelot, Christiane; Allen, J. Icarus; Archer, Stephen D.; Bopp, Laurent; Deal, Clara; Elliott, Scott; Jin, Meibing; Malin, Gill; Schoemann, Veronique; Simo, Rafel; Six, Katharina D.; Stefels, Jacqueline

    2010-01-01

    Ocean dimethylsulfide (DMS) produced by marine biota is the largest natural source of atmospheric sulfur, playing a major role in the formation and evolution of aerosols, and consequently affecting climate. Several dynamic process-based DMS models have been developed over the last decade, and work

  18. Survey on Prognostics Techniques for Updating Initiating Event Frequency in PSA

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyeonmin; Heo, Gyunyoung [Kyung Hee University, Yongin (Korea, Republic of)

    2015-05-15

    One of the applications using PSA is a risk monito. The risk monitoring is real-time analysis tool to decide real-time risk based on real state of components and systems. In order to utilize more effective, the methodologies that manipulate the data from Prognostics was suggested. Generally, Prognostic comprehensively includes not only prognostic but also monitoring and diagnostic. The prognostic method must need condition monitoring. In case of applying PHM to a PSA model, the latest condition of NPPs can be identified more clearly. For reducing the conservatism and uncertainties, we suggested the concept that updates the initiating event frequency in a PSA model by using Bayesian approach which is one of the prognostics techniques before. From previous research, the possibility that PSA is updated by using data more correctly was found. In reliability theory, the Bathtub curve divides three parts (infant failure, constant and random failure, wareout failure). In this paper, in order to investigate the applicability of prognostic methods in updating quantitative data in a PSA model, the OLM acceptance criteria from NUREG, the concept of how to using prognostic in PSA, and the enabling prognostic techniques are suggested. The prognostic has the motivation that improved the predictive capabilities using existing monitoring systems, data, and information will enable more accurate equipment risk assessment for improved decision-making.

  19. Survey on Prognostics Techniques for Updating Initiating Event Frequency in PSA

    International Nuclear Information System (INIS)

    Kim, Hyeonmin; Heo, Gyunyoung

    2015-01-01

    One of the applications using PSA is a risk monito. The risk monitoring is real-time analysis tool to decide real-time risk based on real state of components and systems. In order to utilize more effective, the methodologies that manipulate the data from Prognostics was suggested. Generally, Prognostic comprehensively includes not only prognostic but also monitoring and diagnostic. The prognostic method must need condition monitoring. In case of applying PHM to a PSA model, the latest condition of NPPs can be identified more clearly. For reducing the conservatism and uncertainties, we suggested the concept that updates the initiating event frequency in a PSA model by using Bayesian approach which is one of the prognostics techniques before. From previous research, the possibility that PSA is updated by using data more correctly was found. In reliability theory, the Bathtub curve divides three parts (infant failure, constant and random failure, wareout failure). In this paper, in order to investigate the applicability of prognostic methods in updating quantitative data in a PSA model, the OLM acceptance criteria from NUREG, the concept of how to using prognostic in PSA, and the enabling prognostic techniques are suggested. The prognostic has the motivation that improved the predictive capabilities using existing monitoring systems, data, and information will enable more accurate equipment risk assessment for improved decision-making

  20. Evaluation of Simulated Marine Aerosol Production Using the WaveWatchIII Prognostic Wave Model Coupled to the Community Atmosphere Model within the Community Earth System Model

    Energy Technology Data Exchange (ETDEWEB)

    Long, M. S. [Harvard Univ., Cambridge, MA (United States). School of Engineering and Applied Sciences; Keene, William C. [Univ. of Virginia, Charlottesville, VA (United States). Dept. of Environmental Sciences; Zhang, J. [Univ. of North Dakota, Grand Forks, ND (United States). Dept. of Atmospheric Sciences; Reichl, B. [Univ. of Rhode Island, Narragansett, RI (United States). Graduate School of Oceanography; Shi, Y. [Univ. of North Dakota, Grand Forks, ND (United States). Dept. of Atmospheric Sciences; Hara, T. [Univ. of Rhode Island, Narragansett, RI (United States). Graduate School of Oceanography; Reid, J. S. [Naval Research Lab. (NRL), Monterey, CA (United States); Fox-Kemper, B. [Brown Univ., Providence, RI (United States). Earth, Environmental and Planetary Sciences; Craig, A. P. [National Center for Atmospheric Research, Boulder, CO (United States); Erickson, D. J. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Computer Science and Mathematics Division; Ginis, I. [Univ. of Rhode Island, Narragansett, RI (United States). Graduate School of Oceanography; Webb, A. [Univ. of Tokyo (Japan). Dept. of Ocean Technology, Policy, and Environment

    2016-11-08

    Primary marine aerosol (PMA) is emitted into the atmosphere via breaking wind waves on the ocean surface. Most parameterizations of PMA emissions use 10-meter wind speed as a proxy for wave action. This investigation coupled the 3rd generation prognostic WAVEWATCH-III wind-wave model within a coupled Earth system model (ESM) to drive PMA production using wave energy dissipation rate – analogous to whitecapping – in place of 10-meter wind speed. The wind speed parameterization did not capture basin-scale variability in relations between wind and wave fields. Overall, the wave parameterization did not improve comparison between simulated versus measured AOD or Na+, thus highlighting large remaining uncertainties in model physics. Results confirm the efficacy of prognostic wind-wave models for air-sea exchange studies coupled with laboratory- and field-based characterizations of the primary physical drivers of PMA production. No discernible correlations were evident between simulated PMA fields and observed chlorophyll or sea surface temperature.

  1. Evaporator modeling - A hybrid approach

    International Nuclear Information System (INIS)

    Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun

    2009-01-01

    In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis

  2. Real-Time Prognostics of a Rotary Valve Actuator

    Science.gov (United States)

    Daigle, Matthew

    2015-01-01

    Valves are used in many domains and often have system-critical functions. As such, it is important to monitor the health of valves and their actuators and predict remaining useful life. In this work, we develop a model-based prognostics approach for a rotary valve actuator. Due to limited observability of the component with multiple failure modes, a lumped damage approach is proposed for estimation and prediction of damage progression. In order to support the goal of real-time prognostics, an approach to prediction is developed that does not require online simulation to compute remaining life, rather, a function mapping the damage state to remaining useful life is found offline so that predictions can be made quickly online with a single function evaluation. Simulation results demonstrate the overall methodology, validating the lumped damage approach and demonstrating real-time prognostics.

  3. 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

  4. 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.

  5. Performance and customization of 4 prognostic models for postoperative onset of nausea and vomiting in ear, nose, and throat surgery.

    Science.gov (United States)

    Engel, Jörg M; Junger, Axel; Hartmann, Bernd; Little, Simon; Schnöbel, Rose; Mann, Valesco; Jost, Andreas; Welters, Ingeborg D; Hempelmann, Gunter

    2006-06-01

    To evaluate the performance of 4 published prognostic models for postoperative onset of nausea and vomiting (PONV) by means of discrimination and calibration and the possible impact of customization on these models. Prospective, observational study. Tertiary care university hospital. 748 adult patients (>18 years old) enrolled in this study. Severe obesity (weight > 150 kg or body mass index > 40 kg/m) was an exclusion criterion. All perioperative data were recorded with an anesthesia information management system. A standardized patient interview was performed on the postoperative morning and afternoon. Individual PONV risk was calculated using 4 original regression equations by Koivuranta et al, Apfel et al, Sinclair et al, and Junger et al Discrimination was assessed using receiver operating characteristic (ROC) curves. Calibration was tested using Hosmer-Lemeshow goodness-of-fit statistics. New predictive equations for the 4 models were derived by means of logistic regression (customization). The prognostic performance of the customized models was validated using the "leaving-one-out" technique. Postoperative onset of nausea and vomiting was observed in 11.2% of the specialized patient population. Discrimination could be demonstrated as shown by areas under the receiver operating characteristic curve of 0.62 for the Koivuranta et al model, 0.63 for the Apfel et al model, 0.70 for the Sinclair et al model, and 0.70 for the Junger et al model. Calibration was poor for all 4 original models, indicated by a P value lower than 0.01 in the C and H statistics. Customization improved the accuracy of the prediction for all 4 models. However, the simplified risk scores of the Koivuranta et al model and the Apfel et al model did not show the same efficiency as those of the Sinclair et al model and the Junger et al model. This is possibly a result of having relatively few patients at high risk for PONV in combination with an information loss caused by too few dichotomous

  6. Perioperative and long-term outcome of thymectomy for myasthenia gravis: comparison of surgical approaches and prognostic analysis.

    Science.gov (United States)

    Liu, Cheng-wu; Luo, Meng; Mei, Jian-dong; Zhu, Yun-ke; Pu, Qiang; Ma, Lin; Che, Guo-wei; Lin, Yi-dan; Wu, Zhu; Wang, Yun; Kou, Ying-li; Liu, Lun-xu

    2013-01-01

    Thymectomy is an established treatment for myasthenia gravis (MG), and video-assisted thoracoscopic surgery (VATS) thymectomy has become an acceptable surgical procedure. This study aimed to compare the results of VATS thymectomy and open thymectomy and to identify the prognostic factors after thymectomy. The clinical data of 187 consecutive thymectomies performed between July 2000 and December 2009 were retrospectively reviewed; 75 open thymectomies and 112 VATS thymectomies. Clinical efficacy and variables influencing outcome were assessed by Kaplan-Meier survival curves and Cox proportional hazards regression analysis. The operative blood loss in the VATS group was significantly less than that in the open group ((62.14 ± 55.43) ml vs. (137.87 ± 165.25) ml, P CSR) was the end point for evaluation of the treatment results. The overall five-year CSR rate was 57.5%. Two good prognostic factors were identified; preoperative prescription of anticholinesterase alone (P = 0.035) and non-thymomatous MG (P = 0.003). The five-year CSR rate of the ocular type of MG reached a high level of 67.4%. Thymectomy can achieve good long-term CSR in MG, and VATS is an ideal alternative method. High-dose prescription of anticholinesterase and the advanced stage by Myasthenia Gravis Foundation of America (MGFA) classification have higher risks of postoperative crisis. Preoperative prescription of anticholinesterase alone and non-thymomatous MG are good prognostic factors. Thymectomy should also be considered for the ocular type of MG.

  7. Updated survivals and prognostic factor analysis in myeloma treated by a staged approach use of bortezomib/thalidomide/dexamethasone in transplant eligible patients

    Directory of Open Access Journals (Sweden)

    Chim Chor

    2010-11-01

    Full Text Available Abstract Background Bortezomib, an NFkB inhibitor, is an active agent for the treatment of myeloma (MM. We have reported a promising complete remission (CR rate for newly diagnosed myeloma patients treated by a staged approach, in which chemosensitive patients underwent autologous haematopoietic stem cell transplantation (auto-HSCT while less chemosensitive patients received salvage therapy with bortezomib/thalidomide/dexamethasone prior to auto-HSCT. Methods Herein, with an additional 13 months of follow-up, we reported the updated survivals, and examined potential prognostic factors impacting event-free (EFS and overall survival (OS. Results With a median follow-up of 30 months, the projected OS was 73% and EFS was 50.2%. Age, gender, clinical stage and DAPK methylation could not account for the differential chemosensitivity. Advanced ISS stage and DAPK methylation adversely impacted OS whereas oligoclonal reconstitution predicted superior EFS. Conclusions Our staged approach illustrated an economical use of expensive targeted agents while preserving a good CR rate and OS. The comparable survivals of chemosensitive and less chemosensitive patients suggested the staged approach might have abolished the adverse prognostic impact of suboptimal chemosensitivity. Finally, the adverse impact of DAPK methylation and favorable impact of oligoclonal reconstitution in myeloma warrants further study.

  8. Cutaneous Lymphoma International Consortium Study of Outcome in Advanced Stages of Mycosis Fungoides and Sézary Syndrome: Effect of Specific Prognostic Markers on Survival and Development of a Prognostic Model

    Science.gov (United States)

    Scarisbrick, Julia J.; Prince, H. Miles; Vermeer, Maarten H.; Quaglino, Pietro; Horwitz, Steven; Porcu, Pierluigi; Stadler, Rudolf; Wood, Gary S.; Beylot-Barry, Marie; Pham-Ledard, Anne; Foss, Francine; Girardi, Michael; Bagot, Martine; Michel, Laurence; Battistella, Maxime; Guitart, Joan; Kuzel, Timothy M.; Martinez-Escala, Maria Estela; Estrach, Teresa; Papadavid, Evangelia; Antoniou, Christina; Rigopoulos, Dimitis; Nikolaou, Vassilki; Sugaya, Makoto; Miyagaki, Tomomitsu; Gniadecki, Robert; Sanches, José Antonio; Cury-Martins, Jade; Miyashiro, Denis; Servitje, Octavio; Muniesa, Cristina; Berti, Emilio; Onida, Francesco; Corti, Laura; Hodak, Emilia; Amitay-Laish, Iris; Ortiz-Romero, Pablo L.; Rodríguez-Peralto, Jose L.; Knobler, Robert; Porkert, Stefanie; Bauer, Wolfgang; Pimpinelli, Nicola; Grandi, Vieri; Cowan, Richard; Rook, Alain; Kim, Ellen; Pileri, Alessandro; Patrizi, Annalisa; Pujol, Ramon M.; Wong, Henry; Tyler, Kelly; Stranzenbach, Rene; Querfeld, Christiane; Fava, Paolo; Maule, Milena; Willemze, Rein; Evison, Felicity; Morris, Stephen; Twigger, Robert; Talpur, Rakhshandra; Kim, Jinah; Ognibene, Grant; Li, Shufeng; Tavallaee, Mahkam; Hoppe, Richard T.; Duvic, Madeleine; Whittaker, Sean J.; Kim, Youn H.

    2015-01-01

    Purpose Advanced-stage mycosis fungoides (MF; stage IIB to IV) and Sézary syndrome (SS) are aggressive lymphomas with a median survival of 1 to 5 years. Clinical management is stage based; however, there is wide range of outcome within stages. Published prognostic studies in MF/SS have been single-center trials. Because of the rarity of MF/SS, only a large collaboration would power a study to identify independent prognostic markers. Patients and Methods Literature review identified the following 10 candidate markers: stage, age, sex, cutaneous histologic features of folliculotropism, CD30 positivity, proliferation index, large-cell transformation, WBC/lymphocyte count, serum lactate dehydrogenase, and identical T-cell clone in blood and skin. Data were collected at specialist centers on patients diagnosed with advanced-stage MF/SS from 2007. Each parameter recorded at diagnosis was tested against overall survival (OS). Results Staging data on 1,275 patients with advanced MF/SS from 29 international sites were included for survival analysis. The median OS was 63 months, with 2- and 5-year survival rates of 77% and 52%, respectively. The median OS for patients with stage IIB disease was 68 months, but patients diagnosed with stage III disease had slightly improved survival compared with patients with stage IIB, although patients diagnosed with stage IV disease had significantly worse survival (48 months for stage IVA and 33 months for stage IVB). Of the 10 variables tested, four (stage IV, age > 60 years, large-cell transformation, and increased lactate dehydrogenase) were independent prognostic markers for a worse survival. Combining these four factors in a prognostic index model identified the following three risk groups across stages with significantly different 5-year survival rates: low risk (68%), intermediate risk (44%), and high risk (28%). Conclusion To our knowledge, this study includes the largest cohort of patients with advanced-stage MF/SS and

  9. HEDR modeling approach: Revision 1

    International Nuclear Information System (INIS)

    Shipler, D.B.; Napier, B.A.

    1994-05-01

    This report is a revision of the previous Hanford Environmental Dose Reconstruction (HEDR) Project modeling approach report. This revised report describes the methods used in performing scoping studies and estimating final radiation doses to real and representative individuals who lived in the vicinity of the Hanford Site. The scoping studies and dose estimates pertain to various environmental pathways during various periods of time. The original report discussed the concepts under consideration in 1991. The methods for estimating dose have been refined as understanding of existing data, the scope of pathways, and the magnitudes of dose estimates were evaluated through scoping studies

  10. Implicit coupling of turbulent diffusion with chemical reaction mechanisms for prognostic atmospheric dispersion models

    Energy Technology Data Exchange (ETDEWEB)

    Berlowitz, D.R.

    1996-11-01

    In the last few decades the negative impact by humans on the thin atmospheric layer enveloping the earth, the basis for life on this planet, has increased steadily. In order to halt, or at least slow down this development, the knowledge and study of these anthropogenic influence has to be increased and possible remedies have to be suggested. An important tool for these studies are computer models. With their help the atmospheric system can be approximated and the various processes, which have led to the current situation can be quantified. They also serve as an instrument to assess short or medium term strategies to reduce this human impact. However, to assure efficiency as well as accuracy, a careful analysis of the numerous processes involved in the dispersion of pollutants in the atmosphere is called for. This should help to concentrate on the essentials and also prevent excessive usage of sometimes scarce computing resources. The basis of the presented work is the EUMAC Zooming Model (ETM), and particularly the component calculating the dispersion of pollutants in the atmosphere, the model MARS. The model has two main parts: an explicit solver, where the advection and the horizontal diffusion of pollutants are calculated, and an implicit solution mechanism, allowing the joint computation of the change of concentration due to chemical reactions, coupled with the respective influence of the vertical diffusion of the species. The aim of this thesis is to determine particularly the influence of the horizontal components of the turbulent diffusion on the existing implicit solver of the model. Suggestions for a more comprehensive inclusion of the full three dimensional diffusion operator in the implicit solver are made. This is achieved by an appropriate operator splitting. A selection of numerical approaches to tighten the coupling of the diffusion processes with the calculation of the applied chemical reaction mechanisms are examined. (author) figs., tabs., refs.

  11. Performance and evaluation of a coupled prognostic model TAPM over a mountainous complex terrain industrial area

    Science.gov (United States)

    Matthaios, Vasileios N.; Triantafyllou, Athanasios G.; Albanis, Triantafyllos A.; Sakkas, Vasileios; Garas, Stelios

    2018-05-01

    Atmospheric modeling is considered an important tool with several applications such as prediction of air pollution levels, air quality management, and environmental impact assessment studies. Therefore, evaluation studies must be continuously made, in order to improve the accuracy and the approaches of the air quality models. In the present work, an attempt is made to examine the air pollution model (TAPM) efficiency in simulating the surface meteorology, as well as the SO2 concentrations in a mountainous complex terrain industrial area. Three configurations under different circumstances, firstly with default datasets, secondly with data assimilation, and thirdly with updated land use, ran in order to investigate the surface meteorology for a 3-year period (2009-2011) and one configuration applied to predict SO2 concentration levels for the year of 2011.The modeled hourly averaged meteorological and SO2 concentration values were statistically compared with those from five monitoring stations across the domain to evaluate the model's performance. Statistical measures showed that the surface temperature and relative humidity are predicted well in all three simulations, with index of agreement (IOA) higher than 0.94 and 0.70 correspondingly, in all monitoring sites, while an overprediction of extreme low temperature values is noted, with mountain altitudes to have an important role. However, the results also showed that the model's performance is related to the configuration regarding the wind. TAPM default dataset predicted better the wind variables in the center of the simulation than in the boundaries, while improvement in the boundary horizontal winds implied the performance of TAPM with updated land use. TAPM assimilation predicted the wind variables fairly good in the whole domain with IOA higher than 0.83 for the wind speed and higher than 0.85 for the horizontal wind components. Finally, the SO2 concentrations were assessed by the model with IOA varied from 0

  12. The differentiation and prognostic implication of the solitary colonic polyp and the polyposis syndromes: A radiologic, histologic, and pathologic approach

    International Nuclear Information System (INIS)

    Olmsted, W.W.; Lichtenstein, J.E.

    1987-01-01

    The differential diagnosis of the solitary colonic polyp and the implications and prognostic significance of the solitary colonic polyp and the polyposis syndromes are frequently confusing because of imprecise and overlapping terminology. Such confusion may lead to misdiagnosis or overdiagnosis and improper patient treatment and surveillance. In the first part of this course, basic terms are defined to acquaint all participants with current common ground. The most frequently occurring solitary polyps (e.g., the colonic adenoma, hyperplastic polyp, Peutz-Jeghers hamartoma, juvenile hamartoma, and inflammatory polyp) are illustrated in detail with radiologic-histologic-pathologic correlation. The prognostic significance of each type of lesion and a scheme for proper colonic surveillance is discussed. In the second part of the session, there is a thorough discussion of multiple colonic polyps and the polyposis syndromes. Radiologic-pathologic correlation are used to illustrate these entities, and therapeutic and diagnostic implications are thoroughly covered. The differential diagnosis of the polyposis syndromes, including lymphoid abnormalities, pneumatosis intestinalis, and colitis cystica profunda, are mentioned. The participant should expect to gain a full understanding of the solitary and multiple colonic polyp states and algorithms for prognosis and treatment

  13. Integrating Tenascin-C protein expression and 1q25 copy number status in pediatric intracranial ependymoma prognostication: A new model for risk stratification.

    Science.gov (United States)

    Andreiuolo, Felipe; Le Teuff, Gwénaël; Bayar, Mohamed Amine; Kilday, John-Paul; Pietsch, Torsten; von Bueren, André O; Witt, Hendrik; Korshunov, Andrey; Modena, Piergiorgio; Pfister, Stefan M; Pagès, Mélanie; Castel, David; Giangaspero, Felice; Chimelli, Leila; Varlet, Pascale; Rutkowski, Stefan; Frappaz, Didier; Massimino, Maura; Grundy, Richard; Grill, Jacques

    2017-01-01

    Despite multimodal therapy, prognosis of pediatric intracranial ependymomas remains poor with a 5-year survival rate below 70% and frequent late deaths. This multicentric European study evaluated putative prognostic biomarkers. Tenascin-C (TNC) immunohistochemical expression and copy number status of 1q25 were retained for a pooled analysis of 5 independent cohorts. The prognostic value of TNC and 1q25 on the overall survival (OS) was assessed using a Cox model adjusted to age at diagnosis, tumor location, WHO grade, extent of resection, radiotherapy and stratified by cohort. Stratification on a predictor that did not satisfy the proportional hazards assumption was considered. Model performance was evaluated and an internal-external cross validation was performed. Among complete cases with 5-year median follow-up (n = 470; 131 deaths), TNC and 1q25 gain were significantly associated with age at diagnosis and posterior fossa tumor location. 1q25 status added independent prognostic value for death beyond the classical variables with a hazard ratio (HR) = 2.19 95%CI = [1.29; 3.76] (p = 0.004), while TNC prognostic relation was tumor location-dependent with HR = 2.19 95%CI = [1.29; 3.76] (p = 0.004) in posterior fossa and HR = 0.64 [0.28; 1.48] (p = 0.295) in supratentorial (interaction p value = 0.015). The derived prognostic score identified 3 different robust risk groups. The omission of upfront RT was not associated with OS for good and intermediate prognostic groups while the absence of upfront RT was negatively associated with OS in the poor risk group. Integrated TNC expression and 1q25 status are useful to better stratify patients and to eventually adapt treatment regimens in pediatric intracranial ependymoma.

  14. Integrating Tenascin-C protein expression and 1q25 copy number status in pediatric intracranial ependymoma prognostication: A new model for risk stratification.

    Directory of Open Access Journals (Sweden)

    Felipe Andreiuolo

    Full Text Available Despite multimodal therapy, prognosis of pediatric intracranial ependymomas remains poor with a 5-year survival rate below 70% and frequent late deaths.This multicentric European study evaluated putative prognostic biomarkers. Tenascin-C (TNC immunohistochemical expression and copy number status of 1q25 were retained for a pooled analysis of 5 independent cohorts. The prognostic value of TNC and 1q25 on the overall survival (OS was assessed using a Cox model adjusted to age at diagnosis, tumor location, WHO grade, extent of resection, radiotherapy and stratified by cohort. Stratification on a predictor that did not satisfy the proportional hazards assumption was considered. Model performance was evaluated and an internal-external cross validation was performed.Among complete cases with 5-year median follow-up (n = 470; 131 deaths, TNC and 1q25 gain were significantly associated with age at diagnosis and posterior fossa tumor location. 1q25 status added independent prognostic value for death beyond the classical variables with a hazard ratio (HR = 2.19 95%CI = [1.29; 3.76] (p = 0.004, while TNC prognostic relation was tumor location-dependent with HR = 2.19 95%CI = [1.29; 3.76] (p = 0.004 in posterior fossa and HR = 0.64 [0.28; 1.48] (p = 0.295 in supratentorial (interaction p value = 0.015. The derived prognostic score identified 3 different robust risk groups. The omission of upfront RT was not associated with OS for good and intermediate prognostic groups while the absence of upfront RT was negatively associated with OS in the poor risk group.Integrated TNC expression and 1q25 status are useful to better stratify patients and to eventually adapt treatment regimens in pediatric intracranial ependymoma.

  15. 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.

  16. Mucins as diagnostic and prognostic biomarkers in a fish-parasite model: transcriptional and functional analysis.

    Directory of Open Access Journals (Sweden)

    Jaume Pérez-Sánchez

    Full Text Available Mucins are O-glycosylated glycoproteins present on the apex of all wet-surfaced epithelia with a well-defined expression pattern, which is disrupted in response to a wide range of injuries or challenges. The aim of this study was to identify mucin gene sequences of gilthead sea bream (GSB, to determine its pattern of distribution in fish tissues and to analyse their transcriptional regulation by dietary and pathogenic factors. Exhaustive search of fish mucins was done in GSB after de novo assembly of next-generation sequencing data hosted in the IATS transcriptome database (www.nutrigroup-iats.org/seabreamdb. Six sequences, three categorized as putative membrane-bound mucins and three putative secreted-gel forming mucins, were identified. The transcriptional tissue screening revealed that Muc18 was the predominant mucin in skin, gills and stomach of GSB. In contrast, Muc19 was mostly found in the oesophagus and Muc13 was along the entire intestinal tract, although the posterior intestine exhibited a differential pattern with a high expression of an isoform that does not share a clear orthologous in mammals. This mucin was annotated as intestinal mucin (I-Muc. Its RNA expression was highly regulated by the nutritional background, whereas the other mucins, including Muc2 and Muc2-like, were expressed more constitutively and did not respond to high replacement of fish oil (FO by vegetable oils (VO in plant protein-based diets. After challenge with the intestinal parasite Enteromyxum leei, the expression of a number of mucins was decreased mainly in the posterior intestine of infected fish. But, interestingly, the highest down-regulation was observed for the I-Muc. Overall, the magnitude of the changes reflected the intensity and progression of the infection, making mucins and I-Muc, in particular, reliable markers of prognostic and diagnostic value of fish intestinal health.

  17. Gene Expression of the EGF System-a Prognostic Model in Non-Small Cell Lung Cancer Patients Without Activating EGFR Mutations

    DEFF Research Database (Denmark)

    Sandfeld-Paulsen, Birgitte; Folkersen, Birgitte Holst; Rasmussen, Torben Riis

    2016-01-01

    OBJECTIVES: Contradicting results have been demonstrated for the expression of the epidermal growth factor receptor (EGFR) as a prognostic marker in non-small cell lung cancer (NSCLC). The complexity of the EGF system with four interacting receptors and more than a dozen activating ligands is a l.......17-6.47], P model that takes the complexity of the EGF system into account and shows that this model is a strong prognostic marker in NSCLC patients.......OBJECTIVES: Contradicting results have been demonstrated for the expression of the epidermal growth factor receptor (EGFR) as a prognostic marker in non-small cell lung cancer (NSCLC). The complexity of the EGF system with four interacting receptors and more than a dozen activating ligands...... is a likely explanation. The aim of this study is to demonstrate that the combined network of receptors and ligands from the EGF system is a prognostic marker. MATERIAL AND METHODS: Gene expression of the receptors EGFR, HER2, HER3, HER4, and the ligands AREG, HB-EGF, EPI, TGF-α, and EGF was measured...

  18. A Bayesian approach to model uncertainty

    International Nuclear Information System (INIS)

    Buslik, A.

    1994-01-01

    A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given

  19. A prognostic model of triple-negative breast cancer based on miR-27b-3p and node status.

    Directory of Open Access Journals (Sweden)

    Songjie Shen

    Full Text Available Triple-negative breast cancer (TNBC is an aggressive but heterogeneous subtype of breast cancer. This study aimed to identify and validate a prognostic signature for TNBC patients to improve prognostic capability and to guide individualized treatment.We retrospectively analyzed the prognostic performance of clinicopathological characteristics and miRNAs in a training set of 58 patients with invasive ductal TNBC diagnosed between 2002 and 2012. A prediction model was developed based on independent clinicopathological and miRNA covariates. The prognostic value of the model was further validated in a separate set of 41 TNBC patients diagnosed between 2007 and 2008.Only lymph node status was marginally significantly associated with poor prognosis of TNBC (P = 0.054, whereas other clinicopathological factors, including age, tumor size, histological grade, lymphovascular invasion, P53 status, Ki-67 index, and type of surgery, were not. The expression levels of miR-27b-3p, miR-107, and miR-103a-3p were significantly elevated in the metastatic group compared with the disease-free group (P value: 0.008, 0.005, and 0.050, respectively. The Cox proportional hazards regression analysis revealed that lymph node status and miR-27b-3p were independent predictors of poor prognosis (P value: 0.012 and 0.027, respectively. A logistic regression model was developed based on these two independent covariates, and the prognostic value of the model was subsequently confirmed in a separate validation set. The two different risk groups, which were stratified according to the model, showed significant differences in the rates of distant metastasis and breast cancer-related death not only in the training set (P value: 0.001 and 0.040, respectively but also in the validation set (P value: 0.013 and 0.012, respectively.This model based on miRNA and node status covariates may be used to stratify TNBC patients into different prognostic subgroups for potentially

  20. System Behavior Models: A Survey of Approaches

    Science.gov (United States)

    2016-06-01

    OF FIGURES Spiral Model .................................................................................................3 Figure 1. Approaches in... spiral model was chosen for researching and structuring this thesis, shown in Figure 1. This approach allowed multiple iterations of source material...applications and refining through iteration. 3 Spiral Model Figure 1. D. SCOPE The research is limited to a literature review, limited

  1. A state-space-based prognostics model for lithium-ion battery degradation

    International Nuclear Information System (INIS)

    Xu, Xin; Chen, Nan

    2017-01-01

    This paper proposes to analyze the degradation of lithium-ion batteries with the sequentially observed discharging profiles. A general state-space model is developed in which the observation model is used to approximate the discharging profile of each cycle, the corresponding parameter vector is treated as the hidden state, and the state-transition model is used to track the evolution of the parameter vector as the battery ages. The EM and EKF algorithms are adopted to estimate and update the model parameters and states jointly. Based on this model, we construct prediction on the end of discharge times for unobserved cycles and the remaining useful cycles before the battery failure. The effectiveness of the proposed model is demonstrated using a real lithium-ion battery degradation data set. - Highlights: • Unifying model for Li-Ion battery SOC and SOH estimation. • Extended Kalman filter based efficient inference algorithm. • Using voltage curves in discharging to have wide validity.

  2. Using Enthalpy as a Prognostic Variable in Atmospheric Modelling with Variable Composition

    Science.gov (United States)

    2016-04-14

    Sela, personal communication, 2005). These terms are also routinely neglected in models. In models with a limited number of gaseous tracers, such as...so-called energy- exchange term (second term on the left- hand side) in Equation (5). The finite-difference schemes in existing atmospheric models have...equation for the sum of enthalpy and kinetic energy of horizontal motion is solved. This eliminates the energy- exchange term and automatically

  3. Learning Actions Models: Qualitative Approach

    DEFF Research Database (Denmark)

    Bolander, Thomas; Gierasimczuk, Nina

    2015-01-01

    In dynamic epistemic logic, actions are described using action models. In this paper we introduce a framework for studying learnability of action models from observations. We present first results concerning propositional action models. First we check two basic learnability criteria: finite ident...

  4. Development and validation of a prognostic model incorporating texture analysis derived from standardised segmentation of PET in patients with oesophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Foley, Kieran G. [Cardiff University, Division of Cancer and Genetics, Cardiff (United Kingdom); Hills, Robert K. [Cardiff University, Haematology Clinical Trials Unit, Cardiff (United Kingdom); Berthon, Beatrice; Marshall, Christopher [Wales Research and Diagnostic PET Imaging Centre, Cardiff (United Kingdom); Parkinson, Craig; Spezi, Emiliano [Cardiff University, School of Engineering, Cardiff (United Kingdom); Lewis, Wyn G. [University Hospital of Wales, Department of Upper GI Surgery, Cardiff (United Kingdom); Crosby, Tom D.L. [Department of Oncology, Velindre Cancer Centre, Cardiff (United Kingdom); Roberts, Stuart Ashley [University Hospital of Wales, Department of Clinical Radiology, Cardiff (United Kingdom)

    2018-01-15

    This retrospective cohort study developed a prognostic model incorporating PET texture analysis in patients with oesophageal cancer (OC). Internal validation of the model was performed. Consecutive OC patients (n = 403) were chronologically separated into development (n = 302, September 2010-September 2014, median age = 67.0, males = 227, adenocarcinomas = 237) and validation cohorts (n = 101, September 2014-July 2015, median age = 69.0, males = 78, adenocarcinomas = 79). Texture metrics were obtained using a machine-learning algorithm for automatic PET segmentation. A Cox regression model including age, radiological stage, treatment and 16 texture metrics was developed. Patients were stratified into quartiles according to a prognostic score derived from the model. A p-value < 0.05 was considered statistically significant. Primary outcome was overall survival (OS). Six variables were significantly and independently associated with OS: age [HR =1.02 (95% CI 1.01-1.04), p < 0.001], radiological stage [1.49 (1.20-1.84), p < 0.001], treatment [0.34 (0.24-0.47), p < 0.001], log(TLG) [5.74 (1.44-22.83), p = 0.013], log(Histogram Energy) [0.27 (0.10-0.74), p = 0.011] and Histogram Kurtosis [1.22 (1.04-1.44), p = 0.017]. The prognostic score demonstrated significant differences in OS between quartiles in both the development (X{sup 2} 143.14, df 3, p < 0.001) and validation cohorts (X{sup 2} 20.621, df 3, p < 0.001). This prognostic model can risk stratify patients and demonstrates the additional benefit of PET texture analysis in OC staging. (orig.)

  5. Integrating models with data in ecology and palaeoecology: advances towards a model-data fusion approach.

    Science.gov (United States)

    Peng, Changhui; Guiot, Joel; Wu, Haibin; Jiang, Hong; Luo, Yiqi

    2011-05-01

    It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process-based ecological models and data in cohesive, systematic ways. Model-data fusion (MDF) is an emerging area of research in ecology and palaeoecology. It provides a new quantitative approach that offers a high level of empirical constraint over model predictions based on observations using inverse modelling and data assimilation (DA) techniques. Increasing demands to integrate model and data methods in the past decade has led to MDF utilization in palaeoecology, ecology and earth system sciences. This paper reviews key features and principles of MDF and highlights different approaches with regards to DA. After providing a critical evaluation of the numerous benefits of MDF and its current applications in palaeoecology (i.e., palaeoclimatic reconstruction, palaeovegetation and palaeocarbon storage) and ecology (i.e. parameter and uncertainty estimation, model error identification, remote sensing and ecological forecasting), the paper discusses method limitations, current challenges and future research direction. In the ongoing data-rich era of today's world, MDF could become an important diagnostic and prognostic tool in which to improve our understanding of ecological processes while testing ecological theory and hypotheses and forecasting changes in ecosystem structure, function and services. © 2011 Blackwell Publishing Ltd/CNRS.

  6. Structural Health and Prognostics Management for Offshore Wind Turbines: Sensitivity Analysis of Rotor Fault and Blade Damage with O&M Cost Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Myrent, Noah J. [Vanderbilt Univ., Nashville, TN (United States). Lab. for Systems Integrity and Reliability; Barrett, Natalie C. [Vanderbilt Univ., Nashville, TN (United States). Lab. for Systems Integrity and Reliability; Adams, Douglas E. [Vanderbilt Univ., Nashville, TN (United States). Lab. for Systems Integrity and Reliability; Griffith, Daniel Todd [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Wind Energy Technology Dept.

    2014-07-01

    Operations and maintenance costs for offshore wind plants are significantly higher than the current costs for land-based (onshore) wind plants. One way to reduce these costs would be to implement a structural health and prognostic management (SHPM) system as part of a condition based maintenance paradigm with smart load management and utilize a state-based cost model to assess the economics associated with use of the SHPM system. To facilitate the development of such a system a multi-scale modeling and simulation approach developed in prior work is used to identify how the underlying physics of the system are affected by the presence of damage and faults, and how these changes manifest themselves in the operational response of a full turbine. This methodology was used to investigate two case studies: (1) the effects of rotor imbalance due to pitch error (aerodynamic imbalance) and mass imbalance and (2) disbond of the shear web; both on a 5-MW offshore wind turbine in the present report. Sensitivity analyses were carried out for the detection strategies of rotor imbalance and shear web disbond developed in prior work by evaluating the robustness of key measurement parameters in the presence of varying wind speeds, horizontal shear, and turbulence. Detection strategies were refined for these fault mechanisms and probabilities of detection were calculated. For all three fault mechanisms, the probability of detection was 96% or higher for the optimized wind speed ranges of the laminar, 30% horizontal shear, and 60% horizontal shear wind profiles. The revised cost model provided insight into the estimated savings in operations and maintenance costs as they relate to the characteristics of the SHPM system. The integration of the health monitoring information and O&M cost versus damage/fault severity information provides the initial steps to identify processes to reduce operations and maintenance costs for an offshore wind farm while increasing turbine availability

  7. Validation of Model-Based Prognostics for Pneumatic Valves in a Demonstration Testbed

    Science.gov (United States)

    2014-10-02

    predict end of life ( EOL ) and remaining useful life (RUL). The approach still follows the general estimation-prediction framework devel- oped in the...atmosphere, with linearly increasing leak area. kA2leak = Cleak (16) We define valve end of life ( EOL ) through open/close time limits of the valves, as in...represents end of life ( EOL ), and ∆kE represents remaining useful life (RUL). For valves, timing requirements are provided that de- fine the maximum

  8. Model Updating and Uncertainty Management for Aircraft Prognostic Systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal addresses the integration of physics-based damage propagation models with diagnostic measures of current state of health in a mathematically rigorous...

  9. Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals

    DEFF Research Database (Denmark)

    Smith, Todd; Muller, David C; Moons, Karel G M

    2018-01-01

    in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted......-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained....

  10. EVALUATION OF PROGNOSTIC FACTORS IN QUALITY OF LIFE OF PATIENTS WITH ADOLESCENT IDIOPATHIC SCOLIOSIS UNDERGOING SPINAL FUSION BY THE POSTERIOR APPROACH

    Directory of Open Access Journals (Sweden)

    FELIPE DE MORAES POMAR

    Full Text Available ABSTRACT Objective: To evaluate the prognostic factors in the treatment of patients diagnosed with adolescent idiopathic scoliosis undergoing spinal fusion by the posterior approach. Methods: The study included 48 patients with idiopathic adolescent scoliosis (43 females and 5 males who underwent spinal fusion by the posterior approach, with an average age at diagnosis of 12 years, and clinical signs of Risser between 3 and 4 at the time of surgery. Clinical and radiographic measurements were performed, the participants answered the SRS-30 questionnaire, and the analysis of the medical record data was performed in two occasions during the preoperative period and at the end of two years of follow-up. Results: All satisfaction measures showed statistically significant change after the procedure (p<0.05 with respect to the radiographic characteristics, except for the lumbar apical vertebral translation (p=0.540 and Cobb L1-L5 (p=0.225. Conclusion: In general, it was found that patients who received surgical treatment were more satisfied with their appearance than those who underwent conservative treatment.

  11. Global energy modeling - A biophysical approach

    Energy Technology Data Exchange (ETDEWEB)

    Dale, Michael

    2010-09-15

    This paper contrasts the standard economic approach to energy modelling with energy models using a biophysical approach. Neither of these approaches includes changing energy-returns-on-investment (EROI) due to declining resource quality or the capital intensive nature of renewable energy sources. Both of these factors will become increasingly important in the future. An extension to the biophysical approach is outlined which encompasses a dynamic EROI function that explicitly incorporates technological learning. The model is used to explore several scenarios of long-term future energy supply especially concerning the global transition to renewable energy sources in the quest for a sustainable energy system.

  12. Prognostic model for long-term survival of locally advanced non-small-cell lung cancer patients after neoadjuvant radiochemotherapy and resection integrating clinical and histopathologic factors

    International Nuclear Information System (INIS)

    Pöttgen, Christoph; Stuschke, Martin; Graupner, Britta; Theegarten, Dirk; Gauler, Thomas; Jendrossek, Verena; Freitag, Lutz; Jawad, Jehad Abu; Gkika, Eleni; Wohlschlaeger, Jeremias; Welter, Stefan; Hoiczyk, Matthias; Schuler, Martin; Stamatis, Georgios; Eberhardt, Wilfried

    2015-01-01

    Outcome of consecutive patients with locally advanced non-small cell lung cancer and histopathologically proven mediastional lymph node metastases treated with induction chemotherapy, neoadjuvant radiochemotherapy and thoracotomy at the West German Cancer Center between 08/2000 and 06/2012 was analysed. A clinico-pathological prognostic model for survival was built including partial or complete response according to computed tomography imaging (CT) as clinical parameters as well as pathologic complete remission (pCR) and mediastinal nodal clearance (MNC) as histopathologic factors. Proportional hazard analysis (PHA) and recursive partitioning analysis (RPA) were used to identify prognostic factors for survival. Long-term survival was defined as survival ≥ 36 months. A total of 157 patients were treated, median follow-up was 97 months. Among these patients, pCR and MNC were observed in 41 and 85 patients, respectively. Overall survival was 56 ± 4% and 36 ± 4% at 24 and 60 months, respectively. Sensitivities of pCR and MNC to detect long-term survivors were 38% and 61%, specificities were 84% and 52%, respectively. Multivariable survival analysis revealed pCR, cN3 category, and gender, as prognostic factors at a level of α < 0.05. Considering only preoperative available parameters, CT response became significant. Classifying patients with a predicted hazard above the median as high risk group and the remaining as low risk patients yielded better separation of the survival curves by the inclusion of histopathologic factors than by preoperative factors alone (p < 0.0001, log rank test). Using RPA, pCR was identified as the top prognostic factor above clinical factors (p = 0.0006). No long term survivors were observed in patients with cT3-4 cN3 tumors without pCR. pCR is the dominant histopathologic response parameter and improves prognostic classifiers, based on clinical parameters. The validated prognostic model can be used to estimate individual prognosis and

  13. A Discussion on Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

    Data.gov (United States)

    National Aeronautics and Space Administration — This article presented a discussion on uncertainty representation and management for model-based prog- nostics methodologies based on the Bayesian tracking framework...

  14. A Unified Approach to Modeling and Programming

    DEFF Research Database (Denmark)

    Madsen, Ole Lehrmann; Møller-Pedersen, Birger

    2010-01-01

    of this paper is to go back to the future and get inspiration from SIMULA and propose a unied approach. In addition to reintroducing the contributions of SIMULA and the Scandinavian approach to object-oriented programming, we do this by discussing a number of issues in modeling and programming and argue3 why we......SIMULA was a language for modeling and programming and provided a unied approach to modeling and programming in contrast to methodologies based on structured analysis and design. The current development seems to be going in the direction of separation of modeling and programming. The goal...

  15. Few promising multivariable prognostic models exist for recovery of people with non-specific neck pain in musculoskeletal primary care: a systematic review.

    Science.gov (United States)

    Wingbermühle, Roel W; van Trijffel, Emiel; Nelissen, Paul M; Koes, Bart; Verhagen, Arianne P

    2018-01-01

    Which multivariable prognostic model(s) for recovery in people with neck pain can be used in primary care? Systematic review of studies evaluating multivariable prognostic models. People with non-specific neck pain presenting at primary care. Baseline characteristics of the participants. Recovery measured as pain reduction, reduced disability, or perceived recovery at short-term and long-term follow-up. Fifty-three publications were included, of which 46 were derivation studies, four were validation studies, and three concerned combined studies. The derivation studies presented 99 multivariate models, all of which were at high risk of bias. Three externally validated models generated usable models in low risk of bias studies. One predicted recovery in non-specific neck pain, while two concerned participants with whiplash-associated disorders (WAD). Discriminative ability of the non-specific neck pain model was area under the curve (AUC) 0.65 (95% CI 0.59 to 0.71). For the first WAD model, discriminative ability was AUC 0.85 (95% CI 0.79 to 0.91). For the second WAD model, specificity was 99% (95% CI 93 to 100) and sensitivity was 44% (95% CI 23 to 65) for prediction of non-recovery, and 86% (95% CI 73 to 94) and 55% (95% CI 41 to 69) for prediction of recovery, respectively. Initial Neck Disability Index scores and age were identified as consistent prognostic factors in these three models. Three externally validated models were found to be usable and to have low risk of bias, of which two showed acceptable discriminative properties for predicting recovery in people with neck pain. These three models need further validation and evaluation of their clinical impact before their broad clinical use can be advocated. PROSPERO CRD42016042204. [Wingbermühle RW, van Trijffel E, Nelissen PM, Koes B, Verhagen AP (2018) Few promising multivariable prognostic models exist for recovery of people with non-specific neck pain in musculoskeletal primary care: a systematic review

  16. Surface Prognostic Charts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Surface Prognostic Charts are historical surface prognostic (forecast) charts created by the United States Weather Bureau. They include fronts, isobars, cloud, and...

  17. Treatment outcome and prognostic factor analysis in transplant-eligible Chinese myeloma patients receiving bortezomib-based induction regimens including the staged approach, PAD or VTD

    Directory of Open Access Journals (Sweden)

    Chim Chor

    2012-06-01

    Full Text Available Abstract Background We have reported promising outcomes using a staged approach, in which bortezomib/thalidomide/dexamethasone was used only in 14 patients with suboptimal response to VAD (vincristine/adriamycin/dexamethasone before autologous stem cell transplantation (ASCT. Here we compared the outcomes of the staged approach with frontline PAD (bortezomib/doxorubicin/dexamethasone or VTD (bortezomib/thalidomide/dexamethasone induction, and analysed prognostic factors for outcome. Patients and methods Ninety-one transplant-eligible Chinese patients received three induction regimens prior to ASCT [staged approach (N = 25, PAD (N = 31, VTD (N = 35]. and received thalidomide maintenance for 2 years post-ASCT. Results 43 (47.3% patients had International Staging System (ISS III disease. By an intention-to-treat analysis, the overall CR/nCR rate were 37.4% post-induction, and 62.6% post-ASCT. Five-year overall (OS and event-free (EFS survivals were 66% and 45.1%. There was no difference of the post-induction CR/nCR rate, EFS or OS between patients induced by these three regimens. Moreover, ISS III disease did not affect CR/nCR rates. Multivariate analysis showed that ISS and post-ASCT CR/nCR impacted OS while ISS and post-induction CR/nCR impacted EFS. Conclusions These three induction regimens produced comparable and favorable outcomes in myeloma. The unfavorable outcome of ISS stage III persisted despite upfront/early use of bortezomib. CR/nCR predicted favorable survivals.

  18. Multiple Model Approaches to Modelling and Control,

    DEFF Research Database (Denmark)

    on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating......, and allows direct incorporation of high-level and qualitative plant knowledge into themodel. These advantages have proven to be very appealing for industrial applications, and the practical, intuitively appealing nature of the framework isdemonstrated in chapters describing applications of local methods...... to problems in the process industries, biomedical applications and autonomoussystems. The successful application of the ideas to demanding problems is already encouraging, but creative development of the basic framework isneeded to better allow the integration of human knowledge with automated learning...

  19. Geometrical approach to fluid models

    International Nuclear Information System (INIS)

    Kuvshinov, B.N.; Schep, T.J.

    1997-01-01

    Differential geometry based upon the Cartan calculus of differential forms is applied to investigate invariant properties of equations that describe the motion of continuous media. The main feature of this approach is that physical quantities are treated as geometrical objects. The geometrical notion of invariance is introduced in terms of Lie derivatives and a general procedure for the construction of local and integral fluid invariants is presented. The solutions of the equations for invariant fields can be written in terms of Lagrange variables. A generalization of the Hamiltonian formalism for finite-dimensional systems to continuous media is proposed. Analogously to finite-dimensional systems, Hamiltonian fluids are introduced as systems that annihilate an exact two-form. It is shown that Euler and ideal, charged fluids satisfy this local definition of a Hamiltonian structure. A new class of scalar invariants of Hamiltonian fluids is constructed that generalizes the invariants that are related with gauge transformations and with symmetries (Noether). copyright 1997 American Institute of Physics

  20. Exploring Stage I non-small-cell lung cancer: development of a prognostic model predicting 5-year survival after surgical resection†.

    Science.gov (United States)

    Guerrera, Francesco; Errico, Luca; Evangelista, Andrea; Filosso, Pier Luigi; Ruffini, Enrico; Lisi, Elena; Bora, Giulia; Asteggiano, Elena; Olivetti, Stefania; Lausi, Paolo; Ardissone, Francesco; Oliaro, Alberto

    2015-06-01

    Despite impressive results in diagnosis and treatment of non-small-cell lung cancer (NSCLC), more than 30% of patients with Stage I NSCLC die within 5 years after surgical treatment. Identification of prognostic factors to select patients with a poor prognosis and development of tailored treatment strategies are then advisable. The aim of our study was to design a model able to define prognosis in patients with Stage I NSCLC, submitted to surgery with curative intent. A retrospective analysis of two surgical registries was performed. Predictors of survival were investigated using the Cox model with shared frailty (accounting for the within-centre correlation). Candidate predictors were: age, gender, smoking habit, morbidity, previous malignancy, Eastern Cooperative Oncology Group performance status, clinical N stage, maximum standardized uptake value (SUV(max)), forced expiratory volume in 1 s, carbon monoxide lung diffusion capacity (DLCO), extent of surgical resection, systematic lymphadenectomy, vascular invasion, pathological T stage, histology and histological grading. The final model included predictors with P model demonstrated that mortality was significantly associated with age, male sex, presence of cardiac comorbidities, DLCO (%), SUV(max), systematic nodal dissection, presence of microscopic vascular invasion, pTNM stage and histological grading. The final model showed a fair discrimination ability (C-statistic = 0.69): the calibration of the model indicated a good agreement between observed and predicted survival. We designed an effective prognostic model based on clinical, pathological and surgical covariates. Our preliminary results need to be refined and validated in a larger patient population, in order to provide an easy-to-use prognostic tool for Stage I NSCLC patients. © The Author 2014. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

  1. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  2. Development and analysis of prognostic equations for mesoscale kinetic energy and mesoscale (subgrid scale) fluxes for large-scale atmospheric models

    Science.gov (United States)

    Avissar, Roni; Chen, Fei

    1993-01-01

    Generated by landscape discontinuities (e.g., sea breezes) mesoscale circulation processes are not represented in large-scale atmospheric models (e.g., general circulation models), which have an inappropiate grid-scale resolution. With the assumption that atmospheric variables can be separated into large scale, mesoscale, and turbulent scale, a set of prognostic equations applicable in large-scale atmospheric models for momentum, temperature, moisture, and any other gaseous or aerosol material, which includes both mesoscale and turbulent fluxes is developed. Prognostic equations are also developed for these mesoscale fluxes, which indicate a closure problem and, therefore, require a parameterization. For this purpose, the mean mesoscale kinetic energy (MKE) per unit of mass is used, defined as E-tilde = 0.5 (the mean value of u'(sub i exp 2), where u'(sub i) represents the three Cartesian components of a mesoscale circulation (the angle bracket symbol is the grid-scale, horizontal averaging operator in the large-scale model, and a tilde indicates a corresponding large-scale mean value). A prognostic equation is developed for E-tilde, and an analysis of the different terms of this equation indicates that the mesoscale vertical heat flux, the mesoscale pressure correlation, and the interaction between turbulence and mesoscale perturbations are the major terms that affect the time tendency of E-tilde. A-state-of-the-art mesoscale atmospheric model is used to investigate the relationship between MKE, landscape discontinuities (as characterized by the spatial distribution of heat fluxes at the earth's surface), and mesoscale sensible and latent heat fluxes in the atmosphere. MKE is compared with turbulence kinetic energy to illustrate the importance of mesoscale processes as compared to turbulent processes. This analysis emphasizes the potential use of MKE to bridge between landscape discontinuities and mesoscale fluxes and, therefore, to parameterize mesoscale fluxes

  3. Distributed simulation a model driven engineering approach

    CERN Document Server

    Topçu, Okan; Oğuztüzün, Halit; Yilmaz, Levent

    2016-01-01

    Backed by substantive case studies, the novel approach to software engineering for distributed simulation outlined in this text demonstrates the potent synergies between model-driven techniques, simulation, intelligent agents, and computer systems development.

  4. Service creation: a model-based approach

    NARCIS (Netherlands)

    Quartel, Dick; van Sinderen, Marten J.; Ferreira Pires, Luis

    1999-01-01

    This paper presents a model-based approach to support service creation. In this approach, services are assumed to be created from (available) software components. The creation process may involve multiple design steps in which the requested service is repeatedly decomposed into more detailed

  5. Models of galaxies - The modal approach

    International Nuclear Information System (INIS)

    Lin, C.C.; Lowe, S.A.

    1990-01-01

    The general viability of the modal approach to the spiral structure in normal spirals and the barlike structure in certain barred spirals is discussed. The usefulness of the modal approach in the construction of models of such galaxies is examined, emphasizing the adoption of a model appropriate to observational data for both the spiral structure of a galaxy and its basic mass distribution. 44 refs

  6. Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

    Energy Technology Data Exchange (ETDEWEB)

    Louie, Alexander V., E-mail: Dr.alexlouie@gmail.com [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands); Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, Massachusetts (United States); Haasbeek, Cornelis J.A. [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands); Mokhles, Sahar [Department of Cardio-Thoracic Surgery, Erasmus University Medical Center, Rotterdam (Netherlands); Rodrigues, George B. [Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Stephans, Kevin L. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Lagerwaard, Frank J. [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands); Palma, David A. [Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Videtic, Gregory M.M. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Warner, Andrew [Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario (Canada); Takkenberg, Johanna J.M. [Department of Cardio-Thoracic Surgery, Erasmus University Medical Center, Rotterdam (Netherlands); Reddy, Chandana A. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Maat, Alex P.W.M. [Department of Cardio-Thoracic Surgery, Erasmus University Medical Center, Rotterdam (Netherlands); Woody, Neil M. [Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic, Cleveland, Ohio (United States); Slotman, Ben J.; Senan, Suresh [Department of Radiation Oncology, VU University Medical Center, Amsterdam (Netherlands)

    2015-09-01

    Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogram for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.

  7. Hearing preservation in retrosigmoid approach of small vestibular schwannomas: prognostic value of the degree of internal auditory canal filling.

    Science.gov (United States)

    Tringali, Stéphane; Ferber-Viart, Chantal; Fuchsmann, Carine; Buiret, Guillaume; Zaouche, Sandra; Dubreuil, Christian

    2010-12-01

    To assess the contribution of preoperative radiologic appearance of vestibular schwannoma (VS) on the magnetic resonance imaging in constructive interference in steady-state sequences and demonstrate if the degree of the internal auditory canal (IAC) filling is correlated with hearing and facial preservation. A group of 278 patients who underwent VS surgery in a tertiary referral center. Retrosigmoid approach surgery. Patients were classified in 4 groups according to the percentage of IAC filling on the preoperative magnetic resonance imaging as Group IAC 1(IAC empty or filled filled from 25% to 50% with free fundus), Group IAC 3 (IAC filled from 50% to 75% with free fundus), and Group IAC 4 (complete filling of the IAC without fundus obliteration). A good correlation was observed between the IAC classification and the rate of hearing and facial preservation. The global rate of postoperative facial palsy was 10.4%. The global rate of hearing preservation in 213 patients with preoperative hearing class A and B was 40.8%. Regression analysis showed that the degree of lateral extension of the VS in the IAC was a strong predictor of hearing preservation ( p facial outcomes in selected patients with possible hearing preservation. In case of patient with small tumor and IAC empty or filled less than 75% and with free fundus, surgery is the treatment of choice for patients with serviceable hearing and the desire to retain it.

  8. Multiscale approach to equilibrating model polymer melts

    DEFF Research Database (Denmark)

    Svaneborg, Carsten; Ali Karimi-Varzaneh, Hossein; Hojdis, Nils

    2016-01-01

    We present an effective and simple multiscale method for equilibrating Kremer Grest model polymer melts of varying stiffness. In our approach, we progressively equilibrate the melt structure above the tube scale, inside the tube and finally at the monomeric scale. We make use of models designed...

  9. Application of various FLD modelling approaches

    Science.gov (United States)

    Banabic, D.; Aretz, H.; Paraianu, L.; Jurco, P.

    2005-07-01

    This paper focuses on a comparison between different modelling approaches to predict the forming limit diagram (FLD) for sheet metal forming under a linear strain path using the recently introduced orthotropic yield criterion BBC2003 (Banabic D et al 2005 Int. J. Plasticity 21 493-512). The FLD models considered here are a finite element based approach, the well known Marciniak-Kuczynski model, the modified maximum force criterion according to Hora et al (1996 Proc. Numisheet'96 Conf. (Dearborn/Michigan) pp 252-6), Swift's diffuse (Swift H W 1952 J. Mech. Phys. Solids 1 1-18) and Hill's classical localized necking approach (Hill R 1952 J. Mech. Phys. Solids 1 19-30). The FLD of an AA5182-O aluminium sheet alloy has been determined experimentally in order to quantify the predictive capabilities of the models mentioned above.

  10. Development and Validation of a Lifecycle-based Prognostics Architecture with Test Bed Validation

    Energy Technology Data Exchange (ETDEWEB)

    Hines, J. Wesley [Univ. of Tennessee, Knoxville, TN (United States); Upadhyaya, Belle [Univ. of Tennessee, Knoxville, TN (United States); Sharp, Michael [Univ. of Tennessee, Knoxville, TN (United States); Ramuhalli, Pradeep [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Jeffries, Brien [Univ. of Tennessee, Knoxville, TN (United States); Nam, Alan [Univ. of Tennessee, Knoxville, TN (United States); Strong, Eric [Univ. of Tennessee, Knoxville, TN (United States); Tong, Matthew [Univ. of Tennessee, Knoxville, TN (United States); Welz, Zachary [Univ. of Tennessee, Knoxville, TN (United States); Barbieri, Federico [Univ. of Tennessee, Knoxville, TN (United States); Langford, Seth [Univ. of Tennessee, Knoxville, TN (United States); Meinweiser, Gregory [Univ. of Tennessee, Knoxville, TN (United States); Weeks, Matthew [Univ. of Tennessee, Knoxville, TN (United States)

    2014-11-06

    RUL predictions, with as little uncertainty as possible. From a reliability and maintenance standpoint, there would be improved safety by avoiding all failures. Calculated risk would decrease, saving money by avoiding unnecessary maintenance. One major bottleneck for data-driven prognostics is the availability of run-to-failure degradation data. Without enough degradation data leading to failure, prognostic models can yield RUL distributions with large uncertainty or mathematically unsound predictions. To address these issues a "Lifecycle Prognostics" method was developed to create RUL distributions from Beginning of Life (BOL) to End of Life (EOL). This employs established Type I, II, and III prognostic methods, and Bayesian transitioning between each Type. Bayesian methods, as opposed to classical frequency statistics, show how an expected value, a priori, changes with new data to form a posterior distribution. For example, when you purchase a component you have a prior belief, or estimation, of how long it will operate before failing. As you operate it, you may collect information related to its condition that will allow you to update your estimated failure time. Bayesian methods are best used when limited data are available. The use of a prior also means that information is conserved when new data are available. The weightings of the prior belief and information contained in the sampled data are dependent on the variance (uncertainty) of the prior, the variance (uncertainty) of the data, and the amount of measured data (number of samples). If the variance of the prior is small compared to the uncertainty of the data, the prior will be weighed more heavily. However, as more data are collected, the data will be weighted more heavily and will eventually swamp out the prior in calculating the posterior distribution of model parameters. Fundamentally Bayesian analysis updates a prior belief with new data to get a posterior belief. The general approach to applying the

  11. A Prognostic Model for Estimating the Time to Virologic Failure in HIV-1 Infected Patients Undergoing a New Combination Antiretroviral Therapy Regimen

    Directory of Open Access Journals (Sweden)

    Micheli Valeria

    2011-06-01

    Full Text Available Abstract Background HIV-1 genotypic susceptibility scores (GSSs were proven to be significant prognostic factors of fixed time-point virologic outcomes after combination antiretroviral therapy (cART switch/initiation. However, their relative-hazard for the time to virologic failure has not been thoroughly investigated, and an expert system that is able to predict how long a new cART regimen will remain effective has never been designed. Methods We analyzed patients of the Italian ARCA cohort starting a new cART from 1999 onwards either after virologic failure or as treatment-naïve. The time to virologic failure was the endpoint, from the 90th day after treatment start, defined as the first HIV-1 RNA > 400 copies/ml, censoring at last available HIV-1 RNA before treatment discontinuation. We assessed the relative hazard/importance of GSSs according to distinct interpretation systems (Rega, ANRS and HIVdb and other covariates by means of Cox regression and random survival forests (RSF. Prediction models were validated via the bootstrap and c-index measure. Results The dataset included 2337 regimens from 2182 patients, of which 733 were previously treatment-naïve. We observed 1067 virologic failures over 2820 persons-years. Multivariable analysis revealed that low GSSs of cART were independently associated with the hazard of a virologic failure, along with several other covariates. Evaluation of predictive performance yielded a modest ability of the Cox regression to predict the virologic endpoint (c-index≈0.70, while RSF showed a better performance (c-index≈0.73, p Conclusions GSSs of cART and several other covariates were investigated using linear and non-linear survival analysis. RSF models are a promising approach for the development of a reliable system that predicts time to virologic failure better than Cox regression. Such models might represent a significant improvement over the current methods for monitoring and optimization of cART.

  12. Risk Modelling for Passages in Approach Channel

    Directory of Open Access Journals (Sweden)

    Leszek Smolarek

    2013-01-01

    Full Text Available Methods of multivariate statistics, stochastic processes, and simulation methods are used to identify and assess the risk measures. This paper presents the use of generalized linear models and Markov models to study risks to ships along the approach channel. These models combined with simulation testing are used to determine the time required for continuous monitoring of endangered objects or period at which the level of risk should be verified.

  13. Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.

    Science.gov (United States)

    Guinney, Justin; Wang, Tao; Laajala, Teemu D; Winner, Kimberly Kanigel; Bare, J Christopher; Neto, Elias Chaibub; Khan, Suleiman A; Peddinti, Gopal; Airola, Antti; Pahikkala, Tapio; Mirtti, Tuomas; Yu, Thomas; Bot, Brian M; Shen, Liji; Abdallah, Kald; Norman, Thea; Friend, Stephen; Stolovitzky, Gustavo; Soule, Howard; Sweeney, Christopher J; Ryan, Charles J; Scher, Howard I; Sartor, Oliver; Xie, Yang; Aittokallio, Tero; Zhou, Fang Liz; Costello, James C

    2017-01-01

    Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a

  14. Set-Theoretic Approach to Maturity Models

    DEFF Research Database (Denmark)

    Lasrado, Lester Allan

    Despite being widely accepted and applied, maturity models in Information Systems (IS) have been criticized for the lack of theoretical grounding, methodological rigor, empirical validations, and ignorance of multiple and non-linear paths to maturity. This PhD thesis focuses on addressing...... these criticisms by incorporating recent developments in configuration theory, in particular application of set-theoretic approaches. The aim is to show the potential of employing a set-theoretic approach for maturity model research and empirically demonstrating equifinal paths to maturity. Specifically...... methodological guidelines consisting of detailed procedures to systematically apply set theoretic approaches for maturity model research and provides demonstrations of it application on three datasets. The thesis is a collection of six research papers that are written in a sequential manner. The first paper...

  15. Mathematical Modeling Approaches in Plant Metabolomics.

    Science.gov (United States)

    Fürtauer, Lisa; Weiszmann, Jakob; Weckwerth, Wolfram; Nägele, Thomas

    2018-01-01

    The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.

  16. Cytogenetic prognostication within medulloblastoma subgroups.

    Science.gov (United States)

    Shih, David J H; Northcott, Paul A; Remke, Marc; Korshunov, Andrey; Ramaswamy, Vijay; Kool, Marcel; Luu, Betty; Yao, Yuan; Wang, Xin; Dubuc, Adrian M; Garzia, Livia; Peacock, John; Mack, Stephen C; Wu, Xiaochong; Rolider, Adi; Morrissy, A Sorana; Cavalli, Florence M G; Jones, David T W; Zitterbart, Karel; Faria, Claudia C; Schüller, Ulrich; Kren, Leos; Kumabe, Toshihiro; Tominaga, Teiji; Shin Ra, Young; Garami, Miklós; Hauser, Peter; Chan, Jennifer A; Robinson, Shenandoah; Bognár, László; Klekner, Almos; Saad, Ali G; Liau, Linda M; Albrecht, Steffen; Fontebasso, Adam; Cinalli, Giuseppe; De Antonellis, Pasqualino; Zollo, Massimo; Cooper, Michael K; Thompson, Reid C; Bailey, Simon; Lindsey, Janet C; Di Rocco, Concezio; Massimi, Luca; Michiels, Erna M C; Scherer, Stephen W; Phillips, Joanna J; Gupta, Nalin; Fan, Xing; Muraszko, Karin M; Vibhakar, Rajeev; Eberhart, Charles G; Fouladi, Maryam; Lach, Boleslaw; Jung, Shin; Wechsler-Reya, Robert J; Fèvre-Montange, Michelle; Jouvet, Anne; Jabado, Nada; Pollack, Ian F; Weiss, William A; Lee, Ji-Yeoun; Cho, Byung-Kyu; Kim, Seung-Ki; Wang, Kyu-Chang; Leonard, Jeffrey R; Rubin, Joshua B; de Torres, Carmen; Lavarino, Cinzia; Mora, Jaume; Cho, Yoon-Jae; Tabori, Uri; Olson, James M; Gajjar, Amar; Packer, Roger J; Rutkowski, Stefan; Pomeroy, Scott L; French, Pim J; Kloosterhof, Nanne K; Kros, Johan M; Van Meir, Erwin G; Clifford, Steven C; Bourdeaut, Franck; Delattre, Olivier; Doz, François F; Hawkins, Cynthia E; Malkin, David; Grajkowska, Wieslawa A; Perek-Polnik, Marta; Bouffet, Eric; Rutka, James T; Pfister, Stefan M; Taylor, Michael D

    2014-03-20

    Medulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication. Molecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models. Subgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas. Combining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials.

  17. SLS Navigation Model-Based Design Approach

    Science.gov (United States)

    Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

    2018-01-01

    The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

  18. Integration of prognostic aerosol-cloud interactions in a chemistry transport model coupled offline to a regional climate model

    Science.gov (United States)

    Thomas, M. A.; Kahnert, M.; Andersson, C.; Kokkola, H.; Hansson, U.; Jones, C.; Langner, J.; Devasthale, A.

    2015-06-01

    To reduce uncertainties and hence to obtain a better estimate of aerosol (direct and indirect) radiative forcing, next generation climate models aim for a tighter coupling between chemistry transport models and regional climate models and a better representation of aerosol-cloud interactions. In this study, this coupling is done by first forcing the Rossby Center regional climate model (RCA4) with ERA-Interim lateral boundaries and sea surface temperature (SST) using the standard cloud droplet number concentration (CDNC) formulation (hereafter, referred to as the "stand-alone RCA4 version" or "CTRL" simulation). In the stand-alone RCA4 version, CDNCs are constants distinguishing only between land and ocean surface. The meteorology from this simulation is then used to drive the chemistry transport model, Multiple-scale Atmospheric Transport and Chemistry (MATCH), which is coupled online with the aerosol dynamics model, Sectional Aerosol module for Large Scale Applications (SALSA). CDNC fields obtained from MATCH-SALSA are then fed back into a new RCA4 simulation. In this new simulation (referred to as "MOD" simulation), all parameters remain the same as in the first run except for the CDNCs provided by MATCH-SALSA. Simulations are carried out with this model setup for the period 2005-2012 over Europe, and the differences in cloud microphysical properties and radiative fluxes as a result of local CDNC changes and possible model responses are analysed. Our study shows substantial improvements in cloud microphysical properties with the input of the MATCH-SALSA derived 3-D CDNCs compared to the stand-alone RCA4 version. This model setup improves the spatial, seasonal and vertical distribution of CDNCs with a higher concentration observed over central Europe during boreal summer (JJA) and over eastern Europe and Russia during winter (DJF). Realistic cloud droplet radii (CD radii) values have been simulated with the maxima reaching 13 μm, whereas in the stand

  19. Prognostic Performance Metrics

    Data.gov (United States)

    National Aeronautics and Space Administration — This chapter presents several performance metrics for offline evaluation of prognostics algorithms. A brief overview of different methods employed for performance...

  20. Stochastic approaches to inflation model building

    International Nuclear Information System (INIS)

    Ramirez, Erandy; Liddle, Andrew R.

    2005-01-01

    While inflation gives an appealing explanation of observed cosmological data, there are a wide range of different inflation models, providing differing predictions for the initial perturbations. Typically models are motivated either by fundamental physics considerations or by simplicity. An alternative is to generate large numbers of models via a random generation process, such as the flow equations approach. The flow equations approach is known to predict a definite structure to the observational predictions. In this paper, we first demonstrate a more efficient implementation of the flow equations exploiting an analytic solution found by Liddle (2003). We then consider alternative stochastic methods of generating large numbers of inflation models, with the aim of testing whether the structures generated by the flow equations are robust. We find that while typically there remains some concentration of points in the observable plane under the different methods, there is significant variation in the predictions amongst the methods considered

  1. Model validation: a systemic and systematic approach

    International Nuclear Information System (INIS)

    Sheng, G.; Elzas, M.S.; Cronhjort, B.T.

    1993-01-01

    The term 'validation' is used ubiquitously in association with the modelling activities of numerous disciplines including social, political natural, physical sciences, and engineering. There is however, a wide range of definitions which give rise to very different interpretations of what activities the process involves. Analyses of results from the present large international effort in modelling radioactive waste disposal systems illustrate the urgent need to develop a common approach to model validation. Some possible explanations are offered to account for the present state of affairs. The methodology developed treats model validation and code verification in a systematic fashion. In fact, this approach may be regarded as a comprehensive framework to assess the adequacy of any simulation study. (author)

  2. Distributed Prognostic Health Management with Gaussian Process Regression

    Science.gov (United States)

    Saha, Sankalita; Saha, Bhaskar; Saxena, Abhinav; Goebel, Kai Frank

    2010-01-01

    Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. A major challenge encountered in such design is formulation of optimal distributed prognostics algorithms. In this paper. we present a distributed GPR based prognostics algorithm whose target platform is a wireless sensor network. In addition to challenges encountered in a distributed implementation, a wireless network poses constraints on communication patterns, thereby making the problem more challenging. The prognostics application that was used to demonstrate our new algorithms is battery prognostics. In order to present trade-offs within different prognostic approaches, we present comparison with the distributed implementation of a particle filter based prognostics for the same battery data.

  3. A Conceptual Modeling Approach for OLAP Personalization

    Science.gov (United States)

    Garrigós, Irene; Pardillo, Jesús; Mazón, Jose-Norberto; Trujillo, Juan

    Data warehouses rely on multidimensional models in order to provide decision makers with appropriate structures to intuitively analyze data with OLAP technologies. However, data warehouses may be potentially large and multidimensional structures become increasingly complex to be understood at a glance. Even if a departmental data warehouse (also known as data mart) is used, these structures would be also too complex. As a consequence, acquiring the required information is more costly than expected and decision makers using OLAP tools may get frustrated. In this context, current approaches for data warehouse design are focused on deriving a unique OLAP schema for all analysts from their previously stated information requirements, which is not enough to lighten the complexity of the decision making process. To overcome this drawback, we argue for personalizing multidimensional models for OLAP technologies according to the continuously changing user characteristics, context, requirements and behaviour. In this paper, we present a novel approach to personalizing OLAP systems at the conceptual level based on the underlying multidimensional model of the data warehouse, a user model and a set of personalization rules. The great advantage of our approach is that a personalized OLAP schema is provided for each decision maker contributing to better satisfy their specific analysis needs. Finally, we show the applicability of our approach through a sample scenario based on our CASE tool for data warehouse development.

  4. Variational approach to chiral quark models

    Energy Technology Data Exchange (ETDEWEB)

    Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira

    1987-03-01

    A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation.

  5. A variational approach to chiral quark models

    International Nuclear Information System (INIS)

    Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira.

    1987-01-01

    A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation. (author)

  6. A Set Theoretical Approach to Maturity Models

    DEFF Research Database (Denmark)

    Lasrado, Lester; Vatrapu, Ravi; Andersen, Kim Normann

    2016-01-01

    characterized by equifinality, multiple conjunctural causation, and case diversity. We prescribe methodological guidelines consisting of a six-step procedure to systematically apply set theoretic methods to conceptualize, develop, and empirically derive maturity models and provide a demonstration......Maturity Model research in IS has been criticized for the lack of theoretical grounding, methodological rigor, empirical validations, and ignorance of multiple and non-linear paths to maturity. To address these criticisms, this paper proposes a novel set-theoretical approach to maturity models...

  7. A hybrid modeling approach for option pricing

    Science.gov (United States)

    Hajizadeh, Ehsan; Seifi, Abbas

    2011-11-01

    The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.

  8. Heat transfer modeling an inductive approach

    CERN Document Server

    Sidebotham, George

    2015-01-01

    This innovative text emphasizes a "less-is-more" approach to modeling complicated systems such as heat transfer by treating them first as "1-node lumped models" that yield simple closed-form solutions. The author develops numerical techniques for students to obtain more detail, but also trains them to use the techniques only when simpler approaches fail. Covering all essential methods offered in traditional texts, but with a different order, Professor Sidebotham stresses inductive thinking and problem solving as well as a constructive understanding of modern, computer-based practice. Readers learn to develop their own code in the context of the material, rather than just how to use packaged software, offering a deeper, intrinsic grasp behind models of heat transfer. Developed from over twenty-five years of lecture notes to teach students of mechanical and chemical engineering at The Cooper Union for the Advancement of Science and Art, the book is ideal for students and practitioners across engineering discipl...

  9. Nonperturbative approach to the attractive Hubbard model

    International Nuclear Information System (INIS)

    Allen, S.; Tremblay, A.-M. S.

    2001-01-01

    A nonperturbative approach to the single-band attractive Hubbard model is presented in the general context of functional-derivative approaches to many-body theories. As in previous work on the repulsive model, the first step is based on a local-field-type ansatz, on enforcement of the Pauli principle and a number of crucial sumrules. The Mermin-Wagner theorem in two dimensions is automatically satisfied. At this level, two-particle self-consistency has been achieved. In the second step of the approximation, an improved expression for the self-energy is obtained by using the results of the first step in an exact expression for the self-energy, where the high- and low-frequency behaviors appear separately. The result is a cooperon-like formula. The required vertex corrections are included in this self-energy expression, as required by the absence of a Migdal theorem for this problem. Other approaches to the attractive Hubbard model are critically compared. Physical consequences of the present approach and agreement with Monte Carlo simulations are demonstrated in the accompanying paper (following this one)

  10. Quasirelativistic quark model in quasipotential approach

    CERN Document Server

    Matveev, V A; Savrin, V I; Sissakian, A N

    2002-01-01

    The relativistic particles interaction is described within the frames of quasipotential approach. The presentation is based on the so called covariant simultaneous formulation of the quantum field theory, where by the theory is considered on the spatial-like three-dimensional hypersurface in the Minkowski space. Special attention is paid to the methods of plotting various quasipotentials as well as to the applications of the quasipotential approach to describing the characteristics of the relativistic particles interaction in the quark models, namely: the hadrons elastic scattering amplitudes, the mass spectra and widths mesons decays, the cross sections of the deep inelastic leptons scattering on the hadrons

  11. A multiscale modeling approach for biomolecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

    2015-04-15

    This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

  12. A new approach for developing adjoint models

    Science.gov (United States)

    Farrell, P. E.; Funke, S. W.

    2011-12-01

    Many data assimilation algorithms rely on the availability of gradients of misfit functionals, which can be efficiently computed with adjoint models. However, the development of an adjoint model for a complex geophysical code is generally very difficult. Algorithmic differentiation (AD, also called automatic differentiation) offers one strategy for simplifying this task: it takes the abstraction that a model is a sequence of primitive instructions, each of which may be differentiated in turn. While extremely successful, this low-level abstraction runs into time-consuming difficulties when applied to the whole codebase of a model, such as differentiating through linear solves, model I/O, calls to external libraries, language features that are unsupported by the AD tool, and the use of multiple programming languages. While these difficulties can be overcome, it requires a large amount of technical expertise and an intimate familiarity with both the AD tool and the model. An alternative to applying the AD tool to the whole codebase is to assemble the discrete adjoint equations and use these to compute the necessary gradients. With this approach, the AD tool must be applied to the nonlinear assembly operators, which are typically small, self-contained units of the codebase. The disadvantage of this approach is that the assembly of the discrete adjoint equations is still very difficult to perform correctly, especially for complex multiphysics models that perform temporal integration; as it stands, this approach is as difficult and time-consuming as applying AD to the whole model. In this work, we have developed a library which greatly simplifies and automates the alternate approach of assembling the discrete adjoint equations. We propose a complementary, higher-level abstraction to that of AD: that a model is a sequence of linear solves. The developer annotates model source code with library calls that build a 'tape' of the operators involved and their dependencies, and

  13. Eutrophication Modeling Using Variable Chlorophyll Approach

    International Nuclear Information System (INIS)

    Abdolabadi, H.; Sarang, A.; Ardestani, M.; Mahjoobi, E.

    2016-01-01

    In this study, eutrophication was investigated in Lake Ontario to identify the interactions among effective drivers. The complexity of such phenomenon was modeled using a system dynamics approach based on a consideration of constant and variable stoichiometric ratios. The system dynamics approach is a powerful tool for developing object-oriented models to simulate complex phenomena that involve feedback effects. Utilizing stoichiometric ratios is a method for converting the concentrations of state variables. During the physical segmentation of the model, Lake Ontario was divided into two layers, i.e., the epilimnion and hypolimnion, and differential equations were developed for each layer. The model structure included 16 state variables related to phytoplankton, herbivorous zooplankton, carnivorous zooplankton, ammonium, nitrate, dissolved phosphorus, and particulate and dissolved carbon in the epilimnion and hypolimnion during a time horizon of one year. The results of several tests to verify the model, close to 1 Nash-Sutcliff coefficient (0.98), the data correlation coefficient (0.98), and lower standard errors (0.96), have indicated well-suited model’s efficiency. The results revealed that there were significant differences in the concentrations of the state variables in constant and variable stoichiometry simulations. Consequently, the consideration of variable stoichiometric ratios in algae and nutrient concentration simulations may be applied in future modeling studies to enhance the accuracy of the results and reduce the likelihood of inefficient control policies.

  14. Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab

    International Nuclear Information System (INIS)

    An, Dawn; Choi, Joo-Ho; Kim, Nam Ho

    2013-01-01

    This paper presents a Matlab-based tutorial for model-based prognostics, which combines a physical model with observed data to identify model parameters, from which the remaining useful life (RUL) can be predicted. Among many model-based prognostics algorithms, the particle filter is used in this tutorial for parameter estimation of damage or a degradation model. The tutorial is presented using a Matlab script with 62 lines, including detailed explanations. As examples, a battery degradation model and a crack growth model are used to explain the updating process of model parameters, damage progression, and RUL prediction. In order to illustrate the results, the RUL at an arbitrary cycle are predicted in the form of distribution along with the median and 90% prediction interval. This tutorial will be helpful for the beginners in prognostics to understand and use the prognostics method, and we hope it provides a standard of particle filter based prognostics. -- Highlights: ► Matlab-based tutorial for model-based prognostics is presented. ► A battery degradation model and a crack growth model are used as examples. ► The RUL at an arbitrary cycle are predicted using the particle filter

  15. Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques

    Science.gov (United States)

    Saha, Bhaskar; Goebel, kai

    2007-01-01

    Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to the modern Condition- Based Maintenance (CBM)/Prognostic Health Management (PHM) paradigm. The application of the Bayesian techniques to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation as in Particle Filters (PF), provides a powerful tool to integrate the diagnosis and prognosis of battery health. The RVM, which is a Bayesian treatment of the Support Vector Machine (SVM), is used for model identification, while the PF framework uses the learnt model, statistical estimates of noise and anticipated operational conditions to provide estimates of remaining useful life (RUL) in the form of a probability density function (PDF). This type of prognostics generates a significant value addition to the management of any operation involving electrical systems.

  16. Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence Model.

    Science.gov (United States)

    Hong, Sehee; Kim, Soyoung

    2018-01-01

    There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.

  17. Evolutionary modeling-based approach for model errors correction

    Directory of Open Access Journals (Sweden)

    S. Q. Wan

    2012-08-01

    Full Text Available The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963 equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data."

    On the basis of the intelligent features of evolutionary modeling (EM, including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.

  18. MODELS OF TECHNOLOGY ADOPTION: AN INTEGRATIVE APPROACH

    Directory of Open Access Journals (Sweden)

    Andrei OGREZEANU

    2015-06-01

    Full Text Available The interdisciplinary study of information technology adoption has developed rapidly over the last 30 years. Various theoretical models have been developed and applied such as: the Technology Acceptance Model (TAM, Innovation Diffusion Theory (IDT, Theory of Planned Behavior (TPB, etc. The result of these many years of research is thousands of contributions to the field, which, however, remain highly fragmented. This paper develops a theoretical model of technology adoption by integrating major theories in the field: primarily IDT, TAM, and TPB. To do so while avoiding mess, an approach that goes back to basics in independent variable type’s development is proposed; emphasizing: 1 the logic of classification, and 2 psychological mechanisms behind variable types. Once developed these types are then populated with variables originating in empirical research. Conclusions are developed on which types are underpopulated and present potential for future research. I end with a set of methodological recommendations for future application of the model.

  19. Interfacial Fluid Mechanics A Mathematical Modeling Approach

    CERN Document Server

    Ajaev, Vladimir S

    2012-01-01

    Interfacial Fluid Mechanics: A Mathematical Modeling Approach provides an introduction to mathematical models of viscous flow used in rapidly developing fields of microfluidics and microscale heat transfer. The basic physical effects are first introduced in the context of simple configurations and their relative importance in typical microscale applications is discussed. Then,several configurations of importance to microfluidics, most notably thin films/droplets on substrates and confined bubbles, are discussed in detail.  Topics from current research on electrokinetic phenomena, liquid flow near structured solid surfaces, evaporation/condensation, and surfactant phenomena are discussed in the later chapters. This book also:  Discusses mathematical models in the context of actual applications such as electrowetting Includes unique material on fluid flow near structured surfaces and phase change phenomena Shows readers how to solve modeling problems related to microscale multiphase flows Interfacial Fluid Me...

  20. A new modelling approach for zooplankton behaviour

    Science.gov (United States)

    Keiyu, A. Y.; Yamazaki, H.; Strickler, J. R.

    We have developed a new simulation technique to model zooplankton behaviour. The approach utilizes neither the conventional artificial intelligence nor neural network methods. We have designed an adaptive behaviour network, which is similar to BEER [(1990) Intelligence as an adaptive behaviour: an experiment in computational neuroethology, Academic Press], based on observational studies of zooplankton behaviour. The proposed method is compared with non- "intelligent" models—random walk and correlated walk models—as well as observed behaviour in a laboratory tank. Although the network is simple, the model exhibits rich behavioural patterns similar to live copepods.

  1. Continuum modeling an approach through practical examples

    CERN Document Server

    Muntean, Adrian

    2015-01-01

    This book develops continuum modeling skills and approaches the topic from three sides: (1) derivation of global integral laws together with the associated local differential equations, (2) design of constitutive laws and (3) modeling boundary processes. The focus of this presentation lies on many practical examples covering aspects such as coupled flow, diffusion and reaction in porous media or microwave heating of a pizza, as well as traffic issues in bacterial colonies and energy harvesting from geothermal wells. The target audience comprises primarily graduate students in pure and applied mathematics as well as working practitioners in engineering who are faced by nonstandard rheological topics like those typically arising in the food industry.

  2. Global Environmental Change: An integrated modelling approach

    International Nuclear Information System (INIS)

    Den Elzen, M.

    1993-01-01

    Two major global environmental problems are dealt with: climate change and stratospheric ozone depletion (and their mutual interactions), briefly surveyed in part 1. In Part 2 a brief description of the integrated modelling framework IMAGE 1.6 is given. Some specific parts of the model are described in more detail in other Chapters, e.g. the carbon cycle model, the atmospheric chemistry model, the halocarbon model, and the UV-B impact model. In Part 3 an uncertainty analysis of climate change and stratospheric ozone depletion is presented (Chapter 4). Chapter 5 briefly reviews the social and economic uncertainties implied by future greenhouse gas emissions. Chapters 6 and 7 describe a model and sensitivity analysis pertaining to the scientific uncertainties and/or lacunae in the sources and sinks of methane and carbon dioxide, and their biogeochemical feedback processes. Chapter 8 presents an uncertainty and sensitivity analysis of the carbon cycle model, the halocarbon model, and the IMAGE model 1.6 as a whole. Part 4 presents the risk assessment methodology as applied to the problems of climate change and stratospheric ozone depletion more specifically. In Chapter 10, this methodology is used as a means with which to asses current ozone policy and a wide range of halocarbon policies. Chapter 11 presents and evaluates the simulated globally-averaged temperature and sea level rise (indicators) for the IPCC-1990 and 1992 scenarios, concluding with a Low Risk scenario, which would meet the climate targets. Chapter 12 discusses the impact of sea level rise on the frequency of the Dutch coastal defence system (indicator) for the IPCC-1990 scenarios. Chapter 13 presents projections of mortality rates due to stratospheric ozone depletion based on model simulations employing the UV-B chain model for a number of halocarbon policies. Chapter 14 presents an approach for allocating future emissions of CO 2 among regions. (Abstract Truncated)

  3. An Aircraft Lifecycle Approach for the Cost-Benefit Analysis of Prognostics and Condition-Based Maintenance-Based on Discrete-Event Simulation

    Science.gov (United States)

    2014-10-02

    MPD. This manufacturer documentation contains maintenance tasks with specification of intervals and required man-hours that are to be carried out...failures, without consideration of false alarms and missed failures (see also section 4.1.3). The task redundancy rate is the percentage of preventive...Prognostics and Health Management ROI return on investment RUL remaining useful life TCG task code group SB Service Bulletin XML Extensible Markup

  4. Addressing the challenges of obtaining functional outcomes in traumatic brain injury research: missing data patterns, timing of follow-up, and three prognostic models.

    Science.gov (United States)

    Zelnick, Leila R; Morrison, Laurie J; Devlin, Sean M; Bulger, Eileen M; Brasel, Karen J; Sheehan, Kellie; Minei, Joseph P; Kerby, Jeffrey D; Tisherman, Samuel A; Rizoli, Sandro; Karmy-Jones, Riyad; van Heest, Rardi; Newgard, Craig D

    2014-06-01

    Traumatic brain injury (TBI) is common and debilitating. Randomized trials of interventions for TBI ideally assess effectiveness by using long-term functional neurological outcomes, but such outcomes are difficult to obtain and costly. If there is little change between functional status at hospital discharge versus 6 months, then shorter-term outcomes may be adequate for use in future clinical trials. Using data from a previously published multi-center, randomized, placebo-controlled TBI clinical trial, we evaluated patterns of missing outcome data, changes in functional status between hospital discharge and 6 months, and three prognostic models to predict long-term functional outcome from covariates available at hospital discharge (functional measures, demographics, and injury characteristics). The Resuscitation Outcomes Consortium Hypertonic Saline trial enrolled 1282 TBI patients, obtaining the primary outcome of 6-month Glasgow Outcome Score Extended (GOSE) for 85% of patients, but missing the primary outcome for the remaining 15%. Patients with missing outcomes had less-severe injuries, higher neurological function at discharge (GOSE), and shorter hospital stays than patients whose GOSE was obtained. Of 1066 (83%) patients whose GOSE was obtained both at hospital discharge and at 6-months, 71% of patients had the same dichotomized functional status (severe disability/death vs. moderate/no disability) after 6 months as at discharge, 28% had an improved functional status, and 1% had worsened. Performance was excellent (C-statistic between 0.88 and 0.91) for all three prognostic models and calibration adequate for two models (p values, 0.22 and 0.85). Our results suggest that multiple imputation of the standard 6-month GOSE may be reasonable in TBI research when the primary outcome cannot be obtained through other means.

  5. Discovery of a Novel Immune Gene Signature with Profound Prognostic Value in Colorectal Cancer: A Model of Cooperativity Disorientation Created in the Process from Development to Cancer.

    Directory of Open Access Journals (Sweden)

    Ning An

    Full Text Available Immune response-related genes play a major role in colorectal carcinogenesis by mediating inflammation or immune-surveillance evasion. Although remarkable progress has been made to investigate the underlying mechanism, the understanding of the complicated carcinogenesis process was enormously hindered by large-scale tumor heterogeneity. Development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. The association between embryonic development and carcinogenesis makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Here we proposed that the immune genes, responsible for intra-immune cooperativity disorientation (defined in this study as disruption of developmental expression correlation patterns during carcinogenesis, probably contain untapped prognostic resource of colorectal cancer. In this study, we determined the mRNA expression profile of 137 human biopsy samples, including samples from different stages of human colonic development, colorectal precancerous progression and colorectal cancer samples, among which 60 were also used to generate miRNA expression profile. We originally established Spearman correlation transition model to quantify the cooperativity disorientation associated with the transition from normal to precancerous to cancer tissue, in conjunction with miRNA-mRNA regulatory network and machine learning algorithm to identify genes with prognostic value. Finally, a 12-gene signature was extracted, whose prognostic value was evaluated using Kaplan-Meier survival analysis in five independent datasets. Using the log-rank test, the 12-gene signature was closely related to overall survival in four datasets (GSE17536, n = 177, p = 0.0054; GSE17537, n = 55, p = 0.0039; GSE39582, n = 562, p = 0.13; GSE39084, n = 70, p = 0.11, and significantly associated with disease

  6. Crime Modeling using Spatial Regression Approach

    Science.gov (United States)

    Saleh Ahmar, Ansari; Adiatma; Kasim Aidid, M.

    2018-01-01

    Act of criminality in Indonesia increased both variety and quantity every year. As murder, rape, assault, vandalism, theft, fraud, fencing, and other cases that make people feel unsafe. Risk of society exposed to crime is the number of reported cases in the police institution. The higher of the number of reporter to the police institution then the number of crime in the region is increasing. In this research, modeling criminality in South Sulawesi, Indonesia with the dependent variable used is the society exposed to the risk of crime. Modelling done by area approach is the using Spatial Autoregressive (SAR) and Spatial Error Model (SEM) methods. The independent variable used is the population density, the number of poor population, GDP per capita, unemployment and the human development index (HDI). Based on the analysis using spatial regression can be shown that there are no dependencies spatial both lag or errors in South Sulawesi.

  7. Merging Digital Surface Models Implementing Bayesian Approaches

    Science.gov (United States)

    Sadeq, H.; Drummond, J.; Li, Z.

    2016-06-01

    In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades). It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.

  8. MERGING DIGITAL SURFACE MODELS IMPLEMENTING BAYESIAN APPROACHES

    Directory of Open Access Journals (Sweden)

    H. Sadeq

    2016-06-01

    Full Text Available In this research different DSMs from different sources have been merged. The merging is based on a probabilistic model using a Bayesian Approach. The implemented data have been sourced from very high resolution satellite imagery sensors (e.g. WorldView-1 and Pleiades. It is deemed preferable to use a Bayesian Approach when the data obtained from the sensors are limited and it is difficult to obtain many measurements or it would be very costly, thus the problem of the lack of data can be solved by introducing a priori estimations of data. To infer the prior data, it is assumed that the roofs of the buildings are specified as smooth, and for that purpose local entropy has been implemented. In addition to the a priori estimations, GNSS RTK measurements have been collected in the field which are used as check points to assess the quality of the DSMs and to validate the merging result. The model has been applied in the West-End of Glasgow containing different kinds of buildings, such as flat roofed and hipped roofed buildings. Both quantitative and qualitative methods have been employed to validate the merged DSM. The validation results have shown that the model was successfully able to improve the quality of the DSMs and improving some characteristics such as the roof surfaces, which consequently led to better representations. In addition to that, the developed model has been compared with the well established Maximum Likelihood model and showed similar quantitative statistical results and better qualitative results. Although the proposed model has been applied on DSMs that were derived from satellite imagery, it can be applied to any other sourced DSMs.

  9. Implementation and evaluation of prognostic representations of the optical diameter of snow in the SURFEX/ISBA-Crocus detailed snowpack model

    Science.gov (United States)

    Carmagnola, C. M.; Morin, S.; Lafaysse, M.; Domine, F.; Lesaffre, B.; Lejeune, Y.; Picard, G.; Arnaud, L.

    2014-03-01

    In the SURFEX/ISBA-Crocus multi-layer snowpack model, the snow microstructure has up to now been characterised by the grain size and by semi-empirical shape variables which cannot be measured easily in the field or linked to other relevant snow properties. In this work we introduce a new formulation of snow metamorphism directly based on equations describing the rate of change of the optical diameter (dopt). This variable is considered here to be equal to the equivalent sphere optical diameter, which is inversely proportional to the specific surface area (SSA). dopt thus represents quantitatively some of the geometric characteristics of a porous medium. Different prognostic rate equations of dopt, including a re-formulation of the original Crocus scheme and the parameterisations from Taillandier et al. (2007) and Flanner and Zender (2006), were evaluated by comparing their predictions to field measurements carried out at Summit Camp (Greenland) in May and June 2011 and at Col de Porte (French Alps) during the 2009/10 and 2011/12 winter seasons. We focused especially on results in terms of SSA. In addition, we tested the impact of the different formulations on the simulated density profile, the total snow height, the snow water equivalent (SWE) and the surface albedo. Results indicate that all formulations perform well, with median values of the RMSD between measured and simulated SSA lower than 10 m2 kg-1. Incorporating the optical diameter as a fully fledged prognostic variable is an important step forward in the quantitative description of the snow microstructure within snowpack models, because it opens the way to data assimilation of various electromagnetic observations.

  10. Implementation and evaluation of prognostic representations of the optical diameter of snow in the detailed snowpack model SURFEX/ISBA-Crocus

    Science.gov (United States)

    Carmagnola, C. M.; Morin, S.; Lafaysse, M.; Domine, F.; Lesaffre, B.; Lejeune, Y.; Picard, G.; Arnaud, L.

    2013-09-01

    In the SURFEX/ISBA-Crocus multi-layer snowpack model, the snow microstructure was up to now characterized by the grain size and by semi-empirical shape variables which cannot be measured easily in the field or linked to other relevant snow properties. In this work we introduce a new formulation of snow metamorphism directly based on equations describing the rate of change of the optical diameter (dopt). This variable is considered here to be equal to the equivalent sphere optical diameter, which is inversely proportional to the specific surface area (SSA). dopt thus represents quantitatively some of the geometric characteristics of a porous medium. Different prognostic rate equations of dopt, including a re-formulation of the original Crocus scheme and the parametrizations from Taillandier et al. (2007) and Flanner and Zender (2006), were evaluated by comparing their predictions to field measurements carried out at Summit Camp (Greenland) in May and June 2011 and at Col de Porte (French Alps) during the 2009/10 and 2011/12 winter seasons. We focused especially on results in terms of SSA. In addition, we tested the impact of the different formulations on the simulated density profile, the total snow height, the snow water equivalent (SWE) and the surface albedo. Results indicate that all formulations perform well, with median values of the RMSD between measured and simulated SSA lower than 10 m2 kg-1. Incorporating the optical diameter as a fully-fledged prognostic variable is an important step forward in the quantitative description of the snow microstructure within snowpack models, because it opens the way to data assimilation of various electromagnetic observations.

  11. A nationwide modelling approach to decommissioning - 16182

    International Nuclear Information System (INIS)

    Kelly, Bernard; Lowe, Andy; Mort, Paul

    2009-01-01

    In this paper we describe a proposed UK national approach to modelling decommissioning. For the first time, we shall have an insight into optimizing the safety and efficiency of a national decommissioning strategy. To do this we use the General Case Integrated Waste Algorithm (GIA), a universal model of decommissioning nuclear plant, power plant, waste arisings and the associated knowledge capture. The model scales from individual items of plant through cells, groups of cells, buildings, whole sites and then on up to a national scale. We describe the national vision for GIA which can be broken down into three levels: 1) the capture of the chronological order of activities that an experienced decommissioner would use to decommission any nuclear facility anywhere in the world - this is Level 1 of GIA; 2) the construction of an Operational Research (OR) model based on Level 1 to allow rapid what if scenarios to be tested quickly (Level 2); 3) the construction of a state of the art knowledge capture capability that allows future generations to learn from our current decommissioning experience (Level 3). We show the progress to date in developing GIA in levels 1 and 2. As part of level 1, GIA has assisted in the development of an IMechE professional decommissioning qualification. Furthermore, we describe GIA as the basis of a UK-Owned database of decommissioning norms for such things as costs, productivity, durations etc. From level 2, we report on a pilot study that has successfully tested the basic principles for the OR numerical simulation of the algorithm. We then highlight the advantages of applying the OR modelling approach nationally. In essence, a series of 'what if...' scenarios can be tested that will improve the safety and efficiency of decommissioning. (authors)

  12. Multiplex polymerase chain reaction-based prognostic models in diffuse large B-cell lymphoma patients treated with R-CHOP

    DEFF Research Database (Denmark)

    Green, Tina M; Jensen, Andreas K; Holst, René

    2016-01-01

    We present a multiplex analysis for genes known to have prognostic value in an attempt to design a clinically useful classification model in patients with diffuse large B-cell lymphoma (DLBCL). Real-time polymerase chain reaction was used to measure transcript levels of 28 relevant genes in 194 de...... models. The best model was validated in data from an online available R-CHOP treated cohort. With progression-free survival (PFS) as primary endpoint, the best performing IPI independent model incorporated the LMO2 and HLADQA1 as well as gene interactions for GCSAMxMIB1, GCSAMxCTGF and FOXP1xPDE4B....... This model assigned 33% of patients (n = 60) to poor outcome with an estimated 3-year PFS of 40% vs. 87% for low risk (n = 61) and intermediate (n = 60) risk groups (P model incorporated LMO2 and BCL2 and assigned 33% of the patients with a 3-year PFS of 35% vs...

  13. Prognostics of Power MOSFET

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper demonstrates how to apply prognostics to power MOSFETs (metal oxide field effect transistor). The methodology uses thermal cycling to age devices and...

  14. Modeling in transport phenomena a conceptual approach

    CERN Document Server

    Tosun, Ismail

    2007-01-01

    Modeling in Transport Phenomena, Second Edition presents and clearly explains with example problems the basic concepts and their applications to fluid flow, heat transfer, mass transfer, chemical reaction engineering and thermodynamics. A balanced approach is presented between analysis and synthesis, students will understand how to use the solution in engineering analysis. Systematic derivations of the equations and the physical significance of each term are given in detail, for students to easily understand and follow up the material. There is a strong incentive in science and engineering to

  15. Nuclear physics for applications. A model approach

    International Nuclear Information System (INIS)

    Prussin, S.G.

    2007-01-01

    Written by a researcher and teacher with experience at top institutes in the US and Europe, this textbook provides advanced undergraduates minoring in physics with working knowledge of the principles of nuclear physics. Simplifying models and approaches reveal the essence of the principles involved, with the mathematical and quantum mechanical background integrated in the text where it is needed and not relegated to the appendices. The practicality of the book is enhanced by numerous end-of-chapter problems and solutions available on the Wiley homepage. (orig.)

  16. Pedagogic process modeling: Humanistic-integrative approach

    Directory of Open Access Journals (Sweden)

    Boritko Nikolaj M.

    2007-01-01

    Full Text Available The paper deals with some current problems of modeling the dynamics of the subject-features development of the individual. The term "process" is considered in the context of the humanistic-integrative approach, in which the principles of self education are regarded as criteria for efficient pedagogic activity. Four basic characteristics of the pedagogic process are pointed out: intentionality reflects logicality and regularity of the development of the process; discreteness (stageability in dicates qualitative stages through which the pedagogic phenomenon passes; nonlinearity explains the crisis character of pedagogic processes and reveals inner factors of self-development; situationality requires a selection of pedagogic conditions in accordance with the inner factors, which would enable steering the pedagogic process. Offered are two steps for singling out a particular stage and the algorithm for developing an integrative model for it. The suggested conclusions might be of use for further theoretic research, analyses of educational practices and for realistic predicting of pedagogical phenomena. .

  17. A simulation study on estimating biomarker-treatment interaction effects in randomized trials with prognostic variables.

    Science.gov (United States)

    Haller, Bernhard; Ulm, Kurt

    2018-02-20

    To individualize treatment decisions based on patient characteristics, identification of an interaction between a biomarker and treatment is necessary. Often such potential interactions are analysed using data from randomized clinical trials intended for comparison of two treatments. Tests of interactions are often lacking statistical power and we investigated if and how a consideration of further prognostic variables can improve power and decrease the bias of estimated biomarker-treatment interactions in randomized clinical trials with time-to-event outcomes. A simulation study was performed to assess how prognostic factors affect the estimate of the biomarker-treatment interaction for a time-to-event outcome, when different approaches, like ignoring other prognostic factors, including all available covariates or using variable selection strategies, are applied. Different scenarios regarding the proportion of censored observations, the correlation structure between the covariate of interest and further potential prognostic variables, and the strength of the interaction were considered. The simulation study revealed that in a regression model for estimating a biomarker-treatment interaction, the probability of detecting a biomarker-treatment interaction can be increased by including prognostic variables that are associated with the outcome, and that the interaction estimate is biased when relevant prognostic variables are not considered. However, the probability of a false-positive finding increases if too many potential predictors are included or if variable selection is performed inadequately. We recommend undertaking an adequate literature search before data analysis to derive information about potential prognostic variables and to gain power for detecting true interaction effects and pre-specifying analyses to avoid selective reporting and increased false-positive rates.

  18. A novel approach to pipeline tensioner modeling

    Energy Technology Data Exchange (ETDEWEB)

    O' Grady, Robert; Ilie, Daniel; Lane, Michael [MCS Software Division, Galway (Ireland)

    2009-07-01

    As subsea pipeline developments continue to move into deep and ultra-deep water locations, there is an increasing need for the accurate prediction of expected pipeline fatigue life. A significant factor that must be considered as part of this process is the fatigue damage sustained by the pipeline during installation. The magnitude of this installation-related damage is governed by a number of different agents, one of which is the dynamic behavior of the tensioner systems during pipe-laying operations. There are a variety of traditional finite element methods for representing dynamic tensioner behavior. These existing methods, while basic in nature, have been proven to provide adequate forecasts in terms of the dynamic variation in typical installation parameters such as top tension and sagbend/overbend strain. However due to the simplicity of these current approaches, some of them tend to over-estimate the frequency of tensioner pay out/in under dynamic loading. This excessive level of pay out/in motion results in the prediction of additional stress cycles at certain roller beds, which in turn leads to the prediction of unrealistic fatigue damage to the pipeline. This unwarranted fatigue damage then equates to an over-conservative value for the accumulated damage experienced by a pipeline weld during installation, and so leads to a reduction in the estimated fatigue life for the pipeline. This paper describes a novel approach to tensioner modeling which allows for greater control over the velocity of dynamic tensioner pay out/in and so provides a more accurate estimation of fatigue damage experienced by the pipeline during installation. The paper reports on a case study, as outlined in the proceeding section, in which a comparison is made between results from this new tensioner model and from a more conventional approach. The comparison considers typical installation parameters as well as an in-depth look at the predicted fatigue damage for the two methods

  19. [Prognostic scores for pulmonary embolism].

    Science.gov (United States)

    Junod, Alain

    2016-03-23

    Nine prognostic scores for pulmonary embolism (PE), based on retrospective and prospective studies, published between 2000 and 2014, have been analyzed and compared. Most of them aim at identifying PE cases with a low risk to validate their ambulatory care. Important differences in the considered outcomes: global mortality, PE-specific mortality, other complications, sizes of low risk groups, exist between these scores. The most popular score appears to be the PESI and its simplified version. Few good quality studies have tested the applicability of these scores to PE outpatient care, although this approach tends to already generalize in the medical practice.

  20. Evaluation of meteorological fields generated by a prognostic mesoscale model using data collected during the 1993 GMAQS/COAST field study

    International Nuclear Information System (INIS)

    Lolk, N.K.; Douglas, S.G.

    1996-01-01

    In 1993, the US Interior Department's Minerals Management Service (MMS) sponsored the Gulf of Mexico Air Quality Study (GMAQS). Its purpose was to assess potential impacts of offshore petrochemical development on ozone concentrations in nonattainment areas in the Texas/Louisiana Gulf Coast region as mandated by the 1990 Clean Air Act Amendments. The GMAQS comprised data collection, data analysis, and applications of an advanced photochemical air quality model, the variable-grid Urban Airshed Model (UAM-V), and a prognostic mesoscale meteorological model (SAIMM -- Systems Applications International Mesoscale Model) to simulate two ozone episodes that were captured during the summer field study. The primary purpose of this paper is to evaluate the SAIMM-simulated meteorological fields using graphical analysis that utilize the comprehensive GMAQS/COAST (Gulf of Mexico Air Quality Study/Coastal Oxidant Assessment for Southeast Texas) database and to demonstrate the ability of the SAIMM to simulate the day-to-day variations in the evolution and structure of the gulf breeze and the mixed layer

  1. Development and External Validation of Prognostic Model for 2-Year Survival of Non-Small-Cell Lung Cancer Patients Treated With Chemoradiotherapy

    International Nuclear Information System (INIS)

    Dehing-Oberije, Cary; Yu Shipeng; De Ruysscher, Dirk; Meersschout, Sabine; Van Beek, Karen; Lievens, Yolande; Van Meerbeeck, Jan; De Neve, Wilfried; Rao, Bharat Ph.D.; Weide, Hiska van der; Lambin, Philippe

    2009-01-01

    Purpose: Radiotherapy, combined with chemotherapy, is the treatment of choice for a large group of non-small-cell lung cancer (NSCLC) patients. Recent developments in the treatment of these patients have led to improved survival. However, the clinical TNM stage is highly inaccurate for the prediction of survival, and alternatives are lacking. The objective of this study was to develop and validate a prediction model for survival of NSCLC patients, treated with chemoradiotherapy. Patients and Methods: The clinical data from 377 consecutive inoperable NSCLC patients, Stage I-IIIB, treated radically with chemoradiotherapy were collected. A prognostic model for 2-year survival was developed, using 2-norm support vector machines. The performance of the model was expressed as the area under the curve of the receiver operating characteristic and assessed using leave-one-out cross-validation, as well as two external data sets. Results: The final multivariate model consisted of gender, World Health Organization performance status, forced expiratory volume in 1 s, number of positive lymph node stations, and gross tumor volume. The area under the curve, assessed by leave-one-out cross-validation, was 0.74, and application of the model to the external data sets yielded an area under the curve of 0.75 and 0.76. A high- and low-risk group could be clearly identified using a risk score based on the model. Conclusion: The multivariate model performed very well and was able to accurately predict the 2-year survival of NSCLC patients treated with chemoradiotherapy. The model could support clinicians in the treatment decision-making process.

  2. Approaches and models of intercultural education

    Directory of Open Access Journals (Sweden)

    Iván Manuel Sánchez Fontalvo

    2013-10-01

    Full Text Available Needed to be aware of the need to build an intercultural society, awareness must be assumed in all social spheres, where stands the role play education. A role of transcendental, since it must promote educational spaces to form people with virtues and powers that allow them to live together / as in multicultural contexts and social diversities (sometimes uneven in an increasingly globalized and interconnected world, and foster the development of feelings of civic belonging shared before the neighborhood, city, region and country, allowing them concern and critical judgement to marginalization, poverty, misery and inequitable distribution of wealth, causes of structural violence, but at the same time, wanting to work for the welfare and transformation of these scenarios. Since these budgets, it is important to know the approaches and models of intercultural education that have been developed so far, analysing their impact on the contexts educational where apply.   

  3. Transport modeling: An artificial immune system approach

    Directory of Open Access Journals (Sweden)

    Teodorović Dušan

    2006-01-01

    Full Text Available This paper describes an artificial immune system approach (AIS to modeling time-dependent (dynamic, real time transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies for different antigens (different traffic "scenarios". This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

  4. System approach to modeling of industrial technologies

    Science.gov (United States)

    Toropov, V. S.; Toropov, E. S.

    2018-03-01

    The authors presented a system of methods for modeling and improving industrial technologies. The system consists of information and software. The information part is structured information about industrial technologies. The structure has its template. The template has several essential categories used to improve the technological process and eliminate weaknesses in the process chain. The base category is the physical effect that takes place when the technical process proceeds. The programming part of the system can apply various methods of creative search to the content stored in the information part of the system. These methods pay particular attention to energy transformations in the technological process. The system application will allow us to systematize the approach to improving technologies and obtaining new technical solutions.

  5. ECOMOD - An ecological approach to radioecological modelling

    International Nuclear Information System (INIS)

    Sazykina, Tatiana G.

    2000-01-01

    A unified methodology is proposed to simulate the dynamic processes of radionuclide migration in aquatic food chains in parallel with their stable analogue elements. The distinguishing feature of the unified radioecological/ecological approach is the description of radionuclide migration along with dynamic equations for the ecosystem. The ability of the methodology to predict the results of radioecological experiments is demonstrated by an example of radionuclide (iron group) accumulation by a laboratory culture of the algae Platymonas viridis. Based on the unified methodology, the 'ECOMOD' radioecological model was developed to simulate dynamic radioecological processes in aquatic ecosystems. It comprises three basic modules, which are operated as a set of inter-related programs. The 'ECOSYSTEM' module solves non-linear ecological equations, describing the biomass dynamics of essential ecosystem components. The 'RADIONUCLIDE DISTRIBUTION' module calculates the radionuclide distribution in abiotic and biotic components of the aquatic ecosystem. The 'DOSE ASSESSMENT' module calculates doses to aquatic biota and doses to man from aquatic food chains. The application of the ECOMOD model to reconstruct the radionuclide distribution in the Chernobyl Cooling Pond ecosystem in the early period after the accident shows good agreement with observations

  6. Modelling Approach In Islamic Architectural Designs

    Directory of Open Access Journals (Sweden)

    Suhaimi Salleh

    2014-06-01

    Full Text Available Architectural designs contribute as one of the main factors that should be considered in minimizing negative impacts in planning and structural development in buildings such as in mosques. In this paper, the ergonomics perspective is revisited which hence focuses on the conditional factors involving organisational, psychological, social and population as a whole. This paper tries to highlight the functional and architectural integration with ecstatic elements in the form of decorative and ornamental outlay as well as incorporating the building structure such as wall, domes and gates. This paper further focuses the mathematical aspects of the architectural designs such as polar equations and the golden ratio. These designs are modelled into mathematical equations of various forms, while the golden ratio in mosque is verified using two techniques namely, the geometric construction and the numerical method. The exemplary designs are taken from theSabah Bandaraya Mosque in Likas, Kota Kinabalu and the Sarawak State Mosque in Kuching,while the Universiti Malaysia Sabah Mosque is used for the Golden Ratio. Results show thatIslamic architectural buildings and designs have long had mathematical concepts and techniques underlying its foundation, hence, a modelling approach is needed to rejuvenate these Islamic designs.

  7. Risk factors and a prognostic score for survival after autologous stem-cell transplantation for relapsed or refractory Hodgkin lymphoma

    DEFF Research Database (Denmark)

    Bröckelmann, P J; Müller, H; Casasnovas, O

    2017-01-01

    study (n = 1045), precise and valid risk prognostication in HL patients undergoing ASCT can be achieved with five easily available clinical RFs. The proposed prognostic score hence allows reliable stratification of patients for innovative therapeutic approaches in clinical practice and future trials...... therapeutic approaches, we investigated a comprehensive set of risk factors (RFs) for survival after ASCT. Methods: In this multinational prognostic multivariable modeling study, 23 potential RFs were retrospectively evaluated in HL patients from nine prospective trials with multivariable Cox proportional...... of potential RFs had significant impact on progression-free survival (PFS) with hazard ratios (HR) ranging from 1.39 to 2.22. The multivariable analysis identified stage IV disease, time to relapse ≤3 months, ECOG performance status ≥1, bulk ≥5 cm and inadequate response to salvage chemotherapy [

  8. Prognostics Of Power Mosfets Under Thermal Stress Accelerated Aging Using Data-Driven And Model-Based Methodologies

    Data.gov (United States)

    National Aeronautics and Space Administration — An approach for predicting remaining useful life of power MOSFETs (metal oxide field effect transistor) devices has been developed. Power MOSFETs are semiconductor...

  9. Towards A Model-based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

    Data.gov (United States)

    National Aeronautics and Space Administration — A remaining useful life prediction methodology for elec- trolytic capacitors is presented. This methodology adopts a Kalman filter approach in conjunction with an...

  10. An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer.

    Science.gov (United States)

    Saha, Monjoy; Chakraborty, Chandan; Arun, Indu; Ahmed, Rosina; Chatterjee, Sanjoy

    2017-06-12

    Being a non-histone protein, Ki-67 is one of the essential biomarkers for the immunohistochemical assessment of proliferation rate in breast cancer screening and grading. The Ki-67 signature is always sensitive to radiotherapy and chemotherapy. Due to random morphological, color and intensity variations of cell nuclei (immunopositive and immunonegative), manual/subjective assessment of Ki-67 scoring is error-prone and time-consuming. Hence, several machine learning approaches have been reported; nevertheless, none of them had worked on deep learning based hotspots detection and proliferation scoring. In this article, we suggest an advanced deep learning model for computerized recognition of candidate hotspots and subsequent proliferation rate scoring by quantifying Ki-67 appearance in breast cancer immunohistochemical images. Unlike existing Ki-67 scoring techniques, our methodology uses Gamma mixture model (GMM) with Expectation-Maximization for seed point detection and patch selection and deep learning, comprises with decision layer, for hotspots detection and proliferation scoring. Experimental results provide 93% precision, 0.88% recall and 0.91% F-score value. The model performance has also been compared with the pathologists' manual annotations and recently published articles. In future, the proposed deep learning framework will be highly reliable and beneficial to the junior and senior pathologists for fast and efficient Ki-67 scoring.

  11. An integrated approach to permeability modeling using micro-models

    Energy Technology Data Exchange (ETDEWEB)

    Hosseini, A.H.; Leuangthong, O.; Deutsch, C.V. [Society of Petroleum Engineers, Canadian Section, Calgary, AB (Canada)]|[Alberta Univ., Edmonton, AB (Canada)

    2008-10-15

    An important factor in predicting the performance of steam assisted gravity drainage (SAGD) well pairs is the spatial distribution of permeability. Complications that make the inference of a reliable porosity-permeability relationship impossible include the presence of short-scale variability in sand/shale sequences; preferential sampling of core data; and uncertainty in upscaling parameters. Micro-modelling is a simple and effective method for overcoming these complications. This paper proposed a micro-modeling approach to account for sampling bias, small laminated features with high permeability contrast, and uncertainty in upscaling parameters. The paper described the steps and challenges of micro-modeling and discussed the construction of binary mixture geo-blocks; flow simulation and upscaling; extended power law formalism (EPLF); and the application of micro-modeling and EPLF. An extended power-law formalism to account for changes in clean sand permeability as a function of macroscopic shale content was also proposed and tested against flow simulation results. There was close agreement between the model and simulation results. The proposed methodology was also applied to build the porosity-permeability relationship for laminated and brecciated facies of McMurray oil sands. Experimental data was in good agreement with the experimental data. 8 refs., 17 figs.

  12. Risk communication: a mental models approach

    National Research Council Canada - National Science Library

    Morgan, M. Granger (Millett Granger)

    2002-01-01

    ... information about risks. The procedure uses approaches from risk and decision analysis to identify the most relevant information; it also uses approaches from psychology and communication theory to ensure that its message is understood. This book is written in nontechnical terms, designed to make the approach feasible for anyone willing to try it. It is illustrat...

  13. A Multi-Model Approach for System Diagnosis

    DEFF Research Database (Denmark)

    Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur

    2007-01-01

    A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....

  14. Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

    Science.gov (United States)

    Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

    2017-10-01

    The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (pEEG patterns such as generalized periodic discharges (pEEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Peripheral T cell lymphoma, not otherwise specified (PTCL-NOS). A new prognostic model developed by the International T cell Project Network.

    Science.gov (United States)

    Federico, Massimo; Bellei, Monica; Marcheselli, Luigi; Schwartz, Marc; Manni, Martina; Tarantino, Vittoria; Pileri, Stefano; Ko, Young-Hyeh; Cabrera, Maria E; Horwitz, Steven; Kim, Won S; Shustov, Andrei; Foss, Francine M; Nagler, Arnon; Carson, Kenneth; Pinter-Brown, Lauren C; Montoto, Silvia; Spina, Michele; Feldman, Tatyana A; Lechowicz, Mary J; Smith, Sonali M; Lansigan, Frederick; Gabus, Raul; Vose, Julie M; Advani, Ranjana H

    2018-04-19

    Different models to investigate the prognosis of peripheral T cell lymphoma not otherwise specified (PTCL-NOS) have been developed by means of retrospective analyses. Here we report on a new model designed on data from the prospective T Cell Project. Twelve covariates collected by the T Cell Project were analysed and a new model (T cell score), based on four covariates (serum albumin, performance status, stage and absolute neutrophil count) that maintained their prognostic value in multiple Cox proportional hazards regression analysis was proposed. Among patients registered in the T Cell Project, 311 PTCL-NOS were retained for study. At a median follow-up of 46 months, the median overall survival (OS) and progression-free survival (PFS) was 20 and 10 months, respectively. Three groups were identified at low risk (LR, 48 patients, 15%, score 0), intermediate risk (IR, 189 patients, 61%, score 1-2), and high risk (HiR, 74 patients, 24%, score 3-4), having a 3-year OS of 76% [95% confidence interval 61-88], 43% [35-51], and 11% [4-21], respectively (P < 0·001). Comparing the performance of the T cell score on OS to that of each of the previously developed models, it emerged that the new score had the best discriminant power. The new T cell score, based on clinical variables, identifies a group with very unfavourable outcomes. © 2018 The Authors British Journal of Haematology published by British Society for Haematology and John Wiley & Sons Ltd.

  16. Prognostic factors in oligodendrogliomas

    DEFF Research Database (Denmark)

    Westergaard, L; Gjerris, F; Klinken, L

    1997-01-01

    An outcome analysis was performed on 96 patients with pure cerebral oligodendrogliomas operated in the 30-year period 1962 to 1991. The most important predictive prognostic factors were youth and no neurological deficit, demonstrated as a median survival for the group younger than 20 years of 17...

  17. Predictive accuracy of model for end stage liver disease (meld) as a prognostic marker for cirrhosis in comparison with child - pugh score

    International Nuclear Information System (INIS)

    Zubair, U.B.; Alam, M.M.; Saeed, F.

    2015-01-01

    To compare Model for End Stage Liver Disease (MELD) and Child-Turcott-Pugh (CTG) scoring as predictors of survival in cirrhotic patients. Study Design: Observational prospective study. Place and Duration of Study: Military Hospital, Rawalpindi from 1st Dec 2008 to 30th April 2009. Material and Methods: The study was carried out at Military Hospital, Rawalpindi a tertiary care hospital of Pakistan. Study included 55 patients suffering from cirrhosis of both genders being above 12 years of age, admitted in medical wards during the period from 1st December, 2008 to 30th April 2009. Each patient was assigned a MELD and CTP score. On discharge, these patients were followed up at 03 months, 06 months and 1 year duration through telephone. Results: Thirty seven (67.3%) patients were male while 18 (32.7%) were female patients, with age ranging from 27 years to 75 years (mean 53). Fourteen (25.4%) patients were dead at 3-months, 22 patients (40%) were dead at 6-months and 29 (52.7%) patients were dead at 1 year follow up. MELD score proved to be a better indicator of survival than CTP score over a period of 01 year follow-up. Conclusion: MELD score is a better prognostic marker for cirrhotic patients as compared to CTP score. (author)

  18. An automated approach to improve efficacy in detecting residual malignant cancer cell for facilitating prognostic assessment of leukemia: an initial study

    Science.gov (United States)

    Qiu, Yuchen; Lu, Xianglan; Tan, Maxine; Li, Shibo; Liu, Hong; Zheng, Bin

    2015-03-01

    The purpose of this study is to investigate the feasibility of applying automatic interphase FISH cells analysis method for detecting the residual malignancy of post chemotherapy leukemia patients. In the experiment, two clinical specimens with translocation between chromosome No. 9 and 22 or No. 11 and 14 were selected from the patients underwent leukemia diagnosis and treatment. The entire slide of each specimen was first digitalized by a commercial fluorescent microscope using a 40× objective lens. Then, the scanned images were processed by a computer-aided detecting (CAD) scheme to identify the analyzable FISH cells, which is accomplished by applying a series of features including the region size, Brenner gradient and maximum intensity. For each identified cell, the scheme detected and counted the number of the FISH signal dots inside the nucleus, using the adaptive threshold of the region size and distance of the labeled FISH dots. The results showed that the new CAD scheme detected 8093 and 6675 suspicious regions of interest (ROI) in two specimens, among which 4546 and 3807 ROI contain analyzable interphase FISH cell. In these analyzable ROIs, CAD selected 334 and 405 residual malignant cancer cells, which is substantially more than those visually detected in a cytogenetic laboratory of our medical center (334 vs. 122, 405 vs. 160). This investigation indicates that an automatic interphase FISH cell scanning and CAD method has the potential to improve the accuracy and efficiency of the prognostic assessment for leukemia and other genetic related cancer patients in the future.

  19. Computational and Game-Theoretic Approaches for Modeling Bounded Rationality

    NARCIS (Netherlands)

    L. Waltman (Ludo)

    2011-01-01

    textabstractThis thesis studies various computational and game-theoretic approaches to economic modeling. Unlike traditional approaches to economic modeling, the approaches studied in this thesis do not rely on the assumption that economic agents behave in a fully rational way. Instead, economic

  20. Towards A Model-Based Prognostics Methodology For Electrolytic Capacitors: A Case Study Based On Electrical Overstress Accelerated Aging

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a model-driven methodology for predict- ing the remaining useful life of electrolytic capacitors. This methodology adopts a Kalman filter...

  1. Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model

    OpenAIRE

    Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

    2017-01-01

    Purpose The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. Materials and Methods This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC m...

  2. Early prognostication markers in cardiac arrest patients treated with hypothermia.

    Science.gov (United States)

    Karapetkova, M; Koenig, M A; Jia, X

    2016-03-01

    Established prognostication markers, such as clinical findings, electroencephalography (EEG) and biochemical markers, used by clinicians to predict neurological outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. MEDLINE and Embase were searched for evidence on the current standards for neurological outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers and multimodal approaches for prognostication are included and reviewed. Whilst the prognostic accuracy of various tests after TH has been questioned, pupillary light reflexes and somatosensory evoked potentials are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 h after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as magnetic resonance imaging and computed tomography, can identify functional and structural brain injury but are not readily available at the patient's bedside because of limited availability and high costs. A multimodal algorithm composed of neurological examination, EEG-based quantitative testing and somatosensory evoked potentials, in conjunction with newer magnetic resonance imaging sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed more than 72 h after CA. © 2015 EAN.

  3. Digital System e-Prognostics for Critical Aircraft Computer Systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Impact Technologies, in cooperation with Raytheon, proposes to develop and demonstrate an innovative prognostics approach for aircraft digital electronics. The...

  4. A Discrete Monetary Economic Growth Model with the MIU Approach

    Directory of Open Access Journals (Sweden)

    Wei-Bin Zhang

    2008-01-01

    Full Text Available This paper proposes an alternative approach to economic growth with money. The production side is the same as the Solow model, the Ramsey model, and the Tobin model. But we deal with behavior of consumers differently from the traditional approaches. The model is influenced by the money-in-the-utility (MIU approach in monetary economics. It provides a mechanism of endogenous saving which the Solow model lacks and avoids the assumption of adding up utility over a period of time upon which the Ramsey approach is based.

  5. Mathematical Modelling Approach in Mathematics Education

    Science.gov (United States)

    Arseven, Ayla

    2015-01-01

    The topic of models and modeling has come to be important for science and mathematics education in recent years. The topic of "Modeling" topic is especially important for examinations such as PISA which is conducted at an international level and measures a student's success in mathematics. Mathematical modeling can be defined as using…

  6. A Multivariate Approach to Functional Neuro Modeling

    DEFF Research Database (Denmark)

    Mørch, Niels J.S.

    1998-01-01

    by the application of linear and more flexible, nonlinear microscopic regression models to a real-world dataset. The dependency of model performance, as quantified by generalization error, on model flexibility and training set size is demonstrated, leading to the important realization that no uniformly optimal model......, provides the basis for a generalization theoretical framework relating model performance to model complexity and dataset size. Briefly summarized the major topics discussed in the thesis include: - An introduction of the representation of functional datasets by pairs of neuronal activity patterns...... exists. - Model visualization and interpretation techniques. The simplicity of this task for linear models contrasts the difficulties involved when dealing with nonlinear models. Finally, a visualization technique for nonlinear models is proposed. A single observation emerges from the thesis...

  7. Rival approaches to mathematical modelling in immunology

    Science.gov (United States)

    Andrew, Sarah M.; Baker, Christopher T. H.; Bocharov, Gennady A.

    2007-08-01

    In order to formulate quantitatively correct mathematical models of the immune system, one requires an understanding of immune processes and familiarity with a range of mathematical techniques. Selection of an appropriate model requires a number of decisions to be made, including a choice of the modelling objectives, strategies and techniques and the types of model considered as candidate models. The authors adopt a multidisciplinary perspective.

  8. C-reactive protein and serum amyloid A as early-phase and prognostic indicators of acute radiation exposure in nonhuman primate total-body irradiation model

    Energy Technology Data Exchange (ETDEWEB)

    Ossetrova, N.I., E-mail: ossetrova@afrri.usuhs.mil [Armed Forces Radiobiology Research Institute, 8901 Wisconsin Avenue, Bldg. 42, Bethesda, MD 20889-5603 (United States); Sandgren, D.J.; Blakely, W.F. [Armed Forces Radiobiology Research Institute, 8901 Wisconsin Avenue, Bldg. 42, Bethesda, MD 20889-5603 (United States)

    2011-09-15

    Terrorist radiological attacks or nuclear accidents could expose large numbers of people to ionizing radiation. In mass-casualty radiological incidents early medical-management requires triage tools for first-responders to quantitatively identify individuals exposed to life-threatening radiation doses and for early initiation (i.e., within one day after radiation exposure) of cytokine therapy for treatment of bone marrow acute radiation syndrome. Herein, we present results from 30 rhesus macaques total-body irradiated (TBI) to a broad dose range of 1-8.5 Gy with {sup 60}Co {gamma}-rays (0.55 Gy min{sup -1}) and demonstrate dose- and time-dependent changes in blood of C-reactive protein (CRP), serum amyloid A (SAA), and interleukin 6 (IL-6) measured by enzyme linked immunosorbent assay (ELISA). CRP and SAA dose-response results are consistent with {approx}1 Gy and {approx}0.2 Gy thresholds for photon-exposure at 24 h after TBI, respectively. Highly significant elevations of CRP and SAA (p = 0.00017 and p = 0.0024, respectively) were found in animal plasma at 6 h after all TBI doses suggesting their potential use as early-phase biodosimeters. Results also show that the dynamics and content of CRP and SAA levels reflect the course and severity of the acute radiation sickness (ARS) and may function as prognostic indicators of ARS outcome. These results demonstrate proof-of-concept that these radiation-responsive proteins show promise as a complementary approach to conventional biodosimetry for early assessment of radiation exposures and may also contribute as diagnostic indices in the medical management of radiation accidents.

  9. A hybrid agent-based approach for modeling microbiological systems.

    Science.gov (United States)

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  10. Building and validation of a prognostic model for predicting extracorporeal circuit clotting in patients with continuous renal replacement therapy.

    Science.gov (United States)

    Fu, Xia; Liang, Xinling; Song, Li; Huang, Huigen; Wang, Jing; Chen, Yuanhan; Zhang, Li; Quan, Zilin; Shi, Wei

    2014-04-01

    To develop a predictive model for circuit clotting in patients with continuous renal replacement therapy (CRRT). A total of 425 cases were selected. 302 cases were used to develop a predictive model of extracorporeal circuit life span during CRRT without citrate anticoagulation in 24 h, and 123 cases were used to validate the model. The prediction formula was developed using multivariate Cox proportional-hazards regression analysis, from which a risk score was assigned. The mean survival time of the circuit was 15.0 ± 1.3 h, and the rate of circuit clotting was 66.6 % during 24 h of CRRT. Five significant variables were assigned a predicting score according to the regression coefficient: insufficient blood flow, no anticoagulation, hematocrit ≥0.37, lactic acid of arterial blood gas analysis ≤3 mmol/L and APTT R (2) = 0.232; P = 0.301). A risk score that includes the five above-mentioned variables can be used to predict the likelihood of extracorporeal circuit clotting in patients undergoing CRRT.

  11. Numerical modelling approach for mine backfill

    Indian Academy of Sciences (India)

    Muhammad Zaka Emad

    2017-07-24

    Jul 24, 2017 ... conditions. This paper discusses a numerical modelling strategy for modelling mine backfill material. The .... placed in an ore pass that leads the ore to the ore bin and crusher, from ... 1 year, depending on the mine plan.

  12. Uncertainty in biology a computational modeling approach

    CERN Document Server

    Gomez-Cabrero, David

    2016-01-01

    Computational modeling of biomedical processes is gaining more and more weight in the current research into the etiology of biomedical problems and potential treatment strategies.  Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process.  This book wants to address four main issues related to the building and validation of computational models of biomedical processes: Modeling establishment under uncertainty Model selection and parameter fitting Sensitivity analysis and model adaptation Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples.  This book is intended for graduate stude...

  13. OILMAP: A global approach to spill modeling

    International Nuclear Information System (INIS)

    Spaulding, M.L.; Howlett, E.; Anderson, E.; Jayko, K.

    1992-01-01

    OILMAP is an oil spill model system suitable for use in both rapid response mode and long-range contingency planning. It was developed for a personal computer and employs full-color graphics to enter data, set up spill scenarios, and view model predictions. The major components of OILMAP include environmental data entry and viewing capabilities, the oil spill models, and model prediction display capabilities. Graphic routines are provided for entering wind data, currents, and any type of geographically referenced data. Several modes of the spill model are available. The surface trajectory mode is intended for quick spill response. The weathering model includes the spreading, evaporation, entrainment, emulsification, and shoreline interaction of oil. The stochastic and receptor models simulate a large number of trajectories from a single site for generating probability statistics. Each model and the algorithms they use are described. Several additional capabilities are planned for OILMAP, including simulation of tactical spill response and subsurface oil transport. 8 refs

  14. Relaxed memory models: an operational approach

    OpenAIRE

    Boudol , Gérard; Petri , Gustavo

    2009-01-01

    International audience; Memory models define an interface between programs written in some language and their implementation, determining which behaviour the memory (and thus a program) is allowed to have in a given model. A minimal guarantee memory models should provide to the programmer is that well-synchronized, that is, data-race free code has a standard semantics. Traditionally, memory models are defined axiomatically, setting constraints on the order in which memory operations are allow...

  15. Modeling composting kinetics: A review of approaches

    NARCIS (Netherlands)

    Hamelers, H.V.M.

    2004-01-01

    Composting kinetics modeling is necessary to design and operate composting facilities that comply with strict market demands and tight environmental legislation. Current composting kinetics modeling can be characterized as inductive, i.e. the data are the starting point of the modeling process and

  16. Conformally invariant models: A new approach

    International Nuclear Information System (INIS)

    Fradkin, E.S.; Palchik, M.Ya.; Zaikin, V.N.

    1996-02-01

    A pair of mathematical models of quantum field theory in D dimensions is analyzed, particularly, a model of a charged scalar field defined by two generations of secondary fields in the space of even dimensions D>=4 and a model of a neutral scalar field defined by two generations of secondary fields in two-dimensional space. 6 refs

  17. MICRONUCLEI: A PROGNOSTIC TOOL

    OpenAIRE

    Ankit; Rinky; Manisha; Sonalika; Anand; Sanyog

    2014-01-01

    Squamous cell carcinoma is one the most common oral mucosal malignant tumor, diagnosis of oral squamous cell carcinoma rarely presents difficulty, it is the cancer staging and histo pathological grading that are more important for prognosis, micronuclei are good prognostic indicator. Micronuclei screening can be done easily by exfoliative cytology, one of the most valuable diagnostic method other than routine histopathology (H and E-stained sections) and immunohistochemist...

  18. No prognostic value added by vitamin D pathway SNPs to current prognostic system for melanoma survival.

    Directory of Open Access Journals (Sweden)

    Li Luo

    Full Text Available The prognostic improvement attributed to genetic markers over current prognostic system has not been well studied for melanoma. The goal of this study is to evaluate the added prognostic value of Vitamin D Pathway (VitD SNPs to currently known clinical and demographic factors such as age, sex, Breslow thickness, mitosis and ulceration (CDF. We utilized two large independent well-characterized melanoma studies: the Genes, Environment, and Melanoma (GEM and MD Anderson studies, and performed variable selection of VitD pathway SNPs and CDF using Random Survival Forest (RSF method in addition to Cox proportional hazards models. The Harrell's C-index was used to compare the performance of model predictability. The population-based GEM study enrolled 3,578 incident cases of cutaneous melanoma (CM, and the hospital-based MD Anderson study consisted of 1,804 CM patients. Including both VitD SNPs and CDF yielded C-index of 0.85, which provided slight but not significant improvement by CDF alone (C-index = 0.83 in the GEM study. Similar results were observed in the independent MD Anderson study (C-index = 0.84 and 0.83, respectively. The Cox model identified no significant associations after adjusting for multiplicity. Our results do not support clinically significant prognostic improvements attributable to VitD pathway SNPs over current prognostic system for melanoma survival.

  19. Prospective validation of a prognostic model for respiratory syncytial virus bronchiolitis in late preterm infants: a multicenter birth cohort study.

    Directory of Open Access Journals (Sweden)

    Maarten O Blanken

    Full Text Available This study aimed to update and validate a prediction rule for respiratory syncytial virus (RSV hospitalization in preterm infants 33-35 weeks gestational age (WGA.The RISK study consisted of 2 multicenter prospective birth cohorts in 41 hospitals. Risk factors were assessed at birth among healthy preterm infants 33-35 WGA. All hospitalizations for respiratory tract infection were screened for proven RSV infection by immunofluorescence or polymerase chain reaction. Multivariate logistic regression analysis was used to update an existing prediction model in the derivation cohort (n = 1,227. In the validation cohort (n = 1,194, predicted versus actual RSV hospitalization rates were compared to determine validity of the model.RSV hospitalization risk in both cohorts was comparable (5.7% versus 4.9%. In the derivation cohort, a prediction rule to determine probability of RSV hospitalization was developed using 4 predictors: family atopy (OR 1.9; 95%CI, 1.1-3.2, birth period (OR 2.6; 1.6-4.2, breastfeeding (OR 1.7; 1.0-2.7 and siblings or daycare attendance (OR 4.7; 1.7-13.1. The model showed good discrimination (c-statistic 0.703; 0.64-0.76, 0.702 after bootstrapping. External validation showed good discrimination and calibration (c-statistic 0.678; 0.61-0.74.Our prospectively validated prediction rule identifies infants at increased RSV hospitalization risk, who may benefit from targeted preventive interventions. This prediction rule can facilitate country-specific, cost-effective use of RSV prophylaxis in late preterm infants.

  20. Performance of three prognostic models in patients with cancer in need of intensive care in a medical center in China.

    Directory of Open Access Journals (Sweden)

    XueZhong Xing

    Full Text Available The aim of this study was to evaluate the performance of Acute Physiology and Chronic Health Evaluation II (APACHE II, Simplified Acute Physiology Score 3 (SAPS 3, and Acute Physiology and Chronic Health Evaluation IV (APACHE IV in patients with cancer admitted to intensive care unit (ICU in a single medical center in China.This is a retrospective observational cohort study including nine hundred and eighty one consecutive patients over a 2-year period.The hospital mortality rate was 4.5%. When all 981 patients were evaluated, the area under the receiver operating characteristic curve (AUROC, 95% Confidential Intervals of the three models in predicting hospital mortality were 0.948 (0.914-0.982, 0.863 (0.804-0.923, and 0.873 (0.813-0.934 for SAPS 3, APACHE II and APACHE IV respectively. The p values of Hosmer-Lemeshow statistics for the models were 0.759, 0.900 and 0.878 for SAPS 3, APACHE II and APACHE IV respectively. However, SAPS 3 and APACHE IV underestimated the in-hospital mortality with standardized mortality ratio (SMR of 1.5 and 1.17 respectively, while APACHE II overestimated the in-hospital mortality with SMR of 0.72. Further analysis showed that discrimination power was better with SAPS 3 than with APACHE II and APACHE IV whether for emergency surgical and medical patients (AUROC of 0.912 vs 0.866 and 0.857 or for scheduled surgical patients (AUROC of 0.945 vs 0.834 and 0.851. Calibration was good for all models (all p > 0.05 whether for scheduled surgical patients or emergency surgical and medical patients. However, in terms of SMR, SAPS 3 was both accurate in predicting the in-hospital mortality for emergency surgical and medical patients and for scheduled surgical patients, while APACHE IV and APACHE II were not.In this cohort, we found that APACHE II, APACHE IV and SAPS 3 models had good discrimination and calibration ability in predicting in-hospital mortality of critically ill patients with cancer in need of intensive care. Of

  1. A copula-based sampling method for data-driven prognostics

    International Nuclear Information System (INIS)

    Xi, Zhimin; Jing, Rong; Wang, Pingfeng; Hu, Chao

    2014-01-01

    This paper develops a Copula-based sampling method for data-driven prognostics. The method essentially consists of an offline training process and an online prediction process: (i) the offline training process builds a statistical relationship between the failure time and the time realizations at specified degradation levels on the basis of off-line training data sets; and (ii) the online prediction process identifies probable failure times for online testing units based on the statistical model constructed in the offline process and the online testing data. Our contributions in this paper are three-fold, namely the definition of a generic health index system to quantify the health degradation of an engineering system, the construction of a Copula-based statistical model to learn the statistical relationship between the failure time and the time realizations at specified degradation levels, and the development of a simulation-based approach for the prediction of remaining useful life (RUL). Two engineering case studies, namely the electric cooling fan health prognostics and the 2008 IEEE PHM challenge problem, are employed to demonstrate the effectiveness of the proposed methodology. - Highlights: • We develop a novel mechanism for data-driven prognostics. • A generic health index system quantifies health degradation of engineering systems. • Off-line training model is constructed based on the Bayesian Copula model. • Remaining useful life is predicted from a simulation-based approach

  2. Molecular Pathology: Predictive, Prognostic, and Diagnostic Markers in Uterine Tumors.

    Science.gov (United States)

    Ritterhouse, Lauren L; Howitt, Brooke E

    2016-09-01

    This article focuses on the diagnostic, prognostic, and predictive molecular biomarkers in uterine malignancies, in the context of morphologic diagnoses. The histologic classification of endometrial carcinomas is reviewed first, followed by the description and molecular classification of endometrial epithelial malignancies in the context of histologic classification. Taken together, the molecular and histologic classifications help clinicians to approach troublesome areas encountered in clinical practice and evaluate the utility of molecular alterations in the diagnosis and subclassification of endometrial carcinomas. Putative prognostic markers are reviewed. The use of molecular alterations and surrogate immunohistochemistry as prognostic and predictive markers is also discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. 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.

  4. A systemic approach to modelling of radiobiological effects

    International Nuclear Information System (INIS)

    Obaturov, G.M.

    1988-01-01

    Basic principles of the systemic approach to modelling of the radiobiological effects at different levels of cell organization have been formulated. The methodology is proposed for theoretical modelling of the effects at these levels

  5. Serpentinization reaction pathways: implications for modeling approach

    Energy Technology Data Exchange (ETDEWEB)

    Janecky, D.R.

    1986-01-01

    Experimental seawater-peridotite reaction pathways to form serpentinites at 300/sup 0/C, 500 bars, can be accurately modeled using the EQ3/6 codes in conjunction with thermodynamic and kinetic data from the literature and unpublished compilations. These models provide both confirmation of experimental interpretations and more detailed insight into hydrothermal reaction processes within the oceanic crust. The accuracy of these models depends on careful evaluation of the aqueous speciation model, use of mineral compositions that closely reproduce compositions in the experiments, and definition of realistic reactive components in terms of composition, thermodynamic data, and reaction rates.

  6. Consumer preference models: fuzzy theory approach

    Science.gov (United States)

    Turksen, I. B.; Wilson, I. A.

    1993-12-01

    Consumer preference models are widely used in new product design, marketing management, pricing and market segmentation. The purpose of this article is to develop and test a fuzzy set preference model which can represent linguistic variables in individual-level models implemented in parallel with existing conjoint models. The potential improvements in market share prediction and predictive validity can substantially improve management decisions about what to make (product design), for whom to make it (market segmentation) and how much to make (market share prediction).

  7. A visual approach for modeling spatiotemporal relations

    NARCIS (Netherlands)

    R.L. Guimarães (Rodrigo); C.S.S. Neto; L.F.G. Soares

    2008-01-01

    htmlabstractTextual programming languages have proven to be difficult to learn and to use effectively for many people. For this sake, visual tools can be useful to abstract the complexity of such textual languages, minimizing the specification efforts. In this paper we present a visual approach for

  8. PRODUCT TRIAL PROCESSING (PTP): A MODEL APPROACH ...

    African Journals Online (AJOL)

    Admin

    This study is a theoretical approach to consumer's processing of product trail, and equally explored ... consumer's first usage experience with a company's brand or product that is most important in determining ... product, what it is really marketing is the expected ..... confidence, thus there is a positive relationship between ...

  9. 12 A multi-centre randomised feasibility study evaluating the impact of a prognostic model for management of blunt chest wall trauma patients: stumbl trial.

    Science.gov (United States)

    Battle, Ceri; Hutchings, Hayley; Abbott, Zoe; O'neill, Claire; Groves, Sam; Watkins, Alan; Lecky, Fiona; Jones, Sally; Gagg, James; Body, Rick; Evans, Phillip

    2017-12-01

    A new prognostic model has been developed and externally validated, the aim of which is to assist in the management of the blunt chest wall trauma patient in the Emergency Department (ED). A definitive randomised controlled trial (impact trial), is required to assess the clinical and cost effectiveness of the new model, before it can be accepted in clinical practice. The purpose of this trial is to assess the feasibility and acceptability of such a definitive trial and inform its design. This feasibility trial is designed to test the methods of a multi-centre, cluster-randomised (stepped wedge) trial, with a substantial qualitative component. Four EDs in England and Wales will collect data for all blunt chest wall trauma patients over a five month period; in the initial period acting as the controls (normal care) and the second period, acting as the interventions (in which the new model will be used). Baseline measurements including completion of the SF-12v2 will be obtained on initial assessment in the ED. Patient outcome data will then be collected for any subsequent hospitalisations. Data collection will conclude with a six week follow-up completion of two surveys (SF-12v2 and Client Services Receipt Inventory).Analysis of outcomes will focus on feasibility, acceptability and trial processes and will include recruitment and retention rates, attendance at clinician training rates and use of model in the ED. Qualitative feedback will be obtained through clinician interviews and a research nurse focus group. An evaluation of the feasibility of health economics outcomes data will be completed. Wales Research Ethics Committee 6 granted approval for the trial in September 2016. Health Care Research Wales Research Permissions and the HRA have granted approval for the study. Patient recruitment commenced in February 2017. Planned dissemination is through publication in a peer-reviewed Emergency Medicine Journal, presentation at appropriate conferences and to

  10. Protocol for a multicentre randomised feasibility STUdy evaluating the impact of a prognostic model for Management of BLunt chest wall trauma patients: STUMBL trial.

    Science.gov (United States)

    Battle, Ceri; Abbott, Zoe; Hutchings, Hayley A; O'Neill, Claire; Groves, Sam; Watkins, Alan; Lecky, Fiona E; Jones, Sally; Gagg, James; Body, Richard; Evans, Philip A

    2017-07-10

    A new prognostic model has been developed and externally validated, the aim of which is to assist in the management of the blunt chest wall trauma patient in the emergency department (ED). A definitive randomised controlled trial (impact trial) is required to assess the clinical and cost effectiveness of the new model before it can be accepted in clinical practice. The purpose of this trial is to assess the feasibility and acceptability of such a definitive trial and inform its design. This feasibility trial is designed to test the methods of a multicentre, cluster-randomised (stepped- wedge) trial, with a substantial qualitative component. Four EDs in England and Wales will collect data for all blunt chest wall trauma patients over a 5-month period; in the initial period acting as the controls (normal care), and in the second period acting as the interventions (in which the new model will be used). Baseline measurements including completion of the SF-12v2 will be obtained on initial assessment in the ED. Patient outcome data will then be collected for any subsequent hospitalisations. Data collection will conclude with a 6-week follow-up completion of two surveys (SF-12v2 and Client Services Receipt Inventory). Analysis of outcomes will focus on feasibility, acceptability and trial processes and will include recruitment and retention rates, attendance at clinician training rates and use of model in the ED. Qualitative feedback will be obtained through clinician interviews and a research nurse focus group. An evaluation of the feasibility of health economics outcomes data will be completed. Wales Research Ethics Committee 6 granted approval for the trial in September 2016. Patient recruitment will commence in February 2017. Planned dissemination is through publication in a peer-reviewed Emergency Medicine Journal , presentation at appropriate conferences and to stakeholders at professional meetings. ISRCTN95571506; Pre-results. © Article author(s) (or their

  11. Nonlinear Modeling of the PEMFC Based On NNARX Approach

    OpenAIRE

    Shan-Jen Cheng; Te-Jen Chang; Kuang-Hsiung Tan; Shou-Ling Kuo

    2015-01-01

    Polymer Electrolyte Membrane Fuel Cell (PEMFC) is such a time-vary nonlinear dynamic system. The traditional linear modeling approach is hard to estimate structure correctly of PEMFC system. From this reason, this paper presents a nonlinear modeling of the PEMFC using Neural Network Auto-regressive model with eXogenous inputs (NNARX) approach. The multilayer perception (MLP) network is applied to evaluate the structure of the NNARX model of PEMFC. The validity and accurac...

  12. Development of a Conservative Model Validation Approach for Reliable Analysis

    Science.gov (United States)

    2015-01-01

    CIE 2015 August 2-5, 2015, Boston, Massachusetts, USA [DRAFT] DETC2015-46982 DEVELOPMENT OF A CONSERVATIVE MODEL VALIDATION APPROACH FOR RELIABLE...obtain a conservative simulation model for reliable design even with limited experimental data. Very little research has taken into account the...3, the proposed conservative model validation is briefly compared to the conventional model validation approach. Section 4 describes how to account

  13. Comparison of two novel approaches to model fibre reinforced concrete

    NARCIS (Netherlands)

    Radtke, F.K.F.; Simone, A.; Sluys, L.J.

    2009-01-01

    We present two approaches to model fibre reinforced concrete. In both approaches, discrete fibre distributions and the behaviour of the fibre-matrix interface are explicitly considered. One approach employs the reaction forces from fibre to matrix while the other is based on the partition of unity

  14. Prognostic factors of breast cancer

    International Nuclear Information System (INIS)

    Gonzalez Ortega, Jose Maria; Morales Wong, Mario Miguel; Lopez Cuevas, Zoraida; Diaz Valdez, Marilin

    2011-01-01

    The prognostic factors must to be differentiated of the predictive ones. A prognostic factor is any measurement used at moment of the surgery correlated with the free interval of disease or global survival in the absence of the systemic adjuvant treatment and as result is able to correlate with the natural history of the disease. In contrast, a predictive factor is any measurement associated with the response to a given treatment. Among the prognostic factors of the breast cancer are included the clinical, histological, biological, genetic and psychosocial factors. In present review of psychosocial prognostic factors has been demonstrated that the stress and the depression are negative prognostic factors in patients presenting with breast cancer. It is essential to remember that the assessment of just one prognostic parameter is a help but it is not useful to clinical and therapeutic management of the patient.(author)

  15. Modeling thrombin generation: plasma composition based approach.

    Science.gov (United States)

    Brummel-Ziedins, Kathleen E; Everse, Stephen J; Mann, Kenneth G; Orfeo, Thomas

    2014-01-01

    Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.

  16. A simple approach to modeling ductile failure.

    Energy Technology Data Exchange (ETDEWEB)

    Wellman, Gerald William

    2012-06-01

    Sandia National Laboratories has the need to predict the behavior of structures after the occurrence of an initial failure. In some cases determining the extent of failure, beyond initiation, is required, while in a few cases the initial failure is a design feature used to tailor the subsequent load paths. In either case, the ability to numerically simulate the initiation and propagation of failures is a highly desired capability. This document describes one approach to the simulation of failure initiation and propagation.

  17. A new approach for modeling composite materials

    Science.gov (United States)

    Alcaraz de la Osa, R.; Moreno, F.; Saiz, J. M.

    2013-03-01

    The increasing use of composite materials is due to their ability to tailor materials for special purposes, with applications evolving day by day. This is why predicting the properties of these systems from their constituents, or phases, has become so important. However, assigning macroscopical optical properties for these materials from the bulk properties of their constituents is not a straightforward task. In this research, we present a spectral analysis of three-dimensional random composite typical nanostructures using an Extension of the Discrete Dipole Approximation (E-DDA code), comparing different approaches and emphasizing the influences of optical properties of constituents and their concentration. In particular, we hypothesize a new approach that preserves the individual nature of the constituents introducing at the same time a variation in the optical properties of each discrete element that is driven by the surrounding medium. The results obtained with this new approach compare more favorably with the experiment than previous ones. We have also applied it to a non-conventional material composed of a metamaterial embedded in a dielectric matrix. Our version of the Discrete Dipole Approximation code, the EDDA code, has been formulated specifically to tackle this kind of problem, including materials with either magnetic and tensor properties.

  18. An Integrated Approach to Modeling Evacuation Behavior

    Science.gov (United States)

    2011-02-01

    A spate of recent hurricanes and other natural disasters have drawn a lot of attention to the evacuation decision of individuals. Here we focus on evacuation models that incorporate two economic phenomena that seem to be increasingly important in exp...

  19. Infectious disease modeling a hybrid system approach

    CERN Document Server

    Liu, Xinzhi

    2017-01-01

    This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.

  20. On Combining Language Models: Oracle Approach

    National Research Council Canada - National Science Library

    Hacioglu, Kadri; Ward, Wayne

    2001-01-01

    In this paper, we address the of combining several language models (LMs). We find that simple interpolation methods, like log-linear and linear interpolation, improve the performance but fall short of the performance of an oracle...

  1. Advanced language modeling approaches, case study: Expert search

    NARCIS (Netherlands)

    Hiemstra, Djoerd

    2008-01-01

    This tutorial gives a clear and detailed overview of advanced language modeling approaches and tools, including the use of document priors, translation models, relevance models, parsimonious models and expectation maximization training. Expert search will be used as a case study to explain the

  2. Approaches to modelling hydrology and ecosystem interactions

    Science.gov (United States)

    Silberstein, Richard P.

    2014-05-01

    As the pressures of industry, agriculture and mining on groundwater resources increase there is a burgeoning un-met need to be able to capture these multiple, direct and indirect stresses in a formal framework that will enable better assessment of impact scenarios. While there are many catchment hydrological models and there are some models that represent ecological states and change (e.g. FLAMES, Liedloff and Cook, 2007), these have not been linked in any deterministic or substantive way. Without such coupled eco-hydrological models quantitative assessments of impacts from water use intensification on water dependent ecosystems under changing climate are difficult, if not impossible. The concept would include facility for direct and indirect water related stresses that may develop around mining and well operations, climate stresses, such as rainfall and temperature, biological stresses, such as diseases and invasive species, and competition such as encroachment from other competing land uses. Indirect water impacts could be, for example, a change in groundwater conditions has an impact on stream flow regime, and hence aquatic ecosystems. This paper reviews previous work examining models combining ecology and hydrology with a view to developing a conceptual framework linking a biophysically defensable model that combines ecosystem function with hydrology. The objective is to develop a model capable of representing the cumulative impact of multiple stresses on water resources and associated ecosystem function.

  3. Constructing a justice model based on Sen's capability approach

    OpenAIRE

    Yüksel, Sevgi; Yuksel, Sevgi

    2008-01-01

    The thesis provides a possible justice model based on Sen's capability approach. For this goal, we first analyze the general structure of a theory of justice, identifying the main variables and issues. Furthermore, based on Sen (2006) and Kolm (1998), we look at 'transcendental' and 'comparative' approaches to justice and concentrate on the sufficiency condition for the comparative approach. Then, taking Rawls' theory of justice as a starting point, we present how Sen's capability approach em...

  4. Challenges and opportunities for integrating lake ecosystem modelling approaches

    Science.gov (United States)

    Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B.R.; Degermendzhy, Andrey G.; DeAngelis, Donald L.; Domis, Lisette N. De Senerpont; Downing, Andrea S.; Elliott, J. Alex; Ruberto, Carlos Ruberto; Gaedke, Ursula; Genova, Svetlana N.; Gulati, Ramesh D.; Hakanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; Hoen, Jochem 't; Hulsmann, Stephan; Los, F. Hans; Makler-Pick, Vardit; Petzoldt, Thomas; Prokopkin, Igor G.; Rinke, Karsten; Schep, Sebastiaan A.; Tominaga, Koji; Van Dam, Anne A.; Van Nes, Egbert H.; Wells, Scott A.; Janse, Jan H.

    2010-01-01

    A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative

  5. An ontology-based approach for modelling architectural styles

    OpenAIRE

    Pahl, Claus; Giesecke, Simon; Hasselbring, Wilhelm

    2007-01-01

    peer-reviewed The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework.We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. Architect...

  6. Prognostic indices for brain metastases – usefulness and challenges

    Directory of Open Access Journals (Sweden)

    Nieder Carsten

    2009-03-01

    Full Text Available Abstract Background This review addresses the strengths and weaknesses of 6 different prognostic indices, published since the Radiation Therapy Oncology Group (RTOG developed and validated the widely used 3-tiered prognostic index known as recursive partitioning analysis (RPA classes, i.e. between 1997 and 2008. In addition, other analyses of prognostic factors in groups of patients, which typically are underrepresented in large trials or databases, published in the same time period are reviewed. Methods Based on a systematic literature search, studies with more than 20 patients were included. The methods and results of prognostic factor analyses were extracted and compared. The authors discuss why current data suggest a need for a more refined index than RPA. Results So far, none of the indices has been derived from analyses of all potential prognostic factors. The 3 most recently published indices, including the RTOG's graded prognostic assessment (GPA, all expanded from the primary 3-tiered RPA system to a 4-tiered system. The authors' own data confirm the results of the RTOG GPA analysis and support further evaluation of this tool. Conclusion This review provides a basis for further refinement of the current prognostic indices by identifying open questions regarding, e.g., performance of the ideal index, evaluation of new candidate parameters, and separate analyses for different cancer types. Unusual primary tumors and their potential differences in biology or unique treatment approaches are not well represented in large pooled analyses.

  7. Mathematical modelling a case studies approach

    CERN Document Server

    Illner, Reinhard; McCollum, Samantha; Roode, Thea van

    2004-01-01

    Mathematical modelling is a subject without boundaries. It is the means by which mathematics becomes useful to virtually any subject. Moreover, modelling has been and continues to be a driving force for the development of mathematics itself. This book explains the process of modelling real situations to obtain mathematical problems that can be analyzed, thus solving the original problem. The presentation is in the form of case studies, which are developed much as they would be in true applications. In many cases, an initial model is created, then modified along the way. Some cases are familiar, such as the evaluation of an annuity. Others are unique, such as the fascinating situation in which an engineer, armed only with a slide rule, had 24 hours to compute whether a valve would hold when a temporary rock plug was removed from a water tunnel. Each chapter ends with a set of exercises and some suggestions for class projects. Some projects are extensive, as with the explorations of the predator-prey model; oth...

  8. An Efficient Deterministic Approach to Model-based Prediction Uncertainty

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the...

  9. The simplified models approach to constraining supersymmetry

    Energy Technology Data Exchange (ETDEWEB)

    Perez, Genessis [Institut fuer Theoretische Physik, Karlsruher Institut fuer Technologie (KIT), Wolfgang-Gaede-Str. 1, 76131 Karlsruhe (Germany); Kulkarni, Suchita [Laboratoire de Physique Subatomique et de Cosmologie, Universite Grenoble Alpes, CNRS IN2P3, 53 Avenue des Martyrs, 38026 Grenoble (France)

    2015-07-01

    The interpretation of the experimental results at the LHC are model dependent, which implies that the searches provide limited constraints on scenarios such as supersymmetry (SUSY). The Simplified Models Spectra (SMS) framework used by ATLAS and CMS collaborations is useful to overcome this limitation. SMS framework involves a small number of parameters (all the properties are reduced to the mass spectrum, the production cross section and the branching ratio) and hence is more generic than presenting results in terms of soft parameters. In our work, the SMS framework was used to test Natural SUSY (NSUSY) scenario. To accomplish this task, two automated tools (SModelS and Fastlim) were used to decompose the NSUSY parameter space in terms of simplified models and confront the theoretical predictions against the experimental results. The achievement of both, just as the strengths and limitations, are here expressed for the NSUSY scenario.

  10. Lightweight approach to model traceability in a CASE tool

    Science.gov (United States)

    Vileiniskis, Tomas; Skersys, Tomas; Pavalkis, Saulius; Butleris, Rimantas; Butkiene, Rita

    2017-07-01

    A term "model-driven" is not at all a new buzzword within the ranks of system development community. Nevertheless, the ever increasing complexity of model-driven approaches keeps fueling all kinds of discussions around this paradigm and pushes researchers forward to research and develop new and more effective ways to system development. With the increasing complexity, model traceability, and model management as a whole, becomes indispensable activities of model-driven system development process. The main goal of this paper is to present a conceptual design and implementation of a practical lightweight approach to model traceability in a CASE tool.

  11. Prognostic factors for medulloblastoma

    International Nuclear Information System (INIS)

    Jenkin, Derek; Al Shabanah, Mohamed; Al Shail, Essam; Gray, Alan; Hassounah, Maher; Khafaga, Yasser; Kofide, Amani; Mustafa, Mahmoud; Schultz, Henrik

    2000-01-01

    Purpose: To evaluate prognostic factors for medulloblastoma. Methods and Materials: One hundred and seventy-three consecutive patients with medulloblastoma, treated at King Faisal Specialist Hospital (KFSH) from 1988-1997, were reviewed. Eighty-four percent were children less than 15 years old. From 1988-1994, treatment was at the discretion of the investigator. From 1994-1998, patients entered a single-arm best practice protocol in which, in staged patients, the surgical intent was total resection, standard radiation treatment was defined, and adjuvant chemotherapy was given to a 'high-risk' subset. Results: For 150 patients who completed surgical and radiation treatment, the 5-year survival rate was 58%, compared with 0% for 16 patients who were unable to start or complete radiation treatment. For staged patients, the 5-year survival was M0 + M1, 78% and M2 + M3, 21% (p 14 years and gross cystic/necrotic features in the primary tumor. The size of the primary tumor, the degree of hydrocephalus at diagnosis, the presence of residual tumor in the post-operative CT/MRI, and the functional status of the patient prior to radiation treatment were not significant factors. Conclusions: Stage M0 + M1 was the most powerful favorable prognostic factor. In Saudi Arabia more patients present with advanced disseminated disease, 41% M2 + M3, than in the West, and this impacts adversely on overall survival. Total resection and standard radiation treatment were not sensitive prognostic factors in a treatment environment in which 78% of patients underwent at least 90% tumor resection and 60% received standard radiation treatment. In order to improve the proportion of patients able to complete radiation treatment, consideration should be given to limiting resection when the attainment of total resection is likely to be morbid, and to delaying rather than omitting radiation treatment in the patient severely compromised postoperatively

  12. New approaches for modeling type Ia supernovae

    International Nuclear Information System (INIS)

    Zingale, Michael; Almgren, Ann S.; Bell, John B.; Day, Marcus S.; Rendleman, Charles A.; Woosley, Stan

    2007-01-01

    Type Ia supernovae (SNe Ia) are the largest thermonuclear explosions in the Universe. Their light output can be seen across great distances and has led to the discovery that the expansion rate of the Universe is accelerating. Despite the significance of SNe Ia, there are still a large number of uncertainties in current theoretical models. Computational modeling offers the promise to help answer the outstanding questions. However, even with today's supercomputers, such calculations are extremely challenging because of the wide range of length and timescales. In this paper, we discuss several new algorithms for simulations of SNe Ia and demonstrate some of their successes

  13. Chancroid transmission dynamics: a mathematical modeling approach.

    Science.gov (United States)

    Bhunu, C P; Mushayabasa, S

    2011-12-01

    Mathematical models have long been used to better understand disease transmission dynamics and how to effectively control them. Here, a chancroid infection model is presented and analyzed. The disease-free equilibrium is shown to be globally asymptotically stable when the reproduction number is less than unity. High levels of treatment are shown to reduce the reproduction number suggesting that treatment has the potential to control chancroid infections in any given community. This result is also supported by numerical simulations which show a decline in chancroid cases whenever the reproduction number is less than unity.

  14. A kinetic approach to magnetospheric modeling

    International Nuclear Information System (INIS)

    Whipple, E.C. Jr.

    1979-01-01

    The earth's magnetosphere is caused by the interaction between the flowing solar wind and the earth's magnetic dipole, with the distorted magnetic field in the outer parts of the magnetosphere due to the current systems resulting from this interaction. It is surprising that even the conceptually simple problem of the collisionless interaction of a flowing plasma with a dipole magnetic field has not been solved. A kinetic approach is essential if one is to take into account the dispersion of particles with different energies and pitch angles and the fact that particles on different trajectories have different histories and may come from different sources. Solving the interaction problem involves finding the various types of possible trajectories, populating them with particles appropriately, and then treating the electric and magnetic fields self-consistently with the resulting particle densities and currents. This approach is illustrated by formulating a procedure for solving the collisionless interaction problem on open field lines in the case of a slowly flowing magnetized plasma interacting with a magnetic dipole

  15. A kinetic approach to magnetospheric modeling

    Science.gov (United States)

    Whipple, E. C., Jr.

    1979-01-01

    The earth's magnetosphere is caused by the interaction between the flowing solar wind and the earth's magnetic dipole, with the distorted magnetic field in the outer parts of the magnetosphere due to the current systems resulting from this interaction. It is surprising that even the conceptually simple problem of the collisionless interaction of a flowing plasma with a dipole magnetic field has not been solved. A kinetic approach is essential if one is to take into account the dispersion of particles with different energies and pitch angles and the fact that particles on different trajectories have different histories and may come from different sources. Solving the interaction problem involves finding the various types of possible trajectories, populating them with particles appropriately, and then treating the electric and magnetic fields self-consistently with the resulting particle densities and currents. This approach is illustrated by formulating a procedure for solving the collisionless interaction problem on open field lines in the case of a slowly flowing magnetized plasma interacting with a magnetic dipole.

  16. Fractal approach to computer-analytical modelling of tree crown

    International Nuclear Information System (INIS)

    Berezovskaya, F.S.; Karev, G.P.; Kisliuk, O.F.; Khlebopros, R.G.; Tcelniker, Yu.L.

    1993-09-01

    In this paper we discuss three approaches to the modeling of a tree crown development. These approaches are experimental (i.e. regressive), theoretical (i.e. analytical) and simulation (i.e. computer) modeling. The common assumption of these is that a tree can be regarded as one of the fractal objects which is the collection of semi-similar objects and combines the properties of two- and three-dimensional bodies. We show that a fractal measure of crown can be used as the link between the mathematical models of crown growth and light propagation through canopy. The computer approach gives the possibility to visualize a crown development and to calibrate the model on experimental data. In the paper different stages of the above-mentioned approaches are described. The experimental data for spruce, the description of computer system for modeling and the variant of computer model are presented. (author). 9 refs, 4 figs

  17. Systematic review of renal carcinoma prognostic factors.

    Science.gov (United States)

    Lorente, D; Trilla, E; Meseguer, A; Planas, J; Placer, J; Celma, A; Salvador, C; Regis, L; Morote, J

    2017-05-01

    The natural history of renal cell carcinoma is heterogeneous. Some scenarios can be found in terms of clinical presentation, clinical evolution or type of recurrence (local/metastatic). The aim of this publication is to analyze the most important prognostic factors published in the literature. A literature review ob published papers was performed using the Pubmed, from first Motzer's classification published in 1999 to 2015, according to PRISMA declaration. Search was done using the following keywords: kidney neoplasm, kidney cancer, renal cell carcinoma, prognostic factors, mortality, survival and disease progression. Papers were classified according to level of evidence, the number of patients included and the type of study performed. The evolution in the knowledge of molecular pathways related to renal oncogenesis and the new targeted therapies has left to remain obsolete the old prognostic models. It's necessary to perform a continuous review to actualize nomograms and to adapt them to the new scenarios. Is necessary to perform a proper external validation of existing prognostic factors using prospective and multicentric studies to add them into the daily urologist clinical practice. Copyright © 2016 AEU. Publicado por Elsevier España, S.L.U. All rights reserved.

  18. A novel approach to modeling atmospheric convection

    Science.gov (United States)

    Goodman, A.

    2016-12-01

    The inadequate representation of clouds continues to be a large source of uncertainty in the projections from global climate models (GCMs). With continuous advances in computational power, however, the ability for GCMs to explicitly resolve cumulus convection will soon be realized. For this purpose, Jung and Arakawa (2008) proposed the Vector Vorticity Model (VVM), in which vorticity is the predicted variable instead of momentum. This has the advantage of eliminating the pressure gradient force within the framework of an anelastic system. However, the VVM was designed for use on a planar quadrilateral grid, making it unsuitable for implementation in global models discretized on the sphere. Here we have proposed a modification to the VVM where instead the curl of the horizontal vorticity is the primary predicted variable. This allows us to maintain the benefits of the original VVM while working within the constraints of a non-quadrilateral mesh. We found that our proposed model produced results from a warm bubble simulation that were consistent with the VVM. Further improvements that can be made to the VVM are also discussed.

  19. INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

    Science.gov (United States)

    Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

  20. A new approach to model mixed hydrates

    Czech Academy of Sciences Publication Activity Database

    Hielscher, S.; Vinš, Václav; Jäger, A.; Hrubý, Jan; Breitkopf, C.; Span, R.

    2018-01-01

    Roč. 459, March (2018), s. 170-185 ISSN 0378-3812 R&D Projects: GA ČR(CZ) GA17-08218S Institutional support: RVO:61388998 Keywords : gas hydrate * mixture * modeling Subject RIV: BJ - Thermodynamics Impact factor: 2.473, year: 2016 https://www.sciencedirect.com/science/article/pii/S0378381217304983

  1. Energy and development : A modelling approach

    NARCIS (Netherlands)

    van Ruijven, B.J.|info:eu-repo/dai/nl/304834521

    2008-01-01

    Rapid economic growth of developing countries like India and China implies that these countries become important actors in the global energy system. Examples of this impact are the present day oil shortages and rapidly increasing emissions of greenhouse gases. Global energy models are used explore

  2. Modeling Approaches for Describing Microbial Population Heterogeneity

    DEFF Research Database (Denmark)

    Lencastre Fernandes, Rita

    environmental conditions. Three cases are presented and discussed in this thesis. Common to all is the use of S. cerevisiae as model organism, and the use of cell size and cell cycle position as single-cell descriptors. The first case focuses on the experimental and mathematical description of a yeast...

  3. Energy and Development. A Modelling Approach

    International Nuclear Information System (INIS)

    Van Ruijven, B.J.

    2008-01-01

    Rapid economic growth of developing countries like India and China implies that these countries become important actors in the global energy system. Examples of this impact are the present day oil shortages and rapidly increasing emissions of greenhouse gases. Global energy models are used to explore possible future developments of the global energy system and identify policies to prevent potential problems. Such estimations of future energy use in developing countries are very uncertain. Crucial factors in the future energy use of these regions are electrification, urbanisation and income distribution, issues that are generally not included in present day global energy models. Model simulations in this thesis show that current insight in developments in low-income regions lead to a wide range of expected energy use in 2030 of the residential and transport sectors. This is mainly caused by many different model calibration options that result from the limited data availability for model development and calibration. We developed a method to identify the impact of model calibration uncertainty on future projections. We developed a new model for residential energy use in India, in collaboration with the Indian Institute of Science. Experiments with this model show that the impact of electrification and income distribution is less univocal than often assumed. The use of fuelwood, with related health risks, can decrease rapidly if the income of poor groups increases. However, there is a trade off in terms of CO2 emissions because these groups gain access to electricity and the ownership of appliances increases. Another issue is the potential role of new technologies in developing countries: will they use the opportunities of leapfrogging? We explored the potential role of hydrogen, an energy carrier that might play a central role in a sustainable energy system. We found that hydrogen only plays a role before 2050 under very optimistic assumptions. Regional energy

  4. Integration models: multicultural and liberal approaches confronted

    Science.gov (United States)

    Janicki, Wojciech

    2012-01-01

    European societies have been shaped by their Christian past, upsurge of international migration, democratic rule and liberal tradition rooted in religious tolerance. Boosting globalization processes impose new challenges on European societies, striving to protect their diversity. This struggle is especially clearly visible in case of minorities trying to resist melting into mainstream culture. European countries' legal systems and cultural policies respond to these efforts in many ways. Respecting identity politics-driven group rights seems to be the most common approach, resulting in creation of a multicultural society. However, the outcome of respecting group rights may be remarkably contradictory to both individual rights growing out from liberal tradition, and to reinforced concept of integration of immigrants into host societies. The hereby paper discusses identity politics upturn in the context of both individual rights and integration of European societies.

  5. Modelling thermal plume impacts - Kalpakkam approach

    International Nuclear Information System (INIS)

    Rao, T.S.; Anup Kumar, B.; Narasimhan, S.V.

    2002-01-01

    A good understanding of temperature patterns in the receiving waters is essential to know the heat dissipation from thermal plumes originating from coastal power plants. The seasonal temperature profiles of the Kalpakkam coast near Madras Atomic Power Station (MAPS) thermal out fall site are determined and analysed. It is observed that the seasonal current reversal in the near shore zone is one of the major mechanisms for the transport of effluents away from the point of mixing. To further refine our understanding of the mixing and dilution processes, it is necessary to numerically simulate the coastal ocean processes by parameterising the key factors concerned. In this paper, we outline the experimental approach to achieve this objective. (author)

  6. Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

    Energy Technology Data Exchange (ETDEWEB)

    Liao, James C. [Univ. of California, Los Angeles, CA (United States)

    2016-10-01

    Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

  7. Nuclear security assessment with Markov model approach

    International Nuclear Information System (INIS)

    Suzuki, Mitsutoshi; Terao, Norichika

    2013-01-01

    Nuclear security risk assessment with the Markov model based on random event is performed to explore evaluation methodology for physical protection in nuclear facilities. Because the security incidences are initiated by malicious and intentional acts, expert judgment and Bayes updating are used to estimate scenario and initiation likelihood, and it is assumed that the Markov model derived from stochastic process can be applied to incidence sequence. Both an unauthorized intrusion as Design Based Threat (DBT) and a stand-off attack as beyond-DBT are assumed to hypothetical facilities, and performance of physical protection and mitigation and minimization of consequence are investigated to develop the assessment methodology in a semi-quantitative manner. It is shown that cooperation between facility operator and security authority is important to respond to the beyond-DBT incidence. (author)

  8. An Approach for Modeling Supplier Resilience

    Science.gov (United States)

    2016-04-30

    interests include resilience modeling of supply chains, reliability engineering, and meta- heuristic optimization. [m.hosseini@ou.edu] Abstract...be availability , or the extent to which the products produced by the supply chain are available for use (measured as a ratio of uptime to total time...of the use of the product). Available systems are important in many industries, particularly in the Department of Defense, where weapons systems

  9. Tumour resistance to cisplatin: a modelling approach

    International Nuclear Information System (INIS)

    Marcu, L; Bezak, E; Olver, I; Doorn, T van

    2005-01-01

    Although chemotherapy has revolutionized the treatment of haematological tumours, in many common solid tumours the success has been limited. Some of the reasons for the limitations are: the timing of drug delivery, resistance to the drug, repopulation between cycles of chemotherapy and the lack of complete understanding of the pharmacokinetics and pharmacodynamics of a specific agent. Cisplatin is among the most effective cytotoxic agents used in head and neck cancer treatments. When modelling cisplatin as a single agent, the properties of cisplatin only have to be taken into account, reducing the number of assumptions that are considered in the generalized chemotherapy models. The aim of the present paper is to model the biological effect of cisplatin and to simulate the consequence of cisplatin resistance on tumour control. The 'treated' tumour is a squamous cell carcinoma of the head and neck, previously grown by computer-based Monte Carlo techniques. The model maintained the biological constitution of a tumour through the generation of stem cells, proliferating cells and non-proliferating cells. Cell kinetic parameters (mean cell cycle time, cell loss factor, thymidine labelling index) were also consistent with the literature. A sensitivity study on the contribution of various mechanisms leading to drug resistance is undertaken. To quantify the extent of drug resistance, the cisplatin resistance factor (CRF) is defined as the ratio between the number of surviving cells of the resistant population and the number of surviving cells of the sensitive population, determined after the same treatment time. It is shown that there is a supra-linear dependence of CRF on the percentage of cisplatin-DNA adducts formed, and a sigmoid-like dependence between CRF and the percentage of cells killed in resistant tumours. Drug resistance is shown to be a cumulative process which eventually can overcome tumour regression leading to treatment failure

  10. Tumour resistance to cisplatin: a modelling approach

    Energy Technology Data Exchange (ETDEWEB)

    Marcu, L [School of Chemistry and Physics, University of Adelaide, North Terrace, SA 5000 (Australia); Bezak, E [School of Chemistry and Physics, University of Adelaide, North Terrace, SA 5000 (Australia); Olver, I [Faculty of Medicine, University of Adelaide, North Terrace, SA 5000 (Australia); Doorn, T van [School of Chemistry and Physics, University of Adelaide, North Terrace, SA 5000 (Australia)

    2005-01-07

    Although chemotherapy has revolutionized the treatment of haematological tumours, in many common solid tumours the success has been limited. Some of the reasons for the limitations are: the timing of drug delivery, resistance to the drug, repopulation between cycles of chemotherapy and the lack of complete understanding of the pharmacokinetics and pharmacodynamics of a specific agent. Cisplatin is among the most effective cytotoxic agents used in head and neck cancer treatments. When modelling cisplatin as a single agent, the properties of cisplatin only have to be taken into account, reducing the number of assumptions that are considered in the generalized chemotherapy models. The aim of the present paper is to model the biological effect of cisplatin and to simulate the consequence of cisplatin resistance on tumour control. The 'treated' tumour is a squamous cell carcinoma of the head and neck, previously grown by computer-based Monte Carlo techniques. The model maintained the biological constitution of a tumour through the generation of stem cells, proliferating cells and non-proliferating cells. Cell kinetic parameters (mean cell cycle time, cell loss factor, thymidine labelling index) were also consistent with the literature. A sensitivity study on the contribution of various mechanisms leading to drug resistance is undertaken. To quantify the extent of drug resistance, the cisplatin resistance factor (CRF) is defined as the ratio between the number of surviving cells of the resistant population and the number of surviving cells of the sensitive population, determined after the same treatment time. It is shown that there is a supra-linear dependence of CRF on the percentage of cisplatin-DNA adducts formed, and a sigmoid-like dependence between CRF and the percentage of cells killed in resistant tumours. Drug resistance is shown to be a cumulative process which eventually can overcome tumour regression leading to treatment failure.

  11. ISM Approach to Model Offshore Outsourcing Risks

    Directory of Open Access Journals (Sweden)

    Sunand Kumar

    2014-07-01

    Full Text Available In an effort to achieve a competitive advantage via cost reductions and improved market responsiveness, organizations are increasingly employing offshore outsourcing as a major component of their supply chain strategies. But as evident from literature number of risks such as Political risk, Risk due to cultural differences, Compliance and regulatory risk, Opportunistic risk and Organization structural risk, which adversely affect the performance of offshore outsourcing in a supply chain network. This also leads to dissatisfaction among different stake holders. The main objective of this paper is to identify and understand the mutual interaction among various risks which affect the performance of offshore outsourcing.  To this effect, authors have identified various risks through extant review of literature.  From this information, an integrated model using interpretive structural modelling (ISM for risks affecting offshore outsourcing is developed and the structural relationships between these risks are modeled.  Further, MICMAC analysis is done to analyze the driving power and dependency of risks which shall be helpful to managers to identify and classify important criterions and to reveal the direct and indirect effects of each criterion on offshore outsourcing. Results show that political risk and risk due to cultural differences are act as strong drivers.

  12. Remote sensing approach to structural modelling

    International Nuclear Information System (INIS)

    El Ghawaby, M.A.

    1989-01-01

    Remote sensing techniques are quite dependable tools in investigating geologic problems, specially those related to structural aspects. The Landsat imagery provides discrimination between rock units, detection of large scale structures as folds and faults, as well as small scale fabric elements such as foliation and banding. In order to fulfill the aim of geologic application of remote sensing, some essential surveying maps might be done from images prior to the structural interpretation: land-use, land-form drainage pattern, lithological unit and structural lineament maps. Afterwards, the field verification should lead to interpretation of a comprehensive structural model of the study area to apply for the target problem. To deduce such a model, there are two ways of analysis the interpreter may go through: the direct and the indirect methods. The direct one is needed in cases where the resources or the targets are controlled by an obvious or exposed structural element or pattern. The indirect way is necessary for areas where the target is governed by a complicated structural pattern. Some case histories of structural modelling methods applied successfully for exploration of radioactive minerals, iron deposits and groundwater aquifers in Egypt are presented. The progress in imagery, enhancement and integration of remote sensing data with the other geophysical and geochemical data allow a geologic interpretation to be carried out which become better than that achieved with either of the individual data sets. 9 refs

  13. Development and validation of a prognostic model to predict death in patients with traumatic bleeding, and evaluation of the effect of tranexamic acid on mortality according to baseline risk: a secondary analysis of a randomised controlled trial.

    Science.gov (United States)

    Perel, P; Prieto-Merino, D; Shakur, H; Roberts, I

    2013-06-01

    Severe bleeding accounts for about one-third of in-hospital trauma deaths. Patients with a high baseline risk of death have the most to gain from the use of life-saving treatments. An accurate and user-friendly prognostic model to predict mortality in bleeding trauma patients could assist doctors and paramedics in pre-hospital triage and could shorten the time to diagnostic and life-saving procedures such as surgery and tranexamic acid (TXA). The aim of the study was to develop and validate a prognostic model for early mortality in patients with traumatic bleeding and to examine whether or not the effect of TXA on the risk of death and thrombotic events in bleeding adult trauma patients varies according to baseline risk. Multivariable logistic regression and risk-stratified analysis of a large international cohort of trauma patients. Two hundred and seventy-four hospitals in 40 high-, medium- and low-income countries. We derived prognostic models in a large placebo-controlled trial of the effects of early administration of a short course of TXA [Clinical Randomisation of an Antifibrinolytic in Significant Haemorrhage (CRASH-2) trial]. The trial included 20,127 trauma patients with, or at risk of, significant bleeding, within 8 hours of injury. We externally validated the model on 14,220 selected trauma patients from the Trauma Audit and Research Network (TARN), which included mainly patients from the UK. We examined the effect of TXA on all-cause mortality, death due to bleeding and thrombotic events (fatal and non-fatal myocardial infarction, stroke, deep-vein thrombosis and pulmonary embolism) within risk strata in the CRASH-2 trial data set and we estimated the proportion of premature deaths averted by applying the odds ratio (OR) from the CRASH-2 trial to each of the risk strata in TARN. For the stratified analysis according baseline risk we considered the intervention TXA (1 g over 10 minutes followed by 1 g over 8 hours) or matching placebo. For the

  14. A moving approach for the Vector Hysteron Model

    Energy Technology Data Exchange (ETDEWEB)

    Cardelli, E. [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Faba, A., E-mail: antonio.faba@unipg.it [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Laudani, A. [Department of Engineering, Roma Tre University, Via V. Volterra 62, 00146 Rome (Italy); Quondam Antonio, S. [Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia (Italy); Riganti Fulginei, F.; Salvini, A. [Department of Engineering, Roma Tre University, Via V. Volterra 62, 00146 Rome (Italy)

    2016-04-01

    A moving approach for the VHM (Vector Hysteron Model) is here described, to reconstruct both scalar and rotational magnetization of electrical steels with weak anisotropy, such as the non oriented grain Silicon steel. The hysterons distribution is postulated to be function of the magnetization state of the material, in order to overcome the practical limitation of the congruency property of the standard VHM approach. By using this formulation and a suitable accommodation procedure, the results obtained indicate that the model is accurate, in particular in reproducing the experimental behavior approaching to the saturation region, allowing a real improvement respect to the previous approach.

  15. Agribusiness model approach to territorial food development

    Directory of Open Access Journals (Sweden)

    Murcia Hector Horacio

    2011-04-01

    Full Text Available

    Several research efforts have coordinated the academic program of Agricultural Business Management from the University De La Salle (Bogota D.C., to the design and implementation of a sustainable agribusiness model applied to food development, with territorial projection. Rural development is considered as a process that aims to improve the current capacity and potential of the inhabitant of the sector, which refers not only to production levels and productivity of agricultural items. It takes into account the guidelines of the Organization of the United Nations “Millennium Development Goals” and considered the concept of sustainable food and agriculture development, including food security and nutrition in an integrated interdisciplinary context, with holistic and systemic dimension. Analysis is specified by a model with an emphasis on sustainable agribusiness production chains related to agricultural food items in a specific region. This model was correlated with farm (technical objectives, family (social purposes and community (collective orientations projects. Within this dimension are considered food development concepts and methodologies of Participatory Action Research (PAR. Finally, it addresses the need to link the results to low-income communities, within the concepts of the “new rurality”.

  16. Engineering approach to modeling of piled systems

    International Nuclear Information System (INIS)

    Coombs, R.F.; Silva, M.A.G. da

    1980-01-01

    Available methods of analysis of piled systems subjected to dynamic excitation invade areas of mathematics usually beyond the reach of a practising engineer. A simple technique that avoids that conflict is proposed, at least for preliminary studies, and its application, compared with other methods, is shown to be satisfactory. A corrective factor for parameters currently used to represent transmitting boundaries is derived for a finite strip that models an infinite layer. The influence of internal damping on the dynamic stiffness of the layer and on radiation damping is analysed. (Author) [pt

  17. Jackiw-Pi model: A superfield approach

    Science.gov (United States)

    Gupta, Saurabh

    2014-12-01

    We derive the off-shell nilpotent and absolutely anticommuting Becchi-Rouet-Stora-Tyutin (BRST) as well as anti-BRST transformations s ( a) b corresponding to the Yang-Mills gauge transformations of 3D Jackiw-Pi model by exploiting the "augmented" super-field formalism. We also show that the Curci-Ferrari restriction, which is a hallmark of any non-Abelian 1-form gauge theories, emerges naturally within this formalism and plays an instrumental role in providing the proof of absolute anticommutativity of s ( a) b .

  18. Applied Regression Modeling A Business Approach

    CERN Document Server

    Pardoe, Iain

    2012-01-01

    An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a

  19. Prognostic factors in lupus nephritis

    DEFF Research Database (Denmark)

    Faurschou, Mikkel; Starklint, Henrik; Halberg, Poul

    2006-01-01

    To evaluate the prognostic significance of clinical and renal biopsy findings in an unselected cohort of patients with systemic lupus erythematosus (SLE) and nephritis.......To evaluate the prognostic significance of clinical and renal biopsy findings in an unselected cohort of patients with systemic lupus erythematosus (SLE) and nephritis....

  20. Implicit moral evaluations: A multinomial modeling approach.

    Science.gov (United States)

    Cameron, C Daryl; Payne, B Keith; Sinnott-Armstrong, Walter; Scheffer, Julian A; Inzlicht, Michael

    2017-01-01

    Implicit moral evaluations-i.e., immediate, unintentional assessments of the wrongness of actions or persons-play a central role in supporting moral behavior in everyday life. Yet little research has employed methods that rigorously measure individual differences in implicit moral evaluations. In five experiments, we develop a new sequential priming measure-the Moral Categorization Task-and a multinomial model that decomposes judgment on this task into multiple component processes. These include implicit moral evaluations of moral transgression primes (Unintentional Judgment), accurate moral judgments about target actions (Intentional Judgment), and a directional tendency to judge actions as morally wrong (Response Bias). Speeded response deadlines reduced Intentional Judgment but not Unintentional Judgment (Experiment 1). Unintentional Judgment was stronger toward moral transgression primes than non-moral negative primes (Experiments 2-4). Intentional Judgment was associated with increased error-related negativity, a neurophysiological indicator of behavioral control (Experiment 4). Finally, people who voted for an anti-gay marriage amendment had stronger Unintentional Judgment toward gay marriage primes (Experiment 5). Across Experiments 1-4, implicit moral evaluations converged with moral personality: Unintentional Judgment about wrong primes, but not negative primes, was negatively associated with psychopathic tendencies and positively associated with moral identity and guilt proneness. Theoretical and practical applications of formal modeling for moral psychology are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Modeling Saturn's Inner Plasmasphere: Cassini's Closest Approach

    Science.gov (United States)

    Moore, L.; Mendillo, M.

    2005-05-01

    Ion densities from the three-dimensional Saturn-Thermosphere-Ionosphere-Model (STIM, Moore et al., 2004) are extended above the plasma exobase using the formalism of Pierrard and Lemaire (1996, 1998), which evaluates the balance of gravitational, centrifugal and electric forces on the plasma. The parameter space of low-energy ionospheric contributions to Saturn's plasmasphere is explored by comparing results that span the observed extremes of plasma temperature, 650 K to 1700 K, and a range of velocity distributions, Lorentzian (or Kappa) to Maxwellian. Calculations are made for plasma densities along the path of the Cassini spacecraft's orbital insertion on 1 July 2004. These calculations neglect any ring or satellite sources of plasma, which are most likely minor contributors at 1.3 Saturn radii. Modeled densities will be compared with Cassini measurements as they become available. Moore, L.E., M. Mendillo, I.C.F. Mueller-Wodarg, and D.L. Murr, Icarus, 172, 503-520, 2004. Pierrard, V. and J. Lemaire, J. Geophys. Res., 101, 7923-7934, 1996. Pierrard, V. and J. Lemaire, J. Geophys. Res., 103, 4117, 1998.

  2. Keyring models: An approach to steerability

    Science.gov (United States)

    Miller, Carl A.; Colbeck, Roger; Shi, Yaoyun

    2018-02-01

    If a measurement is made on one half of a bipartite system, then, conditioned on the outcome, the other half has a new reduced state. If these reduced states defy classical explanation—that is, if shared randomness cannot produce these reduced states for all possible measurements—the bipartite state is said to be steerable. Determining which states are steerable is a challenging problem even for low dimensions. In the case of two-qubit systems, a criterion is known for T-states (that is, those with maximally mixed marginals) under projective measurements. In the current work, we introduce the concept of keyring models—a special class of local hidden state models. When the measurements made correspond to real projectors, these allow us to study steerability beyond T-states. Using keyring models, we completely solve the steering problem for real projective measurements when the state arises from mixing a pure two-qubit state with uniform noise. We also give a partial solution in the case when the uniform noise is replaced by independent depolarizing channels.

  3. Elevated neutrophil and monocyte counts in peripheral blood are associated with poor survival in patients with metastatic melanoma: a prognostic model

    DEFF Research Database (Denmark)

    Schmidt, H; Bastholt, L; Geertsen, P

    2005-01-01

    factors in univariate analyses. Subsequently, a multivariate Cox's regression analysis identified elevated LDH (Pperformance status of 2 (P=0.008, hazard ratio 1.6) as independent prognostic factors for poor survival...... of several phase II protocols and the majority received treatment with intermediate dose subcutaneous IL-2 and interferon-alpha. Neutrophil and monocyte counts, lactate dehydrogenase (LDH), number of metastatic sites, location of metastases and performance status were all statistically significant prognostic...... survival of 12.6 months (95% confidence interval (CI), 11.4-13.8), 6.0 months (95% CI, 4.8-7.2) and 3.4 months (95% CI, 1.2-5.6), respectively. The low-risk group encompassed the majority of long-term survivors, whereas the patients in the high-risk group with a very poor prognosis should probably...

  4. Mathematical Modeling in Mathematics Education: Basic Concepts and Approaches

    Science.gov (United States)

    Erbas, Ayhan Kürsat; Kertil, Mahmut; Çetinkaya, Bülent; Çakiroglu, Erdinç; Alacaci, Cengiz; Bas, Sinem

    2014-01-01

    Mathematical modeling and its role in mathematics education have been receiving increasing attention in Turkey, as in many other countries. The growing body of literature on this topic reveals a variety of approaches to mathematical modeling and related concepts, along with differing perspectives on the use of mathematical modeling in teaching and…

  5. A BEHAVIORAL-APPROACH TO LINEAR EXACT MODELING

    NARCIS (Netherlands)

    ANTOULAS, AC; WILLEMS, JC

    1993-01-01

    The behavioral approach to system theory provides a parameter-free framework for the study of the general problem of linear exact modeling and recursive modeling. The main contribution of this paper is the solution of the (continuous-time) polynomial-exponential time series modeling problem. Both

  6. A modular approach to numerical human body modeling

    NARCIS (Netherlands)

    Forbes, P.A.; Griotto, G.; Rooij, L. van

    2007-01-01

    The choice of a human body model for a simulated automotive impact scenario must take into account both accurate model response and computational efficiency as key factors. This study presents a "modular numerical human body modeling" approach which allows the creation of a customized human body

  7. A Bayesian approach for quantification of model uncertainty

    International Nuclear Information System (INIS)

    Park, Inseok; Amarchinta, Hemanth K.; Grandhi, Ramana V.

    2010-01-01

    In most engineering problems, more than one model can be created to represent an engineering system's behavior. Uncertainty is inevitably involved in selecting the best model from among the models that are possible. Uncertainty in model selection cannot be ignored, especially when the differences between the predictions of competing models are significant. In this research, a methodology is proposed to quantify model uncertainty using measured differences between experimental data and model outcomes under a Bayesian statistical framework. The adjustment factor approach is used to propagate model uncertainty into prediction of a system response. A nonlinear vibration system is used to demonstrate the processes for implementing the adjustment factor approach. Finally, the methodology is applied on the engineering benefits of a laser peening process, and a confidence band for residual stresses is established to indicate the reliability of model prediction.

  8. A Networks Approach to Modeling Enzymatic Reactions.

    Science.gov (United States)

    Imhof, P

    2016-01-01

    Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.

  9. Carbonate rock depositional models: A microfacies approach

    Energy Technology Data Exchange (ETDEWEB)

    Carozzi, A.V.

    1988-01-01

    Carbonate rocks contain more than 50% by weight carbonate minerals such as calcite, dolomite, and siderite. Understanding how these rocks form can lead to more efficient methods of petroleum exploration. Micofacies analysis techniques can be used as a method of predicting models of sedimentation for carbonate rocks. Micofacies in carbonate rocks can be seen clearly only in thin sections under a microscope. This section analysis of carbonate rocks is a tool that can be used to understand depositional environments, diagenetic evolution of carbonate rocks, and the formation of porosity and permeability in carbonate rocks. The use of micofacies analysis techniques is applied to understanding the origin and formation of carbonate ramps, carbonate platforms, and carbonate slopes and basins. This book will be of interest to students and professionals concerned with the disciplines of sedimentary petrology, sedimentology, petroleum geology, and palentology.

  10. Accelerated Aging with Electrical Overstress and Prognostics for Power MOSFETs

    Science.gov (United States)

    Saha, Sankalita; Celaya, Jose Ramon; Vashchenko, Vladislav; Mahiuddin, Shompa; Goebel, Kai F.

    2011-01-01

    Power electronics play an increasingly important role in energy applications as part of their power converter circuits. Understanding the behavior of these devices, especially their failure modes as they age with nominal usage or sudden fault development is critical in ensuring efficiency. In this paper, a prognostics based health management of power MOSFETs undergoing accelerated aging through electrical overstress at the gate area is presented. Details of the accelerated aging methodology, modeling of the degradation process of the device and prognostics algorithm for prediction of the future state of health of the device are presented. Experiments with multiple devices demonstrate the performance of the model and the prognostics algorithm as well as the scope of application. Index Terms Power MOSFET, accelerated aging, prognostics

  11. Risk prediction model: Statistical and artificial neural network approach

    Science.gov (United States)

    Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

    2017-04-01

    Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

  12. Localized primary gastrointestinal diffuse large B cell lymphoma received a surgical approach: an analysis of prognostic factors and comparison of staging systems in 101 patients from a single institution.

    Science.gov (United States)

    Zhang, Shengting; Wang, Li; Yu, Dong; Shen, Yang; Cheng, Shu; Zhang, Li; Qian, Ying; Shen, Zhixiang; Li, Qinyu; Zhao, Weili

    2015-08-15

    Diffuse large B cell lymphoma (DLBCL) represents the most common histological subtype of primary gastrointestinal lymphoma and is a heterogeneous group of disease. Prognostic characterization of individual patients is an essential prerequisite for a proper risk-based therapeutic choice. Clinical and pathological prognostic factors were identified, and predictive value of four previously described prognostic systems were assessed in 101 primary gastrointestinal DLBCL (PG-DLBCL) patients with localized disease, including Ann Arbor staging with Musshoff modification, International Prognostic Index (IPI), Lugano classification, and Paris staging system. Univariate factors correlated with inferior survival time were clinical parameters [age>60 years old, multiple extranodal/gastrointestinal involvement, elevated serum lactate dehydrogenase and β2-microglobulin, and decreased serum albumin], as well as pathological parameters (invasion depth beyond serosa, involvement of regional lymph node or adjacent tissue, Ki-67 index, and Bcl-2 expression). Major independent variables of adverse outcome indicated by multivariate analysis were multiple gastrointestinal involvement. In patients unfit for Rituximab but received surgery, radical surgery significantly prolonged the survival time, comparing with alleviative surgery. Addition of Rituximab could overcome the negative prognostic effect of alleviative surgery. Among the four prognostic systems, IPI and Lugano classification clearly separated patients into different risk groups. IPI was able to further stratify the early-stage patients of Lugano classification into groups with distinct prognosis. Radical surgery might be proposed for the patients unfit for Rituximab treatment, and a combination of clinical and pathological staging systems was more helpful to predict the disease outcome of PG-DLBCL patients.

  13. A dual model approach to ground water recovery trench design

    International Nuclear Information System (INIS)

    Clodfelter, C.L.; Crouch, M.S.

    1992-01-01

    The design of trenches for contaminated ground water recovery must consider several variables. This paper presents a dual-model approach for effectively recovering contaminated ground water migrating toward a trench by advection. The approach involves an analytical model to determine the vertical influence of the trench and a numerical flow model to determine the capture zone within the trench and the surrounding aquifer. The analytical model is utilized by varying trench dimensions and head values to design a trench which meets the remediation criteria. The numerical flow model is utilized to select the type of backfill and location of sumps within the trench. The dual-model approach can be used to design a recovery trench which effectively captures advective migration of contaminants in the vertical and horizontal planes

  14. Virtuous organization: A structural equation modeling approach

    Directory of Open Access Journals (Sweden)

    Majid Zamahani

    2013-02-01

    Full Text Available For years, the idea of virtue was unfavorable among researchers and virtues were traditionally considered as culture-specific, relativistic and they were supposed to be associated with social conservatism, religious or moral dogmatism, and scientific irrelevance. Virtue and virtuousness have been recently considered seriously among organizational researchers. The proposed study of this paper examines the relationships between leadership, organizational culture, human resource, structure and processes, care for community and virtuous organization. Structural equation modeling is employed to investigate the effects of each variable on other components. The data used in this study consists of questionnaire responses from employees in Payam e Noor University in Yazd province. A total of 250 questionnaires were sent out and a total of 211 valid responses were received. Our results have revealed that all the five variables have positive and significant impacts on virtuous organization. Among the five variables, organizational culture has the most direct impact (0.80 and human resource has the most total impact (0.844 on virtuous organization.

  15. A systemic approach for modeling soil functions

    Science.gov (United States)

    Vogel, Hans-Jörg; Bartke, Stephan; Daedlow, Katrin; Helming, Katharina; Kögel-Knabner, Ingrid; Lang, Birgit; Rabot, Eva; Russell, David; Stößel, Bastian; Weller, Ulrich; Wiesmeier, Martin; Wollschläger, Ute

    2018-03-01

    The central importance of soil for the functioning of terrestrial systems is increasingly recognized. Critically relevant for water quality, climate control, nutrient cycling and biodiversity, soil provides more functions than just the basis for agricultural production. Nowadays, soil is increasingly under pressure as a limited resource for the production of food, energy and raw materials. This has led to an increasing demand for concepts assessing soil functions so that they can be adequately considered in decision-making aimed at sustainable soil management. The various soil science disciplines have progressively developed highly sophisticated methods to explore the multitude of physical, chemical and biological processes in soil. It is not obvious, however, how the steadily improving insight into soil processes may contribute to the evaluation of soil functions. Here, we present to a new systemic modeling framework that allows for a consistent coupling between reductionist yet observable indicators for soil functions with detailed process understanding. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. The non-linear character of these interactions produces stability and resilience of soil with respect to functional characteristics. We anticipate that this new conceptional framework will integrate the various soil science disciplines and help identify important future research questions at the interface between disciplines. It allows the overwhelming complexity of soil systems to be adequately coped with and paves the way for steadily improving our capability to assess soil functions based on scientific understanding.

  16. Modeling of phase equilibria with CPA using the homomorph approach

    DEFF Research Database (Denmark)

    Breil, Martin Peter; Tsivintzelis, Ioannis; Kontogeorgis, Georgios

    2011-01-01

    For association models, like CPA and SAFT, a classical approach is often used for estimating pure-compound and mixture parameters. According to this approach, the pure-compound parameters are estimated from vapor pressure and liquid density data. Then, the binary interaction parameters, kij, are ...

  17. Modular Modelling and Simulation Approach - Applied to Refrigeration Systems

    DEFF Research Database (Denmark)

    Sørensen, Kresten Kjær; Stoustrup, Jakob

    2008-01-01

    This paper presents an approach to modelling and simulation of the thermal dynamics of a refrigeration system, specifically a reefer container. A modular approach is used and the objective is to increase the speed and flexibility of the developed simulation environment. The refrigeration system...

  18. A Constructive Neural-Network Approach to Modeling Psychological Development

    Science.gov (United States)

    Shultz, Thomas R.

    2012-01-01

    This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept…

  19. The Intersystem Model of Psychotherapy: An Integrated Systems Treatment Approach

    Science.gov (United States)

    Weeks, Gerald R.; Cross, Chad L.

    2004-01-01

    This article introduces the intersystem model of psychotherapy and discusses its utility as a truly integrative and comprehensive approach. The foundation of this conceptually complex approach comes from dialectic metatheory; hence, its derivation requires an understanding of both foundational and integrational constructs. The article provides a…

  20. Bystander Approaches: Empowering Students to Model Ethical Sexual Behavior

    Science.gov (United States)

    Lynch, Annette; Fleming, Wm. Michael

    2005-01-01

    Sexual violence on college campuses is well documented. Prevention education has emerged as an alternative to victim-- and perpetrator--oriented approaches used in the past. One sexual violence prevention education approach focuses on educating and empowering the bystander to become a point of ethical intervention. In this model, bystanders to…

  1. Modelling road accidents: An approach using structural time series

    Science.gov (United States)

    Junus, Noor Wahida Md; Ismail, Mohd Tahir

    2014-09-01

    In this paper, the trend of road accidents in Malaysia for the years 2001 until 2012 was modelled using a structural time series approach. The structural time series model was identified using a stepwise method, and the residuals for each model were tested. The best-fitted model was chosen based on the smallest Akaike Information Criterion (AIC) and prediction error variance. In order to check the quality of the model, a data validation procedure was performed by predicting the monthly number of road accidents for the year 2012. Results indicate that the best specification of the structural time series model to represent road accidents is the local level with a seasonal model.

  2. Numerical approaches to expansion process modeling

    Directory of Open Access Journals (Sweden)

    G. V. Alekseev

    2017-01-01

    Full Text Available Forage production is currently undergoing a period of intensive renovation and introduction of the most advanced technologies and equipment. More and more often such methods as barley toasting, grain extrusion, steaming and grain flattening, boiling bed explosion, infrared ray treatment of cereals and legumes, followed by flattening, and one-time or two-time granulation of the purified whole grain without humidification in matrix presses By grinding the granules. These methods require special apparatuses, machines, auxiliary equipment, created on the basis of different methods of compiled mathematical models. When roasting, simulating the heat fields arising in the working chamber, provide such conditions, the decomposition of a portion of the starch to monosaccharides, which makes the grain sweetish, but due to protein denaturation the digestibility of the protein and the availability of amino acids decrease somewhat. Grain is roasted mainly for young animals in order to teach them to eat food at an early age, stimulate the secretory activity of digestion, better development of the masticatory muscles. In addition, the high temperature is detrimental to bacterial contamination and various types of fungi, which largely avoids possible diseases of the gastrointestinal tract. This method has found wide application directly on the farms. Apply when used in feeding animals and legumes: peas, soy, lupine and lentils. These feeds are preliminarily ground, and then cooked or steamed for 1 hour for 30–40 minutes. In the feed mill. Such processing of feeds allows inactivating the anti-nutrients in them, which reduce the effectiveness of their use. After processing, legumes are used as protein supplements in an amount of 25–30% of the total nutritional value of the diet. But it is recommended to cook and steal a grain of good quality. A poor-quality grain that has been stored for a long time and damaged by pathogenic micro flora is subject to

  3. Modelling and Generating Ajax Applications : A Model-Driven Approach

    NARCIS (Netherlands)

    Gharavi, V.; Mesbah, A.; Van Deursen, A.

    2008-01-01

    Preprint of paper published in: IWWOST 2008 - 7th International Workshop on Web-Oriented Software Technologies, 14-15 July 2008 AJAX is a promising and rapidly evolving approach for building highly interactive web applications. In AJAX, user interface components and the event-based interaction

  4. LAMININS IN COLORECTAL CANCER: EXPRESSION, FUNCTION, PROGNOSTIC POWER AND MOLECULAR MECHANISMS

    Directory of Open Access Journals (Sweden)

    S. A. Rodin

    2017-01-01

    Full Text Available Extracellular matrix (ECM proteins are a major component of the tumor stroma. Laminins emerge as one of the main families of ECM proteins with signaling properties. Apart from the structural function, laminins and products of their degradation affect survival and differentiation of cancer cells, motility of cancer and stromal cells, angiogenesis, invasion into distant organs, and other aspects of cancer development. Here, we discus expression of laminins in colorectal cancer (CRC, studying of laminin functions in in vitro and in vivo models of CRC, and using laminins as prognostic markers of CRC. Recently, we have reported a new approach to assessing prognostic power using classifiers constructed from sets of laminin genes. The method allows for accurate prognosis of CRC and provides additional information that may suggest possible molecular mechanisms of laminin function in CRC progression.

  5. Understanding Gulf War Illness: An Integrative Modeling Approach

    Science.gov (United States)

    2017-10-01

    using a novel mathematical model. The computational biology approach will enable the consortium to quickly identify targets of dysfunction and find... computer / mathematical paradigms for evaluation of treatment strategies 12-30 50% Develop pilot clinical trials on basis of animal studies 24-36 60...the goal of testing chemical treatments. The immune and autonomic biomarkers will be tested using a computational modeling approach allowing for a

  6. A Structural Modeling Approach to a Multilevel Random Coefficients Model.

    Science.gov (United States)

    Rovine, Michael J.; Molenaar, Peter C. M.

    2000-01-01

    Presents a method for estimating the random coefficients model using covariance structure modeling and allowing one to estimate both fixed and random effects. The method is applied to real and simulated data, including marriage data from J. Belsky and M. Rovine (1990). (SLD)

  7. Data Analysis A Model Comparison Approach, Second Edition

    CERN Document Server

    Judd, Charles M; Ryan, Carey S

    2008-01-01

    This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. T

  8. A Prognostic Indicator for Patients Hospitalized with Heart Failure.

    Science.gov (United States)

    Snow, Richard; Vogel, Karen; Vanderhoff, Bruce; Kelch, Benjamin P; Ferris, Frank D

    2016-12-01

    Current methods for identifying patients at risk of dying within six months suffer from clinician biases resulting in underestimation of this risk. As a result, patients who are potentially eligible for hospice and palliative care services frequently do not benefit from these services until they are very close to the end of their lives. To develop a prospective prognostic indicator based on actual survival within Centers for Medicare and Medicaid Services (CMS) claims data that identifies patients with congestive heart failure (CHF) who are at risk of six-month mortality. CMS claims data from January 1, 2008 to June 30, 2009 were reviewed to find the first hospitalization for CHF patients with episode of care diagnosis-related groups (DRGs) 291, 292, and 293. Univariate and multivariable analyses were used to determine the associations between demographic and clinical factors and six-month mortality. The resulting model was evaluated for discrimination and calibration. The resulting prospective prognostic model demonstrated fair discrimination with an ROC of 0.71 and good calibration with a Hosmer-Lemshow statistic of 0.98. Across all DRGs, 5% of discharged patients had a six-month mortality risk of greater than 50%. This prospective approach appears to provide a method to identify patients with CHF who would potentially benefit from a clinical evaluation for referral to hospice care or for a palliative care consult due to high predicted risk of dying within 180 days after discharge from a hospital. This approach can provide a model to match at-risk patients with evidenced-based care in a more consistent manner. This method of identifying patients at risk needs further prospective evaluation to see if it has value for clinicians, increases referrals to hospice and palliative care services, and benefits patients and families.

  9. Unavailability of thymidine kinase does not preclude the use of German comprehensive prognostic index: results of an external validation analysis in early chronic lymphocytic leukemia and comparison with MD Anderson Cancer Center model.

    Science.gov (United States)

    Molica, Stefano; Giannarelli, Diana; Mirabelli, Rosanna; Levato, Luciano; Russo, Antonio; Linardi, Maria; Gentile, Massimo; Morabito, Fortunato

    2016-01-01

    A comprehensive prognostic index that includes clinical (i.e., age, sex, ECOG performance status), serum (i.e., ß2-microglobulin, thymidine kinase [TK]), and molecular (i.e., IGVH mutational status, del 17p, del 11q) markers developed by the German CLL Study Group (GCLLSG) was externally validated in a prospective, community-based cohort consisting of 338 patients with early chronic lymphocytic leukemia (CLL) using as endpoint the time to first treatment (TTFT). Because serum TK was not available, a slightly modified version of the model based on seven instead of eight prognostic variables was used. By German index, 62.9% of patients were scored as having low-risk CLL (score 0-2), whereas 37.1% had intermediate-risk CLL (score 3-5). This stratification translated into a significant difference in the TTFT [HR = 4.21; 95% C.I. (2.71-6.53); P reliability [HR = 2.73; 95% C.I. (1.79-4.17); P German score. The c-statistic of the MDACC model was 0.65 (range, 0.53-0.78) a level below that of the German index [0.71 (range, 0.60-0.82)] and below the accepted 0.7 threshold necessary to have value at the individual patient level. Results of this external comparative validation analysis strongly support the German score as the benchmark for comparison of any novel prognostic scheme aimed at evaluating the TTFT in patients with early CLL even when a modified version which does not include TK is utilized. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  10. Individual participant data meta-analysis of prognostic factor studies: state of the art?

    Directory of Open Access Journals (Sweden)

    Abo-Zaid Ghada

    2012-04-01

    Full Text Available Abstract Background Prognostic factors are associated with the risk of a subsequent outcome in people with a given disease or health condition. Meta-analysis using individual participant data (IPD, where the raw data are synthesised from multiple studies, has been championed as the gold-standard for synthesising prognostic factor studies. We assessed the feasibility and conduct of this approach. Methods A systematic review to identify published IPD meta-analyses of prognostic factors studies, followed by detailed assessment of a random sample of 20 articles published from 2006. Six of these 20 articles were from the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials in traumatic brain injury collaboration, for which additional information was also used from simultaneously published companion papers. Results Forty-eight published IPD meta-analyses of prognostic factors were identified up to March 2009. Only three were published before 2000 but thereafter a median of four articles exist per year, with traumatic brain injury the most active research field. Availability of IPD offered many advantages, such as checking modelling assumptions; analysing variables on their continuous scale with the possibility of assessing for non-linear relationships; and obtaining results adjusted for other variables. However, researchers also faced many challenges, such as large cost and time required to obtain and clean IPD; unavailable IPD for some studies; different sets of prognostic factors in each study; and variability in study methods of measurement. The IMPACT initiative is a leading example, and had generally strong design, methodological and statistical standards. Elsewhere, standards are not always as high and improvements in the conduct of IPD meta-analyses of prognostic factor studies are often needed; in particular, continuous variables are often categorised without reason; publication bias and availability bias are rarely

  11. Colorectal Cancer: Prognostic Values

    Directory of Open Access Journals (Sweden)

    Suzana Manxhuka-Kerliu

    2009-02-01

    Full Text Available After lung cancer colorectal cancer (Cc is ranked the second, as a cause of cancer-related death. The purpose of this study was to analyze the Cc cases in our material with respect to all prognostic values including histological type and grade, vascular invasion, perineural invasion, and tumor border features. There were investigated 149 cases of resection specimen with colorectal cancer, which were fixed in buffered neutral formalin and embedded in paraffin. Tissue sections (4(µm thick were cut and stained with H&E. Adenocarcinoma was the most frequent histological type found in 85,90% of cases, in 60,94% of males and 39,06% of females; squamous cell carcinoma in 7,38%, in 63,63% of males and 36,36% of females; mucinous carcinoma in 4,68%, in 57,15% of males and 42,85% of females; while adenosquamous carcinoma, undifferentiated carcinoma and carcinoma in situ in 0,71% of cases each. Dukes' classification was used in order to define the depth of invasion. Dukes B was found in 68,45% of cases, whereas in 31,54% of cases Dukes C was found. As far as histological grading is concerned, Cc was mostly with moderate differentiation (75,16% with neither vascular nor perineural invasion. Resection margins were in all cases free of tumor. Our data indicate that the pathologic features of the resection specimen constitute the most powerful predictors of postoperative outcome in Cc. Dukes' stage and degree of differentiation provide independent prognostic information in Cc. However, differentiation should be assessed by the worst pattern.

  12. Prediction of paraquat exposure and toxicity in clinically ill poisoned patients: a model based approach.

    Science.gov (United States)

    Wunnapuk, Klintean; Mohammed, Fahim; Gawarammana, Indika; Liu, Xin; Verbeeck, Roger K; Buckley, Nicholas A; Roberts, Michael S; Musuamba, Flora T

    2014-10-01

    Paraquat poisoning is a medical problem in many parts of Asia and the Pacific. The mortality rate is extremely high as there is no effective treatment. We analyzed data collected during an ongoing cohort study on self-poisoning and from a randomized controlled trial assessing the efficacy of immunosuppressive therapy in hospitalized paraquat-intoxicated patients. The aim of this analysis was to characterize the toxicokinetics and toxicodynamics of paraquat in this population. A non-linear mixed effects approach was used to perform a toxicokinetic/toxicodynamic population analysis in a cohort of 78 patients. The paraquat plasma concentrations were best fitted by a two compartment toxicokinetic structural model with first order absorption and first order elimination. Changes in renal function were used for the assessment of paraquat toxicodynamics. The estimates of toxicokinetic parameters for the apparent clearance, the apparent volume of distribution and elimination half-life were 1.17 l h(-1) , 2.4 l kg(-1) and 87 h, respectively. Renal function, namely creatinine clearance, was the most significant covariate to explain between patient variability in paraquat clearance.This model suggested that a reduction in paraquat clearance occurred within 24 to 48 h after poison ingestion, and afterwards the clearance was constant over time. The model estimated that a paraquat concentration of 429 μg l(-1) caused 50% of maximum renal toxicity. The immunosuppressive therapy tested during this study was associated with only 8% improvement of renal function. The developed models may be useful as prognostic tools to predict patient outcome based on patient characteristics on admission and to assess drug effectiveness during antidote drug development. © 2014 The British Pharmacological Society.

  13. A novel approach to modeling and diagnosing the cardiovascular system

    Energy Technology Data Exchange (ETDEWEB)

    Keller, P.E.; Kangas, L.J.; Hashem, S.; Kouzes, R.T. [Pacific Northwest Lab., Richland, WA (United States); Allen, P.A. [Life Link, Richland, WA (United States)

    1995-07-01

    A novel approach to modeling and diagnosing the cardiovascular system is introduced. A model exhibits a subset of the dynamics of the cardiovascular behavior of an individual by using a recurrent artificial neural network. Potentially, a model will be incorporated into a cardiovascular diagnostic system. This approach is unique in that each cardiovascular model is developed from physiological measurements of an individual. Any differences between the modeled variables and the variables of an individual at a given time are used for diagnosis. This approach also exploits sensor fusion to optimize the utilization of biomedical sensors. The advantage of sensor fusion has been demonstrated in applications including control and diagnostics of mechanical and chemical processes.

  14. Synthesis of industrial applications of local approach to fracture models

    International Nuclear Information System (INIS)

    Eripret, C.

    1993-03-01

    This report gathers different applications of local approach to fracture models to various industrial configurations, such as nuclear pressure vessel steel, cast duplex stainless steels, or primary circuit welds such as bimetallic welds. As soon as models are developed on the basis of microstructural observations, damage mechanisms analyses, and fracture process, the local approach to fracture proves to solve problems where classical fracture mechanics concepts fail. Therefore, local approach appears to be a powerful tool, which completes the standard fracture criteria used in nuclear industry by exhibiting where and why those classical concepts become unvalid. (author). 1 tab., 18 figs., 25 refs

  15. Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

    Science.gov (United States)

    Molgaard Nielsen, Anne; Hestbaek, Lise; Vach, Werner; Kent, Peter; Kongsted, Alice

    2017-08-09

    Heterogeneity in patients with low back pain is well recognised and different approaches to subgrouping have been proposed. One statistical technique that is increasingly being used is Latent Class Analysis as it performs subgrouping based on pattern recognition with high accuracy. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two-stage approach. However, their prognostic capacity was unexplored. This study (i) determined whether the subgrouping approaches were associated with the future outcomes of pain intensity, pain frequency and disability, (ii) assessed whether one of these two approaches was more strongly or more consistently associated with these outcomes, and (iii) assessed the performance of the novel subgroupings as compared to the following variables: two existing subgrouping tools (STarT Back Tool and Quebec Task Force classification), four baseline characteristics and a group of previously identified domain-specific patient categorisations (collectively, the 'comparator variables'). This was a longitudinal cohort study of 928 patients consulting for low back pain in primary care. The associations between each subgroup approach and outcomes at 2 weeks, 3 and 12 months, and with weekly SMS responses were tested in linear regression models, and their prognostic capacity (variance explained) was compared to that of the comparator variables listed above. The two previously identified subgroupings were similarly associated with all outcomes. The prognostic capacity of both subgroupings was better than that of the comparator variables, except for participants' recovery beliefs and the domain-specific categorisations, but was still limited. The explained variance ranged from 4.3%-6.9% for pain intensity and

  16. Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325).

    Science.gov (United States)

    Dehing-Oberije, Cary; Aerts, Hugo; Yu, Shipeng; De Ruysscher, Dirk; Menheere, Paul; Hilvo, Mika; van der Weide, Hiska; Rao, Bharat; Lambin, Philippe

    2011-10-01

    Currently, prediction of survival for non-small-cell lung cancer patients treated with (chemo)radiotherapy is mainly based on clinical factors. The hypothesis of this prospective study was that blood biomarkers related to hypoxia, inflammation, and tumor load would have an added prognostic value for predicting survival. Clinical data and blood samples were collected prospectively (NCT00181519, NCT00573040, and NCT00572325) from 106 inoperable non-small-cell lung cancer patients (Stages I-IIIB), treated with curative intent with radiotherapy alone or combined with chemotherapy. Blood biomarkers, including lactate dehydrogenase, C-reactive protein, osteopontin, carbonic anhydrase IX, interleukin (IL) 6, IL-8, carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1, were measured. A multivariate model, built on a large patient population (N = 322) and externally validated, was used as a baseline model. An extended model was created by selecting additional biomarkers. The model's performance was expressed as the area under the curve (AUC) of the receiver operating characteristic and assessed by use of leave-one-out cross validation as well as a validation cohort (n = 52). The baseline model consisted of gender, World Health Organization performance status, forced expiratory volume, number of positive lymph node stations, and gross tumor volume and yielded an AUC of 0.72. The extended model included two additional blood biomarkers (CEA and IL-6) and resulted in a leave-one-out AUC of 0.81. The performance of the extended model was significantly better than the clinical model (p = 0.004). The AUC on the validation cohort was 0.66 and 0.76, respectively. The performance of the prognostic model for survival improved markedly by adding two blood biomarkers: CEA and IL-6. Copyright © 2011 Elsevier Inc. All rights reserved.

  17. Mathematical models for therapeutic approaches to control HIV disease transmission

    CERN Document Server

    Roy, Priti Kumar

    2015-01-01

    The book discusses different therapeutic approaches based on different mathematical models to control the HIV/AIDS disease transmission. It uses clinical data, collected from different cited sources, to formulate the deterministic as well as stochastic mathematical models of HIV/AIDS. It provides complementary approaches, from deterministic and stochastic points of view, to optimal control strategy with perfect drug adherence and also tries to seek viewpoints of the same issue from different angles with various mathematical models to computer simulations. The book presents essential methods and techniques for students who are interested in designing epidemiological models on HIV/AIDS. It also guides research scientists, working in the periphery of mathematical modeling, and helps them to explore a hypothetical method by examining its consequences in the form of a mathematical modelling and making some scientific predictions. The model equations, mathematical analysis and several numerical simulations that are...

  18. A model-driven approach to information security compliance

    Science.gov (United States)

    Correia, Anacleto; Gonçalves, António; Teodoro, M. Filomena

    2017-06-01

    The availability, integrity and confidentiality of information are fundamental to the long-term survival of any organization. Information security is a complex issue that must be holistically approached, combining assets that support corporate systems, in an extended network of business partners, vendors, customers and other stakeholders. This paper addresses the conception and implementation of information security systems, conform the ISO/IEC 27000 set of standards, using the model-driven approach. The process begins with the conception of a domain level model (computation independent model) based on information security vocabulary present in the ISO/IEC 27001 standard. Based on this model, after embedding in the model mandatory rules for attaining ISO/IEC 27001 conformance, a platform independent model is derived. Finally, a platform specific model serves the base for testing the compliance of information security systems with the ISO/IEC 27000 set of standards.

  19. A Model-Driven Approach for Telecommunications Network Services Definition

    Science.gov (United States)

    Chiprianov, Vanea; Kermarrec, Yvon; Alff, Patrick D.

    Present day Telecommunications market imposes a short concept-to-market time for service providers. To reduce it, we propose a computer-aided, model-driven, service-specific tool, with support for collaborative work and for checking properties on models. We started by defining a prototype of the Meta-model (MM) of the service domain. Using this prototype, we defined a simple graphical modeling language specific for service designers. We are currently enlarging the MM of the domain using model transformations from Network Abstractions Layers (NALs). In the future, we will investigate approaches to ensure the support for collaborative work and for checking properties on models.

  20. Prognostic value of proliferation in pleomorphic soft tissue sarcomas

    DEFF Research Database (Denmark)

    Seinen, Jojanneke M; Jönsson, Mats; Bendahl, Pär-Ola O

    2012-01-01

    = 1.6-12.1), Top2a (hazard ratio = 2.2, CI = 1.2-3.5) and high S-phase fraction (hazard ratio = 1.8, CI = 1.2-3.7) significantly correlated with risk for metastasis. When combined with currently used prognostic factors, Ki-67, S-phase fraction and Top2a fraction contributed to refined identification...... of prognostic risk groups. Proliferation, as assessed by expression of Ki-67 and Top2a and evaluation of S-phase fraction and applied to statistical decision-tree models, provides prognostic information in soft tissue sarcomas of the extremity and trunk wall. Though proliferation contributes independently...... to currently applied prognosticators, its role is particularly strong when few other factors are available, which suggests a role in preoperative decision-making related to identification of high-risk individuals who would benefit from neoadjuvant therapy....

  1. An approach for activity-based DEVS model specification

    DEFF Research Database (Denmark)

    Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

    2016-01-01

    Creation of DEVS models has been advanced through Model Driven Architecture and its frameworks. The overarching role of the frameworks has been to help develop model specifications in a disciplined fashion. Frameworks can provide intermediary layers between the higher level mathematical models...... and their corresponding software specifications from both structural and behavioral aspects. Unlike structural modeling, developing models to specify behavior of systems is known to be harder and more complex, particularly when operations with non-trivial control schemes are required. In this paper, we propose specifying...... activity-based behavior modeling of parallel DEVS atomic models. We consider UML activities and actions as fundamental units of behavior modeling, especially in the presence of recent advances in the UML 2.5 specifications. We describe in detail how to approach activity modeling with a set of elemental...

  2. Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model.

    Science.gov (United States)

    Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

    2018-01-01

    The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC models were compared using: concordance index (CI), bias-corrected concordance index (BCCI), calibration plots, the Grønnesby and Borgan test, Bayesian Information Criterion (BIC), generalized R 2 , Integrated Discrimination Improvement (IDI), and continuous Net Reclassification Index (cNRI) for individual risk factors and the three risk groups. Three hundred and twenty-one patients were eligible for analyses. The modified-IMDC model with NLR value of 3.6 and PLR value of 157 was selected for comparison with the IMDC model. Both models were well calibrated. All other measures favoured the modified-IMDC model over the IMDC model (CI, 0.706 vs. 0.677; BCCI, 0.699 vs. 0.671; BIC, 2,176.2 vs. 2,190.7; generalized R 2 , 0.238 vs. 0.202; IDI, 0.044; cNRI, 0.279 for individual risk factors; and CI, 0.669 vs. 0.641; BCCI, 0.669 vs. 0.641; BIC, 2,183.2 vs. 2,198.1; generalized R 2 , 0.163 vs. 0.123; IDI, 0.045; cNRI, 0.165 for the three risk groups). Incorporation of NLR and PLR in place of neutrophil count and platelet count improved prognostic accuracy of the IMDC model. These findings require external validation before introducing into clinical practice.

  3. Modelling diversity in building occupant behaviour: a novel statistical approach

    DEFF Research Database (Denmark)

    Haldi, Frédéric; Calì, Davide; Andersen, Rune Korsholm

    2016-01-01

    We propose an advanced modelling framework to predict the scope and effects of behavioural diversity regarding building occupant actions on window openings, shading devices and lighting. We develop a statistical approach based on generalised linear mixed models to account for the longitudinal nat...

  4. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  5. A qualitative evaluation approach for energy system modelling frameworks

    DEFF Research Database (Denmark)

    Wiese, Frauke; Hilpert, Simon; Kaldemeyer, Cord

    2018-01-01

    properties define how useful it is in regard to the existing challenges. For energy system models, evaluation methods exist, but we argue that many decisions upon properties are rather made on the model generator or framework level. Thus, this paper presents a qualitative approach to evaluate frameworks...

  6. Modeling Alaska boreal forests with a controlled trend surface approach

    Science.gov (United States)

    Mo Zhou; Jingjing Liang

    2012-01-01

    An approach of Controlled Trend Surface was proposed to simultaneously take into consideration large-scale spatial trends and nonspatial effects. A geospatial model of the Alaska boreal forest was developed from 446 permanent sample plots, which addressed large-scale spatial trends in recruitment, diameter growth, and mortality. The model was tested on two sets of...

  7. Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of

  8. Towards modeling future energy infrastructures - the ELECTRA system engineering approach

    DEFF Research Database (Denmark)

    Uslar, Mathias; Heussen, Kai

    2016-01-01

    of the IEC 62559 use case template as well as needed changes to cope particularly with the aspects of controller conflicts and Greenfield technology modeling. From the original envisioned use of the standards, we show a possible transfer on how to properly deal with a Greenfield approach when modeling....

  9. A Model-Driven Approach to e-Course Management

    Science.gov (United States)

    Savic, Goran; Segedinac, Milan; Milenkovic, Dušica; Hrin, Tamara; Segedinac, Mirjana

    2018-01-01

    This paper presents research on using a model-driven approach to the development and management of electronic courses. We propose a course management system which stores a course model represented as distinct machine-readable components containing domain knowledge of different course aspects. Based on this formally defined platform-independent…

  10. Prognostic and predictive factors in colorectal cancer.

    Science.gov (United States)

    Bolocan, A; Ion, D; Ciocan, D N; Paduraru, D N

    2012-01-01

    Colorectal cancer (CRC) is an important public health problem; it is a leading cause of cancer mortality in the industrialized world, second to lung cancer: each year there are nearly one million new cases of CRC diagnosed worldwide and half a million deaths (1). This review aims to summarise the most important currently available markers for CRC that provide prognostic or predictive information. Amongst others, it covers serum markers such as CEA and CA19-9, markers expressed by tumour tissues, such as thymidylate synthase, and also the expression/loss of expression of certain oncogenes and tumour suppressor genes such as K-ras and p53. The prognostic value of genomic instability, angiogenesis and proliferative indices, such as the apoptotic index, are discussed. The advent of new therapies created the pathway for a personalized approach of the patient. This will take into consideration the complex genetic mechanisms involved in tumorigenesis, besides the classical clinical and pathological stagings. The growing number of therapeutic agents and known molecular targets in oncology lead to a compulsory study of the clinical use of biomarkers with role in improving response and survival, as well as in reducing toxicity and establishing economic stability. The potential predictive and prognostic biomarkers which have arisen from the study of the genetic basis of colorectal cancer and their therapeutical significance are discussed. RevistaChirurgia.

  11. A study of multidimensional modeling approaches for data warehouse

    Science.gov (United States)

    Yusof, Sharmila Mat; Sidi, Fatimah; Ibrahim, Hamidah; Affendey, Lilly Suriani

    2016-08-01

    Data warehouse system is used to support the process of organizational decision making. Hence, the system must extract and integrate information from heterogeneous data sources in order to uncover relevant knowledge suitable for decision making process. However, the development of data warehouse is a difficult and complex process especially in its conceptual design (multidimensional modeling). Thus, there have been various approaches proposed to overcome the difficulty. This study surveys and compares the approaches of multidimensional modeling and highlights the issues, trend and solution proposed to date. The contribution is on the state of the art of the multidimensional modeling design.

  12. Gray-box modelling approach for description of storage tunnel

    DEFF Research Database (Denmark)

    Harremoës, Poul; Carstensen, Jacob

    1999-01-01

    The dynamics of a storage tunnel is examined using a model based on on-line measured data and a combination of simple deterministic and black-box stochastic elements. This approach, called gray-box modeling, is a new promising methodology for giving an on-line state description of sewer systems...... of the water in the overflow structures. The capacity of a pump draining the storage tunnel is estimated for two different rain events, revealing that the pump was malfunctioning during the first rain event. The proposed modeling approach can be used in automated online surveillance and control and implemented...

  13. Meta-analysis a structural equation modeling approach

    CERN Document Server

    Cheung, Mike W-L

    2015-01-01

    Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the impo

  14. Heterogeneity of Prognostic Profiles in Non-small Cell Lung Cancer: Too Many Variables but a Few Relevant

    International Nuclear Information System (INIS)

    Camara, Agustin Gomez de la; Lopez-Encuentra, Angel; Ferrando, Paloma

    2005-01-01

    Objective: Many prognostic factors, exceeding 150, for non-small cell lung cancer (NSCLC) are mentioned in the literature. The different statistical weight of the some variables at issue, their heterogeneity and their clinical uselessness is reviewed. Study design and setting: Survival analysis of a cohort of NSCLC operated (n = 1730, 1993-1997) was carried out utilizing different statistical approaches: Cox proportional hazard analysis (CPHA), logistic regression (LRA), and recursive partitioning (CART). Results: CPHA identified 13 prognostic variables and 11 LRA. Of the 17 possible variables, 10 are coincident. CART provided five different diagnostic groups but only three differentiated survival levels. Parsimonious models were constructed including only T and N cancer staging variables. Areas under the ROC curve of 0.68 and 0.68 were found for CPHA and LGA parsimonious models respectively, and 0.72 and 0.71 for complete models. Conclusion: Variables with a minimal impact on the respective models and thus with little or scarce predictive clinical repercussion were identified. Differences in the prognostic profile of survival can be caused by the different methodological approaches used. No relevant differences were found between the parsimonious and complete models. Although the amount of information managed is considerable, there continues to be a large predictive gap yet to be explained

  15. Learning the Task Management Space of an Aircraft Approach Model

    Science.gov (United States)

    Krall, Joseph; Menzies, Tim; Davies, Misty

    2014-01-01

    Validating models of airspace operations is a particular challenge. These models are often aimed at finding and exploring safety violations, and aim to be accurate representations of real-world behavior. However, the rules governing the behavior are quite complex: nonlinear physics, operational modes, human behavior, and stochastic environmental concerns all determine the responses of the system. In this paper, we present a study on aircraft runway approaches as modeled in Georgia Tech's Work Models that Compute (WMC) simulation. We use a new learner, Genetic-Active Learning for Search-Based Software Engineering (GALE) to discover the Pareto frontiers defined by cognitive structures. These cognitive structures organize the prioritization and assignment of tasks of each pilot during approaches. We discuss the benefits of our approach, and also discuss future work necessary to enable uncertainty quantification.

  16. Dissecting the regulatory microenvironment of a large animal model of non-Hodgkin lymphoma: evidence of a negative prognostic impact of FOXP3+ T cells in canine B cell lymphoma.

    Directory of Open Access Journals (Sweden)

    Dammy Pinheiro

    Full Text Available The cancer microenvironment plays a pivotal role in oncogenesis, containing a number of regulatory cells that attenuate the anti-neoplastic immune response. While the negative prognostic impact of regulatory T cells (Tregs in the context of most solid tissue tumors is well established, their role in lymphoid malignancies remains unclear. T cells expressing FOXP3 and Helios were documented in the fine needle aspirates of affected lymph nodes of dogs with spontaneous multicentric B cell lymphoma (BCL, proposed to be a model for human non-Hodgkin lymphoma. Multivariable analysis revealed that the frequency of lymph node FOXP3(+ T cells was an independent negative prognostic factor, impacting both progression-free survival (hazard ratio 1.10; p = 0.01 and overall survival (hazard ratio 1.61; p = 0.01 when comparing dogs showing higher than the median FOXP3 expression with those showing the median value of FOXP3 expression or less. Taken together, these data suggest the existence of a population of Tregs operational in canine multicentric BCL that resembles thymic Tregs, which we speculate are co-opted by the tumor from the periphery. We suggest that canine multicentric BCL represents a robust large animal model of human diffuse large BCL, showing clinical, cytological and immunophenotypic similarities with the disease in man, allowing comparative studies of immunoregulatory mechanisms.

  17. A novel approach of modeling continuous dark hydrogen fermentation.

    Science.gov (United States)

    Alexandropoulou, Maria; Antonopoulou, Georgia; Lyberatos, Gerasimos

    2018-02-01

    In this study a novel modeling approach for describing fermentative hydrogen production in a continuous stirred tank reactor (CSTR) was developed, using the Aquasim modeling platform. This model accounts for the key metabolic reactions taking place in a fermentative hydrogen producing reactor, using fixed stoichiometry but different reaction rates. Biomass yields are determined based on bioenergetics. The model is capable of describing very well the variation in the distribution of metabolic products for a wide range of hydraulic retention times (HRT). The modeling approach is demonstrated using the experimental data obtained from a CSTR, fed with food industry waste (FIW), operating at different HRTs. The kinetic parameters were estimated through fitting to the experimental results. Hydrogen and total biogas production rates were predicted very well by the model, validating the basic assumptions regarding the implicated stoichiometric biochemical reactions and their kinetic rates. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. An integrated modeling approach to age invariant face recognition

    Science.gov (United States)

    Alvi, Fahad Bashir; Pears, Russel

    2015-03-01

    This Research study proposes a novel method for face recognition based on Anthropometric features that make use of an integrated approach comprising of a global and personalized models. The system is aimed to at situations where lighting, illumination, and pose variations cause problems in face recognition. A Personalized model covers the individual aging patterns while a Global model captures general aging patterns in the database. We introduced a de-aging factor that de-ages each individual in the database test and training sets. We used the k nearest neighbor approach for building a personalized model and global model. Regression analysis was applied to build the models. During the test phase, we resort to voting on different features. We used FG-Net database for checking the results of our technique and achieved 65 percent Rank 1 identification rate.

  19. [Comparison of the prognostic value of mortality Child Pugh Score and forecasting models of chronic liver disease in patients with decompensated cirrhosis of the Hospital Nacional Cayetano Heredia, Lima-Peru].

    Science.gov (United States)

    Valenzuela Granados, Vanessa; Salazar-Quiñones, Maria; Cheng-Zárate, Lester; Malpica-Castillo, Alexander; Huerta Mercado, Jorge; Ticse, Ray

    2015-01-01

    The assessment of prognosis is an essential part of the evaluation of all patients with liver cirrhosis. Currently continues to develop new models to optimize forecast accuracy mortality score is calculated by the Child-Turcotte-Pugh (CTP) and the model for end-stage liver disease (MELD). Compare the prognostic accuracy of hospital mortality and short-term mortality CTP, MELD and other models in patients with decompensated liver cirrhosis. Prospective descriptive study, comparison type of diagnostic test that included 84 patients. The score CTP, MELD and other models were calculated on the first day of hospitalization. The prognostic accuracy of mortality was assessed by the area under the ROC curve (AUROCs) of score CTP, MELD and other models. Hospital mortality and mortality in the short-term monitoring was 20 (23.8%) and 44 (52.4%), respectively. The AUROCs CTP, MELD, MELD Na, MESO, iMELD, RefitMELD and RefitMELD Na to predict hospital mortality was 0.4488, 0.5645, 0.5426, 0.5578, 0.5719, 0.5598 and 0.5754; and to predict short-term mortality was 0.5386, 0.5747, 0.5770, 0.5781, 0.5631, 0.5881 and 0.5693, respectively. By comparing each AUROCs of the CTP score, MELD and other models proved to be no better than the other (p>0.05). This study has not shown the predictive utility of the CTP score, MELD and other models (MELD Na, MESO, iMELD, Refit Refit MELD and MELD Na) to evaluate hospital mortality or short-term mortality in a sample of patients with decompensated cirrhosis of the Hospital Cayetano Heredia.

  20. Benchmarking novel approaches for modelling species range dynamics.

    Science.gov (United States)

    Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

    2016-08-01

    Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

  1. On a model-based approach to radiation protection

    International Nuclear Information System (INIS)

    Waligorski, M.P.R.

    2002-01-01

    There is a preoccupation with linearity and absorbed dose as the basic quantifiers of radiation hazard. An alternative is the fluence approach, whereby radiation hazard may be evaluated, at least in principle, via an appropriate action cross section. In order to compare these approaches, it may be useful to discuss them as quantitative descriptors of survival and transformation-like endpoints in cell cultures in vitro - a system thought to be relevant to modelling radiation hazard. If absorbed dose is used to quantify these biological endpoints, then non-linear dose-effect relations have to be described, and, e.g. after doses of densely ionising radiation, dose-correction factors as high as 20 are required. In the fluence approach only exponential effect-fluence relationships can be readily described. Neither approach alone exhausts the scope of experimentally observed dependencies of effect on dose or fluence. Two-component models, incorporating a suitable mixture of the two approaches, are required. An example of such a model is the cellular track structure theory developed by Katz over thirty years ago. The practical consequences of modelling radiation hazard using this mixed two-component approach are discussed. (author)

  2. Towards Prognostics for Electronics Components

    Data.gov (United States)

    National Aeronautics and Space Administration — Electronics components have an increasingly critical role in avionics systems and in the development of future aircraft systems. Prognostics of such components is...

  3. Modeling gene expression measurement error: a quasi-likelihood approach

    Directory of Open Access Journals (Sweden)

    Strimmer Korbinian

    2003-03-01

    Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also

  4. A review of function modeling: Approaches and applications

    OpenAIRE

    Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.

    2008-01-01

    This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research fields of artificial intelligence, design theory, and maintenance are discussed. In this discussion the goals are to highlight the features of various classical approaches in relation to FM, to delin...

  5. Top-down approach to unified supergravity models

    International Nuclear Information System (INIS)

    Hempfling, R.

    1994-03-01

    We introduce a new approach for studying unified supergravity models. In this approach all the parameters of the grand unified theory (GUT) are fixed by imposing the corresponding number of low energy observables. This determines the remaining particle spectrum whose dependence on the low energy observables can now be investigated. We also include some SUSY threshold corrections that have previously been neglected. In particular the SUSY threshold corrections to the fermion masses can have a significant impact on the Yukawa coupling unification. (orig.)

  6. Intelligent Transportation and Evacuation Planning A Modeling-Based Approach

    CERN Document Server

    Naser, Arab

    2012-01-01

    Intelligent Transportation and Evacuation Planning: A Modeling-Based Approach provides a new paradigm for evacuation planning strategies and techniques. Recently, evacuation planning and modeling have increasingly attracted interest among researchers as well as government officials. This interest stems from the recent catastrophic hurricanes and weather-related events that occurred in the southeastern United States (Hurricane Katrina and Rita). The evacuation methods that were in place before and during the hurricanes did not work well and resulted in thousands of deaths. This book offers insights into the methods and techniques that allow for implementing mathematical-based, simulation-based, and integrated optimization and simulation-based engineering approaches for evacuation planning. This book also: Comprehensively discusses the application of mathematical models for evacuation and intelligent transportation modeling Covers advanced methodologies in evacuation modeling and planning Discusses principles a...

  7. An object-oriented approach to energy-economic modeling

    Energy Technology Data Exchange (ETDEWEB)

    Wise, M.A.; Fox, J.A.; Sands, R.D.

    1993-12-01

    In this paper, the authors discuss the experiences in creating an object-oriented economic model of the U.S. energy and agriculture markets. After a discussion of some central concepts, they provide an overview of the model, focusing on the methodology of designing an object-oriented class hierarchy specification based on standard microeconomic production functions. The evolution of the model from the class definition stage to programming it in C++, a standard object-oriented programming language, will be detailed. The authors then discuss the main differences between writing the object-oriented program versus a procedure-oriented program of the same model. Finally, they conclude with a discussion of the advantages and limitations of the object-oriented approach based on the experience in building energy-economic models with procedure-oriented approaches and languages.

  8. Multi-model approach to characterize human handwriting motion.

    Science.gov (United States)

    Chihi, I; Abdelkrim, A; Benrejeb, M

    2016-02-01

    This paper deals with characterization and modelling of human handwriting motion from two forearm muscle activity signals, called electromyography signals (EMG). In this work, an experimental approach was used to record the coordinates of a pen tip moving on the (x, y) plane and EMG signals during the handwriting act. The main purpose is to design a new mathematical model which characterizes this biological process. Based on a multi-model approach, this system was originally developed to generate letters and geometric forms written by different writers. A Recursive Least Squares algorithm is used to estimate the parameters of each sub-model of the multi-model basis. Simulations show good agreement between predicted results and the recorded data.

  9. Wave Resource Characterization Using an Unstructured Grid Modeling Approach

    Directory of Open Access Journals (Sweden)

    Wei-Cheng Wu

    2018-03-01

    Full Text Available This paper presents a modeling study conducted on the central Oregon coast for wave resource characterization, using the unstructured grid Simulating WAve Nearshore (SWAN model coupled with a nested grid WAVEWATCH III® (WWIII model. The flexibility of models with various spatial resolutions and the effects of open boundary conditions simulated by a nested grid WWIII model with different physics packages were evaluated. The model results demonstrate the advantage of the unstructured grid-modeling approach for flexible model resolution and good model skills in simulating the six wave resource parameters recommended by the International Electrotechnical Commission in comparison to the observed data in Year 2009 at National Data Buoy Center Buoy 46050. Notably, spectral analysis indicates that the ST4 physics package improves upon the ST2 physics package’s ability to predict wave power density for large waves, which is important for wave resource assessment, load calculation of devices, and risk management. In addition, bivariate distributions show that the simulated sea state of maximum occurrence with the ST4 physics package matched the observed data better than with the ST2 physics package. This study demonstrated that the unstructured grid wave modeling approach, driven by regional nested grid WWIII outputs along with the ST4 physics package, can efficiently provide accurate wave hindcasts to support wave resource characterization. Our study also suggests that wind effects need to be considered if the dimension of the model domain is greater than approximately 100 km, or O (102 km.

  10. A comprehensive dynamic modeling approach for giant magnetostrictive material actuators

    International Nuclear Information System (INIS)

    Gu, Guo-Ying; Zhu, Li-Min; Li, Zhi; Su, Chun-Yi

    2013-01-01

    In this paper, a comprehensive modeling approach for a giant magnetostrictive material actuator (GMMA) is proposed based on the description of nonlinear electromagnetic behavior, the magnetostrictive effect and frequency response of the mechanical dynamics. It maps the relationships between current and magnetic flux at the electromagnetic part to force and displacement at the mechanical part in a lumped parameter form. Towards this modeling approach, the nonlinear hysteresis effect of the GMMA appearing only in the electrical part is separated from the linear dynamic plant in the mechanical part. Thus, a two-module dynamic model is developed to completely characterize the hysteresis nonlinearity and the dynamic behaviors of the GMMA. The first module is a static hysteresis model to describe the hysteresis nonlinearity, and the cascaded second module is a linear dynamic plant to represent the dynamic behavior. To validate the proposed dynamic model, an experimental platform is established. Then, the linear dynamic part and the nonlinear hysteresis part of the proposed model are identified in sequence. For the linear part, an approach based on axiomatic design theory is adopted. For the nonlinear part, a Prandtl–Ishlinskii model is introduced to describe the hysteresis nonlinearity and a constrained quadratic optimization method is utilized to identify its coefficients. Finally, experimental tests are conducted to demonstrate the effectiveness of the proposed dynamic model and the corresponding identification method. (paper)

  11. Prognostic biomarkers in osteoarthritis

    Science.gov (United States)

    Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

    2013-01-01

    Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

  12. A website evaluation model by integration of previous evaluation models using a quantitative approach

    Directory of Open Access Journals (Sweden)

    Ali Moeini

    2015-01-01

    Full Text Available Regarding the ecommerce growth, websites play an essential role in business success. Therefore, many authors have offered website evaluation models since 1995. Although, the multiplicity and diversity of evaluation models make it difficult to integrate them into a single comprehensive model. In this paper a quantitative method has been used to integrate previous models into a comprehensive model that is compatible with them. In this approach the researcher judgment has no role in integration of models and the new model takes its validity from 93 previous models and systematic quantitative approach.

  13. Smeared crack modelling approach for corrosion-induced concrete damage

    DEFF Research Database (Denmark)

    Thybo, Anna Emilie Anusha; Michel, Alexander; Stang, Henrik

    2017-01-01

    In this paper a smeared crack modelling approach is used to simulate corrosion-induced damage in reinforced concrete. The presented modelling approach utilizes a thermal analogy to mimic the expansive nature of solid corrosion products, while taking into account the penetration of corrosion...... products into the surrounding concrete, non-uniform precipitation of corrosion products, and creep. To demonstrate the applicability of the presented modelling approach, numerical predictions in terms of corrosion-induced deformations as well as formation and propagation of micro- and macrocracks were......-induced damage phenomena in reinforced concrete. Moreover, good agreements were also found between experimental and numerical data for corrosion-induced deformations along the circumference of the reinforcement....

  14. A model-data based systems approach to process intensification

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    . Their developments, however, are largely due to experiment based trial and error approaches and while they do not require validation, they can be time consuming and resource intensive. Also, one may ask, can a truly new intensified unit operation be obtained in this way? An alternative two-stage approach is to apply...... a model-based synthesis method to systematically generate and evaluate alternatives in the first stage and an experiment-model based validation in the second stage. In this way, the search for alternatives is done very quickly, reliably and systematically over a wide range, while resources are preserved...... for focused validation of only the promising candidates in the second-stage. This approach, however, would be limited to intensification based on “known” unit operations, unless the PI process synthesis/design is considered at a lower level of aggregation, namely the phenomena level. That is, the model-based...

  15. METHODOLOGICAL APPROACHES FOR MODELING THE RURAL SETTLEMENT DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Gorbenkova Elena Vladimirovna

    2017-10-01

    Full Text Available Subject: the paper describes the research results on validation of a rural settlement developmental model. The basic methods and approaches for solving the problem of assessment of the urban and rural settlement development efficiency are considered. Research objectives: determination of methodological approaches to modeling and creating a model for the development of rural settlements. Materials and methods: domestic and foreign experience in modeling the territorial development of urban and rural settlements and settlement structures was generalized. The motivation for using the Pentagon-model for solving similar problems was demonstrated. Based on a systematic analysis of existing development models of urban and rural settlements as well as the authors-developed method for assessing the level of agro-towns development, the systems/factors that are necessary for a rural settlement sustainable development are identified. Results: we created the rural development model which consists of five major systems that include critical factors essential for achieving a sustainable development of a settlement system: ecological system, economic system, administrative system, anthropogenic (physical system and social system (supra-structure. The methodological approaches for creating an evaluation model of rural settlements development were revealed; the basic motivating factors that provide interrelations of systems were determined; the critical factors for each subsystem were identified and substantiated. Such an approach was justified by the composition of tasks for territorial planning of the local and state administration levels. The feasibility of applying the basic Pentagon-model, which was successfully used for solving the analogous problems of sustainable development, was shown. Conclusions: the resulting model can be used for identifying and substantiating the critical factors for rural sustainable development and also become the basis of

  16. An algebraic approach to modeling in software engineering

    International Nuclear Information System (INIS)

    Loegel, C.J.; Ravishankar, C.V.

    1993-09-01

    Our work couples the formalism of universal algebras with the engineering techniques of mathematical modeling to develop a new approach to the software engineering process. Our purpose in using this combination is twofold. First, abstract data types and their specification using universal algebras can be considered a common point between the practical requirements of software engineering and the formal specification of software systems. Second, mathematical modeling principles provide us with a means for effectively analyzing real-world systems. We first use modeling techniques to analyze a system and then represent the analysis using universal algebras. The rest of the software engineering process exploits properties of universal algebras that preserve the structure of our original model. This paper describes our software engineering process and our experience using it on both research and commercial systems. We need a new approach because current software engineering practices often deliver software that is difficult to develop and maintain. Formal software engineering approaches use universal algebras to describe ''computer science'' objects like abstract data types, but in practice software errors are often caused because ''real-world'' objects are improperly modeled. There is a large semantic gap between the customer's objects and abstract data types. In contrast, mathematical modeling uses engineering techniques to construct valid models for real-world systems, but these models are often implemented in an ad hoc manner. A combination of the best features of both approaches would enable software engineering to formally specify and develop software systems that better model real systems. Software engineering, like mathematical modeling, should concern itself first and foremost with understanding a real system and its behavior under given circumstances, and then with expressing this knowledge in an executable form

  17. Towards a 3d Spatial Urban Energy Modelling Approach

    Science.gov (United States)

    Bahu, J.-M.; Koch, A.; Kremers, E.; Murshed, S. M.

    2013-09-01

    Today's needs to reduce the environmental impact of energy use impose dramatic changes for energy infrastructure and existing demand patterns (e.g. buildings) corresponding to their specific context. In addition, future energy systems are expected to integrate a considerable share of fluctuating power sources and equally a high share of distributed generation of electricity. Energy system models capable of describing such future systems and allowing the simulation of the impact of these developments thus require a spatial representation in order to reflect the local context and the boundary conditions. This paper describes two recent research approaches developed at EIFER in the fields of (a) geo-localised simulation of heat energy demand in cities based on 3D morphological data and (b) spatially explicit Agent-Based Models (ABM) for the simulation of smart grids. 3D city models were used to assess solar potential and heat energy demand of residential buildings which enable cities to target the building refurbishment potentials. Distributed energy systems require innovative modelling techniques where individual components are represented and can interact. With this approach, several smart grid demonstrators were simulated, where heterogeneous models are spatially represented. Coupling 3D geodata with energy system ABMs holds different advantages for both approaches. On one hand, energy system models can be enhanced with high resolution data from 3D city models and their semantic relations. Furthermore, they allow for spatial analysis and visualisation of the results, with emphasis on spatially and structurally correlations among the different layers (e.g. infrastructure, buildings, administrative zones) to provide an integrated approach. On the other hand, 3D models can benefit from more detailed system description of energy infrastructure, representing dynamic phenomena and high resolution models for energy use at component level. The proposed modelling strategies

  18. Fear of knowledge: Clinical hypotheses in diagnostic and prognostic reasoning.

    Science.gov (United States)

    Chiffi, Daniele; Zanotti, Renzo

    2017-10-01

    Patients are interested in receiving accurate diagnostic and prognostic information. Models and reasoning about diagnoses have been extensively investigated from a foundational perspective; however, for all its importance, prognosis has yet to receive a comparable degree of philosophical and methodological attention, and this may be due to the difficulties inherent in accurate prognostics. In the light of these considerations, we discuss a considerable body of critical thinking on the topic of prognostication and its strict relations with diagnostic reasoning, pointing out the distinction between nosographic and pathophysiological types of diagnosis and prognosis, underlying the importance of the explication and explanation processes. We then distinguish between various forms of hypothetical reasoning applied to reach diagnostic and prognostic judgments, comparing them with specific forms of abductive reasoning. The main thesis is that creative abduction regarding clinical hypotheses in diagnostic process is very unlikely to occur, whereas this seems to be often the case for prognostic judgments. The reasons behind this distinction are due to the different types of uncertainty involved in diagnostic and prognostic judgments. © 2016 John Wiley & Sons, Ltd.

  19. Study of Updating Initiating Event Frequency using Prognostics

    International Nuclear Information System (INIS)

    Kim, Hyeonmin; Lee, Sang-Hwan; Park, Jun-seok; Kim, Hyungdae; Chang, Yoon-Suk; Heo, Gyunyoung

    2014-01-01

    The Probabilistic Safety Assessment (PSA) model enables to find the relative priority of accident scenarios, weak points in achieving accident prevention or mitigation, and insights to improve those vulnerabilities. Thus, PSA consider realistic calculation for precise and confidence results. However, PSA model still 'conservative' aspects in the procedures of developing a PSA model. One of the sources for the conservatism is caused by the assumption of safety analysis and the estimation of failure frequency. Recently, Surveillance, Diagnosis, and Prognosis (SDP) is a growing trend in applying space and aviation systems in particular. Furthermore, a study dealing with the applicable areas and state-of-the-art status of the SDP in nuclear industry was published. SDP utilizing massive database and information technology among such enabling techniques is worthwhile to be highlighted in terms of the capability of alleviating the conservatism in the conventional PSA. This paper review the concept of integrating PSA and SDP and suggest the updated methodology of Initiating Event (IE) using prognostics. For more detailed, we focus on IE of the Steam Generator Tube Rupture (SGTR) considering tube degradation. This paper is additional research of previous our suggested the research. In this paper, the concept of integrating PSA and SDP are suggested. Prognostics algorithms in SDP are applied at IE, Bes in the Level 1 PSA. As an example, updating SGTR IE and its ageing were considered. Tube ageing were analyzed by using PASTA and Monte Carlo method. After analyzing the tube ageing, conventional SGTR IE were updated by using Bayesian approach. The studied method can help to cover the static and conservatism in PSA

  20. Study of Updating Initiating Event Frequency using Prognostics

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyeonmin; Lee, Sang-Hwan; Park, Jun-seok; Kim, Hyungdae; Chang, Yoon-Suk; Heo, Gyunyoung [Kyung Hee Univ., Yongin (Korea, Republic of)

    2014-10-15

    The Probabilistic Safety Assessment (PSA) model enables to find the relative priority of accident scenarios, weak points in achieving accident prevention or mitigation, and insights to improve those vulnerabilities. Thus, PSA consider realistic calculation for precise and confidence results. However, PSA model still 'conservative' aspects in the procedures of developing a PSA model. One of the sources for the conservatism is caused by the assumption of safety analysis and the estimation of failure frequency. Recently, Surveillance, Diagnosis, and Prognosis (SDP) is a growing trend in applying space and aviation systems in particular. Furthermore, a study dealing with the applicable areas and state-of-the-art status of the SDP in nuclear industry was published. SDP utilizing massive database and information technology among such enabling techniques is worthwhile to be highlighted in terms of the capability of alleviating the conservatism in the conventional PSA. This paper review the concept of integrating PSA and SDP and suggest the updated methodology of Initiating Event (IE) using prognostics. For more detailed, we focus on IE of the Steam Generator Tube Rupture (SGTR) considering tube degradation. This paper is additional research of previous our suggested the research. In this paper, the concept of integrating PSA and SDP are suggested. Prognostics algorithms in SDP are applied at IE, Bes in the Level 1 PSA. As an example, updating SGTR IE and its ageing were considered. Tube ageing were analyzed by using PASTA and Monte Carlo method. After analyzing the tube ageing, conventional SGTR IE were updated by using Bayesian approach. The studied method can help to cover the static and conservatism in PSA.

  1. Modelling of ductile and cleavage fracture by local approach

    International Nuclear Information System (INIS)

    Samal, M.K.; Dutta, B.K.; Kushwaha, H.S.

    2000-08-01

    This report describes the modelling of ductile and cleavage fracture processes by local approach. It is now well known that the conventional fracture mechanics method based on single parameter criteria is not adequate to model the fracture processes. It is because of the existence of effect of size and geometry of flaw, loading type and rate on the fracture resistance behaviour of any structure. Hence, it is questionable to use same fracture resistance curves as determined from standard tests in the analysis of real life components because of existence of all the above effects. So, there is need to have a method in which the parameters used for the analysis will be true material properties, i.e. independent of geometry and size. One of the solutions to the above problem is the use of local approaches. These approaches have been extensively studied and applied to different materials (including SA33 Gr.6) in this report. Each method has been studied and reported in a separate section. This report has been divided into five sections. Section-I gives a brief review of the fundamentals of fracture process. Section-II deals with modelling of ductile fracture by locally uncoupled type of models. In this section, the critical cavity growth parameters of the different models have been determined for the primary heat transport (PHT) piping material of Indian pressurised heavy water reactor (PHWR). A comparative study has been done among different models. The dependency of the critical parameters on stress triaxiality factor has also been studied. It is observed that Rice and Tracey's model is the most suitable one. But, its parameters are not fully independent of triaxiality factor. For this purpose, a modification to Rice and Tracery's model is suggested in Section-III. Section-IV deals with modelling of ductile fracture process by locally coupled type of models. Section-V deals with the modelling of cleavage fracture process by Beremins model, which is based on Weibulls

  2. Atomistic approach for modeling metal-semiconductor interfaces

    DEFF Research Database (Denmark)

    Stradi, Daniele; Martinez, Umberto; Blom, Anders

    2016-01-01

    realistic metal-semiconductor interfaces and allows for a direct comparison between theory and experiments via the I–V curve. In particular, it will be demonstrated how doping — and bias — modifies the Schottky barrier, and how finite size models (the slab approach) are unable to describe these interfaces......We present a general framework for simulating interfaces using an atomistic approach based on density functional theory and non-equilibrium Green's functions. The method includes all the relevant ingredients, such as doping and an accurate value of the semiconductor band gap, required to model...

  3. Differential T cell response against BK virus regulatory and structural antigens: A viral dynamics modelling approach.

    Directory of Open Access Journals (Sweden)

    Arturo Blazquez-Navarro

    2018-05-01

    Full Text Available BK virus (BKV associated nephropathy affects 1-10% of kidney transplant recipients, leading to graft failure in about 50% of cases. Immune responses against different BKV antigens have been shown to have a prognostic value for disease development. Data currently suggest that the structural antigens and regulatory antigens of BKV might each trigger a different mode of action of the immune response. To study the influence of different modes of action of the cellular immune response on BKV clearance dynamics, we have analysed the kinetics of BKV plasma load and anti-BKV T cell response (Elispot in six patients with BKV associated nephropathy using ODE modelling. The results show that only a small number of hypotheses on the mode of action are compatible with the empirical data. The hypothesis with the highest empirical support is that structural antigens trigger blocking of virus production from infected cells, whereas regulatory antigens trigger an acceleration of death of infected cells. These differential modes of action could be important for our understanding of BKV resolution, as according to the hypothesis, only regulatory antigens would trigger a fast and continuous clearance of the viral load. Other hypotheses showed a lower degree of empirical support, but could potentially explain the clearing mechanisms of individual patients. Our results highlight the heterogeneity of the dynamics, including the delay between immune response against structural versus regulatory antigens, and its relevance for BKV clearance. Our modelling approach is the first that studies the process of BKV clearance by bringing together viral and immune kinetics and can provide a framework for personalised hypotheses generation on the interrelations between cellular immunity and viral dynamics.

  4. Differential T cell response against BK virus regulatory and structural antigens: A viral dynamics modelling approach.

    Science.gov (United States)

    Blazquez-Navarro, Arturo; Schachtner, Thomas; Stervbo, Ulrik; Sefrin, Anett; Stein, Maik; Westhoff, Timm H; Reinke, Petra; Klipp, Edda; Babel, Nina; Neumann, Avidan U; Or-Guil, Michal

    2018-05-01

    BK virus (BKV) associated nephropathy affects 1-10% of kidney transplant recipients, leading to graft failure in about 50% of cases. Immune responses against different BKV antigens have been shown to have a prognostic value for disease development. Data currently suggest that the structural antigens and regulatory antigens of BKV might each trigger a different mode of action of the immune response. To study the influence of different modes of action of the cellular immune response on BKV clearance dynamics, we have analysed the kinetics of BKV plasma load and anti-BKV T cell response (Elispot) in six patients with BKV associated nephropathy using ODE modelling. The results show that only a small number of hypotheses on the mode of action are compatible with the empirical data. The hypothesis with the highest empirical support is that structural antigens trigger blocking of virus production from infected cells, whereas regulatory antigens trigger an acceleration of death of infected cells. These differential modes of action could be important for our understanding of BKV resolution, as according to the hypothesis, only regulatory antigens would trigger a fast and continuous clearance of the viral load. Other hypotheses showed a lower degree of empirical support, but could potentially explain the clearing mechanisms of individual patients. Our results highlight the heterogeneity of the dynamics, including the delay between immune response against structural versus regulatory antigens, and its relevance for BKV clearance. Our modelling approach is the first that studies the process of BKV clearance by bringing together viral and immune kinetics and can provide a framework for personalised hypotheses generation on the interrelations between cellular immunity and viral dynamics.

  5. Systems and context modeling approach to requirements analysis

    Science.gov (United States)

    Ahuja, Amrit; Muralikrishna, G.; Patwari, Puneet; Subhrojyoti, C.; Swaminathan, N.; Vin, Harrick

    2014-08-01

    Ensuring completeness and correctness of the requirements for a complex system such as the SKA is challenging. Current system engineering practice includes developing a stakeholder needs definition, a concept of operations, and defining system requirements in terms of use cases and requirements statements. We present a method that enhances this current practice into a collection of system models with mutual consistency relationships. These include stakeholder goals, needs definition and system-of-interest models, together with a context model that participates in the consistency relationships among these models. We illustrate this approach by using it to analyze the SKA system requirements.

  6. An approach to multiscale modelling with graph grammars.

    Science.gov (United States)

    Ong, Yongzhi; Streit, Katarína; Henke, Michael; Kurth, Winfried

    2014-09-01

    Functional-structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs. A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL. Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas. The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.

  7. A robust quantitative near infrared modeling approach for blend monitoring.

    Science.gov (United States)

    Mohan, Shikhar; Momose, Wataru; Katz, Jeffrey M; Hossain, Md Nayeem; Velez, Natasha; Drennen, James K; Anderson, Carl A

    2018-01-30

    This study demonstrates a material sparing Near-Infrared modeling approach for powder blend monitoring. In this new approach, gram scale powder mixtures are subjected to compression loads to simulate the effect of scale using an Instron universal testing system. Models prepared by the new method development approach (small-scale method) and by a traditional method development (blender-scale method) were compared by simultaneously monitoring a 1kg batch size blend run. Both models demonstrated similar model performance. The small-scale method strategy significantly reduces the total resources expended to develop Near-Infrared calibration models for on-line blend monitoring. Further, this development approach does not require the actual equipment (i.e., blender) to which the method will be applied, only a similar optical interface. Thus, a robust on-line blend monitoring method can be fully developed before any large-scale blending experiment is viable, allowing the blend method to be used during scale-up and blend development trials. Copyright © 2017. Published by Elsevier B.V.

  8. Deep Appearance Models: A Deep Boltzmann Machine Approach for Face Modeling

    OpenAIRE

    Duong, Chi Nhan; Luu, Khoa; Quach, Kha Gia; Bui, Tien D.

    2016-01-01

    The "interpretation through synthesis" approach to analyze face images, particularly Active Appearance Models (AAMs) method, has become one of the most successful face modeling approaches over the last two decades. AAM models have ability to represent face images through synthesis using a controllable parameterized Principal Component Analysis (PCA) model. However, the accuracy and robustness of the synthesized faces of AAM are highly depended on the training sets and inherently on the genera...

  9. Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models

    Science.gov (United States)

    Peltola, Olli; Raivonen, Maarit; Li, Xuefei; Vesala, Timo

    2018-02-01

    Emission via bubbling, i.e. ebullition, is one of the main methane (CH4) emission pathways from wetlands to the atmosphere. Direct measurement of gas bubble formation, growth and release in the peat-water matrix is challenging and in consequence these processes are relatively unknown and are coarsely represented in current wetland CH4 emission models. In this study we aimed to evaluate three ebullition modelling approaches and their effect on model performance. This was achieved by implementing the three approaches in one process-based CH4 emission model. All the approaches were based on some kind of threshold: either on CH4 pore water concentration (ECT), pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run using 4 years of data from a boreal sedge fen and the results were compared with eddy covariance measurements of CH4 fluxes.Modelled annual CH4 emissions were largely unaffected by the different ebullition modelling approaches; however, temporal variability in CH4 emissions varied an order of magnitude between the approaches. Hence the ebullition modelling approach drives the temporal variability in modelled CH4 emissions and therefore significantly impacts, for instance, high-frequency (daily scale) model comparison and calibration against measurements. The modelling approach based on the most recent knowledge of the ebullition process (volume threshold, EBG) agreed the best with the measured fluxes (R2 = 0.63) and hence produced the most reasonable results, although there was a scale mismatch between the measurements (ecosystem scale with heterogeneous ebullition locations) and model results (single horizontally homogeneous peat column). The approach should be favoured over the two other more widely used ebullition modelling approaches and researchers are encouraged to implement it into their CH4 emission models.

  10. Software sensors based on the grey-box modelling approach

    DEFF Research Database (Denmark)

    Carstensen, J.; Harremoës, P.; Strube, Rune

    1996-01-01

    In recent years the grey-box modelling approach has been applied to wastewater transportation and treatment Grey-box models are characterized by the combination of deterministic and stochastic terms to form a model where all the parameters are statistically identifiable from the on......-box model for the specific dynamics is identified. Similarly, an on-line software sensor for detecting the occurrence of backwater phenomena can be developed by comparing the dynamics of a flow measurement with a nearby level measurement. For treatment plants it is found that grey-box models applied to on......-line measurements. With respect to the development of software sensors, the grey-box models possess two important features. Firstly, the on-line measurements can be filtered according to the grey-box model in order to remove noise deriving from the measuring equipment and controlling devices. Secondly, the grey...

  11. Bianchi VI0 and III models: self-similar approach

    International Nuclear Information System (INIS)

    Belinchon, Jose Antonio

    2009-01-01

    We study several cosmological models with Bianchi VI 0 and III symmetries under the self-similar approach. We find new solutions for the 'classical' perfect fluid model as well as for the vacuum model although they are really restrictive for the equation of state. We also study a perfect fluid model with time-varying constants, G and Λ. As in other studied models we find that the behaviour of G and Λ are related. If G behaves as a growing time function then Λ is a positive decreasing time function but if G is decreasing then Λ 0 is negative. We end by studying a massive cosmic string model, putting special emphasis in calculating the numerical values of the equations of state. We show that there is no SS solution for a string model with time-varying constants.

  12. Environmental Radiation Effects on Mammals A Dynamical Modeling Approach

    CERN Document Server

    Smirnova, Olga A

    2010-01-01

    This text is devoted to the theoretical studies of radiation effects on mammals. It uses the framework of developed deterministic mathematical models to investigate the effects of both acute and chronic irradiation in a wide range of doses and dose rates on vital body systems including hematopoiesis, small intestine and humoral immunity, as well as on the development of autoimmune diseases. Thus, these models can contribute to the development of the system and quantitative approaches in radiation biology and ecology. This text is also of practical use. Its modeling studies of the dynamics of granulocytopoiesis and thrombocytopoiesis in humans testify to the efficiency of employment of the developed models in the investigation and prediction of radiation effects on these hematopoietic lines. These models, as well as the properly identified models of other vital body systems, could provide a better understanding of the radiation risks to health. The modeling predictions will enable the implementation of more ef...

  13. A new approach to Naturalness in SUSY models

    CERN Document Server

    Ghilencea, D M

    2013-01-01

    We review recent results that provide a new approach to the old problem of naturalness in supersymmetric models, without relying on subjective definitions for the fine-tuning associated with {\\it fixing} the EW scale (to its measured value) in the presence of quantum corrections. The approach can address in a model-independent way many questions related to this problem. The results show that naturalness and its measure (fine-tuning) are an intrinsic part of the likelihood to fit the data that {\\it includes} the EW scale. One important consequence is that the additional {\\it constraint} of fixing the EW scale, usually not imposed in the data fits of the models, impacts on their overall likelihood to fit the data (or chi^2/ndf, ndf: number of degrees of freedom). This has negative implications for the viability of currently popular supersymmetric extensions of the Standard Model.

  14. Model selection and inference a practical information-theoretic approach

    CERN Document Server

    Burnham, Kenneth P

    1998-01-01

    This book is unique in that it covers the philosophy of model-based data analysis and an omnibus strategy for the analysis of empirical data The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data Kullback-Leibler information represents a fundamental quantity in science and is Hirotugu Akaike's basis for model selection The maximized log-likelihood function can be bias-corrected to provide an estimate of expected, relative Kullback-Leibler information This leads to Akaike's Information Criterion (AIC) and various extensions and these are relatively simple and easy to use in practice, but little taught in statistics classes and far less understood in the applied sciences than should be the case The information theoretic approaches provide a unified and rigorous theory, an extension of likelihood theory, an important application of information theory, and are ...

  15. Merits of a Scenario Approach in Dredge Plume Modelling

    DEFF Research Database (Denmark)

    Pedersen, Claus; Chu, Amy Ling Chu; Hjelmager Jensen, Jacob

    2011-01-01

    Dredge plume modelling is a key tool for quantification of potential impacts to inform the EIA process. There are, however, significant uncertainties associated with the modelling at the EIA stage when both dredging methodology and schedule are likely to be a guess at best as the dredging...... contractor would rarely have been appointed. Simulation of a few variations of an assumed full dredge period programme will generally not provide a good representation of the overall environmental risks associated with the programme. An alternative dredge plume modelling strategy that attempts to encapsulate...... uncertainties associated with preliminary dredging programmes by using a scenario-based modelling approach is presented. The approach establishes a set of representative and conservative scenarios for key factors controlling the spill and plume dispersion and simulates all combinations of e.g. dredge, climatic...

  16. Regularization of quantum gravity in the matrix model approach

    International Nuclear Information System (INIS)

    Ueda, Haruhiko

    1991-02-01

    We study divergence problem of the partition function in the matrix model approach for two-dimensional quantum gravity. We propose a new model V(φ) = 1/2Trφ 2 + g 4 /NTrφ 4 + g'/N 4 Tr(φ 4 ) 2 and show that in the sphere case it has no divergence problem and the critical exponent is of pure gravity. (author)

  17. PASSENGER TRAFFIC MOVEMENT MODELLING BY THE CELLULAR-AUTOMAT APPROACH

    Directory of Open Access Journals (Sweden)

    T. Mikhaylovskaya

    2009-01-01

    Full Text Available The mathematical model of passenger traffic movement developed on the basis of the cellular-automat approach is considered. The program realization of the cellular-automat model of pedastrians streams movement in pedestrian subways at presence of obstacles, at subway structure narrowing is presented. The optimum distances between the obstacles and the angle of subway structure narrowing providing pedastrians stream safe movement and traffic congestion occurance are determined.

  18. The Generalised Ecosystem Modelling Approach in Radiological Assessment

    International Nuclear Information System (INIS)

    Klos, Richard

    2008-03-01

    An independent modelling capability is required by SSI in order to evaluate dose assessments carried out in Sweden by, amongst others, SKB. The main focus is the evaluation of the long-term radiological safety of radioactive waste repositories for both spent fuel and low-level radioactive waste. To meet the requirement for an independent modelling tool for use in biosphere dose assessments, SSI through its modelling team CLIMB commissioned the development of a new model in 2004, a project to produce an integrated model of radionuclides in the landscape. The generalised ecosystem modelling approach (GEMA) is the result. GEMA is a modular system of compartments representing the surface environment. It can be configured, through water and solid material fluxes, to represent local details in the range of ecosystem types found in the past, present and future Swedish landscapes. The approach is generic but fine tuning can be carried out using local details of the surface drainage system. The modular nature of the modelling approach means that GEMA modules can be linked to represent large scale surface drainage features over an extended domain in the landscape. System change can also be managed in GEMA, allowing a flexible and comprehensive model of the evolving landscape to be constructed. Environmental concentrations of radionuclides can be calculated and the GEMA dose pathway model provides a means of evaluating the radiological impact of radionuclide release to the surface environment. This document sets out the philosophy and details of GEMA and illustrates the functioning of the model with a range of examples featuring the recent CLIMB review of SKB's SR-Can assessment

  19. The Generalised Ecosystem Modelling Approach in Radiological Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Klos, Richard

    2008-03-15

    An independent modelling capability is required by SSI in order to evaluate dose assessments carried out in Sweden by, amongst others, SKB. The main focus is the evaluation of the long-term radiological safety of radioactive waste repositories for both spent fuel and low-level radioactive waste. To meet the requirement for an independent modelling tool for use in biosphere dose assessments, SSI through its modelling team CLIMB commissioned the development of a new model in 2004, a project to produce an integrated model of radionuclides in the landscape. The generalised ecosystem modelling approach (GEMA) is the result. GEMA is a modular system of compartments representing the surface environment. It can be configured, through water and solid material fluxes, to represent local details in the range of ecosystem types found in the past, present and future Swedish landscapes. The approach is generic but fine tuning can be carried out using local details of the surface drainage system. The modular nature of the modelling approach means that GEMA modules can be linked to represent large scale surface drainage features over an extended domain in the landscape. System change can also be managed in GEMA, allowing a flexible and comprehensive model of the evolving landscape to be constructed. Environmental concentrations of radionuclides can be calculated and the GEMA dose pathway model provides a means of evaluating the radiological impact of radionuclide release to the surface environment. This document sets out the philosophy and details of GEMA and illustrates the functioning of the model with a range of examples featuring the recent CLIMB review of SKB's SR-Can assessment

  20. Real-Time Adaptive Algorithms for Flight Control Diagnostics and Prognostics, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based machinery diagnostic and prognostic techniques depend upon high-quality mathematical models of the plant. Modeling uncertainties and errors decrease...

  1. Reduced modeling of signal transduction – a modular approach

    Directory of Open Access Journals (Sweden)

    Ederer Michael

    2007-09-01

    Full Text Available Abstract Background Combinatorial complexity is a challenging problem in detailed and mechanistic mathematical modeling of signal transduction. This subject has been discussed intensively and a lot of progress has been made within the last few years. A software tool (BioNetGen was developed which allows an automatic rule-based set-up of mechanistic model equations. In many cases these models can be reduced by an exact domain-oriented lumping technique. However, the resulting models can still consist of a very large number of differential equations. Results We introduce a new reduction technique, which allows building modularized and highly reduced models. Compared to existing approaches further reduction of signal transduction networks is possible. The method also provides a new modularization criterion, which allows to dissect the model into smaller modules that are called layers and can be modeled independently. Hallmarks of the approach are conservation relations within each layer and connection of layers by signal flows instead of mass flows. The reduced model can be formulated directly without previous generation of detailed model equations. It can be understood and interpreted intuitively, as model variables are macroscopic quantities that are converted by rates following simple kinetics. The proposed technique is applicable without using complex mathematical tools and even without detailed knowledge of the mathematical background. However, we provide a detailed mathematical analysis to show performance and limitations of the method. For physiologically relevant parameter domains the transient as well as the stationary errors caused by the reduction are negligible. Conclusion The new layer based reduced modeling method allows building modularized and strongly reduced models of signal transduction networks. Reduced model equations can be directly formulated and are intuitively interpretable. Additionally, the method provides very good

  2. A nonlinear complementarity approach for the national energy modeling system

    International Nuclear Information System (INIS)

    Gabriel, S.A.; Kydes, A.S.

    1995-01-01

    The National Energy Modeling System (NEMS) is a large-scale mathematical model that computes equilibrium fuel prices and quantities in the U.S. energy sector. At present, to generate these equilibrium values, NEMS sequentially solves a collection of linear programs and nonlinear equations. The NEMS solution procedure then incorporates the solutions of these linear programs and nonlinear equations in a nonlinear Gauss-Seidel approach. The authors describe how the current version of NEMS can be formulated as a particular nonlinear complementarity problem (NCP), thereby possibly avoiding current convergence problems. In addition, they show that the NCP format is equally valid for a more general form of NEMS. They also describe several promising approaches for solving the NCP form of NEMS based on recent Newton type methods for general NCPs. These approaches share the feature of needing to solve their direction-finding subproblems only approximately. Hence, they can effectively exploit the sparsity inherent in the NEMS NCP

  3. Non-frontal Model Based Approach to Forensic Face Recognition

    NARCIS (Netherlands)

    Dutta, A.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2012-01-01

    In this paper, we propose a non-frontal model based approach which ensures that a face recognition system always gets to compare images having similar view (or pose). This requires a virtual suspect reference set that consists of non-frontal suspect images having pose similar to the surveillance

  4. A Behavioral Decision Making Modeling Approach Towards Hedging Services

    NARCIS (Netherlands)

    Pennings, J.M.E.; Candel, M.J.J.M.; Egelkraut, T.M.

    2003-01-01

    This paper takes a behavioral approach toward the market for hedging services. A behavioral decision-making model is developed that provides insight into how and why owner-managers decide the way they do regarding hedging services. Insight into those choice processes reveals information needed by

  5. Export of microplastics from land to sea. A modelling approach

    NARCIS (Netherlands)

    Siegfried, Max; Koelmans, A.A.; Besseling, E.; Kroeze, C.

    2017-01-01

    Quantifying the transport of plastic debris from river to sea is crucial for assessing the risks of plastic debris to human health and the environment. We present a global modelling approach to analyse the composition and quantity of point-source microplastic fluxes from European rivers to the sea.

  6. The Bipolar Approach: A Model for Interdisciplinary Art History Courses.

    Science.gov (United States)

    Calabrese, John A.

    1993-01-01

    Describes a college level art history course based on the opposing concepts of Classicism and Romanticism. Contends that all creative work, such as film or architecture, can be categorized according to this bipolar model. Includes suggestions for objects to study and recommends this approach for art education at all education levels. (CFR)

  7. Teaching Modeling with Partial Differential Equations: Several Successful Approaches

    Science.gov (United States)

    Myers, Joseph; Trubatch, David; Winkel, Brian

    2008-01-01

    We discuss the introduction and teaching of partial differential equations (heat and wave equations) via modeling physical phenomena, using a new approach that encompasses constructing difference equations and implementing these in a spreadsheet, numerically solving the partial differential equations using the numerical differential equation…

  8. A review of function modeling : Approaches and applications

    NARCIS (Netherlands)

    Erden, M.S.; Komoto, H.; Van Beek, T.J.; D'Amelio, V.; Echavarria, E.; Tomiyama, T.

    2008-01-01

    This work is aimed at establishing a common frame and understanding of function modeling (FM) for our ongoing research activities. A comparative review of the literature is performed to grasp the various FM approaches with their commonalities and differences. The relations of FM with the research

  9. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

  10. Model-independent approach for dark matter phenomenology

    Indian Academy of Sciences (India)

    We have studied the phenomenology of dark matter at the ILC and cosmic positron experiments based on model-independent approach. We have found a strong correlation between dark matter signatures at the ILC and those in the indirect detection experiments of dark matter. Once the dark matter is discovered in the ...

  11. Model-independent approach for dark matter phenomenology ...

    Indian Academy of Sciences (India)

    Abstract. We have studied the phenomenology of dark matter at the ILC and cosmic positron experiments based on model-independent approach. We have found a strong correlation between dark matter signatures at the ILC and those in the indirect detec- tion experiments of dark matter. Once the dark matter is discovered ...

  12. The variational approach to the Glashow-Weinberg-Salam model

    International Nuclear Information System (INIS)

    Manka, R.; Sladkowski, J.

    1987-01-01

    The variational approach to the Glashow-Weinberg-Salam model, based on canonical quantization, is presented. It is shown that taking into consideration the Becchi-Rouet-Stora symmetry leads to the correct, temperature-dependent, effective potential. This generalization of the Weinberg-Coleman potential leads to a phase transition of the first kind

  13. Methodological Approach for Modeling of Multienzyme in-pot Processes

    DEFF Research Database (Denmark)

    Andrade Santacoloma, Paloma de Gracia; Roman Martinez, Alicia; Sin, Gürkan

    2011-01-01

    This paper presents a methodological approach for modeling multi-enzyme in-pot processes. The methodology is exemplified stepwise through the bi-enzymatic production of N-acetyl-D-neuraminic acid (Neu5Ac) from N-acetyl-D-glucosamine (GlcNAc). In this case study, sensitivity analysis is also used ...

  14. An Approach to Quality Estimation in Model-Based Development

    DEFF Research Database (Denmark)

    Holmegaard, Jens Peter; Koch, Peter; Ravn, Anders Peter

    2004-01-01

    We present an approach to estimation of parameters for design space exploration in Model-Based Development, where synthesis of a system is done in two stages. Component qualities like space, execution time or power consumption are defined in a repository by platform dependent values. Connectors...

  15. EXTENDE MODEL OF COMPETITIVITY THROUG APPLICATION OF NEW APPROACH DIRECTIVES

    Directory of Open Access Journals (Sweden)

    Slavko Arsovski

    2009-03-01

    Full Text Available The basic subject of this work is the model of new approach impact on quality and safety products, and competency of our companies. This work represents real hypothesis on the basis of expert's experiences, in regard to that the infrastructure with using new approach directives wasn't examined until now, it isn't known which product or industry of Serbia is related to directives of the new approach and CE mark, and it is not known which are effects of the use of the CE mark. This work should indicate existing quality reserves and product's safety, the level of possible competency improvement and increasing the profit by discharging new approach directive requires.

  16. Setting conservation management thresholds using a novel participatory modeling approach.

    Science.gov (United States)

    Addison, P F E; de Bie, K; Rumpff, L

    2015-10-01

    We devised a participatory modeling approach for setting management thresholds that show when management intervention is required to address undesirable ecosystem changes. This approach was designed to be used when management thresholds: must be set for environmental indicators in the face of multiple competing objectives; need to incorporate scientific understanding and value judgments; and will be set by participants with limited modeling experience. We applied our approach to a case study where management thresholds were set for a mat-forming brown alga, Hormosira banksii, in a protected area management context. Participants, including management staff and scientists, were involved in a workshop to test the approach, and set management thresholds to address the threat of trampling by visitors to an intertidal rocky reef. The approach involved trading off the environmental objective, to maintain the condition of intertidal reef communities, with social and economic objectives to ensure management intervention was cost-effective. Ecological scenarios, developed using scenario planning, were a key feature that provided the foundation for where to set management thresholds. The scenarios developed represented declines in percent cover of H. banksii that may occur under increased threatening processes. Participants defined 4 discrete management alternatives to address the threat of trampling and estimated the effect of these alternatives on the objectives under each ecological scenario. A weighted additive model was used to aggregate participants' consequence estimates. Model outputs (decision scores) clearly expressed uncertainty, which can be considered by decision makers and used to inform where to set management thresholds. This approach encourages a proactive form of conservation, where management thresholds and associated actions are defined a priori for ecological indicators, rather than reacting to unexpected ecosystem changes in the future. © 2015 The

  17. Treatments and other prognostic factors in the management of the open abdomen: A systematic review.

    Science.gov (United States)

    Cristaudo, Adam T; Jennings, Scott B; Hitos, Kerry; Gunnarsson, Ronny; DeCosta, Alan

    2017-02-01

    The open abdomen (OA) is an important approach for managing intra-abdominal catastrophes and continues to be the standard of care. Despite this, challenges remain with it associated with a high incidence of complications and poor outcomes. The objective of this article is to perform a systematic review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to identify prognostic factors in OA patients in regard to definitive fascial closure (DFC), mortality and intra-abdominal complications. An electronic database search was conducted involving Medline, Excerpta Medica, Central Register of Controlled Trials, Cumulative Index to Nursing, and Allied Health Literature and Clinicaltrials.gov. All studies that described prognostic factors in regard to the above outcomes in OA patients were eligible for inclusion. Data collected were synthesized by each outcome of interest and assessed for methodological quality. Thirty-one studies were included in the final synthesis. Enteral nutrition, organ dysfunction, local and systemic infection, number of reexplorations, worsening Injury Severity Score, and the development of a fistula appeared to significantly delay DFC. Age and Adult Physiology And Chronic Health Evaluation version II score were predictors for in-hospital mortality. Failed DFC, large bowel resection and >5 to 10 L of intravenous fluids in 5 to 10 and >10 L of intravenous fluids in management of OA patients will avoid prolonged treatment and facilitate early DFC. Future research should focus on the development of a prognostic model. Systematic review, level III.

  18. Accurate phenotyping: Reconciling approaches through Bayesian model averaging.

    Directory of Open Access Journals (Sweden)

    Carla Chia-Ming Chen

    Full Text Available Genetic research into complex diseases is frequently hindered by a lack of clear biomarkers for phenotype ascertainment. Phenotypes for such diseases are often identified on the basis of clinically defined criteria; however such criteria may not be suitable for understanding the genetic composition of the diseases. Various statistical approaches have been proposed for phenotype definition; however our previous studies have shown that differences in phenotypes estimated using different approaches have substantial impact on subsequent analyses. Instead of obtaining results based upon a single model, we propose a new method, using Bayesian model averaging to overcome problems associated with phenotype definition. Although Bayesian model averaging has been used in other fields of research, this is the first study that uses Bayesian model averaging to reconcile phenotypes obtained using multiple models. We illustrate the new method by applying it to simulated genetic and phenotypic data for Kofendred personality disorder-an imaginary disease with several sub-types. Two separate statistical methods were used to identify clusters of individuals with distinct phenotypes: latent class analysis and grade of membership. Bayesian model averaging was then used to combine the two clusterings for the purpose of subsequent linkage analyses. We found that causative genetic loci for the disease produced higher LOD scores using model averaging than under either individual model separately. We attribute this improvement to consolidation of the cores of phenotype clusters identified using each individual method.

  19. An Alternative Approach to the Extended Drude Model

    Science.gov (United States)

    Gantzler, N. J.; Dordevic, S. V.

    2018-05-01

    The original Drude model, proposed over a hundred years ago, is still used today for the analysis of optical properties of solids. Within this model, both the plasma frequency and quasiparticle scattering rate are constant, which makes the model rather inflexible. In order to circumvent this problem, the so-called extended Drude model was proposed, which allowed for the frequency dependence of both the quasiparticle scattering rate and the effective mass. In this work we will explore an alternative approach to the extended Drude model. Here, one also assumes that the quasiparticle scattering rate is frequency dependent; however, instead of the effective mass, the plasma frequency becomes frequency-dependent. This alternative model is applied to the high Tc superconductor Bi2Sr2CaCu2O8+δ (Bi2212) with Tc = 92 K, and the results are compared and contrasted with the ones obtained from the conventional extended Drude model. The results point to several advantages of this alternative approach to the extended Drude model.

  20. Multiphysics modeling using COMSOL a first principles approach

    CERN Document Server

    Pryor, Roger W

    2011-01-01

    Multiphysics Modeling Using COMSOL rapidly introduces the senior level undergraduate, graduate or professional scientist or engineer to the art and science of computerized modeling for physical systems and devices. It offers a step-by-step modeling methodology through examples that are linked to the Fundamental Laws of Physics through a First Principles Analysis approach. The text explores a breadth of multiphysics models in coordinate systems that range from 1D to 3D and introduces the readers to the numerical analysis modeling techniques employed in the COMSOL Multiphysics software. After readers have built and run the examples, they will have a much firmer understanding of the concepts, skills, and benefits acquired from the use of computerized modeling techniques to solve their current technological problems and to explore new areas of application for their particular technological areas of interest.