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Sample records for based life prediction

  1. Life prediction of Ni-base superalloy

    Indian Academy of Sciences (India)

    The accelerated creep life of the alloy was evaluated by using iso-stress parametric equations and Monkman–Grant method. Keywords. Rene 80 ... secondary or steady state creep rate to rupture life have been proposed to analyse data ... neous strain, ε0, a decelerating strain rate stage (primary creep) leads to a steady ...

  2. Life prediction of Ni-base superalloy

    Indian Academy of Sciences (India)

    et al (1984) and Castilo et al (1987) claimed that in the case of complex alloys, stress-rupture data exhibits high scatter, and that the Monkman–Grant relationship is unable to distin- guish degenerative effects caused during service. They pro- posed a modified equation which isolates the tertiary stage of creep life and creep ...

  3. A New Approach to Fatigue Life Prediction Based on Nucleation and Growth (Preprint)

    National Research Council Canada - National Science Library

    McClung, R. C; Francis, W. L; Hudak, S. J

    2006-01-01

    Prediction of total fatigue life in components is often performed by summing "initiation" and "propagation" life phases, where initiation life is based on stress-life or strain-life methods calibrated...

  4. Research on bearing life prediction based on support vector machine and its application

    International Nuclear Information System (INIS)

    Sun Chuang; Zhang Zhousuo; He Zhengjia

    2011-01-01

    Life prediction of rolling element bearing is the urgent demand in engineering practice, and the effective life prediction technique is beneficial to predictive maintenance. Support vector machine (SVM) is a novel machine learning method based on statistical learning theory, and is of advantage in prediction. This paper develops SVM-based model for bearing life prediction. The inputs of the model are features of bearing vibration signal and the output is the bearing running time-bearing failure time ratio. The model is built base on a few failed bearing data, and it can fuse information of the predicted bearing. So it is of advantage to bearing life prediction in practice. The model is applied to life prediction of a bearing, and the result shows the proposed model is of high precision.

  5. The Prediction of Fatigue Life Based on Four Point Bending Test

    NARCIS (Netherlands)

    Pramesti, F.P.; Molenaar, A.A.A.; Van de Ven, M.F.C.

    2013-01-01

    To be able to devise optimum strategies for maintenance and rehabilitation, it is essential to formulate an accurate prediction of pavement life and its maintenance needs. One of the pavement life prediction methods is based on the pavement's capability to sustain fatigue. If it were possible to

  6. Shelf Life Prediction for Canned Gudeg using Accelerated Shelf Life Testing (ASLT) Based on Arrhenius Method

    Science.gov (United States)

    Nurhayati, R.; Rahayu NH, E.; Susanto, A.; Khasanah, Y.

    2017-04-01

    Gudeg is traditional food from Yogyakarta. It is consist of jackfruit, chicken, egg and coconut milk. Gudeg generally have a short shelf life. Canning or commercial sterilization is one way to extend the shelf life of gudeg. This aims of this research is to predict the shelf life of Andrawinaloka canned gudeg with Accelerated Shelf Life Test methods, Arrhenius model. Canned gudeg stored at three different temperature, there are 37, 50 and 60°C for two months. Measuring the number of Thio Barbituric Acid (TBA), as a critical aspect, were tested every 7 days. Arrhenius model approach is done with the equation order 0 and order 1. The analysis showed that the equation of order 0 can be used as an approach to estimating the shelf life of canned gudeg. The storage of Andrawinaloka canned gudeg at 30°C is predicted untill 21 months and 24 months for 25°C.

  7. Predicting nature-based tourist roles: a life span perspective

    Science.gov (United States)

    James J. Murdy; Heather J. Gibson; Andrew Yiannakis

    2003-01-01

    The concept of stable, clearly identifiable patterns of tourist behavior, or roles, is a relatively recent development. Yiannakis and Gibson (1988, 1992) identified fifteen tourist roles based on leisure travelers' vacation behaviors. Building on this work, Gibson (1994) used discriminant analysis to determine the combination of needs and demographics are...

  8. The prediction of the residual life of electromechanical equipment based on the artificial neural network

    Science.gov (United States)

    Zhukovskiy, Yu L.; Korolev, N. A.; Babanova, I. S.; Boikov, A. V.

    2017-10-01

    This article is devoted to the prediction of the residual life based on an estimate of the technical state of the induction motor. The proposed system allows to increase the accuracy and completeness of diagnostics by using an artificial neural network (ANN), and also identify and predict faulty states of an electrical equipment in dynamics. The results of the proposed system for estimation the technical condition are probability technical state diagrams and a quantitative evaluation of the residual life, taking into account electrical, vibrational, indirect parameters and detected defects. Based on the evaluation of the technical condition and the prediction of the residual life, a decision is made to change the control of the operating and maintenance modes of the electric motors.

  9. Predictive modelling for shelf life determination of nutricereal based fermented baby food.

    Science.gov (United States)

    Rasane, Prasad; Jha, Alok; Sharma, Nitya

    2015-08-01

    A shelf life model based on storage temperatures was developed for a nutricereal based fermented baby food formulation. The formulated baby food samples were packaged and stored at 10, 25, 37 and 45 °C for a test storage period of 180 days. A shelf life study was conducted using consumer and semi-trained panels, along with chemical analysis (moisture and acidity). The chemical parameters (moisture and titratable acidity) were found inadequate in determining the shelf life of the formulated product. Weibull hazard analysis was used to determine the shelf life of the product based on sensory evaluation. Considering 25 and 50 % rejection probability, the shelf life of the baby food formulation was predicted to be 98 and 322 days, 84 and 271 days, 71 and 221 days and 58 and 171 days for the samples stored at 10, 25, 37 and 45 °C, respectively. A shelf life equation was proposed using the rejection times obtained from the consumer study. Finally, the formulated baby food samples were subjected to microbial analysis for the predicted shelf life period and were found microbiologically safe for consumption during the storage period of 360 days.

  10. Creep Rupture Life Prediction Based on Analysis of Large Creep Deformation

    Directory of Open Access Journals (Sweden)

    YE Wenming

    2016-08-01

    Full Text Available A creep rupture life prediction method for high temperature component was proposed. The method was based on a true stress-strain elastoplastic creep constitutive model and the large deformation finite element analysis method. This method firstly used the high-temperature tensile stress-strain curve expressed by true stress and strain and the creep curve to build materials' elastoplastic and creep constitutive model respectively, then used the large deformation finite element method to calculate the deformation response of high temperature component under a given load curve, finally the creep rupture life was determined according to the change trend of the responsive curve.The method was verified by durable test of TC11 titanium alloy notched specimens under 500 ℃, and was compared with the three creep rupture life prediction methods based on the small deformation analysis. Results show that the proposed method can accurately predict the high temperature creep response and long-term life of TC11 notched specimens, and the accuracy is better than that of the methods based on the average effective stress of notch ligament, the bone point stress and the fracture strain of the key point, which are all based on small deformation finite element analysis.

  11. Fatigue Life Prediction of Metallic Materials Based on the Combined Nonlinear Ultrasonic Parameter

    Science.gov (United States)

    Zhang, Yuhua; Li, Xinxin; Wu, Zhenyong; Huang, Zhenfeng; Mao, Hanling

    2017-08-01

    The fatigue life prediction of metallic materials is always a tough problem that needs to be solved in the mechanical engineering field because it is very important for the secure service of mechanical components. In this paper, a combined nonlinear ultrasonic parameter based on the collinear wave mixing technique is applied for fatigue life prediction of a metallic material. Sweep experiments are first conducted to explore the influence of driving frequency on the interaction of two driving signals and the fatigue damage of specimens, and the amplitudes of sidebands at the difference frequency and sum frequency are tracked when the driving frequency changes. Then, collinear wave mixing tests are carried out on a pair of cylindrically notched specimens with different fatigue damage to explore the relationship between the fatigue damage and the relative nonlinear parameters. The experimental results show when the fatigue degree is below 65% the relative nonlinear parameter increases quickly, and the growth rate is approximately 130%. If the fatigue degree is above 65%, the increase in the relative nonlinear parameter is slow, which has a close relationship with the microstructure evolution of specimens. A combined nonlinear ultrasonic parameter is proposed to highlight the relationship of the relative nonlinear parameter and fatigue degree of specimens; the fatigue life prediction model is built based on the relationship, and the prediction error is below 3%, which is below the prediction error based on the relative nonlinear parameters at the difference and sum frequencies. Therefore, the combined nonlinear ultrasonic parameter using the collinear wave mixing method can effectively estimate the fatigue degree of specimens, which provides a fast and convenient method for fatigue life prediction.

  12. Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter

    International Nuclear Information System (INIS)

    Son, Junbo; Zhou, Shiyu; Sankavaram, Chaitanya; Du, Xinyu; Zhang, Yilu

    2016-01-01

    In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. - Highlights: • A computationally efficient constrained Kalman filter is proposed. • Proposed filter is integrated into an online failure prognosis framework. • A set of proper constraints significantly improves the failure prediction accuracy. • Promising results are reported in the application of battery failure prognosis.

  13. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

    Science.gov (United States)

    Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat

    2015-05-01

    Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.

  14. Reliability residual-life prediction method for thermal aging based on performance degradation

    International Nuclear Information System (INIS)

    Ren Shuhong; Xue Fei; Yu Weiwei; Ti Wenxin; Liu Xiaotian

    2013-01-01

    The paper makes the study of the nuclear power plant main pipeline. The residual-life of the main pipeline that failed due to thermal aging has been studied by the use of performance degradation theory and Bayesian updating methods. Firstly, the thermal aging impact property degradation process of the main pipeline austenitic stainless steel has been analyzed by the accelerated thermal aging test data. Then, the thermal aging residual-life prediction model based on the impact property degradation data is built by Bayesian updating methods. Finally, these models are applied in practical situations. It is shown that the proposed methods are feasible and the prediction accuracy meets the needs of the project. Also, it provides a foundation for the scientific management of aging management of the main pipeline. (authors)

  15. Probabilistic Fatigue Life Prediction of Bridge Cables Based on Multiscaling and Mesoscopic Fracture Mechanics

    Directory of Open Access Journals (Sweden)

    Zhongxiang Liu

    2016-04-01

    Full Text Available Fatigue fracture of bridge stay-cables is usually a multiscale process as the crack grows from micro-scale to macro-scale. Such a process, however, is highly uncertain. In order to make a rational prediction of the residual life of bridge cables, a probabilistic fatigue approach is proposed, based on a comprehensive vehicle load model, finite element analysis and multiscaling and mesoscopic fracture mechanics. Uncertainties in both material properties and external loads are considered. The proposed method is demonstrated through the fatigue life prediction of cables of the Runyang Cable-Stayed Bridge in China, and it is found that cables along the bridge spans may have significantly different fatigue lives, and due to the variability, some of them may have shorter lives than those as expected from the design.

  16. Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

    Directory of Open Access Journals (Sweden)

    Ye Tian

    2014-01-01

    Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

  17. Predicting the life-time benefit of school-based smoking prevention programmes.

    Science.gov (United States)

    Jit, Mark; Aveyard, Paul; Barton, Pelham; Meads, Catherine A

    2010-06-01

    School-based smoking prevention programmes may delay the age of smoking initiation, but do not appear to achieve lasting reductions in smoking prevalence beyond school-leaving age. We explored whether delaying the age at which someone initiates smoking may have life-time benefits by increasing the likelihood of quitting in later life. Data from the General Household Survey of Great Britain were used in a logistic regression model to examine the association between age at which someone initiates regular smoking and the probability that the person will quit smoking later in life. The effect of confounding variables (sex, ethnicity, socio-economic class, education and geographical location) was taken into account. The predicted relationship was used in a cohort model to estimate the life-time reduction in smoking prevalence and all-cause mortality of a school-based smoking prevention programme. Age of regular smoking initiation was associated strongly with the probability of quitting later in life (coefficient -0.103, P < 0.001). The strength of the association was slightly reduced but still significant when confounding variables were included (coefficient -0.075, P < 0.001). An intervention that delays smoking initiation without decreasing smoking prevalence at age 18 may reduce adult smoking prevalence by 0.13-0.32% (depending on age) and all-cause mortality by 0.09% over the life-time of the sample. School-based smoking prevention programmes have potential for a beneficial effect over the life-time of the participants even if they have no apparent effect at school-leaving age.

  18. An Analytical Model for Fatigue Life Prediction Based on Fracture Mechanics and Crack Closure

    DEFF Research Database (Denmark)

    Ibsø, Jan Behrend; Agerskov, Henning

    1996-01-01

    test specimens are compared with fatigue life predictions using a fracture mechanics approach. In the calculation of the fatigue life, the influence of the welding residual stresses and crack closure on the fatigue crack growth is considered. A description of the crack closure model for analytical...

  19. Are the Performance Based Logistics Prophets Using Science or Alchemy to Create Life-Cycle Affordability? Using Theory to Predict the Efficacy of Performance Based Logistics

    Science.gov (United States)

    2013-10-01

    Based Logistics Prophets Using Science or Alchemy to Create Life-Cycle Affordability? Using Theory to Predict the Efficacy of Performance Based...Using Science or Alchemy to Create Life-Cycle Affordability? Using Theory to Predict the Efficacy of Performance Based Logistics 5a. CONTRACT NUMBER 5b...Are the PBL Prophets Using Science or Alchemy to Create Life Cycle Affordability? 328Defense ARJ, October 2013, Vol. 20 No. 3 : 325–348 Defense

  20. An Analytical Model for Fatigue Life Prediction Based on Fracture Mechanics and Crack Closure

    DEFF Research Database (Denmark)

    Ibsø, Jan Behrend; Agerskov, Henning

    1996-01-01

    test specimens are compared with fatigue life predictions using a fracture mechanics approach. In the calculation of the fatigue life, the influence of the welding residual stresses and crack closure on the fatigue crack growth is considered. A description of the crack closure model for analytical...... of the analytical fatigue lives. Both the analytical and experimental results obtained show that the Miner rule may give quite unconservative predictions of the fatigue life for the types of stochastic loading studied....... determination of the fatigue life is included. Furthermore, the results obtained in studies of the various parameters that have an influence on the fatigue life, are given. A very good agreement between experimental and analytical results is obtained, when the crack closure model is used in determination...

  1. Taylor Series-Based Long-Term Creep-Life Prediction of Alloy 617

    International Nuclear Information System (INIS)

    Yin, Song Nan; Kim, Woo Gon; Kim, Yong Wan; Park, Jae Young; Kim, Soen Jin

    2010-01-01

    In this study, a Taylor series (T-S) model based on the Arrhenius, McVetty, and Monkman-Grant equations was developed using a mathematical analysis. In order to reduce fitting errors, the McVetty equation was transformed by considering the first three terms of the Taylor series equation. The model parameters were accurately determined by a statistical technique of maximum likelihood estimation, and this model was applied to the creep data of alloy 617. The T-S model results showed better agreement with the experimental data than other models such as the Eno, exponential, and L-M models. In particular, the T-S model was converted into an isothermal Taylor series (IT-S) model that can predict the creep strength at a given temperature. It was identified that the estimations obtained using the converted ITS model was better than that obtained using the T-S model for predicting the long-term creep life of alloy 617

  2. Lithium-ion battery remaining useful life prediction based on grey support vector machines

    Directory of Open Access Journals (Sweden)

    Xiaogang Li

    2015-12-01

    Full Text Available In this article, an improved grey prediction model is proposed to address low-accuracy prediction issue of grey forecasting model. The first step is using a trigonometric function to transform the original data sequence to smooth the data, which is called smoothness of grey prediction model, and then a grey support vector machine model by integrating the improved grey model with support vector machine is introduced. At the initial stage of the model, trigonometric functions and accumulation generation operation can be used to preprocess the data, which enhances the smoothness of the data and reduces the associated randomness. In addition, support vector machine is implemented to establish a prediction model for the pre-processed data and select the optimal model parameters via genetic algorithms. Finally, the data are restored through the ‘regressive generate’ operation to obtain the forecasting data. To prove that the grey support vector machine model is superior to the other models, the battery life data from the Center for Advanced Life Cycle Engineering are selected, and the presented model is used to predict the remaining useful life of the battery. The predicted result is compared to that of grey model and support vector machines. For a more intuitive comparison of the three models, this article quantifies the root mean square errors for these three different models in the case of different ratio of training samples and prediction samples. The results show that the effect of grey support vector machine model is optimal, and the corresponding root mean square error is only 3.18%.

  3. Predictive modelling for shelf life determination of nutricereal based fermented baby food

    OpenAIRE

    Rasane, Prasad; Jha, Alok; Sharma, Nitya

    2014-01-01

    A shelf life model based on storage temperatures was developed for a nutricereal based fermented baby food formulation. The formulated baby food samples were packaged and stored at 10, 25, 37 and 45 °C for a test storage period of 180 days. A shelf life study was conducted using consumer and semi-trained panels, along with chemical analysis (moisture and acidity). The chemical parameters (moisture and titratable acidity) were found inadequate in determining the shelf life of the formulated pr...

  4. Physics-based Modeling Tools for Life Prediction and Durability Assessment of Advanced Materials, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The technical objectives of this program are: (1) to develop a set of physics-based modeling tools to predict the initiation of hot corrosion and to address pit and...

  5. Prediction of Combine Economic Life Based on Repair and Maintenance Costs Model

    Directory of Open Access Journals (Sweden)

    A Rohani

    2014-09-01

    Full Text Available Farm machinery managers often need to make complex economic decisions on machinery replacement. Repair and maintenance costs can have significant impacts on this economic decision. The farm manager must be able to predict farm machinery repair and maintenance costs. This study aimed to identify a regression model that can adequately represent the repair and maintenance costs in terms of machine age in cumulative hours of use. The regression model has the ability to predict the repair and maintenance costs for longer time periods. Therefore, it can be used for the estimation of the economic life. The study was conducted using field data collected from 11 John-Deer 955 combine harvesters used in several western provinces of Iran. It was found that power model has a better performance for the prediction of combine repair and maintenance costs. The results showed that the optimum replacement age of John-Deer 955 combine was 54300 cumulative hours.

  6. Developing a support vector machine based QSPR model for prediction of half-life of some herbicides.

    Science.gov (United States)

    Samghani, Kobra; HosseinFatemi, Mohammad

    2016-07-01

    The half-life (t1/2) of 58 herbicides were modeled by quantitative structure-property relationship (QSPR) based molecular structure descriptors. After calculation and the screening of a large number of molecular descriptors, the most relevant those ones selected by stepwise multiple linear regression were used for developing linear and nonlinear models which developed by using multiple linear regression and support vector machine, respectively. Comparison between statistical parameters of linear and nonlinear models indicates the suitability of SVM over MLR model for predicting the half-life of herbicides. The statistical parameters of R(2) and standard error for training set of SVM model were; 0.96 and 0.087, respectively, and were 0.93 and 0.092 for the test set. The SVM model was evaluated by leave one out cross validation test, which its result indicates the robustness and predictability of the model. The established SVM model was used for predicting the half-life of other herbicides that are located in the applicability domain of model that were determined via leverage approach. The results of this study indicate that the relationship among selected molecular descriptors and herbicide's half-life is non-linear. These results emphases that the process of degradation of herbicides in the environment is very complex and can be affected by various environmental and structural features, therefore simple linear model cannot be able to successfully predict it. Copyright © 2016. Published by Elsevier Inc.

  7. Prediction of Quality of Life of Non–Insulin-Dependent Diabetic Patients Based on Perceived Social Support

    Directory of Open Access Journals (Sweden)

    Hossein Shareh

    2012-04-01

    Full Text Available Background: The objective of this study was to predic quality of life based on perceived social support components in non–insulin-dependent diabetic patients.Materials and Method: Fifty patients with non–insulin-dependent diabetes mellitus from Al-Zahra diabetic center in Shiraz participated in a cross-sectional study via survey instrument. All subjects completed multidimensional scale of perceived social support (MSPSS and world health organization quality of life- brief (WHOQOL-BREF questionnaires. Results: On the basis of stepwise multiple regression analysis friends and family dimensions of perceived social support were the best predictors of the quality of life and its dimensions (p<0.01.Conclusion: Friends and family dimensions of perceived social support have significant contributions in predicting quality of life of patients with non–insulin-dependent diabetes mellitus.

  8. Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study

    Science.gov (United States)

    Pekkala, Timo; Hall, Anette; Lötjönen, Jyrki; Mattila, Jussi; Soininen, Hilkka; Ngandu, Tiia; Laatikainen, Tiina; Kivipelto, Miia; Solomon, Alina

    2016-01-01

    Background and objective: This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study. Methods: The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study. The main study population included 709 cognitively normal subjects at first re-examination who returned to the second re-examination up to 10 years later (incident dementia n = 39). An extended population (n = 1009, incident dementia 151) included non-participants/non-survivors (national registers data). DSI was used to develop a dementia index based on first re-examination assessments. Performance in predicting dementia was assessed as area under the ROC curve (AUC). Results: AUCs for DSI were 0.79 and 0.75 for main and extended populations. Included predictors were cognition, vascular factors, age, subjective memory complaints, and APOE genotype. Conclusion: The supervised machine learning method performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. DSI could thus be useful for identifying individuals who are most at risk and may benefit from dementia prevention interventions. PMID:27802228

  9. Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

    Science.gov (United States)

    Pekkala, Timo; Hall, Anette; Lötjönen, Jyrki; Mattila, Jussi; Soininen, Hilkka; Ngandu, Tiia; Laatikainen, Tiina; Kivipelto, Miia; Solomon, Alina

    2017-01-01

    This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study. The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study. The main study population included 709 cognitively normal subjects at first re-examination who returned to the second re-examination up to 10 years later (incident dementia n = 39). An extended population (n = 1009, incident dementia 151) included non-participants/non-survivors (national registers data). DSI was used to develop a dementia index based on first re-examination assessments. Performance in predicting dementia was assessed as area under the ROC curve (AUC). AUCs for DSI were 0.79 and 0.75 for main and extended populations. Included predictors were cognition, vascular factors, age, subjective memory complaints, and APOE genotype. The supervised machine learning method performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. DSI could thus be useful for identifying individuals who are most at risk and may benefit from dementia prevention interventions.

  10. Prediction of Fatigue Life of a Continuous Bridge Girder Based on Vehicle Induced Stress History

    Directory of Open Access Journals (Sweden)

    V.G. Rao

    2003-01-01

    Full Text Available The fatigue damage assessment of bridge components by conducting a full scale fatigue testing is often prohibitive. A need, therefore, exists to estimate the fatigue damage in bridge components by a simulation of bridge-vehicle interaction dynamics due to the action of the actual traffic. In the present paper, a systematic method has been outlined to find the fatigue damage in the continuous bridge girder based on stress range frequency histogram and fatigue strength parameters of the bridge materials. Vehicle induced time history of maximum flexural stresses has been obtained by Monte Carlo simulation process and utilized to develop the stress range frequency histogram taking into consideration of the annual traffic volume. The linear damage accumulation theory is then applied to calculate cumulative damage index and fatigue life of the bridge. Effect of the bridge span, pavement condition, increase of vehicle operating speed, weight and suspension characteristics on fatigue life of the bridge have been examined.

  11. Thermal fatigue life prediction based on crack propagation behaviors in high-temperature materials for power plant components

    International Nuclear Information System (INIS)

    Nitta, Akihito; Ogata, Takashi; Kuwabara, Kazuo

    1986-01-01

    For reducing an electric power supply cost, it is desired to extend the life of thermal power plant being still supplying the greater part of electric power in Japan. It is, therefore, becoming more and more important for the remaining life control of long-operated thermal power plants to exactly estimate the thermal fatigue damage accumulating in high temperature components. In this report, a discussion was made on thermal fatigue life laws derived from the crack propagation laws. As a result, the life laws were found to be effective for the evaluation of thermal fatigue life as well as isothermal fatigue life. Based on the concept of the life laws, the thermal and isothermal fatigue lives were also predicted as a propagation period of a crack with initial length equal to grain size from the characteristics of high temperature fatigue crack propagation. In addition to them, the rapid straining method was found to be required for more accurate estimation of creep strain in in-phase thermal fatigue. (author)

  12. L70 life prediction for solid state lighting using Kalman Filter and Extended Kalman Filter based models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, Lynn

    2013-08-08

    Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life

  13. A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Paulino José García Nieto

    2016-05-01

    Full Text Available Remaining useful life (RUL estimation is considered as one of the most central points in the prognostics and health management (PHM. The present paper describes a nonlinear hybrid ABC–MARS-based model for the prediction of the remaining useful life of aircraft engines. Indeed, it is well-known that an accurate RUL estimation allows failure prevention in a more controllable way so that the effective maintenance can be carried out in appropriate time to correct impending faults. The proposed hybrid model combines multivariate adaptive regression splines (MARS, which have been successfully adopted for regression problems, with the artificial bee colony (ABC technique. This optimization technique involves parameter setting in the MARS training procedure, which significantly influences the regression accuracy. However, its use in reliability applications has not yet been widely explored. Bearing this in mind, remaining useful life values have been predicted here by using the hybrid ABC–MARS-based model from the remaining measured parameters (input variables for aircraft engines with success. A correlation coefficient equal to 0.92 was obtained when this hybrid ABC–MARS-based model was applied to experimental data. The agreement of this model with experimental data confirmed its good performance. The main advantage of this predictive model is that it does not require information about the previous operation states of the aircraft engine.

  14. Prediction of material creep behaviour for strain based life assessment applications

    Energy Technology Data Exchange (ETDEWEB)

    Rantala, J.H.; Hurst, R.C. [EC JRC IAM, Petten (Netherlands); Bregani, F. [ENEL, Milan (Italy)

    1998-12-31

    In this work the idea of using constant load uniaxial creep test results instead of constant stress results for developing a CDM creep model for the P92 material is demonstrated. Due to limited availability of creep test results this work is based on incomplete test data and a general stress rupture line. In spite of these limitations a material creep model was developed for use in a FE analysis. Using P91 material as an example, a method is proposed to account for differences in strain evolution as a function of stress which normally manifests itself as lower strain values at low stresses in a normalised time-strain plot. This allows the CDM model to be used both in FE analysis and in strain-based life assessment engineering calculations. (orig.) 3 refs.

  15. Life Prediction of Seals

    National Research Council Canada - National Science Library

    Cassenti, Brice

    1998-01-01

    .... One method was based on measuring multiple rebounds of a pendulum dropped against the O-ring The second was based on determining the force displacement response of O-rings squeezed between two...

  16. Rolling Bearing Life Prediction, Theory, and Application

    Science.gov (United States)

    Zaretsky, Erwin V.

    2016-01-01

    A tutorial is presented outlining the evolution, theory, and application of rolling-element bearing life prediction from that of A. Palmgren, 1924; W. Weibull, 1939; G. Lundberg and A. Palmgren, 1947 and 1952; E. Ioannides and T. Harris, 1985; and E. Zaretsky, 1987. Comparisons are made between these life models. The Ioannides-Harris model without a fatigue limit is identical to the Lundberg-Palmgren model. The Weibull model is similar to that of Zaretsky if the exponents are chosen to be identical. Both the load-life and Hertz stress-life relations of Weibull, Lundberg and Palmgren, and Ioannides and Harris reflect a strong dependence on the Weibull slope. The Zaretsky model decouples the dependence of the critical shear stress-life relation from the Weibull slope. This results in a nominal variation of the Hertz stress-life exponent. For 9th- and 8th-power Hertz stress-life exponents for ball and roller bearings, respectively, the Lundberg-Palmgren model best predicts life. However, for 12th- and 10th-power relations reflected by modern bearing steels, the Zaretsky model based on the Weibull equation is superior. Under the range of stresses examined, the use of a fatigue limit would suggest that (for most operating conditions under which a rolling-element bearing will operate) the bearing will not fail from classical rolling-element fatigue. Realistically, this is not the case. The use of a fatigue limit will significantly overpredict life over a range of normal operating Hertz stresses. (The use of ISO 281:2007 with a fatigue limit in these calculations would result in a bearing life approaching infinity.) Since the predicted lives of rolling-element bearings are high, the problem can become one of undersizing a bearing for a particular application. Rules had been developed to distinguish and compare predicted lives with those actually obtained. Based upon field and test results of 51 ball and roller bearing sets, 98 percent of these bearing sets had acceptable

  17. Predicting quality of life after breast cancer surgery using ANN-based models: performance comparison with MR.

    Science.gov (United States)

    Tsai, Jinn-Tsong; Hou, Ming-Feng; Chen, Yao-Mei; Wan, Thomas T H; Kao, Hao-Yun; Shi, Hon-Yi

    2013-05-01

    The goal was to develop models for predicting long-term quality of life (QOL) after breast cancer surgery. Data were obtained from 203 breast cancer patients who completed the SF-36 health survey before and 2 years after surgery. Two of the models used to predict QOL after surgery were artificial neural networks (ANNs), which included one multilayer perceptron (MLP) network and one radial basis function (RBF) network. The third model was a multiple regression (MR) model. The criteria for evaluating the accuracy of the system models were mean square error (MSE) and mean absolute percentage error (MAPE). Compared to the MR model, the ANN-based models generally had smaller MSE values and smaller MAPE values in the test data set. One exception was the second year MSE for the test value. Most MAPE values for the ANN models ranged from 10 to 20 %. The one exception was the 6-month physical component summary score (PCS), which ranged from 23.19 to 26.86 %. Comparison of criteria for evaluating system performance showed that the ANN-based systems outperformed the MR system in terms of prediction accuracy. In both the MLP and RBF networks, surgical procedure type was the most sensitive parameter affecting PCS, and preoperative functional status was the most sensitive parameter affecting mental component summary score. The three systems can be combined to obtain a conservative prediction, and a combined approach is a potential supplemental tool for predicting long-term QOL after surgical treatment for breast cancer. Patients should also be advised that their postoperative QOL might depend not only on the success of their operations but also on their preoperative functional status.

  18. Prediction of the Maximum Temperature for Life Based on the Stability of Metabolites to Decomposition in Water

    Directory of Open Access Journals (Sweden)

    William Bains

    2015-03-01

    Full Text Available The components of life must survive in a cell long enough to perform their function in that cell. Because the rate of attack by water increases with temperature, we can, in principle, predict a maximum temperature above which an active terrestrial metabolism cannot function by analysis of the decomposition rates of the components of life, and comparison of those rates with the metabolites’ minimum metabolic half-lives. The present study is a first step in this direction, providing an analytical framework and method, and analyzing the stability of 63 small molecule metabolites based on literature data. Assuming that attack by water follows a first order rate equation, we extracted decomposition rate constants from literature data and estimated their statistical reliability. The resulting rate equations were then used to give a measure of confidence in the half-life of the metabolite concerned at different temperatures. There is little reliable data on metabolite decomposition or hydrolysis rates in the literature, the data is mostly confined to a small number of classes of chemicals, and the data available are sometimes mutually contradictory because of varying reaction conditions. However, a preliminary analysis suggests that terrestrial biochemistry is limited to environments below ~150–180 °C. We comment briefly on why pressure is likely to have a small effect on this.

  19. Actual service life prediction of building components

    DEFF Research Database (Denmark)

    Aagaard, Niels-Jørgen; Brandt, Erik; Hansen, Ernst Jan de Place

    2014-01-01

    , the paper presents an analysis of service life of buildings as such with respect to the use of the building partially based on analysis of data from the nationwide Danish register of buildings and housing as well as turnover in the Danish construction industry from refurbishment and demolition activities......In recent years, sustainability and life cycle cost in the construction industry have been given great attention in many countries due to the heavy climatic and environmental impact from this sector. In Denmark, a sustainability certification scheme for buildings has been developed including...... a condensed method for assessment of life cycle costs for buildings. Estimation of life cycle costs has traditionally been based on predicted service life for building components in terms of technical performance. This paper suggests a method for taking into account other contributing factors...

  20. Shelf-Life Prediction of Extra Virgin Olive Oils Using an Empirical Model Based on Standard Quality Tests

    OpenAIRE

    Guillaume, Claudia; Ravetti, Leandro

    2016-01-01

    Extra virgin olive oil shelf-life could be defined as the length of time under normal storage conditions within which no off-flavours or defects are developed and quality parameters such as peroxide value and specific absorbance are retained within accepted limits for this commercial category. Prediction of shelf-life is a desirable goal in the food industry. Even when extra virgin olive oil shelf-life should be one of the most important quality markers for extra virgin olive oil, it is not r...

  1. FATIGUE LIFE PREDICTION BASED ON MACROSCOPIC PLASTIC ZONE ON FRACTURE SURFACE OF AISI-SAE 1018 STEEL

    Directory of Open Access Journals (Sweden)

    G.M. Domínguez Almaraz

    2010-06-01

    Full Text Available This paper deals with rotating bending fatigue tests at high speed (150 Hz carried out on AISI-SAE 1018 steel with a high content of impurities (non metallic inclusions, for which the high experimental stress inside the specimen is close to the elastic limit of the material. Simulations of rotating loading are obtained by Visual NASTRAN software in order to determine the numerical stresse and strain distributions inside a hypothetical homogeneous specimen; later, this information is used for the experimental set up. A general description of experimental test machine and experimental conditions are developed and then, the experimental results are presented and discussed according the observed failure origin related to the non metallic inclusions and the associated high stress zones. Finally, a simple model is proposed to predict the fatigue life for this non homogeneous steel under high speed rotating bending fatigue tests close to the elastic limit, based on the rate between the visual macro-plastic deformation zone at fracture surface and the total fracture surface, together with the crack initiation inclusion (or inclusions located at this zone.

  2. Development of Reliability Based Life Prediction Methods for Thermal and Environmental Barrier Coatings in Ceramic Matrix Composites

    Science.gov (United States)

    Shah, Ashwin

    2001-01-01

    Literature survey related to the EBC/TBC (environmental barrier coating/thermal barrier coating) fife models, failure mechanisms in EBC/TBC and the initial work plan for the proposed EBC/TBC life prediction methods development was developed as well as the finite element model for the thermal/stress analysis of the GRC-developed EBC system was prepared. Technical report for these activities is given in the subsequent sections.

  3. Novel Approach for Lithium-Ion Battery On-Line Remaining Useful Life Prediction Based on Permutation Entropy

    Directory of Open Access Journals (Sweden)

    Luping Chen

    2018-04-01

    Full Text Available The degradation of lithium-ion battery often leads to electrical system failure. Battery remaining useful life (RUL prediction can effectively prevent this failure. Battery capacity is usually utilized as health indicator (HI for RUL prediction. However, battery capacity is often estimated on-line and it is difficult to be obtained by monitoring on-line parameters. Therefore, there is a great need to find a simple and on-line prediction method to solve this issue. In this paper, as a novel HI, permutation entropy (PE is extracted from the discharge voltage curve for analyzing battery degradation. Then the similarity between PE and battery capacity are judged by Pearson and Spearman correlation analyses. Experiment results illustrate the effectiveness and excellent similar performance of the novel HI for battery fading indication. Furthermore, we propose a hybrid approach combining Variational mode decomposition (VMD denoising technique, autoregressive integrated moving average (ARIMA, and GM(1,1 models for RUL prediction. Experiment results illustrate the accuracy of the proposed approach for lithium-ion battery on-line RUL prediction.

  4. Programming Useful Life Prediction (PULP) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements....

  5. Life Prediction of Low Cycle Fatigue for Ni-base Superalloy GTD111 DS at Elevated Temperature

    International Nuclear Information System (INIS)

    Kim, Jin Yeol; Yoon, Dong Hyun; Kim, Jae Hoon; Bae, Si Yeon; Chang, Sung Yong; Chang, Sung Ho

    2017-01-01

    GTD111 DS of nickel base superalloy has been used for gas turbine blades. In this study, low cycle fatigue test was conducted on the GTD111 DS alloy by setting conditions similar to the real operating environment. The low cycle fatigue tests were conducted at room temperature, 760 °C, 870 °C, and various strain amplitudes. Test results showed that fatigue life decreased with increasing total strain amplitude. Cyclic hardening response was observed at room temperature and 760 °C; however, tests conducted at 870 °C showed cyclic softening response. Stress relaxation was observed at 870 °C because creep effects occurred from holding time. A relationship between fatigue life and total strain range was obtained from the Coffin-Manson method. The fratography using a SEM was carried out at the crack initiation and propagation regions.

  6. End-of-Discharge and End-of-Life Prediction in Lithium-Ion Batteries with Electrochemistry-Based Aging Models

    Science.gov (United States)

    Daigle, Matthew; Kulkarni, Chetan S.

    2016-01-01

    As batteries become increasingly prevalent in complex systems such as aircraft and electric cars, monitoring and predicting battery state of charge and state of health becomes critical. In order to accurately predict the remaining battery power to support system operations for informed operational decision-making, age-dependent changes in dynamics must be accounted for. Using an electrochemistry-based model, we investigate how key parameters of the battery change as aging occurs, and develop models to describe aging through these key parameters. Using these models, we demonstrate how we can (i) accurately predict end-of-discharge for aged batteries, and (ii) predict the end-of-life of a battery as a function of anticipated usage. The approach is validated through an experimental set of randomized discharge profiles.

  7. Fatigue life prediction in composites

    CSIR Research Space (South Africa)

    Huston, RJ

    1994-01-01

    Full Text Available epoxy were used to test residual strength and residual stiffness models. Further fatigue tests were carried out under spectrum loading so that the results could be correlated with the cumulative damage predicted by the residual strength model....

  8. PREDIKSI MASA KEDALUWARSA WAFER DENGAN ARTIFICIAL NEURAL NETWORK (ANN BERDASARKAN PARAMETER NILAI KAPASITANSI (Prediction of Wafer Shelf Life Using Artificial Neural Network Based on Capacitance Parameter

    Directory of Open Access Journals (Sweden)

    Erna Rusliana Muhamad Saleh

    2014-02-01

    Full Text Available Wafer is type of biscuit frequently found on expired condition in market, therefore prediction method should be implemented to avoid this condition. apart from the prediction of shelf-life of wafer done by laboratory test, which were time-consuming, expensive, required trained panelists, complex equipment and suitable ambience, artificial neural network (ANN based dielectric parameters was proposed in nthis study. The aim of study was to develop model to predict shelf-life employing aNN based capacitance parameter. Back propagation algorithm with trial and error was applied in variations of nodes per hidden layer, number of hidden layers, activation functions, the function of learnings and epochs. The result of study was the model was able to predict wafer shelf-life. The accuracy level was shown by low MSE value (0.01 and high coefficient correlation value (89.25%. Keywords: artificial Neural Network, shelf-life, waffer, dielectric, capacitance   ABSTRAK Wafer adalah jenis makanan kering yang sering ditemukan kedaluwarsa. Penentuan masa kedaluwarsa dengan observasi laboratorium memiliki beberapa kelemahan, diantaranya memakan waktu, panelis terlatih, suasana yang tepat, biaya dan alat uji yang kompleks. alternatif solusinya adalah penggunaan artificial Neural Network (ANN berbasiskan parameter kapasitansi. Tujuan kerja ilmiah ini adalah untuk memprediksi masa kedaluwarsa wafer menggunakan aNN berbasiskan parameter kapasitansi. algoritma pembelajaran yang digunakan adalah Backpropagation dengan trial and error variasi jumlah node per hidden layer, jumlah hidden layer, fungsi aktivasi, fungsi pembelajaran dan epoch. Hasil prediksi menunjukkan bahwa aNN hasil pelatihan yang dikombinasikan dengan parameter kapasitansi mampu memprediksi masa kedaluwarsa wafer dengan MSE terendah 0,01 dan R tertinggi 89,25%. Kata kunci: Jaringan Syaraf Tiruan, masa kedaluwarsa, wafer, dielektrik, kapasitansi

  9. Research on the Fatigue Life Prediction Method of Thrust Rod

    Directory of Open Access Journals (Sweden)

    Guoyu Feng

    2016-01-01

    Full Text Available Purpose of this paper is to investigate the fatigue life prediction method of the thrust rod based on the continuum damage mechanics. The equivalent stress used as damage parameters established rubber fatigue life prediction model. Through the finite element simulation and material test, the model parameters and the fatigue damage dangerous positions were obtained. By equivalent stress life model, uniaxial fatigue life of the V-type thrust rod is analyzed to predict the ratio of life and the life of the test was 1.73, within an acceptable range, and the fatigue damage occurring position and finite element analysis are basically the same. Fatigue life analysis shows that the method is of correct, theoretical, and practical value.

  10. Programming Useful Life Prediction (PULP), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements. Relying on...

  11. Risk Factors Analysis and Death Prediction in Some Life-Threatening Ailments Using Chi-Square Case-Based Reasoning (χ2 CBR) Model.

    Science.gov (United States)

    Adeniyi, D A; Wei, Z; Yang, Y

    2018-01-30

    A wealth of data are available within the health care system, however, effective analysis tools for exploring the hidden patterns in these datasets are lacking. To alleviate this limitation, this paper proposes a simple but promising hybrid predictive model by suitably combining the Chi-square distance measurement with case-based reasoning technique. The study presents the realization of an automated risk calculator and death prediction in some life-threatening ailments using Chi-square case-based reasoning (χ 2 CBR) model. The proposed predictive engine is capable of reducing runtime and speeds up execution process through the use of critical χ 2 distribution value. This work also showcases the development of a novel feature selection method referred to as frequent item based rule (FIBR) method. This FIBR method is used for selecting the best feature for the proposed χ 2 CBR model at the preprocessing stage of the predictive procedures. The implementation of the proposed risk calculator is achieved through the use of an in-house developed PHP program experimented with XAMP/Apache HTTP server as hosting server. The process of data acquisition and case-based development is implemented using the MySQL application. Performance comparison between our system, the NBY, the ED-KNN, the ANN, the SVM, the Random Forest and the traditional CBR techniques shows that the quality of predictions produced by our system outperformed the baseline methods studied. The result of our experiment shows that the precision rate and predictive quality of our system in most cases are equal to or greater than 70%. Our result also shows that the proposed system executes faster than the baseline methods studied. Therefore, the proposed risk calculator is capable of providing useful, consistent, faster, accurate and efficient risk level prediction to both the patients and the physicians at any time, online and on a real-time basis.

  12. Service life prediction and cementitious composites

    DEFF Research Database (Denmark)

    Stoklund Larsen, E.

    The present Ph.D.thesis describes and discusses the applicability of a systematic methodology recommended by CIB W80/RILEM-PSL for sevice life prediction. The report describes the most important inherent and environmental factors affecting the service life of structures of cementitious composites...

  13. CT based muscle density predicts muscle function and health-related quality of life in patients with idiopathic inflammatory myopathies

    Science.gov (United States)

    Cleary, Laura C.; Crofford, Leslie J.; Long, Douglas; Charnigo, Richard; Clasey, Jody; Beaman, Francesca; Jenkins, Kirk A.; Fraser, Natasha; Srinivas, Archana; Dhaon, Nicole; Hanaoka, Beatriz Y.

    2016-01-01

    Objective To investigate the association of low-density (lipid-rich) muscle measured by computed tomography (CT) with skeletal muscle function and health-related quality of life in idiopathic inflammatory myopathies (IIMs). Methods Seventeen patients and ten healthy controls underwent CT of the mid-thigh to quantify high (30-100HU) and low density (0-29HU) skeletal muscle areas. Anthropometric measures, body composition, physical activity level, health-related quality of life, skeletal muscle strength, endurance and fatigue were assessed. Patients were compared against controls. The relationship of anthropometric, body composition and disease variables with measures of muscle function were examined using Spearman’s test on the patient group. Linear regression was used to assess the age-and disease-adjusted relationship of muscle quality to physical function and muscle strength. Results Patients had higher body fat% (p=0.042), trunk fat mass (p=0.042), android/gynoid fat (p=0.033) and mid-thigh low density muscle/total muscle area (p<0.001) compared to controls. Mid-thigh low density muscle/total muscle area was negatively correlated with self-reported physical function, strength and endurance; the SF-36 physical functioning (p=0.004), manual muscle testing (p=0.020), knee maximal voluntary isometric contraction/thigh mineral free lean mass (p<0.001) and the endurance step test (p<0.001), suggesting that muscle quality impacts function in IIM. Using multiple linear regression adjusted for age, global disease damage, and total fat mass, poor muscle quality as measured by mid-thigh low density muscle/total muscle area was negatively associated with SF-36 physical functioning (p= 0.009). Conclusion Mid-thigh low density muscle/ total muscle area is a good predictor of muscle strength, endurance and health-related quality of life as it pertains to physical functioning in patients with IIMs. PMID:25623494

  14. A Predictive Framework for Thermomechanical Fatigue Life of High Silicon Molybdenum Ductile Cast Iron Based on Considerations of Strain Energy Dissipation

    Science.gov (United States)

    Avery, Katherine R.

    Isothermal low cycle fatigue (LCF) and anisothermal thermomechanical fatigue (TMF) tests were conducted on a high silicon molybdenum (HiSiMo) cast iron for temperatures up to 1073K. LCF and out-of-phase (OP) TMF lives were significantly reduced when the temperature was near 673K due to an embrittlement phenomenon which decreases the ductility of HiSiMo at this temperature. In this case, intergranular fracture was predominant, and magnesium was observed at the fracture surface. When the thermal cycle did not include 673K, the failure mode was predominantly transgranular, and magnesium was not present on the fracture surface. The in-phase (IP) TMF lives were unaffected when the thermal cycle included 673K, and the predominant failure mode was found to be transgranular fracture, regardless of the temperature. No magnesium was present on the IP TMF fracture surfaces. Thus, the embrittlement phenomenon was found to contribute to fatigue damage only when the temperature was near 673K and a tensile stress was present. To account for the temperature- and stress-dependence of the embrittlement phenomenon on the TMF life of HiSiMo cast iron, an original model based on the cyclic inelastic energy dissipation is proposed which accounts for temperature-dependent differences in the rate of fatigue damage accumulation in tension and compression. The proposed model has few empirical parameters. Despite the simplicity of the model, the predicted fatigue life shows good agreement with more than 130 uniaxial low cycle and thermomechanical fatigue tests, cyclic creep tests, and tests conducted at slow strain rates and with hold times. The proposed model was implemented in a multiaxial formulation and applied to the fatigue life prediction of an exhaust manifold subjected to severe thermal cycles. The simulation results show good agreement with the failure locations and number of cycles to failure observed in a component-level experiment.

  15. A New Method of Fatigue Life Prediction for Notched Specimen

    Directory of Open Access Journals (Sweden)

    JIN Dan

    2017-04-01

    Full Text Available The simulations of the notched specimens under multiaxial loading were conducted by finite element method. The simulation results show that the stress gradient increases with the decrease in notch radius for the same strain path. The equivalent strain method is used to predict the fatigue life based on the strain at the notched root. The prediction results are more conservative with the decrease in notch radius. The effective distance is determinated by the stress gradient method, and the effective distances are decreased with the decrease of notch radius for the same strain path. The fatigue life is predicted based on the strain at the effective distance, and the predictions are scattered and unconservative. Combining the test results and simulations, a new method determinating the effective distance is presented considering the strain gradient. Most prediction results are in a factor-2 scatter band.

  16. Development of a probabilistic model for the prediction of fatigue life in the very high cycle fatigue (VHCF range based on inclusion population

    Directory of Open Access Journals (Sweden)

    Kolyshkin A.

    2014-06-01

    Full Text Available The VHCF behaviour of metallic materials containing microstructural defects such as non-metallic inclusions is determined by the size and distribution of the damage dominating defects. In the present paper, the size and location of about 60.000 inclusions measured on the longitudinal and transversal cross sections of AISI 304 sheet form a database for the probabilistic determination of failure-relevant inclusion distribution in fatigue specimens and their corresponding fatigue lifes. By applying the method of Murakami et al. the biggest measured inclusions were used in order to predict the size of failure-relevant inclusions in the fatigue specimens. The location of the crack initiating inclusions was defined based on the modeled inclusion population and the stress distribution in the fatigue specimen, using the probabilistic Monte Carlo framework. Reasonable agreement was obtained between modeling and experimental results.

  17. Predictive factors of a beneficial quality of life outcome in patients undergoing primary sinonasal surgery: a population-based prospective cohort study.

    Science.gov (United States)

    Alakärppä, Antti I; Koskenkorva, Timo J; Koivunen, Petri T; Alho, Olli-Pekka

    2018-02-28

    To assess predictive factors of a beneficial quality of life (QoL) outcome after primary sinonasal surgery. A population-based prospective cohort study among 160 adult patients undergoing primary sinonasal surgery (76 septoplasties, SP; 84 endoscopic sinus surgeries, ESS) was conducted. We collected QoL data using the Sinonasal Outcome Test-22 (SNOT-22) before and after surgery. A beneficial QoL outcome was defined as a SNOT-22 score change ≥ 9 points 12 months after surgery. Various demographic, clinical and symptom-related factors predicting a beneficial QoL outcome were sought using binary logistic regression analysis. The mean age of the patients was 39 years (range 18-61) and 82 (51%) were males. The SNOT-22 score change varied markedly after SP (range - 17 to + 80) and ESS (range - 20 to + 58), but on average it improved (median + 15 after SP and + 16 after ESS). 41 patients (64%) achieved beneficial QoL outcome after SP and 46 (66%) after ESS. In a multivariate analysis, poor QoL before surgery (preoperative SNOT-22 ≥ 20 points) predicted a beneficial QoL outcome after SP and ESS (adjusted odds ratio 10; 95% confidence interval 1.6-64 and 12; 2.5-55, respectively) and a senior surgeon operating after SP (9.9; 1.5-67). On receiver operating characteristic curve analysis, the integer threshold value for the preoperative SNOT-22 score that gave the highest sensitivity (74%) and specificity (70%) was 30. QoL change after primary SP and ESS varies. A preoperative SNOT-22 score of at least 30 best predicted a beneficial QoL outcome after both procedures.

  18. Study on creep-fatigue evaluation procedures for high-chromium steels-Part I: Test results and life prediction based on measured stress relaxation

    International Nuclear Information System (INIS)

    Takahashi, Yukio

    2008-01-01

    Strong demand for improving thermal efficiency of power generation plants promoted the use of high-chromium steels, which have high creep strength and corrosion resistance. Aiming at cost reduction for future nuclear power plants, these materials are also regarded as candidates for structural materials, being favoured for lower thermal expansion rate compared with austenitic stainless steels. In structural design and life management of these plants, failure due to the combination of fatigue and creep damages has been considered as an important phenomenon to be evaluated, in addition to simple creep failure under sustained loading such as inner pressure. The author has been conducting a series of creep-fatigue tests for three types of high-chromium steels used in fossil power plants and the applicability of life prediction methods has been studied. It was found that the time fraction rule gives a relatively small amount of creep damage and overpredicts the failure life, whereas a simple ductility exhaustion method provides very large creep damage which leads to too conservative prediction of failure lives. A modified ductility exhaustion method developed on the re-definition of creep damage as a ductility consumer gave a moderate amount of creep damage and provided reasonable life predictability. Moreover, an empirical formula was derived which can represent the life reduction in compressive hold tests as a function of pure fatigue life and hold time

  19. Innovative predictive maintenance concepts to improve life cycle management

    NARCIS (Netherlands)

    Tinga, Tiedo

    2014-01-01

    For naval systems with typically long service lives, high sustainment costs and strict availability requirements, an effective and efficient life cycle management process is very important. In this paper four approaches are discussed to improve that process: physics of failure based predictive

  20. A. Palmgren Revisited: A Basis for Bearing Life Prediction

    Science.gov (United States)

    Zaretsky, Erwin V.

    1997-01-01

    Bearing technology, as well as the bearing industry, began to develop with the invention of the bicycle in the 1850's. At the same time, high-quality steel was made possible by the Bessemer process. In 1881, H. Hertz published his contact stress analysis. By 1902, R. Stribeck had published his work based on Hertz theory to calculate the maximum load of a radially loaded ball bearing. By 1920, all of the rolling bearing types used today were being manufactured. AISI 52100 bearing steel became the material of choice for these bearings. Beginning in 1918, engineers directed their attention to predicting the lives of these bearings. In 1924, A. Palmgren published a paper outlining his approach to bearing life prediction. This paper was the basis for the Lundberg-Palmgren life theory published in 1947. A critical review of the 1924 Palmgren paper is presented here together with a discussion of its effect on bearing life prediction.

  1. Towards a unified fatigue life prediction method for marine structures

    CERN Document Server

    Cui, Weicheng; Wang, Fang

    2014-01-01

    In order to apply the damage tolerance design philosophy to design marine structures, accurate prediction of fatigue crack growth under service conditions is required. Now, more and more people have realized that only a fatigue life prediction method based on fatigue crack propagation (FCP) theory has the potential to explain various fatigue phenomena observed. In this book, the issues leading towards the development of a unified fatigue life prediction (UFLP) method based on FCP theory are addressed. Based on the philosophy of the UFLP method, the current inconsistency between fatigue design and inspection of marine structures could be resolved. This book presents the state-of-the-art and recent advances, including those by the authors, in fatigue studies. It is designed to lead the future directions and to provide a useful tool in many practical applications. It is intended to address to engineers, naval architects, research staff, professionals and graduates engaged in fatigue prevention design and survey ...

  2. Predictive Service Life Tests for Roofing Membranes

    Science.gov (United States)

    Bailey, David M.; Cash, Carl G.; Davies, Arthur G.

    2002-09-01

    The average service life of roofing membranes used in low-slope applications on U.S. Army buildings is estimated to be considerably shorter than the industry-presumed 20-year design life, even when installers carefully adhere to the latest guide specifications. This problem is due in large part to market-driven product development cycles, which do not include time for long-term field testing. To reduce delivery costs, contractors may provide untested, interior membranes in place of ones proven satisfactory in long-term service. Federal procurement regulations require that roofing systems and components be selected according to desired properties and generic type, not brand name. The problem is that a material certified to have satisfactory properties at installation time will not necessarily retain those properties in service. The overall objective of this research is to develop a testing program that can be executed in a matter of weeks to adequately predict a membrane's long-term performance in service. This report details accelerated aging tests of 12 popular membrane materials in the laboratory, and describes outdoor experiment stations set up for long-term exposure tests of those same membranes. The laboratory results will later be correlated with the outdoor test results to develop performance models and predictive service life tests.

  3. Early Adolescent Affect Predicts Later Life Outcomes.

    Science.gov (United States)

    Kansky, Jessica; Allen, Joseph P; Diener, Ed

    2016-07-01

    Subjective well-being as a predictor for later behavior and health has highlighted its relationship to health, work performance, and social relationships. However, the majority of such studies neglect the developmental nature of well-being in contributing to important changes across the transition to adulthood. To examine the potential role of subjective well-being as a long-term predictor of critical life outcomes, we examined indicators of positive and negative affect at age 14 as predictors of relationship, adjustment, self-worth, and career outcomes a decade later at ages 23 to 25, controlling for family income and gender. We utilised multi-informant methods including reports from the target participant, close friends, and romantic partners in a demographically diverse community sample of 184 participants. Early adolescent positive affect predicted fewer relationship problems (less self-reported and partner-reported conflict, and greater friendship attachment as rated by close peers) and healthy adjustment to adulthood (lower levels of depression, anxiety, and loneliness). It also predicted positive work functioning (higher levels of career satisfaction and job competence) and increased self-worth. Negative affect did not significantly predict any of these important life outcomes. In addition to predicting desirable mean levels of later outcomes, early positive affect predicted beneficial changes across time in many outcomes. The findings extend early research on the beneficial outcomes of subjective well-being by having an earlier assessment of well-being, including informant reports in measuring a large variety of outcome variables, and by extending the findings to a lower socioeconomic group of a diverse and younger sample. The results highlight the importance of considering positive affect as an important component of subjective well-being distinct from negative affect. © 2016 The International Association of Applied Psychology.

  4. Predicting life-history adaptations to pollutants

    Energy Technology Data Exchange (ETDEWEB)

    Maltby, L. [Univ. of Sheffield (United Kingdom). Dept. of Animal and Plant Sciences

    1995-12-31

    Animals may adapt to pollutant stress so that individuals from polluted environments are less susceptible than those from unpolluted environments. In addition to such direct adaptations, animals may respond to pollutant stress by life-history modifications; so-called indirect adaptations. This paper will demonstrate how, by combining life-history theory and toxicological data, it is possible to predict stress-induced alterations in reproductive output and offspring size. Pollutant-induced alterations in age-specific survival in favor of adults and reductions in juvenile growth, conditions are predicted to select for reduced investment in reproduction and the allocation of this investment into fewer, larger offspring. Field observations on the freshwater crustaceans, Asellus aquaticus and Gammarus pulex, support these predictions. Females from metal-polluted sites had lower investment in reproduction and produced larger offspring than females of the same species from unpolluted sites. Moreover, interpopulation differences in reproductive biology persisted in laboratory cultures indicating that they had a genetic basis and were therefore due to adaptation rather than acclimation. The general applicability of this approach will be considered.

  5. Life prediction for a vacuum fluorescent display based on two improved models using the three-parameter Weibull right approximation method.

    Science.gov (United States)

    Zhang, Jianping; Zhang, Xing; Zong, Yu; Pan, Yaofang; Wu, Helen; Tang, Jieshuo

    2018-02-01

    To obtain precise life information for vacuum fluorescent displays (VFDs), luminance degradation data for VFDs were collected from a group of normal life tests. Instead of exponential function, the three-parameter Weibull right approximation method (TPWRAM) was applied to describe the luminance degradation path of optoelectronic products, and two improved models were established. One of these models calculated the average life by fitting average luminance degradation data, and the other model obtained VFD life by combining the approximation method with luminance degradation test data from each individual sample. The results indicated that the test design under normal working stress was appropriate, and the selection of censored test data was simple. The two models improved by TPWRAM both revealed the luminance decaying law for VFD, and the pseudo failure time was accurately extrapolated. It was further confirmed by comparing relative error that using the second model gave a more accurate prediction of VFD life. The improved models in this study can provide technical references for researchers and manufacturers in aspects of life prediction methodology for its development. Copyright © 2017 John Wiley & Sons, Ltd.

  6. The life prediction study of Rokkasho reprocessing plant materials

    International Nuclear Information System (INIS)

    Kiuchi, K.; Yano, M.; Takizawa, M.; Shibata, S.

    1998-01-01

    The life prediction study of major equipment materials used in heavily corrosive nitric acid solutions of the RRP was carried out. The nitric acid recovery made of type 304ULC austenitic steel and the dissolver made of type 705 metallic zirconium are selected on the present study. This study is composed of major three programs, namely, the mock-up tests by small-sized equipments simulated to the practical design, laboratory tests for examining corrosion controlling factors by small specimens and to establish the data base system for the life prediction. Important parameters on this study was extracted with analyzing the past data of the life prediction on the Tokai reprocessing equipments. The mock-ups design was made by considering the quantitative evaluation of the most important parts on objective equipments, namely, heat conducting tubes in an acid recovery evaporator and a thermal jacket in a dissolver. From pre-examinations, the effects of radioactive species, nitric acid solution chemistry, the corrosion mechanisms were elucidated. Mock-up testing conditions corrosion monitoring methods and a data base concept for the the life prediction were selected from pre-examination data by referencing the plant operation planning. (author)

  7. Aluminum/boron composite - fatigue life prediction

    International Nuclear Information System (INIS)

    Plumtree, A.; Glinka, G.

    2002-01-01

    The fatigue behaviour of a 6061-0 aluminum alloy reinforce with 0.25 volume fraction undirectional boron fibres of 100 μm diameter has been investigated. The specimens were tested under constant stress amplitude using a stress ratio (minimum/maximum stress) of 0.2 with the fibres oriented at an angle to the loading direction in order to study the matrix dominated fatigue behaviour. Two sets of data were obtained for unidirectional specimens tested with fibre to load axis angles of 200 and 450 A third set of data was obtained with V 45 angle-ply specimens. It is shown that a microstress/strain analysis in conjunction with a multiaxial fatigue parameter can be applied to successfully predict the fatigue lives of these boron reinforced aluminum alloy composites. The multiaxial parameter enables a generalized strain-life relationship to be determined using limited experimental data. Once this generalized relationship is known, the life of the composite cycled under different loads and load-fibre angles can be predicted. (author)

  8. Thermomechanical fatigue, oxidation, and Creep: Part II. Life prediction

    Science.gov (United States)

    Neu, R. W.; Sehitoglu, Huseyin

    1989-09-01

    A life prediction model is developed for crack nucleation and early crack growth based on fatigue, environment (oxidation), and creep damage. The model handles different strain-temperature phasings (i.e., in-phase and out-of-phase thermomechanical fatigue, isothermal fatigue, and others, including nonproportional phasings). Fatigue life predictions compare favorably with experiments in 1070 steel for a wide range of test conditions and strain-temperature phasings. An oxide growth (oxide damage) model is based on the repeated microrupture process of oxide observed from microscopic measurements. A creep damage expression, which is stress-based, is coupled with a unified constitutive equation. A set of interrupted tests was performed to provide valuable damage progression information. Tests were performed in air and in helium atmospheres to isolate creep damage from oxidation damage.

  9. Report on an Assessment of the Application of EPP Results from the Strain Limit Evaluation Procedure to the Prediction of Cyclic Life Based on the SMT Methodology

    Energy Technology Data Exchange (ETDEWEB)

    Jetter, R. I. [R. I. Jetter Consulting, Pebble Beach, CA (United States); Messner, M. C. [Argonne National Lab. (ANL), Argonne, IL (United States); Sham, T. -L. [Argonne National Lab. (ANL), Argonne, IL (United States); Wang, Y. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-08-01

    The goal of the proposed integrated Elastic Perfectly-Plastic (EPP) and Simplified Model Test (SMT) methodology is to incorporate an SMT data based approach for creep-fatigue damage evaluation into the EPP methodology to avoid the separate evaluation of creep and fatigue damage and eliminate the requirement for stress classification in current methods; thus greatly simplifying evaluation of elevated temperature cyclic service. This methodology should minimize over-conservatism while properly accounting for localized defects and stress risers. To support the implementation of the proposed methodology and to verify the applicability of the code rules, analytical studies and evaluation of thermomechanical test results continued in FY17. This report presents the results of those studies. An EPP strain limits methodology assessment was based on recent two-bar thermal ratcheting test results on 316H stainless steel in the temperature range of 405 to 7050C. Strain range predictions from the EPP evaluation of the two-bar tests were also evaluated and compared with the experimental results. The role of sustained primary loading on cyclic life was assessed using the results of pressurized SMT data from tests on Alloy 617 at 9500C. A viscoplastic material model was used in an analytic simulation of two-bar tests to compare with EPP strain limits assessments using isochronous stress strain curves that are consistent with the viscoplastic material model. A finite element model of a prior 304H stainless steel Oak Ridge National Laboratory (ORNL) nozzle-to-sphere test was developed and used for an EPP strain limits and creep-fatigue code case damage evaluations. A theoretical treatment of a recurring issue with convergence criteria for plastic shakedown illustrated the role of computer machine precision in EPP calculations.

  10. Predicting Later-Life Outcomes of Early-Life Exposures

    Science.gov (United States)

    Background: In utero exposure of the fetus to a stressor can lead to disease in later life. Epigenetic mechanisms are likely mediators of later-life expression of early-life events.Objectives: We examined the current state of understanding of later-life diseases resulting from ea...

  11. Prediction of war veteran's mental health based on spiritual well-being, social support and self-efficacy variables: The mediating role of life satisfaction

    Science.gov (United States)

    Soltani, Mohsen Ahmadi Tahour; Karaminia, Reza; Hashemian, Sayedeh Asefeh

    2014-01-01

    Introduction: The present study aims to provide a model for explaining the mental health of war veterans based on the variables of spiritual well-being, social support, and self-efficacy, with the mediating role of life satisfaction. Materials and Methods: The research method was descriptive a correlational. The study samples included 210 veterans, who had records in the Veterans Foundation in Tehran's number one district, Sarallah and Imam Khomeini shelters and Essaar Sports Center in Tehran. They were selected randomly and were asked to respond to questionnaires on mental health, spiritual well-being, life satisfaction, social support, and self-efficacy. The data was analyzed by LISREL software version 8.5, using the path analysis. Results: The results showed that the designed model fitted the data (AGFI = 1.00, RMSEA = 0.00 and NFI = 1.00). In the fitted model, life satisfaction and spiritual well-being directly, and social support indirectly, had a significant relationship with the mediator variable of life satisfaction of the war veterans’ mental health. Conclusions: Veterans with better social support, life satisfaction, and spiritual well-being have better mental health. PMID:25077150

  12. Predicting the residual life of plant equipment - Why worry

    International Nuclear Information System (INIS)

    Jaske, C.E.

    1985-01-01

    Predicting the residual life of plant equipment that has been in service for 20 to 30 years or more is a major concern of many industries. This paper reviews the reasons for increased concern for residual-life assessment and the general procedures used in performing such assessments. Some examples and case histories illustrating procedures for assessing remaining service life are discussed. Areas where developments are needed to improve the technology for remaining-life estimation are pointed out. Then, some of the critical issues involved in residual-life assessment are identified. Finally, the future role of residual-life prediction is addressed

  13. Failure analysis and seal life prediction for contacting mechanical seals

    Science.gov (United States)

    Sun, J. J.; He, X. Y.; Wei, L.; Feng, X.

    2008-11-01

    Fault tree analysis method was applied to quantitatively investigate the causes of the leakage failure of mechanical seals. It is pointed out that the change of the surface topography is the main reasons causing the leakage of mechanical seals under the condition of constant preloads. Based on the fractal geometry theory, the relationship between the surface topography and working time were investigated by experiments, and the effects of unit load acting on seal face on leakage path in a mechanical seal were analyzed. The model of predicting seal life of mechanical seals was established on the basis of the relationship between the surface topography and working time and allowable leakage. The seal life of 108 mechanical seal operating at the system of diesel fuel storage and transportation was predicted and the problem of the condition monitoring for the long-period operation of mechanical seal was discussed by this method. The research results indicate that the method of predicting seal life of mechanical seals is feasible, and also is foundation to make scheduled maintenance time and to achieve safe-reliability and low-cost operation for industrial devices.

  14. Life prediction technology of structural materials

    International Nuclear Information System (INIS)

    Nagata, Norio

    1992-01-01

    There is empirically the time limit of use in all industrial plants and components. By defining the loss of functions as the expiration of life, if the forecast of life time or residual life of plants and components can be done, a very useful means becomes available for safety and economical efficiency. The life of plants is controlled by the occurrence and extension of defects in materials, and by the life of the material which is placed under most severe condition. Such severe condition is the environment of use itself with high temperature, corrosive environment, load, vibration and so on. The forecast of material life is to quantitatively grasp the damage behavior of materials under such condition, and to carry out the time control of the functions of plants by defect control. The time dependence of material damage such as fatigue damage, creep damage and corrosion damage is discussed. The forecast of material life by empirical knowledge and theoretical inference and the forecast of residual life are explained. Finally, the forecast of the life time of light water reactors is described as those constructed in initial period approach their design life. (K.I.)

  15. Early-Life Intelligence Predicts Midlife Biological Age.

    Science.gov (United States)

    Schaefer, Jonathan D; Caspi, Avshalom; Belsky, Daniel W; Harrington, Honalee; Houts, Renate; Israel, Salomon; Levine, Morgan E; Sugden, Karen; Williams, Benjamin; Poulton, Richie; Moffitt, Terrie E

    2016-11-01

    Early-life intelligence has been shown to predict multiple causes of death in populations around the world. This finding suggests that intelligence might influence mortality through its effects on a general process of physiological deterioration (i.e., individual variation in "biological age"). We examined whether intelligence could predict measures of aging at midlife before the onset of most age-related disease. We tested whether intelligence assessed in early childhood, middle childhood, and midlife predicted midlife biological age in members of the Dunedin Study, a population-representative birth cohort. Lower intelligence predicted more advanced biological age at midlife as captured by perceived facial age, a 10-biomarker algorithm based on data from the National Health and Nutrition Examination Survey (NHANES), and Framingham heart age (r = 0.1-0.2). Correlations between intelligence and telomere length were less consistent. The associations between intelligence and biological age were not explained by differences in childhood health or parental socioeconomic status, and intelligence remained a significant predictor of biological age even when intelligence was assessed before Study members began their formal schooling. These results suggest that accelerated aging may serve as one of the factors linking low early-life intelligence to increased rates of morbidity and mortality. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. Entropy and the Predictability of Online Life

    Directory of Open Access Journals (Sweden)

    Roberta Sinatra

    2014-01-01

    Full Text Available Using mobile phone records and information theory measures, our daily lives have been recently shown to follow strict statistical regularities, and our movement patterns are, to a large extent, predictable. Here, we apply entropy and predictability measures to two datasets of the behavioral actions and the mobility of a large number of players in the virtual universe of a massive multiplayer online game. We find that movements in virtual human lives follow the same high levels of predictability as offline mobility, where future movements can, to some extent, be predicted well if the temporal correlations of visited places are accounted for. Time series of behavioral actions show similar high levels of predictability, even when temporal correlations are neglected. Entropy conditional on specific behavioral actions reveals that in terms of predictability, negative behavior has a wider variety than positive actions. The actions that contain the information to best predict an individual’s subsequent action are negative, such as attacks or enemy markings, while the positive actions of friendship marking, trade and communication contain the least amount of predictive information. These observations show that predicting behavioral actions requires less information than predicting the mobility patterns of humans for which the additional knowledge of past visited locations is crucial and that the type and sign of a social relation has an essential impact on the ability to determine future behavior.

  17. Service life prediction and fibre reinforced cementitious composites

    DEFF Research Database (Denmark)

    Stoklund Larsen, E.

    The present Ph.D.thesis addresses the service life concept on the fibre reinforced cementitious composites. The advantages and problems of adding fibre to a cementitious matrix and the influence on service life are described. In SBI Report 221, Service life prediction and cementitious somposites,...

  18. Recent Methodologies for Creep Deformation Analysis and Its Life Prediction

    International Nuclear Information System (INIS)

    Kim, Woo-Gon; Park, Jae-Young; Iung

    2016-01-01

    To design the high-temperature creeping materials, various creep data are needed for codification, as follows: i) stress vs. creep rupture time for base metals and weldments (average and minimum), ii) stress vs. time to 1% total strain (average), iii) stress vs. time to onset of tertiary creep (minimum), and iv) constitutive eqns. for conducting time- and temperature- dependent stress-strain (average), and v) isochronous stress-strain curves (average). Also, elevated temperature components such as those used in modern power generation plant are designed using allowable stress under creep conditions. The allowable stress is usually estimated on the basis of up to 10 5 h creep rupture strength at the operating temperature. The master curve of the “sinh” function was found to have a wider acceptance with good flexibility in the low stress ranges beyond the experimental data. The proposed multi-C method in the LM parameter revealed better life prediction than a single-C method. These improved methodologies can be utilized to accurately predict the long-term creep life or strength of Gen-IV nuclear materials which are designed for life span of 60 years

  19. Predicting Battery Life for Electric UAVs

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a novel battery health management technology for the new generation of electric unmanned aerial vehicles powered by long-life, high-density,...

  20. Time-dependent fatigue--phenomenology and life prediction

    International Nuclear Information System (INIS)

    Coffin, L.F.

    1979-01-01

    The time-dependent fatigue behavior of materials used or considered for use in present and advanced systems for power generation is outlined. A picture is first presented to show how basic mechanisms and phenomenological information relate to the performance of the component under consideration through the so-called local strain approach. By this means life prediction criteria and design rules can be formulated utilizing laboratory test information which is directly translated to predicting the performance of a component. The body of phenomenological information relative to time-dependent fatigue is reviewed. Included are effects of strain range, strain rate and frequency, environment and wave shape, all of which are shown to be important in developing both an understanding and design base for time dependent fatigue. Using this information, some of the current methods being considered for the life prediction of components are reviewed. These include the current ASME code case, frequency-modified fatigue equations, strain range partitioning, the damage function method, frequency separation and damage rate equations. From this review, it is hoped that a better perspective on future directions for basic material science at high temperature can be achieved

  1. Statistical characterization of pitting corrosion process and life prediction

    International Nuclear Information System (INIS)

    Sheikh, A.K.; Younas, M.

    1995-01-01

    In order to prevent corrosion failures of machines and structures, it is desirable to know in advance when the corrosion damage will take place, and appropriate measures are needed to mitigate the damage. The corrosion predictions are needed both at development as well as operational stage of machines and structures. There are several forms of corrosion process through which varying degrees of damage can occur. Under certain conditions these corrosion processes at alone and in other set of conditions, several of these processes may occur simultaneously. For a certain type of machine elements and structures, such as gears, bearing, tubes, pipelines, containers, storage tanks etc., are particularly prone to pitting corrosion which is an insidious form of corrosion. The corrosion predictions are usually based on experimental results obtained from test coupons and/or field experiences of similar machines or parts of a structure. Considerable scatter is observed in corrosion processes. The probabilities nature and kinetics of pitting process makes in necessary to use statistical method to forecast the residual life of machine of structures. The focus of this paper is to characterization pitting as a time-dependent random process, and using this characterization the prediction of life to reach a critical level of pitting damage can be made. Using several data sets from literature on pitting corrosion, the extreme value modeling of pitting corrosion process, the evolution of the extreme value distribution in time, and their relationship to the reliability of machines and structure are explained. (author)

  2. Prediction based on mean subset

    DEFF Research Database (Denmark)

    Øjelund, Henrik; Brown, P. J.; Madsen, Henrik

    2002-01-01

    , it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction......Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...

  3. Solid-state lighting life prediction using extended Kalman filter

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep [Auburn Univ., AL (United States); Wei, Junchao [Auburn Univ., AL (United States); Davis, Lynn [RTI International, Durham, NC (United States)

    2013-07-16

    -80 test data for various LEDs have been used for model development. System state has been described in state space form using the measurement of the feature vector, velocity of feature vector change and the acceleration of the feature vector change. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.

  4. Three dimensional thrust chamber life prediction

    Science.gov (United States)

    Armstrong, W. H.; Brogren, E. W.

    1976-01-01

    A study was performed to analytically determine the cyclic thermomechanical behavior and fatigue life of three configurations of a Plug Nozzle Thrust Chamber. This thrust chamber is a test model which represents the current trend in nozzle design calling for high performance coupled with weight and volume limitations as well as extended life for reusability. The study involved the use of different materials and material combinations to evaluate their application to the problem of low-cycle fatigue in the thrust chamber. The thermal and structural analyses were carried out on a three-dimensional basis. Results are presented which show plots of continuous temperature histories and temperature distributions at selected times during the operating cycle of the thrust chamber. Computed structural data show critical regions for low-cycle fatigue and the histories of strain within the regions for each operation cycle.

  5. Fatigue Life Prediction in Journal Bearing

    Directory of Open Access Journals (Sweden)

    Irsyadi Yani

    2017-03-01

    Full Text Available Failure of fatigue is damaged materials where caused frequent load. Fatigue owing to some factors, which is Stress concentration on fatigue, Stress life, Effect size and surface, and Change properties of surface. The fatigue failure of a material is dependent on the interaction of a large stress with a critical flow. In essence, fatigue is controlled by the weakest link of the material, with the probability of a weak link increasing with material volume. This phenomenon is evident in the fatigue test results of a material using specimens of varying diameters. From this research we can get effect of concentration stress on strength fatigue with S-N method. On this method only count fatigue life or endurance limit from Journal bearing housing. By Finite Element Analysis, it is not so easy to determine fatigue life. When we find the first yield point, it means this point is in the highest stress state. Then we can refer S-N curve. In this paper, the effect of bearing and housing elasticity on the stress field, which could result in surface fatigue in journal bearing, has been investigated. This condition is proved with occurred slip lines on surface of specimen. These slip lines are caused on some thousands stress cycles. Additional crack is happened immediately and finally long enough crack. So that formed unstable crack that caused fracture of brittleness or fracture of toughness because section of specimen cannot keep

  6. Prediction and evaluation of route dependent dosimetry of BPA in rats at different life stages using a physiologically based pharmacokinetic model

    International Nuclear Information System (INIS)

    Yang, Xiaoxia; Doerge, Daniel R.; Fisher, Jeffrey W.

    2013-01-01

    Bisphenol A (BPA) has received considerable attention throughout the last decade due to its widespread use in consumer products. For the first time a physiologically based pharmacokinetic (PBPK) model was developed in neonatal and adult rats to quantitatively evaluate age-dependent pharmacokinetics of BPA and its phase II metabolites. The PBPK model was calibrated in adult rats using studies on BPA metabolism and excretion in the liver and gastrointestinal tract, and pharmacokinetic data with BPA in adult rats. For immature rats the hepatic and gastrointestinal metabolism of BPA was inferred from studies on the maturation of phase II enzymes coupled with serum time course data in pups. The calibrated model predicted the measured serum concentrations of BPA and BPA conjugates after administration of 100 μg/kg of d6-BPA in adult rats (oral gavage and intravenous administration) and postnatal days 3, 10, and 21 pups (oral gavage). The observed age-dependent BPA serum concentrations were partially attributed to the immature metabolic capacity of pups. A comparison of the dosimetry of BPA across immature rats and monkeys suggests that dose adjustments would be necessary to extrapolate toxicity studies from neonatal rats to infant humans. - Highlights: • A PBPK model predicts the kinetics of bisphenol A (BPA) in young and adult rats. • BPA metabolism within enterocytes is required for fitting of oral BPA kinetic data. • BPA dosimetry in young rats is different than adult rats and young monkeys

  7. Enhanced Prediction of Gear Tooth Surface Fatigue Life, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Sentient will develop an enhanced prediction of gear tooth surface fatigue life with rigorous analysis of the tribological phenomena that contribute to pitting...

  8. Service life prediction of exterior plastics vision for the future

    CERN Document Server

    Martin, Jon; Chapin, J

    2015-01-01

    This book defines the current state-of-the-art for predicting the lifetime of plastics exposed to weather and outlines future research needed to advance this important field of study. Coverage includes progress in developing new science and test methods to determine how materials respond to weather exposure. This book is ideal for researchers and professionals working in the field of service life prediction. This book also: Examines numerous consensus standards that affect commercial products allowing readers to see the future of standards related to service life prediction Provides the scientific foundation for the latest commercially viable instruments Presents groundbreaking research, including the blueprint of a new test method that will significantly shorten the service life prediction process time Covers two of the latest verified predictive models, which demonstrate realized-potential to transform the field

  9. FORMULASI TEPUNG PENYALUT BERBASIS TEPUNG JAGUNG DAN PENENTUAN UMUR SIMPANNYA DENGAN PENDEKATAN KADAR AIR KRITIS [Formulation of Corn Flour-Based Batter and Prediction of Its Shelf Life using Critical Moisture Approach

    OpenAIRE

    Sugiyono1)*; Fransisca1); Aton Yulianto2)

    2010-01-01

    The objectives of this study were to obtain the best formula for corn flour-based batter and to predict its shelf life using critical moisture approach. According to a hedonic test, the best batter formula was composed of 60% corn flour, 12.5% rice flour, 12.5% tapioca starch, and 15% glutinous rice flour. Addition of glutinous rice flour in the formula changed the proportion of amylose and amylopectin in the batter. As a result, the retrogradation of the batter decreased and the texture of ...

  10. Early Life Events Predict Adult Testicular Function

    DEFF Research Database (Denmark)

    Hart, Roger J; Doherty, Dorota A; Keelan, Jeffrey A

    2016-01-01

    CONTEXT: The impact of early life events on testicular function in adulthood is not well understood. OBJECTIVE: To study the early influences of fetal growth, exposures to cigarette smoke in utero and cord blood estrogens, and the influences of growth and adiposity in childhood through adolescence......; on testicular function in adulthood. DESIGN: Male members of the Western Australian Pregnancy Cohort (Raine) were contacted at 20-22 years of age. Of 913 contacted, 423 (56%) agreed to participate; 404 underwent a testicular ultrasound, 365 provided a semen sample, and reproductive hormones were measured (384...... = .003) in adulthood. CONCLUSIONS: Exposures to maternal smoking and higher cord blood estrogens at delivery were associated with a reduced sperm output in adulthood. Optimal adult testicular function depends on being born at or above average weight, and maintaining optimal growth and adiposity...

  11. FORMULASI TEPUNG PENYALUT BERBASIS TEPUNG JAGUNG DAN PENENTUAN UMUR SIMPANNYA DENGAN PENDEKATAN KADAR AIR KRITIS [Formulation of Corn Flour-Based Batter and Prediction of Its Shelf Life using Critical Moisture Approach

    Directory of Open Access Journals (Sweden)

    Sugiyono1*

    2010-12-01

    Full Text Available The objectives of this study were to obtain the best formula for corn flour-based batter and to predict its shelf life using critical moisture approach. According to a hedonic test, the best batter formula was composed of 60% corn flour, 12.5% rice flour, 12.5% tapioca starch, and 15% glutinous rice flour. Addition of glutinous rice flour in the formula changed the proportion of amylose and amylopectin in the batter. As a result, the retrogradation of the batter decreased and the texture of its fried product was preferred. A critical moisture approach was used to predict the shelf life of the batter. The critical moisture content of the batter was 0.16 g H2O/g solid.The isotherm sorption phenomenon of the batter was best described using Hasley model. The shelf life of the product was 7 months when packaged in polypropylene (0,07 g/m2day.mmHg at 85% RH.

  12. A study of fatigue life prediction for automotive spot weldment using local strain approach

    International Nuclear Information System (INIS)

    Lee, Song In; Yu, Hyo Sun; Na, Sung Hun; Na, Eui Gyun

    2000-01-01

    The fatigue crack initiation life is studied on automotive spot weldment made from cold rolled carbon steel(SPC) sheet by using DCPDM and local strain approach. It can be found that the fatigue crack initiation behavior in spot weldment can be definitely detected by DCPDM system. The local stresses and strains are estimated by elastic-plastic FEM analysis and the alternative approximate method based on Neuber's rule were applied to predict the fatigue life of spot weldment. A satisfactory correlation between the predicted life and experimental life can be found in spot weldment within a factor of 4

  13. Life history theory predicts fish assemblage response to hydrologic regimes.

    Science.gov (United States)

    Mims, Meryl C; Olden, Julian D

    2012-01-01

    The hydrologic regime is regarded as the primary driver of freshwater ecosystems, structuring the physical habitat template, providing connectivity, framing biotic interactions, and ultimately selecting for specific life histories of aquatic organisms. In the present study, we tested ecological theory predicting directional relationships between major dimensions of the flow regime and life history composition of fish assemblages in perennial free-flowing rivers throughout the continental United States. Using long-term discharge records and fish trait and survey data for 109 stream locations, we found that 11 out of 18 relationships (61%) tested between the three life history strategies (opportunistic, periodic, and equilibrium) and six hydrologic metrics (two each describing flow variability, predictability, and seasonality) were statistically significant (P history strategies, with 82% of all significant relationships observed supporting predictions from life history theory. Specifically, we found that (1) opportunistic strategists were positively related to measures of flow variability and negatively related to predictability and seasonality, (2) periodic strategists were positively related to high flow seasonality and negatively related to variability, and (3) the equilibrium strategists were negatively related to flow variability and positively related to predictability. Our study provides important empirical evidence illustrating the value of using life history theory to understand both the patterns and processes by which fish assemblage structure is shaped by adaptation to natural regimes of variability, predictability, and seasonality of critical flow events over broad biogeographic scales.

  14. Application of structural reliability and risk assessment to life prediction and life extension decision making

    International Nuclear Information System (INIS)

    Meyer, T.A.; Balkey, K.R.; Bishop, B.A.

    1987-01-01

    There can be numerous uncertainties involved in performing component life assessments. In addition, sufficient data may be unavailable to make a useful life prediction. Structural Reliability and Risk Assessment (SRRA) is primarily an analytical methodology or tool that quantifies the impact of uncertainties on the structural life of plant components and can address the lack of data in component life prediction. As a prelude to discussing the technical aspects of SRRA, a brief review of general component life prediction methods is first made so as to better develop an understanding of the role of SRRA in such evaluations. SRRA is then presented as it is applied in component life evaluations with example applications being discussed for both nuclear and non-nuclear components

  15. Probabilistic methods for service life predictions

    NARCIS (Netherlands)

    Siemes, A.J.M.

    1999-01-01

    Nowadays it is commonly accepted that the safety of structures should be expressed in terms of reli-ability. This means as the probability of failure. In literature [1, 2, 3, and 4] the bases have been given for the calculation of the failure probability. Making probabilistic calculations can be

  16. A method for uncertainty quantification in the life prediction of gas turbine components

    Energy Technology Data Exchange (ETDEWEB)

    Lodeby, K.; Isaksson, O.; Jaervstraat, N. [Volvo Aero Corporation, Trolhaettan (Sweden)

    1998-12-31

    A failure in an aircraft jet engine can have severe consequences which cannot be accepted and high requirements are therefore raised on engine reliability. Consequently, assessment of the reliability of life predictions used in design and maintenance are important. To assess the validity of the predicted life a method to quantify the contribution to the total uncertainty in the life prediction from different uncertainty sources is developed. The method is a structured approach for uncertainty quantification that uses a generic description of the life prediction process. It is based on an approximate error propagation theory combined with a unified treatment of random and systematic errors. The result is an approximate statistical distribution for the predicted life. The method is applied on life predictions for three different jet engine components. The total uncertainty became of reasonable order of magnitude and a good qualitative picture of the distribution of the uncertainty contribution from the different sources was obtained. The relative importance of the uncertainty sources differs between the three components. It is also highly dependent on the methods and assumptions used in the life prediction. Advantages and disadvantages of this method is discussed. (orig.) 11 refs.

  17. Neural Network Modeling to Predict Shelf Life of Greenhouse Lettuce

    Directory of Open Access Journals (Sweden)

    Wei-Chin Lin

    2009-04-01

    Full Text Available Greenhouse-grown butter lettuce (Lactuca sativa L. can potentially be stored for 21 days at constant 0°C. When storage temperature was increased to 5°C or 10°C, shelf life was shortened to 14 or 10 days, respectively, in our previous observations. Also, commercial shelf life of 7 to 10 days is common, due to postharvest temperature fluctuations. The objective of this study was to establish neural network (NN models to predict the remaining shelf life (RSL under fluctuating postharvest temperatures. A box of 12 - 24 lettuce heads constituted a sample unit. The end of the shelf life of each head was determined when it showed initial signs of decay or yellowing. Air temperatures inside a shipping box were recorded. Daily average temperatures in storage and averaged shelf life of each box were used as inputs, and the RSL was modeled as an output. An R2 of 0.57 could be observed when a simple NN structure was employed. Since the "future" (or remaining storage temperatures were unavailable at the time of making a prediction, a second NN model was introduced to accommodate a range of future temperatures and associated shelf lives. Using such 2-stage NN models, an R2 of 0.61 could be achieved for predicting RSL. This study indicated that NN modeling has potential for cold chain quality control and shelf life prediction.

  18. Simulation work of fatigue life prediction of rubber automotive components

    International Nuclear Information System (INIS)

    Samad, M S A; Ali, Aidy

    2010-01-01

    The usage of rubbers has always been so important, especially in automotive industries. Rubbers have a hyper elastic behaviour which is the ability to withstand very large strain without failure. The normal applications for rubbers are used for shock absorption, sound isolation and mounting. In this study, the predictions of fatigue life of an engine mount of rubber automotive components were presented. The finite element analysis was performed to predict the critical part and the strain output were incorporated into fatigue model for prediction. The predicted result shows agreement in term of failure location of rubber mount.

  19. Effect of Hoop Stress on Ball Bearing Life Prediction

    Science.gov (United States)

    Zaretsky, Erwin V.; August, Richard; Coe, Harold H.

    1995-01-01

    A finite-element analysis (FEA) of a generic, dimensionally normalized inner race of an angular-contact ball bearing was performed under varying conditions of speed and the press (or interference) fit of the inner-race bore on a journal. The FEA results at the ball-race contact were used to derive an equation from which was obtained the radius of an equivalent cylindrical bearing race with the same or similar hoop stress. The radius of the equivalent cylinder was used to obtain a generalized closed-form approximation of the hoop stresses at the ball-inner-race contact in an angular-contact ball bearing. A life analysis was performed on both a 45- and a 120-mm-bore, angular-contact ball bearing. The predicted lives with and without hoop stress were compared with experimental endurance results obtained at 12000 and 25000 rpm with the 120-mm-bore ball bearing. A life factor equation based on hoop stress is presented.

  20. Fatigue crack initiation and growth life prediction with statistical consideration

    International Nuclear Information System (INIS)

    Kwon, J.D.; Choi, S.H.; Kwak, S.G.; Chun, K.O.

    1991-01-01

    Life prediction or residual life prediction of structures or machines is one of the most strongly world wide needed problems as requirement in the stage of slowly developing economy which comes after rapidly and highly developing stage. For the purpose of statistical life prediction, fatigue test was conducted under the 3 stress levels, and for each stress level, 20 specimens are used. The statistical properties of the crack growth parameter m and C in the fatigue crack growth law of da/dN = C(ΔK) m , and the relationship between m and C, and the statistical distribution pattern of fatigue crack initiation, growth and fracture lives can be obtained by experimental results

  1. Purpose in life predicts better emotional recovery from negative stimuli.

    Science.gov (United States)

    Schaefer, Stacey M; Morozink Boylan, Jennifer; van Reekum, Carien M; Lapate, Regina C; Norris, Catherine J; Ryff, Carol D; Davidson, Richard J

    2013-01-01

    Purpose in life predicts both health and longevity suggesting that the ability to find meaning from life's experiences, especially when confronting life's challenges, may be a mechanism underlying resilience. Having purpose in life may motivate reframing stressful situations to deal with them more productively, thereby facilitating recovery from stress and trauma. In turn, enhanced ability to recover from negative events may allow a person to achieve or maintain a feeling of greater purpose in life over time. In a large sample of adults (aged 36-84 years) from the MIDUS study (Midlife in the U.S., http://www.midus.wisc.edu/), we tested whether purpose in life was associated with better emotional recovery following exposure to negative picture stimuli indexed by the magnitude of the eyeblink startle reflex (EBR), a measure sensitive to emotional state. We differentiated between initial emotional reactivity (during stimulus presentation) and emotional recovery (occurring after stimulus offset). Greater purpose in life, assessed over two years prior, predicted better recovery from negative stimuli indexed by a smaller eyeblink after negative pictures offset, even after controlling for initial reactivity to the stimuli during the picture presentation, gender, age, trait affect, and other well-being dimensions. These data suggest a proximal mechanism by which purpose in life may afford protection from negative events and confer resilience is through enhanced automatic emotion regulation after negative emotional provocation.

  2. Purpose in life predicts better emotional recovery from negative stimuli.

    Directory of Open Access Journals (Sweden)

    Stacey M Schaefer

    Full Text Available Purpose in life predicts both health and longevity suggesting that the ability to find meaning from life's experiences, especially when confronting life's challenges, may be a mechanism underlying resilience. Having purpose in life may motivate reframing stressful situations to deal with them more productively, thereby facilitating recovery from stress and trauma. In turn, enhanced ability to recover from negative events may allow a person to achieve or maintain a feeling of greater purpose in life over time. In a large sample of adults (aged 36-84 years from the MIDUS study (Midlife in the U.S., http://www.midus.wisc.edu/, we tested whether purpose in life was associated with better emotional recovery following exposure to negative picture stimuli indexed by the magnitude of the eyeblink startle reflex (EBR, a measure sensitive to emotional state. We differentiated between initial emotional reactivity (during stimulus presentation and emotional recovery (occurring after stimulus offset. Greater purpose in life, assessed over two years prior, predicted better recovery from negative stimuli indexed by a smaller eyeblink after negative pictures offset, even after controlling for initial reactivity to the stimuli during the picture presentation, gender, age, trait affect, and other well-being dimensions. These data suggest a proximal mechanism by which purpose in life may afford protection from negative events and confer resilience is through enhanced automatic emotion regulation after negative emotional provocation.

  3. Fracture Mechanics Prediction of Fatigue Life of Aluminum Highway Bridges

    DEFF Research Database (Denmark)

    Rom, Søren; Agerskov, Henning

    2015-01-01

    Fracture mechanics prediction of the fatigue life of aluminum highway bridges under random loading is studied. The fatigue life of welded joints has been determined from fracture mechanics analyses and the results obtained have been compared with results from experimental investigations. The fati......Fracture mechanics prediction of the fatigue life of aluminum highway bridges under random loading is studied. The fatigue life of welded joints has been determined from fracture mechanics analyses and the results obtained have been compared with results from experimental investigations...... against fatigue in aluminum bridges, may give results which are unconservative. Furthermore, it was in both investigations found that the validity of the results obtained from Miner's rule will depend on the distribution of the load history in tension and compression....

  4. Progressive Failure And Life Prediction of Ceramic and Textile Composites

    Science.gov (United States)

    Xue, David Y.; Shi, Yucheng; Katikala, Madhu; Johnston, William M., Jr.; Card, Michael F.

    1998-01-01

    An engineering approach to predict the fatigue life and progressive failure of multilayered composite and textile laminates is presented. Analytical models which account for matrix cracking, statistical fiber failures and nonlinear stress-strain behavior have been developed for both composites and textiles. The analysis method is based on a combined micromechanics, fracture mechanics and failure statistics analysis. Experimentally derived empirical coefficients are used to account for the interface of fiber and matrix, fiber strength, and fiber-matrix stiffness reductions. Similar approaches were applied to textiles using Repeating Unit Cells. In composite fatigue analysis, Walker's equation is applied for matrix fatigue cracking and Heywood's formulation is used for fiber strength fatigue degradation. The analysis has been compared with experiment with good agreement. Comparisons were made with Graphite-Epoxy, C/SiC and Nicalon/CAS composite materials. For textile materials, comparisons were made with triaxial braided and plain weave materials under biaxial or uniaxial tension. Fatigue predictions were compared with test data obtained from plain weave C/SiC materials tested at AS&M. Computer codes were developed to perform the analysis. Composite Progressive Failure Analysis for Laminates is contained in the code CPFail. Micromechanics Analysis for Textile Composites is contained in the code MicroTex. Both codes were adapted to run as subroutines for the finite element code ABAQUS and CPFail-ABAQUS and MicroTex-ABAQUS. Graphic user interface (GUI) was developed to connect CPFail and MicroTex with ABAQUS.

  5. Reengineering Aircraft Structural Life Prediction Using a Digital Twin

    Directory of Open Access Journals (Sweden)

    Eric J. Tuegel

    2011-01-01

    Full Text Available Reengineering of the aircraft structural life prediction process to fully exploit advances in very high performance digital computing is proposed. The proposed process utilizes an ultrahigh fidelity model of individual aircraft by tail number, a Digital Twin, to integrate computation of structural deflections and temperatures in response to flight conditions, with resulting local damage and material state evolution. A conceptual model of how the Digital Twin can be used for predicting the life of aircraft structure and assuring its structural integrity is presented. The technical challenges to developing and deploying a Digital Twin are discussed in detail.

  6. Reengineering Aircraft Structural Life Prediction Using a Digital Twin

    OpenAIRE

    Tuegel, Eric J.; Ingraffea, Anthony R.; Eason, Thomas G.; Spottswood, S. Michael

    2011-01-01

    Reengineering of the aircraft structural life prediction process to fully exploit advances in very high performance digital computing is proposed. The proposed process utilizes an ultrahigh fidelity model of individual aircraft by tail number, a Digital Twin, to integrate computation of structural deflections and temperatures in response to flight conditions, with resulting local damage and material state evolution. A conceptual model of how the Digital Twin can be used for predicting the lif...

  7. Durability and service life prediction for concrete structures – developments and challenges

    Directory of Open Access Journals (Sweden)

    Alexander Mark G

    2018-01-01

    Full Text Available The paper reviews developments in service life prediction for concrete structures. It indicates the difficulties inherent in rational service life design, in view of the multiple factors and variabilities involved in the process. The paper also emphasises the advantages of performance-based approaches to durability prediction, and considers performance testing, which is critical to achieving intended service life. Such approaches allow service life modelling, which the current prescriptive approaches do not. The concept of ‘durability indicators’ is covered, with a practical example showing how this can be used to improve concrete durability in construction. The paper also stresses the importance of an ‘integrated approach’ to durability specifications, performance-based predictions, and site quality control.

  8. Survey on damage mechanics models for fatigue life prediction

    NARCIS (Netherlands)

    Silitonga, S.; Maljaars, J.; Soetens, F.; Snijder, H.H.

    2013-01-01

    Engineering methods to predict the fatigue life of structures have been available since the beginning of the 20th century. However, a practical problem arises from complex loading conditions and a significant concern is the accuracy of the methods under variable amplitude loading. This paper

  9. General life satisfaction predicts dementia in community living older adults: a prospective cohort study.

    Science.gov (United States)

    Peitsch, Lorraine; Tyas, Suzanne L; Menec, Verena H; St John, Philip D

    2016-07-01

    Low life satisfaction predicts adverse outcomes, and may predict dementia. The objectives were: (1) to determine if life satisfaction predicts dementia over a five year period in those with normal cognition at baseline; and (2) to determine if different aspects of life satisfaction differentially predict dementia. Secondary analysis of an existing population-based cohort study with initial assessment in 1991 and follow-up five years later. Initially, 1,751 adults age 65+ living in the community were sampled from a representative sampling frame. Of these, 1,024 were alive and had complete data at time 2, of whom 96 were diagnosed with dementia. Life satisfaction was measured using the Terrible-Delightful scale, which measures overall life satisfaction on a 7-point scale, as well as various aspects of life satisfaction (e.g. friendships, finances, etc.) Dementia was diagnosed by clinical examination using DSM-IIIR criteria. Logistic regression models were constructed for the outcome of dementia at time 2, and adjusted for age, gender, education, and comorbidities. Overall life satisfaction predicted dementia five years later, at time 2. The unadjusted Odds Ratio (OR; 95% confidence interval) for dementia at time 2 was 0.72 (0.55, 0.95) per point. The adjusted OR for dementia was 0.70 (0.51, 0.96). No individual item on the life satisfaction scale predicted dementia. However, the competing risk of mortality was very high for some items. A global single-item measure of life satisfaction predicts dementia over a five year period in older adults without cognitive impairment.

  10. SSL and LED life prediction and assessment of CCT shift

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep [Auburn Univ., AL (United States); Sakalaus, Peter [Auburn Univ., AL (United States); Wei, Junchao [Auburn Univ., AL (United States); Davis, Lynn [RTI International, Research Triangle Park, NC (United States)

    2014-05-27

    Solid-state lighting (SSL) products can have a predicted life of 70% lumen output (L70) from 26,000 to 40,000 hours using the LM-80-08 testing standards. Chromaticity shift, correlated color temperature (CCT) and lumen maintenance (LM) will dramatically reduce the nominal life of SSL luminaires. In this work, an off-the-shelf luminaire from Philips (AmbientLED) has been aged in a standard wet hot temperature operating life (WHTOL) of 85% relative humidity and 85°C (85/85) in order to assess reliability of prolonged exposer in a harsh environment. Failure criterion has been derived using the Arrhenius equation from the LM-80-08 standard, as well as the 60W LED Lamp test report from an isothermal environment of 45°C. This is a similar luminaire to the test vehicle used in this research. Data characterization between the two data sets has been carried out to determine the luminaires reliability and life under the 85/85 test conditions. This characterization allows for the determination of poor quality luminaire products in the market place. The distribution properties of the shifting mean values of CCT and LM were incorporated into the Bayesian Linear Regression (BLR) to determine the degradation pattern, in order to predict the remaining useful life (RUL) of the system due to aging before the end-of-life (EoL).

  11. Shelf life prediction of apple brownies using accelerated method

    Science.gov (United States)

    Pulungan, M. H.; Sukmana, A. D.; Dewi, I. A.

    2018-03-01

    The aim of this research was to determine shelf life of apple brownies. Shelf life was determined with Accelerated Shelf Life Testing method and Arrhenius equation. Experiment was conducted at 25, 35, and 45°C for 30 days. Every five days, the sample was analysed for free fatty acid (FFA), water activity (Aw), and organoleptic acceptance (flavour, aroma, and texture). The shelf life of the apple brownies based on FFA were 110, 54, and 28 days at temperature of 25, 35, and 45°C, respectively.

  12. Predicting Bullying: Exploring the Contributions of Childhood Negative Life Experiences in Predicting Adolescent Bullying Behavior.

    Science.gov (United States)

    Connell, Nadine M; Morris, Robert G; Piquero, Alex R

    2016-07-01

    Although there has been much interest in research on aggression and in particular bullying, a relatively less charted area of research has centered on articulating a better understanding of the mechanisms and processes by which persons are at increased risk for bullying. Furthermore, those studies that have investigated the linkages between childhood experiences and bullying perpetration have been limited with respect to definitional and operational issues, reliance on cross-sectional data, and the lack of assessing competing explanations of bullying perpetration. Using five waves of data from a community-based longitudinal sample of children followed through age 18 (N = 763), the current study examines the extent to which childhood negative life events in a variety of domains predict adolescent bullying. Results show that early childhood experiences, particularly those within the family and school domains, may alter life trajectories and can act as predictors for later adolescent bullying, thereby underscoring the potential importance that relatively minor experiences can have over the long term. Implications for future research based on these analyses are examined. © The Author(s) 2015.

  13. Life Prediction Issues in Thermal/Environmental Barrier Coatings in Ceramic Matrix Composites

    Science.gov (United States)

    Shah, Ashwin R.; Brewer, David N.; Murthy, Pappu L. N.

    2001-01-01

    Issues and design requirements for the environmental barrier coating (EBC)/thermal barrier coating (TBC) life that are general and those specific to the NASA Ultra-Efficient Engine Technology (UEET) development program have been described. The current state and trend of the research, methods in vogue related to the failure analysis, and long-term behavior and life prediction of EBCITBC systems are reported. Also, the perceived failure mechanisms, variables, and related uncertainties governing the EBCITBC system life are summarized. A combined heat transfer and structural analysis approach based on the oxidation kinetics using the Arrhenius theory is proposed to develop a life prediction model for the EBC/TBC systems. Stochastic process-based reliability approach that includes the physical variables such as gas pressure, temperature, velocity, moisture content, crack density, oxygen content, etc., is suggested. Benefits of the reliability-based approach are also discussed in the report.

  14. Life prediction of steam generator tubing due to stress corrosion crack using Monte Carlo Simulation

    International Nuclear Information System (INIS)

    Hu Jun; Liu Fei; Cheng Guangxu; Zhang Zaoxiao

    2011-01-01

    Highlights: → A life prediction model for SG tubing was proposed. → The initial crack length for SCC was determined. → Two failure modes called rupture mode and leak mode were considered. → A probabilistic life prediction code based on Monte Carlo method was developed. - Abstract: The failure of steam generator tubing is one of the main accidents that seriously affects the availability and safety of a nuclear power plant. In order to estimate the probability of the failure, a probabilistic model was established to predict the whole life-span and residual life of steam generator (SG) tubing. The failure investigated was stress corrosion cracking (SCC) after the generation of one through-wall axial crack. Two failure modes called rupture mode and leak mode based on probabilistic fracture mechanics were considered in this proposed model. It took into account the variance in tube geometry and material properties, and the variance in residual stresses and operating conditions, all of which govern the propagations of cracks. The proposed model was numerically calculated by using Monte Carlo Simulation (MCS). The plugging criteria were first verified and then the whole life-span and residual life of the SG tubing were obtained. Finally, important sensitivity analysis was also carried out to identify the most important parameters affecting the life of SG tubing. The results will be useful in developing optimum strategies for life-cycle management of the feedwater system in nuclear power plants.

  15. Towards a Universal Biology: Is the Origin and Evolution of Life Predictable?

    Science.gov (United States)

    Rothschild, Lynn J.

    2017-01-01

    The origin and evolution of life seems an unpredictable oddity, based on the quirks of contingency. Celebrated by the late Stephen Jay Gould in several books, "evolution by contingency" has all the adventure of a thriller, but lacks the predictive power of the physical sciences. Not necessarily so, replied Simon Conway Morris, for convergence reassures us that certain evolutionary responses are replicable. The outcome of this debate is critical to Astrobiology. How can we understand where we came from on Earth without prophesy? Further, we cannot design a rational strategy for the search for life elsewhere - or to understand what the future will hold for life on Earth and beyond - without extrapolating from pre-biotic chemistry and evolution. There are several indirect approaches to understanding, and thus describing, what life must be. These include philosophical approaches to defining life (is there even a satisfactory definition of life?), using what we know of physics, chemistry and life to imagine alternate scenarios, using different approaches that life takes as pseudoreplicates (e.g., ribosomal vs non-ribosomal protein synthesis), and experimental approaches to understand the art of the possible. Given that: (1) Life is a process based on physical components rather than simply an object; (2). Life is likely based on organic carbon and needs a solvent for chemistry, most likely water, and (3) Looking for convergence in terrestrial evolution we can predict certain tendencies, if not quite "laws", that provide predictive power. Biological history must obey the laws of physics and chemistry, the principles of natural selection, the constraints of an evolutionary past, genetics, and developmental biology. This amalgam creates a surprising amount of predictive power in the broad outline. Critical is the apparent prevalence of organic chemistry, and uniformity in the universe of the laws of chemistry and physics. Instructive is the widespread occurrence of

  16. Prediction of Service Life for Assembly with Time-variant Deviation

    Science.gov (United States)

    Zeng, Wenhui; Rao, Yunqing; Long, Chenxi; Wang, Peng

    2017-06-01

    During operation, the time-variant deviations, such as deformation, thermal expansion, friction and wear always occur and affect the mechanical performance and service life of assembly. In this paper, a methodology for the prediction of service life for assembly with time-variant deviations is proposed. Firstly, based on the modified Unified Jacobian-Torsor model and Monte Carlo simulation, according to the distribution the geometric and dimension tolerances are randomly generated to limit the variations of surface of part. Secondly, the deformations caused by load and thermal expansion are obtained by finite element analysis, and considering the friction and wear, the prediction model of service life is constructed subject to the constraints. At last, an application is given to illustrate the prediction model, and the influences of time-variant deviations on the assembly deviation and service life are analyzed.

  17. Purpose in life predicts allostatic load ten years later.

    Science.gov (United States)

    Zilioli, Samuele; Slatcher, Richard B; Ong, Anthony D; Gruenewald, Tara L

    2015-11-01

    Living a purposeful life is associated with better mental and physical health, including longevity. Accumulating evidence shows that these associations might be explained by the association between life purpose and regulation of physiological systems involved in the stress response. The aim of this study was to investigate the prospective associations between life purpose and allostatic load over a 10-year period. Analyses were conducted using data from the Midlife in the United States (MIDUS) survey. Assessment of life purpose, psychological covariates and demographics were obtained at baseline, while biomarkers of allostatic load were assessed at the 10-year follow-up. We found that greater life purpose predicted lower levels of allostatic load at follow-up, even when controlling for other aspects of psychological well-being potentially associated with allostatic load. Further, life purpose was also a strong predictor of individual differences in self-health locus of control-i.e., beliefs about how much influence individuals can exert on their own health-which, in turn, partially mediated the association between purpose and allostatic load. Although life purpose was also negatively linked to other-health locus of control-i.e., the extent to which individuals believe their health is controlled by others/chance-this association did not mediate the impact of life purpose on allostatic load. The current study provides the first empirical evidence for the long-term physiological correlates of life purpose and supports the hypothesis that self-health locus of control acts as one proximal psychological mechanism through which life purpose may be linked to positive biological outcomes. Copyright © 2015. Published by Elsevier Inc.

  18. Life-Space Mobility Change Predicts 6-Month Mortality.

    Science.gov (United States)

    Kennedy, Richard E; Sawyer, Patricia; Williams, Courtney P; Lo, Alexander X; Ritchie, Christine S; Roth, David L; Allman, Richard M; Brown, Cynthia J

    2017-04-01

    To examine 6-month change in life-space mobility as a predictor of subsequent 6-month mortality in community-dwelling older adults. Prospective cohort study. Community-dwelling older adults from five Alabama counties in the University of Alabama at Birmingham (UAB) Study of Aging. A random sample of 1,000 Medicare beneficiaries, stratified according to sex, race, and rural or urban residence, recruited between November 1999 and February 2001, followed by a telephone interview every 6 months for the subsequent 8.5 years. Mortality data were determined from informant contacts and confirmed using the National Death Index and Social Security Death Index. Life-space was measured at each interview using the UAB Life-Space Assessment, a validated instrument for assessing community mobility. Eleven thousand eight hundred seventeen 6-month life-space change scores were calculated over 8.5 years of follow-up. Generalized linear mixed models were used to test predictors of mortality at subsequent 6-month intervals. Three hundred fifty-four deaths occurred within 6 months of two sequential life-space assessments. Controlling for age, sex, race, rural or urban residence, and comorbidity, life-space score and life-space decline over the preceding 6-month interval predicted mortality. A 10-point decrease in life-space resulted in a 72% increase in odds of dying over the subsequent 6 months (odds ratio = 1.723, P space score at the beginning of a 6-month interval and change in life-space over 6 months were each associated with significant differences in subsequent 6-month mortality. Life-space assessment may assist clinicians in identifying older adults at risk of short-term mortality. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  19. A comparison of two total fatigue life prediction methods

    Energy Technology Data Exchange (ETDEWEB)

    Chen, N.; Lawrence, F.V.

    1999-07-01

    A 2-D analytical model which is termed the PICC-RICC model combines the effects of plasticity-induced crack closure (PICC) and roughness-induced crack closure (RICC). The PICC-RICC model handles naturally the gradual transition from RICC to PICC dominated crack growth. In this study, the PICC-RICC model is combined with a crack nucleation model to predict the total fatigue life of a notched component. This modified PICC-RICC model will be used to examine several controversial aspects of an earlier, computationally simpler total-life model known as the IP model.

  20. Shelf life prediction of radiation sterilized polymeric materials

    International Nuclear Information System (INIS)

    Sandford, Craig; Woo, Lecon

    1988-01-01

    The functional properties of many polymers employed in medical disposables are unaffected by sterilizing doses of ionizing radiation. However, some materials (PVC, polypropylene, cellulosics, etc.) undergo undesirable changes which continue to occur for the shelf life of the product. In many cases, conventional accelerated aging techniques do not accurately predict the real time properties of the materials. As real time aging is not generally practical, it has become necessary to develop accelerated aging techniques which can predict the functional properties of a material for the shelf life of the product. This presentation will address issues involved in developing these tests. Real time physical property data is compared to data generated by various acceleration methods. (author)

  1. Data-Based Predictive Control with Multirate Prediction Step

    Science.gov (United States)

    Barlow, Jonathan S.

    2010-01-01

    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  2. One- and two-stage Arrhenius models for pharmaceutical shelf life prediction.

    Science.gov (United States)

    Fan, Zhewen; Zhang, Lanju

    2015-01-01

    One of the most challenging aspects of the pharmaceutical development is the demonstration and estimation of chemical stability. It is imperative that pharmaceutical products be stable for two or more years. Long-term stability studies are required to support such shelf life claim at registration. However, during drug development to facilitate formulation and dosage form selection, an accelerated stability study with stressed storage condition is preferred to quickly obtain a good prediction of shelf life under ambient storage conditions. Such a prediction typically uses Arrhenius equation that describes relationship between degradation rate and temperature (and humidity). Existing methods usually rely on the assumption of normality of the errors. In addition, shelf life projection is usually based on confidence band of a regression line. However, the coverage probability of a method is often overlooked or under-reported. In this paper, we introduce two nonparametric bootstrap procedures for shelf life estimation based on accelerated stability testing, and compare them with a one-stage nonlinear Arrhenius prediction model. Our simulation results demonstrate that one-stage nonlinear Arrhenius method has significant lower coverage than nominal levels. Our bootstrap method gave better coverage and led to a shelf life prediction closer to that based on long-term stability data.

  3. Structure life prediction at high temperature: present and future capabilities

    International Nuclear Information System (INIS)

    Chaboche, J.L.

    1987-01-01

    The life prediction techniques for high temperature conditions include several aspects which are considered successively in this article. Crack initiation criteria themselves, defined for the isolated volume element (the tension-compression specimen for example), including parametric relationships and continuous damage approaches and calculation of local stress and strain fields in the structure and their evolution under cyclic plasticity, which poses several difficult problems to obtain stabilized cyclic solutions are examined. The use of crack initiation criteria or damage rules from the result of the cyclic inelastic analysis and the prediction of crack growth in the structure are considered. Different levels are considered for the predictive tools: the classical approach, future methods presently under development and intermediate rules, which are already in use. Several examples are given on materials and components used either in the nuclear industry or in gas turbine engines. (author)

  4. A computational approach for thermomechanical fatigue life prediction of dissimilarly welded superheater tubes

    Energy Technology Data Exchange (ETDEWEB)

    Krishnasamy, Ram-Kumar; Seifert, Thomas; Siegele, Dieter [Fraunhofer-Institut fuer Werkstoffmechanik (IWM), Freiburg im Breisgau (Germany)

    2010-07-01

    In this paper a computational approach for fatigue life prediction of dissimilarly welded superheater tubes is presented and applied to a dissimilar weld between tubes made of the nickel base alloy Alloy617 tube and the 12% chromium steel VM12. The approach comprises the calculation of the residual stresses in the welded tubes with a multi-pass dissimilar welding simulation, the relaxation of the residual stresses in a post weld heat treatment (PWHT) simulation and the fatigue life prediction using the remaining residual stresses as initial condition. A cyclic fiscoplasticity model is used to calculate the transient stresses and strains under thermocyclic service loadings. The fatigue life is predicted with a damage parameter which is based on fracture mechanics. The adjustable parameters of the model are determined based on LCF and TMF experiments. The simulations show, that the residual stresses that remain after PWHT further relax in the first loading cycles. The predicted fatigue lives depend on the residual stresses and, thus, on the choice of the loading cycle in which the damage parameter is evaluated. It the first loading cycle, where residual stresses are still present, is considered, lower fatigue lives are predicted compared to predictions considering loading cycles with relaxed residual stresses. (orig.)

  5. Shelf life prediction of canned fried-rice using accelerated shelf life testing (ASLT) arrhenius method

    Science.gov (United States)

    Kurniadi, M.; Bintang, R.; Kusumaningrum, A.; Nursiwi, A.; Nurhikmat, A.; Susanto, A.; Angwar, M.; Triwiyono; Frediansyah, A.

    2017-12-01

    Research on shelf-life prediction of canned fried rice using Accelerated Shelf-life Test (ASLT) of Arrhenius model has been conducted. The aim of this research to predict shelf life of canned-fried rice products. Lethality value of 121°C for 15 and 20 minutes and Total Plate count methods are used to determine time and temperatures of sterilization process.Various storage temperatures of ASLT Arrhenius method were 35, 45 and 55°C during 35days. Rancidity is one of the derivation quality of canned fried rice. In this research, sample of canned fried rice is tested using rancidity value (TBA). TBA value was used as parameter which be measured once a week periodically. The use of can for fried rice without any chemical preservative is one of the advantage of the product, additionaly the use of physicalproperties such as temperature and pressure during its process can extend the shelf life and reduce the microbial contamination. The same research has never done before for fried rice as ready to eat meal. The result showed that the optimum conditions of sterilization process were 121°C,15 minutes with total plate count number of 9,3 × 101 CFU/ml. Lethality value of canned fried rice at 121°C,15 minutes was 3.63 minutes. The calculated Shelf-life of canned fried rice using Accelerated Shelf-life Test (ASLT) of Arrhenius method was 10.3 months.

  6. Fatigue life prediction of mechanical structures under stochastic loading

    Directory of Open Access Journals (Sweden)

    Leitner Bohuš

    2018-01-01

    Full Text Available Problems of fatigue life prediction of materials and structures are discussed in the paper. Service loading is assumed as a continuous loading process with possible discontinuous events, which are caused by various operating conditions. The damage in a material is due to a cumulative degradation process. The damaging process is then represented either by rain-flow matrices or by a fatigue damage function which is derived using some hypothesis of a fatigue failure criterion. Presented theoretical procedure enables a very effective estimation of a service life and/or reliable evaluation of residual life of any structures under various types of loading and environmental conditions. This approach creates a good basis for powerful expert systems in structural and mechanical engineering. The aim of the paper is to present briefly some results of analysis of load-bearing steel structure loads of special railway crane PKP 25/20i which was utilized in some specific ad relatively hard operating conditions. Virtual models of the structure were being used in an analysis of acting working dynamics loads influence to be able to forecast fatigue life of load-bearing of the crane jib.

  7. Personality predicts recurrence of late-life depression.

    Science.gov (United States)

    Steunenberg, Bas; Beekman, Aartjan T F; Deeg, Dorly J H; Kerkhof, Ad J F M

    2010-06-01

    To examine the association of personality with recurrence of depression in later life. A subsample of 91 subjects from the Longitudinal Aging Study Amsterdam (LASA; baseline sample size n=3107; aged > or = 55 years) depressed at baseline, who had recovered in the course of three years (first follow-up cycle) was identified. 41 (45%) respondents experienced a recurrence during the subsequent six years. The influences of personality and late life stress (demographic factors, health and social factors) on recurrence were investigated prospectively. Recurrence of depression was associated with a high level of neuroticism and low level of mastery, residual depressive symptoms at time of recovery, female gender, pain complaints and feelings of loneliness. In multivariable analysis entering all predictors significant in single variable analysis, residual depressive symptoms and lack of mastery remained significantly associated with recurrence. In predicting the recurrence of depression in later life, the direct effects of personality remain important and comparable in strength with other late life stressors related to recurrence. Copyright 2009 Elsevier B.V. All rights reserved.

  8. Reinforcement Corrosion: Numerical Simulation and Service Life Prediction

    DEFF Research Database (Denmark)

    Michel, Alexander

    Modelling of deterioration processes in concrete structures plays an increasing role in the design of reinforced concrete structures. Large sums are spent every year to ensure the durability of concrete structures, especially towards reinforcement corrosion. Improved durability provides increased...... structural reliability, economical improvements in form of less need for maintenance and repair as well as increased sustainability due to an increased energy and resource efficiency. Several service life prediction models dealing with reinforcement corrosion in concrete structurescan be found...... in the literature. However, the applicability of these models to determine the service life of concrete structures in aggressive environments needs to be investigated as the majority of the models a) assume an initial pristine state of the reinforced concrete structure neglecting the presence of cracks and other...

  9. Using ABAQUS Scripting Interface for Materials Evaluation and Life Prediction

    Science.gov (United States)

    Powers, Lynn M.; Arnold, Steven M.; Baranski, Andrzej

    2006-01-01

    An ABAQUS script has been written to aid in the evaluation of the mechanical behavior of viscoplastic materials. The purposes of the script are to: handle complex load histories; control load/displacement with alternate stopping criteria; predict failure and life; and verify constitutive models. Material models from the ABAQUS library may be used or the UMAT routine may specify mechanical behavior. User subroutines implemented include: UMAT for the constitutive model; UEXTERNALDB for file manipulation; DISP for boundary conditions; and URDFIL for results processing. Examples presented include load, strain and displacement control tests on a single element model. The tests are creep with a life limiting strain criterion, strain control with a stress limiting cycle and a complex interrupted cyclic relaxation test. The techniques implemented in this paper enable complex load conditions to be solved efficiently with ABAQUS.

  10. Life Prediction for a CMC Component Using the NASALIFE Computer Code

    Science.gov (United States)

    Gyekenyesi, John Z.; Murthy, Pappu L. N.; Mital, Subodh K.

    2005-01-01

    The computer code, NASALIFE, was used to provide estimates for life of an SiC/SiC stator vane under varying thermomechanical loading conditions. The primary intention of this effort is to show how the computer code NASALIFE can be used to provide reasonable estimates of life for practical propulsion system components made of advanced ceramic matrix composites (CMC). Simple loading conditions provided readily observable and acceptable life predictions. Varying the loading conditions such that low cycle fatigue and creep were affected independently provided expected trends in the results for life due to varying loads and life due to creep. Analysis was based on idealized empirical data for the 9/99 Melt Infiltrated SiC fiber reinforced SiC.

  11. Development of a Generic Creep-Fatigue Life Prediction Model

    Science.gov (United States)

    Goswami, Tarun

    2002-01-01

    The objective of this research proposal is to further compile creep-fatigue data of steel alloys and superalloys used in military aircraft engines and/or rocket engines and to develop a statistical multivariate equation. The newly derived model will be a probabilistic fit to all the data compiled from various sources. Attempts will be made to procure the creep-fatigue data from NASA Glenn Research Center and other sources to further develop life prediction models for specific alloy groups. In a previous effort [1-3], a bank of creep-fatigue data has been compiled and tabulated under a range of known test parameters. These test parameters are called independent variables, namely; total strain range, strain rate, hold time, and temperature. The present research attempts to use these variables to develop a multivariate equation, which will be a probabilistic equation fitting a large database. The data predicted by the new model will be analyzed using the normal distribution fits, the closer the predicted lives are with the experimental lives (normal line 1 to 1 fit) the better the prediction. This will be evaluated in terms of a coefficient of correlation, R 2 as well. A multivariate equation developed earlier [3] has the following form, where S, R, T, and H have specific meaning discussed later.

  12. CARES/LIFE Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program

    Science.gov (United States)

    Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

    2003-01-01

    This manual describes the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction (CARES/LIFE) computer program. The program calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. CARES/LIFE is an extension of the CARES (Ceramic Analysis and Reliability Evaluation of Structures) computer program. The program uses results from MSC/NASTRAN, ABAQUS, and ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker law. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled by using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. The probabilistic time-dependent theories used in CARES/LIFE, along with the input and output for CARES/LIFE, are described. Example problems to demonstrate various features of the program are also included.

  13. Fatigue life prediction of autofrettage tubes using actual material behaviour

    International Nuclear Information System (INIS)

    Jahed, Hamid; Farshi, Behrooz; Hosseini, Mohammad

    2006-01-01

    There is a profound Bauschinger effect in the behaviour of high-strength steels used in autofrettaged tubes. This has led to development of methods capable of considering experimentally obtained (actual) material behaviour in residual stress calculations. The extension of these methods to life calculations is presented here. To estimate the life of autofrettaged tubes with a longitudinal surface crack emanating from the bore more accurately, instead of using idealized models, the experimental loading-unloading stress-strain behaviour is employed. The resulting stresses are then used to calculate stress intensity factors by the weight function method as input to fatigue life determination. Fatigue lives obtained using the actual material behaviour are then compared with the results of frequently used ideal models including those considering Bauschinger effect factors and strain hardening in unloading. Using standard fatigue crack growth relationships, life of the vessel is then calculated based on recommended initial and final crack length. It is shown that the life gain due to autofrettage above 70% overstrain is considerable

  14. Prediction of drug terminal half-life and terminal volume of distribution after intravenous dosing based on drug clearance, steady-state volume of distribution, and physiological parameters of the body.

    Science.gov (United States)

    Berezhkovskiy, Leonid M

    2013-02-01

    The steady state, V(ss), terminal volume of distribution, V(β), and the terminal half-life, t(1/2), are commonly obtained from the drug plasma concentration-time profile, C(p)(t), following intravenous dosing. Unlike V(ss) that can be calculated based on the physicochemical properties of drugs considering the equilibrium partitioning between plasma and organ tissues, t(1/2) and V(β) cannot be calculated that way because they depend on the rates of drug transfer between blood and tissues. Considering the physiological pharmacokinetic model pertinent to the terminal phase of drug elimination, a novel equation that calculates t(1/2) (and consequently V(β)) was derived. It turns out that V(ss), the total body clearance, Cl, equilibrium blood-plasma concentration ratio, r; and the physiological parameters of the body such as cardiac output, and blood and tissue volumes are sufficient for determination of terminal kinetics. Calculation of t(1/2) by the obtained equation appears to be in good agreement with the experimentally observed vales of this parameter in pharmacokinetic studies in rat, monkey, dog, and human. The equation for the determination of the pre-exponent of the terminal phase of C(p)(t) is also found. The obtained equation allows to predict t(1/2) in human assuming that V(ss) and Cl were either obtained by allometric scaling or, respectively, calculated in silico or based on in vitro drug stability measurements. For compounds that have high clearance, the derived equation may be applied to calculate r just using the routine data on Cl, V(ss), and t(1/2), rather than doing the in vitro assay to measure this parameter. Copyright © 2012 Wiley Periodicals, Inc.

  15. Personality Predicts Health Declines Through Stressful Life Events During Late Mid-Life.

    Science.gov (United States)

    Iacovino, Juliette M; Bogdan, Ryan; Oltmanns, Thomas F

    2016-08-01

    Personality predicts the occurrence of dependent stressful life events (SLE; i.e., events reliant, at least in part, on an individual's behavior). This process, termed stress generation, contributes to psychiatric outcomes, but its role in physical health is unknown. Data were included from 998 participants (aged 55-64) in the St. Louis Personality and Aging Network (SPAN) study. Assessments occurred every 6 months for 18 months. Neuroticism, impulsivity, and agreeableness were measured with the Revised NEO Personality Inventory. Dependent (e.g., divorce) and independent (e.g., family death) SLE occurring within 6 months following baseline were assessed with the List of Threatening Experiences and confirmed by interviews. Health problems occurring within a year after SLE were the outcome. Analyses examined whether neuroticism, impulsivity, and agreeableness indirectly predict the onset of new health problems through exposure to dependent SLE. Each personality trait was associated with dependent, but not independent, SLE. Only dependent SLE predicted new health problems. Each personality trait indirectly predicted the onset of new health problems through dependent SLE. Findings suggest that personality-driven stress generation influences physical health during late mid-life. Addressing personality in interventions may reduce the occurrence of SLE, in turn decreasing health risks. © 2015 Wiley Periodicals, Inc.

  16. Physical/chemical modeling for photovoltaic module life prediction

    Science.gov (United States)

    Moacanin, J.; Carroll, W. F.; Gupta, A.

    1979-01-01

    The paper presents a generalized methodology for identification and evaluation of potential degradation and failure of terrestrial photovoltaic encapsulation. Failure progression modeling and an interaction matrix are utilized to complement the conventional approach to failure degradation mode identification. Comparison of the predicted performance based on these models can produce: (1) constraints on system or component design, materials or operating conditions, (2) qualification (predicted satisfactory function), and (3) uncertainty. The approach has been applied to an investigation of an unexpected delamination failure; it is being used to evaluate thermomechanical interactions in photovoltaic modules and to study corrosion of contacts and interconnects.

  17. Stress analysis and life prediction of gas turbine blade

    Science.gov (United States)

    Hsiung, H. C.; Dunn, A. J.; Woodling, D. R.; Loh, D. L.

    1988-01-01

    A stress analysis procedure is presented for a redesign of the Space Shuttle Main Engine high pressure fuel turbopump turbine blades. The analysis consists of the one-dimensional scoping analysis to support the design layout and the follow-on three-dimensional finite element analysis to confirm the blade design at operating loading conditions. Blade life is evaluated based on high-cycle fatigue and low-cycle fatigue.

  18. A Simple Fatigue Life Prediction Algorithm Using the Modified NASGRO Equation

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2016-01-01

    Full Text Available A simple fatigue life prediction algorithm using the modified NASGRO equation is proposed in this paper. The NASGRO equation is modified by introducing the concept of intrinsic effective threshold stress intensity factor (SIF range ΔKeffth. One advantage of the proposed method is that the complex growth behavior analysis of small cracks can be avoided, and then the fatigue life can be calculated by directly integrating the crack growth model from the initial defect size to the critical crack size. The fatigue limit and the intrinsic effective threshold SIF range ΔKeffth are used to calculate the initial defect size or initial flaw size. The value of ΔKeffth is determined by extrapolating the crack propagation rate curves. Instead of using the fatigue limit determined by the fatigue strength at the specific fatigue life, the fatigue limit is selected based on the horizontal tendency of the S-N curve. The calculated fatigue lives are compared to the experimental data of two different alloys. The predicted S-N curves agree with the test data well. Besides, the prediction results are compared with that calculated using the FASTRAN code. Results indicate that the proposed life prediction algorithm is simple and efficient.

  19. Life Prediction of Spent Fuel Storage Canister Material

    Energy Technology Data Exchange (ETDEWEB)

    Ballinger, Ronald

    2018-04-16

    The original purpose of this project was to develop a probabilistic model for SCC-induced failure of spent fuel storage canisters, exposed to a salt-air environment in the temperature range 30-70°C for periods up to and exceeding 100 years. The nature of this degradation process, which involves multiple degradation mechanisms, combined with variable and uncertain environmental conditions dictates a probabilistic approach to life prediction. A final report for the original portion of the project was submitted earlier. However, residual stress measurements for as-welded and repair welds could not be performed within the original time of the project. As a result of this, a no-cost extension was granted in order to complete these tests. In this report, we report on the results of residual stress measurements.

  20. Life prediction and constitutive models for anisotropic materials

    Science.gov (United States)

    Bill, R. C.

    1982-01-01

    The intent of this program is to develop a basic understanding of cyclic creep-fatigue deformation mechanisms and damage accumulation, a capability for reliable life prediction, and the ability to model the constitutive behavior of anisotropic single crystal (SC) and directionally solidified or recrystallized (DSR) comprise the program, and the work breakdown for each option reflects a distinct concern for two classes of anisotropic materials, SC and DSR materials, at temperatures encountered in the primary gas path (airfoil temperatures), and at temperatures typical of the blade root attachment and shank area. Work directed toward the higher temperature area of concern in the primary gas path includes effects of coatings on the behavior and properties of the materials of interest. The blade root attachment work areas will address the effects of stress concentrations associated with attachment features.

  1. Life Prediction of Large Lithium-Ion Battery Packs with Active and Passive Balancing

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Ying [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Smith, Kandler A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zane, Regan [Utah State University; Anderson, Dyche [Ford Motor Company

    2017-07-03

    Lithium-ion battery packs take a major part of large-scale stationary energy storage systems. One challenge in reducing battery pack cost is to reduce pack size without compromising pack service performance and lifespan. Prognostic life model can be a powerful tool to handle the state of health (SOH) estimate and enable active life balancing strategy to reduce cell imbalance and extend pack life. This work proposed a life model using both empirical and physical-based approaches. The life model described the compounding effect of different degradations on the entire cell with an empirical model. Then its lower-level submodels considered the complex physical links between testing statistics (state of charge level, C-rate level, duty cycles, etc.) and the degradation reaction rates with respect to specific aging mechanisms. The hybrid approach made the life model generic, robust and stable regardless of battery chemistry and application usage. The model was validated with a custom pack with both passive and active balancing systems implemented, which created four different aging paths in the pack. The life model successfully captured the aging trajectories of all four paths. The life model prediction errors on capacity fade and resistance growth were within +/-3% and +/-5% of the experiment measurements.

  2. Quality of life prediction in children with joint hypermobility syndrome.

    Science.gov (United States)

    Pacey, Verity; Tofts, Louise; Adams, Roger D; Munns, Craig F; Nicholson, Leslie L

    2015-07-01

    To assess the child- and parent-reported health-related quality of life (HRQOL) of children with joint hypermobility syndrome (JHS), to compare these with other chronic paediatric conditions and to determine whether symptoms experienced by children with JHS can predict their HRQOL. Eighty-nine children with JHS and one of their parents completed the Pediatric Quality of Life Inventory 4.0 Generic Core Scale, the Multidimensional Fatigue Scale and the Pediatric Pain Questionnaire. Anthropometric measures and reported symptoms were recorded. Child-reported HRQOL scores were compared with parent report, and both child- and parent-reported HRQOL scores of children with JHS were compared with those of children with other chronic conditions. Stepwise multiple regression was undertaken to determine whether any combination of measures could predict HRQOL. Parent- and child-reported HRQOL scores were strongly correlated (r = 0.6-0.84, all P children with JHS perceived lower overall HRQOL (mean difference = 4.44, P = 0.001), physical (mean difference = 7.11, P children. When considered together with previously reported HRQOL scores for children with other chronic conditions, parent and child scores were similarly strongly correlated (r = 0.93, P = 0.001). Multiple regression revealed that 75% of the variance in child-reported HRQOL scores was accounted for by a child's level of pain and fatigue, and presence of stress incontinence symptoms (P Children with JHS experience poor HRQOL and disabling fatigue, with parent scores providing a good proxy. Pain, fatigue and the presence of stress incontinence symptoms have the greatest impact on their HRQOL. © 2015 The Authors. Journal of Paediatrics and Child Health © 2015 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

  3. Life-Space Predicts Health Care Utilization in Community-Dwelling Older Adults.

    Science.gov (United States)

    Kennedy, Richard E; Williams, Courtney P; Sawyer, Patricia; Lo, Alexander X; Connelly, Kay; Nassel, Ariann; Brown, Cynthia J

    2017-09-01

    To determine whether decline in life-space mobility predicts increased health care utilization among community-dwelling older adults. Health care utilization (number of emergency department [ED] visits and hospitalizations) was self-reported during monthly interviews among 419 community-dwelling African American and non-Hispanic White adults aged 75 years and older in The University of Alabama at Birmingham (UAB) Study of Aging II. Life-space was measured using the UAB Life-Space Assessment. Generalized estimating equations were used to examine associations of life-space at the beginning of each interval with health care utilization over the 1-month interval. Overall, 400 participants were followed for 36 months. A 10-point decrease in life-space was associated with 14% increased odds of an ED visit and/or hospitalization over the next month, adjusting for demographics, transportation difficulty, comorbidity, and having a doctor visit in the last month. Life-space is a practical alternative in predicting future health care utilization to performance-based measures, which can be difficult to incorporate into clinical or public health practice.

  4. Thermomechanical Fatigue of Ductile Cast Iron and Its Life Prediction

    Science.gov (United States)

    Wu, Xijia; Quan, Guangchun; MacNeil, Ryan; Zhang, Zhong; Liu, Xiaoyang; Sloss, Clayton

    2015-06-01

    Thermomechanical fatigue (TMF) behaviors of ductile cast iron (DCI) were investigated under out-of-phase (OP), in-phase (IP), and constrained strain-control conditions with temperature hold in various temperature ranges: 573 K to 1073 K, 723 K to 1073 K, and 433 K to 873 K (300 °C to 800 °C, 450 °C to 800 °C, and 160 °C to 600 °C). The integrated creep-fatigue theory (ICFT) model was incorporated into the finite element method to simulate the hysteresis behavior and predict the TMF life of DCI under those test conditions. With the consideration of four deformation/damage mechanisms: (i) plasticity-induced fatigue, (ii) intergranular embrittlement, (iii) creep, and (iv) oxidation, as revealed from the previous study on low cycle fatigue of the material, the model delineates the contributions of these physical mechanisms in the asymmetrical hysteresis behavior and the damage accumulation process leading to final TMF failure. This study shows that the ICFT model can simulate the stress-strain response and life of DCI under complex TMF loading profiles (OP and IP, and constrained with temperature hold).

  5. Predicting Education Effects on Entrepreneur’s Strategic Choices and Life Quality

    Directory of Open Access Journals (Sweden)

    Tarja Niemela

    2015-11-01

    Full Text Available We demonstrate four models in prediction of the dependencies between entrepreneurs’ education, developmental intentions and perception of quality of life based on survey data (2012, n=460. Entrepreneurs with the higher level of education were more likely to maintain the current production line, plan pluriactive businesses and consider wage income and cooperation more important than others. Similarly, entrepreneurs with lower level of education experienced more often problems to cope with current and future farm work with existing resources. To conclude, spouses’ education seems to influence farm’s choices and quality of life. Implications for human capital theory and entrepreneurship education emerged.

  6. Probabilistic approaches to life prediction of nuclear plant structural components

    International Nuclear Information System (INIS)

    Villain, B.; Pitner, P.; Procaccia, H.

    1996-01-01

    In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in a assessment of the performance of these structural components, probabilistic methods. The benefits of a probabilistic approach are the clear treatment of uncertainly and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel). (authors)

  7. Probabilistic approaches to life prediction of nuclear plant structural components

    International Nuclear Information System (INIS)

    Villain, B.; Pitner, P.; Procaccia, H.

    1996-01-01

    In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in an assessment of the performance of these structural components, probabilistic methods provide an attractive alternative or supplement to more conventional deterministic methods. The benefits of a probabilistic approach are the clear treatment of uncertainty and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel)

  8. Numerical analysis of rolling contact fatigue crack initiation and fatigue life prediction of the railway crossing

    OpenAIRE

    Xin, L.; Markine, V.L.; Shevtsov, I.

    2015-01-01

    The procedure for analysing rolling contact fatigue crack initiation and fatigue life prediction of the railway turnout crossing is developed. A three-dimensional finite element (FE) model is used to obtain stress and strain results, considering the dynamic effects of wheel-crossing rolling contact. Material model accounting for elastic- plastic isotropic and kinematic hardening effects is adopted. The results from FE analysis are combined with J-S fatigue model that is based on critical plan...

  9. Trust-based collective view prediction

    CERN Document Server

    Luo, Tiejian; Xu, Guandong; Zhou, Jia

    2013-01-01

    Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users' past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View

  10. Method and apparatus to predict the remaining service life of an operating system

    Science.gov (United States)

    Greitzer, Frank L.; Kangas, Lars J.; Terrones, Kristine M.; Maynard, Melody A.; Pawlowski, Ronald A. , Ferryman; Thomas A.; Skorpik, James R.; Wilson, Bary W.

    2008-11-25

    A method and computer-based apparatus for monitoring the degradation of, predicting the remaining service life of, and/or planning maintenance for, an operating system are disclosed. Diagnostic information on degradation of the operating system is obtained through measurement of one or more performance characteristics by one or more sensors onboard and/or proximate the operating system. Though not required, it is preferred that the sensor data are validated to improve the accuracy and reliability of the service life predictions. The condition or degree of degradation of the operating system is presented to a user by way of one or more calculated, numeric degradation figures of merit that are trended against one or more independent variables using one or more mathematical techniques. Furthermore, more than one trendline and uncertainty interval may be generated for a given degradation figure of merit/independent variable data set. The trendline(s) and uncertainty interval(s) are subsequently compared to one or more degradation figure of merit thresholds to predict the remaining service life of the operating system. The present invention enables multiple mathematical approaches in determining which trendline(s) to use to provide the best estimate of the remaining service life.

  11. Ways that Social Change Predicts Personal Quality of Life

    Science.gov (United States)

    Cheung, Chau-Kiu; Leung, Kwok

    2010-01-01

    A notable way that social change affects personal quality of life would rely on the person's experience with social change. This experience may influence societal quality of life and quality of work life, which may in turn affect personal quality of life. Additionally, the experience of social change is possibly less detrimental to personal…

  12. Game-Based Life-Long Learning

    NARCIS (Netherlands)

    Kelle, Sebastian; Sigurðarson, Steinn; Westera, Wim; Specht, Marcus

    2010-01-01

    Kelle, S., Sigurðarson, S., Westera, W., & Specht, M. (2011). Game-Based Life-Long Learning. In G. D. Magoulas (Ed.), E-Infrastructures and Technologies for Lifelong Learning: Next Generation Environments (pp. 337-349). Hershey, PA: IGI Global.

  13. Durability and life prediction modeling in polyimide composites

    Science.gov (United States)

    Binienda, Wieslaw K.

    1995-01-01

    Sudden appearance of cracks on a macroscopically smooth surface of brittle materials due to cooling or drying shrinkage is a phenomenon related to many engineering problems. Although conventional strength theories can be used to predict the necessary condition for crack appearance, they are unable to predict crack spacing and depth. On the other hand, fracture mechanics theory can only study the behavior of existing cracks. The theory of crack initiation can be summarized into three conditions, which is a combination of a strength criterion and laws of energy conservation, the average crack spacing and depth can thus be determined. The problem of crack initiation from the surface of an elastic half plane is solved and compares quite well with available experimental evidence. The theory of crack initiation is also applied to concrete pavements. The influence of cracking is modeled by the additional compliance according to Okamura's method. The theoretical prediction by this structural mechanics type of model correlates very well with the field observation. The model may serve as a theoretical foundation for future pavement joint design. The initiation of interactive cracks of quasi-brittle material is studied based on a theory of cohesive crack model. These cracks may grow simultaneously, or some of them may close during certain stages. The concept of crack unloading of cohesive crack model is proposed. The critical behavior (crack bifurcation, maximum loads) of the cohesive crack model are characterized by rate equations. The post-critical behavior of crack initiation is also studied.

  14. Life-history traits predict perennial species response to fire in a desert ecosystem

    Science.gov (United States)

    Shryock, Daniel F.; DeFalco, Lesley A.; Esque, Todd C.

    2014-01-01

    The Mojave Desert of North America has become fire-prone in recent decades due to invasive annual grasses that fuel wildfires following years of high rainfall. Perennial species are poorly adapted to fire in this system, and post-fire shifts in species composition have been substantial but variable across community types. To generalize across a range of conditions, we investigated whether simple life-history traits could predict how species responded to fire. Further, we classified species into plant functional types (PFTs) based on combinations of life-history traits and evaluated whether these groups exhibited a consistent fire-response. Six life-history traits varied significantly between burned and unburned areas in short (up to 4 years) or long-term (up to 52 years) post-fire datasets, including growth form, lifespan, seed size, seed dispersal, height, and leaf longevity. Forbs and grasses consistently increased in abundance after fire, while cacti were reduced and woody species exhibited a variable response. Woody species were classified into three PFTs based on combinations of life-history traits. Species in Group 1 increased in abundance after fire and were characterized by short lifespans, small, wind-dispersed seeds, low height, and deciduous leaves. Species in Group 2 were reduced by fire and distinguished from Group 1 by longer lifespans and evergreen leaves. Group 3 species, which also decreased after fire, were characterized by long lifespans, large non-wind dispersed seeds, and taller heights. Our results show that PFTs based on life-history traits can reliably predict the responses of most species to fire in the Mojave Desert. Dominant, long-lived species of this region possess a combination of traits limiting their ability to recover, presenting a clear example of how a novel disturbance regime may shift selective environmental pressures to favor alternative life-history strategies.

  15. Basic traits predict the prevalence of personality disorder across the life span: the example of psychopathy.

    Science.gov (United States)

    Vachon, David D; Lynam, Donald R; Widiger, Thomas A; Miller, Joshua D; McCrae, Robert R; Costa, Paul T

    2013-05-01

    Personality disorders (PDs) may be better understood in terms of dimensions of general personality functioning rather than as discrete categorical conditions. Personality-trait descriptions of PDs are robust across methods and settings, and PD assessments based on trait measures show good construct validity. The study reported here extends research showing that basic traits (e.g., impulsiveness, warmth, straightforwardness, modesty, and deliberation) can re-create the epidemiological characteristics associated with PDs. Specifically, we used normative changes in absolute trait levels to simulate age-related differences in the prevalence of psychopathy in a forensic setting. Results demonstrated that trait information predicts the rate of decline for psychopathy over the life span; discriminates the decline of psychopathy from that of a similar disorder, antisocial PD; and accurately predicts the differential decline of subfactors of psychopathy. These findings suggest that basic traits provide a parsimonious account of PD prevalence across the life span.

  16. International Space Station Bacteria Filter Element Post-Flight Testing and Service Life Prediction

    Science.gov (United States)

    Perry, J. L.; von Jouanne, R. G.; Turner, E. H.

    2003-01-01

    The International Space Station uses high efficiency particulate air (HEPA) filters to remove particulate matter from the cabin atmosphere. Known as Bacteria Filter Elements (BFEs), there are 13 elements deployed on board the ISS's U.S. Segment. The pre-flight service life prediction of 1 year for the BFEs is based upon performance engineering analysis of data collected during developmental testing that used a synthetic dust challenge. While this challenge is considered reasonable and conservative from a design perspective, an understanding of the actual filter loading is required to best manage the critical ISS Program resources. Thus testing was conducted on BFEs returned from the ISS to refine the service life prediction. Results from this testing and implications to ISS resource management are discussed. Recommendations for realizing significant savings to the ISS Program are presented.

  17. A Modelling Study for Predicting Life of Downhole Tubes Considering Service Environmental Parameters and Stress

    Directory of Open Access Journals (Sweden)

    Tianliang Zhao

    2016-09-01

    Full Text Available A modelling effort was made to try to predict the life of downhole tubes or casings, synthetically considering the effect of service influencing factors on corrosion rate. Based on the discussed corrosion mechanism and corrosion processes of downhole tubes, a mathematic model was established. For downhole tubes, the influencing factors are environmental parameters and stress, which vary with service duration. Stress and the environmental parameters including water content, partial pressure of H2S and CO2, pH value, total pressure and temperature, were considered to be time-dependent. Based on the model, life-span of an L80 downhole tube in oilfield Halfaya, an oilfield in Iraq, was predicted. The results show that life-span of the L80 downhole tube in Halfaya is 247 months (approximately 20 years under initial stress of 0.1 yield strength and 641 months (approximately 53 years under no initial stress, which indicates that an initial stress of 0.1 yield strength will reduce the life-span by more than half.

  18. A Modelling Study for Predicting Life of Downhole Tubes Considering Service Environmental Parameters and Stress

    Science.gov (United States)

    Zhao, Tianliang; Liu, Zhiyong; Du, Cuiwei; Hu, Jianpeng; Li, Xiaogang

    2016-01-01

    A modelling effort was made to try to predict the life of downhole tubes or casings, synthetically considering the effect of service influencing factors on corrosion rate. Based on the discussed corrosion mechanism and corrosion processes of downhole tubes, a mathematic model was established. For downhole tubes, the influencing factors are environmental parameters and stress, which vary with service duration. Stress and the environmental parameters including water content, partial pressure of H2S and CO2, pH value, total pressure and temperature, were considered to be time-dependent. Based on the model, life-span of an L80 downhole tube in oilfield Halfaya, an oilfield in Iraq, was predicted. The results show that life-span of the L80 downhole tube in Halfaya is 247 months (approximately 20 years) under initial stress of 0.1 yield strength and 641 months (approximately 53 years) under no initial stress, which indicates that an initial stress of 0.1 yield strength will reduce the life-span by more than half. PMID:28773872

  19. Prediction of composite fatigue life under variable amplitude loading using artificial neural network trained by genetic algorithm

    Science.gov (United States)

    Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung

    2018-04-01

    Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

  20. Life estimation I and C cable insulation materials based on accelerated life testing accelerated life testing

    International Nuclear Information System (INIS)

    Santhosh, T.V.; Ramteke, P.K.; Shrestha, N.B.; Ahirwar, A.K.; Gopika, V.

    2016-01-01

    Accelerated Iife tests are becoming increasingly popular in today's industry due to the need for obtaining life data quickly and reliably. Life testing of products under higher stress levels without introducing additional failure modes can provide significant savings of both time and money. Correct analysis of data gathered via such accelerated life testing will yield parameters and other information for the product's life under use stress conditions. To be of practical use in assessing the operational behaviour of cables in NPPs, laboratory ageing aims to mimic the type of degradation observed under operational conditions. Conditions of testing therefore need to be carefully chosen to ensure that the degradation mechanism occurring in the accelerated tests are similar to those which occur in service. This paper presents the results of an investigation in which the elongation-at-break (EAB) measurements were carried on a typical control cable to predict the mean life at service conditions. A low voltage polyvinyl chloride (PVC) insulated and PVC sheathed control cable, used in NPP instrumentation and control (I and C) applications, was subjected thermal ageing at three elevated temperatures

  1. Predicting the creep life and failure mode of low-alloy steel weldments

    Energy Technology Data Exchange (ETDEWEB)

    Brear, J.M.; Middleton, C.J.; Aplin, P.F. [ERA Technology Ltd., Leatherhead (United Kingdom)

    1998-12-31

    This presentation reviews and consolidates experience gained through a number of research projects and practical plant assessments in predicting both the life and the likely failure mode and location in low alloy steel weldments. The approach adopted begins with the recognition that the relative strength difference between the microstructural regions is a key factor controlling both life and failure location. Practical methods based on hardness measurement and adaptable to differing weld geometries are presented and evidence for correlations between hardness ratio, damage accumulation and strain development is discussed. Predictor diagrams relating weld life and failure location to the service conditions and the hardness of the individual microstructural constituents are suggested and comments are given on the implications for identifying the circumstances in which Type IV cracking is to be expected. (orig.) 6 refs.

  2. The Fatigue Life Prediction of Train Wheel Rims Containing Spherical Inclusions

    Science.gov (United States)

    Li, Yajie; Chen, Huanguo; Cai, Li; Chen, Pei; Qian, Jiacheng; Wu, Jianwei

    2018-03-01

    It is a common phenomenon that fatigue crack initiation occurs frequently in the inclusions of wheel rims. Research on the fatigue life of wheel rims with spherical inclusions is of great significance on the reliability of wheels. To find the danger point and working condition of a wheel, the stress state of the wheel rim with spherical inclusions was analyzed using the finite element method. Results revealed that curve conditions are dangerous. The critical plane method, based on the cumulative fatigue damage theory, was used to predict the fatigue life of the wheel rim and whether it contained spherical inclusions or not under curve conditions. It was found that the fatigue life of the wheel rim is significantly shorter when the wheel rim contains spherical inclusions. Analysis of the results can provide a theoretical basis and technical support for train operations and maintenance.

  3. Predicting Rose Vase Life in a Supply Chain

    NARCIS (Netherlands)

    Meeteren, van U.; Schouten, R.E.; Woltering, E.J.

    2015-01-01

    An important quality attribute of cut flowers is their vase life. With increasing market globalization, the vase life is more and more affected by transport and storage. However, techniques to measure the potential vase life at the point of sale in the chain are not available at this moment.

  4. The Social Life of a Data Base

    Science.gov (United States)

    Linde, Charlotte; Wales, Roxana; Clancy, Dan (Technical Monitor)

    2002-01-01

    This paper presents the complex social life of a large data base. The topics include: 1) Social Construction of Mechanisms of Memory; 2) Data Bases: The Invisible Memory Mechanism; 3) The Human in the Machine; 4) Data of the Study: A Large-Scale Problem Reporting Data Base; 5) The PRACA Study; 6) Description of PRACA; 7) PRACA and Paper; 8) Multiple Uses of PRACA; 9) The Work of PRACA; 10) Multiple Forms of Invisibility; 11) Such Systems are Everywhere; and 12) Two Morals to the Story. This paper is in viewgraph form.

  5. Speech Intelligibility Prediction Based on Mutual Information

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, Cees H.

    2014-01-01

    a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting......This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...

  6. Ghrelin level negatively predicts quality of life in obese women.

    Science.gov (United States)

    Lu, P H; Song, Y L; Hsu, C H

    2017-02-01

    A cross-sectional cohort study was conducted to investigate whether ghrelin level in obese women predicts the quality of life (QOL). A total of 307 subjects fulfilled the criteria: (1) age between 20 and 65 years old, (2) body mass index ≥27 kg/m 2 (3) waist circumference ≥80 cm were enrolled in the study. All subjects were assigned to one of the plasma ghrelin level categories according to the quartiles. The median of age and BMI of the 307 obese women were 45 ± 18 years and 29.9 ± 4.1 kg/m 2 , respectively. The main outcome evaluated is the associations of plasma ghrelin level and QOL, which were evaluated using multiple linear regression analysis. Results of linear trend test show significant statistical difference in plasma lipoproteins (triglyceride, cholesterol, HDL-cholestero and LDL-cholesterol = and levels of obesity-related hormone peptides, including leptin, adiponectin, insulin among quartiles of ghrelin. Multiple liner regression analysis of serum obesity-related hormone peptide level and QOL using stepwise method shows ghrelin concentration was the only predictor of QOL, including PCS-12 level (β = -0.18, p = 0.001), MCS-12 level (β = -0.14, p = 0.009), WHOQOL-BREF scores: physical (β = -0.13, p = 0.03), psychological (β = -0.16, p = 0.007), social (β = -0.21, p =  ghrelin concentration is strongly associated with QOL level among obese women. Hence, ghrelin concentration might be a valuable marker to be monitored in obese women.

  7. Calorimeter prediction based on multiple exponentials

    International Nuclear Information System (INIS)

    Smith, M.K.; Bracken, D.S.

    2002-01-01

    Calorimetry allows very precise measurements of nuclear material to be carried out, but it also requires relatively long measurement times to do so. The ability to accurately predict the equilibrium response of a calorimeter would significantly reduce the amount of time required for calorimetric assays. An algorithm has been developed that is effective at predicting the equilibrium response. This multi-exponential prediction algorithm is based on an iterative technique using commercial fitting routines that fit a constant plus a variable number of exponential terms to calorimeter data. Details of the implementation and the results of trials on a large number of calorimeter data sets will be presented

  8. Statistical methodology for predicting the life of lithium-ion cells via accelerated degradation testing

    Science.gov (United States)

    Thomas, E. V.; Bloom, I.; Christophersen, J. P.; Battaglia, V. S.

    Statistical models based on data from accelerated aging experiments are used to predict cell life. In this article, we discuss a methodology for estimating the mean cell life with uncertainty bounds that uses both a degradation model (reflecting average cell performance) and an error model (reflecting the measured cell-to-cell variability in performance). Specific forms for the degradation and error models are presented and illustrated with experimental data that were acquired from calendar-life testing of high-power lithium-ion cells as part of the U.S. Department of Energy's (DOEs) Advanced Technology Development program. Monte Carlo simulations, based on the developed models, are used to assess lack-of-fit and develop uncertainty limits for the average cell life. In addition, we discuss the issue of assessing the applicability of degradation models (based on data acquired from cells aged under static conditions) to the degradation of cells aged under more realistic dynamic conditions (e.g., varying temperature).

  9. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  10. A method for gear fatigue life prediction considering the internal flow field of the gear pump

    Science.gov (United States)

    Shen, Haidong; Li, Zhiqiang; Qi, Lele; Qiao, Liang

    2018-01-01

    Gear pump is the most widely used volume type hydraulic pump, and it is the main power source of the hydraulic system. Its performance is influenced by many factors, such as working environment, maintenance, fluid pressure and so on. It is different from the gear transmission system, the internal flow field of gear pump has a greater impact on the gear life, therefore it needs to consider the internal hydraulic system when predicting the gear fatigue life. In this paper, a certain aircraft gear pump as the research object, aim at the typical failure forms, gear contact fatigue, of gear pump, proposing the prediction method based on the virtual simulation. The method use CFD (Computational fluid dynamics) software to analyze pressure distribution of internal flow field of the gear pump, and constructed the unidirectional flow-solid coupling model of gear to acquire the contact stress of tooth surface on Ansys workbench software. Finally, employing nominal stress method and Miner cumulative damage theory to calculated the gear contact fatigue life based on modified material P-S-N curve. Engineering practice show that the method is feasible and efficient.

  11. Numerical/phenomenological model for fatigue life prediction of hybrid laminates

    Science.gov (United States)

    Dadej, Konrad; Surowska, Barbara; Bieniaś, Jarosław

    2018-01-01

    In this article, the fatigue stress-cycle (S-N) curves of carbon fiber reinforced polymer (CFRP) and glass fiber reinforced polymer (GFRP) were investigated. Experimental fatigue tests were performed on unidirectional specimens and the S-N curves for GFRP and CFRP materials were determined. Obtained S-N curves were next described by phenomenological model (PM) based on mathematical function containing convexity and concavity ranges of stress-cycle curve. Based on the PM and numerical static analyses performed in ABAQUS/Standard on hybrid glass-carbon fiber reinforced polymer, the fatigue S-N curve was predicted for this material. Numerical/phenomenological model predictions were validated by experimental tests, where good agreement was obtained in the field of static tensile strength, shape of S-N curve and infinite fatigue life.

  12. Knowledge-Based Systems in Biomedicine and Computational Life Science

    CERN Document Server

    Jain, Lakhmi

    2013-01-01

    This book presents a sample of research on knowledge-based systems in biomedicine and computational life science. The contributions include: ·         personalized stress diagnosis system ·         image analysis system for breast cancer diagnosis ·         analysis of neuronal cell images ·         structure prediction of protein ·         relationship between two mental disorders ·         detection of cardiac abnormalities ·         holistic medicine based treatment ·         analysis of life-science data  

  13. Fuzzy Activity Based Life Cycle Costing For Repairable Equipment

    Directory of Open Access Journals (Sweden)

    Mulubrhan Freselam

    2016-01-01

    Full Text Available Life-cycle cost (LCC is the much known method used for decision making that considers all costs in the life of a system or equipment. Predicting LCCs is fraught with potential errors, owing to the uncertainty in future events, future costs, interest rates, and even hidden costs. These uncertainties have a direct impact on the decision making. Activity based LCC is used to identify the activities and cost drivers in acquisition, operation and maintenance phase. This activity based LCC is integrated with fuzzy set theory and interval mathematics to model these uncertainties. Day–Stout–Warren (DSW algorithm and the vertex method are then used to evaluate competing alternatives. A case of two pumps (Pump A and Pump B are taken and their LCC is analysed using the developed model. The equivalent annual cost of Pump B is greater than Pump A, which leads the decision maker to choose Pump A over Pump B.

  14. DESIGN PROCEDURE OF SAFE LIFE AND PREDICTION OF DURABILITY OF MACHINES DETAILS AT FRICTION LOADING

    Directory of Open Access Journals (Sweden)

    В. Варюхно

    2011-04-01

    Full Text Available The aspects of prediction of durability of machines details are examined by friction loading. Onthe basis of used forecasts of change of object conditions the design procedure of safe life ofaviation engineering products, which works in conditions of friction loading. On the basis ofanalysis of the received results the theoretical model of prediction of the wear processes duringservice life is offered

  15. Do Proxies for the Neurotransmitter Cortisol Predict Adaptation to Life with Chronic Pain?

    Science.gov (United States)

    Deamond, Wade

    Among the numerous difficulties encountered by chronic pain patients, impulsive and dysfunctional decision-making complicate their already difficult life situations yet remains relatively understudied. This study examined a recently published neurobiological decision making model that identifies eight specific neurotransmitters and hormones (Dopamine, Testosterone, Endogenous Opioids Glutamate, Serotonin, Norepinephrine, Cortisol, and GABA) linked to unsound decision making related to cognitive, motivational and emotional dysregulation (Nussbaum et al., 2011) (see Appendix 2). The Perceived Stress Scale (PSS), a proxy for the cortisol element in the pharmacological decision making model was analyzed for the neurotransmitter's relationship to functionality and quality of life in a group of 37 chronic pain patients. Participants were comprised of males and females ranging from 23 to 52 years of age and were classified with respect to levels of adjustment to living with chronic pain based on the Quality of Life Scale (QLS), the Dartmouth WONCA COOP Charts and the Global Assessment of Functioning (GAF). The Iowa Gambling Task (IGT) and Frontal System Behavioral Scale (FSBS) measured decision making related to immediate gratification and daily living respectively. Results suggest that emotional dysregulation, as measured by the PSS is a significant predictor for adaptation to life with chronic pain and the PSS is superior to predicting adaptation to life with chronic pain than reported levels of pain as measured by the McGill Pain Questionnaire.

  16. Fatigue life prediction for a cold worked T316 stainless steel

    International Nuclear Information System (INIS)

    Manjoine, M.J.

    1983-01-01

    Permanent damage curves of initiation-life and propagation-life which predict the fatigue life of specimens of a cold-worked type 316 stainless steel under complex strain-range histories were generated by a limited test program. Analysis of the test data showed that fatigue damage is not linear throughout life and that propagation life is longer than initiation-life at high strain ranges but is shorter at low strain ranges. If permanent damage has been initiated by prior history and/or fabrication, propagation to a given life can occur at a lower strain range than that estimated from the fatigue curves for constant CSR. (author) [pt

  17. Predicting Rose Vase Life in a Supply Chain

    NARCIS (Netherlands)

    Meeteren, van U.; Schouten, R.E.; Harkema, H.; Bastiaan-Net, S.; Woltering, E.J.

    2013-01-01

    With increasing market globalization quality management of cut flowers is a necessity. An important attribute of quality of cut flowers is their vase life at the final consumer. However, techniques to measure the potential vase life at points of sale in the chain are not available at this moment.

  18. Method for estimating capacity and predicting remaining useful life of lithium-ion battery

    International Nuclear Information System (INIS)

    Hu, Chao; Jain, Gaurav; Tamirisa, Prabhakar; Gorka, Tom

    2014-01-01

    Highlights: • We develop an integrated method for the capacity estimation and RUL prediction. • A state projection scheme is derived for capacity estimation. • The Gauss–Hermite particle filter technique is used for the RUL prediction. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the capacity of Li-ion battery and predict the remaining useful life (RUL) throughout the whole life-time. This paper presents an integrated method for the capacity estimation and RUL prediction of Li-ion battery used in implantable medical devices. A state projection scheme from the author’s previous study is used for the capacity estimation. Then, based on the capacity estimates, the Gauss–Hermite particle filter technique is used to project the capacity fade to the end-of-service (EOS) value (or the failure limit) for the RUL prediction. Results of 10 years’ continuous cycling test on Li-ion prismatic cells in the lab suggest that the proposed method achieves good accuracy in the capacity estimation and captures the uncertainty in the RUL prediction. Post-explant weekly cycling data obtained from field cells with 4–7 implant years further verify the effectiveness of the proposed method in the capacity estimation

  19. Life Prediction for FRP composites with Data Fusion & Machine Learning

    Data.gov (United States)

    National Aeronautics and Space Administration — High-fidelity, probabilistic predictions of damage evolution in fiber-reinforced polymer (FRP) composite structures could accelerate development and certification of...

  20. Neural network fatigue life prediction in steel i-beams using mathematically modeled acoustic emission data

    Science.gov (United States)

    Selvadorai, Prathikshen N.

    The purpose of this research is to predict fatigue cracking in metal beams using mathematically modeled acoustic emission (AE) data. The AE data was collected from nine samples of steel Ibeam that were subjected to three-point bending caused by cyclic loading. The data gathered during these tests were filtered in order to remove long duration hits, multiple hit data, and obvious outliers. Based on the duration, energy, amplitude, and average frequency of the AE hits, the filtered data were classified into the various failure mechanisms of metals using NeuralWorksRTM Professional II/Plus software based self-organizing map (SOM) neural network. The parameters from mathematically modeled AE failure mechanism data were used to predict plastic deformation data. Amplitude data from classified plastic deformation data is mathematically modeled herein using bounded Johnson distributions and Weibull distribution. A backpropagation neural network (BPNN) is generated using MATLABRTM. This BPNN is able to predict the number of cycles that ultimately cause the steel I-beams to fail via five different models of plastic deformation data. These five models are data without any mathematical modeling and four which are mathematically modeled using three methods of bounded Johnson distribution (Slifker and Shapiro, Mage and Linearization) and Weibull distribution. Currently, the best method is the Linearization method that has prediction error not more than 17%. Multiple linear regression (MLR) analysis is also performed on the four sets of mathematically modeled plastic deformation data as named above using the bounded Johnson and Weibull shape parameters. The MLR gives the best prediction for the Linearized method which has a prediction error not more than 2%. The final conclusion made is that both BPNN and MLR are excellent tools for accurate fatigue life cycle prediction.

  1. Mastery and Neuroticism Predict Recovery of Depression in later Life.

    NARCIS (Netherlands)

    Steunenberg, B.; Beekman, A.T.F.; Deeg, D.J.H.; Bremmer, M.A.; Kerkhof, A.J.F.M.

    2007-01-01

    Objective: The authors examined whether personality characteristics such as mastery, self-efficacy, and neuroticism predict the likelihood of recovery of depression among elderly in the community. It was hypothesized that these personality characteristics do predict recovery but that their effect is

  2. Degradation model and application in life prediction of rotating-mechanism

    International Nuclear Information System (INIS)

    Zhou Yuhui

    2009-01-01

    The degradation data can provide additional information beyond that provided by the failure observations, both sets of observations need to be considered when doing inference on the statistical parameters of the product and system lifetime distributions. By the degradation model showing the wear out failure, the predicted results of mechanism life is more accurate. Strength is one of the important capabilities of the rotating mechanism. In this paper, the degradation data of strength are described as a stochastic process model. Accelerated tests expose the products to greater environmental stress levels so that we can obtain lifetime and degradation measurements in a more timely fashion. Using the Best Linear Unbiased Estimation (BLUE) Method, the parameters under the degradation path were estimated from the accelerated life test (ALT) data of the rotating mechanism. Based on solving the singularity of degradation equation, at any time the reliability is estimated by the using the strength-stress interference theory. So we can predict the life of the rotating mechanism. (authors)

  3. A Micromechanics-Based Method for Multiscale Fatigue Prediction

    Science.gov (United States)

    Moore, John Allan

    An estimated 80% of all structural failures are due to mechanical fatigue, often resulting in catastrophic, dangerous and costly failure events. However, an accurate model to predict fatigue remains an elusive goal. One of the major challenges is that fatigue is intrinsically a multiscale process, which is dependent on a structure's geometric design as well as its material's microscale morphology. The following work begins with a microscale study of fatigue nucleation around non- metallic inclusions. Based on this analysis, a novel multiscale method for fatigue predictions is developed. This method simulates macroscale geometries explicitly while concurrently calculating the simplified response of microscale inclusions. Thus, providing adequate detail on multiple scales for accurate fatigue life predictions. The methods herein provide insight into the multiscale nature of fatigue, while also developing a tool to aid in geometric design and material optimization for fatigue critical devices such as biomedical stents and artificial heart valves.

  4. Global life satisfaction predicts ambulatory affect, stress, and cortisol in daily life in working adults.

    Science.gov (United States)

    Smyth, Joshua M; Zawadzki, Matthew J; Juth, Vanessa; Sciamanna, Christopher N

    2017-04-01

    Global life satisfaction has been linked with long-term health advantages, yet how life satisfaction impacts the trajectory of long-term health is unclear. This paper examines one such possible mechanism-that greater life satisfaction confers momentary benefits in daily life that accumulate over time. A community sample of working adults (n = 115) completed a measure of life satisfaction and then three subsequent days of ecological momentary assessment surveys (6 times/day) measuring affect (i.e., emotional valence, arousal), and perceived stress, and also provided salivary cortisol samples. Multilevel models indicated that people with higher (vs. lower) levels of life satisfaction reported better momentary affect, less stress, marginally lower momentary levels and significantly altered diurnal slopes of cortisol. Findings suggest individuals with high global life satisfaction have advantageous daily experiences, providing initial evidence for potential mechanisms through which global life satisfaction may help explain long-term health benefits.

  5. Predicting employment status and subjective quality of life in patients with schizophrenia

    Directory of Open Access Journals (Sweden)

    Haruo Fujino

    2016-03-01

    Full Text Available Although impaired social functioning, particularly poor employment status, is a cardinal feature of patients with schizophrenia and leads to decreased quality of life (QOL, few studies have addressed the relationship between these two clinical issues. The aim of this study was to determine whether employment status predicts subjective QOL and to evaluate a model in which functional capacity mediates the relationship between general cognitive performance and employment status. Ninety-three patients with schizophrenia were administered a comprehensive battery of cognitive tests, the UCSD Performance-based Skills Assessment-Brief version (UPSA-B, the Social Functioning Scale (SFS, and the Subjective Quality of Life Scale (SQLS. First, we evaluated a model for predicting the employment/occupation subscale score of the SFS using path analysis, and the model fitted well (χ2 (4 = 3.6, p = 0.46; CFI = 1.0; RMSEA < 0.001, with 90% CIs: 0–0.152. Employment status was predicted by negative symptoms and functional capacity, which was in turn predicted by general cognitive performance. Second, we added subjective QOL to this model. In a final path model, QOL was predicted by negative symptoms and employment status. This model also satisfied good fit criteria (χ2 (7 = 10.3, p = 0.17; CFI = 0.987; RMSEA = 0.072, with 90% CIs: 0–0.159. The UPSA-B and SFS scores were moderately correlated with most measures of cognitive performance. These results support the notion that better employment status enhances subjective QOL in patients with schizophrenia.

  6. Extended Aging Theories for Predictions of Safe Operational Life of Critical Airborne Structural Components

    Science.gov (United States)

    Ko, William L.; Chen, Tony

    2006-01-01

    The previously developed Ko closed-form aging theory has been reformulated into a more compact mathematical form for easier application. A new equivalent loading theory and empirical loading theories have also been developed and incorporated into the revised Ko aging theory for the prediction of a safe operational life of airborne failure-critical structural components. The new set of aging and loading theories were applied to predict the safe number of flights for the B-52B aircraft to carry a launch vehicle, the structural life of critical components consumed by load excursion to proof load value, and the ground-sitting life of B-52B pylon failure-critical structural components. A special life prediction method was developed for the preflight predictions of operational life of failure-critical structural components of the B-52H pylon system, for which no flight data are available.

  7. Highway traffic noise prediction based on GIS

    Science.gov (United States)

    Zhao, Jianghua; Qin, Qiming

    2014-05-01

    Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.

  8. The meaning of life (events) predicts changes in attachment security.

    Science.gov (United States)

    Davila, Joanna; Sargent, Erica

    2003-11-01

    Building on prior research, which has failed to find consistent effects of life events on change in self-reported adult attachment security over time, the present study tested the hypothesis that it is the meaning people attach to events, rather than the objective features of events, that is associated with changing levels of security. Participants engaged in an 8-week daily diary study, during which they completed daily self-report measures of attachment security, negative life events, perceptions of loss associated with events, and mood. Hierarchical linear modeling revealed that perceptions of greater interpersonal (but not achievement) loss associated with life events were significantly associated with greater insecurity on a day-to-day basis, even controlling for objective features of events and for mood. Trait levels of security did not moderate this association. Results are discussed with regard to social-cognitive models of attachment security and the utility of understanding the meaning of life events to understand how attachment models may be confirmed or disconfirmed.

  9. Personality predicts recurrence of late-life depression.

    NARCIS (Netherlands)

    Steunenberg, B.; Beekman, A.T.F.; Deeg, D.J.H.; Kerkhof, A.J.F.M.

    2010-01-01

    Objective: To examine the association of personality with recurrence of depression in later life. Method: A subsample of 91 subjects from the Longitudinal Aging Study Amsterdam (LASA; baseline sample size n = 3107; aged ≥ 55 years) depressed at baseline, who had recovered in the course of three

  10. Dst Prediction Based on Solar Wind Parameters

    Directory of Open Access Journals (Sweden)

    Yoon-Kyung Park

    2009-12-01

    Full Text Available We reevaluate the Burton equation (Burton et al. 1975 of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q and the decay time (tau of the equation, we examine the relationships between Dst* and VB_s, Delta Dst* and VB_s, and Delta Dst* and Dst* during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to the solar wind forcing. The injection term is found to be Q({nT}/h=-3.56VB_s for VB_s>0.5mV/m and Q({nT}/h=0 for VB_s leq0.5mV/m. The tau (hour is estimated as 0.060 Dst* + 16.65 for Dst*>-175nT and 6.15 hours for Dst* leq -175nT. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted Dst* is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975 and O'Brien & McPherron (2000a. The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms (Dst* lesssim -200nT.

  11. The prediction of reliability and residual life of reactor pressure components

    International Nuclear Information System (INIS)

    Nemec, J.; Antalovsky, S.

    1978-01-01

    The paper deals with the problem of PWR pressure components reliability and residual life evaluation and prediction. A physical model of damage cumulation which serves as a theoretical basis for all considerations presents two major aspects. The first one describes the dependence of the degree of damage in the crack leading-edge in pressure components on the reactor system load-time history, i.e. on the number of transient loads. Both stages, fatigue crack initiation and growth through the wall until the critical length is reached, are investigated. The crack is supposed to initiate at the flaws in a strength weld joint or in the bimetallic weld of the base ferritic steel and the austenitic stainless overlay cladding. The growth rates of developed cracks are analysed in respect to different load-time histories. Important cyclic properties of some steels are derived from the low-cycle fatigue theory. The second aspect is the load-time history-dependent process of precipitation, deformation and radiation aging, characterized entirely by the critical crack-length value mentioned above. The fracture point, defined by the equation ''crack-length=critical value'' and hence the residual life, can be evaluated using this model and verified by in-service inspection. The physical model described is randomized by considering all the parameters of the model as random. Monte Carlo methods are applied and fatigue crack initiation and growth is simulated. This permits evaluation of the reliability and residual life of the component. The distributions of material and load-time history parameters are needed for such simulation. Both the deterministic and computer-simulated probabilistic predictions of reliability and residual life are verified by prior-to-failure sequential testing of data coming from in-service NDT periodical inspections. (author)

  12. Planner-Based Control of Advanced Life Support Systems

    Science.gov (United States)

    Muscettola, Nicola; Kortenkamp, David; Fry, Chuck; Bell, Scott

    2005-01-01

    The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems. Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics due to the integration of a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster: simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction. In particular, methods from model-based planning and scheduling can provide effective resource management over long time periods. We describe reference implementation of an advanced control system using the IDEA control architecture developed at NASA Ames Research Center. IDEA uses planning/scheduling as the sole reasoning method for predictive and reactive closed loop control. We describe preliminary experiments in planner-based control of ALS carried out on an integrated ALS simulation developed at NASA Johnson Space Center.

  13. Predicting the Remaining Useful Life of Rolling Element Bearings

    DEFF Research Database (Denmark)

    Hooghoudt, Jan Otto; Jantunen, E; Yi, Yang

    2018-01-01

    Condition monitoring of rolling element bearings is of vital importance in order to keep the industrial wheels running. In wind industry this is especially important due to the challenges in practical maintenance. The paper presents an attempt to improve the capability of prediction of remaining...

  14. Cyclic behaviour and fatigue life prediction in welded aluminium joints

    International Nuclear Information System (INIS)

    Kosteas, D.

    1979-01-01

    The paper gives an overall state-of-the-art view of international attempts to find a solution, describes cyclic stress-strain behavior for the different zones of aluminium weldments, as stated above, states results from a recent research program of the Versuchsanstalt Stahl, Holz, und Steine in Karlsruhe and gives a step by step model for the calculation procedure of fatigue life. (orig.) 891 RW/orig. 892 RKD [de

  15. Fatigue life prediction of pedicle screw for spinal surgery

    Czech Academy of Sciences Publication Activity Database

    Major, Štěpán; Kocour, Vladimír; Cyrus, P.

    2016-01-01

    Roč. 10, č. 35 (2016), s. 379-388 ISSN 1971-8993. [European Conference on Fracture. ECF21. Catania, 20.06.2015-20.06.2015] Institutional support: RVO:68378297 Keywords : pedicle-screw * titan alloy * fatigue life * finite element analysis Subject RIV: JK - Corrosion ; Surface Treatment of Materials http://www.fracturae.com/index.php/fis/article/view/IGF-ESIS.35.43

  16. Predicting quality of work life on nurses' intention to leave.

    Science.gov (United States)

    Lee, Ya-Wen; Dai, Yu-Tzu; Park, Chang-Gi; McCreary, Linda L

    2013-06-01

    The purpose of this study was to explore the relationship between quality of work life (QWL) and nurses' intention to leave their organization (ITLorg). A descriptive cross-sectional survey design was conducted using purposive sampling of 1,283 nurses at seven hospitals in Taiwan. Data were collected from March to June 2012. Three questionnaires, including the Chinese version of the Quality of Nursing Work Life scale (C-QNWL), a questionnaire of intention to leave the organization, and a demographic questionnaire, with two informed consent forms were delivered to the nurses at their workplaces. Descriptive data, Pearson's correlations, and the ordinal regression model were analyzed. Over half (52.5%) of nurses had ITLorg. Seven QWL dimensions were significantly negatively correlated with ITLorg (r = -0.17 to -0.37, p working in a nonteaching hospital. Four of the QWL dimensions--supportive milieu with job security and professional recognition, work arrangement and workload, work or home life balance, and nursing staffing and patient care--were also predictors of ITLorg. Three QWL dimensions were not predictors of ITLorg. This study showed that individual-related variables (being single, having a diploma or lower educational level), a work-related variable (working at a nonteaching hospital), and the four QWL dimensions play a significant role in nurses' ITLorg. After the QWL dimensions were added to the regression, the variance explained by the model more than doubled. To reduce nurses' ITLorg, nursing administrators may offer more focused interventions to improve the supportive milieu with job security and professional recognition, work arrangement and workload, work or home life balance, and nursing staffing and patient care. © 2013 Sigma Theta Tau International.

  17. Extreme Environment Damage Index and Accumulation Model for CMC Laminate Fatigue Life Prediction, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Materials Research & Design (MR&D) is proposing in the SBIR Phase II an effort to develop a tool for predicting the fatigue life of C/SiC composite...

  18. Characterizing Cracking and Permanent Deformation; An Attempt for Predicting the End of the Structural Pavement Life

    NARCIS (Netherlands)

    Pramesti, F.P.; Molenaar, A.A.A.; van de Ven, M.F.C.

    2017-01-01

    Durable, therefore sustainable, road needs to attain specific characteristics, among others, resistance to permanent deformation and cracking. Determining the development of both characteristics are important to be able to predict pavement life and performance. In this research, permanent

  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. Fundamental understanding and life prediction of stress corrosion cracking in BWRs and energy systems

    International Nuclear Information System (INIS)

    Andresen, P.L.; Ford, F.P.

    1998-01-01

    The objective of this paper is to present an approach for design and lifetime evaluation of environmental cracking based on experimental and fundamental modeling of the underlying processes operative in crack advance. In detailed this approach and its development and quantification for energy (hot water) systems, the requirements for a life prediction methodology will be highlighted and the shortcomings of the existing design and lifetime evaluation codes reviewed. Examples are identified of its use in a variety of cracking systems, such as stainless steels, low alloy steels, nickel base alloys, and irradiation assisted stress corrosion cracking in boiling water reactor (BWR) water, as well as preliminary use for low alloy steel and Alloy 600 in pressurized water reactors (PWRs) and turbine steels in steam turbines. Identification of the common aspects with environmental cracking in other hot water systems provides a secure basis for its extension to related energy systems. 166 refs., 49 figs

  1. Fatigue life prediction in composites using progressive damage modelling under block and spectrum loading

    DEFF Research Database (Denmark)

    Passipoularidis, Vaggelis; Philippidis, T.P.; Brøndsted, Povl

    2010-01-01

    series can be simulated. The predictions are validated against fatigue life data both from repeated block tests at a single stress ratio as well as against spectral fatigue using the WISPER, WISPERX and NEW WISPER load sequences on a Glass/Epoxy multidirectional laminate typical of a Wind Turbine Rotor....... In general, FADAS performs well in predicting life under both spectral and block loading fatigue....

  2. Time-Delay Artificial Neural Network Computing Models for Predicting Shelf Life of Processed Cheese

    OpenAIRE

    Sumit Goyal; Gyanendra Kumar Goyal

    2012-01-01

    This paper presents the capability of Time–delay artificial neural network models for predicting shelf life of processed cheese. Datasets were divided into two subsets (30 for training and 6 for validation). Models with single and multi layers were developed and compared with each other. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash -
    Sutcliffo Coefficient were used as performance evaluators, Time- delay model predicted the shelf life of...

  3. A review on fatigue life prediction methods for anti-vibration rubber materials

    Directory of Open Access Journals (Sweden)

    Xiaoli WANG

    2016-08-01

    Full Text Available Anti-vibration rubber, because of its superior elasticity, plasticity, waterproof and trapping characteristics, is widely used in the automotive industry, national defense, construction and other fields. The theory and technology of predicting fatigue life is of great significance to improve the durability design and manufacturing of anti-vibration rubber products. According to the characteristics of the anti-vibration rubber products in service, the technical difficulties for analyzing fatigue properties of anti-vibration rubber materials are pointed out. The research progress of the fatigue properties of rubber materials is reviewed from three angles including methods of fatigue crack initiation, fatigue crack propagation and fatigue damage accumulation. It is put forward that some nonlinear characteristics of rubber under fatigue loading, including the Mullins effect, permanent deformation and cyclic stress softening, should be considered in the further study of rubber materials. Meanwhile, it is indicated that the fatigue damage accumulation method based on continuum damage mechanics might be more appropriate to solve fatigue damage and life prediction problems for complex rubber materials and structures under fatigue loading.

  4. Vasovagal syncope related to emotional stress predicts coronary events in later life.

    Science.gov (United States)

    Zysko, Dorota; Melander, Olle; Fedorowski, Artur

    2013-08-01

    The aim of the study was to assess whether history of vasovagal syncope (VVS) mediated by emotional (emotional VVS) or orthostatic stress (orthostatic VVS) is associated with an increased risk of cardiovascular (CV) events in later life. Retrospective analysis based on medical records of the consecutive 3,288 cardiologic outpatients (mean age, 61 ± 12 years; 43% men). A total of 254 patients (7.7%) reported emotional VVS, whereas 294 (9.0%) had history of orthostatic VVS. First-ever syncopal episode was reported at a median age of 16 years (interquartile range [IQR], 12 years to 28 years), and the median total number of episodes was two (IQR, 1 to 5). There were 779 patients (23.7%) with at least one CV event, and the median age for the first CV event was 59 years (IQR, 52 years to 67 years). In the fully adjusted model, history of emotional VVS was predictive of CV event (hazard ratio [95% confidence interval]: 1.63, [1.27-2.09]; P emotional VVS and gender. Emotional VVS was predictive of CV event in men (1.89 [1.41-2.53]; P emotional but not orthostatic VVS is independently associated with increased risk of coronary events in later life. The relationship between predisposition to emotional VVS in adolescence and development of cardiovascular disease requires further studies. ©2013, The Authors. Journal compilation ©2013 Wiley Periodicals, Inc.

  5. Risk-informed prediction of feeder end of life

    International Nuclear Information System (INIS)

    Jyrkama, M.; Pandey, M.

    2011-01-01

    The operating life of feeder piping is negatively impacted by flow accelerated corrosion (FAC). In this study, an assessment of a large set of inspection data reveals that FAC in feeders is a relatively stationary process, with variability only at the local scale. Given the added uncertainty from inspection coverage, a new method for estimating the thinning rate and feeder EOL is developed using a probabilistic approach. The results of the study illustrate the benefits of the methodology in supporting risk-informed decision making at the station by quantifying the present and incremental risk in the feeder system over time. (author)

  6. Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

    Science.gov (United States)

    Wang, Dong; Zhao, Yang; Yang, Fangfang; Tsui, Kwok-Leung

    2017-09-01

    Brownian motion with adaptive drift has attracted much attention in prognostics because its first hitting time is highly relevant to remaining useful life prediction and it follows the inverse Gaussian distribution. Besides linear degradation modeling, nonlinear-drifted Brownian motion has been developed to model nonlinear degradation. Moreover, the first hitting time distribution of the nonlinear-drifted Brownian motion has been approximated by time-space transformation. In the previous studies, the drift coefficient is the only hidden state used in state space modeling of the nonlinear-drifted Brownian motion. Besides the drift coefficient, parameters of a nonlinear function used in the nonlinear-drifted Brownian motion should be treated as additional hidden states of state space modeling to make the nonlinear-drifted Brownian motion more flexible. In this paper, a prognostic method based on nonlinear-drifted Brownian motion with multiple hidden states is proposed and then it is applied to predict remaining useful life of rechargeable batteries. 26 sets of rechargeable battery degradation samples are analyzed to validate the effectiveness of the proposed prognostic method. Moreover, some comparisons with a standard particle filter based prognostic method, a spherical cubature particle filter based prognostic method and two classic Bayesian prognostic methods are conducted to highlight the superiority of the proposed prognostic method. Results show that the proposed prognostic method has lower average prediction errors than the particle filter based prognostic methods and the classic Bayesian prognostic methods for battery remaining useful life prediction.

  7. Academic Life Satisfaction Scale (ALSS) and Its Effectiveness in Predicting Academic Success

    Science.gov (United States)

    Kumar, P.K. Sudheesh; P., Dileep

    2006-01-01

    This study is undertaken to examine the effectiveness of a newly constructed psychometric instrument to assess Academic Life Satisfaction along with the components of Emotional Intelligence. The Academic Life Satisfaction Scale is used to predict the scholastic achievement as an index of Academic success. The investigators found that Academic Life…

  8. Structural health monitoring for fatigue life prediction of orthotropic brdige decks

    NARCIS (Netherlands)

    Pijpers, R.J.M.; Pahlavan, P.L.; Paulissen, J.H.; Hakkesteegt, H.C.; Jansen, T.H.

    2013-01-01

    Infrastructure asset owners are more and more confronted with structures reaching the end of their structural life. Structural Health Monitoring (SHM) systems should provide up-to-date information about the actual condition, as well predict the structural life and required maintenance of the assets

  9. Performance reliability prediction for thermal aging based on kalman filtering

    International Nuclear Information System (INIS)

    Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

    2015-01-01

    The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

  10. Aluminum 7075-T6 fatigue data generation and probabilistic life prediction formulation

    OpenAIRE

    Kemna, John G.

    1998-01-01

    Approved for public release; distribution is unlimited. The life extension of aging fleet aircraft requires an assessment of the safe-life remaining after refurbishment. Risk can be estimated by conventional deterministic fatigue analysis coupled with a subjective factor of safety. Alternatively, risk can be quantitatively and objectively predicted by probabilistic analysis. In this investigation, a general probabilistic life formulation is specialized for constant amplitude, fully reverse...

  11. A Fatigue Life Prediction Model of Welded Joints under Combined Cyclic Loading

    Science.gov (United States)

    Goes, Keurrie C.; Camarao, Arnaldo F.; Pereira, Marcos Venicius S.; Ferreira Batalha, Gilmar

    2011-01-01

    A practical and robust methodology is developed to evaluate the fatigue life in seam welded joints when subjected to combined cyclic loading. The fatigue analysis was conducted in virtual environment. The FE stress results from each loading were imported to fatigue code FE-Fatigue and combined to perform the fatigue life prediction using the S x N (stress x life) method. The measurement or modelling of the residual stresses resulting from the welded process is not part of this work. However, the thermal and metallurgical effects, such as distortions and residual stresses, were considered indirectly through fatigue curves corrections in the samples investigated. A tube-plate specimen was submitted to combined cyclic loading (bending and torsion) with constant amplitude. The virtual durability analysis result was calibrated based on these laboratory tests and design codes such as BS7608 and Eurocode 3. The feasibility and application of the proposed numerical-experimental methodology and contributions for the technical development are discussed. Major challenges associated with this modelling and improvement proposals are finally presented.

  12. TWT transmitter fault prediction based on ANFIS

    Science.gov (United States)

    Li, Mengyan; Li, Junshan; Li, Shuangshuang; Wang, Wenqing; Li, Fen

    2017-11-01

    Fault prediction is an important component of health management, and plays an important role in the reliability guarantee of complex electronic equipments. Transmitter is a unit with high failure rate. The cathode performance of TWT is a common fault of transmitter. In this dissertation, a model based on a set of key parameters of TWT is proposed. By choosing proper parameters and applying adaptive neural network training model, this method, combined with analytic hierarchy process (AHP), has a certain reference value for the overall health judgment of TWT transmitters.

  13. Extrapolative prediction using physically-based QSAR

    Science.gov (United States)

    Cleves, Ann E.; Jain, Ajay N.

    2016-02-01

    Surflex-QMOD integrates chemical structure and activity data to produce physically-realistic models for binding affinity prediction . Here, we apply QMOD to a 3D-QSAR benchmark dataset and show broad applicability to a diverse set of targets. Testing new ligands within the QMOD model employs automated flexible molecular alignment, with the model itself defining the optimal pose for each ligand. QMOD performance was compared to that of four approaches that depended on manual alignments (CoMFA, two variations of CoMSIA, and CMF). QMOD showed comparable performance to the other methods on a challenging, but structurally limited, test set. The QMOD models were also applied to test a large and structurally diverse dataset of ligands from ChEMBL, nearly all of which were synthesized years after those used for model construction. Extrapolation across diverse chemical structures was possible because the method addresses the ligand pose problem and provides structural and geometric means to quantitatively identify ligands within a model's applicability domain. Predictions for such ligands for the four tested targets were highly statistically significant based on rank correlation. Those molecules predicted to be highly active (pK_i ≥ 7.5) had a mean experimental pK_i of 7.5, with potent and structurally novel ligands being identified by QMOD for each target.

  14. Crack Growth Modeling and Life Prediction of Pipeline Steels Exposed to Near-Neutral pH Environments: Stage II Crack Growth and Overall Life Prediction

    Science.gov (United States)

    Zhao, Jiaxi; Chen, Weixing; Yu, Mengshan; Chevil, Karina; Eadie, Reg; Been, Jenny; Van Boven, Greg; Kania, Richard; Keane, Sean

    2017-04-01

    This investigation was initiated to provide governing equations for crack initiation, crack growth, and service life prediction of pipeline steels in near-neutral pH (NNpH) environments. This investigation develops a predictive model considering loading interactions occurring during oil and gas pipeline operation with underload-type variable pressure fluctuations. This method has predicted lifetimes comparable to the actual service lives found in the field. This is in sharp contrast with the predictions made by existing methods that are either conservative or inconsistent with the field observations. It has been demonstrated that large slash loads ( R-ratio is 0.05), often seen during gas pipeline operation, are a major life-limiting factor and should be avoided where possible. Oil pipelines have shorter lifetime because of their more frequent pressure fluctuations and larger amplitude load cycles. The accuracy of prediction can be improved if pressure data with appropriate sampling intervals are used. The sampling interval error is much larger in the prediction of oil pipelines than gas pipelines because of their different compressibility but is minimized if the pressure sampling rate for the data is at or less than one minute.

  15. Prediction of cladding life in waste package environments

    International Nuclear Information System (INIS)

    McCoy, J.K.; Doering, T.W.

    1994-01-01

    Fuel cladding can potentially provide longer containment or slower release of radionuclides from spent fuel after geologic disposal. To predict the amount of benefit that cladding can provide, we surveyed degradation modes and developed a model for creep rupture by diffusion-controlled cavity growth, the mechanism that several authors have concluded is the most important. In this mechanism, voids nucleate on the grain boundaries and grow by diffusion of vacancies along the grain boundaries to the voids. When a certain fraction of the grain boundary area is covered with voids, the material fails. An analytic expression for cladding lifetime is developed. Besides materials constants, the predicted lifetime depends on the temperature history, the hoop stress in the cladding, the spacing between void nuclei, and the micro-structure. The inclusion of microstructure is a significant new feature of the model; this feature is used to help avoid excessive conservatism. The model is applied in a sample calculation for disposal of spent fuel, and the practice of using temperature limits to evaluate repository designs is examined

  16. Life prediction study of reactor pressure vessel as essential technical foundation for plant life extension

    International Nuclear Information System (INIS)

    Nakajima, H.; Nakajima, N.; Kondo, T.

    1987-01-01

    The life of a LWR plant is determined essentially by the limit of reliable performance of the components which are difficult to replace without high economic and/or safety risks. Typical of such a component is the reactor pressure vessel (RPV). The engineering life of a RPV of a given quality of steel is considered to be a complex function of factors such as the resistance to fracture, which has deteriorated due to neutron irradiation and thermal aging, and generation of surface flaws by environmental effects such as corrosion and their growth under operational load that varies during steady state operation and transients. In an attempt to evaluate the engineering life of a RPV of a LWR, a preliminary survey was made by applying a set of knowledge accumulated primarily in the field of subcritical crack growth behavior of RPV steels in reactor water environments. The major conclusions drawn are: (1) the life of a RPV is dependent on the quality of steel used, particularly with respect to any minor impurities it contains. (2) The issue of plant life extension in RPV aspect is found to be optimistic for cases where the steels used satisfy a reasonable level of quality control. (3) The importance of providing sound scientific foundation is stressed for the implementation of a practicable life extension scheme: this can be established through intensified studies of flaw growth and fracture behaviours in well defined testings under reasonably simulated service conditions

  17. Fatigue Life Prediction of 2D Woven Ceramic-Matrix Composites at Room and Elevated Temperatures

    Science.gov (United States)

    Longbiao, Li

    2017-03-01

    In this paper, the fatigue life of 2D woven ceramic-matrix composites, i.e., SiC/SiC, SiC/Si-N-C, SiC/Si-B4C, and Nextel 610™/Aluminosilicate, at room and elevated temperatures has been predicted using the micromechanics approach. An effective coefficient of the fiber volume fraction along the loading direction (ECFL) was introduced to describe the fiber architecture of preforms. The Budiansky-Hutchinson-Evans shear-lag model was used to describe the microstress field of the damaged composite considering fibers failure. The statistical matrix multicracking model and fracture mechanics interface debonding criterion were used to determine the matrix crack spacing and interface debonded length. The interface shear stress and fibers strength degradation model and oxidation region propagation model have been adopted to analyze the fatigue and oxidation effects on fatigue life of the composite, which is controlled by interface frictional slip and diffusion of oxygen gas through matrix multicrackings. Under cyclic fatigue loading, the fibers broken fraction was determined by combining the interface/fiber oxidation model, interface wear model and fibers statistical failure model at elevated temperatures, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfy the Global Load Sharing (GLS) criterion. When the broken fibers fraction approaches to the critical value, the composites fatigue fractures. The fatigue life S- N curves of 2D SiC/SiC, SiC/Si-N-C, SiC/Si-B4C, and Nextel 610™/Aluminosilicate composites at room temperature and 800, 1000 and 1200 °C in air and steam have been predicted.

  18. Probabilistic Modeling and Simulation of Metal Fatigue Life Prediction

    National Research Council Canada - National Science Library

    Heffern, Thomas

    2002-01-01

    ...% FLE The work of this thesis was to investigate the probability distributions of test data taken for aluminum 7050-T745 1, and to attempt to develop a probability based model from the variation...

  19. Bayesian techniques for fatigue life prediction and for inference in linear time dependent PDEs

    KAUST Repository

    Scavino, Marco

    2016-01-08

    In this talk we introduce first the main characteristics of a systematic statistical approach to model calibration, model selection and model ranking when stress-life data are drawn from a collection of records of fatigue experiments. Focusing on Bayesian prediction assessment, we consider fatigue-limit models and random fatigue-limit models under different a priori assumptions. In the second part of the talk, we present a hierarchical Bayesian technique for the inference of the coefficients of time dependent linear PDEs, under the assumption that noisy measurements are available in both the interior of a domain of interest and from boundary conditions. We present a computational technique based on the marginalization of the contribution of the boundary parameters and apply it to inverse heat conduction problems.

  20. Spatio-temporal dynamics of growth and survival of Lesser Sandeel early life-stages in the North Sea: Predictions from a coupled individual-based and hydrodynamic-biogeochemical model

    DEFF Research Database (Denmark)

    Gurkan, Zeren; Christensen, Asbjørn; Maar, Marie

    2013-01-01

    Accounting for the individual variability and regional variations are important when predicting recruitment in fish species. Spatially explicit descriptions for recruitment in sandeels are necessary and sandeel growth and survival depend locally on zooplankton prey. We investigate the responses o...

  1. 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...

  2. A case study of remaining storage life prediction using stochastic filtering with the influence of condition monitoring

    International Nuclear Information System (INIS)

    Wang, Zhaoqiang; Hu, Changhua; Wang, Wenbin; Zhou, Zhijie; Si, Xiaosheng

    2014-01-01

    Some systems may spend most of their time in storage, but once needed, must be fully functional. Slow degradation occurs when the system is in storage, so to ensure the functionality of these systems, condition monitoring is usually conducted periodically to check the condition of the system. However, taking the condition monitoring data may require putting the system under real testing situation which may accelerate the degradation, and therefore, shorten the storage life of the system. This paper presents a case study of condition-based remaining storage life prediction for gyros in the inertial navigation system on the basis of the condition monitoring data and the influence of the condition monitoring data taking process. A stochastic-filtering-based degradation model is developed to incorporate both into the prediction of the remaining storage life distribution. This makes the predicted remaining storage life depend on not only the condition monitoring data but also the testing process of taking the condition monitoring data, which the existing prognostic techniques and algorithms did not consider. The presented model is fitted to the real condition monitoring data of gyros testing using the maximum likelihood estimation method for parameter estimation. Comparisons are made with the model without considering the process of taking the condition monitoring data, and the results clearly demonstrate the superiority of the newly proposed model

  3. Longitudinal Prediction of Quality-of-Life Scores and Locomotion in Individuals With Traumatic Spinal Cord Injury.

    Science.gov (United States)

    Hiremath, Shivayogi V; Hogaboom, Nathan S; Roscher, Melissa R; Worobey, Lynn A; Oyster, Michelle L; Boninger, Michael L

    2017-12-01

    To examine (1) differences in quality-of-life scores for groups based on transitions in locomotion status at 1, 5, and 10 years postdischarge in a sample of people with spinal cord injury (SCI); and (2) whether demographic factors and transitions in locomotion status can predict quality-of-life measures at these time points. Retrospective case study of the National SCI Database. Model SCI Systems Centers. Individuals with SCI (N=10,190) from 21 SCI Model Systems Centers, identified through the National SCI Model Systems Centers database between the years 1985 and 2012. Subjects had FIM (locomotion mode) data at discharge and at least 1 of the following: 1, 5, or 10 years postdischarge. Not applicable. FIM-locomotion mode; Severity of Depression Scale; Satisfaction With Life Scale; and Craig Handicap Assessment and Reporting Technique. Participants who transitioned from ambulation to wheelchair use reported lower participation and life satisfaction, and higher depression levels (P.05) or life satisfaction (P>.05) compared with those who transitioned from wheelchair to ambulation. Demographic factors and locomotion transitions predicted quality-of-life scores at all time points (P<.05). The results of this study indicate that transitioning from ambulation to wheelchair use can negatively impact psychosocial health 10 years after SCI. Clinicians should be aware of this when deciding on ambulation training. Further work to characterize who may be at risk for these transitions is needed. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

  4. Personality traits predicting quality of life and overall functioning in schizophrenia.

    Science.gov (United States)

    Ridgewell, Caitlin; Blackford, Jennifer Urbano; McHugo, Maureen; Heckers, Stephan

    2017-04-01

    Clinical symptoms and sociodemographic variables predict level of functioning and quality of life in patients with schizophrenia. However, few studies have examined the effect of personality traits on quality of life and overall functioning in schizophrenia. Personality traits are premorbid to illness and may predict the way patients experience schizophrenia. The aim of this study was to examine the individual and additive effects of two core personality traits-neuroticism and extraversion-on quality of life and functioning. Patients with schizophrenia-spectrum disorders (n=153) and healthy controls (n=125) completed personality and quality of life questionnaires. Global functioning was assessed during a clinician-administered structured interview. Neuroticism and extraversion scores were analyzed both as continuous variables and as categorical extremes (High versus Normal Neuroticism, Low versus Normal Extraversion). Quality of life was significantly associated with neuroticism, extraversion, and the neuroticism×diagnosis and extraversion×diagnosis interactions. For patients, a lower neuroticism score (in the normal range) was associated with quality of life scores comparable to controls; whereas high neuroticism scores in patients were associated with the lowest quality of life. For overall functioning, only diagnosis had a significant effect. Neuroticism modulates quality of life and may provide an important key to improving the life of patients with schizophrenia. Copyright © 2016 Elsevier B.V. All rights reserved.

  5. LCF life prediction for waspaloy in the creep-fatigue interaction regime

    International Nuclear Information System (INIS)

    Yeom, Jong Taek; Park, Nho Kwang

    2001-01-01

    This paper describes the empirical rule of strain rate modified linear accumulation of creep damage(SRM rule) for Low-Cycle Fatigue(LCF) life prediction of Waspaloy in the creep-fatigue interaction regime and Chaboche type unified viscoplastic model predicting the stress-strain response in various cyclic loading conditions. The comparison of the experimental data and the predictions for strain controlled LCF tests carried out for various strain ranges at 600 .deg. C and 650 .deg. C was made. Chaboche type unified viscoplastic model described efficiently the inelastic deformation behavior during LCF tests. Crack-initiation lifting method to predict the material life was investigated with Strain Rate Modification(SRM) rule. The application of SRM rule to LCF tests on Waspaloy indicated a good agreement between measured and predicted cycles to failure

  6. Factors predicting quality of life in older people with diabetes in Thailand

    Directory of Open Access Journals (Sweden)

    Tassana Choowattanapakorn

    2016-12-01

    Full Text Available The study aimed to investigate factors affecting the quality of life of older persons with diabetes. Data were collected on 345 persons from 5 regional hospitals in Thailand. The instruments measured characteristic, quality of life, resilience and selfcare behavior. Participants exhibited low-level physical and mental health quality of life ( x =45.78, 47.60; SD=8.963, 8.93. Resilience and self-care behavior showed a moderate level ( x=121.89, 38.2; SD=21.084, 7.363. Stepwise regression indicated that resilience, self-care behavior, age, education and gender were predictive of physical health quality of life. Mental health quality of life was found to be predicted by resilience, self-care behavior and marital status. We determined that resilience, personal characteristics, self-care behavior and demographic factors were predictive of quality of life among older diabetics. Health care professionals need to be aware of individual differences among older diabetics towards promoting better quality of life.

  7. Minimal important change (MIC) based on a predictive modeling approach was more precise than MIC based on ROC analysis

    NARCIS (Netherlands)

    Terluin, B.; Eekhout, I.; Terwee, C.B.; de Vet, H.C.W.

    2015-01-01

    Objectives To present a new method to estimate a "minimal important change" (MIC) of health-related quality of life (HRQOL) scales, based on predictive modeling, and to compare its performance with the MIC based on receiver operating characteristic (ROC) analysis. To illustrate how the new method

  8. Based on BP Neural Network Stock Prediction

    Science.gov (United States)

    Liu, Xiangwei; Ma, Xin

    2012-01-01

    The stock market has a high profit and high risk features, on the stock market analysis and prediction research has been paid attention to by people. Stock price trend is a complex nonlinear function, so the price has certain predictability. This article mainly with improved BP neural network (BPNN) to set up the stock market prediction model, and…

  9. Robustness: predicting the effects of life history perturbations on stage-structured population dynamics.

    Science.gov (United States)

    Hodgson, Dave; Townley, Stuart; McCarthy, Dominic

    2006-09-01

    Matrix-based models lie at the core of many applications across the physical, engineering and life sciences. In ecology, matrix models arise naturally via population projection matrices (PPM). The eigendata of PPMs provide detailed quantitative and qualitative information on the dynamic behaviour of model populations, especially their asymptotic rates of growth or decline. A fundamental task in modern ecology is to assess the effect that perturbations to life-cycle transition rates of individuals have on such eigendata. The prevailing assessment tools in ecological applications of PPMs are direct matrix simulations of eigendata and linearised extrapolations to the typically non-linear relationship between perturbation magnitude and the resulting matrix eigenvalues. In recent years, mathematical systems theory has developed an analytical framework, called 'Robustness Analysis and Robust Control', encompassing also algorithms and numerical tools. This framework provides a systematic and precise approach to studying perturbations and uncertainty in systems represented by matrices. Here we lay down the foundations and concepts for a 'robustness' inspired approach to predictive analyses in population ecology. We treat a number of application-specific perturbation problems and show how they can be formulated and analysed using these robustness methodologies.

  10. Comparison of LIFE-4 and TEMECH code predictions with TREAT transient test data

    International Nuclear Information System (INIS)

    Gneiting, B.C.; Bard, F.E.; Hunter, C.W.

    1984-09-01

    Transient tests in the TREAT reactor were performed on FFTF Reference design mixed-oxide fuel pins, most of which had received prior steady-state irradiation in the EBR-II reactor. These transient test results provide a data base for calibration and verification of fuel performance codes and for evaluation of processes that affect pin damage during transient events. This paper presents a comparison of the LIFE-4 and TEMECH fuel pin thermal/mechanical analysis codes with the results from 20 HEDL TREAT experiments, ten of which resulted in pin failure. Both the LIFE-4 and TEMECH codes provided an adequate representation of the thermal and mechanical data from the TREAT experiments. Also, a criterion for 50% probability of pin failure was developed for each code using an average cumulative damage fraction value calculated for the pins that failed. Both codes employ the two major cladding loading mechanisms of differential thermal expansion and central cavity pressurization which were demonstrated by the test results. However, a detailed evaluation of the code predictions shows that the two code systems weigh the loading mechanism differently to reach the same end points of the TREAT transient results

  11. TBCs for Gas Turbines under Thermomechanical Loadings: Failure Behaviour and Life Prediction

    Science.gov (United States)

    Beck, T.; Trunova, O.; Herzog, R.; Singheiser, L.

    2012-10-01

    The present contribution gives an overview about recent research on a thermal barrier coating (TBC) system consisted of (i) an intermetallic MCrAlY-alloy Bondcoat (BC) applied by vacuum plasma spraying (VPS) and (ii) an Yttria Stabilised Zirconia (YSZ) top coat air plasma sprayed (APS) at Forschungszentrum Juelich, Institute of Energy and Climate Research (IEK-1). The influence of high temperature dwell time, maximum and minimum temperature on crack growth kinetics during thermal cycling of such plasma sprayed TBCs is investigated using infrared pulse thermography (IT), acoustic emission (AE) analysis and scanning electron microscopy. Thermocyclic life in terms of accumulated time at maximum temperature decreases with increasing high temperature dwell time and increases with increasing minimum temperature. AE analysis proves that crack growth mainly occurs during cooling at temperatures below the ductile-to-brittle transition temperature of the BC. Superimposed mechanical load cycles accelerate delamination crack growth and, in case of sufficiently high mechanical loadings, result in premature fatigue failure of the substrate. A life prediction model based on TGO growth kinetics and a fracture mechanics approach has been developed which accounts for the influence of maximum and minimum temperature as well as of high temperature dwell time with good accuracy in an extremely wide parameter range.

  12. Study on creep damage and life prediction of threaded connections at high temperature

    Directory of Open Access Journals (Sweden)

    Qingmin Yu

    2016-01-01

    Full Text Available In this study, Kachanov–Rabotnov model and stress relaxation damage constitutive equations deduced from Kachanov–Rabotnov model were applied to analyze the creep damage and to predict life for threaded connection structure at high temperature with finite element method. The parameters of Kachanov–Rabotnov model were obtained by fitting the results of creep experiments for titanium alloy at 650°C. Based on the experimental and finite element analysis results for standard specimen, a creep failure criterion was established. Then the influences of the external tensile load on the creep damage and life, as well as the stress relaxation on the initial preload, were studied. The analysis of stress relaxation for bolt shows that the stress relaxation has a remarkable effect on the bolt preload. The preloads decrease to a determined value with creep time and remain almost unchanged later. When the determined value is less than the required preload acting on the bolt, the structure will fail due to insufficient preload caused by stress relaxation.

  13. Service Life Prediction of Wood Claddings by in-situ Measurement of Wood Moisture Content

    DEFF Research Database (Denmark)

    Engelund, Emil Tang; Lindegaard, Berit; Morsing, Niels

    2009-01-01

    of wood moisture are done by in-situ resistance moisture meters (Lindegaard and Morsing 2006). The aim is that the test should form the basis of evaluation of the maintenance requirements and the prediction of service life of the surface treatment and the wood/construction. At the moment 60 test racks...... to predict the service life of the construction in terms of maintenance period and the risk of biological degradation of the construction.......The Danish Technological Institute is in co-operation with industry partners running a project aiming at predicting the service life of different wood protecting systems. The project focuses on examining the moisture reducing effect of different protecting systems for timber claddings...

  14. VIEWS ON SUCCESS IN LIFE BASED GENDER

    Directory of Open Access Journals (Sweden)

    Adina Magdalena IORGA

    2014-12-01

    Full Text Available In order to study the characteristics of success in life we must consider the social construction of genders (male and female manifested in the interaction between the sexes. Social interpretation of biological sex leads to the identification of a set of behaviors particular to each sex, both in society and subsequently in private life as well as in the public eye. The research aims to identify the opinions and beliefs on the matter of students from the Veterinary Medicine University of Bucharest, their views on success in life, in the work place, in their study environment and in society as a whole, the characteristics of each gender, equality between women and men. The research findings reveal a specific social pattern determined by gender and residential environment.

  15. Weather, knowledge base and life-style

    Science.gov (United States)

    Bohle, Martin

    2015-04-01

    Why to main-stream curiosity for earth-science topics, thus to appraise these topics as of public interest? Namely, to influence practices how humankind's activities intersect the geosphere. How to main-stream that curiosity for earth-science topics? Namely, by weaving diverse concerns into common threads drawing on a wide range of perspectives: be it beauty or particularity of ordinary or special phenomena, evaluating hazards for or from mundane environments, or connecting the scholarly investigation with concerns of citizens at large; applying for threading traditional or modern media, arts or story-telling. Three examples: First "weather"; weather is a topic of primordial interest for most people: weather impacts on humans lives, be it for settlement, for food, for mobility, for hunting, for fishing, or for battle. It is the single earth-science topic that went "prime-time" since in the early 1950-ties the broadcasting of weather forecasts started and meteorologists present their work to the public, daily. Second "knowledge base"; earth-sciences are a relevant for modern societies' economy and value setting: earth-sciences provide insights into the evolution of live-bearing planets, the functioning of Earth's systems and the impact of humankind's activities on biogeochemical systems on Earth. These insights bear on production of goods, living conditions and individual well-being. Third "life-style"; citizen's urban culture prejudice their experiential connections: earth-sciences related phenomena are witnessed rarely, even most weather phenomena. In the past, traditional rural communities mediated their rich experiences through earth-centric story-telling. In course of the global urbanisation process this culture has given place to society-centric story-telling. Only recently anthropogenic global change triggered discussions on geoengineering, hazard mitigation, demographics, which interwoven with arts, linguistics and cultural histories offer a rich narrative

  16. Size matters: Installed maximal unit size predicts market life cycles of electricity generation technologies and systems

    International Nuclear Information System (INIS)

    Li, N.

    2008-01-01

    The electricity generation technologies and systems are complex and change in very dynamic fashions, with a multitude of energy sources and prime movers. Since an important concept in generator design is the 'economies of scale', we discover that the installed maximal unit size (capacity) of the generators is a key 'envelope-pushing' characteristic with logistical behaviors. The logistical wavelet analysis of the max unit sizes for different fuels and prime movers, and the cumulative capacities, reveals universal quantitative features in the aggregate evolution of the power industry. We extract the transition times of the max sizes (spanning 10-90% of the saturation limits) for different technologies and systems, and discover that the max size saturation in the 90-99% range precedes the saturation of cumulative capacities of the corresponding systems in the US. While these universal laws are still empirical, they give us a simple yet elegant framework to examine the evolution of the power industry and markets in predictive, not just descriptive, terms. Such laws give us a quantitative tool to spot trends and predict future development, invaluable in planning and resource allocation based on intrinsic technology and system market life cycles. (author)

  17. Early life stress predicts thalamic hyperconnectivity: A transdiagnostic study of global connectivity.

    Science.gov (United States)

    Philip, Noah S; Tyrka, Audrey R; Albright, Sarah E; Sweet, Lawrence H; Almeida, Jorge; Price, Lawrence H; Carpenter, Linda L

    2016-08-01

    Early life stress (ELS) is an established risk factor for psychiatric illness and is associated with altered functional connectivity within- and between intrinsic neural networks. The widespread nature of these disruptions suggests that broad imaging measures of neural connectivity, such as global based connectivity (GBC), may be particularly appropriate for studies of this population. GBC is designed to identify brain regions having maximal functional connectedness with the rest of the brain, and alterations in GBC may reflect a restriction or broadening of network synchronization. We evaluated whether ELS severity predicted GBC in a sample (N = 46) with a spectrum of ELS exposure. Participants included healthy controls without ELS, those with at least moderate ELS but without psychiatric disorders, and a group of patients with ELS- related psychiatric disorders. The spatial distribution of GBC peaked in regions of the salience and default mode networks, and ELS severity predicted increased GBC of the left thalamus (corrected p < 0.005, r = 0.498). Thalamic connectivity was subsequently evaluated and revealed reduced connectivity with the salience network, particularly the dorsal anterior cingulate cortex (corrected p < 0.005), only in the patient group. These findings support a model of disrupted thalamic connectivity in ELS and trauma-related negative affect states, and underscore the importance of a transdiagnostic, dimensional neuroimaging approach to understanding the sequelae of trauma exposure. Published by Elsevier Ltd.

  18. Remaining useful life prediction of degrading systems subjected to imperfect maintenance: Application to draught fans

    Science.gov (United States)

    Wang, Zhao-Qiang; Hu, Chang-Hua; Si, Xiao-Sheng; Zio, Enrico

    2018-02-01

    Current degradation modeling and remaining useful life prediction studies share a common assumption that the degrading systems are not maintained or maintained perfectly (i.e., to an as-good-as new state). This paper concerns the issues of how to model the degradation process and predict the remaining useful life of degrading systems subjected to imperfect maintenance activities, which can restore the health condition of a degrading system to any degradation level between as-good-as new and as-bad-as old. Toward this end, a nonlinear model driven by Wiener process is first proposed to characterize the degradation trajectory of the degrading system subjected to imperfect maintenance, where negative jumps are incorporated to quantify the influence of imperfect maintenance activities on the system's degradation. Then, the probability density function of the remaining useful life is derived analytically by a space-scale transformation, i.e., transforming the constructed degradation model with negative jumps crossing a constant threshold level to a Wiener process model crossing a random threshold level. To implement the proposed method, unknown parameters in the degradation model are estimated by the maximum likelihood estimation method. Finally, the proposed degradation modeling and remaining useful life prediction method are applied to a practical case of draught fans belonging to a kind of mechanical systems from steel mills. The results reveal that, for a degrading system subjected to imperfect maintenance, our proposed method can obtain more accurate remaining useful life predictions than those of the benchmark model in literature.

  19. Decline curve based models for predicting natural gas well performance

    Directory of Open Access Journals (Sweden)

    Arash Kamari

    2017-06-01

    Full Text Available The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN modelling strategy, least square support vector machine (LSSVM approach, adaptive neuro-fuzzy inference system (ANFIS, and decision tree (DT method for the prediction of cumulative gas production as well as initial decline rate multiplied by time as a function of the Arps' decline curve exponent and ratio of initial gas flow rate over total gas flow rate. It was concluded that the results obtained based on the models developed in current study are in satisfactory agreement with the actual gas well production data. Furthermore, the results of comparative study performed demonstrates that the LSSVM strategy is superior to the other models investigated for the prediction of both cumulative gas production, and initial decline rate multiplied by time.

  20. Arrhenius equation modeling for the shelf life prediction of tomato paste containing a natural preservative.

    Science.gov (United States)

    Jafari, Seid Mahdi; Ganje, Mohammad; Dehnad, Danial; Ghanbari, Vahid; Hajitabar, Javad

    2017-12-01

    The shelf life of tomato paste with microencapsulated olive leaf extract was compared with that of samples containing a commercial preservative by accelerated shelf life testing. Based on previous studies showing that olive leaf extract as a rich source of phenolic compounds can have antimicrobial properties, application of its encapsulated form to improve the storage stability of tomato paste is proposed here. Regarding total soluble solids, the control and the sample containing 1000 µg g -1 sodium benzoate had the lowest (Q 10  = 1.63) and highest (Q 10  = 1.88) sensitivity to temperature changes respectively; also, the microencapsulated sample containing 1000 µg g -1 encapsulated olive leaf extract (Q 10  = 1.83) followed the sample containing 1000 µg g -1 sodium benzoate in terms of the highest kinetic rates. In the case of consistency, the lowest and highest activation energies (E a ) corresponded to samples containing 1000 µg g -1 non-encapsulated olive leaf extract and 1000 µg g -1 microencapsulated olive leaf extract respectively. Interestingly, samples containing microencapsulated olive leaf extract could maintain the original quality of the tomato paste very well, while those with non-encapsulated olive leaf extract rated the worst performance (among all specimens) in terms of maintaining their quality indices for a long time period. Overall, the shelf life equation was able to predict the consistency index of all tomato paste samples during long-time storage with high precision. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  1. A New Approach for Reliability Life Prediction of Rail Vehicle Axle by Considering Vibration Measurement

    Directory of Open Access Journals (Sweden)

    Meral Bayraktar

    2014-01-01

    Full Text Available The effect of vibration on the axle has been considered. Vibration measurements at different speeds have been performed on the axle of a running rail vehicle to figure out displacement, acceleration, time, and frequency response. Based on the experimental works, equivalent stress has been used to find out life of the axles for 90% and 10% reliability. Calculated life values of the rail vehicle axle have been compared with the real life data and it is found that the life of a vehicle axle taking into account the vibration effects is in good agreement with the real life of the axle.

  2. Life Prediction/Reliability Data of Glass-Ceramic Material Determined for Radome Applications

    Science.gov (United States)

    Choi, Sung R.; Gyekenyesi, John P.

    2002-01-01

    Brittle materials, ceramics, are candidate materials for a variety of structural applications for a wide range of temperatures. However, the process of slow crack growth, occurring in any loading configuration, limits the service life of structural components. Therefore, it is important to accurately determine the slow crack growth parameters required for component life prediction using an appropriate test methodology. This test methodology also should be useful in determining the influence of component processing and composition variables on the slow crack growth behavior of newly developed or existing materials, thereby allowing the component processing and composition to be tailored and optimized to specific needs. Through the American Society for Testing and Materials (ASTM), the authors recently developed two test methods to determine the life prediction parameters of ceramics. The two test standards, ASTM 1368 for room temperature and ASTM C 1465 for elevated temperatures, were published in the 2001 Annual Book of ASTM Standards, Vol. 15.01. Briefly, the test method employs constant stress-rate (or dynamic fatigue) testing to determine flexural strengths as a function of the applied stress rate. The merit of this test method lies in its simplicity: strengths are measured in a routine manner in flexure at four or more applied stress rates with an appropriate number of test specimens at each applied stress rate. The slow crack growth parameters necessary for life prediction are then determined from a simple relationship between the strength and the applied stress rate. Extensive life prediction testing was conducted at the NASA Glenn Research Center using the developed ASTM C 1368 test method to determine the life prediction parameters of a glass-ceramic material that the Navy will use for radome applications.

  3. Prediction of mortality based on facial characteristics

    Directory of Open Access Journals (Sweden)

    Arnaud Delorme

    2016-05-01

    Full Text Available Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail. Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance and warrants further investigation.

  4. Infants Generate Goal-Based Action Predictions

    Science.gov (United States)

    Cannon, Erin N.; Woodward, Amanda L.

    2012-01-01

    Predicting the actions of others is critical to smooth social interactions. Prior work suggests that both understanding and anticipation of goal-directed actions appears early in development. In this study, on-line goal prediction was tested explicitly using an adaptation of Woodward's (1998) paradigm for an eye-tracking task. Twenty 11-month-olds…

  5. Multi-Axial Damage Index and Accumulation Model for Predicting Fatigue Life of CMC Materials, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The fatigue life of CMCs must be well characterized for the safe and reliable use of these materials as integrated TPS components. Existing fatigue life prediction...

  6. COPD in primary care: Towards simple prediction of quality of life, exacerbations and mortality

    NARCIS (Netherlands)

    Siebeling, L.

    2014-01-01

    We found that previous health-related quality of life (HRQL) was the best predictor in our models to predict COPD-specific HRQL in primary care COPD patients. Asking patients explicitly about dyspnoea, fatigue, depression and how they cope with COPD provides additional important information about

  7. The Role of Life Satisfaction and Parenting Styles in Predicting Delinquent Behaviors among High School Students

    Science.gov (United States)

    Onder, Fulya Cenkseven; Yilmaz, Yasin

    2012-01-01

    The purpose of this study is to determine whether the parenting styles and life satisfaction predict delinquent behaviors frequently or not. Firstly the data were collected from 471 girls and 410 boys, a total of 881 high school students. Then the research was carried out with 502 students showing low (n = 262, 52.2%) and high level of delinquent…

  8. The Predictive Adaptive Response: Modeling the Life-History Evolution of the Butterfly

    NARCIS (Netherlands)

    Heuvel, van den J.; Saastamoinen, M.; Brakefield, P.M.; Kirkwood, T.B.; Zwaan, B.J.; Shanley, D.P.

    2013-01-01

    A predictive adaptive response (PAR) is a type of developmental plasticity where the response to an environmental cue is not immediately advantageous but instead is later in life. The PAR is a way for organisms to maximize fitness in varying environments. Insects living in seasonal environments are

  9. Numerical Analysis of Rolling Contact Fatigue Crack Initiation and Fatigue Life Prediction of the Railway Crossing

    NARCIS (Netherlands)

    Xin, L.; Markine, V.L.; Shevtsov, I.

    2015-01-01

    The procedure for analysing rolling contact fatigue crack initiation and fatigue life prediction of the railway turnout crossing is developed. A three-dimensional finite element (FE) model is used to obtain stress and strain results, considering the dynamic effects of wheel-crossing rolling contact.

  10. The Level of Quality of Work Life to Predict Work Alienation

    Science.gov (United States)

    Erdem, Mustafa

    2014-01-01

    The current research aims to determine the level of elementary school teachers' quality of work life (QWL) to predict work alienation. The study was designed using the relational survey model. The research population consisted of 1096 teachers employed at 25 elementary schools within the city of Van in the academic year 2010- 2011, and 346…

  11. Failure analysis and life prediction of a large, complex plate fin heat exchanger

    CSIR Research Space (South Africa)

    Carter, P

    1996-03-01

    Full Text Available Failure analysis and life prediction of a large, complex fin plate heat exchanger required metallurgical analysis, at the beginning of 1993, inter-stream leaks were found in two aluminium plate fin heat exchangers in parallel operation at a...

  12. The Roles of Life Satisfaction, Teaching Efficacy, and Self-Esteem in Predicting Teachers' Job Satisfaction

    Science.gov (United States)

    Çevik, Gülsen Büyüksahin

    2017-01-01

    The current research aims to find out the extent to which high school teachers' life satisfaction, teaching efficacy, and self-esteem predict their job satisfaction. Research participants included a total of 358 teachers (age = 38.82; Ss = 6.73; range, 22-58), 222 males (62%) and 136 females (38%), employed in 21 public high schools in the city…

  13. Do illness perceptions predict attendance at cardiac rehabilitation and quality of life following myocardial infarction?

    Science.gov (United States)

    French, David P; Lewin, Robert J P; Watson, Nina; Thompson, David R

    2005-11-01

    The aim of this study was to examine the extent to which illness perceptions predict attendance at cardiac rehabilitation and quality of life following myocardial infarction (MI). The illness perceptions of 194 MI patients were assessed whilst the patients were still in hospital following an MI. The mean age was 63.3 years (S.D. = 10.6), and 142 of the patients were men. Cardiac rehabilitation attendance and quality of life were assessed via a postal questionnaire 6 months later. In contrast to previous work reported in this area, illness perceptions were not significantly associated with attendance at cardiac rehabilitation. Illness perceptions measured within 24 h of an acute MI were predictive of quality of life 6 months later. Previous reports may have overestimated the extent to which illness perceptions predict attendance at cardiac rehabilitation. The relationship between illness perceptions and quality of life at 6 months suggests that interventions to alter illness perceptions, especially perceptions of consequences, may be useful in improving health-related quality of life (HRQoL) following an MI.

  14. Validation of a pediatric bedside tool to predict time to death after withdrawal of life support.

    Science.gov (United States)

    Das, Ashima; Anderson, Ingrid M; Speicher, David G; Speicher, Richard H; Shein, Steven L; Rotta, Alexandre T

    2016-02-08

    To evaluate the accuracy of a tool developed to predict timing of death following withdrawal of life support in children. Pertinent variables for all pediatric deaths (age ≤ 21 years) from 1/2009 to 6/2014 in our pediatric intensive care unit (PICU) were extracted through a detailed review of the medical records. As originally described, a recently developed tool that predicts timing of death in children following withdrawal of life support (dallas predictor tool [DPT]) was used to calculate individual scores for each patient. Individual scores were calculated for prediction of death within 30 min (DPT30) and within 60 min (DPT60). For various resulting DPT30 and DPT60 scores, sensitivity, specificity and area under the receiver operating characteristic curve were calculated. There were 8829 PICU admissions resulting in 132 (1.5%) deaths. Death followed withdrawal of life support in 70 patients (53%). After excluding subjects with insufficient data to calculate DPT scores, 62 subjects were analyzed. Average age of patients was 5.3 years (SD: 6.9), median time to death after withdrawal of life support was 25 min (range; 7 min to 16 h 54 min). Respiratory failure, shock and sepsis were the most common diagnoses. Thirty-seven patients (59.6%) died within 30 min of withdrawal of life support and 52 (83.8%) died within 60 min. DPT30 scores ranged from -17 to 16. A DPT30 score ≥ -3 was most predictive of death within that time period, with sensitivity = 0.76, specificity = 0.52, AUC = 0.69 and an overall classification accuracy = 66.1%. DPT60 scores ranged from -21 to 28. A DPT60 score ≥ -9 was most predictive of death within that time period, with sensitivity = 0.75, specificity = 0.80, AUC = 0.85 and an overall classification accuracy = 75.8%. In this external cohort, the DPT is clinically relevant in predicting time from withdrawal of life support to death. In our patients, the DPT is more useful in predicting death within 60 min of withdrawal of life support

  15. Towards a Life Cycle Based Chemical Alternative Assessment (LCAA)

    DEFF Research Database (Denmark)

    Jolliet, O.; Huang, L.; Overcash, Michael

    2017-01-01

    There is a need for an operational quantitative screening-level assessment of alternatives, that is life-cycle based and able to serve both Life cycle Assessment (LCA and chemical alternatives assessment (CAA). This presentation therefore aims to develop and illustrate a new approach called “Life...... Cycle Based Chemical Alternative Assessment (LCAA)” that will quantify exposure and life cycle impacts consistently and efficiently over the main life cycle stages. The new LCAA approach is illustrated though a proof-of-concept case study of alternative plasticizers in vinyl flooring. The proposed LCAA...... ingredient in the product, first-order inter-compartmental transfer fractions and a matrix approach to determine Product Intake Fractions, and c) toxicity-related outcomes are compared with other life cycle impacts to evaluate the relevance of different impact categories for different consumer product...

  16. Protein structure based prediction of catalytic residues

    Science.gov (United States)

    2013-01-01

    Background Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. Results We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. Conclusions We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific

  17. Predicting time to death after withdrawal of life-sustaining therapy.

    Science.gov (United States)

    Munshi, Laveena; Dhanani, Sonny; Shemie, Sam D; Hornby, Laura; Gore, Genevieve; Shahin, Jason

    2015-06-01

    Predicting time to death following the withdrawal of life-sustaining therapy is difficult. Accurate predictions may better prepare families and improve the process of donation after circulatory death. We systematically reviewed any predictive factors for time to death after withdrawal of life support therapy. Fifteen observational studies met our inclusion criteria. The primary outcome was time to death, which was evaluated to be within 60 min in the majority of studies (13/15). Additional time endpoints evaluated included time to death within 30, 120 min, and 10 h, respectively. While most studies evaluated risk factors associated with time to death, a few derived or validated prediction tools. Consistent predictors of time to death that were identified in five or more studies included the following risk factors: controlled ventilation, oxygenation, vasopressor use, Glasgow Coma Scale/Score, and brain stem reflexes. Seven unique prediction tools were derived, validated, or both across some of the studies. These tools, at best, had only moderate sensitivity to predicting the time to death. Simultaneous withdrawal of all support and physician opinion were only evaluated in more recent studies and demonstrated promising predictor capabilities. While the risk factors controlled ventilation, oxygenation, vasopressors, level of consciousness, and brainstem reflexes have been most consistently found to be associated with time to death, the addition of novel predictors, such as physician opinion and simultaneous withdrawal of all support, warrant further investigation. The currently existing prediction tools are not highly sensitive. A more accurate and generalizable tool is needed to inform end-of-life care and enhance the predictions of donation after circulatory death eligibility.

  18. Functional Independence in Late-Life: Maintaining Physical Functioning in Older Adulthood Predicts Daily Life Function after Age 80.

    Science.gov (United States)

    Vaughan, Leslie; Leng, Xiaoyan; La Monte, Michael J; Tindle, Hilary A; Cochrane, Barbara B; Shumaker, Sally A

    2016-03-01

    We examined physical functioning (PF) trajectories (maintaining, slowly declining, and rapidly declining) spanning 15 years in older women aged 65-80 and protective factors that predicted better current levels and less decline in functional independence outcomes after age 80. Women's Health Initiative extension participants who met criteria (enrolled in either the clinical trial or observational study cohort, >80 years at the data release cutoff, PF survey data from initial enrollment to age 80, and functional independence survey data after age 80) were included in these analyses (mean [SD] age = 84.0 [1.4] years; N = 10,478). PF was measured with the SF-36 (mean = 4.9 occasions). Functional independence was measured by self-reported level of dependence in basic and instrumental activities of daily living (ADLs and IADLs) (mean = 3.4 and 3.3 occasions). Maintaining consistent PF in older adulthood extends functional independence in ADL and IADL in late-life. Protective factors shared by ADL and IADL include maintaining PF over time, self-reported excellent or very good health, no history of hip fracture after age 55, and no history of cardiovascular disease. Better IADL function is uniquely predicted by a body mass index less than 25 and no depression. Less ADL and IADL decline is predicted by better self-reported health, and less IADL decline is uniquely predicted by having no history of hip fracture after age 55. Maintaining or improving PF and preventing injury and disease in older adulthood (ages 65-80) has far-reaching implications for improving late-life (after age 80) functional independence. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Distance saturation product predicts health-related quality of life among sarcoidosis patients.

    Science.gov (United States)

    Bourbonnais, Julie M; Malaisamy, Subramanian; Dalal, Bhavinkumar D; Samarakoon, Priyan C; Parikh, Swapna R; Samavati, Lobelia

    2012-06-13

    Sarcoidosis is a chronic disease with different phenotypic manifestations. Health-related quality of life is an important aspect in sarcoidosis, yet difficult to measure. The objective of this study was to identify clinical markers predictive of poor quality of life in sarcoidosis patients that can be followed over time and targeted for intervention. We assessed the quality of life of 162 patients with confirmed sarcoidosis in a prospective, cross-sectional study using the Sarcoidosis Health Questionnaire (SHQ) and Short Form-36 Health Survey (SF-36). We evaluated the validity of these questionnaires and sought to identify variables that would best explain the performance scores of the patients. On multivariate regression analyses, the very best composite model to predict total scores from both surveys was a model containing the distance-saturation product and Borg Dyspnea Scale score at the end of a 6-min walk test. This model could better predict SF-36 scores (R² = 0.33) than SHQ scores (R² = 0.24). Substitution of distanced walked in 6 min for the distance-saturation product in this model resulted in a lesser ability to predict both scores (R² = 0.26 for SF-36; R² = 0.22 for SHQ). Both the SHQ and SF-36 surveys are valuable tools in the assessment of health-related quality of life in sarcoidosis patients. The best model to predict quality of life among these patients, as determined by regression analyses, included the distance-saturation product and Borg score after the 6-min walk test. Both variables represent easily obtainable clinical parameters that can be followed over time and targeted for intervention.

  20. Statistical-Based Forecasting of Avalanche Prediction

    OpenAIRE

    K. Srinivasan; Girish Semwal; T. Sunil

    1999-01-01

    This paper describes the study carried out to predict few meteorological parameters of the nextday using the observed parameters of previous day through statistical methods. Multiple linear regression model was formulated for a hill station, Patsio, situated between Manali and Leh, for two winter months(December and January) separately. Twelve meteorological parameters were predicted using 18 predictorsob served on the previous day. Ten years data has been used for the computation of regressi...

  1. Computational models for residual creep life prediction of power plant components

    International Nuclear Information System (INIS)

    Grewal, G.S.; Singh, A.K.; Ramamoortry, M.

    2006-01-01

    All high temperature - high pressure power plant components are prone to irreversible visco-plastic deformation by the phenomenon of creep. The steady state creep response as well as the total creep life of a material is related to the operational component temperature through, respectively, the exponential and inverse exponential relationships. Minor increases in the component temperature can thus have serious consequences as far as the creep life and dimensional stability of a plant component are concerned. In high temperature steam tubing in power plants, one mechanism by which a significant temperature rise can occur is by the growth of a thermally insulating oxide film on its steam side surface. In the present paper, an elegantly simple and computationally efficient technique is presented for predicting the residual creep life of steel components subjected to continual steam side oxide film growth. Similarly, fabrication of high temperature power plant components involves extensive use of welding as the fabrication process of choice. Naturally, issues related to the creep life of weldments have to be seriously addressed for safe and continual operation of the welded plant component. Unfortunately, a typical weldment in an engineering structure is a zone of complex microstructural gradation comprising of a number of distinct sub-zones with distinct meso-scale and micro-scale morphology of the phases and (even) chemistry and its creep life prediction presents considerable challenges. The present paper presents a stochastic algorithm, which can be' used for developing experimental creep-cavitation intensity versus residual life correlations for welded structures. Apart from estimates of the residual life in a mean field sense, the model can be used for predicting the reliability of the plant component in a rigorous probabilistic setting. (author)

  2. Prediction-based dynamic load-sharing heuristics

    Science.gov (United States)

    Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

    1993-01-01

    The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

  3. A new simplified allometric approach for predicting the biological half-life of radionuclides in reptiles

    International Nuclear Information System (INIS)

    Beresford, N.A.; Wood, M.D.

    2014-01-01

    A major source of uncertainty in the estimation of radiation dose to wildlife is the prediction of internal radionuclide activity concentrations. Allometric (mass-dependent) relationships describing biological half-life (T 1/2b ) of radionuclides in organisms can be used to predict organism activity concentrations. The establishment of allometric expressions requires experimental data which are often lacking. An approach to predict the T 1/2b in homeothermic vertebrates has recently been proposed. In this paper we have adapted this to be applicable to reptiles. For Cs, Ra and Sr, over a mass range of 0.02–1.5 kg, resultant predictions were generally within a factor of 6 of reported values demonstrating that the approach can be used when measured T 1/2b data are lacking. However, the effect of mass on reptilian radionuclide T 1/2b is minimal. If sufficient measured data are available for a given radionuclide then it is likely that these would give a reasonable estimate of T 1/2b in any reptile species. - Highlights: • An allometric approach to predict radionuclide T 1/2b values in reptiles is derived. • Predictions are generally within a factor of six of measured values. • Radionuclide biological half-life is in-effect mass independent

  4. Physical activity predicts quality of life and happiness in children and adolescents with cerebral palsy.

    Science.gov (United States)

    Maher, Carol Ann; Toohey, Monica; Ferguson, Monika

    2016-01-01

    To examine the associations between physical activity, health-related quality of life and happiness in young people with cerebral palsy. A total of 70 young people with cerebral palsy (45 males, 25 females; mean age 13 years 11 months, SD 2 years 0 month) took part in a cross-sectional, descriptive postal survey assessing physical activity (Physical Activity Questionnaire for Adolescents), functional ability (Gross Motor Function Classification System), quality of life (Pediatric Quality of Life Inventory 4.0) and happiness (single Likert-scale item). Relationships between physical activity, quality of life and happiness were examined using backward stepwise linear regression. Physical activity significantly predicted physical quality of life (R(2 )= 0.64, β = 6.12, p = 0.02), social quality of life (R(2 )= 0.28, β = 9.27, p happiness (R(2 )= 0.08, β = 0.9, p = 0.04). Physical activity was not associated with emotional or school quality of life. This study found a positive association between physical activity, social and physical quality of life, and happiness in young people with cerebral palsy. Findings underscore the potential benefits of physical activity for the wellbeing of young people with cerebral palsy, in addition to its well-recognised physical and health benefits. Physical activity is a key predictor of quality of life and happiness in young people with cerebral palsy. Physical activity is widely recognised as having physical health benefits for young people with cerebral palsy; however, this study also highlights that it may have important benefits for wellbeing, quality of life and happiness. This emphasises the need for clinical services and intervention studies aimed specifically at increasing physical activity amongst children and adolescents with cerebral palsy.

  5. Measurement techniques and instruments suitable for life-prediction testing of photovoltaic arrays. Interim report

    Energy Technology Data Exchange (ETDEWEB)

    Noel, G.T.; Sliemers, F.A.; Deringer, G.C.; Wood, V.E.; Wilkes, K.E.; Gaines, G.B.; Carmichael, D.C.

    1978-01-15

    The validation of a service life of 20 years for low-cost photovoltaic arrays must be accomplished through accelerated life-prediction tests. A methodology for such tests has been developed in a preceding study. The results discussed consist of the initial identification and assessment of all known measurement techniques and instruments that might be used in these life-prediction tests. Array failure modes, relevant materials property changes, and primary degradation mechanisms are discussed as a prerequisite to identifying suitable measurement techniques and instruments. Candidate techniques and instruments are identified on the basis of extensive reviews of published and unpublished information. These methods are organized in six measurement categories--chemical, electrical, optical, thermal, mechanical, and ''other physicals''. Using specified evaluation criteria, the most promising techniques and instruments for use in life-prediction tests of arrays are then selected. These recommended techniques and their characteristics are described. Recommendations are made regarding establishment of the adequacy, particularly with respect to precision, of the more fully developed techniques for this application, and regarding the experimental evaluation of promising developmental techniques. Measurement needs not satisfied by presently available techniques/instruments are also identified.

  6. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  7. Does life satisfaction predict five-year mortality in community-living older adults?

    Science.gov (United States)

    St John, Philip D; Mackenzie, Corey; Menec, Verena

    2015-01-01

    Depression and depressive symptoms predict death, but it is less clear if more general measures of life satisfaction (LS) predict death. Our objectives were to determine: (1) if LS predicts mortality over a five-year period in community-living older adults; and (2) which aspects of LS predict death. 1751 adults over the age of 65 who were living in the community were sampled from a representative population sampling frame in 1991/1992 and followed five years later. Age, gender, and education were self-reported. An index of multimorbidity and the Older American Resource Survey measured health and functional status, and the Terrible-Delightful Scale assessed overall LS as well as satisfaction with: health, finances, family, friends, housing, recreation, self-esteem, religion, and transportation. Cox proportional hazards models examined the influence of LS on time to death. 417 participants died during the five-year study period. Overall LS and all aspects of LS except finances, religion, and self-esteem predicted death in unadjusted analyses. In fully adjusted analyses, LS with health, housing, and recreation predicted death. Other aspects of LS did not predict death after accounting for functional status and multimorbidity. LS predicted death, but certain aspects of LS are more strongly associated with death. The effect of LS is complex and may be mediated or confounded by health and functional status. It is important to consider different domains of LS when considering the impact of this important emotional indicator on mortality among older adults.

  8. Menopausal symptoms: do life events predict severity of symptoms in peri- and post-menopause?

    Science.gov (United States)

    Pimenta, Filipa; Leal, Isabel; Maroco, João; Ramos, Catarina

    2012-08-01

    Hormonal changes during menopausal transition are linked to physical and psychological symptoms' emergence. This study aims to explore if life events predict menopausal symptoms. This cross-sectional research encompasses a community sample of 992 women who answered to socio-demographic, health, menopause-related and lifestyle questionnaires; menopausal symptoms and life events were assessed with validated instruments. Structural equation modeling was used to build a causal model. Menopausal status predicted only three symptoms: skin/facial hair changes (β=.136; p=.020), sexual (β=.157; p=.004) and, marginally, vasomotor symptoms (β=.094; p=.054). Life events predicted depressive mood (β=-.391; p=.002), anxiety (β=-.271; p=.003), perceived cognitive impairment (β=-.295; p=.003), body shape changes (β=-.136; p=.031), aches/pain (β=-.212; p=.007), skin/facial hair changes (β=-.171; p=.021), numbness (β=-.169; p=.015), perceived loss of control (β=-.234; p=.008), mouth, nails and hair changes (β=-.290; p=.004), vasomotor (β=-.113; p=.044) and sexual symptoms (β=-.208; p=.009). Although women in peri- and post-menopausal manifested higher symptoms' severity than their pre-menopausal counterparts, only three of the menopausal symptoms assessed were predicted by menopausal status. Since the vast majority of menopausal symptoms' severity was significantly influenced by the way women perceived their recent life events, it is concluded that the symptomatology exacerbation, in peri- and post-menopausal women, might be due to life conditions and events, rather than hormonal changes (nonetheless, the inverse influence should be investigated in future studies). Therefore, these should be accounted for in menopause-related clinical and research settings. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  9. Prediction of inelastic behavior and creep-fatigue life of perforated plates

    International Nuclear Information System (INIS)

    Igari, Toshihide; Yamauchi, Masafumi; Nomura, Shinichi.

    1992-01-01

    Prediction methods of macroscopic and local stress-strain behaviors of perforated plates in plastic and creep regime are proposed in this paper, and are applied to the creep-fatigue life prediction of perforated plates. Both equivalent-solid-plate properties corresponding to the macroscopic behavior and the stress-strain concentration around a hole were obtained by assuming the analogy between plasticity and creep and also by extending the authors' proposal in creep condition. The perforated plates which were made of Hastelloy XR were subjected to the strain-controlled cyclic test at 950degC in air in order to experimentally obtain the macroscopic behavior such as the cyclic stress-strain curve and creep-fatigue life around a hole. The results obtained are summarized as follows. (1) The macroscopic behavior of perforated plates including cyclic stress-strain behavior and relaxation is predictable by using the proposed method in this paper. (2) The creep-fatigue life around a hole can be predicted by using the proposed method for stress-strain concentration around a hole. (author)

  10. Practical life log video indexing based on content and context

    Science.gov (United States)

    Tancharoen, Datchakorn; Yamasaki, Toshihiko; Aizawa, Kiyoharu

    2006-01-01

    Today, multimedia information has gained an important role in daily life and people can use imaging devices to capture their visual experiences. In this paper, we present our personal Life Log system to record personal experiences in form of wearable video and environmental data; in addition, an efficient retrieval system is demonstrated to recall the desirable media. We summarize the practical video indexing techniques based on Life Log content and context to detect talking scenes by using audio/visual cues and semantic key frames from GPS data. Voice annotation is also demonstrated as a practical indexing method. Moreover, we apply body media sensors to record continuous life style and use body media data to index the semantic key frames. In the experiments, we demonstrated various video indexing results which provided their semantic contents and showed Life Log visualizations to examine personal life effectively.

  11. Predicting quality of life in pediatric asthma: the role of emotional competence and personality.

    Science.gov (United States)

    Lahaye, Magali; Van Broeck, Nady; Bodart, Eddy; Luminet, Olivier

    2013-05-01

    The present study examined the predictive value of emotional competence and the five-factor model of personality on the quality of life of children with asthma. Participants were 90 children (M age = 11.73, SD = 2.60) having controlled and partly controlled asthma, undergoing everyday treatment. Children filled in questionnaires assessing emotional competence and quality of life. Parents completed questionnaires assessing the personality of their child. Results showed that two emotional competences, bodily awareness and verbal sharing of emotions, were related to the quality of life of children with asthma. Moreover, one personality trait, benevolence, was associated with children's quality of life. Regression analyses showed that the predictive value of these three dimensions remained significant over and above asthma control and socio-demographic variables frequently associated with the quality of life of children with asthma (age, gender, and educational level of parents). These findings emphasize the importance of alerting the clinician who works with children with asthma to observe and assess the child's expression of emotions, attention to bodily sensations, and benevolence.

  12. Life Predicted in a Probabilistic Design Space for Brittle Materials With Transient Loads

    Science.gov (United States)

    Nemeth, Noel N.; Palfi, Tamas; Reh, Stefan

    2005-01-01

    Analytical techniques have progressively become more sophisticated, and now we can consider the probabilistic nature of the entire space of random input variables on the lifetime reliability of brittle structures. This was demonstrated with NASA s CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code combined with the commercially available ANSYS/Probabilistic Design System (ANSYS/PDS), a probabilistic analysis tool that is an integral part of the ANSYS finite-element analysis program. ANSYS/PDS allows probabilistic loads, component geometry, and material properties to be considered in the finite-element analysis. CARES/Life predicts the time dependent probability of failure of brittle material structures under generalized thermomechanical loading--such as that found in a turbine engine hot-section. Glenn researchers coupled ANSYS/PDS with CARES/Life to assess the effects of the stochastic variables of component geometry, loading, and material properties on the predicted life of the component for fully transient thermomechanical loading and cyclic loading.

  13. Early-life exposures predicting onset and resolution of childhood overweight or obesity.

    Science.gov (United States)

    Kerr, Jessica A; Long, Catherine; Clifford, Susan A; Muller, Joshua; Gillespie, Alanna N; Donath, Susan; Wake, Melissa

    2017-10-01

    To determine which of multiple early-life exposures predict onset or resolution of overweight/obesity during a 9-year period. Design : longitudinal cohort from three harmonised community-based cohorts enriched for overweight and obesity. Early-life exposures : child-gestational age; delivery; birth weight; breast feeding; solids introduction; baseline body mass index (BMI); waist circumference; diet; activity; global, physical and psychosocial health. Mother-baseline BMI; education; age; neighbourhood disadvantage; concern for child's weight. Outcome : change in BMI category. Analyses : adjusted logistic regression. On average, the 363 children (57% retention) were 6 and 15 years old at baseline and follow-up. Children were classified as 'never' overweight/obese (38%), 'resolving' overweight/obese (15%), 'becoming' overweight/obese (8%) or 'always' overweight/obese (39%). Compared with 'never overweight/obese' children, odds of 'becoming overweight/obese' were greater with higher child (OR 2.33, 95% CI 1.02 to 5.29) and maternal BMI (OR 1.18, CI 1.07 to 1.31), and lower with higher maternal education (OR 0.09, CI 0.02 to 0.34). Compared with 'always overweight/obese' children, odds of 'resolving overweight/obese' were lower with higher maternal BMI (OR 0.87, CI 0.78 to 0.97), and higher with better child physical health (OR 1.06, CI 1.02 to 1.10) and higher maternal age (OR 1.11, CI 1.01 to 1.22) and education (OR 4.07, CI 1.02 to 16.19). Readily available baseline information (child/maternal BMI, maternal age, education and child health) were the strongest predictors of both onset and resolution of overweight/obesity between the primary school and adolescent years. Perinatal, breastfeeding and lifestyle exposures were not strongly predictive. Results could stimulate development of algorithms identifying children most in need of targeted prevention or treatment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under

  14. Model for Predicting Traffic Signs Functional Service Life – The Republic of Croatia Case Study

    Directory of Open Access Journals (Sweden)

    Dario Babić

    2017-06-01

    Full Text Available Traffic signs are the basic elements of communication between the relevant road authorities and road users. They manage, regulate, inform and warn road users to ensure their safe movement throughout transport networks. Traffic signs must be timely visible to all traffic participants in all weather and traffic conditions in order to fulfil their function, which means they must have satisfactory retroreflection properties. This paper presents a research of the deterioration of traffic signs retroreflection. The aim of this article is to develop models that will effectively enable predicting the retroreflection of traffic signs and thus optimize the maintenance activities and replacement of road signs to increase road safety. The research included measurements of retroreflection of retroreflective material Classes I and II (white, red and blue colour and Class III (red and yellow colour. Based on the collected data from the City of Zagreb (Republic of Croatia, the authors developed the models to estimate the functional service life of certain colours and materials used to make traffic signs. Considering that the average coefficient of determination for all the models is between 0.55-0.60, they present an effective tool in the traffic sign maintenance system.

  15. Activity Prediction: A Twitter-based Exploration

    NARCIS (Netherlands)

    Weerkamp, W.; de Rijke, M.

    2012-01-01

    Social media platforms allow users to share their messages with everyone else. In microblogs, e.g., Twitter, people mostly report on what they did, they talk about current activities, and mention things they plan to do in the near future. In this paper, we propose the task of activity prediction,

  16. Fatigue Life Prediction of Multi Leaf Spring used in the Suspension System of Light Commercial Vehicle

    OpenAIRE

    V.K.Aher; R.A.Gujar; J.P.Wagh; P.M.Sonawane

    2012-01-01

    The Leaf spring is widely used in automobiles and one of the components of suspension system. It needs to have high fatigue life. As a general rule, the leaf spring is regarded as a safety component as failure could lead to severe accidents. The purpose of this paper is to predict the fatigue life of steel leaf spring along with analytical stress and deflection calculations. This present work describes static and fatigue analysis of a steel leaf spring of a light commercial vehicle (LCV). Th...

  17. Residual Stress Estimation and Fatigue Life Prediction of an Autofrettaged Pressure Vessel

    Energy Technology Data Exchange (ETDEWEB)

    Song, Kyung Jin; Kim, Eun Kyum; Koh, Seung Kee [Kunsan Nat’l Univ., Kunsan (Korea, Republic of)

    2017-09-15

    Fatigue failure of an autofrettaged pressure vessel with a groove at the outside surface occurs owing to the fatigue crack initiation and propagation at the groove root. In order to predict the fatigue life of the autofrettaged pressure vessel, residual stresses in the autofrettaged pressure vessel were evaluated using the finite element method, and the fatigue properties of the pressure vessel steel were obtained from the fatigue tests. Fatigue life of a pressure vessel obtained through summation of the crack initiation and propagation lives was calculated to be 2,598 cycles for an 80% autofrettaged pressure vessel subjected to a pulsating internal pressure of 424 MPa.

  18. Life prediction methodology for ceramic components of advanced vehicular heat engines: Volume 1. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Khandelwal, P.K.; Provenzano, N.J.; Schneider, W.E. [Allison Engine Co., Indianapolis, IN (United States)

    1996-02-01

    One of the major challenges involved in the use of ceramic materials is ensuring adequate strength and durability. This activity has developed methodology which can be used during the design phase to predict the structural behavior of ceramic components. The effort involved the characterization of injection molded and hot isostatic pressed (HIPed) PY-6 silicon nitride, the development of nondestructive evaluation (NDE) technology, and the development of analytical life prediction methodology. Four failure modes are addressed: fast fracture, slow crack growth, creep, and oxidation. The techniques deal with failures initiating at the surface as well as internal to the component. The life prediction methodology for fast fracture and slow crack growth have been verified using a variety of confirmatory tests. The verification tests were conducted at room and elevated temperatures up to a maximum of 1371 {degrees}C. The tests involved (1) flat circular disks subjected to bending stresses and (2) high speed rotating spin disks. Reasonable correlation was achieved for a variety of test conditions and failure mechanisms. The predictions associated with surface failures proved to be optimistic, requiring re-evaluation of the components` initial fast fracture strengths. Correlation was achieved for the spin disks which failed in fast fracture from internal flaws. Time dependent elevated temperature slow crack growth spin disk failures were also successfully predicted.

  19. A Reliability-Based Determination of Economic Life of Marine power plants

    International Nuclear Information System (INIS)

    Atua, K.

    1999-01-01

    The reliability-based life approach is utilized. Selective failure modes of marine power plants are used for illustration. A case study of the Egyptian Commercial Fleet owned by the Public Sector Company was analyzed and used to establish a demonstration of the expected economic life based on local operating and maintenance conditions. The data acquired is analyzed and failure trend is derived for each failure mode. Probabilistic techniques are used to randomly generate numbers and times of occurrence of different failure modes. The reliability analysis is performed on the life span expected by the manufacture to predict the total number of failures, dependent failures, and cost of failures. Total expenditure due to random failure and cost of scheduled maintenance together with the annual income are utilized (using the time value of money) to determine the economic life of the plant. Conclusions are derived and recommendations for the enhancement of this work in the future are made

  20. Anisotropic Elastoplastic Damage Mechanics Method to Predict Fatigue Life of the Structure

    Directory of Open Access Journals (Sweden)

    Hualiang Wan

    2016-01-01

    Full Text Available New damage mechanics method is proposed to predict the low-cycle fatigue life of metallic structures under multiaxial loading. The microstructure mechanical model is proposed to simulate anisotropic elastoplastic damage evolution. As the micromodel depends on few material parameters, the present method is very concise and suitable for engineering application. The material parameters in damage evolution equation are determined by fatigue experimental data of standard specimens. By employing further development on the ANSYS platform, the anisotropic elastoplastic damage mechanics-finite element method is developed. The fatigue crack propagation life of satellite structure is predicted using the present method and the computational results comply with the experimental data very well.

  1. Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

    OpenAIRE

    Wu, Han-Zhou; Wang, Hong-Xia; Shi, Yun-Qing

    2016-01-01

    This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on th...

  2. QNA-Based Prediction of Sites of Metabolism

    OpenAIRE

    Olga Tarasova; Anastassia Rudik; Alexander Dmitriev; Alexey Lagunin; Dmitry Filimonov; Vladimir Poroikov

    2017-01-01

    Metabolism of xenobiotics (Greek xenos: exogenous substances) plays an essential role in the prediction of biological activity and testing for the subsequent research and development of new drug candidates. Integration of various methods and techniques using different computational and experimental approaches is one of the keys to a successful metabolism prediction. While multiple structure-based and ligand-based approaches to metabolism prediction exist, the most important problem arises at ...

  3. Revealing life-history traits by contrasting genetic estimations with predictions of effective population size.

    Science.gov (United States)

    Greenbaum, Gili; Renan, Sharon; Templeton, Alan R; Bouskila, Amos; Saltz, David; Rubenstein, Daniel I; Bar-David, Shirli

    2017-12-22

    Effective population size, a central concept in conservation biology, is now routinely estimated from genetic surveys, and can also be theoretically-predicted from demographic, life-history and mating-system hypotheses. However, by evaluating the consistency of theoretical predictions with empirically-estimated effective size, insights can be gained regarding life-history characteristics, as well as the relative impact of different life-history traits on genetic drift. These insights can be used to design and inform management strategies aimed at increasing effective population size. Here we describe and demonstrate this approach by addressing the conservation of a reintroduced population of Asiatic wild ass (Equus hemionus). We estimate the variance effective size (N ev ) from genetic data (N ev = 24.3), and we formulate predictions for the impacts on N ev of demography, polygyny, female variance in life-time reproductive success, and heritability of female reproductive success. By contrasting the genetic estimation with theoretical predictions, we find that polygyny is the strongest factor effecting genetic drift, as only when accounting for polygyny were predictions consistent with the genetically-measured N ev , with 10.6% mating males per generation when heritability of female RS was unaccounted for (polygyny responsible for 81% decrease in N ev ), and 19.5% when it was accounted for (polygyny responsible for 67% decrease in N ev ). Heritability of female reproductive success was also found to affect N ev , with h f 2 = 0.91 (heritability responsible for 41% decrease in N ev ). The low effective population size is of concern, and we suggest specific management actions focusing on factors identified as strongly affecting N ev -increasing the availability of artificial water sources to increase number of dominant males contributing to the gene pool. This approach - evaluating life-history hypotheses, in light of their impact on effective population size, and

  4. An Adaptive Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-ion Batteries

    Data.gov (United States)

    National Aeronautics and Space Administration — Prognostics is an emerging science of predicting the health condition of a system (or its components) based upon current and previous system states. A reliable...

  5. [A predictive model for the quality of sexual life in hysterectomized women].

    Science.gov (United States)

    Urrutia, María Teresa; Araya, Alejandra; Rivera, Soledad; Viviani, Paola; Villarroel, Luis

    2007-03-01

    The effects of hysterectomy on sexuality has been extensively studied. To establish a model to predict the quality of sexual life in hysterectomized women, six months after surgery. Analytical, longitudinal and prospective study of 90 hysterectomized women aged 45+/-7 years. Two structured interviews at the time of surgery and six months later were carried out to determine the characteristics of sexuality and communication within the couple. In the two interviews, communication and the quality of sexual life were described as "good" in 72 and 77% of women, respectively (NS). The variables that had a 40% influence on the quality of sexual life sixth months after surgery, were oophorectomy status, the presence of orgasm, the characteristics of communication and the basal sexuality with the couple. The sexuality of the hysterectomized women will depend, on a great extent, of pre-surgical variables. Therefore, it is important to consider these variables for the education of hysterectomized women.

  6. Predicting the Reliability of Ceramics Under Transient Loads and Temperatures With CARES/Life

    Science.gov (United States)

    Nemeth, Noel N.; Jadaan, Osama M.; Palfi, Tamas; Baker, Eric H.

    2003-01-01

    A methodology is shown for predicting the time-dependent reliability of ceramic components against catastrophic rupture when subjected to transient thermomechanical loads (including cyclic loads). The methodology takes into account the changes in material response that can occur with temperature or time (i.e., changing fatigue and Weibull parameters with temperature or time). This capability has been added to the NASA CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. The code has been modified to have the ability to interface with commercially available finite element analysis (FEA) codes executed for transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

  7. Preadmission quality of life can predict mortality in intensive care unit—A prospective cohort study

    DEFF Research Database (Denmark)

    Bukan, Ramin I; Møller, Ann M; Henning, Mattias A S

    2014-01-01

    PURPOSE: We sought to investigate whether preadmission quality of life could act as a predictor of mortality among patients admitted to the intensive care unit (ICU). MATERIALS AND METHODS: This is a prospective observational study of all patients above the age of 18 years admitted to the ICU...... quality of life, assessed by SF-36 and SF-12, is as good at predicting ICU, 30-, and 90-day mortality as APACHE II in patients admitted to the ICU for longer than 24 hours. This indicates that estimated preadmission quality of life, potentially available in the pre-ICU setting, could aid decision making...... regarding ICU admission and deserves more attention by those caring for critically ill patients....

  8. A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades

    Directory of Open Access Journals (Sweden)

    Zheng-Yong Yu

    2017-05-01

    Full Text Available As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB and Fatemi-Socie (FS models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models.

  9. The effect of discounting, different mortality reduction schemes and predictive cohort life tables on risk acceptability criteria

    International Nuclear Information System (INIS)

    Rackwitz, Ruediger

    2006-01-01

    Technical facilities should be optimal with respect to benefits and cost. Optimization of technical facilities involving risks for human life and limb require an acceptability criterion and suitable discount rates both for the public and the operator depending on for whom the optimization is carried out. The life quality index is presented and embedded into modem socio-economic concepts. A general risk acceptability criterion is derived. The societal life saving cost to be used in optimization as life saving or compensation cost and the societal willingness-to-pay based on the societal value of a statistical life or on the societal life quality index are developed. Different mortality reduction schemes are studied. Also, predictive cohort life tables are derived and applied. Discount rates γ must be long-term averages in view of the time horizon of some 20 to more than 100 years for the facilities of interest and net of inflation and taxes. While the operator may use long-term averages from the financial market for his cost-benefit analysis the assessment of interest rates for investments of the public into risk reduction is more difficult. The classical Ramsey model decomposes the real interest rate (=output growth rate) into the rate of time preference of consumption and the rate of economical growth multiplied by the elasticity of marginal utility of consumption. It is proposed to use a relatively small interest rate of 3% implying a rate of time preference of consumption of about 1%. This appears intergenerationally acceptable from an ethical point of view. Risk-consequence curves are derived for an example

  10. How do Major, Violent and Nonviolent Opposition Campaigns, Impact Predicted Life Expectancy at birth?

    Directory of Open Access Journals (Sweden)

    Judith Stoddard

    2013-08-01

    Full Text Available This study compared the effects of major violent and nonviolent opposition campaigns for regime change, on predicted life expectancy at birth. The study measured life expectancy five and ten years after the campaign ended, so that deaths which occurred during the campaign would not be included in the metric, and thus enabling the study of changes made in the state on the social determinants affecting longevity, after the campaign was over. Life expectancy is one of the best reported World Development Indicators and is considered to be a good indication of the overall health and general living conditions of the state and therefore is an ideal indicator to reflect the changes made in the state following a major campaign. The results of this analysis showed that states have a hard time recovering from a major opposition campaign and initially drop behind the growth trend in the world average for predicted life expectancy at birth. But, the type of campaign that was waged and whether it was successful, greatly affects the state’s ability to recover. Encouragingly by a decade after the campaign ends, states that experienced a nonviolent campaign that was successful had caught up to the world average and inched ahead of it. This shows that on this important development indicator, new governments that were ushered into power by nonviolent social movements, had made positive changes in the state that enabled it to surpass world averages.

  11. Factors predicting quality of work life among nurses in tertiary-level hospitals, Bangladesh.

    Science.gov (United States)

    Akter, N; Akkadechanunt, T; Chontawan, R; Klunklin, A

    2017-11-03

    This study examined the level of quality of work life and predictability of years of education, monthly income, years of experience, job stress, organizational commitment and work environment on quality of work life among nurses in tertiary-level hospitals in the People's Republic of Bangladesh. There is an acute shortage of nurses worldwide including Bangladesh. Quality of work life is important for quality of patient care and nurse retention. Nurses in Bangladesh are fighting to provide quality care for emerging health problems for the achievement of sustainable development goals. We collected data from 288 randomly selected registered nurses, from six tertiary-level hospitals. All nurses were requested to fill questionnaire consisted of Demographic Data Sheet, Quality of Nursing Work Life Survey, Expanded Nursing Stress Scale, Questionnaire of Organizational Commitment and Practice Environment Scale of the Nursing Work Index. Data were analysed by descriptive statistics and multiple regression. The quality of work life as perceived by nurses in Bangladesh was at moderate level. Monthly income was found as the best predictor followed by work environment, organizational commitment and job stress. A higher monthly income helps nurses to fulfil their personal needs; positive work environment helps to provide quality care to the patients. Quality of work life and predictors measured by self-report only may not reflect the original picture of the quality of work life among nurses. Findings provide information for nursing and health policymakers to develop policies to improve quality of work life among nurses that can contribute to quality of nursing care. This includes the working environment, commitment to the organization and measures to reduce job stress. © 2017 International Council of Nurses.

  12. Fatigue Life Prediction in Rapid Die Casting - Preliminary Work in View of Current Research

    International Nuclear Information System (INIS)

    Chuan Huat Ng; Grote, Karl-Heinrich; Baehr, Ruediger

    2007-01-01

    Numerical simulation technique as a prediction tool is slowly adopted in metal casting industry for predicting design modelling solidification analysis. The reasons for this activity is found in the need to further enhance the geometrical design and mechanical properties of the tool design and the correct prediction methodology to fulfil industrial needs. The present state of numerical simulation capabilities in rapid die casting technologies is reviewed and the failure mode mechanisms of thermal fatigue, aimed at developing a numerical simulation with a systematic design guidance for predicting the thermal cyclic loading analysis and improvement is presented along with several other methods. The economic benefits of a numerical simulation technique in die casting are limited to tool life time, mechanical properties and design guidance. The extensive computer capabilities of a numerical simulation with a systematic design guidance methodology are exploited to provide a solution for flexible design, mechanical properties and mould life time. Related research carried out worldwide by different organisations and academic institutions are discussed

  13. Remaining Useful Life Prediction of Gas Turbine Engine using Autoregressive Model

    Directory of Open Access Journals (Sweden)

    Ahsan Shazaib

    2017-01-01

    Full Text Available Gas turbine (GT engines are known for their high availability and reliability and are extensively used for power generation, marine and aero-applications. Maintenance of such complex machines should be done proactively to reduce cost and sustain high availability of the GT. The aim of this paper is to explore the use of autoregressive (AR models to predict remaining useful life (RUL of a GT engine. The Turbofan Engine data from NASA benchmark data repository is used as case study. The parametric investigation is performed to check on any effect of changing model parameter on modelling accuracy. Results shows that a single sensory data cannot accurately predict RUL of GT and further research need to be carried out by incorporating multi-sensory data. Furthermore, the predictions made using AR model seems to give highly pessimistic values for RUL of GT.

  14. Sensor Based Engine Life Calculation: A Probabilistic Perspective

    Science.gov (United States)

    Guo, Ten-Huei; Chen, Philip

    2003-01-01

    It is generally known that an engine component will accumulate damage (life usage) during its lifetime of use in a harsh operating environment. The commonly used cycle count for engine component usage monitoring has an inherent range of uncertainty which can be overly costly or potentially less safe from an operational standpoint. With the advance of computer technology, engine operation modeling, and the understanding of damage accumulation physics, it is possible (and desirable) to use the available sensor information to make a more accurate assessment of engine component usage. This paper describes a probabilistic approach to quantify the effects of engine operating parameter uncertainties on the thermomechanical fatigue (TMF) life of a selected engine part. A closed-loop engine simulation with a TMF life model is used to calculate the life consumption of different mission cycles. A Monte Carlo simulation approach is used to generate the statistical life usage profile for different operating assumptions. The probabilities of failure of different operating conditions are compared to illustrate the importance of the engine component life calculation using sensor information. The results of this study clearly show that a sensor-based life cycle calculation can greatly reduce the risk of component failure as well as extend on-wing component life by avoiding unnecessary maintenance actions.

  15. Nomogram for Predicting Time to Death After Withdrawal of Life-Sustaining Treatment in Patients With Devastating Neurological Injury.

    Science.gov (United States)

    He, X; Xu, G; Liang, W; Liu, B; Xu, Y; Luan, Z; Lu, Y; Ko, D S C; Manyalich, M; Schroder, P M; Guo, Z

    2015-08-01

    Reliable prediction of time of death after withdrawal of life-sustaining treatment in patients with devastating neurological injury is crucial to successful donation after cardiac death. Herein, we conducted a study of 419 neurocritical patients who underwent life support withdrawal at four neurosurgical centers in China. Based on a retrospective cohort, we used multivariate Cox regression analysis to identify prognostic factors for patient death, which were then integrated into a nomogram. The model was calibrated and validated using data from an external retrospective cohort and a prospective cohort. We identified 10 variables that were incorporated into a nomogram. The C-indexes for predicting the 60-min death probability in the training, external validation and prospective validation cohorts were 0.96 (0.93-0.98), 0.94 (0.91-0.97), and 0.99 (0.97-1.00), respectively. The calibration plots after WLST showed an optimal agreement between the prediction of time to death by the nomogram and the actual observation for all cohorts. Then we identified 22, 26 and 37 as cut-points for risk stratification into four groups. Kaplan-Meier curves indicated distinct prognoses between patients in the different risk groups (p death donors in neurocritical patients in a Chinese population. © Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons.

  16. Inculcating home economics based life skills in rural women in ...

    African Journals Online (AJOL)

    This study investigated the strategies for inculcating Home Economics based life (survival) skills among rural women as a panacea for poverty alleviation. The study was a descriptive survey that was based on two research questions. From a population of 1,815 respondents, purposive sampling was used to select a sample ...

  17. Size-based predictions of food web patterns

    DEFF Research Database (Denmark)

    Zhang, Lai; Hartvig, Martin; Knudsen, Kim

    2014-01-01

    We employ size-based theoretical arguments to derive simple analytic predictions of ecological patterns and properties of natural communities: size-spectrum exponent, maximum trophic level, and susceptibility to invasive species. The predictions are brought about by assuming that an infinite number...... simulations with varying species richness. To this end, we develop a new size- and trait-based food web model that can be simplified into an analytically solvable size-based model. We confirm existing solutions for the size distribution and derive novel predictions for maximum trophic level and invasion...... of species are continuously distributed on a size-trait axis. It is, however, an open question whether such predictions are valid for a food web with a finite number of species embedded in a network structure. We address this question by comparing the size-based predictions to results from dynamic food web...

  18. Prediction of Mortality Based on Facial Characteristics

    OpenAIRE

    Delorme, Arnaud; Pierce, Alan; Michel, Leena; Radin, Dean

    2016-01-01

    Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief e...

  19. Prediction of mortality based on facial characteristics

    OpenAIRE

    Arnaud Delorme; Arnaud Delorme; Alan Pierce; Leena Michel; Dean Radin

    2016-01-01

    Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief ...

  20. Leg and Trunk Impairments Predict Participation in Life Roles in Older Adults: Results From Boston RISE.

    Science.gov (United States)

    Beauchamp, Marla K; Jette, Alan M; Ni, Pengsheng; Latham, Nancy K; Ward, Rachel E; Kurlinski, Laura A; Percac-Lima, Sanja; Leveille, Suzanne G; Bean, Jonathan F

    2016-05-01

    The physical impairments that affect participation in life roles among older adults have not been identified. Using the International Classification of Functioning Disability and Health as a conceptual framework, we aimed to determine the leg and trunk impairments that predict participation over 2 years, both directly and indirectly through mediation by changes in activities. We analyzed 2 years of data from the Boston Rehabilitative Impairment Study of the Elderly, a cohort study of 430 primary care patients with self-reported mobility limitation (mean age 77 years; 68% female; average of four chronic conditions). Frequency of and limitations in participation were examined using the Late-Life Disability Instrument. Baseline physical impairments included: leg strength, leg speed of movement, knee range of motion (ROM), ankle ROM, leg strength asymmetry, kyphosis, and trunk extensor endurance. Structural equation modeling with latent growth curve analysis was used to identify the impairments that predicted participation at year 2, mediated by changes in activities. Models were adjusted for baseline participation, age, and gender. Leg speed and ankle ROM directly influenced participation in life roles during follow-up (βdirect = 1.39-4.53 and 4.70, respectively). Additionally, ankle ROM and trunk extensor endurance contributed indirectly to participation score at follow-up via effects on changes in activities (βindirect = -1.06 to -4.24 and 1.01 to 4.18, respectively). Leg speed, ankle ROM, and trunk extensor endurance are key physical impairments predicting participation in life roles in older adults. These results have implications for the development of exercise interventions to enhance participation. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Fatigue, fracture, and life prediction criteria for composite materials in magnets

    International Nuclear Information System (INIS)

    Wong, F.M.G.

    1990-06-01

    An explosively-bonded copper/Inconel 718/copper laminate conductor was proposed to withstand the severe face compression stresses in the central core of the Alcator C-MOD tokamak toroidal field (TF) magnet. Due to the severe duty of the TF magnet, it is critical that an accurate estimate of useful life be determined. As part of the effort to formulate an appropriate life prediction, fatigue crack growth experiments were performed on the laminate as well as its components. Metallographic evaluation of the laminate interface revealed many shear bands in the Inconel 718. Shear bands and shear band cracks were produced in the Inconel 718 as a result of the explosion bonding process. These shear bands were shown to have a detrimental effect on the crack growth behavior of the laminate, by significantly reducing the load carrying capability of the reinforcement layer and providing for easy crack propagation paths. Fatigue crack growth rate was found not only to be dependent on temperature but also on orientation. Fatigue cracks grew faster in directions which contained shear bands in the plane of the propagating crack. Fractography showed crack advancement by fatigue cracking in the Inconel 718 and ductile tearing of the copper at the interface. However, further away from the interfaces, the copper exhibited fatigue striations indicating that cracks were now propagating by fatigue. Laminate life prediction results showed a strong dependence on shear band orientation, and exhibited little variation between room temperature and 77 degree K. Predicted life of this laminate was lower when the crack propagation was along a shear band than when crack propagation was across the shear bands. Shear bands appear to have a dominating effect on crack growth behavior

  2. Do Culture-based Segments Predict Selection of Market Strategy?

    OpenAIRE

    Veronika Jadczaková

    2015-01-01

    Academists and practitioners have already acknowledged the importance of unobservable segmentation bases (such as psychographics) yet still focusing on how well these bases are capable of describing relevant segments (the identifiability criterion) rather than on how precisely these segments can predict (the predictability criterion). Therefore, this paper intends to add a debate to this topic by exploring whether culture-based segments do account for a selection of market strategy. To do so,...

  3. Leaf and life history traits predict plant growth in a green roof ecosystem.

    Directory of Open Access Journals (Sweden)

    Jeremy Lundholm

    Full Text Available Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime's C-S-R strategies for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that

  4. Leaf and life history traits predict plant growth in a green roof ecosystem.

    Science.gov (United States)

    Lundholm, Jeremy; Heim, Amy; Tran, Stephanie; Smith, Tyler

    2014-01-01

    Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth) to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime's C-S-R strategies) for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that favor less

  5. Shelf-life dating of shelf-stable strawberry juice based on survival analysis of consumer acceptance information.

    Science.gov (United States)

    Buvé, Carolien; Van Bedts, Tine; Haenen, Annelien; Kebede, Biniam; Braekers, Roel; Hendrickx, Marc; Van Loey, Ann; Grauwet, Tara

    2017-12-27

    Accurate shelf-life dating of food products is crucial for consumers and industries. Therefore, in this study we applied a science-based approach for shelf-life assessment, including accelerated shelf-life testing (ASLT), acceptability testing and the screening of analytical attributes for fast shelf-life predictions. Shelf-stable strawberry juice was selected as a case study. Ambient storage (20 °C) had no effect on the aroma-based acceptance of strawberry juice. The colour-based acceptability decreased during storage under ambient and accelerated (28-42 °C) conditions. The application of survival analysis showed that the colour-based shelf-life was reached in the early stages of storage (≤11 weeks) and that the shelf-life was shortened at higher temperatures. None of the selected attributes (a * and ΔE * value, anthocyanin and ascorbic acid content) is an ideal analytical marker for shelf-life predictions in the investigated temperature range (20-42 °C). Nevertheless, an overall analytical cut-off value over the whole temperature range can be selected. Colour changes of strawberry juice during storage are shelf-life limiting. Combining ASLT with acceptability testing allowed to gain faster insight into the change in colour-based acceptability and to perform shelf-life predictions relying on scientific data. An analytical marker is a convenient tool for shelf-life predictions in the context of ASLT. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  6. Copula-based prediction of economic movements

    Science.gov (United States)

    García, J. E.; González-López, V. A.; Hirsh, I. D.

    2016-06-01

    In this paper we model the discretized returns of two paired time series BM&FBOVESPA Dividend Index and BM&FBOVESPA Public Utilities Index using multivariate Markov models. The discretization corresponds to three categories, high losses, high profits and the complementary periods of the series. In technical terms, the maximal memory that can be considered for a Markov model, can be derived from the size of the alphabet and dataset. The number of parameters needed to specify a discrete multivariate Markov chain grows exponentially with the order and dimension of the chain. In this case the size of the database is not large enough for a consistent estimation of the model. We apply a strategy to estimate a multivariate process with an order greater than the order achieved using standard procedures. The new strategy consist on obtaining a partition of the state space which is constructed from a combination, of the partitions corresponding to the two marginal processes and the partition corresponding to the multivariate Markov chain. In order to estimate the transition probabilities, all the partitions are linked using a copula. In our application this strategy provides a significant improvement in the movement predictions.

  7. Statistical model based gender prediction for targeted NGS clinical panels

    Directory of Open Access Journals (Sweden)

    Palani Kannan Kandavel

    2017-12-01

    The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

  8. Psychological approach to successful ageing predicts future quality of life in older adults

    Directory of Open Access Journals (Sweden)

    Iliffe Steve

    2011-03-01

    Full Text Available Abstract Background Public policies aim to promote well-being, and ultimately the quality of later life. Positive perspectives of ageing are underpinned by a range of appraoches to successful ageing. This study aimed to investigate whether baseline biological, psychological and social aproaches to successful ageing predicted future QoL. Methods Postal follow-up in 2007/8 of a national random sample of 999 people aged 65 and over in 1999/2000. Of 496 valid addresses of survivors at follow-up, the follow-up response rate was 58% (287. Measures of the different concepts of successful ageing were constructed using baseline indicators. They were assessed for their ability to independently predict quality of life at follow-up. Results Few respondents achieved all good scores within each of the approaches to successful ageing. Each approach was associated with follow-up QoL when their scores were analysed continuously. The biomedical (health approach failed to achieve significance when the traditional dichotomous cut-off point for successfully aged (full health, or not (less than full health, was used. In multiple regression analyses of the relative predictive ability of each approach, only the psychological approach (perceived self-efficacy and optimism retained significance. Conclusion Only the psychological approach to successful ageing independently predicted QoL at follow-up. Successful ageing is not only about the maintenance of health, but about maximising one's psychological resources, namely self-efficacy and resilience. Increasing use of preventive care, better medical management of morbidity, and changing lifestyles in older people may have beneficial effects on health and longevity, but may not improve their QoL. Adding years to life and life to years may require two distinct and different approaches, one physical and the other psychological. Follow-up health status, number of supporters and social activities, and self-rated active ageing

  9. Fatigue life prediction of a cable harness in an industrial robot using dynamic simulation

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Ji Won; Park, Tae Won [Ajou University, Suwon (Korea, Republic of); Yim, Hong Jae [Kookmin University, Seoul (Korea, Republic of)

    2008-03-15

    The cable which transfers the signal and power in an industrial robot has a problem of fatigue fracture like steel components. Since the cable is very flexible compared to other components of the system, it is difficult to estimate its motion numerically. Some studies have been done on a large deformation problem, especially in a cable, and a few attempts have been made to apply the absolute nodal coordinate formulation (ANCF), which can simulate a large deformation. Only researches about the fatigue life of structural cables or comparative studies of FEM and ANCF simulations can be found. This paper presents a method to simulate the behavior of the cable harness using the ANCF and to predict the fatigue life while computing the strain time history of the point of interest. Rigid body dynamics is applied for the robot system, while ANCF is used for the cable harness. The simulation is performed by using the dynamic analysis process. The material property of the cable is obtained by a test. A simplified model is prepared. With these data, the behavior of the cable is simulated and the fatigue life is predicted

  10. Fatigue life prediction method for contact wire using maximum local stress

    International Nuclear Information System (INIS)

    Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean; Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon

    2015-01-01

    Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

  11. Fatigue life prediction method for contact wire using maximum local stress

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean [Sungkyunkwan University, Suwon (Korea, Republic of); Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon [Korea Railroad Research Institute, Uiwang (Korea, Republic of)

    2015-01-15

    Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

  12. Battery lifetime prediction by pattern recognition. Application to lead-acid battery life-cycling test data

    Science.gov (United States)

    Perone, Sam P.; Spindler, W. C.

    1984-09-01

    A novel approach to battery lifetime prediction has been evaluated by application to life-cycling data collected for 108 ESB EV-106 6-V. golf cart batteries (tests conducted by TRW for NASA-Lewis). This approach utilized computerized pattern recognition methods to examine initial cycling measurements and classify each battery into one of two classes: "long-lived" or "short-lived". The classifier program was based on either a linear discriminant or nearest neighbor analysis of a training set consisting of: each member of the EV battery set which had failed; the relative lifetime of each member — normalized with respect to test conditions; and a set of "features" based on measurements of the initial behavior. The raw data set included capacity trends over the first 8 or 9 cycles and records of specific gravity and water-added for each cell after initial cycling. Features defined from these raw data included the individual data items as well as transformations and combinations of these data. All features were represented as standardized variables. It was shown that lifetime prediction of batteries within the two categories defined could be made with about 87% accuracy. It is concluded that for a similarly-manufactured battery set, relative lifetime prediction could be based on initial measurements of the same type examined here.

  13. Comparisons of prediction models of quality of life after laparoscopic cholecystectomy: a longitudinal prospective study.

    Directory of Open Access Journals (Sweden)

    Hon-Yi Shi

    Full Text Available BACKGROUND: Few studies of laparoscopic cholecystectomy (LC outcome have used longitudinal data for more than two years. Moreover, no studies have considered group differences in factors other than outcome such as age and nonsurgical treatment. Additionally, almost all published articles agree that the essential issue of the internal validity (reproducibility of the artificial neural network (ANN, support vector machine (SVM, Gaussian process regression (GPR and multiple linear regression (MLR models has not been adequately addressed. This study proposed to validate the use of these models for predicting quality of life (QOL after LC and to compare the predictive capability of ANNs with that of SVM, GPR and MLR. METHODOLOGY/PRINCIPAL FINDINGS: A total of 400 LC patients completed the SF-36 and the Gastrointestinal Quality of Life Index at baseline and at 2 years postoperatively. The criteria for evaluating the accuracy of the system models were mean square error (MSE and mean absolute percentage error (MAPE. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and to rank the variables in order of importance. Compared to SVM, GPR and MLR models, the ANN model generally had smaller MSE and MAPE values in the training data set and test data set. Most ANN models had MAPE values ranging from 4.20% to 8.60%, and most had high prediction accuracy. The global sensitivity analysis also showed that preoperative functional status was the best parameter for predicting QOL after LC. CONCLUSIONS/SIGNIFICANCE: Compared with SVM, GPR and MLR models, the ANN model in this study was more accurate in predicting patient-reported QOL and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data.

  14. Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions.

    Science.gov (United States)

    Hauri, D D; Huss, A; Zimmermann, F; Kuehni, C E; Röösli, M

    2013-10-01

    Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  15. A comprehensive energy approach to predict fatigue life in CuAlBe shape memory alloy

    Science.gov (United States)

    Sameallah, S.; Legrand, V.; Saint-Sulpice, L.; Kadkhodaei, M.; Arbab Chirani, S.

    2015-02-01

    Stabilized dissipated energy is an effective parameter on the fatigue life of shape memory alloys (SMAs). In this study, a formula is proposed to directly evaluate the stabilized dissipated energy for different values of the maximum and minimum applied stresses, as well as the loading frequency, under cyclic tensile loadings. To this aim, a one-dimensional fully coupled thermomechanical constitutive model and a cycle-dependent phase diagram are employed to predict the uniaxial stress-strain response of an SMA in a specified cycle, including the stabilized one, with no need of obtaining the responses of the previous cycles. An enhanced phase diagram in which different slopes are defined for the start and finish of a backward transformation strip is also proposed to enable the capture of gradual transformations in a CuAlBe shape memory alloy. It is shown that the present approach is capable of reproducing the experimental responses of CuAlBe specimens under cyclic tensile loadings. An explicit formula is further presented to predict the fatigue life of CuAlBe as a function of the maximum and minimum applied stresses as well as the loading frequency. Fatigue tests are also carried out, and this formula is verified against the empirically predicted number of cycles for failure.

  16. From First Life to Second Life: Evaluating Task-Based Language Learning in a New Environment

    Science.gov (United States)

    Jee, Min Jung

    2014-01-01

    With its growing number of users, Second Life as one of the avatar-based 3D virtual worlds has received attention from educators and researchers in various fields to explore its pedagogical benefits. Given the increasing implementation of technologies broadly in much instruction, this study investigated how ESL students negotiated meanings in…

  17. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations ...

  18. Monitoring Shelf Life of Pasteurized Whole Milk Under Refrigerated Storage Conditions: Predictive Models for Quality Loss.

    Science.gov (United States)

    Ziyaina, Mohamed; Govindan, Byju N; Rasco, Barbara; Coffey, Todd; Sablani, Shyam S

    2018-02-01

    The shelf life of pasteurized milk is generally determined through microbiological analysis. The objective of this study was to correlate microbial quality parameters then to design predictive models for shelf life of pasteurized milk. We analyzed pasteurized milk (3.9% fat) for aerobic plate counts (APCs), psychrotrophic bacteria counts (PBCs), and Bacillus spp. counts at 5, 7, 10, 13, 15, and 19 (±1 °C) to the end of storage time. We also monitored titratable acidity, pH, and, lipase, and protease activity and correlated this with APC, which is the principal index defining shelf life. Results indicate that the shelf life of pasteurized milk was 24, 36, and 72 h at 19, 15, and 13 °C respectively, as determined by APC and acidity indicators. However, milk stored at lower temperatures of 5, 7, and 10 °C had longer shelf life of 30, 24, and 12 d, respectively. A sharp increase in titratable acidity, while decrease pH were observed when APCs reached 5.0 log 10 CFU/mL at all storage temperatures. Lipase and protease activities increased with storage temperature. At 5 and 7 °C, however, protease activity was very low. Therefore, we eliminated this parameter from our quality parameters as a potential spoilage indicator. Findings of this research are useful for monitoring the quality of commercial pasteurized milk, particularly in locations where environmental conditions make longer storage difficult. The study also provides valuable information for development of colorimetric shelf life indicators. © 2018 Institute of Food Technologists®.

  19. Ambulatory fall-risk assessment: amount and quality of daily-life gait predict falls in older adults.

    Science.gov (United States)

    van Schooten, Kimberley S; Pijnappels, Mirjam; Rispens, Sietse M; Elders, Petra J M; Lips, Paul; van Dieën, Jaap H

    2015-05-01

    Ambulatory measurements of trunk accelerations can provide valuable information on the amount and quality of daily-life activities and contribute to the identification of individuals at risk of falls. We compared associations between retrospective and prospective falls with potential risk factors as measured by daily-life accelerometry. In addition, we investigated predictive value of these parameters for 6-month prospective falls. One week of trunk accelerometry (DynaPort MoveMonitor) was obtained in 169 older adults (mean age 75). The amount of daily activity and quality of gait were determined and validated questionnaires on fall-risk factors, grip strength, and trail making test were obtained. Six-month fall incidence was obtained retrospectively by recall and prospectively by fall diaries and monthly telephone contact. Among all participants, 35.5% had a history of ≥1 falls and 34.9% experienced ≥1 falls during 6-month follow-up. Logistic regressions showed that questionnaires, grip strength, and trail making test, as well as the amount and quality of gait, were significantly associated with falls. Significant associations differed between retrospective and prospective analyses although odds ratios indicated similar patterns. Predictive ability based on questionnaires, grip strength, and trail making test (area under the curve .68) improved substantially by accelerometry-derived parameters of the amount of gait (number of strides), gait quality (complexity, intensity, and smoothness), and their interactions (area under the curve .82). Daily-life accelerometry contributes substantially to the identification of individuals at risk of falls, and can predict falls in 6 months with good accuracy. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  20. Shelf life prediction of fresh Italian pork sausage modified atmosphere packed.

    Science.gov (United States)

    Torrieri, E; Russo, F; Di Monaco, R; Cavella, S; Villani, F; Masi, F

    2011-06-01

    The shelf life of fresh Italian pork sausages packed in modified atmosphere was studied. Samples were packed using different levels of oxygen (high and low) with different levels of carbon dioxide (high-low) in the atmospheres headspace and were stored at 4 °C for 9 days. Microbial, physiochemical and sensory parameters were analyzed during storage. A consumer test was performed to determine the critical acceptability levels. Sensory data were mathematically modelled to estimate product shelf life. A first-order kinetic model and a Weibull-type model aptly described, respectively, the changes in fresh pork sausage odor and color over storage time. These models may be used to predict the sensory shelf life of fresh pork sausage. Results showed that 20% O(2) and 70% CO(2) extend fresh pork sausage shelf life to 9 days at 4 °C. The microbial quality of the samples at the critical sensory level of acceptability was within the range of microbial acceptability.

  1. Alcohol-related problems and life satisfaction predict motivation to change among mandated college students.

    Science.gov (United States)

    Diulio, Andrea R; Cero, Ian; Witte, Tracy K; Correia, Christopher J

    2014-04-01

    The present study investigated the role specific types of alcohol-related problems and life satisfaction play in predicting motivation to change alcohol use. Participants were 548 college students mandated to complete a brief intervention following an alcohol-related policy violation. Using hierarchical multiple regression, we tested for the presence of interaction and quadratic effects on baseline data collected prior to the intervention. A significant interaction indicated that the relationship between a respondent's personal consequences and his/her motivation to change differs depending upon the level of concurrent social consequences. Additionally quadratic effects for abuse/dependence symptoms and life satisfaction were found. The quadratic probes suggest that abuse/dependence symptoms and poor life satisfaction are both positively associated with motivation to change for a majority of the sample; however, the nature of these relationships changes for participants with more extreme scores. Results support the utility of using a multidimensional measure of alcohol related problems and assessing non-linear relationships when assessing predictors of motivation to change. The results also suggest that the best strategies for increasing motivation may vary depending on the types of alcohol-related problems and level of life satisfaction the student is experiencing and highlight potential directions for future research. Copyright © 2014. Published by Elsevier Ltd.

  2. Neuroticism and Extraversion in Youth Predict Mental Wellbeing and Life Satisfaction 40 Years Later

    Science.gov (United States)

    Gale, Catharine R; Booth, Tom; Mõttus, René; Kuh, Diana; Deary, Ian J

    2014-01-01

    Neuroticism and Extraversion are linked with current wellbeing, but it is unclear whether these traits in youth predict wellbeing decades later. We applied structural equation modelling to data from 4583 people from the MRC National Survey of Health and Development. We examined the effects of Neuroticism and Extraversion at ages 16 and 26 years on mental wellbeing and life satisfaction at age 60-64 and explored the mediating roles of psychological and physical health. Extraversion had direct, positive effects on both measures of wellbeing. The impact of Neuroticism on both wellbeing and life satisfaction was largely indirect through susceptibility to psychological distress and physical health problems. Personality dispositions in youth have enduring influence on wellbeing assessed about forty years later. PMID:24563560

  3. Predicting the natural mortality of marine fish from life history characteristics

    DEFF Research Database (Denmark)

    Gislason, Henrik

    the information necessary to estimate the scaling of natural mortality with size and asymptotic size. The estimated scaling is compared with output from multispecies fish stock models, with the empirical scaling of the maximum number of recruits per unit of spawning stock biomass with body size......, and with estimates from a comprehensive compilation of empirical data on the natural mortality of marine fishes. The comparisons are all in aggreement with the predictions from the model. We conclude that natural mortality scales with body length raised to a power around -1.6, with the asymptotic length......For fish much of the life history is determined by body size. Body size and asymptotic size significantly influences important life history processes such as growth, maturity, egg production, and natural mortality. Futhermore, for a population to persist, offspring must be able to replace...

  4. Caregiving Motivation Predicts Long-Term Spirituality and Quality of Life of the Caregivers.

    Science.gov (United States)

    Kim, Youngmee; Carver, Charles S; Cannady, Rachel S

    2015-08-01

    Studies have shown that caregivers report impaired quality of life (QOL). This study investigated how caregiving motives predict long-term spirituality and QOL among cancer caregivers and the role of gender in these associations. Caregiving motives of family members (n = 369) were measured 2 years after their relative's cancer diagnosis (T1), and both spirituality and QOL (mental and physical health) were measured at 5 years postdiagnosis (T2). Structural equation modeling was used to test spirituality dimensions as potential mediators of links from caregiving motives to QOL. Among male caregivers, autonomous caregiving motives at T1 related to better mental health at T2, apparently because these motives led caregivers to find greater peace and meaning in life at T2. Findings suggest that caregivers may benefit from interventions that facilitate their ability to be autonomously motivated and find contentment in their caregiving experience, which may improve spiritual adjustment and QOL years later.

  5. Disaster prediction of coal mine gas based on data mining

    Energy Technology Data Exchange (ETDEWEB)

    Shao, Liang-shan; Fu, Gui-xiang [Liaoning Technical University, Fuxin (China)

    2008-09-15

    The technique of data mining was applied to predict gas disasters in view of the characteristics of coal mine gas disasters and feature knowledge based on gas disasters. The rough set theory was used to establish a data mining model of gas disaster prediction, and rough set attributes relations were discussed in a prediction model of gas disaster to supplement the shortages of the rough intensive reduction method by using information entropy criteria. The effectiveness and practicality of data mining technology in the prediction of gas disaster is confirmed through practical application. 7 refs., 11 tabs.

  6. Slope Deformation Prediction Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Lei JIA

    2013-07-01

    Full Text Available This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM. In the prediction process,explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that this model is of high fitting accuracy and generalization, and provides reference for deformation prediction in slope engineering.

  7. Assessment of Predictable Productivity of Nurses Working in Kerman University of Medical Sciences' Teaching Hospitals via the Dimensions of Quality of Work Life.

    Science.gov (United States)

    Borhani, Fariba; Arbabisarjou, Azizollah; Kianian, Toktam; Saber, Saman

    2016-10-01

    Despite the existence of a large community of nurses, specific mechanisms have not been developed yet to consider their needs and the quality of their work life. Moreover, few studies have been conducted to analyze the nature of nursing, nursing places or nurses' quality of work life. In this regard, the present study aimed to assess predictable productivity of nurses working in Kerman University of Medical Sciences' teaching hospitals via the dimensions of Quality of Work Life. The present descriptive-correlational study was conducted to assess predictable productivity of nurses via the dimensions of Quality of Work Life. The study's population consisted of all nurses working in different wards of teaching hospitals associated with Kerman University of Medical Sciences. Out of the whole population, 266 nurses were selected based on the simple random sampling method. To collect data, the questionnaires of 'Quality of Nursing Work Life' and 'Productivity' were used after confirming their reliability (test-retest) and content validity. Finally, the collected data were analyzed through the SPSS software (version 16). Although the quality of work life for nurses was average and their productivity was low but the results showed that quality of life is directly related to nurses' productivity. Quality of life and its dimensions are predictive factors in the in the nurses' productivity. It can conclude that by recognizing the nurses' quality of work life situation, it can realize this group productivity and their values to the efficiency of the health system. For the quality of working life improvement and increasing nurses' productivity more efforts are needed by authorities. The findings can be applied by managers of hospitals and nursing services along with head nurses to enhance the quality of health services and nursing profession in general.

  8. Thermo-mechanical fatigue behaviour and life prediction of C-1023 ...

    African Journals Online (AJOL)

    user

    Nickel based superalloys are used for manufacturing turbine blades and vanes components due to their ability to withstand high stress levels at high temperatures. The complex thermo-mechanical fatigue loadings that those components suffer (as a result of start ups and shutdowns) make life assessment a complex task.

  9. Prediction of speech intelligibility based on an auditory preprocessing model

    DEFF Research Database (Denmark)

    Christiansen, Claus Forup Corlin; Pedersen, Michael Syskind; Dau, Torsten

    2010-01-01

    Classical speech intelligibility models, such as the speech transmission index (STI) and the speech intelligibility index (SII) are based on calculations on the physical acoustic signals. The present study predicts speech intelligibility by combining a psychoacoustically validated model of auditory...

  10. Prediction-based estimating functions: Review and new developments

    DEFF Research Database (Denmark)

    Sørensen, Michael

    2011-01-01

    The general theory of prediction-based estimating functions for stochastic process models is reviewed and extended. Particular attention is given to optimal estimation, asymptotic theory and Gaussian processes. Several examples of applications are presented. In particular, partial observation...

  11. Protein-Based Urine Test Predicts Kidney Transplant Outcomes

    Science.gov (United States)

    ... News Releases News Release Thursday, August 22, 2013 Protein-based urine test predicts kidney transplant outcomes NIH- ... supporting development of noninvasive tests. Levels of a protein in the urine of kidney transplant recipients can ...

  12. Isothermal Fatigue, Damage Accumulation, and Life Prediction of a Woven PMC

    Science.gov (United States)

    Gyekenyesi, Andrew L.

    1998-01-01

    This dissertation focuses on the characterization of the fully reversed fatigue behavior exhibited by a carbon fiber/polyimide resin, woven laminate at room and elevated temperatures. Nondestructive video edge view microscopy and destructive sectioning techniques were used to study the microscopic damage mechanisms that evolved. The residual elastic stiffness was monitored and recorded throughout the fatigue life of the coupon. In addition, residual compressive strength tests were conducted on fatigue coupons with various degrees of damage as quantified by stiffness reduction. Experimental results indicated that the monotonic tensile properties were only minimally influenced by temperature, while the monotonic compressive and fully reversed fatigue properties displayed noticeable reductions due to the elevated temperature. The stiffness degradation, as a function of cycles, consisted of three stages; a short-lived high degradation period, a constant degradation rate segment composing the majority of the life, and a final stage demonstrating an increasing rate of degradation up to failure. Concerning the residual compressive strength tests at room and elevated temperatures, the elevated temperature coupons appeared much more sensitive to damage. At elevated temperatures, coupons experienced a much larger loss in compressive strength when compared to room temperature coupons with equivalent damage. The fatigue damage accumulation law proposed for the model incorporates a scalar representation for damage, but admits a multiaxial, anisotropic evolutionary law. The model predicts the current damage (as quantified by residual stiffness) and remnant life of a composite that has undergone a known load at temperature. The damage/life model is dependent on the applied multiaxial stress state as well as temperature. Comparisons between the model and data showed good predictive capabilities concerning stiffness degradation and cycles to failure.

  13. Fundamental studies for life prediction of materials used in spent fuel reprocessing plant

    International Nuclear Information System (INIS)

    Kiuchi, Kiyoshi; Hayashi, Masanori; Hayakawa, Hitoshi; Kikuchi, Masahiko

    1992-01-01

    Fundamental corrosion study and experimental technology development have been made with respect to the life prediction of device materials used in purex type spent fuel reprocessing. Solution chemistry and corrosiveness of nitric acid environments were examined minutely by means of ICP, IC, NO x gas analysis and electrochemical measurements. New testing methods for evaluating corrosion and environmental cracking in nitric acid environments were also developed. The dominant corrosion failure of each candidate material of austenitic stainless steels, zirconium and titanium alloys was examined quantitatively as functions of environmental and metallurgical controlling parameters. (author)

  14. High-temperature creep properties and life predictions for T91 and T92 steels

    Science.gov (United States)

    Pan, J. P.; Tu, S. H.; Sun, G. L.; Zhu, X. W.; Tan, L. J.; Hu, B.

    2018-01-01

    9-11%Cr heat-resistant steels are widely used in high-temperature and high-pressure boilers of advanced power plants. In the current paper, high-temperature creep behaviors of T91 and T92 steels have been investigated. Creep tests were performed for both steels at varied temperatures. The creep mechanisms of T91 and T92 steels were elucidated by analyzing the creep rupture data of the two steels. In addition, Manson-Haferd model was employed to predict the creep life of T91 and T92 steels, the results of which indicate that the Manson-Haferd model works well for the two steels.

  15. New paradigm for prediction of radiation life-time of reactor pressure vessel

    International Nuclear Information System (INIS)

    Kotrechko, S.A.; Meshkov, Yu.Ya.; Neklyudov, I.M.; Revka, V.N.

    2011-01-01

    New paradigm for prediction of radiation life-time of reactor pressure vessel is presented. Equation for limiting state of reactor pressure vessel wall with crack-like defect is obtained. It is exhibited that the value of critical fluence Φ c may be determined not by shift of critical temperature of fracture of surveillance specimen, which is indirect characteristic, but by direct method, namely, by the condition of initiation of brittle fracture of irradiated metal ahead of a crack in RPV wall. Within the framework of engineering version of LA to fracture the technique for Φ c ascertainment is developed. Prediction of Φ c for WWER pressure vessels demonstrates potentialities of this technique.

  16. The Potential United Kingdom Energy Gap and Creep Life Prediction Methodologies

    Science.gov (United States)

    Evans, Mark

    2013-01-01

    The United Kingdom faces a looming energy gap with around 20 pct of its generating capacity due for closure in the next 10 to 15 years as a result of plant age and new European legislation on environmental protection and safety at work. A number of solutions exist for this problem including the use of new materials so that new plants can operate at higher temperatures, new technologies related to carbon capture and gasification, development of renewable resources, and less obviously the use of accurate models for predicting creep life. This article reviews, with illustrations, some of the more applicable and successful creep prediction methodologies used by academics and industrialists and highlights how these techniques can help alleviate the looming energy gap. The role that these approaches can play in solving the energy gap is highlighted throughout.

  17. Microarray-Based Cancer Prediction Using Soft Computing Approach

    Directory of Open Access Journals (Sweden)

    Xiaosheng Wang

    2009-01-01

    Full Text Available One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

  18. CLINICAL DATABASE ANALYSIS USING DMDT BASED PREDICTIVE MODELLING

    Directory of Open Access Journals (Sweden)

    Srilakshmi Indrasenan

    2013-04-01

    Full Text Available In recent years, predictive data mining techniques play a vital role in the field of medical informatics. These techniques help the medical practitioners in predicting various classes which is useful in prediction treatment. One of such major difficulty is prediction of survival rate in breast cancer patients. Breast cancer is a common disease these days and fighting against it is a tough battle for both the surgeons and the patients. To predict the survivability rate in breast cancer patients which helps the medical practitioner to select the type of treatment a predictive data mining technique called Diversified Multiple Decision Tree (DMDT classification is used. Additionally, to avoid difficulties from the outlier and skewed data, it is also proposed to perform the improvement of training space by outlier filtering and over sampling. As a result, this novel approach gives the survivability rate of the cancer patients based on which the medical practitioners can choose the type of treatment.

  19. SARNA-Predict: accuracy improvement of RNA secondary structure prediction using permutation-based simulated annealing.

    Science.gov (United States)

    Tsang, Herbert H; Wiese, Kay C

    2010-01-01

    Ribonucleic acid (RNA), a single-stranded linear molecule, is essential to all biological systems. Different regions of the same RNA strand will fold together via base pair interactions to make intricate secondary and tertiary structures that guide crucial homeostatic processes in living organisms. Since the structure of RNA molecules is the key to their function, algorithms for the prediction of RNA structure are of great value. In this article, we demonstrate the usefulness of SARNA-Predict, an RNA secondary structure prediction algorithm based on Simulated Annealing (SA). A performance evaluation of SARNA-Predict in terms of prediction accuracy is made via comparison with eight state-of-the-art RNA prediction algorithms: mfold, Pseudoknot (pknotsRE), NUPACK, pknotsRG-mfe, Sfold, HotKnots, ILM, and STAR. These algorithms are from three different classes: heuristic, dynamic programming, and statistical sampling techniques. An evaluation for the performance of SARNA-Predict in terms of prediction accuracy was verified with native structures. Experiments on 33 individual known structures from eleven RNA classes (tRNA, viral RNA, antigenomic HDV, telomerase RNA, tmRNA, rRNA, RNaseP, 5S rRNA, Group I intron 23S rRNA, Group I intron 16S rRNA, and 16S rRNA) were performed. The results presented in this paper demonstrate that SARNA-Predict can out-perform other state-of-the-art algorithms in terms of prediction accuracy. Furthermore, there is substantial improvement of prediction accuracy by incorporating a more sophisticated thermodynamic model (efn2).

  20. Deep-Learning-Based Approach for Prediction of Algal Blooms

    Directory of Open Access Journals (Sweden)

    Feng Zhang

    2016-10-01

    Full Text Available Algal blooms have recently become a critical global environmental concern which might put economic development and sustainability at risk. However, the accurate prediction of algal blooms remains a challenging scientific problem. In this study, a novel prediction approach for algal blooms based on deep learning is presented—a powerful tool to represent and predict highly dynamic and complex phenomena. The proposed approach constructs a five-layered model to extract detailed relationships between the density of phytoplankton cells and various environmental parameters. The algal blooms can be predicted by the phytoplankton density obtained from the output layer. A case study is conducted in coastal waters of East China using both our model and a traditional back-propagation neural network for comparison. The results show that the deep-learning-based model yields better generalization and greater accuracy in predicting algal blooms than a traditional shallow neural network does.

  1. Disability but not social support predicts cognitive deterioration in late-life depression.

    Science.gov (United States)

    Riddle, Meghan; McQuoid, Douglas R; Potter, Guy G; Steffens, David C; Taylor, Warren D

    2015-05-01

    Depression in late life is a risk factor for cognitive decline. Depression is also associated with increased disability and social support deficits; these may precede conversion to dementia and inform risk. In this study, we examined if baseline or one-year change in disability and social support predicted later cognitive deterioration. 299 cognitively intact depressed older adults were followed for an average of approximately seven years. Participants received antidepressant treatment according to a standardized algorithm. Neuropsychological testing and assessment of disability and social support were assessed annually. Cognitive diagnosis was reviewed annually at a consensus conference to determine if participants remained cognitively normal, or if they progressed to either dementia or cognitively impaired, no dementia (CIND). During study participation, 167 individuals remained cognitively normal (56%), 83 progressed to CIND (28%), and 49 progressed to dementia (16%). Greater baseline instrumental activities of daily living (IADL) deficits predicted subsequent conversion to a cognitive diagnosis (CIND or dementia). However, neither baseline measures nor one-year change in basic ADLs (BADLs) and social support predicted cognitive conversion. In post hoc analyses, two IADL measures (managing finances, preparing meals) significantly increased the odds of cognitive conversion. Greater IADL deficits predicted increased risk of cognitive conversion. Assessment of IADL deficits may provide clues about risk of later cognitive decline.

  2. Adolescent inpatient girls׳ report of dependent life events predicts prospective suicide risk.

    Science.gov (United States)

    Stone, Lindsey B; Liu, Richard T; Yen, Shirley

    2014-09-30

    Adolescents with a history of suicidal behavior are especially vulnerable for future suicide attempts, particularly following discharge from an inpatient psychiatric admission. This study is the first to test whether adolescents׳ tendency to generate stress, or report more dependent events to which they contributed, was predictive of prospective suicide events. Ninety adolescent psychiatric inpatients who were admitted for recent suicide risk, completed diagnostic interviews, assessments of history of suicidal behavior, and a self-report questionnaire of major life events at baseline. Participants were followed over the subsequent 6 months after discharge to assess stability vs. onset of suicide events. Cox proportional hazard regressions were used to predict adolescents׳ time to suicide events. Results supported hypothesis, such that only recent greater dependent events, not independent or overall events, predicted risk for prospective suicide events. This effect was specific to adolescent girls. Importantly, dependent events maintained statistical significance as a predictor of future suicide events after co-varying for the effects of several established risk factors and psychopathology. Results suggest that the tendency to generate dependent events may contribute unique additional prediction for adolescent girls׳ prospective suicide risk, and highlight the need for future work in this area. Published by Elsevier Ireland Ltd.

  3. Genomic biomarkers of prenatal intrauterine inflammation in umbilical cord tissue predict later life neurological outcomes.

    Directory of Open Access Journals (Sweden)

    Sloane K Tilley

    Full Text Available Preterm birth is a major risk factor for neurodevelopmental delays and disorders. This study aimed to identify genomic biomarkers of intrauterine inflammation in umbilical cord tissue in preterm neonates that predict cognitive impairment at 10 years of age.Genome-wide messenger RNA (mRNA levels from umbilical cord tissue were obtained from 43 neonates born before 28 weeks of gestation. Genes that were differentially expressed across four indicators of intrauterine inflammation were identified and their functions examined. Exact logistic regression was used to test whether expression levels in umbilical cord tissue predicted neurocognitive function at 10 years of age.Placental indicators of inflammation were associated with changes in the mRNA expression of 445 genes in umbilical cord tissue. Transcripts with decreased expression showed significant enrichment for biological signaling processes related to neuronal development and growth. The altered expression of six genes was found to predict neurocognitive impairment when children were 10 years old These genes include two that encode for proteins involved in neuronal development.Prenatal intrauterine inflammation is associated with altered gene expression in umbilical cord tissue. A set of six of the differentially expressed genes predict cognitive impairment later in life, suggesting that the fetal environment is associated with significant adverse effects on neurodevelopment that persist into later childhood.

  4. Reliability prediction for condition-based maintained systems

    Energy Technology Data Exchange (ETDEWEB)

    Saranga, H.; Knezevic, J

    2001-02-01

    The paper presents a methodology based on relevant condition predictor (RCP) for reliability prediction for systems under condition-based maintenance. By considering the event of not being able to recognise the fault initiation or the critical state in RCP-based maintenance, the methodology uses Markov models for reliability prediction. The cases of single and multiple relevant condition predictors are presented along with a numerical procedure to obtain the reliability functions for RCP-based maintained systems. Numerical examples are used to illustrate the methodology and the values of reliability are obtained at discrete time points using the numerical algorithm.

  5. Degradation Prediction Model Based on a Neural Network with Dynamic Windows

    Science.gov (United States)

    Zhang, Xinghui; Xiao, Lei; Kang, Jianshe

    2015-01-01

    Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully researched, but for some high reliability components, it is very difficult to collect run-to-failure condition monitoring data, i.e., from normal to failure. Only a certain number of condition indicators in certain period can be used to estimate RUL. In addition, some existing prediction methods have problems which block RUL estimation due to poor extrapolability. The predicted value converges to a certain constant or fluctuates in certain range. Moreover, the fluctuant condition features also have bad effects on prediction. In order to solve these dilemmas, this paper proposes a RUL prediction model based on neural network with dynamic windows. This model mainly consists of three steps: window size determination by increasing rate, change point detection and rolling prediction. The proposed method has two dominant strengths. One is that the proposed approach does not need to assume the degradation trajectory is subject to a certain distribution. The other is it can adapt to variation of degradation indicators which greatly benefits RUL prediction. Finally, the performance of the proposed RUL prediction model is validated by real field data and simulation data. PMID:25806873

  6. Uncertainties in model-based outcome predictions for treatment planning

    International Nuclear Information System (INIS)

    Deasy, Joseph O.; Chao, K.S. Clifford; Markman, Jerry

    2001-01-01

    Purpose: Model-based treatment-plan-specific outcome predictions (such as normal tissue complication probability [NTCP] or the relative reduction in salivary function) are typically presented without reference to underlying uncertainties. We provide a method to assess the reliability of treatment-plan-specific dose-volume outcome model predictions. Methods and Materials: A practical method is proposed for evaluating model prediction based on the original input data together with bootstrap-based estimates of parameter uncertainties. The general framework is applicable to continuous variable predictions (e.g., prediction of long-term salivary function) and dichotomous variable predictions (e.g., tumor control probability [TCP] or NTCP). Using bootstrap resampling, a histogram of the likelihood of alternative parameter values is generated. For a given patient and treatment plan we generate a histogram of alternative model results by computing the model predicted outcome for each parameter set in the bootstrap list. Residual uncertainty ('noise') is accounted for by adding a random component to the computed outcome values. The residual noise distribution is estimated from the original fit between model predictions and patient data. Results: The method is demonstrated using a continuous-endpoint model to predict long-term salivary function for head-and-neck cancer patients. Histograms represent the probabilities for the level of posttreatment salivary function based on the input clinical data, the salivary function model, and the three-dimensional dose distribution. For some patients there is significant uncertainty in the prediction of xerostomia, whereas for other patients the predictions are expected to be more reliable. In contrast, TCP and NTCP endpoints are dichotomous, and parameter uncertainties should be folded directly into the estimated probabilities, thereby improving the accuracy of the estimates. Using bootstrap parameter estimates, competing treatment

  7. A predictive model of health-related quality of life in young adult survivors of childhood cancer

    NARCIS (Netherlands)

    Maurice-Stam, H.; Oort, F.J.; Last, B.F.; Grootenhuis, M.A.

    2009-01-01

    MAURICE-STAM H., OORT F.J., LAST B.F. & GROOTENHUIS M.A. (2009) European Journal of Cancer Care 18, 339-349A predictive model of health-related quality of life in young adult survivors of childhood cancer This study aimed to examine factors that affect survivors' health-related quality of life

  8. NAPR: a Cloud-Based Framework for Neuroanatomical Age Prediction.

    Science.gov (United States)

    Pardoe, Heath R; Kuzniecky, Ruben

    2018-01-01

    The availability of cloud computing services has enabled the widespread adoption of the "software as a service" (SaaS) approach for software distribution, which utilizes network-based access to applications running on centralized servers. In this paper we apply the SaaS approach to neuroimaging-based age prediction. Our system, named "NAPR" (Neuroanatomical Age Prediction using R), provides access to predictive modeling software running on a persistent cloud-based Amazon Web Services (AWS) compute instance. The NAPR framework allows external users to estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. As a demonstration of the NAPR approach, we have developed two age prediction models that were trained using healthy control data from the ABIDE, CoRR, DLBS and NKI Rockland neuroimaging datasets (total N = 2367, age range 6-89 years). The provided age prediction models were trained using (i) relevance vector machines and (ii) Gaussian processes machine learning methods applied to cortical thickness surfaces obtained using Freesurfer v5.3. We believe that this transparent approach to out-of-sample evaluation and comparison of neuroimaging age prediction models will facilitate the development of improved age prediction models and allow for robust evaluation of the clinical utility of these methods.

  9. Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus.

    Directory of Open Access Journals (Sweden)

    Pamella Akoth Ogada

    Full Text Available Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant, as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.

  10. Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus.

    Science.gov (United States)

    Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

    2016-01-01

    Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.

  11. Hospital at home: home-based end of life care

    Science.gov (United States)

    Shepperd, Sasha; Wee, Bee; Straus, Sharon E

    2014-01-01

    Background The policy in a number of countries is to provide people with a terminal illness the choice of dying at home. This policy is supported by surveys indicating that the general public and patients with a terminal illness would prefer to receive end of life care at home. Objectives To determine if providing home-based end of life care reduces the likelihood of dying in hospital and what effect this has on patients’ symptoms, quality of life, health service costs and care givers compared with inpatient hospital or hospice care. Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library) to October 2009, Ovid MED-LINE(R) 1950 to March 2011, EMBASE 1980 to October 2009, CINAHL 1982 to October 2009 and EconLit to October 2009. We checked the reference lists of articles identified for potentially relevant articles. Selection criteria Randomised controlled trials, interrupted time series or controlled before and after studies evaluating the effectiveness of home-based end of life care with inpatient hospital or hospice care for people aged 18 years and older. Data collection and analysis Two authors independently extracted data and assessed study quality. We combined the published data for dichotomous outcomes using fixed-effect Mantel-Haenszel meta-analysis. When combining outcome data was not possible we presented the data in narrative summary tables. Main results We included four trials in this review. Those receiving home-based end of life care were statistically significantly more likely to die at home compared with those receiving usual care (RR 1.33, 95% CI 1.14 to 1.55, P = 0.0002; Chi 2 = 1.72, df = 2, P = 0.42, I2 = 0% (three trials; N=652)). We detected no statistically significant differences for functional status (measured by the Barthel Index), psychological well-being or cognitive status, between patients receiving home-based end of life care compared with those receiving standard care (which

  12. Towards evaluation and prediction of building sustainability using life cycle behaviour simulation

    Directory of Open Access Journals (Sweden)

    Marzouk Mohamed

    2017-01-01

    Full Text Available Nowadays researchers and practitioners are oriented towards questioning how effective are the different building life cycle activities contribution to preserving the environment and fulfilling the need for equilibrium. Terminologies such as Building sustainability and Green Buildings have long been adopted yet the evaluation of such has been driven through the use of rating systems. LEED of the United States, BREEAM of the United Kingdom, and Pearl of the United Arab Emirates are namely good examples of these rating systems. This paper introduces a new approach for evaluation of building life cycle sustainability through simulation of activities interaction and studying its behaviour. The effort focuses on comprehending impact and effect of suitability related activities over the whole building life cycle or period of time. The methodology includes gathering a pool of parameters through benchmarking of five selected rating systems, analytical factorization for the gathered parameters is used to elect the most influencing parameters. Followed by simulation modelling using System dynamics to capture the interaction of the considered parameters. The resulting behaviour obtained from simulation is studied and used in designing a tool for prediction of sustainability.

  13. In your eyes: does theory of mind predict impaired life functioning in bipolar disorder?

    Science.gov (United States)

    Purcell, Amanda L; Phillips, Mary; Gruber, June

    2013-12-01

    Deficits in emotion perception and social functioning are strongly implicated in bipolar disorder (BD). Examining theory of mind (ToM) may provide one potential mechanism to explain observed socio-emotional impairments in this disorder. The present study prospectively investigated the relationship between theory of mind performance and life functioning in individuals diagnosed with BD compared to unipolar depression and healthy control groups. Theory of mind (ToM) performance was examined in 26 individuals with remitted bipolar I disorder (BD), 29 individuals with remitted unipolar depression (UD), and 28 healthy controls (CTL) using a well-validated advanced theory of mind task. Accuracy and response latency scores were calculated from the task. Life functioning was measured during a 12 month follow-up session. No group differences for ToM accuracy emerged. However, the BD group exhibited significantly shorter response times than the UD and CTL groups. Importantly, quicker response times in the BD group predicted greater life functioning impairment at a 12-month follow-up, even after controlling for baseline symptoms. The stimuli were static representations of emotional states and do not allow for evaluating the appropriateness of context during emotional communication; due to sample size, neither specific comorbidities nor medication effects were analyzed for the BD and UD groups; preliminary status of theory of mind as a construct. Results suggest that quickened socio-emotional decision making may represent a risk factor for future functional impairment in BD. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. Life history predicts risk of species decline in a stochastic world.

    Science.gov (United States)

    Van Allen, Benjamin G; Dunham, Amy E; Asquith, Christopher M; Rudolf, Volker H W

    2012-07-07

    Understanding what traits determine the extinction risk of species has been a long-standing challenge. Natural populations increasingly experience reductions in habitat and population size concurrent with increasing novel environmental variation owing to anthropogenic disturbance and climate change. Recent studies show that a species risk of decline towards extinction is often non-random across species with different life histories. We propose that species with life histories in which all stage-specific vital rates are more evenly important to population growth rate may be less likely to decline towards extinction under these pressures. To test our prediction, we modelled declines in population growth rates under simulated stochastic disturbance to the vital rates of 105 species taken from the literature. Populations with more equally important vital rates, determined using elasticity analysis, declined more slowly across a gradient of increasing simulated environmental variation. Furthermore, higher evenness of elasticity was significantly correlated with a reduced chance of listing as Threatened on the International Union for Conservation of Nature Red List. The relative importance of life-history traits of diverse species can help us infer how natural assemblages will be affected by novel anthropogenic and climatic disturbances.

  15. Sleep quality subtypes predict health-related quality of life in children.

    Science.gov (United States)

    Magee, Christopher A; Robinson, Laura; Keane, Carol

    2017-07-01

    This paper aimed to investigate whether distinct sleep quality subtypes predicted health-related quality of life in a nonclinical sample of children. This paper utilized data from two waves of the Longitudinal Study of Australian Children, a cohort study that follows a representative population of children in Australia. This paper examined data from Waves 4 and 5 of the LSAC (covering the period 2010-2012) and included 3974 children aged 10-11 years at Wave 4 (51.4% male). Multiple dimensions of sleep quality were assessed using a combination of child- and parent-reported measures. Health-related quality of life (HRQOL) was assessed through the Pediatric Quality of Life Inventory. Latent class analysis indicated six distinct sleep quality classes in children, namely good sleep, moderate sleep quality, mild sleep disturbances, short sleep, long sleep, and disordered sleep. In general, the disordered sleep and minor sleep disturbance classes had poorer HRQOL, which worsened over time. The long sleep and moderate sleep quality classes also showed some decreases in HRQOL over time. This study demonstrates that there are distinct sleep quality subtypes in children that could have implications for HRQOL. These findings may inform future strategies to promote improved sleep and HRQOL in children. Copyright © 2017. Published by Elsevier B.V.

  16. REMAINING LIFE TIME PREDICTION OF BEARINGS USING K-STAR ALGORITHM – A STATISTICAL APPROACH

    Directory of Open Access Journals (Sweden)

    R. SATISHKUMAR

    2017-01-01

    Full Text Available The role of bearings is significant in reducing the down time of all rotating machineries. The increasing trend of bearing failures in recent times has triggered the need and importance of deployment of condition monitoring. There are multiple factors associated to a bearing failure while it is in operation. Hence, a predictive strategy is required to evaluate the current state of the bearings in operation. In past, predictive models with regression techniques were widely used for bearing lifetime estimations. The Objective of this paper is to estimate the remaining useful life of bearings through a machine learning approach. The ultimate objective of this study is to strengthen the predictive maintenance. The present study was done using classification approach following the concepts of machine learning and a predictive model was built to calculate the residual lifetime of bearings in operation. Vibration signals were acquired on a continuous basis from an experiment wherein the bearings are made to run till it fails naturally. It should be noted that the experiment was carried out with new bearings at pre-defined load and speed conditions until the bearing fails on its own. In the present work, statistical features were deployed and feature selection process was carried out using J48 decision tree and selected features were used to develop the prognostic model. The K-Star classification algorithm, a supervised machine learning technique is made use of in building a predictive model to estimate the lifetime of bearings. The performance of classifier was cross validated with distinct data. The result shows that the K-Star classification model gives 98.56% classification accuracy with selected features.

  17. Predicting the risk of physical disability in old age using modifiable mid-life risk factors.

    Science.gov (United States)

    Wong, Evelyn; Stevenson, Christopher; Backholer, Kathryn; Woodward, Mark; Shaw, Jonathan E; Peeters, Anna

    2015-01-01

    We aimed to investigate the relationship between potentially modifiable risk factors in middle age and disability after 13 years using the Framingham Offspring Study (FOS). We further aimed to develop a disability risk algorithm to estimate the risk of future disability for those aged 45-65 years. FOS is a longitudinal study. We used examination 5 (1991-1995; 'baseline') and examination 8 (2005-2008; 'follow-up'). We included participants aged between 45-65 years at 'baseline' with complete predictor and outcome measures (n=2031; mean age 53.9 years). Predictors considered were body mass index, smoking, hypertension, diabetes and dyslipidaemia. We used multinomial logistic regression to identify predictors of disability or death.We assessed external validity using Australian data. By examination 8, 156 participants had disability and 198 had died. Disability was associated with smoking (OR (95% CI) 1.81 (1.18 to 2.78)); obesity (2.95 (1.83 to 4.77)); diabetes 1.96 (1.11 to 3.45) and being female (OR 1.67 (1.13 to 2.45). The model performed moderately well in predicting disability and death in an Australian population. Based on our algorithm, a 45-year-old man/woman with the combined risk factors of obesity, diabetes and smoking has similar likelihood of surviving free of disability to a 65-year-old man/woman without any of the same risk factors. The derived risk algorithm allows, for the first time, quantification of the substantial combined impact on future disability of key modifiable risk factors in mid-life. Here we demonstrated the combined impact of obesity, diabetes and smoking to be similar to 20 years of aging. 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.

  18. A Review of Quality of Life after Predictive Testing for and Earlier Identification of Neurodegenerative Diseases

    Science.gov (United States)

    Paulsen, Jane S.; Nance, Martha; Kim, Ji-In; Carlozzi, Noelle E.; Panegyres, Peter K.; Erwin, Cheryl; Goh, Anita; McCusker, Elizabeth; Williams, Janet K.

    2013-01-01

    The past decade has witnessed an explosion of evidence suggesting that many neurodegenerative diseases can be detected years, if not decades, earlier than previously thought. To date, these scientific advances have not provoked any parallel translational or clinical improvements. There is an urgency to capitalize on this momentum so earlier detection of disease can be more readily translated into improved health-related quality of life for families at risk for, or suffering with, neurodegenerative diseases. In this review, we discuss health-related quality of life (HRQOL) measurement in neurodegenerative diseases and the importance of these “patient reported outcomes” for all clinical research. Next, we address HRQOL following early identification or predictive genetic testing in some neurodegenerative diseases: Huntington disease, Alzheimer's disease, Parkinson's disease, Dementia with Lewy bodies, frontotemporal dementia, amyotrophic lateral sclerosis, prion diseases, hereditary ataxias, Dentatorubral-pallidoluysian atrophy and Wilson's disease. After a brief report of available direct-to-consumer genetic tests, we address the juxtaposition of earlier disease identification with assumed reluctance towards predictive genetic testing. Forty-one studies examining health related outcomes following predictive genetic testing for neurodegenerative disease suggested that (a) extreme or catastrophic outcomes are rare; (b) consequences commonly include transiently increased anxiety and/or depression; (c) most participants report no regret; (d) many persons report extensive benefits to receiving genetic information; and (e) stigmatization and discrimination for genetic diseases are poorly understood and policy and laws are needed. Caution is appropriate for earlier identification of neurodegenerative diseases but findings suggest further progress is safe, feasible and likely to advance clinical care. PMID:24036231

  19. Bayesian probabilistic model for life prediction and fault mode classification of solid state luminaires

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep [Auburn Univ., Auburn, AL (United States); Wei, Junchao [Auburn Univ., Auburn, AL (United States); Sakalaukus, Peter [Auburn Univ., Auburn, AL (United States)

    2014-06-22

    A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminous flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

  20. Implementation of neural network based non-linear predictive control

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1999-01-01

    This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...

  1. Implementation of neural network based non-linear predictive

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non-linear...... systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi...

  2. Structural reliability benchmark exercise for primary-circuit components life prediction methods

    International Nuclear Information System (INIS)

    Lehrke, H.P.

    1989-09-01

    Results of NDT inspections, crack growth data taken from small specimens, and results of stress calculation together with a load time history are used to predict the growth to failure of defects intentionally introduced into the welds of a 1/5 scale pressure vessel. The prediction results are compared with further NDT results taken during the fatigue test. Analysing the discrepancies between the analytical and the test results, the question, how to define an equivalent crack to each detected defect, is found to be the weakest link in the procedure of crack growth and life prediction. The NDT results differ considerably from one inspection to another and contain only the positions and sizes of the defects but no information on the shape and whether a defect is crack-like or not. Therefore it is necessary to define equivalent cracks with assumed shapes e.g. elliptical, and to take into account an incubation time of crack initiation at the blunt (instead of sharp) edges of the defects. However, NDT gives no information to set up the necessary calculation parameters, especially for the decision, whether a defect of critical size will start to grow immediately when in-service, after a short (or long) incubation time, or never

  3. Life histories of hosts and pathogens predict patterns in tropical fungal plant diseases.

    Science.gov (United States)

    García-Guzmán, Graciela; Heil, Martin

    2014-03-01

    Plant pathogens affect the fitness of their hosts and maintain biodiversity. However, we lack theories to predict the type and intensity of infections in wild plants. Here we demonstrate using fungal pathogens of tropical plants that an examination of the life histories of hosts and pathogens can reveal general patterns in their interactions. Fungal infections were more commonly reported for light-demanding than for shade-tolerant species and for evergreen rather than for deciduous hosts. Both patterns are consistent with classical defence theory, which predicts lower resistance in fast-growing species and suggests that the deciduous habit can reduce enemy populations. In our literature survey, necrotrophs were found mainly to infect shade-tolerant woody species whereas biotrophs dominated in light-demanding herbaceous hosts. Far-red signalling and its inhibitory effects on jasmonic acid signalling are likely to explain this phenomenon. Multiple changes between the necrotrophic and the symptomless endophytic lifestyle at the ecological and evolutionary scale indicate that endophytes should be considered when trying to understand large-scale patterns in the fungal infections of plants. Combining knowledge about the molecular mechanisms of pathogen resistance with classical defence theory enables the formulation of testable predictions concerning general patterns in the infections of wild plants by fungal pathogens. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  4. Life-history traits and landscape characteristics predict macro-moth responses to forest fragmentation.

    Science.gov (United States)

    Slade, Eleanor M; Merckx, Thomas; Riutta, Terhi; Bebber, Daniel P; Redhead, David; Riordan, Philip; Macdonald, David W

    2013-07-01

    How best to manage forest patches, mitigate the consequences of forest fragmentation, and enable landscape permeability are key questions facing conservation scientists and managers. Many temperate forests have become increasingly fragmented, resulting in reduced interior forest habitat, increased edge habitats, and reduced connectivity. Using a citizen science landscape-scale mark-release-recapture study on 87 macro-moth species, we investigated how both life-history traits and landscape characteristics predicted macro-moth responses to forest fragmentation. Wingspan, wing shape, adult feeding, and larval feeding guild predicted macro-moth mobility, although the predictive power of wingspan and wing shape depended on the species' affinity to the forest. Solitary trees and small fragments functioned as "stepping stones," especially when their landscape connectivity was increased, by being positioned within hedgerows or within a favorable matrix. Mobile forest specialists were most affected by forest fragmentation: despite their high intrinsic dispersal capability, these species were confined mostly to the largest of the forest patches due to their strong affinity for the forest habitat, and were also heavily dependent on forest connectivity in order to cross the agricultural matrix. Forest fragments need to be larger than five hectares and to have interior forest more than 100 m from the edge in order to sustain populations of forest specialists. Our study provides new insights into the movement patterns of a functionally important insect group, with implications for the landscape-scale management of forest patches within agricultural landscapes.

  5. Recent developments on SMA actuators: predicting the actuation fatigue life for variable loading schemes

    Science.gov (United States)

    Wheeler, Robert W.; Lagoudas, Dimitris C.

    2017-04-01

    Shape memory alloys (SMAs), due to their ability to repeatably recover substantial deformations under applied mechanical loading, have the potential to impact the aerospace, automotive, biomedical, and energy industries as weight and volume saving replacements for conventional actuators. While numerous applications of SMA actuators have been flight tested and can be found in industrial applications, these actuators are generally limited to non-critical components, are not widely implemented and frequently one-off designs, and are generally overdesigned due to a lack of understanding of the effect of the loading path on the fatigue life and the lack of an accurate method for predicting actuator lifetimes. In recent years, multiple research efforts have increased our understanding of the actuation fatigue process of SMAs. These advances can be utilized to predict the fatigue lives and failure loads in SMA actuators. Additionally, these prediction methods can be implemented in order to intelligently design actuators in accordance with their fatigue and failure limits. In the following paper, both simple and complex thermomechanical loading paths have been considered. Experimental data was utilized from two material systems: equiatomic Nickel-Titanium and Nickelrich Nickel-Titanium.

  6. Negative fateful life events in midlife and advanced predicted brain aging.

    Science.gov (United States)

    Hatton, Sean N; Franz, Carol E; Elman, Jeremy A; Panizzon, Matthew S; Hagler, Donald J; Fennema-Notestine, Christine; Eyler, Lisa T; McEvoy, Linda K; Lyons, Michael J; Dale, Anders M; Kremen, William S

    2018-03-08

    Negative fateful life events (FLEs) such as interpersonal conflict, death in the family, financial hardship, and serious medical emergencies can act as allostatic stressors that accelerate biological aging. However, the relationship between FLEs and neuroanatomical aging is not well understood. We examined 359 men (mean age 62 years) participating in the Vietnam Era twin study of aging (VETSA) to determine whether negative midlife FLEs are associated with advanced brain aging after controlling for physical, psychological, and lifestyle factors. At two different time points, participants were assessed for negative FLEs, health and well-being, general cognitive ability, socioeconomic status, depression, and ethnicity. Participants underwent a magnetic resonance imaging examination, and T1-weighted images were processed with FreeSurfer. Subsequent neuroanatomical measurements were entered into the Brain-Age Regression Analysis and Computation Utility software (BARACUS) to predict brain age. Having more midlife FLEs, particularly relating to interpersonal relationships, was associated with advanced predicted brain aging (i.e., higher predicted brain age relative to chronological age). This association remained after controlling for the significant covariates of alcohol consumption, cardiovascular risk, adult socioeconomic status, and ethnicity. Copyright © 2018 Elsevier Inc. All rights reserved.

  7. Fatigue life prediction of casing welded pipes by using the extended finite element method

    Directory of Open Access Journals (Sweden)

    Ljubica Lazić Vulićević

    2016-03-01

    Full Text Available The extended finite element (XFEM method has been used to simulate fatigue crack growth in casing pipe, made of API J55 steel by high-frequency welding, in order estimate its structural integrity and life. Based on the critical value of stress intensity factor KIc, measured in different regions of welded joint, the crack was located in the base metal as the region with the lowest resistance to crack initiation and propagation. The XFEM was first applied to the 3 point bending specimens to verify numerical results with the experimental ones. After successful verification, the XFEM was used to simulate fatigue crack growth, position axially in the pipe, and estimate its remaining life.

  8. Life-Stage Physiologically-Based Pharmacokinetic (PBPK) ...

    Science.gov (United States)

    This presentation discusses methods used to extrapolate from in vitro high-throughput screening (HTS) toxicity data for an endocrine pathway to in vivo for early life stages in humans, and the use of a life stage PBPK model to address rapidly changing physiological parameters. Adverse outcome pathways (AOPs), in this case endocrine disruption during development, provide a biologically-based framework for linking molecular initiating events triggered by chemical exposures to key events leading to adverse outcomes. The application of AOPs to human health risk assessment requires extrapolation of in vitro HTS toxicity data to in vivo exposures (IVIVE) in humans, which can be achieved through the use of a PBPK/PD model. Exposure scenarios for chemicals in the PBPK/PD model will consider both placental and lactational transfer of chemicals, with a focus on age dependent dosimetry during fetal development and after birth for a nursing infant. This talk proposes a universal life-stage computational model that incorporates changing physiological parameters to link environmental exposures to in vitro levels of HTS assays related to a developmental toxicological AOP for vascular disruption. In vitro toxicity endpoints discussed are based on two mechanisms: 1) Fetal vascular disruption, and 2) Neurodevelopmental toxicity induced by altering thyroid hormone levels in neonates via inhibition of thyroperoxidase in the thyroid gland. Application of our Life-stage computati

  9. Dynamic prediction technology for gas based on data fusion theory

    Energy Technology Data Exchange (ETDEWEB)

    Shao, Liang-shan; Fu, Gui-xiang [Liaoning Technical University, Fuxin (China). Institute of System Engineering

    2008-05-15

    A new method was presented based on the fusion method, using Bayesian analysis and self-adapting weighted data to process information and fuse data. It used the Dempster-Shafer evidence theory to deal with the uncertainty produced in gas prediction. It comprehensively considered the gas concentration and other related parameters and realized the optimization and integration of gas measurement and predicted parameters. This method improves the accuracy of gas detection systems for coal mines. 15 refs., 1 fig., 1 tab.

  10. Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

    Directory of Open Access Journals (Sweden)

    Milan Vukićević

    2014-01-01

    Full Text Available Rapid growth and storage of biomedical data enabled many opportunities for predictive modeling and improvement of healthcare processes. On the other side analysis of such large amounts of data is a difficult and computationally intensive task for most existing data mining algorithms. This problem is addressed by proposing a cloud based system that integrates metalearning framework for ranking and selection of best predictive algorithms for data at hand and open source big data technologies for analysis of biomedical data.

  11. Accurate Multisteps Traffic Flow Prediction Based on SVM

    Directory of Open Access Journals (Sweden)

    Zhang Mingheng

    2013-01-01

    Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

  12. Belief-based action prediction in preverbal infants.

    Science.gov (United States)

    Southgate, Victoria; Vernetti, Angelina

    2014-01-01

    Successful mindreading entails both the ability to think about what others know or believe, and to use this knowledge to generate predictions about how mental states will influence behavior. While previous studies have demonstrated that young infants are sensitive to others' mental states, there continues to be much debate concerning how to characterize early theory of mind abilities. In the current study, we asked whether 6-month-old infants appreciate the causal role that beliefs play in action. Specifically, we tested whether infants generate action predictions that are appropriate given an agent's current belief. We exploited a novel, neural indication of action prediction: motor cortex activation as measured by sensorimotor alpha suppression, to ask whether infants would generate differential predictions depending on an agent's belief. After first verifying our paradigm and measure with a group of adult participants, we found that when an agent had a false belief that a ball was in the box, motor activity indicated that infants predicted she would reach for the box, but when the agent had a false belief that a ball was not in the box, infants did not predict that she would act. In both cases, infants based their predictions on what the agent, rather than the infant, believed to be the case, suggesting that by 6months of age, infants can exploit their sensitivity to other minds for action prediction. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

  13. Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model

    Directory of Open Access Journals (Sweden)

    Jingzhou Xin

    2018-01-01

    Full Text Available Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA, and generalized autoregressive conditional heteroskedasticity (GARCH. Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS deformation monitoring system demonstrated that: (1 the Kalman filter is capable of denoising the bridge deformation monitoring data; (2 the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3 in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity; the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data

  14. Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.

    Science.gov (United States)

    Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu

    2018-01-19

    Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing

  15. Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows

    Science.gov (United States)

    Huber, K.; Dänicke, S.; Rehage, J.; Sauerwein, H.; Otto, W.; Rolle-Kampczyk, U.; von Bergen, M.

    2016-01-01

    The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life. PMID:27089826

  16. The effect of genealogy-based haplotypes on genomic prediction

    DEFF Research Database (Denmark)

    Edriss, Vahid; Fernando, Rohan L.; Su, Guosheng

    2013-01-01

    on haplotypes instead of regression on individual markers. The aim of this study was to investigate the accuracy of genomic prediction using haplotypes based on local genealogy information. Methods A total of 4429 Danish Holstein bulls were genotyped with the 50K SNP chip. Haplotypes were constructed using...... local genealogical trees. Effects of haplotype covariates were estimated with two types of prediction models: (1) assuming that effects had the same distribution for all haplotype covariates, i.e. the GBLUP method and (2) assuming that a large proportion (pi) of the haplotype covariates had zero effect......, i.e. a Bayesian mixture method. Results About 7.5 times more covariate effects were estimated when fitting haplotypes based on local genealogical trees compared to fitting individuals markers. Genealogy-based haplotype clustering slightly increased the accuracy of genomic prediction and, in some...

  17. An IoT Based Predictive Connected Car Maintenance Approach

    Directory of Open Access Journals (Sweden)

    Rohit Dhall

    2017-03-01

    Full Text Available Internet of Things (IoT is fast emerging and becoming an almost basic necessity in general life. The concepts of using technology in our daily life is not new, but with the advancements in technology, the impact of technology in daily activities of a person can be seen in almost all the aspects of life. Today, all aspects of our daily life, be it health of a person, his location, movement, etc. can be monitored and analyzed using information captured from various connected devices. This paper discusses one such use case, which can be implemented by the automobile industry, using technological advancements in the areas of IoT and Analytics. ‘Connected Car’ is a terminology, often associated with cars and other passenger vehicles, which are capable of internet connectivity and sharing of various kinds of data with backend applications. The data being shared can be about the location and speed of the car, status of various parts/lubricants of the car, and if the car needs urgent service or not. Once data are transmitted to the backend services, various workflows can be created to take necessary actions, e.g. scheduling a service with the car service provider, or if large numbers of care are in the same location, then the traffic management system can take necessary action. ’Connected cars’ can also communicate with each other, and can send alerts to each other in certain scenarios like possible crash etc. This paper talks about how the concept of ‘connected cars’ can be used to perform ‘predictive car maintenance’. It also discusses how certain technology components, i.e., Eclipse Mosquito and Eclipse Paho can be used to implement a predictive connected car use case.

  18. Response Surface Approximation for Fatigue Life Prediction and Its Application to Multi-Criteria Optimization With a Priori Preference Information

    International Nuclear Information System (INIS)

    Baek, Seok Heum; Joo, Won Sik; Cho, Seok Swoo

    2009-01-01

    In this paper, a versatile multi-criteria optimization concept for fatigue life prediction is introduced. Multi-criteria decision making in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Compromise decision support problems are used to model engineering decisions involving multiple trade-offs. These methods typically rely on a summation of weighted attributes to accomplish trade-offs among competing objectives. This paper gives an interpretation of the decision parameters as governing both the relative importance of the attributes and the degree of compensation between them. The approach utilizes a response surface model, the compromise decision support problem, which is a multi-objective formulation based on goal programming. Examples illustrate the concepts and demonstrate their applicability

  19. Life Cycle Assessment of Paper Based Printed Circuits

    OpenAIRE

    Wan, Qiansu

    2017-01-01

    Printed circuit boards have been massively manufactured and wildly used in all kinds of electronic devices during people’s daily life for more than thirty years since the last century. As a highly integrated device mainly consists of silicon base, an etched copper layer and other soldered components, massive production of printed circuit boards are considered to be environmentally unfriendly due to the wet chemical manufacturing mode and lack of recycling ability. On the other hand, the newly...

  20. Life management of power plant based on structural damage testing

    Energy Technology Data Exchange (ETDEWEB)

    Tallermo, H.; Klevtsov, I. [Thermal Engineering Department of Tallinn Technical University, Tallinn (Estonia); Arras, V. [Eesti Energia, Tallinn (Estonia)

    1998-12-31

    Life management system is based on the valid nowadays in Estonian power plants regulation documentation. The system allows to estimate stress distribution in components, find computational assessment of cumulated creep damage, determine when and where it is necessary to cut off the particular number of microsamples or take replicas. Finally, the real metal condition may be assessed on the basis of metallographic specimen research and reasonable 3-R decision - run, repair, replacement - made on further component use. (orig.) 6 refs.

  1. Support vector machine based estimation of remaining useful life: current research status and future trends

    International Nuclear Information System (INIS)

    Huang, Hong Zhong; Wang, Hai Kun; Li, Yan Feng; Zhang, Longlong; Liu, Zhiliang

    2015-01-01

    Estimation of remaining useful life (RUL) is helpful to manage life cycles of machines and to reduce maintenance cost. Support vector machine (SVM) is a promising algorithm for estimation of RUL because it can easily process small training sets and multi-dimensional data. Many SVM based methods have been proposed to predict RUL of some key components. We did a literature review related to SVM based RUL estimation within a decade. The references reviewed are classified into two categories: improved SVM algorithms and their applications to RUL estimation. The latter category can be further divided into two types: one, to predict the condition state in the future and then build a relationship between state and RUL; two, to establish a direct relationship between current state and RUL. However, SVM is seldom used to track the degradation process and build an accurate relationship between the current health condition state and RUL. Based on the above review and summary, this paper points out that the ability to continually improve SVM, and obtain a novel idea for RUL prediction using SVM will be future works.

  2. Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services

    Science.gov (United States)

    Chaplin-Kramer, Rebecca; Sim, Sarah; Hamel, Perrine; Bryant, Benjamin; Noe, Ryan; Mueller, Carina; Rigarlsford, Giles; Kulak, Michal; Kowal, Virginia; Sharp, Richard; Clavreul, Julie; Price, Edward; Polasky, Stephen; Ruckelshaus, Mary; Daily, Gretchen

    2017-04-01

    International corporations in an increasingly globalized economy exert a major influence on the planet's land use and resources through their product design and material sourcing decisions. Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predictive ecological information to reveal key impacts on climate, water and biodiversity. We present advances for LCA that integrate spatially explicit modelling of land change and ecosystem services in a Land-Use Change Improved (LUCI)-LCA. Comparing increased demand for bioplastics derived from two alternative feedstock-location scenarios for maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption, and of different magnitudes for soil erosion and biodiversity. This approach highlights the importance of including information about where and how land-use change and related impacts will occur in supply chain and innovation decisions.

  3. Preference for novel faces in male infant monkeys predicts cerebrospinal fluid oxytocin concentrations later in life.

    Science.gov (United States)

    Madrid, Jesus E; Oztan, Ozge; Sclafani, Valentina; Del Rosso, Laura A; Calonder, Laura A; Chun, Katie; Capitanio, John P; Garner, Joseph P; Parker, Karen J

    2017-10-11

    The ability to recognize individuals is a critical skill acquired early in life for group living species. In primates, individual recognition occurs predominantly through face discrimination. Despite the essential adaptive value of this ability, robust individual differences in conspecific face recognition exist, yet its associated biology remains unknown. Although pharmacological administration of oxytocin has implicated this neuropeptide in face perception and social memory, no prior research has tested the relationship between individual differences in face recognition and endogenous oxytocin concentrations. Here we show in a male rhesus monkey cohort (N = 60) that infant performance in a task used to determine face recognition ability (specifically, the ability of animals to show a preference for a novel face) robustly predicts cerebrospinal fluid, but not blood, oxytocin concentrations up to five years after behavioural assessment. These results argue that central oxytocin biology may be related to individual face perceptual abilities necessary for group living, and that these differences are stable traits.

  4. Development and Life Prediction of Erosion Resistant Turbine Low Conductivity Thermal Barrier Coatings

    Science.gov (United States)

    Zhu, Dongming; Miller, Robert A.; Kuczmarski, Maria A.

    2010-01-01

    Future rotorcraft propulsion systems are required to operate under highly-loaded conditions and in harsh sand erosion environments, thereby imposing significant material design and durability issues. The incorporation of advanced thermal barrier coatings (TBC) in high pressure turbine systems enables engine designs with higher inlet temperatures, thus improving the engine efficiency, power density and reliability. The impact and erosion resistance of turbine thermal barrier coating systems are crucial to the turbine coating technology application, because a robust turbine blade TBC system is a prerequisite for fully utilizing the potential coating technology benefit in the rotorcraft propulsion. This paper describes the turbine blade TBC development in addressing the coating impact and erosion resistance. Advanced thermal barrier coating systems with improved performance have also been validated in laboratory simulated engine erosion and/or thermal gradient environments. A preliminary life prediction modeling approach to emphasize the turbine blade coating erosion is also presented.

  5. Availability and mean life time prediction of multistage degraded system with partial repairs

    International Nuclear Information System (INIS)

    Pham, Hoang; Suprasad, A.; Misra, R.B.

    1997-01-01

    In some environments, components might not always fail fully, but can degrade, and there can be multiple stages of degradation. In such cases, the efficiency of the system may decrease. After a certain stage of degradation the efficiency of the system may decrease to an unacceptable limit and can be considered as a total failure. However, the system can fail randomly from any stage. and can be repaired. Further, the repair action cannot bring the system to the good stage, but can make it operational and the failure rate of the system will, therefore, remain the same as before the failure. In this study, we present a model for predicting the reliability, availability, mean life time, and mean time to first failure of multistage degraded systems with partial repairs. In the analysis, state dependent transition rates for the degradation process, as well as repair processes, are considered. A numerical example is provided to illustrate the results

  6. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  7. Link prediction based on non-negative matrix factorization

    Science.gov (United States)

    Chen, Bolun; Li, Fenfen; Hu, Ronglin; Chen, Ling

    2017-01-01

    With the rapid expansion of internet, the complex networks has become high-dimensional, sparse and redundant. Besides, the problem of link prediction in such networks has also obatined increasingly attention from different types of domains like information science, anthropology, sociology and computer sciences. It makes requirements for effective link prediction techniques to extract the most essential and relevant information for online users in internet. Therefore, this paper attempts to put forward a link prediction algorithm based on non-negative matrix factorization. In the algorithm, we reconstruct the correlation between different types of matrix through the projection of high-dimensional vector space to a low-dimensional one, and then use the similarity between the column vectors of the weight matrix as the scoring matrix. The experiment results demonstrate that the algorithm not only reduces data storage space but also effectively makes the improvements of the prediction performance during the process of sustaining a low time complexity. PMID:28854195

  8. Link prediction based on non-negative matrix factorization.

    Science.gov (United States)

    Chen, Bolun; Li, Fenfen; Chen, Senbo; Hu, Ronglin; Chen, Ling

    2017-01-01

    With the rapid expansion of internet, the complex networks has become high-dimensional, sparse and redundant. Besides, the problem of link prediction in such networks has also obatined increasingly attention from different types of domains like information science, anthropology, sociology and computer sciences. It makes requirements for effective link prediction techniques to extract the most essential and relevant information for online users in internet. Therefore, this paper attempts to put forward a link prediction algorithm based on non-negative matrix factorization. In the algorithm, we reconstruct the correlation between different types of matrix through the projection of high-dimensional vector space to a low-dimensional one, and then use the similarity between the column vectors of the weight matrix as the scoring matrix. The experiment results demonstrate that the algorithm not only reduces data storage space but also effectively makes the improvements of the prediction performance during the process of sustaining a low time complexity.

  9. Prediction on carbon dioxide emissions based on fuzzy rules

    Science.gov (United States)

    Pauzi, Herrini; Abdullah, Lazim

    2014-06-01

    There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

  10. Generalized ESO and Predictive Control Based Robust Autopilot Design

    Directory of Open Access Journals (Sweden)

    Bhavnesh Panchal

    2016-01-01

    Full Text Available A novel continuous time predictive control and generalized extended state observer (GESO based acceleration tracking pitch autopilot design is proposed for a tail controlled, skid-to-turn tactical missile. As the dynamics of missile are significantly uncertain with mismatched uncertainty, GESO is employed to estimate the state and uncertainty in an integrated manner. The estimates are used to meet the requirement of state and to robustify the output tracking predictive controller designed for nominal system. Closed loop stability for the controller-observer structure is established. An important feature of the proposed design is that it does not require any specific information about the uncertainty. Also the predictive control design yields the feedback control gain and disturbance compensation gain simultaneously. Effectiveness of GESO in estimation of the states and uncertainties and in robustifying the predictive controller in the presence of parametric uncertainties, external disturbances, unmodeled dynamics, and measurement noise is illustrated by simulation.

  11. Eukaryotic promoter prediction based on relative entropy and positional information.

    Science.gov (United States)

    Wu, Shuanhu; Xie, Xudong; Liew, Alan Wee-Chung; Yan, Hong

    2007-04-01

    The eukaryotic promoter prediction is one of the most important problems in DNA sequence analysis, but also a very difficult one. Although a number of algorithms have been proposed, their performances are still limited by low sensitivities and high false positives. We present a method for improving the performance of promoter regions prediction. We focus on the selection of most effective features for different functional regions in DNA sequences. Our feature selection algorithm is based on relative entropy or Kullback-Leibler divergence, and a system combined with position-specific information for promoter regions prediction is developed. The results of testing on large genomic sequences and comparisons with the PromoterInspector and Dragon Promoter Finder show that our algorithm is efficient with higher sensitivity and specificity in predicting promoter regions.

  12. Compressed sensing based missing nodes prediction in temporal communication network

    Science.gov (United States)

    Cheng, Guangquan; Ma, Yang; Liu, Zhong; Xie, Fuli

    2018-02-01

    The reconstruction of complex network topology is of great theoretical and practical significance. Most research so far focuses on the prediction of missing links. There are many mature algorithms for link prediction which have achieved good results, but research on the prediction of missing nodes has just begun. In this paper, we propose an algorithm for missing node prediction in complex networks. We detect the position of missing nodes based on their neighbor nodes under the theory of compressed sensing, and extend the algorithm to the case of multiple missing nodes using spectral clustering. Experiments on real public network datasets and simulated datasets show that our algorithm can detect the locations of hidden nodes effectively with high precision.

  13. Predicting cycle 24 using various dynamo-based tools

    Directory of Open Access Journals (Sweden)

    M. Dikpati

    2008-02-01

    Full Text Available Various dynamo-based techniques have been used to predict the mean solar cycle features, namely the amplitude and the timings of onset and peak. All methods use information from previous cycles, including particularly polar fields, drift-speed of the sunspot zone to the equator, and remnant magnetic flux from the decay of active regions. Polar fields predict a low cycle 24, while spot zone migration and remnant flux both lead to predictions of a high cycle 24. These methods both predict delayed onset for cycle 24. We will describe how each of these methods relates to dynamo processes. We will present the latest results from our flux-transport dynamo, including some sensitivity tests and how our model relates to polar fields and spot zone drift methods.

  14. Bioregenerative life support system for a lunar base

    Science.gov (United States)

    Liu, H.; Wang, J.; Manukovsky, N. S.; Kovalev, V. S.; Gurevich, Yu. L.

    We have studied a modular approach to construction of bioregenerative life support system BLSS for a lunar base using soil-like substrate SLS for plant cultivation Calculations of massflow rates in BLSS were based mostly on a vegetarian diet and biological conversion of plant residues in SLS Plant candidate list for lunar BLSS includes the following basic species rice Oryza sativa soy Glycine max sweet potato Ipomoea batatas and wheat Triticum aestivum To reduce the time necessary for transition of the system to steady state we suggest that the first seeding and sprouting could be made on Earth

  15. Cortisol response and coping style predict quality of life in schizophrenia.

    Science.gov (United States)

    Brenner, Karene; St-Hilaire, Annie; Liu, Aihua; Laplante, David P; King, Suzanne

    2011-05-01

    Stress and coping have been found to be strongly associated with quality of life (QOL). Compared to community controls (CC), individuals diagnosed with schizophrenia (SZ) report a lower QOL. Lower QOL in SZ may be explained by patients' tendency to react differently to stress and to use less effective coping strategies than CC, but no studies to date have examined these possible associations. A main goal of this study, therefore, was to examine the roles of stress response and coping style in explaining QOL in SZ and CC, while controlling for potential confounds including personality. Subjects were 30 SZ patients and 29 matched controls who completed the Trier Social Stress Test (TSST). Salivary cortisol was used as an objective measure of stress response. Participants rated their coping strategies with the Brief COPE, judged their QOL with the Satisfaction with Life Scale, and rated their personality using the NEO-Five Factor Inventory. Results indicate that, even when confounds are controlled for, blunted cortisol response predicts better QOL in SZ patients. Additionally, results suggest that more frequent use of coping strategies is associated with better QOL but only in patients with blunted cortisol response; those who showed an increase in cortisol in response to the TSST have better QOL the lower their coping score. Possible explanations and clinical implications of these findings are discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

  16. Satellite Lithium-Ion Battery Remaining Cycle Life Prediction with Novel Indirect Health Indicator Extraction

    Directory of Open Access Journals (Sweden)

    Haitao Liao

    2013-07-01

    Full Text Available Prognostics and remaining useful life (RUL estimation for lithium-ion batteries play an important role in intelligent battery management systems (BMS. The capacity is often used as the fade indicator for estimating the remaining cycle life of a lithium-ion battery. For spacecraft requiring high reliability and long lifetime, in-orbit RUL estimation and reliability verification on ground should be carefully addressed. However, it is quite challenging to monitor and estimate the capacity of a lithium-ion battery on-line in satellite applications. In this work, a novel health indicator (HI is extracted from the operating parameters of a lithium-ion battery to quantify battery degradation. Moreover, the Grey Correlation Analysis (GCA is utilized to evaluate the similarities between the extracted HI and the battery’s capacity. The result illustrates the effectiveness of using this new HI for fading indication. Furthermore, we propose an optimized ensemble monotonic echo state networks (En_MONESN algorithm, in which the monotonic constraint is introduced to improve the adaptivity of degradation trend estimation, and ensemble learning is integrated to achieve high stability and precision of RUL prediction. Experiments with actual testing data show the efficiency of our proposed method in RUL estimation and degradation modeling for the satellite lithium-ion battery application.

  17. Drug-target interaction prediction from PSSM based evolutionary information.

    Science.gov (United States)

    Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-01-01

    The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Prediction of Suspect Location Based on Spatiotemporal Semantics

    Directory of Open Access Journals (Sweden)

    Lian Duan

    2017-06-01

    Full Text Available The prediction of suspect location enables proactive experiences for crime investigations and offers essential intelligence for crime prevention. However, existing studies have failed to capture the complex social location transition patterns of suspects and lack the capacity to address the issue of data sparsity. This paper proposes a novel location prediction model called CMoB (Crime Multi-order Bayes model based on the spatiotemporal semantics to enhance the prediction performance. In particular, the model groups suspects with similar spatiotemporal semantics as one target suspect. Then, their mobility data are applied to estimate Markov transition probabilities of unobserved locations based on a KDE (kernel density estimating smoothing method. Finally, by integrating the total transition probabilities, which are derived from the multi-order property of the Markov transition matrix, into a Bayesian-based formula, it is able to realize multi-step location prediction for the individual suspect. Experiments with the mobility dataset covering 210 suspects and their 18,754 location records from January to June 2012 in Wuhan City show that the proposed CMoB model significantly outperforms state-of-the-art algorithms for suspect location prediction in the context of data sparsity.

  19. A modelling study for long-term life prediction of carbon steel overpack for geological isolation of High-Level Radioactive Waste

    International Nuclear Information System (INIS)

    Taniguchi, Naoki; Honda, Akira; Ishikawa, Hirohisa

    1996-01-01

    Current plans for the geological disposal of High-Level Radioactive Waste (HLW) in Japan include metal overpacks which contain HLW. Overpacks may be required to remain intact for more than several hundred years in order to provide containment of radio nuclides. The main factor limiting the performance of overpacks is considered to be corrosion by groundwater. Carbon steel is one of the candidate material for overpacks. A mathematical model for life prediction of carbon steel overpack has been developed based on corrosion mechanism. General corrosion and localized corrosion are considered because these are likely to initiate in repository conditions. In general corrosion model, the reduction of oxygen and water are considered as cathodic reaction. In localized corrosion model, we have constructed a model which predict the period for localized corrosion based on oxygen transport in bentonite. We also developed a model which predict the propagation rate of localized corrosion that is based on mass balance within the corroding cavity. (author)

  20. Being present: Focusing on the present predicts improvements in life satisfaction but not happiness.

    Science.gov (United States)

    Felsman, Peter; Verduyn, Philippe; Ayduk, Ozlem; Kross, Ethan

    2017-10-01

    Mindfulness theorists suggest that people spend most of their time focusing on the past or future rather than the present. Despite the prevalence of this assumption, no research that we are aware of has evaluated whether it is true or what the implications of focusing on the present are for subjective well-being. We addressed this issue by using experience sampling to examine how frequently people focus on the present throughout the day over the course of a week and whether focusing on the present predicts improvements in the 2 components of subjective well-being over time-how people feel and how satisfied they are with their lives. Results indicated that participants were present-focused the majority of the time (66%). Moreover, focusing on the present predicted improvements in life satisfaction (but not happiness) over time by reducing negative rumination. These findings advance our understanding of how temporal orientation and well-being relate. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  1. Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Kandler A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Saxon, Aron R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Keyser, Matthew A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Lundstrom, Blake R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cao, Ziwei [SunPower Corporation; Roc, Albert [SunPower Corp.

    2017-08-25

    Life Prediction Model for Grid-Connected Li-ion Battery Energy Storage System: Preprint Lithium-ion (Li-ion) batteries are being deployed on the electrical grid for a variety of purposes, such as to smooth fluctuations in solar renewable power generation. The lifetime of these batteries will vary depending on their thermal environment and how they are charged and discharged. To optimal utilization of a battery over its lifetime requires characterization of its performance degradation under different storage and cycling conditions. Aging tests were conducted on commercial graphite/nickel-manganese-cobalt (NMC) Li-ion cells. A general lifetime prognostic model framework is applied to model changes in capacity and resistance as the battery degrades. Across 9 aging test conditions from 0oC to 55oC, the model predicts capacity fade with 1.4 percent RMS error and resistance growth with 15 percent RMS error. The model, recast in state variable form with 8 states representing separate fade mechanisms, is used to extrapolate lifetime for example applications of the energy storage system integrated with renewable photovoltaic (PV) power generation.

  2. Quality of life and predictive factors in patients undergoing assisted reproduction techniques.

    Science.gov (United States)

    Heredia, M; Tenías, J M; Rocio, R; Amparo, F; Calleja, M A; Valenzuela, J C

    2013-04-01

    To evaluate the quality of life (QOL) of a cohort of women undergoing assisted reproduction techniques (ART), to compare two QOL questionnaires [Short Form 36 (SF36) and FertiQoL], and to identify the predictive factors related to QOL. Women who received infertility medication from a hospital pharmacist during a one-year period were included in this study. Two standardized validated questionnaires - FertiQoL and SF36 - were used. Multivariate analyses were used to assess predictive factors for QOL. Sixty-one women participated in this study. Median QOL scores ranged from 58 to 100. Comparisons between the two questionnaires revealed lower QOL scores when using FertiQoL. Most correlations between the questionnaires were positive, and significant for the majority of SF36 mental dimensions. The major predictors of QOL were: accompanied to the pharmacist's visit by partner, nationality, ART (in vitro fertilization or artificial insemination), employment status (employed or unemployed), tobacco consumption, age, number of cycles, infertility factor and treatment results (pregnancy, no pregnancy or treatment cancellation). FertiQoL examines dimensions such as partner and social relationships. As such, it is recommended that FertiQoL should be used together with a short version of SF36 to investigate QOL among patients undergoing ART. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  3. Quality of life related to health chronic kidney disease: Predictive importance of mood and somatic symptoms.

    Science.gov (United States)

    Perales Montilla, Carmen M; Duschek, Stefan; Reyes Del Paso, Gustavo A

    2016-01-01

    To compare the predictive capacity of self-reported somatic symptoms and mood (depression and anxiety) on health-related quality of life (HRQOL) in patients with chronic renal disease. Data were obtained from 52 patients undergoing haemodialysis. Measures included a) the SF-36 health survey, b) the somatic symptoms scale revised (ESS-R) and c) the hospital anxiety and depression scale (HADS). Multiple regression was the main method of statistical analysis. Patients exhibited HRQOL levels below normative values, with anxiety and depression prevalence at 36.5% and 27%, respectively. Mood was the strongest predictor of physical (β=-.624) and mental (β=-.709) HRQOL. Somatic symptoms were also associated with physical HRQOL, but their predictive value was weaker (β=-.270). These results indicate that mood is a superior predictor of the physical and mental components of HRQOL in patients compared with the number and severity of physical symptoms. The data underline the importance of assessing negative emotional states (depression and anxiety) in kidney patients as a basis for intervention, which may facilitate reduction of the impact of chronic renal disease on HRQOL. Copyright © 2016 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

  4. A 3.5 year diary study: Remembering and life story importance are predicted by different event characteristics.

    Science.gov (United States)

    Thomsen, Dorthe Kirkegaard; Jensen, Thomas; Holm, Tine; Olesen, Martin Hammershøj; Schnieber, Anette; Tønnesvang, Jan

    2015-11-01

    Forty-five participants described and rated two events each week during their first term at university. After 3.5 years, we examined whether event characteristics rated in the diary predicted remembering, reliving, and life story importance at the follow-up. In addition, we examined whether ratings of life story importance were consistent across a three year interval. Approximately 60% of events were remembered, but only 20% of these were considered above medium importance to life stories. Higher unusualness, rehearsal, and planning predicted whether an event was remembered 3.5 years later. Higher goal-relevance, importance, emotional intensity, and planning predicted life story importance 3.5 years later. There was a moderate correlation between life story importance rated three months after the diary and rated at the 3.5 year follow-up. The results suggest that autobiographical memory and life stories are governed by different mechanisms and that life story memories are characterized by some degree of stability. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. A Fusion Link Prediction Method Based on Limit Theorem

    Directory of Open Access Journals (Sweden)

    Yiteng Wu

    2017-12-01

    Full Text Available The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the way they derive the similarity matrix, and investigates whether there a theoretical limit exists for combination methods. We propose and prove necessary and sufficient conditions for the combination method to reach the theoretical limit. The limit theorem reveals the essence of combination method that is to estimate probability density functions of existing links and nonexistent links. Based on limit theorem, a new combination method, theoretical limit fusion (TLF method, is proposed. Simulations and experiments on real networks demonstrated that TLF method can achieve higher prediction accuracy.

  6. Protein Microarrays-Based Strategies for Life Detection in Astrobiology

    Science.gov (United States)

    Parro, Víctor; Rivas, Luis A.; Gómez-Elvira, Javier

    2008-03-01

    The detection of organic molecules of unambiguous biological origin is fundamental for the confirmation of present or past life. Planetary exploration requires the development of miniaturized apparatus for in situ life detection. Analytical techniques based on mass spectrometry have been traditionally used in space science. Following the Viking landers, gas chromatography-mass spectrometry (GC-MS) for organic detection has gained general acceptance and has been used successfully in the Cassini-Huygens mission to Titan. Microfluidics allows the development of miniaturized capillary electrophoresis devices for the detection of important molecules for life, like amino acids or nucleobases. Recently, a new approach is gaining acceptance in the space science community: the application of the well-known, highly specific, antibody-antigen affinity interaction for the detection and identification of organics and biochemical compounds. Antibodies can specifically bind a plethora of structurally different compounds of a broad range of molecular sizes, from amino acids level to whole cells. Antibody microarray technology allows us to look for the presence of thousands of different compounds in a single assay and in just one square centimeter. Herein, we discuss several important issues—most of which are common with other instruments dealing with life signature detection in the solar system—that must be addressed in order to use antibody microarrays for life detection and planetary exploration. These issues include (1) preservation of biomarkers, (2) the extraction techniques for biomarkers, (3) terrestrial analogues, (4) the antibody stability under space environments, (5) the selection of unequivocal biomarkers for the antibody production, or (6) the instrument design and implementation.

  7. A Human Life-Stage Physiologically Based Pharmacokinetic and Pharmacodynamic Model for Chlorpyrifos: Development and Validation

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Jordan N.; Hinderliter, Paul M.; Timchalk, Charles; Bartels, M. J.; Poet, Torka S.

    2014-08-01

    Sensitivity to chemicals in animals and humans are known to vary with age. Age-related changes in sensitivity to chlorpyrifos have been reported in animal models. A life-stage physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model was developed to computationally predict disposition of CPF and its metabolites, chlorpyrifos-oxon (the ultimate toxicant) and 3,5,6-trichloro-2-pyridinol (TCPy), as well as B-esterase inhibition by chlorpyrifos-oxon in humans. In this model, age-dependent body weight was calculated from a generalized Gompertz function, and compartments (liver, brain, fat, blood, diaphragm, rapid, and slow) were scaled based on body weight from polynomial functions on a fractional body weight basis. Blood flows among compartments were calculated as a constant flow per compartment volume. The life-stage PBPK/PD model was calibrated and tested against controlled adult human exposure studies. Model simulations suggest age-dependent pharmacokinetics and response may exist. At oral doses ≥ 0.55 mg/kg of chlorpyrifos (significantly higher than environmental exposure levels), 6 mo old children are predicted to have higher levels of chlorpyrifos-oxon in blood and higher levels of red blood cell cholinesterase inhibition compared to adults from equivalent oral doses of chlorpyrifos. At lower doses that are more relevant to environmental exposures, the model predicts that adults will have slightly higher levels of chlorpyrifos-oxon in blood and greater cholinesterase inhibition. This model provides a computational framework for age-comparative simulations that can be utilized to predict CPF disposition and biological response over various postnatal life-stages.

  8. Relating lab to life: Decrements in attention over time predict math productivity among children with ADHD.

    Science.gov (United States)

    Fosco, Whitney D; Hawk, Larry W

    2017-02-01

    A child's ability to sustain attention over time (AOT) is critical in attention-deficit/hyperactivity disorder (ADHD), yet no prior work has examined the extent to which a child's decrement in AOT on laboratory tasks relates to clinically-relevant behavior. The goal of this study is to provide initial evidence for the criterion validity of laboratory assessments of AOT. A total of 20 children with ADHD (7-12 years of age) who were enrolled in a summer treatment program completed two lab attention tasks (a continuous performance task and a self-paced choice discrimination task) and math seatwork. Analyses focused on relations between attention task parameters and math productivity. Individual differences in overall attention (OA) measures (averaged across time) accounted for 23% of the variance in math productivity, supporting the criterion validity of lab measures of attention. The criterion validity was enhanced by consideration of changes in AOT. Performance on all laboratory attention measures deteriorated as time-on-task increased, and individual differences in the decrement in AOT accounted for 40% of the variance in math productivity. The only variable to uniquely predict math productivity was from the self-paced choice discrimination task. This study suggests that attention tasks in the lab do predict a clinically-relevant target behavior in children with ADHD, supporting their use as a means to study attention processes in a controlled environment. Furthermore, this prediction is improved when attention is examined as a function of time-on-task and when the attentional demands are consistent between lab and life contexts.

  9. Neither Basic Life Support knowledge nor self-efficacy are predictive of skills among dental students.

    Science.gov (United States)

    Mac Giolla Phadraig, C; Ho, J D; Guerin, S; Yeoh, Y L; Mohamed Medhat, M; Doody, K; Hwang, S; Hania, M; Boggs, S; Nolan, A; Nunn, J

    2017-08-01

    Basic life support (BLS) is considered a core competence for the graduating dentist. This study aimed to measure BLS knowledge, self-efficacy and skills of undergraduate dental students in Dublin. This study consisted of a cross-sectional survey measuring BLS knowledge and self-efficacy, accompanied by a directly observed BLS skills assessment in a subsample of respondents. Data were collected in January 2014. Bivariate correlations between descriptive and outcome variables (knowledge, self-efficacy and skills) were tested using Pearson's chi-square. We included knowledge and self-efficacy as predictor variables, along with other variables showing association, into a binary logistic regression model with BLS skills as the outcome measure. One hundred and thirty-five students participated. Almost all (n = 133, 98.5%) participants had BLS training within the last 2 years. One hundred and four (77%) felt that they were capable of providing effective BLS (self-efficacy), whilst only 46 (34.1%) scored >80% of knowledge items correct. Amongst the skills (n = 85) subsample, 38.8% (n = 33) were found to pass the BLS skills assessment. Controlling for gender, age and skills assessor, the regression model did not identify a predictive relationship between knowledge or self-efficacy and BLS skills. Neither knowledge nor self-efficacy was predictive of BLS skills. Dental students had low levels of knowledge and skills in BLS. Despite this, their confidence in their ability to perform BLS was high and did not predict actual competence. There is a need for additional hands-on training, focusing on self-efficacy and BLS skills, particularly the use of AED. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  10. Domain-Based Predictive Models for Protein-Protein Interaction Prediction

    Directory of Open Access Journals (Sweden)

    Chen Xue-Wen

    2006-01-01

    Full Text Available Protein interactions are of biological interest because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Recently, methods for predicting protein interactions using domain information are proposed and preliminary results have demonstrated their feasibility. In this paper, we develop two domain-based statistical models (neural networks and decision trees for protein interaction predictions. Unlike most of the existing methods which consider only domain pairs (one domain from one protein and assume that domain-domain interactions are independent of each other, the proposed methods are capable of exploring all possible interactions between domains and make predictions based on all the domains. Compared to maximum-likelihood estimation methods, our experimental results show that the proposed schemes can predict protein-protein interactions with higher specificity and sensitivity, while requiring less computation time. Furthermore, the decision tree-based model can be used to infer the interactions not only between two domains, but among multiple domains as well.

  11. Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

    Directory of Open Access Journals (Sweden)

    Wenbiao Li

    2016-04-01

    Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

  12. Are Macro variables good predictors? A prediction based on the number of total medals acquired

    Directory of Open Access Journals (Sweden)

    Shahram Shafiee

    2012-01-01

    Full Text Available A large amount of effort is spent on forecasting the outcome of sporting events. Moreover, there are large quantities of data regarding the outcomes of sporting events and the factors which are assumed to contribute to those outcomes. In this paper we tried to predict the success of nations at the Asian Games through macro-economic, political, social and cultural variables. we used the information of variables include urban population, Education Expenditures, Age Structure, GDP Real Growth Rate, GDP Per Capita, Unemployment Rate, Population, Inflation Average, current account balance, life expectancy at birth and Merchandise Trade for all of the participating countries in Asian Games from 1970 to 2006 in order to build the model and then this model was tested by the information of variables in 2010. The prediction is based on the number of total medals acquired each country. In this research we used WEKA software that is a popular suite of machine learning software written in Java. The value of correlation coefficient between the predicted and original ranks is 90.42%. Neural Network Model, between 28 countries mentioned, predicts their ranks according to the maximum difference between predicted and original ranks of 19 countries (67.85% is 3, the maximum difference between predicted and original ranks of 8 countries (28.57% is between 4 to 6 and the difference between predicted and original ranks of 1 countries (3.57% is more than 6.

  13. Predicting animal production on sourveld: a species-based approach

    African Journals Online (AJOL)

    Presents a simulation model which was developed to predict average daily gain in cattle and sheep grazing different species and swards of different species composition on Dohne Sourveld. The model was based upon measured ingestive and digestive characteristics of different grass species and incorporates an explicit ...

  14. Snippet-based relevance predictions for federated web search

    NARCIS (Netherlands)

    Demeester, Thomas; Nguyen, Dong-Phuong; Trieschnigg, Rudolf Berend; Develder, Chris; Hiemstra, Djoerd

    How well can the relevance of a page be predicted, purely based on snippets? This would be highly useful in a Federated Web Search setting where caching large amounts of result snippets is more feasible than caching entire pages. The experiments reported in this paper make use of result snippets and

  15. Lifetime Prediction of IGBT Modules based on Linear Damage Accumulation

    DEFF Research Database (Denmark)

    Choi, Uimin; Blaabjerg, Frede; Ma, Ke

    2017-01-01

    In this paper, the lifetime prediction of power device modules based on the linear damage accumulation in conjunction with real mission profile assessment is studied. Four tests are performed under two superimposed power cycling conditions using an advanced power cycling test setup with 600 V, 30...

  16. Methodology for predicting the life of waste-package materials, and components using multifactor accelerated life tests

    International Nuclear Information System (INIS)

    Accelerated life tests are essential for estimating the service life of waste-package materials and components. A recommended methodology for generating accelerated life tests is described in this report. The objective of the methodology is to define an accelerated life test program that is scientifically and statistically defensible. The methodology is carried out using a select team of scientists and usually requires 4 to 12 man-months of effort. Specific agendas for the successive meetings of the team are included in the report for use by the team manager. The agendas include assignments for the team scientists and a different set of assignments for the team statistician. The report also includes descriptions of factorial tables, hierarchical trees, and associated mathematical models that are proposed as technical tools to guide the efforts of the design team

  17. Living Slow and Being Moral : Life History Predicts the Dual Process of Other-Centered Reasoning and Judgments.

    Science.gov (United States)

    Zhu, Nan; Hawk, Skyler T; Chang, Lei

    2018-03-08

    Drawing from the dual process model of morality and life history theory, the present research examined the role of cognitive and emotional processes as bridges between basic environmental challenges (i.e., unpredictability and competition) and other-centered moral orientation (i.e., prioritizing the welfare of others). In two survey studies, cognitive and emotional processes represented by future-oriented planning and emotional attachment, respectively (Study 1, N = 405), or by perspective taking and empathic concern, respectively (Study 2, N = 424), positively predicted other-centeredness in prosocial moral reasoning (Study 1) and moral judgment dilemmas based on rationality or intuition (Study 2). Cognitive processes were more closely related to rational aspects of other-centeredness, whereas the emotional processes were more closely related to the intuitive aspects of other-centeredness (Study 2). Finally, the cognitive and emotional processes also mediated negative effects of unpredictability (i.e., negative life events and childhood financial insecurity), as well as positive effects of individual-level, contest competition (i.e., educational and occupational competition) on other-centeredness. Overall, these findings support the view that cognitive and emotional processes do not necessarily contradict each other. Rather, they might work in concert to promote other-centeredness in various circumstances and might be attributed to humans' developmental flexibility in the face of environmental challenges.

  18. Prediction of Human Vertebral Compressive Strength Using Quantitative Computed Tomography Based Nonlinear Finite Element Method

    Directory of Open Access Journals (Sweden)

    Ahad Zeinali

    2007-12-01

    Full Text Available Introduction: Because of the importance of vertebral compressive fracture (VCF role in increasing the patients’ death rate and reducing their quality of life, many studies have been conducted for a noninvasive prediction of vertebral compressive strength based on bone mineral density (BMD determination and recently finite element analysis. In this study, QCT-voxel based nonlinear finite element method is used for predicting vertebral compressive strength. Material and Methods: Four thoracolumbar vertebrae were excised from 3 cadavers with an average age of 42 years. They were then put in a water phantom and were scanned using the QCT. Using a computer program prepared in MATLAB, detailed voxel based geometry and mechanical characteristics of the vertebra were extracted from the CT images. The three dimensional finite element models of the samples were created using ANSYS computer program. The compressive strength of each vertebra body was calculated based on a linearly elastic-linearly plastic model and large deformation analysis in ANSYS and was compared to the value measured experimentally for that sample. Results: Based on the obtained results the QCT-voxel based nonlinear finite element method (FEM can predict vertebral compressive strength more effectively and accurately than the common QCT-voxel based linear FEM. The difference between the predicted strength values using this method and the measured ones was less than 1 kN for all the samples. Discussion and Conclusion: It seems that the QCT-voxel based nonlinear FEM used in this study can predict more effectively and accurately the vertebral strengths based on every vertebrae specification by considering their detailed geometric and densitometric characteristics.

  19. Blind Test of Physics-Based Prediction of Protein Structures

    Science.gov (United States)

    Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

    2009-01-01

    We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

  20. Temperature- and CO2-dependent life table parameters of Spodoptera litura (Noctuidae: Lepidoptera) on sunflower and prediction of pest scenarios.

    Science.gov (United States)

    Manimanjari, D; Srinivasa Rao, M; Swathi, P; Rama Rao, C A; Vanaja, M; Maheswari, M

    2014-01-01

    Predicted increase in temperature and atmospheric CO2 concentration will influence the growth of crop plants and phytophagous insects. The present study, conducted at the Central Research Institute for Dryland Agriculture, Hyderabad, India, aimed at (1) construction of life tables at six constant temperatures viz., 20, 25, 27, 30, 33, and 35 ± 0.5 °C for Spodoptera litura (Fabricius) (Noctuidae: Lepidoptera) reared on sunflower (Helianthus annus L.) grown under ambient and elevated CO2 (eCO2) (550 ppm) concentration in open top chambers and (2) prediction of the pest status in near future (NF) and distant future (DF) climate change scenarios at major sunflower growing locations of India. Significantly lower leaf nitrogen, higher carbon and higher relative proportion of carbon to nitrogen (C:N) were observed in sunflower foliage grown under eCO2 over ambient. Feeding trials conducted on sunflower foliage obtained from two CO2 conditions showed that the developmental time of S. litura (Egg to adult) declined with increase in temperature and was more evident at eCO2. Finite (λ) and intrinsic rates of increase (r(m)), net reproductive rate (Ro), mean generation time, (T) and doubling time (DT) of S. litura increased significantly with temperature up to 27-30 °C and declined with further increase in temperature. Reduction of 'T' was observed from maximum value of 58 d at 20 °C to minimum of 24.9 d at 35 °C. The DT of population was higher (5.88 d) at 20 °C and lower (3.05 d) at 30 °C temperature of eCO2. The data on these life table parameters were plotted against temperature and two nonlinear models were developed separately for each of the CO2 conditions for predicting the pest scenarios. The NF and DF scenarios temperature data of four sunflower growing locations in India is based on PRECIS A1B emission scenario. It was predicted that increased 'rm', 'λ', and 'Ro' and reduced 'T' would occur during NF and DF scenario over present period at all

  1. EMD-Based Predictive Deep Belief Network for Time Series Prediction: An Application to Drought Forecasting

    Directory of Open Access Journals (Sweden)

    Norbert A. Agana

    2018-02-01

    Full Text Available Drought is a stochastic natural feature that arises due to intense and persistent shortage of precipitation. Its impact is mostly manifested as agricultural and hydrological droughts following an initial meteorological phenomenon. Drought prediction is essential because it can aid in the preparedness and impact-related management of its effects. This study considers the drought forecasting problem by developing a hybrid predictive model using a denoised empirical mode decomposition (EMD and a deep belief network (DBN. The proposed method first decomposes the data into several intrinsic mode functions (IMFs using EMD, and a reconstruction of the original data is obtained by considering only relevant IMFs. Detrended fluctuation analysis (DFA was applied to each IMF to determine the threshold for robust denoising performance. Based on their scaling exponents, irrelevant intrinsic mode functions are identified and suppressed. The proposed method was applied to predict different time scale drought indices across the Colorado River basin using a standardized streamflow index (SSI as the drought index. The results obtained using the proposed method was compared with standard methods such as multilayer perceptron (MLP and support vector regression (SVR. The proposed hybrid model showed improvement in prediction accuracy, especially for multi-step ahead predictions.

  2. Prediction-Based Control for Nonlinear Systems with Input Delay

    Directory of Open Access Journals (Sweden)

    I. Estrada-Sánchez

    2017-01-01

    Full Text Available This work has two primary objectives. First, it presents a state prediction strategy for a class of nonlinear Lipschitz systems subject to constant time delay in the input signal. As a result of a suitable change of variable, the state predictor asymptotically provides the value of the state τ units of time ahead. Second, it proposes a solution to the stabilization and trajectory tracking problems for the considered class of systems using predicted states. The predictor-controller convergence is proved by considering a complete Lyapunov functional. The proposed predictor-based controller strategy is evaluated using numerical simulations.

  3. Prediction of Banking Systemic Risk Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Shouwei Li

    2013-01-01

    Full Text Available Banking systemic risk is a complex nonlinear phenomenon and has shed light on the importance of safeguarding financial stability by recent financial crisis. According to the complex nonlinear characteristics of banking systemic risk, in this paper we apply support vector machine (SVM to the prediction of banking systemic risk in an attempt to suggest a new model with better explanatory power and stability. We conduct a case study of an SVM-based prediction model for Chinese banking systemic risk and find the experiment results showing that support vector machine is an efficient method in such case.

  4. Thermal Cycling Life Prediction of Sn-3.0Ag-0.5Cu Solder Joint Using Type-I Censored Data

    Directory of Open Access Journals (Sweden)

    Jinhua Mi

    2014-01-01

    Full Text Available Because solder joint interconnections are the weaknesses of microelectronic packaging, their reliability has great influence on the reliability of the entire packaging structure. Based on an accelerated life test the reliability assessment and life prediction of lead-free solder joints using Weibull distribution are investigated. The type-I interval censored lifetime data were collected from a thermal cycling test, which was implemented on microelectronic packaging with lead-free ball grid array (BGA and fine-pitch ball grid array (FBGA interconnection structures. The number of cycles to failure of lead-free solder joints is predicted by using a modified Engelmaier fatigue life model and a type-I censored data processing method. Then, the Pan model is employed to calculate the acceleration factor of this test. A comparison of life predictions between the proposed method and the ones calculated directly by Matlab and Minitab is conducted to demonstrate the practicability and effectiveness of the proposed method. At last, failure analysis and microstructure evolution of lead-free solders are carried out to provide useful guidance for the regular maintenance, replacement of substructure, and subsequent processing of electronic products.

  5. Rate-Based Model Predictive Control of Turbofan Engine Clearance

    Science.gov (United States)

    DeCastro, Jonathan A.

    2006-01-01

    An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

  6. Prediction of Academic Aspiration based on Spiritual Intelligence and Tenacity

    Directory of Open Access Journals (Sweden)

    Safari H.

    2016-02-01

    Full Text Available Aims: The students’ academic achievements are noticed by the managers of academic centers.  One of the major factors in the academic achievements is academic enthusiasm. The aim of this study was to predict the academic enthusiasm based on spiritual intelligence and psychological tenacity in the students of Birjand University of Medical Sciences.  Instrument & Methods: In the correlational cross-section study, 165 students of Birjand University of Medical Sciences were studied in 2015-16 academic year. The subjects were selected based on Morgan table and via stratified random sampling method. Data was collected using spiritual intelligence, Ahvaz psychological tenacity, and academic enthusiasm scales. Data was analyzed by SPSS 22 software using Pearson correlational coefficient, synchronic regression, and independent T test.  Findings: There were positive and significant correlations between academic enthusiasm and spiritual intelligence (r=0.10 and psychological tenacity (r=0.21; p<0.01. 0.16 of academic enthusiasm variance were predicted by spiritual intelligence and psychological tenacity, mutually. Of the components of spiritual intelligence, existential critical thinking and transcendental consciousness could predict academic enthusiasm, only.  Conclusion: Academic enthusiasm can be predicted based on spiritual intelligence and psychological tenacity. 

  7. Pace of life, predators and parasites: predator-induced life-history evolution in Trinidadian guppies predicts decrease in parasite tolerance.

    Science.gov (United States)

    Stephenson, J F; van Oosterhout, C; Cable, J

    2015-11-01

    A common evolutionary response to predation pressure is increased investment in reproduction, ultimately resulting in a fast life history. Theory and comparative studies suggest that short-lived organisms invest less in defence against parasites than those that are longer lived (the pace of life hypothesis). Combining these tenets of evolutionary theory leads to the specific, untested prediction that within species, populations experiencing higher predation pressure invest less in defence against parasites. The Trinidadian guppy, Poecilia reticulata, presents an excellent opportunity to test this prediction: guppy populations in lower courses of rivers experience higher predation pressure, and as a consequence have evolved faster life histories, than those in upper courses. Data from a large-scale field survey showed that fish infected with Gyrodactylus parasites were of a lower body condition (quantified using the scaled mass index) than uninfected fish, but only in lower course populations. Although the evidence we present is correlational, it suggests that upper course guppies sustain lower fitness costs of infection, i.e. are more tolerant, than lower course guppies. The data are therefore consistent with the pace of life hypothesis of parasite defence allocation, and suggest that life-history traits mediate the indirect effect of predators on the parasites of their prey. © 2015 The Author(s).

  8. Microbial quality and shelf life prediction of vacuum-packaged ready to eat beef rounds containing gum arabic

    Directory of Open Access Journals (Sweden)

    Johnson K. Mwove

    2017-04-01

    Full Text Available Research has shown that gum arabic from Acacia senegal var. kerensis can be used in beef rounds, at a level of 2.5% of the formulated product weight, as a binder and texture modifier. However, the effect of gum arabic addition on the microbial quality and shelf life of the resulting meat product has not yet been reported. Thus, the objective of this work was to study the microbial quality of beef rounds containing 2.5% gum arabic and to study shelf life based on the growth parameters of Total Viable Counts (TVC and Lactic Acid Bacteria (LAB. Beef round samples were injected at 30% with curing brines containing gum arabic and cooked through boiling. The growth kinetics of LAB and TVC were studied for vacuum packaged sliced beef round samples stored at 7 oC and 15 oC for a period of 21 days. Baranyi and modified Gompertz models were used to fit the LAB and TVC data obtained using DMFit. Results of microbial analysis indicated that coliforms, yeasts and molds as well as pathogenic bacteria; Salmonella, Escherichia coli, and Staphylococcus aureus, were below detection limit. In addition, TVC and LAB were found to be 1.87 ± 1.09 and 1.25 ± 0.75 Log 10 CFU g-1, respectively. The results of accuracy analysis showed that both the Baranyi and modified Gompertz models were adequate in representing the bacterial growth in beef rounds injected with curing brines containing gum arabic. The predicted shelf life was found to be between 84.3 – 88.1 h and 158.0 – 173.1 h at 15 oC and 7 oC, respectively.

  9. Bayesian Predictive Modeling Based on Multidimensional Connectivity Profiling

    Science.gov (United States)

    Herskovits, Edward

    2015-01-01

    Dysfunction of brain structural and functional connectivity is increasingly being recognized as playing an important role in many brain disorders. Diffusion tensor imaging (DTI) and functional magnetic resonance (fMR) imaging are widely used to infer structural and functional connectivity, respectively. How to combine structural and functional connectivity patterns for predictive modeling is an important, yet open, problem. We propose a new method, called Bayesian prediction based on multidimensional connectivity profiling (BMCP), to distinguish subjects at the individual level based on structural and functional connectivity patterns. BMCP combines finite mixture modeling and Bayesian network classification. We demonstrate its use in distinguishing young and elderly adults based on DTI and resting-state fMR data. PMID:25924166

  10. miRNA-target prediction based on transcriptional regulation

    Directory of Open Access Journals (Sweden)

    Fujiwara Toyofumi

    2013-02-01

    Full Text Available Abstract Background microRNAs (miRNAs are tiny endogenous RNAs that have been discovered in animals and plants, and direct the post-transcriptional regulation of target mRNAs for degradation or translational repression via binding to the 3'UTRs and the coding exons. To gain insight into the biological role of miRNAs, it is essential to identify the full repertoire of mRNA targets (target genes. A number of computer programs have been developed for miRNA-target prediction. These programs essentially focus on potential binding sites in 3'UTRs, which are recognized by miRNAs according to specific base-pairing rules. Results Here, we introduce a novel method for miRNA-target prediction that is entirely independent of existing approaches. The method is based on the hypothesis that transcription of a miRNA and its target genes tend to be co-regulated by common transcription factors. This hypothesis predicts the frequent occurrence of common cis-elements between promoters of a miRNA and its target genes. That is, our proposed method first identifies putative cis-elements in a promoter of a given miRNA, and then identifies genes that contain common putative cis-elements in their promoters. In this paper, we show that a significant number of common cis-elements occur in ~28% of experimentally supported human miRNA-target data. Moreover, we show that the prediction of human miRNA-targets based on our method is statistically significant. Further, we discuss the random incidence of common cis-elements, their consensus sequences, and the advantages and disadvantages of our method. Conclusions This is the first report indicating prevalence of transcriptional regulation of a miRNA and its target genes by common transcription factors and the predictive ability of miRNA-targets based on this property.

  11. CD-Based Indices for Link Prediction in Complex Network.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Lots of similarity-based algorithms have been designed to deal with the problem of link prediction in the past decade. In order to improve prediction accuracy, a novel cosine similarity index CD based on distance between nodes and cosine value between vectors is proposed in this paper. Firstly, node coordinate matrix can be obtained by node distances which are different from distance matrix and row vectors of the matrix are regarded as coordinates of nodes. Then, cosine value between node coordinates is used as their similarity index. A local community density index LD is also proposed. Then, a series of CD-based indices include CD-LD-k, CD*LD-k, CD-k and CDI are presented and applied in ten real networks. Experimental results demonstrate the effectiveness of CD-based indices. The effects of network clustering coefficient and assortative coefficient on prediction accuracy of indices are analyzed. CD-LD-k and CD*LD-k can improve prediction accuracy without considering the assortative coefficient of network is negative or positive. According to analysis of relative precision of each method on each network, CD-LD-k and CD*LD-k indices have excellent average performance and robustness. CD and CD-k indices perform better on positive assortative networks than on negative assortative networks. For negative assortative networks, we improve and refine CD index, referred as CDI index, combining the advantages of CD index and evolutionary mechanism of the network model BA. Experimental results reveal that CDI index can increase prediction accuracy of CD on negative assortative networks.

  12. Prediction of potential drug targets based on simple sequence properties

    Directory of Open Access Journals (Sweden)

    Lai Luhua

    2007-09-01

    Full Text Available Abstract Background During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets. Results Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research. Conclusion We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.

  13. Review of time-dependent fatigue behavior and life prediction for 2 1/4 Cr-1 Mo steel

    International Nuclear Information System (INIS)

    Booker, M.K.; Majumdar, S.

    1982-01-01

    Available data on creep-fatigue life and fracture behavior of 2 1/4 Cr-1 Mo steel are reviewed. Whereas creep-fatigue interaction is important for Type 304 stainless steel, oxidation effects appear to dominate the time-dependent fatigue behavior of 2 1/4 Cr-1 Mo steel. Four of the currently available predictive methods - the Linear Damage Rule, Frequency Separation Equation, Strain Range Partitioning Equation, and Damage Rate Equation - are evaluated for their predictive capability. Variations in the parameters for the various predictive methods with temperature, heat of material, heat treatment, and environment are investigated. Relative trends in the lives predicted by the various methods as functions of test duration, waveshape, etc., are discussed. The predictive methods will need modification in order to account for oxidation and aging effects in the 2 1/4 Cr-1 Mo steel. Future tests that will emphasize the difference between the various predictive methods are proposed

  14. Microscopic Void Detection for Predicting Remaining Life in Electric Cable Insulation

    International Nuclear Information System (INIS)

    Horvath, David A.; Avila, Steven M.

    2003-01-01

    A reliable method of testing for remaining life in electric cable insulation has continued to elude the nuclear industry as it seeks to extend the life and license of its nuclear stations. Until recently, a trendable, measurable electrical property has not been found, and unexpected cable failures continue to be reported. Most reliable approaches to date rely on monitoring mechanical properties, which are assumed to degrade faster than the insulation's electrical properties. This paper introduces a promising technique based on void characterization, which is dependent on an electrical property related to dielectric strength. A relationship between insulation void characteristics (size and density) and the onset of partial discharge is known to exist. A similar relationship can be shown between void characteristics and unacceptable leakage currents (another typical cable failure criterion). For low-voltage cables, it is believed void content can be correlated to mechanical property degradation.This paper will report on an approach for using void information, research results showing the existence of trendable void characteristics in commonly used electric insulation materials, and techniques for detecting the voids (both laboratory- and field-based techniques). Acoustical microscopy was found to be potentially more suitable than conventional ultrasound for nondestructive in situ detection and monitoring of void characteristics in jacketed multiconductor insulation while ignoring the jacket. Also, optical and scanning electron microscope techniques will play an essential role in establishing the database necessary for continued development and implementation of this promising technique

  15. New Approaches for Channel Prediction Based on Sinusoidal Modeling

    Directory of Open Access Journals (Sweden)

    Ekman Torbjörn

    2007-01-01

    Full Text Available Long-range channel prediction is considered to be one of the most important enabling technologies to future wireless communication systems. The prediction of Rayleigh fading channels is studied in the frame of sinusoidal modeling in this paper. A stochastic sinusoidal model to represent a Rayleigh fading channel is proposed. Three different predictors based on the statistical sinusoidal model are proposed. These methods outperform the standard linear predictor (LP in Monte Carlo simulations, but underperform with real measurement data, probably due to nonstationary model parameters. To mitigate these modeling errors, a joint moving average and sinusoidal (JMAS prediction model and the associated joint least-squares (LS predictor are proposed. It combines the sinusoidal model with an LP to handle unmodeled dynamics in the signal. The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.

  16. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

    2006-01-01

    algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main conclusions We highlight an important source of uncertainty in assessments of the impacts of climate......Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions......, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current...

  17. Workpiece Machining Accuracy Prediction Based on Milling Simulation

    Directory of Open Access Journals (Sweden)

    Lv Yan-peng

    2016-01-01

    Full Text Available To ensure the machining accuracy of workpiece, it is necessary to predict the workpiece deformation in machining process through establishing a high precision workpiece deformation forecast model. To solve these problems, a more efficient variable stiffness analysis model is proposed, which can obtain quantitative stiffness value of the machining surface. Applying simulated cutting force in sampling points using finite element analysis software ABAQUS, the single direction variable stiffness rule can be obtained. First of all, finite element simulation model of face milling is established with the Johnson-Cook material model and failure model of 7050 aluminum alloy. Prediction model is established based on SVM and input data is provided by the finite element software ABAQUS simulation. Results show that the model prediction relative error is less than 5%. It is concluded that the effects of milling parameters on workpiece machining deformation and practical guide for production.

  18. Prediction of COPD-specific health-related quality of life in primary care COPD patients: a prospective cohort study

    OpenAIRE

    Siebeling, Lara; Musoro, Jammbe Z; Geskus, Ronald B; Zoller, Marco; Muggensturm, Patrick; Frei, Anja; Puhan, Milo A; ter Riet, Gerben

    2014-01-01

    Background: Health-related quality of life (HRQL) is an important patient-reported outcome for chronic obstructive pulmonary disease (COPD). Aim: We developed models predicting chronic respiratory questionnaire (CRQ) dyspnoea, fatigue, emotional function, mastery and overall HRQL at 6 and 24 months using predictors easily available in primary care. Methods: We used the “least absolute shrinkage and selection operator” (lasso) method to build the models and assessed their predictive performanc...

  19. Report on three Genomes to Life Workshops: Data Infrastructure, Modeling and Simulation, and Protein Structure Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Geist, GA

    2003-09-16

    On July 22, 23, 24, 2003, three one day workshops were held in Gaithersburg, Maryland. Each was attended by about 30 computational biologists, mathematicians, and computer scientists who were experts in the respective workshop areas The first workshop discussed the data infrastructure needs for the Genomes to Life (GTL) program with the objective to identify gaps in the present GTL data infrastructure and define the GTL data infrastructure required for the success of the proposed GTL facilities. The second workshop discussed the modeling and simulation needs for the next phase of the GTL program and defined how these relate to the experimental data generated by genomics, proteomics, and metabolomics. The third workshop identified emerging technical challenges in computational protein structure prediction for DOE missions and outlining specific goals for the next phase of GTL. The workshops were attended by representatives from both OBER and OASCR. The invited experts at each of the workshops made short presentations on what they perceived as the key needs in the GTL data infrastructure, modeling and simulation, and structure prediction respectively. Each presentation was followed by a lively discussion by all the workshop attendees. The following findings and recommendations were derived from the three workshops. A seamless integration of GTL data spanning the entire range of genomics, proteomics, and metabolomics will be extremely challenging but it has to be treated as the first-class component of the GTL program to assure GTL's chances for success. High-throughput GTL facilities and ultrascale computing will make it possible to address the ultimate goal of modern biology: to achieve a fundamental, comprehensive, and systematic understanding of life. But first the GTL community needs to address the problem of the massive quantities and increased complexity of biological data produced by experiments and computations. Genome-scale collection, analysis

  20. Transcription factor binding sites prediction based on modified nucleosomes.

    Directory of Open Access Journals (Sweden)

    Mohammad Talebzadeh

    Full Text Available In computational methods, position weight matrices (PWMs are commonly applied for transcription factor binding site (TFBS prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP predictions and so are impoverished sources of information. Several studies have employed additional sources of information such as sequence conservation or the vicinity to transcription start sites to distinguish true binding regions from random ones. Recently, the spatial distribution of modified nucleosomes has been shown to be associated with different promoter architectures. These aligned patterns can facilitate DNA accessibility for transcription factors. We hypothesize that using data from these aligned and periodic patterns can improve the performance of binding region prediction. In this study, we propose two effective features, "modified nucleosomes neighboring" and "modified nucleosomes occupancy", to decrease FP in binding site discovery. Based on these features, we designed a logistic regression classifier which estimates the probability of a region as a TFBS. Our model learned each feature based on Sp1 binding sites on Chromosome 1 and was tested on the other chromosomes in human CD4+T cells. In this work, we investigated 21 histone modifications and found that only 8 out of 21 marks are strongly correlated with transcription factor binding regions. To prove that these features are not specific to Sp1, we combined the logistic regression classifier with the PWM, and created a new model to search TFBSs on the genome. We tested the model using transcription factors MAZ, PU.1 and ELF1 and compared the results to those using only the PWM. The results show that our model can predict Transcription factor binding regions more successfully. The relative simplicity of the model and capability of integrating other features make it a superior method

  1. [Hyperspectrum based prediction model for nitrogen content of apple flowers].

    Science.gov (United States)

    Zhu, Xi-Cun; Zhao, Geng-Xing; Wang, Ling; Dong, Fang; Lei, Tong; Zhan, Bing

    2010-02-01

    The present paper aims to quantitatively retrieve nitrogen content in apple flowers, so as to provide an important basis for apple informationization management. By using ASD FieldSpec 3 field spectrometer, hyperspectral reflectivity of 120 apple flower samples in full-bloom stage was measured and their nitrogen contents were analyzed. Based on the apple flower original spectrum and first derivative spectral characteristics, correlation analysis was carried out between apple flowers original spectrum and first derivative spectrum reflectivity and nitrogen contents, so as to determine the sensitive bands. Based on characteristic spectral parameters, prediction models were built, optimized and tested. The results indicated that the nitrogen content of apple was very significantly negatively correlated with the original spectral reflectance in the 374-696, 1 340-1 890 and 2 052-2 433 nm, while in 736-913 nm they were very significantly positively correlated; the first derivative spectrum in 637-675 nm was very significantly negatively correlated, and in 676-746 nm was very significantly positively correlated. All the six spectral parameters established were significantly correlated with the nitrogen content of apple flowers. Through further comparison and selection, the prediction models built with original spectral reflectance of 640 and 676 nm were determined as the best for nitrogen content prediction of apple flowers. The test results showed that the coefficients of determination (R2) of the two models were 0.825 8 and 0.893 6, the total root mean square errors (RMSE) were 0.732 and 0.638 6, and the slopes were 0.836 1 and 1.019 2 respectively. Therefore the models produced desired results for nitrogen content prediction of apple flowers with average prediction accuracy of 92.9% and 94.0%. This study will provide theoretical basis and technical support for rapid apple flower nitrogen content prediction and nutrition diagnosis.

  2. Empirical comparison of web-based antimicrobial peptide prediction tools.

    Science.gov (United States)

    Gabere, Musa Nur; Noble, William Stafford

    2017-07-01

    Antimicrobial peptides (AMPs) are innate immune molecules that exhibit activities against a range of microbes, including bacteria, fungi, viruses and protozoa. Recent increases in microbial resistance against current drugs has led to a concomitant increase in the need for novel antimicrobial agents. Over the last decade, a number of AMP prediction tools have been designed and made freely available online. These AMP prediction tools show potential to discriminate AMPs from non-AMPs, but the relative quality of the predictions produced by the various tools is difficult to quantify. We compiled two sets of AMP and non-AMP peptides, separated into three categories-antimicrobial, antibacterial and bacteriocins. Using these benchmark data sets, we carried out a systematic evaluation of ten publicly available AMP prediction methods. Among the six general AMP prediction tools-ADAM, CAMPR3(RF), CAMPR3(SVM), MLAMP, DBAASP and MLAMP-we find that CAMPR3(RF) provides a statistically significant improvement in performance, as measured by the area under the receiver operating characteristic (ROC) curve, relative to the other five methods. Surprisingly, for antibacterial prediction, the original AntiBP method significantly outperforms its successor, AntiBP2 based on one benchmark dataset. The two bacteriocin prediction tools, BAGEL3 and BACTIBASE, both provide very good performance and BAGEL3 outperforms its predecessor, BACTIBASE, on the larger of the two benchmarks. gaberemu@ngha.med.sa or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  3. Deep-Learning-Based Drug-Target Interaction Prediction.

    Science.gov (United States)

    Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

    2017-04-07

    Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

  4. The Dissolved Oxygen Prediction Method Based on Neural Network

    Directory of Open Access Journals (Sweden)

    Zhong Xiao

    2017-01-01

    Full Text Available The dissolved oxygen (DO is oxygen dissolved in water, which is an important factor for the aquaculture. Using BP neural network method with the combination of purelin, logsig, and tansig activation functions is proposed for the prediction of aquaculture’s dissolved oxygen. The input layer, hidden layer, and output layer are introduced in detail including the weight adjustment process. The breeding data of three ponds in actual 10 consecutive days were used for experiments; these ponds were located in Beihai, Guangxi, a traditional aquaculture base in southern China. The data of the first 7 days are used for training, and the data of the latter 3 days are used for the test. Compared with the common prediction models, curve fitting (CF, autoregression (AR, grey model (GM, and support vector machines (SVM, the experimental results show that the prediction accuracy of the neural network is the highest, and all the predicted values are less than 5% of the error limit, which can meet the needs of practical applications, followed by AR, GM, SVM, and CF. The prediction model can help to improve the water quality monitoring level of aquaculture which will prevent the deterioration of water quality and the outbreak of disease.

  5. Quantitative Method for Network Security Situation Based on Attack Prediction

    Directory of Open Access Journals (Sweden)

    Hao Hu

    2017-01-01

    Full Text Available Multistep attack prediction and security situation awareness are two big challenges for network administrators because future is generally unknown. In recent years, many investigations have been made. However, they are not sufficient. To improve the comprehensiveness of prediction, in this paper, we quantitatively convert attack threat into security situation. Actually, two algorithms are proposed, namely, attack prediction algorithm using dynamic Bayesian attack graph and security situation quantification algorithm based on attack prediction. The first algorithm aims to provide more abundant information of future attack behaviors by simulating incremental network penetration. Through timely evaluating the attack capacity of intruder and defense strategies of defender, the likely attack goal, path, and probability and time-cost are predicted dynamically along with the ongoing security events. Furthermore, in combination with the common vulnerability scoring system (CVSS metric and network assets information, the second algorithm quantifies the concealed attack threat into the surfaced security risk from two levels: host and network. Examples show that our method is feasible and flexible for the attack-defense adversarial network environment, which benefits the administrator to infer the security situation in advance and prerepair the critical compromised hosts to maintain normal network communication.

  6. Life history traits predict relative abundance in an assemblage of forest caterpillars.

    Science.gov (United States)

    Lind, Eric M; Barbosa, Pedro

    2010-11-01

    Species in a given trophic level occur in vastly unequal abundance, a pattern commonly documented but poorly explained for most taxa. Theoretical predictions of species density such as those arising from the metabolic theory of ecology hold well at large spatial and temporal scales but are not supported in many communities sampled at a relatively small scale. At these scales ecological factors may be more important than the inherent limits to energy use set by allometric scaling of mass. These factors include the amount of resources available, and the ability of individuals to convert these resources successfully into population growth. While previous studies have demonstrated the limits of macroecological theory in explaining local abundance, few studies have tested alternative generalized mechanisms determining abundance at the community scale. Using an assemblage of forest moth species found co-occurring as caterpillars on a single host plant species, we tested whether species abundance on that plant could be explained by mass allometry, intrinsic population growth, diet breadth, or some combination of these traits. We parameterized life history traits of the caterpillars in association with the host plant in both field and laboratory settings, so that the population growth estimate was specific to the plant on which abundance was measured. Using a generalized least-squares regression method incorporating phylogenetic relatedness, we found no relationship between abundance and mass but found that abundance was best explained by both intrinsic population growth rate and diet breadth. Species population growth potential was most affected by survivorship and larval development time on the host plant. Metabolic constraints may determine upper limits to local abundance levels for species, but local community abundance is strongly predicted by the potential for population increase and the resources available to that species in the environment.

  7. Prediction of Quality of Life in Asian Patients with Schizophrenia: A Cross-sectional Pilot Study

    Directory of Open Access Journals (Sweden)

    Carol C. Choo

    2017-10-01

    Full Text Available BackgroundThere has been a shift in mental health services from an emphasis on treatment focused on reducing symptoms to a more holistic approach involving quality of life (QOL and overall well-being. Many psychosocial variables are associated with QOL but a parsimonious framework is needed to deepen our understanding about the contribution of psychosocial factors in influencing the QOL of Asian patients with schizophrenia in Singapore. The study aimed to address the current gap in literature by analysis of QOL using available predictors in Asian patients with schizophrenia in Singapore.Methods43 Singaporean patients diagnosed with schizophrenia were recruited at a large teaching hospital in Singapore from January to May 2010 and were invited to complete questionnaires. Of the sample, 65.1% were females, ages ranged from 18 to 65 (M = 44.60, SD = 12.19. Available variables were subjected to regression analysis.FindingsThe data were analyzed using SPSS Version 23 with the alpha level set at 0.05. The final model with five predictors was significant in predicting QOL. Positive Re-appraisal, Social Support, Avoidant Coping, Duration of Hospitalization, and Education accounted for 47.2% of the variance (Adjusted R2 = 40.0% in QOL, F (5, 37 = 6.60, p < 0.001. Those with post-secondary or higher education had higher QOL than those with secondary or lower education. Duration of hospitalization negatively predicted QOL.ConclusionThe findings were discussed in regards to clinical implications for informing interventions to enhance QOL in patients with schizophrenia.

  8. Predicting quality of life and self-management from dyadic support and overprotection after myocardial infarction.

    Science.gov (United States)

    Joekes, Katherine; Maes, Stan; Warrens, Matthijs

    2007-11-01

    Using a self-regulatory framework, this study aims to identify how couples perceive a partner's support style after myocardial infarction (MI), and whether this predicts the patient's health-related quality of life (HR-QoL) and self-management (S-M) 9 months later. This longitudinal dyadic study includes 73 couples (86% of patients were men), recruited from two cardiac rehabilitation programmes in the Netherlands. Mean age of patients was 54.8 (SD=9.6) and of partners 52.5 (SD=9.8). Participants were interviewed and completed questionnaires at baseline (T1). Repeat questionnaires were returned by 69 and 67 couples after 3 (T2) and 9 months (T3), respectively. Support by partners is conceptualized in this study as 'active engagement' (AE), which involves the extent to which a partner engages the patient in conversations which focus on emotional support and problem solving. Levels of AE do not change over time, nor do they differ between members of the dyad. Levels of overprotection (OP) diminish with time, whilst patients consistently perceive more OP than partners report providing. Patients' experience of goal hindrance (at T3) due to the MI is associated with a decreased HR-QoL at T3 (controlling for baseline measures). The perception of having a supportive (AE) partner at T1 contributes to enhanced patient HR-QoL at each subsequent time point, although not to physical functioning. Perceiving a partner as overprotective (at T1) predicts worsened physical functioning in patients (at T3). Improvements in S-M at T3 (controlling for baseline measures) are reported by patients whose partner displays active engagement at T1. Cardiac rehabilitation should aim to redress the experience of goal disturbance and advise partners on how to provide support.

  9. Predictive Software Measures based on Z Specifications - A Case Study

    Directory of Open Access Journals (Sweden)

    Andreas Bollin

    2012-07-01

    Full Text Available Estimating the effort and quality of a system is a critical step at the beginning of every software project. It is necessary to have reliable ways of calculating these measures, and, it is even better when the calculation can be done as early as possible in the development life-cycle. Having this in mind, metrics for formal specifications are examined with a view to correlations to complexity and quality-based code measures. A case study, based on a Z specification and its implementation in ADA, analyzes the practicability of these metrics as predictors.

  10. Consistency of prediction across generation: explaining quality of life by family functioning and health-promoting behaviors.

    Science.gov (United States)

    Ali, Sehrish; Malik, Jamil A

    2015-09-01

    The study aimed to investigate the consistency of relationship between family functioning, health-promoting behaviors, and quality of life across generations in joint families. The sample comprises of 79 joint families (N = 316 members, n = 79 grandparents (grandfathers = 27, grandmothers = 52) n = 158 parents (fathers = 79, mothers = 79), and n = 79 grandchildren (girls = 61, boys = 18)). Data were collected on Self-Report Family Inventory, SFI, Health-Promoting Lifestyle Profile II, HPLP-II, and World Health Organization Quality of Life Scale BREF WHO QOL BREF. All three variables, i.e., family functioning, health-promoting behaviors, and quality of life, were modeled as latent variables. Analyses were conducted separately for each group. Results showed that in grandparents, family functioning predicted (β = .44, p life (R (2) = .85). Family functioning appears to have significant indirect effects (β = .34, p life. The model fit indices showed a good fit (IFI = .917, CFI = .910, RMSEA = .078) of the model of the data. For all other groups, i.e., fathers, mothers, and grandchildren, family functioning and health-promoting behaviors independently predicted quality of life (R (2) = .55, .67, and .54, respectively). Our results showed that family functioning and health-promoting behaviors are consistent predictors of quality of life across generations.

  11. A time series based sequence prediction algorithm to detect activities of daily living in smart home.

    Science.gov (United States)

    Marufuzzaman, M; Reaz, M B I; Ali, M A M; Rahman, L F

    2015-01-01

    The goal of smart homes is to create an intelligent environment adapting the inhabitants need and assisting the person who needs special care and safety in their daily life. This can be reached by collecting the ADL (activities of daily living) data and further analysis within existing computing elements. In this research, a very recent algorithm named sequence prediction via enhanced episode discovery (SPEED) is modified and in order to improve accuracy time component is included. The modified SPEED or M-SPEED is a sequence prediction algorithm, which modified the previous SPEED algorithm by using time duration of appliance's ON-OFF states to decide the next state. M-SPEED discovered periodic episodes of inhabitant behavior, trained it with learned episodes, and made decisions based on the obtained knowledge. The results showed that M-SPEED achieves 96.8% prediction accuracy, which is better than other time prediction algorithms like PUBS, ALZ with temporal rules and the previous SPEED. Since human behavior shows natural temporal patterns, duration times can be used to predict future events more accurately. This inhabitant activity prediction system will certainly improve the smart homes by ensuring safety and better care for elderly and handicapped people.

  12. GM(1,Nmodel-based prediction of carbon steel corrosion rate

    Directory of Open Access Journals (Sweden)

    ZHENG Ruyan

    2018-02-01

    Full Text Available [Objectives] The corrosion rate prediction of carbon steel in marine environment is very complicated and uncertain. [Methods] To improve the accuracy of prediction model in view of the low precision of grey prediction model for corrosion rate of carbon steel at present stage, the key factors which affect the corrosion rate can be concluded from the grey theory analysis of marine environment and corrosion rate of carbon steel, and then the GM(1,N) model which can predict the corrosion rate of carbon steel is established. [Results] According to the case analysis, the main factors that affect the corrosion rate in seaareas of Qindao, Xiamen, Zhousan, Yulin coastal region are seawater temperature, biofouling, pH value and salinity, and based on the above, the establishment of GM(1,5 model possesses higher precision and less computational costs. [Conclusions] The research shows that the GM(1,N) model can predict the corrosion rate of carbon steel effectively, and also provide a theoretical basis for the prediction of residual life of carbon steel.

  13. Prediction of clearance, volume of distribution and half-life by allometric scaling and by use of plasma concentrations predicted from pharmacokinetic constants: a comparative study.

    Science.gov (United States)

    Mahmood, I

    1999-08-01

    Pharmacokinetic parameters (clearance, CL, volume of distribution in the central compartment, VdC, and elimination half-life, t1/2beta) predicted by an empirical allometric approach have been compared with parameters predicted from plasma concentrations calculated by use of the pharmacokinetic constants A, B, alpha and beta, where A and B are the intercepts on the Y axis of the plot of plasma concentration against time and alpha and beta are the rate constants, both pairs of constants being for the distribution and elimination phases, respectively. The pharmacokinetic parameters of cefpiramide, actisomide, troglitazone, procaterol, moxalactam and ciprofloxacin were scaled from animal data obtained from the literature. Three methods were used to generate plots for the prediction of clearance in man: dependence of clearance on body weight (simple allometric equation); dependence of the product of clearance and maximum life-span potential (MLP) on body weight; and dependence of the product of clearance and brain weight on body weight. Plasma concentrations of the drugs were predicted in man by use of A, B, alpha and beta obtained from animal data. The predicted plasma concentrations were then used to calculate CL, VdC and t1/2beta. The pharmacokinetic parameters predicted by use of both approaches were compared with measured values. The results indicate that simple allometry did not predict clearance satisfactorily for actisomide, troglitazone, procaterol and ciprofloxacin. Use of MLP or the product of clearance and brain weight improved the prediction of clearance for these four drugs. Except for troglitazone, VdC and t1/2beta predicted for man by use of the allometric approach were comparable with measured values for the drugs studied. CL, VdC and t1/2beta predicted by use of pharmacokinetic constants were comparable with values predicted by simple allometry. Thus, if simple allometry failed to predict clearance of a drug, so did the pharmacokinetic constant

  14. Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data

    Directory of Open Access Journals (Sweden)

    Esther I. Metting

    2016-01-01

    Full Text Available The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215. Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%. Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool.

  15. Results of fatigue tests and prediction of fatigue life under superposed stress wave and combined superposed stress wave

    International Nuclear Information System (INIS)

    Takasugi, Shunji; Horikawa, Takeshi; Tsunenari, Toshiyasu; Nakamura, Hiroshi

    1983-01-01

    In order to examine fatigue life prediction methods at high temperatures where creep damage need not be taken into account, fatigue tests were carried out on plane bending specimens of alloy steels (SCM 435, 2 1/4Cr-1Mo) under superposed and combined superposed stress waves at room temperature and 500 0 C. The experimental data were compared with the fatigue lives predicted by using the cycle counting methods (range pair, range pair mean and zero-cross range pair mean methods), the modified Goodman's equation and the modified Miner's rule. The main results were as follows. (1) The fatigue life prediction method which is being used for the data at room temperature is also applicable to predict the life at high temperatures. The range pair mean method is especially better than other cycle counting methods. The zero-cross range pair mean method gives the estimated lives on the safe side of the experimental lives. (2) The scatter bands of N-bar/N-barsub(es) (experimental life/estimated life) becomes narrower when the following equation is used instead of the modified Goodman's equation for predicting the effect of mean stress on fatigue life. σ sub(t) = σ sub(a) / (1 - Sigma-s sub(m) / kσ sub(B)) σ sub(t); stress amplitude at zero mean stress (kg/mm 2 ) σ sub(B); tensile strength (kg/mm 2 ) σ sub(m); mean stress (kg/mm 2 ) σ sub(a); stress amplitude (kg/mm 2 ) k; modified coefficient of σ sub(B) (author)

  16. Vehicle Driving Risk Prediction Based on Markov Chain Model

    Directory of Open Access Journals (Sweden)

    Xiaoxia Xiong

    2018-01-01

    Full Text Available A driving risk status prediction algorithm based on Markov chain is presented. Driving risk states are classified using clustering techniques based on feature variables describing the instantaneous risk levels within time windows, where instantaneous risk levels are determined in time-to-collision and time-headway two-dimension plane. Multinomial Logistic models with recursive feature variable estimation method are developed to improve the traditional state transition probability estimation, which also takes into account the comprehensive effects of driving behavior, traffic, and road environment factors on the evolution of driving risk status. The “100-car” natural driving data from Virginia Tech is employed for the training and validation of the prediction model. The results show that, under the 5% false positive rate, the prediction algorithm could have high prediction accuracy rate for future medium-to-high driving risks and could meet the timeliness requirement of collision avoidance warning. The algorithm could contribute to timely warning or auxiliary correction to drivers in the approaching-danger state.

  17. Computational prediction of drug solubility in lipid based formulation excipients.

    Science.gov (United States)

    Persson, Linda C; Porter, Christopher J H; Charman, William N; Bergström, Christel A S

    2013-12-01

    To investigate if drug solubility in pharmaceutical excipients used in lipid based formulations (LBFs) can be predicted from physicochemical properties. Solubility was measured for 30 structurally diverse drug molecules in soybean oil (SBO, long-chain triglyceride; TGLC), Captex355 (medium-chain triglyceride; TGMC), polysorbate 80 (PS80; surfactant) and PEG400 co-solvent and used as responses during PLS model development. Melting point and calculated molecular descriptors were used as variables and the PLS models were validated with test sets and permutation tests. Solvation capacity of SBO and Captex355 was equal on a mol per mol scale (R (2) = 0.98). A strong correlation was also found between PS80 and PEG400 (R (2) = 0.85), identifying the significant contribution of the ethoxylation for the solvation capacity of PS80. In silico models based on calculated descriptors were successfully developed for drug solubility in SBO (R (2) = 0.81, Q (2) = 0.76) and Captex355 (R (2) = 0.84, Q (2) = 0.80). However, solubility in PS80 and PEG400 were not possible to quantitatively predict from molecular structure. Solubility measured in one excipient can be used to predict solubility in another, herein exemplified with TGMC versus TGLC, and PS80 versus PEG400. We also show, for the first time, that solubility in TGMC and TGLC can be predicted from rapidly calculated molecular descriptors.

  18. Predicting online ratings based on the opinion spreading process

    Science.gov (United States)

    He, Xing-Sheng; Zhou, Ming-Yang; Zhuo, Zhao; Fu, Zhong-Qian; Liu, Jian-Guo

    2015-10-01

    Predicting users' online ratings is always a challenge issue and has drawn lots of attention. In this paper, we present a rating prediction method by combining the user opinion spreading process with the collaborative filtering algorithm, where user similarity is defined by measuring the amount of opinion a user transfers to another based on the primitive user-item rating matrix. The proposed method could produce a more precise rating prediction for each unrated user-item pair. In addition, we introduce a tunable parameter λ to regulate the preferential diffusion relevant to the degree of both opinion sender and receiver. The numerical results for Movielens and Netflix data sets show that this algorithm has a better accuracy than the standard user-based collaborative filtering algorithm using Cosine and Pearson correlation without increasing computational complexity. By tuning λ, our method could further boost the prediction accuracy when using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) as measurements. In the optimal cases, on Movielens and Netflix data sets, the corresponding algorithmic accuracy (MAE and RMSE) are improved 11.26% and 8.84%, 13.49% and 10.52% compared to the item average method, respectively.

  19. Chaos Time Series Prediction Based on Membrane Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Meng Li

    2015-01-01

    Full Text Available This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m and least squares support vector machine (LS-SVM (γ,σ by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE, root mean square error (RMSE, and mean absolute percentage error (MAPE.

  20. PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

    Directory of Open Access Journals (Sweden)

    Jiangning Song

    Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

  1. Appreciation and Life Satisfaction: Does Appreciation Uniquely Predict Life Satisfaction above Gender, Coping Skills, Self-Esteem, and Positive Affectivity?

    Science.gov (United States)

    Halle, Joshua Solomon

    2015-01-01

    The primary purpose of this research was to examine whether appreciation explains variance in life satisfaction after controlling for gender, positive affectivity, self-esteem, and coping skills. Two hundred ninety-eight undergraduates went to the informed consent page of the online survey composed of the Appreciation Scale, the Satisfaction With…

  2. Reconstruction of biological networks based on life science data integration

    Directory of Open Access Journals (Sweden)

    Kormeier Benjamin

    2010-06-01

    Full Text Available For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

  3. Life cycle assessment needs predictive spatial modelling for biodiversity and ecosystem services

    Science.gov (United States)

    Chaplin-Kramer, Rebecca; Sim, Sarah; Hamel, Perrine; Bryant, Benjamin; Noe, Ryan; Mueller, Carina; Rigarlsford, Giles; Kulak, Michal; Kowal, Virginia; Sharp, Richard; Clavreul, Julie; Price, Edward; Polasky, Stephen; Ruckelshaus, Mary; Daily, Gretchen

    2017-01-01

    International corporations in an increasingly globalized economy exert a major influence on the planet's land use and resources through their product design and material sourcing decisions. Many companies use life cycle assessment (LCA) to evaluate their sustainability, yet commonly-used LCA methodologies lack the spatial resolution and predictive ecological information to reveal key impacts on climate, water and biodiversity. We present advances for LCA that integrate spatially explicit modelling of land change and ecosystem services in a Land-Use Change Improved (LUCI)-LCA. Comparing increased demand for bioplastics derived from two alternative feedstock-location scenarios for maize and sugarcane, we find that the LUCI-LCA approach yields results opposite to those of standard LCA for greenhouse gas emissions and water consumption, and of different magnitudes for soil erosion and biodiversity. This approach highlights the importance of including information about where and how land-use change and related impacts will occur in supply chain and innovation decisions. PMID:28429710

  4. Tool life prediction under multi-cycle loading conditions: A feasibility study

    Directory of Open Access Journals (Sweden)

    Yuan Xi

    2015-01-01

    Full Text Available In the present research, the friction and wear behaviour of a hard coating were studied by using ball-on-disc tests to simulate the wear process of the coated tools for sheet metal forming process. The evolution of the friction coefficient followed a typical dual-plateau pattern, i.e. at the initial stage of sliding, the friction coefficient was relatively low, followed by a sharp increase due to the breakdown of the coatings after a certain number of cyclic dynamic loadings. This phenomenon was caused by the interactive response between the friction and wear from a coating tribo-system, which has not been addressed so far by metal forming researchers, and constant friction coefficient values are normally used in the FE simulations to represent the complex tribological nature at the contact interfaces. Meanwhile, most of the current FE simulations are single cycle, whereas most sheet metal forming operations are conducted as multi-cycle. Therefore, a novel friction/wear interactive friction model was developed to, simultaneously, characterise the evolutions of friction coefficient and the remaining thickness of the coating layer, to enable the wear life of coated tooling to be predicted. The friction model was then implemented into the FE simulation of a sheet metal forming process for feasibility study.

  5. Implicit theories about willpower predict self-regulation and grades in everyday life.

    Science.gov (United States)

    Job, Veronika; Walton, Gregory M; Bernecker, Katharina; Dweck, Carol S

    2015-04-01

    Laboratory research shows that when people believe that willpower is an abundant (rather than highly limited) resource they exhibit better self-control after demanding tasks. However, some have questioned whether this "nonlimited" theory leads to squandering of resources and worse outcomes in everyday life when demands on self-regulation are high. To examine this, we conducted a longitudinal study, assessing students' theories about willpower and tracking their self-regulation and academic performance. As hypothesized, a nonlimited theory predicted better self-regulation (better time management and less procrastination, unhealthy eating, and impulsive spending) for students who faced high self-regulatory demands. Moreover, among students taking a heavy course load, those with a nonlimited theory earned higher grades, which was mediated by less procrastination. These findings contradict the idea that a limited theory helps people allocate their resources more effectively; instead, it is people with the nonlimited theory who self-regulate well in the face of high demands. (c) 2015 APA, all rights reserved).

  6. Offset Free Tracking Predictive Control Based on Dynamic PLS Framework

    Directory of Open Access Journals (Sweden)

    Jin Xin

    2017-10-01

    Full Text Available This paper develops an offset free tracking model predictive control based on a dynamic partial least square (PLS framework. First, state space model is used as the inner model of PLS to describe the dynamic system, where subspace identification method is used to identify the inner model. Based on the obtained model, multiple independent model predictive control (MPC controllers are designed. Due to the decoupling character of PLS, these controllers are running separately, which is suitable for distributed control framework. In addition, the increment of inner model output is considered in the cost function of MPC, which involves integral action in the controller. Hence, the offset free tracking performance is guaranteed. The results of an industry background simulation demonstrate the effectiveness of proposed method.

  7. PREDICTIVE POTENTIAL FIELD-BASED COLLISION AVOIDANCE FOR MULTICOPTERS

    Directory of Open Access Journals (Sweden)

    M. Nieuwenhuisen

    2013-08-01

    Full Text Available Reliable obstacle avoidance is a key to navigating with UAVs in the close vicinity of static and dynamic obstacles. Wheel-based mobile robots are often equipped with 2D or 3D laser range finders that cover the 2D workspace sufficiently accurate and at a high rate. Micro UAV platforms operate in a 3D environment, but the restricted payload prohibits the use of fast state-of-the-art 3D sensors. Thus, perception of small obstacles is often only possible in the vicinity of the UAV and a fast collision avoidance system is necessary. We propose a reactive collision avoidance system based on artificial potential fields, that takes the special dynamics of UAVs into account by predicting the influence of obstacles on the estimated trajectory in the near future using a learned motion model. Experimental evaluation shows that the prediction leads to smoother trajectories and allows to navigate collision-free through passageways.

  8. Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking

    Science.gov (United States)

    2015-07-01

    Traditional path- tracking controllers would represent the robot using a bicycle model (Figure 8) with steering angle, δcmd,k, and linear velocity...Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking Chris J. Ostafew Institute for Aerospace Studies...paper presents a Learning-based Nonlinear Model Predictive Control (LB-NMPC) algorithm to achieve high-performance path tracking in challenging off-road

  9. Computational Prediction of Drug Solubility in Lipid Based Formulation Excipients

    OpenAIRE

    Persson, Linda C.; Porter, Christopher J. H.; Charman, William N.; Bergstr?m, Christel A. S.

    2013-01-01

    ABSTRACT Purpose To investigate if drug solubility in pharmaceutical excipients used in lipid based formulations (LBFs) can be predicted from physicochemical properties. Methods Solubility was measured for 30 structurally diverse drug molecules in soybean oil (SBO, long-chain triglyceride; TGLC), Captex355 (medium-chain triglyceride; TGMC), polysorbate 80 (PS80; surfactant) and PEG400 co-solvent and used as responses during PLS model development. Melting point and calculated molecular descrip...

  10. Quality of life following endonasal skull base surgery.

    Science.gov (United States)

    Pant, Harshita; Bhatki, Amol M; Snyderman, Carl H; Vescan, Allan D; Carrau, Ricardo L; Gardner, Paul; Prevedello, Daniel; Kassam, Amin B

    2010-01-01

    The importance of quality of life (QOL) outcomes following treatments for head and neck tumors are now increasingly appreciated and measured to improve medical and surgical care for these patients. An understanding of the definitions in the setting of health care and the use of appropriate QOL instruments and measures are critical to obtain meaningful information that guides decision making in various aspects of patient health care. QOL outcomes following cranial base surgery is only recently being defined. In this article, we describe the current published data on QOL outcomes following cranial base surgery and provide preliminary prospective data on QOL outcomes and sinonasal morbidity in patients who underwent endonasal cranial base surgery for management of various skull base tumors at our institution. We used a disease-specific multidimensional instrument to measure QOL outcomes in these patients. Our results show that although sinonasal morbidity is increased, this is temporary, and the vast majority of patients have a very good QOL by 4 to 6 months after endonasal approach to the cranial base.

  11. Life cycle environmental impacts of wastewater-based algal biofuels.

    Science.gov (United States)

    Mu, Dongyan; Min, Min; Krohn, Brian; Mullins, Kimberley A; Ruan, Roger; Hill, Jason

    2014-10-07

    Recent research has proposed integrating wastewater treatment with algae cultivation as a way of producing algal biofuels at a commercial scale more sustainably. This study evaluates the environmental performance of wastewater-based algal biofuels with a well-to-wheel life cycle assessment (LCA). Production pathways examined include different nutrient sources (municipal wastewater influent to the activated sludge process, centrate from the sludge drying process, swine manure, and freshwater with synthetic fertilizers) combined with emerging biomass conversion technologies (microwave pyrolysis, combustion, wet lipid extraction, and hydrothermal liquefaction). Results show that the environmental performance of wastewater-based algal biofuels is generally better than freshwater-based algal biofuels, but depends on the characteristics of the wastewater and the conversion technologies. Of 16 pathways compared, only the centrate cultivation with wet lipid extraction pathway and the centrate cultivation with combustion pathway have lower impacts than petroleum diesel in all environmental categories examined (fossil fuel use, greenhouse gas emissions, eutrophication potential, and consumptive water use). The potential for large-scale implementation of centrate-based algal biofuel, however, is limited by availability of centrate. Thus, it is unlikely that algal biofuels can provide a large-scale and environmentally preferable alternative to petroleum transportation fuels without considerable improvement in current production technologies. Additionally, the cobenefit of wastewater-based algal biofuel production as an alternate means of treating various wastewaters should be further explored.

  12. THE SHELF LIFE PREDICTING OF IMMUNOENZYME COMBINED TEST-SYSTEMS FOR HIV1/2 DIAGNOSTICS

    Directory of Open Access Journals (Sweden)

    Trokhymchuk

    2016-08-01

    Full Text Available The aim of the research was to determine the shelf life of the ELISA test kit DIA-HIVAg/Ab (PJSC "SPC" Diaproph-Med" intended for the determination of antibodies to HIV1/2 and p24 HIV1 antigen using accelerated storage model at elevated temperatures. It is established that the thermal inactivation process is subject to a first-order kinetic law. The dependence of the rate constants of inactivation (lnK on temperature (1 / T is described by the Arrhenius equation at 95% probability level (F-test. Calculated on the basis of this model, the activation energy (ΔEa equals 23.27 kcal • mol-1. It is established that the projected shelf life of the test kit was 2 years and 1 month when stored at 4 °C in terms of reduction of its diagnostic activity by 10%. Isothermal method of accelerated storage based on the Arrhenius model can significantly save time by determining the expiration date of the test kit as early as at the stages of its development or modification. The obtained data can be used for confirmation of the diagnostic kit stability studies, in terms of long-term storage, correction recommended conditions, and for determination of test kit capability of withstanding exposure to adverse environmental factors, which may occur during transportation and storage.

  13. Health-related quality of life and its predictive role for analgesic effect in patients with painful polyneuropathy

    DEFF Research Database (Denmark)

    Otto, Marit; Bach, Flemming W; Jensen, Troels S

    2007-01-01

    Painful polyneuropathy is a common neuropathic pain condition. The present study describes health-related quality of life (HRQL) in a sample of patients with painful polyneuropathy of different origin and the possible predictive role of HRQL for analgesic effect. Ninety-three patients with a diag...

  14. Prediction of COPD-specific health-related quality of life in primary care COPD patients: a prospective cohort study

    NARCIS (Netherlands)

    Siebeling, Lara; Musoro, Jammbe Z.; Geskus, Ronald B.; Zoller, Marco; Muggensturm, Patrick; Frei, Anja; Puhan, Milo A.; ter Riet, Gerben

    2014-01-01

    Health-related quality of life (HRQL) is an important patient-reported outcome for chronic obstructive pulmonary disease (COPD). We developed models predicting chronic respiratory questionnaire (CRQ) dyspnoea, fatigue, emotional function, mastery and overall HRQL at 6 and 24 months using predictors

  15. Using Self-Determination of Senior College Students with Disabilities to Predict Their Quality of Life One Year after Graduation

    Science.gov (United States)

    Chao, Pen-Chiang

    2018-01-01

    The purpose of this study was to assess the correlation and predictive relationship between self-determination and quality of life of college students with disabilities. Subjects were 145 senior college students recruited from northern Taiwan. Subjects' age ranged from 22 to 25 years and their disabilities varied, including visual impairments (n =…

  16. Coping Styles, Social Support, Relational Self-Construal, and Resilience in Predicting Students' Adjustment to University Life

    Science.gov (United States)

    Rahat, Enes; Ilhan, Tahsin

    2016-01-01

    The purpose of the present study is to investigate how well coping styles, social support, relational self-construal, and resilience characteristics predict first year university students' ability to adjust to university life. Participants consisted of 527 at-risk students attending a state university in Turkey. The Personal Information Form, Risk…

  17. Interaction between serotonin transporter gene variants and life events predicts response to antidepressants in the GENDEP project

    DEFF Research Database (Denmark)

    Keers, R.; Uher, R.; Huezo-Diaz, P.

    2011-01-01

    , and several polymorphisms in the serotonin transporter gene (SLC6A4) have been genotyped including the serotonin transporter-linked polymorphic region (5-HTTLPR). Stressful life events were shown to predict a significantly better response to escitalopram but had no effect on response to nortriptyline...

  18. Seminal Quality Prediction Using Clustering-Based Decision Forests

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-08-01

    Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

  19. Simple criterion for predicting fatigue life under combined bending and torsion loading

    Directory of Open Access Journals (Sweden)

    K. Slámečka

    2017-07-01

    Full Text Available Multiaxial fatigue is a challenging problem and, consequently, a number of methods has been developed to aid in design of components and assemblies. Following the complexity of the problem, these approaches are often elaborate and it is difficult to use them for simple loading cases. In this paper, an empirical approach for constant amplitude, proportional axial and torsion loading is introduced to serve as a basic engineering tool for estimating fatigue life of rotational structural parts. The criterion relies on a quadratic equivalent-stress formula and requires one constant parameter to be determined from experiments. The comparison with similar classical stressbased approaches using data on diverse materials (several steels, aluminium alloy, and nickel base superalloy reveals very good agreement with experimental data.

  20. A Modified Fatigue Damage Model for High-Cycle Fatigue Life Prediction

    Directory of Open Access Journals (Sweden)

    Meng Wang

    2016-01-01

    Full Text Available Based on the assumption of quasibrittle failure under high-cycle fatigue for the metal material, the damage constitutive equation and the modified damage evolution equation are obtained with continuum damage mechanics. Then, finite element method (FEM is used to describe the failure process of metal material. The increment of specimen’s life and damage state can be researched using damage mechanics-FEM. Finally, the lifetime of the specimen is got at the given stress level. The damage mechanics-FEM is inserted into ABAQUS with subroutine USDFLD and the Python language is used to simulate the fatigue process of titanium alloy specimens. The simulation results have a good agreement with the testing results under constant amplitude loading, which proves the accuracy of the method.

  1. New Temperature-based Models for Predicting Global Solar Radiation

    International Nuclear Information System (INIS)

    Hassan, Gasser E.; Youssef, M. Elsayed; Mohamed, Zahraa E.; Ali, Mohamed A.; Hanafy, Ahmed A.

    2016-01-01

    Highlights: • New temperature-based models for estimating solar radiation are investigated. • The models are validated against 20-years measured data of global solar radiation. • The new temperature-based model shows the best performance for coastal sites. • The new temperature-based model is more accurate than the sunshine-based models. • The new model is highly applicable with weather temperature forecast techniques. - Abstract: This study presents new ambient-temperature-based models for estimating global solar radiation as alternatives to the widely used sunshine-based models owing to the unavailability of sunshine data at all locations around the world. Seventeen new temperature-based models are established, validated and compared with other three models proposed in the literature (the Annandale, Allen and Goodin models) to estimate the monthly average daily global solar radiation on a horizontal surface. These models are developed using a 20-year measured dataset of global solar radiation for the case study location (Lat. 30°51′N and long. 29°34′E), and then, the general formulae of the newly suggested models are examined for ten different locations around Egypt. Moreover, the local formulae for the models are established and validated for two coastal locations where the general formulae give inaccurate predictions. Mostly common statistical errors are utilized to evaluate the performance of these models and identify the most accurate model. The obtained results show that the local formula for the most accurate new model provides good predictions for global solar radiation at different locations, especially at coastal sites. Moreover, the local and general formulas of the most accurate temperature-based model also perform better than the two most accurate sunshine-based models from the literature. The quick and accurate estimations of the global solar radiation using this approach can be employed in the design and evaluation of performance for

  2. Perceived social support predicted quality of life in patients with heart failure, but the effect is mediated by depressive symptoms.

    Science.gov (United States)

    Chung, Misook L; Moser, Debra K; Lennie, Terry A; Frazier, Susan K

    2013-09-01

    Depressive symptoms and inadequate social support are well-known independent predictors of increased mortality and morbidity in heart failure (HF). However, it is unclear how depressive symptoms and social support interact to influence quality of life. Thus, the purpose of this study was to determine the nature of the relationships (direct, mediator, and moderator) among depressive symptoms, social support, and quality of life in patients with HF. We performed a secondary data analysis that included 362 patients with HF who completed the measures of depressive symptoms (the Beck Depression Inventory-II), perceived social support (the Multidimensional Scale of Perceived Social Support), and quality of life (the Minnesota Living with Heart Failure Questionnaire) instruments. The direct, mediator, and moderator effects of both depressive symptoms and social support on quality of life were tested using multiple regressions and 2 × 2 ANCOVA. Less social support and greater depressive symptoms independently predicted poorer quality of life. The relationship between social support and quality of life was mediated by depressive symptoms. Neither social support nor depressive symptoms moderated quality of life. Promotion of social support will improve quality of life only when depressive symptoms are also effectively managed.

  3. Environmental education - an approach based on the concept of life

    Directory of Open Access Journals (Sweden)

    J. Fourie

    1990-10-01

    Full Text Available Environmental education is described as an enterprise aiming at a philosophy of life and therefore as a matter of life. This suggests the concept of life as a natural foundation for an approach to environmental education. Therefore a reflection on the phenomenon of life is offered in which the 'philosophy of life' or vitalist philosophy is reviewed. It is argued that life is a multi-levelled phenomenon and that a monolithic view of life is inadequate. A functional definition of life is proposed in which the microbiological description of life, its link with the abiotic aspect of reality, its other relationships and its spiritual potential are respected. This is used as the ground for an exemplary discussion of life at the levels suggested by the philosophical reflection, viz. life and the individual (which concentrates mainly on the biological aspect, life and the community (concentrating on the social aspect, life and the ecosystem (concentrating primarily on the relationship between abiotic and biotic, and life and the cosmos (which reaches the limit of the authors' task. The need for an ethic is related to these levels and the idea of responsibility is developed with recourse to ancient texts in which comparable ethical implications for the environment are contained. Finally, some practical suggestions are made for implementing the results of the argument in environmental education.

  4. Power system dynamic state estimation using prediction based evolutionary technique

    International Nuclear Information System (INIS)

    Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

    2016-01-01

    In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

  5. Fuzzy subtractive clustering based prediction model for brand association analysis

    Directory of Open Access Journals (Sweden)

    Widodo Imam Djati

    2018-01-01

    Full Text Available The brand is one of the crucial elements that determine the success of a product. Consumers in determining the choice of a product will always consider product attributes (such as features, shape, and color, however consumers are also considering the brand. Brand will guide someone to associate a product with specific attributes and qualities. This study was designed to identify the product attributes and predict brand performance with those attributes. A survey was run to obtain the attributes affecting the brand. Subtractive Fuzzy Clustering was used to classify and predict product brand association based aspects of the product under investigation. The result indicates that the five attributes namely shape, ease, image, quality and price can be used to classify and predict the brand. Training step gives best FSC model with radii (ra = 0.1. It develops 70 clusters/rules with MSE (Training is 9.7093e-016. By using 14 data testing, the model can predict brand very well (close to the target with MSE is 0.6005 and its’ accuracy rate is 71%.

  6. BLANNOTATOR: enhanced homology-based function prediction of bacterial proteins

    Directory of Open Access Journals (Sweden)

    Kankainen Matti

    2012-02-01

    Full Text Available Abstract Background Automated function prediction has played a central role in determining the biological functions of bacterial proteins. Typically, protein function annotation relies on homology, and function is inferred from other proteins with similar sequences. This approach has become popular in bacterial genomics because it is one of the few methods that is practical for large datasets and because it does not require additional functional genomics experiments. However, the existing solutions produce erroneous predictions in many cases, especially when query sequences have low levels of identity with the annotated source protein. This problem has created a pressing need for improvements in homology-based annotation. Results We present an automated method for the functional annotation of bacterial protein sequences. Based on sequence similarity searches, BLANNOTATOR accurately annotates query sequences with one-line summary descriptions of protein function. It groups sequences identified by BLAST into subsets according to their annotation and bases its prediction on a set of sequences with consistent functional information. We show the results of BLANNOTATOR's performance in sets of bacterial proteins with known functions. We simulated the annotation process for 3090 SWISS-PROT proteins using a database in its state preceding the functional characterisation of the query protein. For this dataset, our method outperformed the five others that we tested, and the improved performance was maintained even in the absence of highly related sequence hits. We further demonstrate the value of our tool by analysing the putative proteome of Lactobacillus crispatus strain ST1. Conclusions BLANNOTATOR is an accurate method for bacterial protein function prediction. It is practical for genome-scale data and does not require pre-existing sequence clustering; thus, this method suits the needs of bacterial genome and metagenome researchers. The method and a

  7. Application of a Predictive Growth Model of Pseudomonas spp. for Estimating Shelf Life of Fresh Agaricus bisporus.

    Science.gov (United States)

    Wang, Jianming; Chen, Junran; Hu, Yunfeng; Hu, Hanyan; Liu, Guohua; Yan, Ruixiang

    2017-10-01

    For prediction of the shelf life of the mushroom Agaricus bisporus, the growth curve of the main spoilage microorganisms was studied under isothermal conditions at 2 to 22°C with a modified Gompertz model. The effect of temperature on the growth parameters for the main spoilage microorganisms was quantified and modeled using the square root model. Pseudomonas spp. were the main microorganisms causing A. bisporus decay, and the modified Gompertz model was useful for modelling the growth curve of Pseudomonas spp. All the bias factors values of the model were close to 1. By combining the modified Gompertz model with the square root model, a prediction model to estimate the shelf life of A. bisporus as a function of storage temperature was developed. The model was validated for A. bisporus stored at 6, 12, and 18°C, and adequate agreement was found between the experimental and predicted data.

  8. Imputation for transcription factor binding predictions based on deep learning.

    Directory of Open Access Journals (Sweden)

    Qian Qin

    2017-02-01

    Full Text Available Understanding the cell-specific binding patterns of transcription factors (TFs is fundamental to studying gene regulatory networks in biological systems, for which ChIP-seq not only provides valuable data but is also considered as the gold standard. Despite tremendous efforts from the scientific community to conduct TF ChIP-seq experiments, the available data represent only a limited percentage of ChIP-seq experiments, considering all possible combinations of TFs and cell lines. In this study, we demonstrate a method for accurately predicting cell-specific TF binding for TF-cell line combinations based on only a small fraction (4% of the combinations using available ChIP-seq data. The proposed model, termed TFImpute, is based on a deep neural network with a multi-task learning setting to borrow information across transcription factors and cell lines. Compared with existing methods, TFImpute achieves comparable accuracy on TF-cell line combinations with ChIP-seq data; moreover, TFImpute achieves better accuracy on TF-cell line combinations without ChIP-seq data. This approach can predict cell line specific enhancer activities in K562 and HepG2 cell lines, as measured by massively parallel reporter assays, and predicts the impact of SNPs on TF binding.

  9. CMC Property Variability and Life Prediction Methods for Turbine Engine Component Application

    Science.gov (United States)

    Cheplak, Matthew L.

    2004-01-01

    The ever increasing need for lower density and higher temperature-capable materials for aircraft engines has led to the development of Ceramic Matrix Composites (CMCs). Today's aircraft engines operate with >3000"F gas temperatures at the entrance to the turbine section, but unless heavily cooled, metallic components cannot operate above approx.2000 F. CMCs attempt to push component capability to nearly 2700 F with much less cooling, which can help improve engine efficiency and performance in terms of better fuel efficiency, higher thrust, and reduced emissions. The NASA Glenn Research Center has been researching the benefits of the SiC/SiC CMC for engine applications. A CMC is made up of a matrix material, fibers, and an interphase, which is a protective coating over the fibers. There are several methods or architectures in which the orientation of the fibers can be manipulated to achieve a particular material property objective as well as a particular component geometric shape and size. The required shape manipulation can be a limiting factor in the design and performance of the component if there is a lack of bending capability of the fiber as making the fiber more flexible typically sacrifices strength and other fiber properties. Various analysis codes are available (pcGINA, CEMCAN) that can predict the effective Young's Moduli, thermal conductivities, coefficients of thermal expansion (CTE), and various other properties of a CMC. There are also various analysis codes (NASAlife) that can be used to predict the life of CMCs under expected engine service conditions. The objective of this summer study is to utilize and optimize these codes for examining the tradeoffs between CMC properties and the complex fiber architectures that will be needed for several different component designs. For example, for the pcGINA code, there are six variations of architecture available. Depending on which architecture is analyzed, the user is able to specify the fiber tow size, tow

  10. Human Posture and Movement Prediction based on Musculoskeletal Modeling

    DEFF Research Database (Denmark)

    Farahani, Saeed Davoudabadi

    2014-01-01

    Abstract This thesis explores an optimization-based formulation, so-called inverse-inverse dynamics, for the prediction of human posture and motion dynamics performing various tasks. It is explained how this technique enables us to predict natural kinematic and kinetic patterns for human posture...... and motion using AnyBody Modeling System (AMS). AMS uses inverse dynamics to analyze musculoskeletal systems and is, therefore, limited by its dependency on input kinematics. We propose to alleviate this dependency by assuming that voluntary postures and movement strategies in humans are guided by a desire...... specifications. The model is then scaled to the desired anthropometric data by means of one of the existing scaling law in AMS. If the simulation results are to be compared with the experimental measurements, the model should be scaled to match the involved subjects. Depending on the scientific question...

  11. Construction Worker Fatigue Prediction Model Based on System Dynamic

    Directory of Open Access Journals (Sweden)

    Wahyu Adi Tri Joko

    2017-01-01

    Full Text Available Construction accident can be caused by internal and external factors such as worker fatigue and unsafe project environment. Tight schedule of construction project forcing construction worker to work overtime in long period. This situation leads to worker fatigue. This paper proposes a model to predict construction worker fatigue based on system dynamic (SD. System dynamic is used to represent correlation among internal and external factors and to simulate level of worker fatigue. To validate the model, 93 construction workers whom worked in a high rise building construction projects, were used as case study. The result shows that excessive workload, working elevation and age, are the main factors lead to construction worker fatigue. Simulation result also shows that these factors can increase worker fatigue level to 21.2% times compared to normal condition. Beside predicting worker fatigue level this model can also be used as early warning system to prevent construction worker accident

  12. Machine-Learning-Based No Show Prediction in Outpatient Visits

    Directory of Open Access Journals (Sweden)

    Carlos Elvira

    2018-03-01

    Full Text Available A recurring problem in healthcare is the high percentage of patients who miss their appointment, be it a consultation or a hospital test. The present study seeks patient’s behavioural patterns that allow predicting the probability of no- shows. We explore the convenience of using Big Data Machine Learning models to accomplish this task. To begin with, a predictive model based only on variables associated with the target appointment is built. Then the model is improved by considering the patient’s history of appointments. In both cases, the Gradient Boosting algorithm was the predictor of choice. Our numerical results are considered promising given the small amount of information available. However, there seems to be plenty of room to improve the model if we manage to collect additional data for both patients and appointments.

  13. Prediction and Validation of Mars Pathfinder Hypersonic Aerodynamic Data Base

    Science.gov (United States)

    Gnoffo, Peter A.; Braun, Robert D.; Weilmuenster, K. James; Mitcheltree, Robert A.; Engelund, Walter C.; Powell, Richard W.

    1998-01-01

    Postflight analysis of the Mars Pathfinder hypersonic, continuum aerodynamic data base is presented. Measured data include accelerations along the body axis and axis normal directions. Comparisons of preflight simulation and measurements show good agreement. The prediction of two static instabilities associated with movement of the sonic line from the shoulder to the nose and back was confirmed by measured normal accelerations. Reconstruction of atmospheric density during entry has an uncertainty directly proportional to the uncertainty in the predicted axial coefficient. The sensitivity of the moment coefficient to freestream density, kinetic models and center-of-gravity location are examined to provide additional consistency checks of the simulation with flight data. The atmospheric density as derived from axial coefficient and measured axial accelerations falls within the range required for sonic line shift and static stability transition as independently determined from normal accelerations.

  14. The Application Law of Large Numbers That Predicts The Amount of Actual Loss in Insurance of Life

    Science.gov (United States)

    Tinungki, Georgina Maria

    2018-03-01

    The law of large numbers is a statistical concept that calculates the average number of events or risks in a sample or population to predict something. The larger the population is calculated, the more accurate predictions. In the field of insurance, the Law of Large Numbers is used to predict the risk of loss or claims of some participants so that the premium can be calculated appropriately. For example there is an average that of every 100 insurance participants, there is one participant who filed an accident claim, then the premium of 100 participants should be able to provide Sum Assured to at least 1 accident claim. The larger the insurance participant is calculated, the more precise the prediction of the calendar and the calculation of the premium. Life insurance, as a tool for risk spread, can only work if a life insurance company is able to bear the same risk in large numbers. Here apply what is called the law of large number. The law of large numbers states that if the amount of exposure to losses increases, then the predicted loss will be closer to the actual loss. The use of the law of large numbers allows the number of losses to be predicted better.

  15. Predictive factors for body weight loss and its impact on quality of life following gastrectomy.

    Science.gov (United States)

    Tanabe, Kazuaki; Takahashi, Masazumi; Urushihara, Takashi; Nakamura, Yoichi; Yamada, Makoto; Lee, Sang-Woong; Tanaka, Shinnosuke; Miki, Akira; Ikeda, Masami; Nakada, Koji

    2017-07-14

    To determine the predictive factors and impact of body weight loss on postgastrectomy quality of life (QOL). We applied the newly developed integrated questionnaire postgastrectomy syndrome assessment scale-45, which consists of 45 items including those from the Short Form-8 and Gastrointestinal Symptom Rating Scale instruments, in addition to 22 newly selected items. Between July 2009 and December 2010, completed questionnaires were received from 2520 patients with curative resection at 1 year or more after having undergone one of six types of gastrectomy for Stage I gastric cancer at one of 52 participating institutions. Of those, we analyzed 1777 eligible questionnaires from patients who underwent total gastrectomy with Roux-en-Y procedure (TGRY) or distal gastrectomy with Billroth-I (DGBI) or Roux-en-Y (DGRY) procedures. A total of 393, 475 and 909 patients underwent TGRY, DGRY, and DGBI, respectively. The mean age of patients was 62.1 ± 9.2 years. The mean time interval between surgery and retrieval of the questionnaires was 37.0 ± 26.8 mo. On multiple regression analysis, higher preoperative body mass index, total gastrectomy, and female sex, in that order, were independent predictors of greater body weight loss after gastrectomy. There was a significant difference in the degree of weight loss ( P 25 kg/m 2 ). Multiple linear regression analysis identified lower postoperative body mass index, rather than greater body weight loss postoperatively, as a certain factor for worse QOL ( P weight after gastrectomy, the impact of body weight loss on QOL is unexpectedly small.

  16. Quality of life predicts outcome in a heart failure disease management program.

    LENUS (Irish Health Repository)

    O'Loughlin, Christina

    2012-02-01

    BACKGROUND: Chronic heart failure (HF) is associated with a poor Health Related Quality of Life (HRQoL). HRQoL has been shown to be a predictor of HF outcomes however, variability in the study designs make it difficult to apply these findings to a clinical setting. The aim of this study was to establish if HRQoL is a predictor of long-term mortality and morbidity in HF patients followed-up in a disease management program (DMP) and if a HRQoL instrument could be applied to aid in identifying high-risk patients within a clinical context. METHODS: This is a retrospective analysis of HF patients attending a DMP with 18+\\/-9 months follow-up. Clinical and biochemical parameters were recorded on discharge from index HF admission and HRQoL measures were recorded at 2 weeks post index admission. RESULTS: 225 patients were enrolled into the study (mean age=69+\\/-12 years, male=61%, and 78%=systolic HF). In multivariable analysis, all dimensions of HRQoL (measured by the Minnesota Living with HF Questionnaire) were independent predictors of both mortality and readmissions particularly in patients <80 years. A significant interaction between HRQoL and age (Total((HRQoL))age: p<0.001) indicated that the association of HRQoL with outcomes diminished as age increased. CONCLUSIONS: These data demonstrate that HRQoL is a predictor of outcome in HF patients managed in a DMP. Younger patients (<65 years) with a Total HRQoL score of > or =50 are at high risk of an adverse outcome. In older patients > or =80 years HRQoL is not useful in predicting outcome.

  17. Rutting Prediction in Asphalt Pavement Based on Viscoelastic Theory

    Directory of Open Access Journals (Sweden)

    Nahi Mohammed Hadi

    2016-01-01

    Full Text Available Rutting is one of the most disturbing failures on the asphalt roads due to the interrupting it is caused to the drivers. Predicting of asphalt pavement rutting is essential tool leads to better asphalt mixture design. This work describes a method of predicting the behaviour of various asphalt pavement mixes and linking these to an accelerated performance testing. The objective of this study is to develop a finite element model based on viscoplastic theory for simulating the laboratory testing of asphalt mixes in Hamburg Wheel Rut Tester (HWRT for rutting. The creep parameters C1, C2 and C3 are developed from the triaxial repeated load creep test at 50°C and at a frequency of 1 Hz and the modulus of elasticity and Poisson’ s ratio determined at the same temperature. Viscoelastic model (creep model is adopted using a FE simulator (ANSYS in order to calculate the rutting for various mixes under a uniform loading pressure of 500 kPa. An eight-node with a three Degrees of Freedom (UX, UY, and UZ Element is used for the simulation. The creep model developed for HWRT tester was verified by comparing the predicted rut depths with the measured one and by comparing the rut depth with ABAQUS result from literature. Reasonable agreement can be obtained between the predicted rut depths and the measured one. Moreover, it is found that creep model parameter C1 and C3 have a strong relationship with rutting. It was clear that the parameter C1 strongly influences rutting than the parameter C3. Finally, it can be concluded that creep model based on finite element method can be used as an effective tool to analyse rutting of asphalt pavements.

  18. Early Caries Predicts Low Oral Health-Related Quality of Life at a Later Age.

    Science.gov (United States)

    Kragt, Lea; van der Tas, Justin T; Moll, Henriëtte A; Elfrink, Marlies E C; Jaddoe, Vincent W V; Wolvius, Eppo B; Ongkosuwito, Edwin M

    2016-01-01

    Oral health-related quality of life (OHRQOL) is the perceived impact of one's own oral health on daily life. Oral diseases influence children's OHRQOL directly, but OHRQOL might also be related to oral health experiences from the past. We investigate the relation between dental caries at the age of 6 with OHRQOL assessed at the age of 10. This study was conducted within the Generation R Study, a population-based prospective cohort study. Caries experience was assessed with the decayed, missing, and filled teeth index (dmft) at a median age of 6.09 years (90% range: 5.73-6.80). OHRQOL was assessed with a short form of the Child Oral Health Impact Profile at the children's age of 9.79 years (9.49-10.44). In total, 2,833 children participated in this study, of whom 472 (16.6%) had mild caries (dmft 1-3) and 228 (8.0%) had severe caries (dmft >3). The higher the dmft score at the age of 6, the lower the OHRQOL at the age of 10 (p age of 6 had significantly higher odds of being in the lowest OHRQOL quartile at the age of 10 (OR = 1.69; 95% CI: 1.17-2.45). Our study highlights the importance of oral health during childhood, because those who get a compromised start to oral health are much more likely to follow a trajectory which will lead to poor oral health (-related QOL) later. OHRQOL is not only related to current oral health experiences but also to oral health experiences from the past. © 2016 S. Karger AG, Basel.

  19. LÉVY-BASED ERROR PREDICTION IN CIRCULAR SYSTEMATIC SAMPLING

    Directory of Open Access Journals (Sweden)

    Kristjana Ýr Jónsdóttir

    2013-06-01

    Full Text Available In the present paper, Lévy-based error prediction in circular systematic sampling is developed. A model-based statistical setting as in Hobolth and Jensen (2002 is used, but the assumption that the measurement function is Gaussian is relaxed. The measurement function is represented as a periodic stationary stochastic process X obtained by a kernel smoothing of a Lévy basis. The process X may have an arbitrary covariance function. The distribution of the error predictor, based on measurements in n systematic directions is derived. Statistical inference is developed for the model parameters in the case where the covariance function follows the celebrated p-order covariance model.

  20. Prediction and reconstruction of future and missing unobservable modified Weibull lifetime based on generalized order statistics

    Directory of Open Access Journals (Sweden)

    Amany E. Aly

    2016-04-01

    Full Text Available When a system consisting of independent components of the same type, some appropriate actions may be done as soon as a portion of them have failed. It is, therefore, important to be able to predict later failure times from earlier ones. One of the well-known failure distributions commonly used to model component life, is the modified Weibull distribution (MWD. In this paper, two pivotal quantities are proposed to construct prediction intervals for future unobservable lifetimes based on generalized order statistics (gos from MWD. Moreover, a pivotal quantity is developed to reconstruct missing observations at the beginning of experiment. Furthermore, Monte Carlo simulation studies are conducted and numerical computations are carried out to investigate the efficiency of presented results. Finally, two illustrative examples for real data sets are analyzed.