WorldWideScience

Sample records for integrated predictive maintenance

  1. Program integration of predictive maintenance with reliability centered maintenance

    International Nuclear Information System (INIS)

    Strong, D.K. Jr; Wray, D.M.

    1990-01-01

    This paper addresses improving the safety and reliability of power plants in a cost-effective manner by integrating the recently developed reliability centered maintenance techniques with the traditional predictive maintenance techniques of nuclear power plants. The topics of the paper include a description of reliability centered maintenance (RCM), enhancing RCM with predictive maintenance, predictive maintenance programs, condition monitoring techniques, performance test techniques, the mid-Atlantic Reliability Centered Maintenance Users Group, test guides and the benefits of shared guide development

  2. Developing a comprehensive training curriculum for integrated predictive maintenance

    Science.gov (United States)

    Wurzbach, Richard N.

    2002-03-01

    On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of

  3. Integrated maintenance program (IMP)

    International Nuclear Information System (INIS)

    Zemdegs, R.T.; Chout, Q.B.

    1998-01-01

    the station's maintenance effectiveness and reduce maintenance costs including RCM4, callup overhauls, analysis of equipment and system failure history to name a few. It has become apparent that there is no single D o-All m aintenance strategy. What is needed is an integrated program combining the benefits of a variety of problem-specific strategies. Such a program should address both the short term and long term station requirements. The impact of the Integrated Maintenance Program (IMP) is expected to be high. In the short term, IMP will upgrade the call-up management system to provide accurate classification, effective monitoring and reporting, and develop a documented rationale (PMO) for each Preventive Maintenance task. To the greatest extent possible, IMP will utilize on-condition (predictive) maintenance and result in the elimination of replacement of many obsolete or ineffective preventive maintenance call-ups. The IMP described in this paper, will improve maintenance effectiveness, equipment reliability and have cost benefits to Ontario Hydro. In doing so it will reduce the cost of maintenance and improve system availability and reliability. (author)

  4. Predicting older adults' maintenance in exercise participation using an integrated social psychological model

    NARCIS (Netherlands)

    Stiggelbout, M.; Hopman-Rock, M.; Crone, M.; Lechner, L.; Mechelen, W. van

    2006-01-01

    Little is known about the predictors of maintenance in organized exercise programmes. The aim of this study was to investigate the behavioral predictors of maintenance of exercise participation in older adults, using an integrated social psychological model. To this end, we carried out a prospective

  5. Opportune maintenance and predictive maintenance decision support

    OpenAIRE

    Thomas , Edouard; Levrat , Eric; Iung , Benoît; Cocheteux , Pierre

    2009-01-01

    International audience; Conventional maintenance strategies on a single component are being phased out in favour of more predictive maintenance actions. These new kinds of actions are performed in order to control the global performances of the whole industrial system. They are anticipative in nature, which allows a maintenance expert to consider non-already-planned maintenance actions. Two questions naturally emerge: when to perform a predictive maintenance action; how a maintenance expert c...

  6. Crack Growth-Based Predictive Methodology for the Maintenance of the Structural Integrity of Repaired and Nonrepaired Aging Engine Stationary Components

    National Research Council Canada - National Science Library

    Barron, Michael

    1999-01-01

    .... Specifically, the FAA's goal was to develop "Crack Growth-Based Predictive Methodologies for the Maintenance of the Structural Integrity of Repaired and Nonrepaired Aging Engine Stationary Components...

  7. Predictive maintenance primer

    International Nuclear Information System (INIS)

    Flude, J.W.; Nicholas, J.R.

    1991-04-01

    This Predictive Maintenance Primer provides utility plant personnel with a single-source reference to predictive maintenance analysis methods and technologies used successfully by utilities and other industries. It is intended to be a ready reference to personnel considering starting, expanding or improving a predictive maintenance program. This Primer includes a discussion of various analysis methods and how they overlap and interrelate. Additionally, eighteen predictive maintenance technologies are discussed in sufficient detail for the user to evaluate the potential of each technology for specific applications. This document is designed to allow inclusion of additional technologies in the future. To gather the information necessary to create this initial Primer the Nuclear Maintenance Applications Center (NMAC) collected experience data from eighteen utilities plus other industry and government sources. NMAC also contacted equipment manufacturers for information pertaining to equipment utilization, maintenance, and technical specifications. The Primer includes a discussion of six methods used by analysts to study predictive maintenance data. These are: trend analysis; pattern recognition; correlation; test against limits or ranges; relative comparison data; and statistical process analysis. Following the analysis methods discussions are detailed descriptions for eighteen technologies analysts have found useful for predictive maintenance programs at power plants and other industrial facilities. Each technology subchapter has a description of the operating principles involved in the technology, a listing of plant equipment where the technology can be applied, and a general description of the monitoring equipment. Additionally, these descriptions include a discussion of results obtained from actual equipment users and preferred analysis techniques to be used on data obtained from the technology. 5 refs., 30 figs

  8. Integrated predictive maintenance program vibration and lube oil analysis: Part I - history and the vibration program

    Energy Technology Data Exchange (ETDEWEB)

    Maxwell, H.

    1996-12-01

    This paper is the first of two papers which describe the Predictive Maintenance Program for rotating machines at the Palo Verde Nuclear Generating Station. The organization has recently been restructured and significant benefits have been realized by the interaction, or {open_quotes}synergy{close_quotes} between the Vibration Program and the Lube Oil Analysis Program. This paper starts with the oldest part of the program - the Vibration Program and discusses the evolution of the program to its current state. The {open_quotes}Vibration{close_quotes} view of the combined program is then presented.

  9. Integrated predictive maintenance program vibration and lube oil analysis: Part I - history and the vibration program

    International Nuclear Information System (INIS)

    Maxwell, H.

    1996-01-01

    This paper is the first of two papers which describe the Predictive Maintenance Program for rotating machines at the Palo Verde Nuclear Generating Station. The organization has recently been restructured and significant benefits have been realized by the interaction, or open-quotes synergyclose quotes between the Vibration Program and the Lube Oil Analysis Program. This paper starts with the oldest part of the program - the Vibration Program and discusses the evolution of the program to its current state. The open-quotes Vibrationclose quotes view of the combined program is then presented

  10. Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion.

    Science.gov (United States)

    Smith, Rachel A; Kim, Youllee; Zhu, Xun; Doudou, Dimi Théodore; Sternberg, Eleanore D; Thomas, Matthew B

    2018-01-01

    This study documents an investigation into the adoption and diffusion of eave tubes, a novel mosquito vector control, during a large-scale scientific field trial in West Africa. The diffusion of innovations (DOI) and the integrated model of behavior (IMB) were integrated (i.e., innovation attributes with attitudes and social pressures with norms) to predict participants' (N = 329) diffusion intentions. The findings showed that positive attitudes about the innovation's attributes were a consistent positive predictor of diffusion intentions: adopting it, maintaining it, and talking with others about it. As expected by the DOI and the IMB, the social pressure created by a descriptive norm positively predicted intentions to adopt and maintain the innovation. Drawing upon sharing research, we argued that the descriptive norm may dampen future talk about the innovation, because it may no longer be seen as a novel, useful topic to discuss. As predicted, the results showed that as the descriptive norm increased, the intention to talk about the innovation decreased. These results provide broad support for integrating the DOI and the IMB to predict diffusion and for efforts to draw on other research to understand motivations for social diffusion.

  11. Maintenance management for nuclear power plant 'Integrated valve maintenance'

    International Nuclear Information System (INIS)

    Gerner, P.; Zanner, G.

    2001-01-01

    The deregulation of Europe's power market does force many utilities, and especially nuclear power plant operators, to introduce extensive cost-cutting measures in order to be able to compete within this new environment. The optimization of plant outages provides considerable potential for raising plant availability but can also lower operating costs by reducing e.g. expenditure on maintenance. Siemens Nuclear Power GmbH, in cooperation with plant operators, is currently implementing new and improved service concepts which can have a major effect on the way in which maintenance will be performed in the future. Innovative service packages for maintenance in nuclear power plants are available which can be used to perform a time- and cost-effective maintenance. The concepts encompass optimization of the overall sequence from planning in advance to the individual measures including reduction of the scope of maintenance activities, identification of cost cutting potential and bundling of maintenance activities. The main features of these maintenance activities are illustrated here using the examples of outage planning and integrated valve maintenance. In nuclear power plants approx. 5000 valves are periodically preventively, condition-based or breakdown-based maintained. Because of this large number of valves to be maintained a high potential of improvements and cost reductions can be achieved by performing an optimized, cost-effective maintenance based on innovative methods and tools. Siemens Nuclear Power GmbH has developed and qualified such tools which allow to reduce service costs while maintaining high standards of safety and availability. By changing from preventive to predictive (condition-based) maintenance - the number of valves to be maintained may be reduced considerably. The predictive maintenance is based on the Siemens Nuclear Power GmbH diagnostic and evaluation method (ADAM). ADAM is used to monitor the operability of valves by analytical verification of

  12. Integration of infrared thermography into various maintenance methodologies

    Science.gov (United States)

    Morgan, William T.

    1993-04-01

    Maintenance methodologies are in developmental stages throughout the world as global competitiveness drives all industries to improve operational efficiencies. Rapid progress in technical advancements has added an additional strain on maintenance organizations to progressively change. Accompanying needs for advanced training and documentation is the demand for utilization of various analytical instruments and quantitative methods. Infrared thermography is one of the primary elements of engineered approaches to maintenance. Current maintenance methodologies can be divided into six categories; Routine ('Breakdown'), Preventive, Predictive, Proactive, Reliability-Based, and Total Productive (TPM) maintenance. Each of these methodologies have distinctive approaches to achieving improved operational efficiencies. Popular though is that infrared thermography is a Predictive maintenance tool. While this is true, it is also true that it can be effectively integrated into each of the maintenance methodologies for achieving desired results. The six maintenance strategies will be defined. Infrared applications integrated into each will be composed in tabular form.

  13. Selecting Suitable Candidates for Predictive Maintenance

    NARCIS (Netherlands)

    Tiddens, Wieger Willem; Braaksma, Anne Johannes Jan; Tinga, Tiedo

    2018-01-01

    Predictive maintenance (PdM) or Prognostics and Health Management (PHM) assists in better predicting the future state of physical assets and making timely and better-informed maintenance decisions. Many companies nowadays ambition the implementation of such an advanced maintenance policy. However,

  14. Improving the TRIGA facility maintenance by predictive maintenance techniques

    International Nuclear Information System (INIS)

    Preda, M.; Sabau, C.; Barbalata, E.

    1997-01-01

    This work deals with the specific operation of equipment in radioactive environment or in conditions allowing radioactive contamination. The requirements of remote operation ensuring the operators' protection are presented. Also, the requirements of international standards issued by IAEA-Vienna are reviewed. The organizational withdraws of the maintenance activities, based on the standards and maintenance and repair directives still in force, are shown. It is emphasized the fact that this type of maintenance was adequate to a given level of technical development, characteristic for pre-computerized industry, but, at present, it is obsolete and uneconomic both in utilization and maintenance. Such a system constitutes already a burden hindering the efforts of maximizing the availability, maintenance, prolongation the service life of equipment and utilities, finally, of increasing the efficiency of complex installations. Moreover, the predictive maintenance techniques are strongly requested by the character of radioactive installations precluding the direct access in given zones (a potential risk of irradiation or radioactive contamination) of installations during operation. The results obtained by applying the predictive maintenance techniques in the operation of the double circuit irradiation loop, used in the TRIGA reactors, are presented

  15. Electric motor predictive and preventive maintenance guide

    International Nuclear Information System (INIS)

    Oliver, J.A.

    1992-07-01

    Electric motor performance is vital to the reliable and efficient operation of power plants. The failure of one or more critical motors could cause lost capacity and excessive repair and maintenance cost. However, existing maintenance recommendations proposed by vendors for electric motors have sometimes encouraged many overly conservative maintenance practices. These practices have lead to excessive maintenance activities and costs which have provided no extra margin of operability. EPRI has sponsored RP2814-35 to develop a guide which provides power plants with information and guidance for establishing an effective maintenance program which will aid in preventing unexpected motor failures and assist in planning motor maintenance efforts. The guide includes a technical description which summarizes technical data relative to the four basic types of motors and their components in general use in power plants. The significant causes of motor failures are investigated and described in detail and methods to optimize service life and minimize maintenance cost through appropriate preventive maintenance and conditioning program are presented. This guide provides a foundation for an effective electric motor maintenance program and simplifies the selection of predictive and preventive maintenance tasks. Its use will enable maintenance personnel in nuclear and fossil plants to plan motor repairs during scheduled outages and avoid costly unexpected failures

  16. MOV predictive maintenance program at Darlington NGS

    International Nuclear Information System (INIS)

    Morrison, J.F.

    1992-01-01

    This paper details the Motor Operated Valve (MOV) Predictive Maintenance program at Darlington Nuclear Generating Station. The program encompasses the use of diagnostics tooling in conjunction with more standard maintenance techniques, with the goal of improving performance of MOV's. Problems encountered and solutions developed during the first two phases of this program are presented, along with proposed actions for the final trending phase of the program. This paper also touches on the preventive and corrective maintenance aspects of an overall MOV maintenance program. 6 refs., 6 tabs., 6 figs

  17. A VITAL service for predictive MOV maintenance

    International Nuclear Information System (INIS)

    Anon.

    1990-01-01

    Motor-operated valve (MOV) maintenance can be a major contributor to unplanned plant downtime, either because valve malfunctions cause unscheduled outages, or because unnecessary valve maintenance lengthens scheduled outages. The cause of both situations is a preventive approach to valve maintenance, where maintenance is scheduled according to a timetable instead of according to a demonstrated need. To move towards a predictive maintenance approach, inexpensive methods of collecting and diagnosing real-time data on the conditions of a valve must be made available. Such a system must be capable of detecting and diagnosing degrading mechanical and electrical behaviour at an early stage, as well as being able to predict the time of failure. Without this data, a predictive approach to maintenance is impossible. Westinghouse is addressing the requirements for a predictive approach to MOV maintenance with the introduction of a third-generation of diagnostic systems for motor-operated valves -the portable Valve Intelligent Test and Analysis System (VITALS) and the on-line Valve Monitoring System (VMS). (author)

  18. Integrated reliability condition monitoring and maintenance of equipment

    CERN Document Server

    Osarenren, John

    2015-01-01

    Consider a Viable and Cost-Effective Platform for the Industries of the Future (IOF) Benefit from improved safety, performance, and product deliveries to your customers. Achieve a higher rate of equipment availability, performance, product quality, and reliability. Integrated Reliability: Condition Monitoring and Maintenance of Equipment incorporates reliable engineering and mathematical modeling to help you move toward sustainable development in reliability condition monitoring and maintenance. This text introduces a cost-effective integrated reliability growth monitor, integrated reliability degradation monitor, technological inheritance coefficient sensors, and a maintenance tool that supplies real-time information for predicting and preventing potential failures of manufacturing processes and equipment. The author highlights five key elements that are essential to any improvement program: improving overall equipment and part effectiveness, quality, and reliability; improving process performance with maint...

  19. Integrated maintenance planning in manufacturing systems

    CERN Document Server

    Al-Turki, Umar M; Yilbas, Bekir Sami; Sahin, Ahmet Ziyaettin

    2014-01-01

    This book introduces the concept of integrated planning for maintenance and production taken into account quality and safety for high global socio-economic impact. It provides insight into the planning process at a global level starting from the business level and ending with the operational level where the plan is implemented and controlled.

  20. Mechatronics technology in predictive maintenance method

    Science.gov (United States)

    Majid, Nurul Afiqah A.; Muthalif, Asan G. A.

    2017-11-01

    This paper presents recent mechatronics technology that can help to implement predictive maintenance by combining intelligent and predictive maintenance instrument. Vibration Fault Simulation System (VFSS) is an example of mechatronics system. The focus of this study is the prediction on the use of critical machines to detect vibration. Vibration measurement is often used as the key indicator of the state of the machine. This paper shows the choice of the appropriate strategy in the vibration of diagnostic process of the mechanical system, especially rotating machines, in recognition of the failure during the working process. In this paper, the vibration signature analysis is implemented to detect faults in rotary machining that includes imbalance, mechanical looseness, bent shaft, misalignment, missing blade bearing fault, balancing mass and critical speed. In order to perform vibration signature analysis for rotating machinery faults, studies have been made on how mechatronics technology is used as predictive maintenance methods. Vibration Faults Simulation Rig (VFSR) is designed to simulate and understand faults signatures. These techniques are based on the processing of vibrational data in frequency-domain. The LabVIEW-based spectrum analyzer software is developed to acquire and extract frequency contents of faults signals. This system is successfully tested based on the unique vibration fault signatures that always occur in a rotating machinery.

  1. A predictive maintenance approach for improved nuclear plant availability

    International Nuclear Information System (INIS)

    Verma, R.M.P.; Pandya, M.B.; Kini, M.P.

    1979-01-01

    Predictive maintenance programme as against preventive maintenance programme aims at diagnosing, inspecting, monitoring, and objective condition-checking of equipment. It helps in forecasting failures, and scheduling the optimal frequencies for overhauls, replacements, lubrication etc. It also helps in establishing work load, manpower, resource planning and inventory control. Various stages of predictive maintenance programme for a nuclear power plant are outlined. A partial list of instruments for predictive maintenance is given. (M.G.B.)

  2. Predicting maintenance of attendance at walking groups: testing constructs from three leading maintenance theories.

    Science.gov (United States)

    Kassavou, Aikaterini; Turner, Andrew; Hamborg, Thomas; French, David P

    2014-07-01

    Little is known about the processes and factors that account for maintenance, with several theories existing that have not been subject to many empirical tests. The aim of this study was to test how well theoretical constructs derived from the Health Action Process Approach, Rothman's theory of maintenance, and Verplanken's approach to habitual behavior predicted maintenance of attendance at walking groups. 114 participants, who had already attended walking groups in the community for at least 3 months, completed a questionnaire assessing theoretical constructs regarding maintenance. An objective assessment of attendance over the subsequent 3 months was gained. Multilevel modeling was used to predict maintenance, controlling for clustering within walking groups. Recovery self-efficacy predicted maintenance, even after accounting for clustering. Satisfaction with social outcomes, satisfaction with health outcomes, and overall satisfaction predicted maintenance, but only satisfaction with health outcomes significantly predicted maintenance after accounting for clustering. Self-reported habitual behavior did not predict maintenance despite mean previous attendance being 20.7 months. Recovery self-efficacy, and satisfaction with health outcomes of walking group attendance appeared to be important for objectively measured maintenance, whereas self-reported habit appeared not to be important for maintenance at walking groups. The findings suggest that there is a need for intervention studies to boost recovery self-efficacy and satisfaction with outcomes of walking group attendance, to assess impact on maintenance.

  3. Rotating Machinery Predictive Maintenance Through Expert System

    Directory of Open Access Journals (Sweden)

    M. Sarath Kumar

    2000-01-01

    Full Text Available Modern rotating machines such as turbomachines, either produce or absorb huge amount of power. Some of the common applications are: steam turbine-generator and gas turbine-compressor-generator trains produce power and machines, such as pumps, centrifugal compressors, motors, generators, machine tool spindles, etc., are being used in industrial applications. Condition-based maintenance of rotating machinery is a common practice where the machine's condition is monitored constantly, so that timely maintenance can be done. Since modern machines are complex and the amount of data to be interpreted is huge, we need precise and fast methods in order to arrive at the best recommendations to prevent catastrophic failure and to prolong the life of the equipment. In the present work using vibration characteristics of a rotor-bearing system, the condition of a rotating machinery (electrical rotor is predicted using an off-line expert system. The analysis of the problem is carried out in an Object Oriented Programming (OOP framework using the finite element method. The expert system which is also developed in an OOP paradigm gives the type of the malfunctions, suggestions and recommendations. The system is implemented in C++.

  4. Integrated Logistics Support Analysis of the International Space Station Alpha: An Overview of the Maintenance Time Dependent Parameter Prediction Methods Enhancement

    Science.gov (United States)

    Sepehry-Fard, F.; Coulthard, Maurice H.

    1995-01-01

    The objective of this publication is to introduce the enhancement methods for the overall reliability and maintainability methods of assessment on the International Space Station. It is essential that the process to predict the values of the maintenance time dependent variable parameters such as mean time between failure (MTBF) over time do not in themselves generate uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. Furthermore, the very acute problems of micrometeorite, Cosmic rays, flares, atomic oxygen, ionization effects, orbital plumes and all the other factors that differentiate maintainable space operations from non-maintainable space operations and/or ground operations must be accounted for. Therefore, these parameters need be subjected to a special and complex process. Since reliability and maintainability strongly depend on the operating conditions that are encountered during the entire life of the International Space Station, it is important that such conditions are accurately identified at the beginning of the logistics support requirements process. Environmental conditions which exert a strong influence on International Space Station will be discussed in this report. Concurrent (combined) space environments may be more detrimental to the reliability and maintainability of the International Space Station than the effects of a single environment. In characterizing the logistics support requirements process, the developed design/test criteria must consider both the single and/or combined environments in anticipation of providing hardware capability to withstand the hazards of the International Space Station profile. The effects of the combined environments (typical) in a matrix relationship on the International Space Station will be shown. The combinations of the environments where the total effect is more damaging than the cumulative effects of the environments acting singly, may include a

  5. Simulation based comparison of predictive maintenance policies

    NARCIS (Netherlands)

    Tinga, Tiedo; Janssen, R.H.P.; Steenbergen, R.; van Gelder, P.

    2013-01-01

    When an asset is operated in variable conditions, its operational efficiency can be improved significantly when the maintenance is performed in a dynamic manner. This means that variations in usage and operating environment are taken into account when deciding on the length of the maintenance

  6. Demonstration of Sensor Data Integration Across Naval Aviation Maintenance

    Science.gov (United States)

    2018-02-01

    Concepts, Programs and Processes; Maintenance Unit Department, Division Organization; Manpower Management ; and Aviation Officers.” http...Naval Aviation Maintenance Alejandra Jolodosky and Adi Zolotov February 2018 This work was performed under Federal Government Contract...underutilized sensor data. CNA proposed a pilot program that integrated sensor data across maintenance levels to expedite repairs of aviation parts

  7. Establishing a predictive maintenance program at the Hanford Site

    International Nuclear Information System (INIS)

    Winslow, R.W.

    1994-05-01

    This document contains information about a new Predictive Maintenance Program being developed and implemented at the Hanford Reservation. Details of the document include: background on persons developing the program, history of predictive maintenance, implementation of new program, engineering task analysis, network development and new software, issues to be resolved, benefits expected, and appendix gives information about the symposium from which this paper is based

  8. Predictive Maintenance and Robotic System Design

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Business objectives include: reduce equipment maintenance time, reduce ... Data Acquisition: Proprietary machine diagnostic systems and sensors .... and Logistics, Volume #IPart# http://www.ifac-papersonline.net,. Identifier ...

  9. Wireless sensors for predictive maintenance of rotating equipment in research reactors

    International Nuclear Information System (INIS)

    Hashemian, H.M.

    2011-01-01

    In 2008-2009, the High Flux Isotope Reactor (HFIR) at the Oak Ridge National Laboratory (ORNL) tested the potential of predictive or condition-based maintenance techniques to reduce maintenance costs, minimize the risk of catastrophic failures, and maximize system availability by attaching wireless-based sensors to selected rotating equipment at HFIR. Rotating equipment is an ideal 'test case' for the viability of integrated, online predictive maintenance strategies because motors, bearings, and shafts are ubiquitous in nuclear power plants and because the maintenance methods typically performed on rotating equipment today (such as portable or handheld vibration data collection equipment) are highly labor-intensive. The HFIR project achieved all five of its objectives: (1) to identify rotating machinery of the types used in research reactors and determine their operational characteristics, degradation mechanisms, and failure modes, (2) to establish a predictive maintenance program for rotating equipment in research reactors, (3) to identify wireless sensors that are suitable for predictive maintenance of rotating machinery and test them in a laboratory setting, (4) to establish the requirements and procedures to be followed when implementing wireless sensors for predictive maintenance in research reactors, and (5) to develop a conceptual design for a predictive maintenance system for research reactors based on wireless sensors. The project demonstrated that wireless sensors offer an effective method for monitoring key process conditions continuously and remotely, thereby enhancing the safety, reliability, and efficiency of the aging research reactor fleet.

  10. Multi-objective group scheduling optimization integrated with preventive maintenance

    Science.gov (United States)

    Liao, Wenzhu; Zhang, Xiufang; Jiang, Min

    2017-11-01

    This article proposes a single-machine-based integration model to meet the requirements of production scheduling and preventive maintenance in group production. To describe the production for identical/similar and different jobs, this integrated model considers the learning and forgetting effects. Based on machine degradation, the deterioration effect is also considered. Moreover, perfect maintenance and minimal repair are adopted in this integrated model. The multi-objective of minimizing total completion time and maintenance cost is taken to meet the dual requirements of delivery date and cost. Finally, a genetic algorithm is developed to solve this optimization model, and the computation results demonstrate that this integrated model is effective and reliable.

  11. Electrical predictive maintenance at Trillo I Nuclear Power Plant

    International Nuclear Information System (INIS)

    Vicente, L. R.; Fernandez de la Mata, R.; Cano Gonzalez, J. C.

    1998-01-01

    An electrical predictive maintenance plan is currently being put into effect at Trillo I Nuclear Power Plant which is initially being applied to three types of equipment: motors, transformers and motor-driven valves. This paper describes the different phases considered in the implementation of the Predictive Maintenance Plan: study of existing techniques for such equipment (tangoδ, spectral analysis of stator current, chromatographic analysis of gases, spectral analysis of the axial stray magnetic flux, etc), study of the special characteristics of the electrical equipment at Trillo NPP, analysis of applicable techniques (characteristic parameters, alert-alarm values, experience with such techniques, etc), analysis of machine history records, study of the optimum preventive-predictive case, study of applicable frequencies and definition of the computerised predictive maintenance management tool. With the exception of the computerised predictive maintenance management applications which are presently being implemented, all the activities described above have been carried out on the three types of equipment mentioned. (Author)

  12. Predictive maintenance: A new approach in maintenance of nuclear power plants

    International Nuclear Information System (INIS)

    Benvenuto, F.; Ferrari, L.

    2005-01-01

    The maintenance services for a Nuclear Power Plant are in general aimed at reaching the following goals: - Increase component availability and consequently decrease intervention frequency; - Reduce unexpected costs from unexpected repairs; - Progressively decrease the time of each intervention; - Improve the spare parts supply efficiency; - Improve spare parts and consumable warehouse managing; - Decrease maintenance costs. Most of the currently used maintenance activities refer to run-to-failure or preventive approaches: - Run-to-failure or Corrective Maintenance means that work is only carried out when a component or system is faulty and unable to perform its critical function. Non critical components such as filters or components with spare may be maintained in this way; - Preventive or Scheduled Maintenance involves a regular pre-set schedule programme of maintenance work. Programme outlined by the manufacturer of the component in question based on the design life of the component and based on past experience by operation. One step further than Preventive Maintenance is represented by Predictive Maintenance. Whereas Preventive Maintenance bases its schedules on past performance data, a predictive system acquires condition data from the machine to be maintained whilst the machine is in operation. The information obtained from this analysis indicates the condition in real time, provides a diagnosis of wear and shows any trend towards critical conditions. Predictive maintenance mainly consists of the following interventions: - Lubricant analysis; - Collection / analysis of functional parameters, such as motor absorption, flow rate, pressure, temperature, noise, vibration of rotating equipment, thermal efficiency, etc; - Periodical test of lifting systems; - Other operations to acquire sensitive equipment parameters. Predictive Maintenance can reduce the accidental intervention and extend the components life, and, in the end, is increasing the global availability

  13. Integrated sign management system : ADOT maintenance group

    Science.gov (United States)

    2003-12-01

    The Arizona Department of Transportation (ADOT) maintains and manages an inventory of roadway signs. Before the implementation of this project, sign technicians maintained inventory records on individual laptops to track their daily sign maintenance ...

  14. Predictive maintenance of maritime systems : models and challenges

    NARCIS (Netherlands)

    Tinga, T.; Tiddens, W.W.; Amoiralis, F.; Politis, M.; Cepin, Marko; Bris, Radim

    2017-01-01

    To reduce maintenance and logistic costs and increase the asset availability, a predictive maintenance concept for maritime systems is developed. In the present paper, the physics-of-failure based prognostic methods will be introduced, but also other issues related to the development and application

  15. Predictive Maintenance (PdM) Centralization for Significant Energy Savings

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Dale

    2010-09-15

    Cost effective predictive maintenance (PdM) technologies and basic energy calculations can mine energy savings form processes or maintenance activities. Centralizing and packaging this information correctly empowers facility maintenance and reliability professionals to build financial justification and support for strategies and personnel to weather global economic downturns and competition. Attendees will learn how to: Systematically build a 'pilot project' for applying PdM and tracking systems; Break down a typical electrical bill to calculate energy savings; Use return on investment (ROI) calculations to identify the best and highest value options, strategies and tips for substantiating your energy reduction maintenance strategies.

  16. Risk-Based Predictive Maintenance for Safety-Critical Systems by Using Probabilistic Inference

    Directory of Open Access Journals (Sweden)

    Tianhua Xu

    2013-01-01

    Full Text Available Risk-based maintenance (RBM aims to improve maintenance planning and decision making by reducing the probability and consequences of failure of equipment. A new predictive maintenance strategy that integrates dynamic evolution model and risk assessment is proposed which can be used to calculate the optimal maintenance time with minimal cost and safety constraints. The dynamic evolution model provides qualified risks by using probabilistic inference with bucket elimination and gives the prospective degradation trend of a complex system. Based on the degradation trend, an optimal maintenance time can be determined by minimizing the expected maintenance cost per time unit. The effectiveness of the proposed method is validated and demonstrated by a collision accident of high-speed trains with obstacles in the presence of safety and cost constrains.

  17. Automated System Checkout to Support Predictive Maintenance for the Reusable Launch Vehicle

    Science.gov (United States)

    Patterson-Hine, Ann; Deb, Somnath; Kulkarni, Deepak; Wang, Yao; Lau, Sonie (Technical Monitor)

    1998-01-01

    The Propulsion Checkout and Control System (PCCS) is a predictive maintenance software system. The real-time checkout procedures and diagnostics are designed to detect components that need maintenance based on their condition, rather than using more conventional approaches such as scheduled or reliability centered maintenance. Predictive maintenance can reduce turn-around time and cost and increase safety as compared to conventional maintenance approaches. Real-time sensor validation, limit checking, statistical anomaly detection, and failure prediction based on simulation models are employed. Multi-signal models, useful for testability analysis during system design, are used during the operational phase to detect and isolate degraded or failed components. The TEAMS-RT real-time diagnostic engine was developed to utilize the multi-signal models by Qualtech Systems, Inc. Capability of predicting the maintenance condition was successfully demonstrated with a variety of data, from simulation to actual operation on the Integrated Propulsion Technology Demonstrator (IPTD) at Marshall Space Flight Center (MSFC). Playback of IPTD valve actuations for feature recognition updates identified an otherwise undetectable Main Propulsion System 12 inch prevalve degradation. The algorithms were loaded into the Propulsion Checkout and Control System for further development and are the first known application of predictive Integrated Vehicle Health Management to an operational cryogenic testbed. The software performed successfully in real-time, meeting the required performance goal of 1 second cycle time.

  18. Understanding and Predicting the Process of Software Maintenance Releases

    Science.gov (United States)

    Basili, Victor; Briand, Lionel; Condon, Steven; Kim, Yong-Mi; Melo, Walcelio L.; Valett, Jon D.

    1996-01-01

    One of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. The objective of this paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. This study was conducted in the Flight Dynamics Division (FDD) of NASA Goddard Space Flight Center(GSFC). This paper presents three main results: 1) a predictive effort model developed for the FDD's software maintenance release process; 2) measurement-based lessons learned about the maintenance process in the FDD; and 3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. In addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.

  19. Complete guide to preventive and predictive maintenance

    CERN Document Server

    Levitt, Joel

    2011-01-01

    This book shares the best practices, mistakes, victories, and essential steps for success which the author has gleaned from working with countless organizations. Unlike other books that only focus on the engineering issues (task lists) or management issues (CMMS), this in-depth resource is the first to give true emphasize to the four aspects of success in preventive maintenance systems - engineering, management, economic, and psychological - thereby enabling readers to have a balanced view and understanding of what is happening in their organizations. Additionally, it blends concrete actionable steps and structures with the theory behind the steps. It includes check sheets, history of PM, stories, photographs, and case histories. It contains a glossary of terms. It provides sample task lists for a variety of equipment with some of the logic behind each task. It offers templates for developing your own tasking. It includes protocols for detailed economic analysis with examples.

  20. Predictive Attitude Maintenance For A Space Station

    Science.gov (United States)

    Hattis, Philip D.

    1989-01-01

    Paper provides mathematical basis for predictive management of angular momenta of control-moment gyroscopes (CMG's) to control attitude of orbiting space station. Numerical results presented for pitch control of proposed power-tower space station. Based on prior orbit history and mathematical model of density of atmosphere, predictions made of requirements on dumping and storage of angular momentum in relation to current loading state of CMG's and to acceptable attitude tolerances.

  1. Information-Based Maintenance Optimization with Focus on Predictive Maintenance (Informatiegebaseerde onderhoudsoptimalisatie met focus op predictief onderhoud)

    OpenAIRE

    Van Horenbeek, Adriaan

    2013-01-01

    This dissertation presents an information-based maintenance optimization methodology for physical assets; with focus on, but not limited to, predictive maintenance (PdM). The overall concept of information-based maintenance is that of updating maintenance decisions based on evolving knowledge of operation history and anticipated usage of the machinery, as well as the physics and dynamics of material degradation in critical machinery components. Within this concept, predictive maintenance is a...

  2. Multi-level predictive maintenance for multi-component systems

    International Nuclear Information System (INIS)

    Nguyen, Kim-Anh; Do, Phuc; Grall, Antoine

    2015-01-01

    In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenance actions are needed regarding the predictive reliability of the system. At component level the decision rules aim at identifying optimally a group of several components to be preventively maintained when preventive maintenance is trigged due to the system level decision. Selecting optimal components is based on a cost-based group improvement factor taking into account the predictive reliability of the components, the economic dependencies as well as the location of the components in the system. Moreover, a cost model is developed to find the optimal maintenance decision variables. A 14-component system is finally introduced to illustrate the use and the performance of the proposed predictive maintenance policy. Different sensitivity analysis are also investigated and discussed. Indeed, the proposed policy provides more flexibility in maintenance decision-making for complex structure systems, hence leading to significant profits in terms of maintenance cost when compared with existing policies. - Highlights: • A predictive maintenance policy for complex structure systems is proposed. • Multi-level decision process based on prognostic results is proposed. • A cost-based group importance measure is introduced for decision-making. • Both positive and negative dependencies between components are investigated. • A cost model and Monte Carlo simulation are developed for optimization process.

  3. Integrated maintenance management model in the printing industry

    Directory of Open Access Journals (Sweden)

    Csaba Horváth

    2010-09-01

    Full Text Available Rapid technological and economic changes are setting radically new task for maintenance divisions of printingworks. In this dissertation the author provides a summary on the possible approaches for the adoption to the newrequirements. He formulates his situation analysis based on an exhaustive questionnaire survey, and points out thecurrents of changes and challenges caused by the expected developments in the maintenance field of the printingindustry.Based on the possible answers on these challenges, the Author has compiled a - yet missing - maintenance managementmodel that encompasses the maintenance specialties of the industry, as well as the professional heritage andthe latest scientific accomplishments in the discipline of maintenance.The model is based on the widely accepted quality focused maintenance approach, that is supplemented by theAuthor with four new aspects - 1 reliability-focused culture, 2 quality management system, 3 employment ofexternal service provides, 4 maintenance characteristics specific to printing machinery - determining their effectsand integrating them into one single system.In order to construct the model, the Author develops specific solutions that can be seen as own scientific achievementson the specification of maintenance characteristics of printing machinery; on the efficiency improving applicationsof quality management systems, modern knowledge management and reliability focused corporate culture;and on the implementation of a maintenance information system.

  4. Predictive maintenance of critical equipment in industrial processes

    Science.gov (United States)

    Hashemian, Hashem M.

    This dissertation is an account of present and past research and development (R&D) efforts conducted by the author to develop and implement new technology for predictive maintenance and equipment condition monitoring in industrial processes. In particular, this dissertation presents the design of an integrated condition-monitoring system that incorporates the results of three current R&D projects with a combined funding of $2.8 million awarded to the author by the U.S. Department of Energy (DOE). This system will improve the state of the art in equipment condition monitoring and has applications in numerous industries including chemical and petrochemical plants, aviation and aerospace, electric power production and distribution, and a variety of manufacturing processes. The work that is presented in this dissertation is unique in that it introduces a new class of condition-monitoring methods that depend predominantly on the normal output of existing process sensors. It also describes current R&D efforts to develop data acquisition systems and data analysis algorithms and software packages that use the output of these sensors to determine the condition and health of industrial processes and their equipment. For example, the output of a pressure sensor in an operating plant can be used not only to indicate the pressure, but also to verify the calibration and response time of the sensor itself and identify anomalies in the process such as blockages, voids, and leaks that can interfere with accurate measurement of process parameters or disturb the plant's operation, safety, or reliability. Today, process data are typically collected at a rate of one sample per second (1 Hz) or slower. If this sampling rate is increased to 100 samples per second or higher, much more information can be extracted from the normal output of a process sensor and then used for condition monitoring, equipment performance measurements, and predictive maintenance. A fast analog-to-digital (A

  5. Developing Predictive Maintenance Expertise to Improve Plant Equipment Reliability

    International Nuclear Information System (INIS)

    Wurzbach, Richard N.

    2002-01-01

    On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of

  6. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time......). Five technical and economic aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality...

  7. Knowledge representation for integrated plant operation and maintenance

    DEFF Research Database (Denmark)

    Lind, Morten

    2010-01-01

    Integrated operation and maintenance of process plants has many advantages. One advantage is the improved economy obtained by reducing the number of plant shutdowns. Another is to increase reliability of operation by monitoring of risk levels during on-line maintenance. Integrated plant operation...... and maintenance require knowledge bases which can capture the interactions between the two plant activities. As an example, taking out a component or a subsystem for maintenance during operation will require a knowledge base representing the interactions between plant structure, functions, operating states...... and goals and incorporate knowledge about redundancy and reliability data. Multilevel Flow Modeling can be used build knowledge bases representing plant goals and functions and has been applied for fault diagnosis and supervisory control but currently it does not take into account structural information...

  8. Integrated preventive maintenance and production decisions for imperfect processes

    International Nuclear Information System (INIS)

    Nourelfath, Mustapha; Nahas, Nabil; Ben-Daya, Mohamed

    2016-01-01

    This paper integrates production, maintenance, and quality for an imperfect process in a multi-period multi-product capacitated lot-sizing context. The production system is modeled as an imperfect machine, whose the status is considered to be either in-control or out-of-control. When the machine is out of control, it produces a fraction of nonconforming items. During each period, this machine is inspected and imperfect preventive maintenance activities are simultaneously performed to reduce its age, proportional to the preventive maintenance level. The objective is to minimize the total cost, while satisfying the demand for all products. Our optimization model allows for a joint selection of the optimal values of production plan, and the maintenance policy, while taking into account quality related costs. A solution algorithm is developed and illustrative numerical examples are presented. It is found that the increase in PM level leads to reductions in quality control costs. Furthermore, if the cost of performing PM is high to the point where it is not compensated for by reductions in the quality related costs, then performing PM is not justifiable. Finally, using non-periodic preventive maintenance with the possibility of different preventive maintenance levels may result in an improvement of the total cost. - Highlights: • We integrate production, maintenance, and quality. • We evaluate all the expected costs. • Our model allows for a joint selection of the optimal values. • A solution algorithm is developed. • Increasing PM level will decrease quality control costs.

  9. Dr. Mainte. Integrated simulator of maintenance optimization of LWRs

    International Nuclear Information System (INIS)

    Isobe, Yoshihiro; Sagisaka, Mitsuyuki; Etoh, Junji; Matsunaga, Takashi; Kosaka, Toru; Matsumoto, Satoshi; Yoshimura, Shinobu

    2014-01-01

    Dr. Mainte, an integrated simulator for maintenance optimization of LWRs (Light Water Reactors) has been developed based on PFM (Probabilistic Fracture Mechanics) analyses. The concept of the simulator is to provide a decision-making system to optimize maintenance activities for representative components and piping systems in nuclear power plants totally and quantitatively in terms of safety, availability and economic efficiency, environmental impact and social acceptance. For the further improvement of the safety and availability, the effect of human error and its reduction on the optimization of plant maintenance activities and approaches of reducing it have been studied. (author)

  10. Adaptation and Implementation of Predictive Maintenance Technique with Nondestructive Testing for Power Plants

    International Nuclear Information System (INIS)

    Jung, Gye Jo; Jung, Nam Gun

    2010-01-01

    Many forces are pressuring utilities to reduce operating and maintenance costs without cutting back on reliability or availability. Many utility managers are re-evaluating maintenance strategies to meet these demands. To utilities how to reduce maintenance costs and extent the effective operating life of equipment, predictive maintenance technique can be adapted. Predictive maintenance had three types program which are in-house program, engineering company program and mixed program. We can approach successful predictive maintenance program with 'smart trust' concept

  11. Two Different Maintenance Strategies in the Hospital Environment: Preventive Maintenance for Older Technology Devices and Predictive Maintenance for Newer High-Tech Devices.

    Science.gov (United States)

    Sezdi, Mana

    2016-01-01

    A maintenance program generated through the consideration of characteristics and failures of medical equipment is an important component of technology management. However, older technology devices and newer high-tech devices cannot be efficiently managed using the same strategies because of their different characteristics. This study aimed to generate a maintenance program comprising two different strategies to increase the efficiency of device management: preventive maintenance for older technology devices and predictive maintenance for newer high-tech devices. For preventive maintenance development, 589 older technology devices were subjected to performance verification and safety testing (PVST). For predictive maintenance development, the manufacturers' recommendations were used for 134 high-tech devices. These strategies were evaluated in terms of device reliability. This study recommends the use of two different maintenance strategies for old and new devices at hospitals in developing countries. Thus, older technology devices that applied only corrective maintenance will be included in maintenance like high-tech devices.

  12. Luminous flux and colour maintenance investigation of integrated LED lamps

    DEFF Research Database (Denmark)

    Corell, Dennis Dan; Thorseth, Anders; Dam-Hansen, Carsten

    2014-01-01

    This article will present an investigation of the luminous flux and colour maintenance of white LED based retrofit lamps. The study includes 23 different types of integrated LED lamps, covering 18 directional and 5 non-directional. Luminous flux and colour data for operation up to 20000 h has been...

  13. Experiences with an integrated management system for aircraft maintenance

    International Nuclear Information System (INIS)

    Huber, U.

    1993-01-01

    For 20 years, SWISSAIR has employed an integrated information system for aircraft maintenance. To date, a wide range of functions has been set up in their own development. For the future SWISSAIR is increasingly basing on the use of SAP/standard software packages. 10 figs

  14. Maintenance personnel performance simulation (MAPPS): a model for predicting maintenance performance reliability in nuclear power plants

    International Nuclear Information System (INIS)

    Knee, H.E.; Krois, P.A.; Haas, P.M.; Siegel, A.I.; Ryan, T.G.

    1983-01-01

    The NRC has developed a structured, quantitative, predictive methodology in the form of a computerized simulation model for assessing maintainer task performance. Objective of the overall program is to develop, validate, and disseminate a practical, useful, and acceptable methodology for the quantitative assessment of NPP maintenance personnel reliability. The program was organized into four phases: (1) scoping study, (2) model development, (3) model evaluation, and (4) model dissemination. The program is currently nearing completion of Phase 2 - Model Development

  15. Predictive Maintenance: One key to improved power plant availability

    International Nuclear Information System (INIS)

    Mobley; Allen, J.W.

    1986-01-01

    Recent developments in microprocessor technology has provided the ability to routinely monitor the actual mechanical condition of all rotating and reciprocating machinery and process variables (i.e. pressure, temperature, flow, etc.) of other process equipment within an operating electric power generating plant. This direct correlation between frequency domain vibration and actual mechanical condition of machinery and trending process variables of non-rotating equipment can provide the ''key'' to improving the availability and reliability, thermal efficiency and provide the baseline information necessary for developing a realistic plan for extending the useful life of power plants. The premise of utilizing microprocessor-based Predictive Maintenance to improve power plant operation has been proven by a number of utilities. This paper provides a comprehensive discussion of the TEC approach to Predictive Maintenance and examples of successful programs

  16. Engineering systems reliability, safety, and maintenance an integrated approach

    CERN Document Server

    Dhillon, B S

    2017-01-01

    Today, engineering systems are an important element of the world economy and each year billions of dollars are spent to develop, manufacture, operate, and maintain various types of engineering systems around the globe. Many of these systems are highly sophisticated and contain millions of parts. For example, a Boeing jumbo 747 is made up of approximately 4.5 million parts including fasteners. Needless to say, reliability, safety, and maintenance of systems such as this have become more important than ever before.  Global competition and other factors are forcing manufacturers to produce highly reliable, safe, and maintainable engineering products. Therefore, there is a definite need for the reliability, safety, and maintenance professionals to work closely during design and other phases. Engineering Systems Reliability, Safety, and Maintenance: An Integrated Approach eliminates the need to consult many different and diverse sources in the hunt for the information required to design better engineering syste...

  17. Application of IoT concept on predictive maintenance of industrial equipment

    Directory of Open Access Journals (Sweden)

    Parpala Radu Constantin

    2017-01-01

    Full Text Available The Internet of Things (IoT concept describes an intelligent connectivity of smart devices using the internet network. Nowadays, companies try different approaches for predictive maintenance as a solution to reduce costs and the frequency of maintenance activities. The IoT platforms provide a good support for predictive maintenance as it can integrate information from different machines and manufacturing systems. The main drawback in integrating production system with IoT dedicated platforms is the communication framework, knowing that the main industrial communication protocols are incompatible with modern communication protocols implemented on IoT platforms. In this context, the present paper proposes a new and simple method for on-line monitoring and predictive maintenance of industrial equipment. This method has two features of connected manufacturing. One of these is process monitoring for constant quality assurance, the other one is condition monitoring in order to prevent unplanned downtimes. A case study is presented to demonstrate the feasibility of the proposed method.

  18. An integrated model of statistical process control and maintenance based on the delayed monitoring

    International Nuclear Information System (INIS)

    Yin, Hui; Zhang, Guojun; Zhu, Haiping; Deng, Yuhao; He, Fei

    2015-01-01

    This paper develops an integrated model of statistical process control and maintenance decision. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to ten-scenarios of the production process, where equipment failure may occur besides quality shift. The equipment failure and the control chart alert trigger the corrective maintenance and the predictive maintenance, respectively. The occurrence probability, the cycle time and the cycle cost of each scenario are obtained by integral calculation; therefore, a mathematical model is established to minimize the expected cost by using the genetic algorithm. A Monte Carlo simulation experiment is conducted and compared with the integral calculation in order to ensure the analysis of the ten-scenario model. Another ordinary integrated model without delayed monitoring is also established as comparison. The results of a numerical example indicate satisfactory economic performance of the proposed model. Finally, a sensitivity analysis is performed to investigate the effect of model parameters. - Highlights: • We develop an integrated model of statistical process control and maintenance. • We propose delayed monitoring policy and derive an economic model with 10 scenarios. • We consider two deterioration mechanisms, quality shift and equipment failure. • The delayed monitoring policy will help reduce the expected cost

  19. An approach to integrating surveillance and maintenance tasks to prevent the dominant failure causes of critical components

    International Nuclear Information System (INIS)

    Martorell, S.; Munoz, A.; Serradell, V.

    1995-01-01

    Surveillance requirements and maintenance activities in a nuclear power plant aim to preserve components' inherent reliability. Up to now, predictive and preventive maintenance mainly concerned plant staff, but the US Nuclear Regulatory Commission Maintenance Rule released in July 1991 will have significant impact on how nuclear power plants perform and document this maintenance. Reliability Centered Maintenance (RCM) is a systematic methodology to establish maintenance tasks for critical components in plant with a high degree of compliance with the goals of the Rule. RCM pursues the identification of applicable and efficient tasks to prevent these components from developing their dominant failure causes, and, in turn, towards achieving proper levels of components availability with low cost. In this paper, we present an approach for identifying the most suitable set of tasks to achieve this goal, which involves the integration of maintenance activities and surveillance requirements for each critical component based on the unavailability and cost associated with each individual task which is performed on it

  20. Hidden Semi-Markov Models for Predictive Maintenance

    Directory of Open Access Journals (Sweden)

    Francesco Cartella

    2015-01-01

    Full Text Available Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs with (i no constraints on the state duration density function and (ii being applied to continuous or discrete observation. To deal with such a type of HSMM, we also propose modifications to the learning, inference, and prediction algorithms. Finally, automatic model selection has been made possible using the Akaike Information Criterion. This paper describes the theoretical formalization of the model as well as several experiments performed on simulated and real data with the aim of methodology validation. In all performed experiments, the model is able to correctly estimate the current state and to effectively predict the time to a predefined event with a low overall average absolute error. As a consequence, its applicability to real world settings can be beneficial, especially where in real time the Remaining Useful Lifetime (RUL of the machine is calculated.

  1. Historical maintenance relevant information road-map for a self-learning maintenance prediction procedural approach

    Science.gov (United States)

    Morales, Francisco J.; Reyes, Antonio; Cáceres, Noelia; Romero, Luis M.; Benitez, Francisco G.; Morgado, Joao; Duarte, Emanuel; Martins, Teresa

    2017-09-01

    A large percentage of transport infrastructures are composed of linear assets, such as roads and rail tracks. The large social and economic relevance of these constructions force the stakeholders to ensure a prolonged health/durability. Even though, inevitable malfunctioning, breaking down, and out-of-service periods arise randomly during the life cycle of the infrastructure. Predictive maintenance techniques tend to diminish the appearance of unpredicted failures and the execution of needed corrective interventions, envisaging the adequate interventions to be conducted before failures show up. This communication presents: i) A procedural approach, to be conducted, in order to collect the relevant information regarding the evolving state condition of the assets involved in all maintenance interventions; this reported and stored information constitutes a rich historical data base to train Machine Learning algorithms in order to generate reliable predictions of the interventions to be carried out in further time scenarios. ii) A schematic flow chart of the automatic learning procedure. iii) Self-learning rules from automatic learning from false positive/negatives. The description, testing, automatic learning approach and the outcomes of a pilot case are presented; finally some conclusions are outlined regarding the methodology proposed for improving the self-learning predictive capability.

  2. Modeling a Predictive Energy Equation Specific for Maintenance Hemodialysis.

    Science.gov (United States)

    Byham-Gray, Laura D; Parrott, J Scott; Peters, Emily N; Fogerite, Susan Gould; Hand, Rosa K; Ahrens, Sean; Marcus, Andrea Fleisch; Fiutem, Justin J

    2017-03-01

    Hypermetabolism is theorized in patients diagnosed with chronic kidney disease who are receiving maintenance hemodialysis (MHD). We aimed to distinguish key disease-specific determinants of resting energy expenditure to create a predictive energy equation that more precisely establishes energy needs with the intent of preventing protein-energy wasting. For this 3-year multisite cross-sectional study (N = 116), eligible participants were diagnosed with chronic kidney disease and were receiving MHD for at least 3 months. Predictors for the model included weight, sex, age, C-reactive protein (CRP), glycosylated hemoglobin, and serum creatinine. The outcome variable was measured resting energy expenditure (mREE). Regression modeling was used to generate predictive formulas and Bland-Altman analyses to evaluate accuracy. The majority were male (60.3%), black (81.0%), and non-Hispanic (76.7%), and 23% were ≥65 years old. After screening for multicollinearity, the best predictive model of mREE ( R 2 = 0.67) included weight, age, sex, and CRP. Two alternative models with acceptable predictability ( R 2 = 0.66) were derived with glycosylated hemoglobin or serum creatinine. Based on Bland-Altman analyses, the maintenance hemodialysis equation that included CRP had the best precision, with the highest proportion of participants' predicted energy expenditure classified as accurate (61.2%) and with the lowest number of individuals with underestimation or overestimation. This study confirms disease-specific factors as key determinants of mREE in patients on MHD and provides a preliminary predictive energy equation. Further prospective research is necessary to test the reliability and validity of this equation across diverse populations of patients who are receiving MHD.

  3. Prediction of the safety level in a tritium processing facility through predictive maintenance

    International Nuclear Information System (INIS)

    Anghel, Vasile

    2007-01-01

    Full text: The safety level of a nuclear facility for personnel and environment depends generally on the technological process quality of operation and maintenance and particularly on several technical, technological, economic, and human factors. The role of maintenance is fundamental because it is determined by all the technical, economic and human elements as parts of an integrated system dominated by an important feedback from upstream activities which eventually define the life cycle of the nuclear facility considered. In the maintenance activity as in case of any dynamic area, new elements may appear which, sometimes, require new methods of approach. For considered installation which is a Nuclear Detritiation Plant (NDP) operating as a division of the National Research and Development Institute for Cryogenics and Isotopic Technologies - ICSI, Rm.Valcea, in order to ensure a safety level in operation as high as possible through predictive maintenance, the fuzzy theory and software LabVIEW were applied. The final aim is to achieve the best practices in maintenance of the tritium processing plant. The safety in operation of the NDP equipment and installations is directly related with the maintenance achieved by improving the reliability through methods and advanced techniques. The maintainability is the capacity of an industrial product, in given utilization conditions, to be maintained and re-established up to achieve specified functions. In general the reliability on some interval is a probability conditioned by good operation at the beginning of the interval, representing thus the probability as the element which operated at t = t 0 to operate in the interval (t 0 , t 1 ). The failure is a fundamental event in the reliability theory. Breakdown (failure) is understood as the stop process of the function required from a given product, the failure representing the effect upon that process. The operation of a product on a certain duration can be a 'success' or a

  4. A dynamic predictive maintenance policy for complex multi-component systems

    International Nuclear Information System (INIS)

    Van Horenbeek, Adriaan; Pintelon, Liliane

    2013-01-01

    The use of prognostic methods in maintenance in order to predict remaining useful life is receiving more attention over the past years. The use of these techniques in maintenance decision making and optimization in multi-component systems is however a still underexplored area. The objective of this paper is to optimally plan maintenance for a multi-component system based on prognostic/predictive information while considering different component dependencies (i.e. economic, structural and stochastic dependence). Consequently, this paper presents a dynamic predictive maintenance policy for multi-component systems that minimizes the long-term mean maintenance cost per unit time. The proposed maintenance policy is a dynamic method as the maintenance schedule is updated when new information on the degradation and remaining useful life of components becomes available. The performance, regarding the objective of minimal long-term mean cost per unit time, of the developed dynamic predictive maintenance policy is compared to five other conventional maintenance policies, these are: block-based maintenance, age-based maintenance, age-based maintenance with grouping, inspection condition-based maintenance and continuous condition-based maintenance. The ability of the predictive maintenance policy to react to changing component deterioration and dependencies within a multi-component system is quantified and the results show significant cost savings

  5. Optimizing production and imperfect preventive maintenance planning's integration in failure-prone manufacturing systems

    International Nuclear Information System (INIS)

    Aghezzaf, El-Houssaine; Khatab, Abdelhakim; Tam, Phuoc Le

    2016-01-01

    This paper investigates the issue of integrating production and maintenance planning in a failure-prone manufacturing system. It is assumed that the system's operating state is stochastically predictable, in terms of its operating age, and that it can accordingly be preventively maintained during preplanned periods. Preventive maintenance is assumed to be imperfect, that is when performed, it brings the manufacturing system to an operating state that lies between ‘as bad as old’ and ‘as good as new’. Only an overhauling of the system brings it to a ‘as good as new’ operating state again. A practical integrated production and preventive maintenance planning model, that takes into account the system's manufacturing capacity and its operational reliability state, is developed. The model is naturally formulated as a mixed-integer non-linear optimization problem, for which an extended mixed-integer linear reformulation is proposed. This reformulation, while it solves the proposed integrated planning problem to optimality, remains quite demanding in terms of computational time. A fix-and-optimize procedure, that takes advantage of some properties of the original model, is then proposed. The reformulation and the fix-and-optimize procedure are tested on some test instances adapted from those available in the literature. The results show that the proposed fix-and-optimize procedure performs quite well and opens new research direction for future improvements. - Highlights: • Integration of production planning and imperfect preventive maintenance is explored. • Imperfect maintenance is modeled using a fitting age reduction hybrid hazard rate. • A practical approximate optimization model for this integration is proposed. • The resulting naturally MINL optimization model is reformulated and solved as a MILP. • An effective fix-and-optimize procedure is proposed for large instances of this MILP.

  6. Hypertext-based integration for nuclear plant maintenance and operations

    International Nuclear Information System (INIS)

    Tsoukalas, L.H.; Upadhyaya, B.R.

    1991-01-01

    A methodology is presented that uses fuzzy graphs in the emerging paradigm of hypertext for the purpose of integrating data, information and multifaceted knowledge resources abounding in power plant operations and maintenance. A hypertext system is viewed as a set of nodes and links where with each link we associate membership functions embodying context-dependent criteria for navigating large information spaces. A general framework for navigation is outlined and graph-theory navigational tools are developed. A numerical example and a HyperCard-based prototype for monitoring special material in the MHTGR-NPR are included. 10 refs., 12 figs

  7. Integrating availability and maintenance objectives in plant design. EDF approach

    International Nuclear Information System (INIS)

    Degrave, Claude; Martin-Onraet, Michel

    1995-01-01

    Energy self sufficiency is a major strategic necessity for France. Regarding the fossil fuels power, competitiveness of nuclear energy is a key goal for Electricite de France. Accordingly, for future nuclear power plants to remain competitive, it is necessary to maintain the kWh production costs of the future units at a level close to those of the latest units under construction (N4 series), while raising the safety level. EDF therefore decided to implement an analytical and systematic process for study of the new projects to optimize the design by integration of the maintenance (durations, costs), availability and radiation exposure goals from the related operating experience. This approach, CIDEM (French acronym for Design Integrating Availability, operating Experience and Maintenance) aims at a single goal: to minimize the kWh production cost incorporating investment, operation and fuel costs, allowing for the operating experience from French and foreign units. The implementation of the CIDEM process constitutes for EDF a new approach to the study of the new Nuclear Power Plant projects. The competitivity of nuclear energy greatly depends on the success of such an approach. The studies conducted in the availability field have already highlighted a number of critical points and have made it possible to define the corresponding goal allocations and to establish a first series of structuring specifications for the project. (J.P.N.)

  8. Low-complexity Behavioral Model for Predictive Maintenance of Railway Turnouts

    DEFF Research Database (Denmark)

    Barkhordari, Pegah; Galeazzi, Roberto; Tejada, Alejandro de Miguel

    2017-01-01

    Maintenance of railway infrastructures represents a major cost driver for any infrastructure manager since reliability and dependability must be guaranteed at all times. Implementation of predictive maintenance policies relies on the availability of condition monitoring systems able to assess...

  9. Predictive Maintenance--An Effective Money Saving Tool Being Applied in Industry Today.

    Science.gov (United States)

    Smyth, Tom

    2000-01-01

    Looks at preventive/predictive maintenance as it is used in industry. Discusses core preventive maintenance tools that must be understood to prepare students. Includes a list of websites related to the topic. (JOW)

  10. Infrared thermography application on predictive maintenance for exhaust fan motor

    International Nuclear Information System (INIS)

    I Wayan Widiana; Jakaria; Artadi Heru; Mulyono

    2013-01-01

    To determine the condition of the exhaust fan motor in terms of heat dissipation, predictive maintenance needs to be done. One way is to use infrared thermography. The method used is an infrared thermography with qualitative technique which the analysis focused on the distribution patterns of heat captured by the infrared camera. From measurement results expected to be obtained data of the heat distribution occurs in the motor exhaust fan so it can be given treatment or further improvements recommendations to avoid failure of the operation. Results of measurements on the motor exhaust fan 9 and the motor exhaust fan 10 indicates that there is excessive heat dissipation (over heating). The recommendation given is increasing the motor capacity of 11 kW to 18 kW with a consideration of the addition load on exhaust fan system and age of motor more than 22 years. (author)

  11. Cryogenic systems advanced monitoring, fault diagnostics, and predictive maintenance

    CERN Document Server

    Arpaia, Pasquale; Inglese, Vitaliano; Pezzetti, Marco

    2018-01-01

    Cryogenics, the study and technology of materials and systems at very low temperature, is widely used for sensors and instruments requiring very highly precise measurements with low electrical resistance, especially for measurements of materials and energies at a very small scale. Thus, the need to understand how instruments operate and perform over time at temperatures below -2920 F (-1800 C) is critical, for applications from Magnetic Resonance Imaging (MRI) to Nuclear Magnetic Resonance Spectroscopy to instrumentation for particle accelerators of all kinds. This book brings to the reader guidance learned from work at the European Laboratory for Nuclear Research (CERN), and its large scale particle accelerator in Switzerland to help engineers and technicians implement best practices in instrumentation at cryogenic temperatures, including a better understanding of fault detection and predictive maintenance. Special problems with devices like flow meters, pressure gauges, and temperature gauges when operating...

  12. Improving nuclear power plant reliability through predictive maintenance

    International Nuclear Information System (INIS)

    Geilhausen, R.; Kunze, U.

    1996-01-01

    Maintenance strategies can be assigned to one of three categories: failure maintenance, periodic maintenance or condition-oriented maintenance. The optimum maintenance scheme can be selected on the basis of a cost-benefit analysis but the safety of life and limb or the political climate for NPP can hardly expressed in numbers. The implementation of preventive maintenance needs two preconditions: high-performance instrumentation in the form of stationary and mobile monitoring systems for the determination of the condition of the nuclear power plant components and provision of a tool that can handle both the organization of the work and the evaluation of the results obtained. (authors)

  13. Operations and maintenance plan : Dallas Integrated Corridor Management (ICM) demonstration project.

    Science.gov (United States)

    2014-01-01

    This Operations and Maintenance (O&M) Plan describes how the Integrated Corridor Management System (ICMS) will be used in daily transportation operations and maintenance activities. The Plan addresses the activities needed to effectively operate the ...

  14. On the Use of Time-Limited Information for Maintenance Decision Support: A Predictive Approach under Maintenance Constraints

    Directory of Open Access Journals (Sweden)

    E. Khoury

    2013-01-01

    Full Text Available This paper deals with a gradually deteriorating system operating under an uncertain environment whose state is only known on a finite rolling horizon. As such, the system is subject to constraints. Maintenance actions can only be planned at imposed times called maintenance opportunities that are available on a limited visibility horizon. This system can, for example, be a commercial vehicle with a monitored critical component that can be maintained only in some specific workshops. Based on the considered system, we aim to use the monitoring data and the time-limited information for maintenance decision support in order to reduce its costs. We propose two predictive maintenance policies based, respectively, on cost and reliability criteria. Classical age-based and condition-based policies are considered as benchmarks. The performance assessment shows the value of the different types of information and the best way to use them in maintenance decision making.

  15. Predictive techniques for river channel evolution and maintenance

    Science.gov (United States)

    Nelson, J.M.

    1996-01-01

    Predicting changes in alluvial channel morphology associated with anthropogenic and natural changes in flow and/or sediment supply is a critical part of the management of riverine systems. Over the past few years, advances in the understanding of the physics of sediment transport in conjunction with rapidly increasing capabilities in computational fluid dynamics have yielded now approaches to problems in river mechanics. Techniques appropriate for length scales ranging from reaches to bars and bedforms are described here. Examples of the use of these computational approaches are discussed for three cases: (1) the design of diversion scenarios that maintain channel morphology in steep cobble-bedded channels in Colorado, (2) determination of channel maintenance flows for the preservation of channel islands in the Snake River in Idaho, and (3) prediction of the temporal evolution of deposits in lateral separation zones for future assessment of the impacts of various dam release scenarios on lateral separation deposits in the Colorado River in Grand Canyon. With continued development of their scientific and technical components, the methodologies described here can provide powerful tools for the management of river environments in the future.

  16. A model for preemptive maintenance of medical linear accelerators—predictive maintenance

    International Nuclear Information System (INIS)

    Able, Charles M.; Baydush, Alan H.; Nguyen, Callistus; Gersh, Jacob; Ndlovu, Alois; Rebo, Igor; Booth, Jeremy; Perez, Mario; Sintay, Benjamin; Munley, Michael T.

    2016-01-01

    Unscheduled accelerator downtime can negatively impact the quality of life of patients during their struggle against cancer. Currently digital data accumulated in the accelerator system is not being exploited in a systematic manner to assist in more efficient deployment of service engineering resources. The purpose of this study is to develop an effective process for detecting unexpected deviations in accelerator system operating parameters and/or performance that predicts component failure or system dysfunction and allows maintenance to be performed prior to the actuation of interlocks. The proposed predictive maintenance (PdM) model is as follows: 1) deliver a daily quality assurance (QA) treatment; 2) automatically transfer and interrogate the resulting log files; 3) once baselines are established, subject daily operating and performance values to statistical process control (SPC) analysis; 4) determine if any alarms have been triggered; and 5) alert facility and system service engineers. A robust volumetric modulated arc QA treatment is delivered to establish mean operating values and perform continuous sampling and monitoring using SPC methodology. Chart limits are calculated using a hybrid technique that includes the use of the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. There are 7 accelerators currently under active surveillance. Currently 45 parameters plus each MLC leaf (120) are analyzed using Individual and Moving Range (I/MR) charts. The initial warning and alarm rule is as follows: warning (2 out of 3 consecutive values ≥ 2σ hybrid ) and alarm (2 out of 3 consecutive values or 3 out of 5 consecutive values ≥ 3σ hybrid ). A customized graphical user interface provides a means to review the SPC charts for each parameter and a visual color code to alert the reviewer of parameter status. Forty-five synthetic errors/changes were introduced to test the effectiveness of our initial chart limits. Forty

  17. A model for preemptive maintenance of medical linear accelerators-predictive maintenance.

    Science.gov (United States)

    Able, Charles M; Baydush, Alan H; Nguyen, Callistus; Gersh, Jacob; Ndlovu, Alois; Rebo, Igor; Booth, Jeremy; Perez, Mario; Sintay, Benjamin; Munley, Michael T

    2016-03-10

    Unscheduled accelerator downtime can negatively impact the quality of life of patients during their struggle against cancer. Currently digital data accumulated in the accelerator system is not being exploited in a systematic manner to assist in more efficient deployment of service engineering resources. The purpose of this study is to develop an effective process for detecting unexpected deviations in accelerator system operating parameters and/or performance that predicts component failure or system dysfunction and allows maintenance to be performed prior to the actuation of interlocks. The proposed predictive maintenance (PdM) model is as follows: 1) deliver a daily quality assurance (QA) treatment; 2) automatically transfer and interrogate the resulting log files; 3) once baselines are established, subject daily operating and performance values to statistical process control (SPC) analysis; 4) determine if any alarms have been triggered; and 5) alert facility and system service engineers. A robust volumetric modulated arc QA treatment is delivered to establish mean operating values and perform continuous sampling and monitoring using SPC methodology. Chart limits are calculated using a hybrid technique that includes the use of the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. There are 7 accelerators currently under active surveillance. Currently 45 parameters plus each MLC leaf (120) are analyzed using Individual and Moving Range (I/MR) charts. The initial warning and alarm rule is as follows: warning (2 out of 3 consecutive values ≥ 2σ hybrid) and alarm (2 out of 3 consecutive values or 3 out of 5 consecutive values ≥ 3σ hybrid). A customized graphical user interface provides a means to review the SPC charts for each parameter and a visual color code to alert the reviewer of parameter status. Forty-five synthetic errors/changes were introduced to test the effectiveness of our initial chart limits. Forty

  18. Technology success: Integration of power plant reliability and effective maintenance

    International Nuclear Information System (INIS)

    Ferguson, K.

    2008-01-01

    The nuclear power generation sector has a tradition of utilizing technology as a key attribute for advancement. Companies that own, manage, and operate nuclear power plants can be expected to continue to rely on technology as a vital element of success. Inherent with the operations of the nuclear power industry in many parts of the world is the close connection between efficiency of power plant operations and successful business survival. The relationship among power plant availability, reliability of systems and components, and viability of the enterprise is more evident than ever. Technology decisions need to be accomplished that reflect business strategies, work processes, as well as needs of stakeholders and authorities. Such rigor is needed to address overarching concerns such as power plant life extension and license renewal, new plant orders, outage management, plant safety, inventory management etc. Particular to power plant reliability, the prudent leveraging of technology as a key to future success is vital. A dominant concern is effective asset management as physical plant assets age. Many plants are in, or are entering in, a situation in which systems and component design life and margins are converging such that failure threats can come into play with increasing frequency. Wisely selected technologies can be vital to the identification of emerging threats to reliable performance of key plant features and initiating effective maintenance actions and investments that can sustain or enhance current reliability in a cost effective manner. This attention to detail is vital to investment in new plants as well This paper and presentation will address (1) specific technology success in place at power plants, including nuclear, that integrates attention to attaining high plant reliability and effective maintenance actions as well as (2) complimentary actions that maximize technology success. In addition, the range of benefits that accrue as a result of

  19. Development the conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation

    Science.gov (United States)

    Milana; Khan, M. K.; Munive, J. E.

    2014-07-01

    The importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective.

  20. Development the conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation

    International Nuclear Information System (INIS)

    Milana; Khan, M K; Munive, J E

    2014-01-01

    The importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective

  1. Health and Maintenance Status Determination and Predictive Fault Diagnosis System, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this project is to demonstrate intelligent health and maintenance status determination and predictive fault diagnosis techniques for NASA rocket...

  2. A maintenance time prediction method considering ergonomics through virtual reality simulation.

    Science.gov (United States)

    Zhou, Dong; Zhou, Xin-Xin; Guo, Zi-Yue; Lv, Chuan

    2016-01-01

    Maintenance time is a critical quantitative index in maintainability prediction. An efficient maintenance time measurement methodology plays an important role in early stage of the maintainability design. While traditional way to measure the maintenance time ignores the differences between line production and maintenance action. This paper proposes a corrective MOD method considering several important ergonomics factors to predict the maintenance time. With the help of the DELMIA analysis tools, the influence coefficient of several factors are discussed to correct the MOD value and the designers can measure maintenance time by calculating the sum of the corrective MOD time of each maintenance therbligs. Finally a case study is introduced, by maintaining the virtual prototype of APU motor starter in DELMIA, designer obtains the actual maintenance time by the proposed method, and the result verifies the effectiveness and accuracy of the proposed method.

  3. Component-Based Data-Driven Predictive Maintenance to Reduce Unscheduled Maintenance Events

    NARCIS (Netherlands)

    Verhagen, W.J.C.; Curran, R.; de Boer, L.W.M.; Chen, C.H.; Trappey, A.C.; Peruzzini, M.; Stjepandić, J.; Wognum, N.

    2017-01-01

    Costs associated with unscheduled and preventive maintenance can contribute significantly to an airline's expenditure. Reliability analysis can help to identify and plan for maintenance events. Reliability analysis in industry is often limited to statistically based

  4. Creating Value by Integrating Logistic Trains Services and Maintenance Activities

    NARCIS (Netherlands)

    Busstra, Marten; van Dongen, Leonardus Adriana Maria

    2015-01-01

    NedTrain is the Netherlands Railway's subsidiary responsible for rolling stock maintenance. Train sets are brought in for short-term routine maintenance after set intervals of some 75 to 120 days. When a major defect occurs, train sets are allocated to one of the three maintenance depots and are

  5. Anthropometric Indicators Predict Metabolic Syndrome Diagnosis in Maintenance Hemodialysis Patients.

    Science.gov (United States)

    Vogt, Barbara Perez; Ponce, Daniela; Caramori, Jacqueline Costa Teixeira

    2016-06-01

    Obesity has been considered the key in metabolic syndrome (MetS) development, and fat accumulation may be responsible for the occurrence of metabolic abnormalities in hemodialysis patients. The use of gold-standard methods to evaluate obesity is limited, and anthropometric measures may be the simplest methods. However, no study has investigated the association between anthropometric indexes and MetS in these patients. Therefore, the aim was to determine which anthropometric indexes had the best association and prediction for MetS in patients undergoing hemodialysis. Cross-sectional study that included patients older than 18 years, undergoing hemodialysis for at least 3 months. Patients with liver disease and cancer or those receiving corticosteroids or antiretroviral therapy were excluded. Diagnostic criteria from Harmonizing Metabolic Syndrome were used for the diagnosis of MetS. Anthropometric indexes evaluated were body mass index (BMI); percent standard of triceps skinfold thickness and of middle arm muscle circumference; waist circumference (WC); sagittal abdominal diameter; neck circumference; waist-to-hip, waist-to-thigh, and waist-to-height ratios; sagittal index; conicity index; and body fat percentage. Ninety-eight patients were included, 54.1% male, and mean age was 57.8 ± 12.9 years. The prevalence of MetS was 74.5%. Individuals with MetS had increased accumulation of abdominal fat and general obesity. Waist-to-height ratio was the variable independently associated with MetS diagnosis (odds ratio, 1.21; 95% confidence interval, 1.09-1.34; P < .01) and that better predicts MetS, followed by WC and BMI (area under the curve of 0.840, 0.836, and 0.798, respectively, P < .01). Waist-to-height ratio was the best anthropometric predictor of MetS in maintenance hemodialysis patients. © 2015 American Society for Parenteral and Enteral Nutrition.

  6. Optimization of reliability centered predictive maintenance scheme for inertial navigation system

    International Nuclear Information System (INIS)

    Jiang, Xiuhong; Duan, Fuhai; Tian, Heng; Wei, Xuedong

    2015-01-01

    The goal of this study is to propose a reliability centered predictive maintenance scheme for a complex structure Inertial Navigation System (INS) with several redundant components. GO Methodology is applied to build the INS reliability analysis model—GO chart. Components Remaining Useful Life (RUL) and system reliability are updated dynamically based on the combination of components lifetime distribution function, stress samples, and the system GO chart. Considering the redundant design in INS, maintenance time is based not only on components RUL, but also (and mainly) on the timing of when system reliability fails to meet the set threshold. The definition of components maintenance priority balances three factors: components importance to system, risk degree, and detection difficulty. Maintenance Priority Number (MPN) is introduced, which may provide quantitative maintenance priority results for all components. A maintenance unit time cost model is built based on components MPN, components RUL predictive model and maintenance intervals for the optimization of maintenance scope. The proposed scheme can be applied to serve as the reference for INS maintenance. Finally, three numerical examples prove the proposed predictive maintenance scheme is feasible and effective. - Highlights: • A dynamic PdM with a rolling horizon is proposed for INS with redundant components. • GO Methodology is applied to build the system reliability analysis model. • A concept of MPN is proposed to quantify the maintenance sequence of components. • An optimization model is built to select the optimal group of maintenance components. • The optimization goal is minimizing the cost of maintaining system reliability

  7. Degradation mode analysis: An approach to establish effective predictive maintenance tasks

    International Nuclear Information System (INIS)

    Sonnett, D.E.; Douglass, P.T.; Barnard, D.D.

    1991-01-01

    A significant number of nuclear generating stations have been employing Reliability Centered Maintenance methodology to arrive at applicable and effective maintenance tasks for their plant equipment. The resultant endpoint of most programs has been an increased emphasis on predictive maintenance as the task of choice for monitoring and trending plant equipment condition to address failure mechanisms of the analyses. Many of these plants have spent several years conducting reliability centered analysis before they seriously begin implementing predictive program improvements. In this paper we present another methodology, entitled Degradation Mode Analysis, which provides a more direct method to quickly and economically achieve the major benefit of reliability centered analysis, namely predictive maintenance. (author)

  8. Model-based fault diagnosis framework for effective predictive maintenance / B.B. Akindele

    OpenAIRE

    Akindele, Babatunde Babajide

    2010-01-01

    Predictive maintenance is a proactive maintenance strategy that is aimed at preventing the unexpected failure of equipment through condition monitoring of the health and performance of the equipment. Incessant equipment outage resulting in low availability of production facilities is a major issue in the Nigerian manufacturing environment. Improving equipment availability in Nigeria industry through institution of a full featured predictive maintenance has been suggested by many authors. T...

  9. Predictive maintenance strategy in the graphics departament of a tobacco company

    Directory of Open Access Journals (Sweden)

    Guilherme Francez Toazza

    2015-09-01

    Full Text Available The purpose of this article was to describe the implementation of a strategy for Predictive Maintenance in the graphics department of the company Souza Cruz SA after the techniques of Vibration Analysis, Thermography, Ferrography and Inspection Sensitive. The research method was the action-research. The proposed study is the application of a management Predictive Maintenance acting strategically within the context in which it is embedded. The article reviews the theoretical concepts and Predictive Maintenance techniques mentioned above. In the survey, were raised in the information system of the company, the rate of breakdown of equipment (downtime, waste energy costs, maintenance costs and availability of H / h (man / hour and availability of equipment for the production the period prior to the implementation of a predictive maintenance management and consistent compared with results after this deployment. From the results obtained, it was evident that only preventive maintenance, combined with a model predictive maintenance is not poor enough to maintain the desired reliability in a department of great importance to your company. So, it is possible to say that the implementation of a predictive maintenance strategy can make the Maintenance sector to work strategically with common goals to the company as a whole.

  10. Integration of plant life management in operation and maintenance

    International Nuclear Information System (INIS)

    Hutin, Jean-Pierre

    2002-01-01

    Full text: 1 - INTRODUCTION. Electricite de France is now operating 58 PWR nuclear power plants which produce 75% of french electricity. Besides maintaining safety and availability on a routine basis, it is outmost important to protect the investment. Indeed, such an asset is a tremendous advantage just as the company is going to face the new european electricity market. That is the reason why EDF is devoting important effort to implement ageing management as an integral part of operation and maintenance programs. But it must be recognized that NPP lifetime is not threatened only by component-related problems: other less technical issues must be seriously considered like industrial support, information system, skilled people, public acceptance, etc. 2 - LIFE MANAGEMENT POLICY. In France, there is no limited licensing period for NPPs. The life management policy of nuclear power plants is based on three principles: - safe and cost-effective operation, looking for excellence in daily activities, with an effective experience feedback organisation taking advantage of the high level of standardization of the units, - every ten years, a new set of safety standards, a complete review of each facility and an upgrading of its safety level through appropriate modifications while maintaining unit standardization in all the fleet, - a Life Management Program, at corporate level, which permanently scrutinizes operation and maintenance activities to identify decisions which could impair plant lifetime and which surveys research and development programs related to ageing phenomenon understanding. 3 - INTEGRATION OF LIFETIME CONCERN IN O and M ACTIVITIES. It is outmost important to take in account lifetime concern in daily operation and maintenance activities and this must be done as early as possible in plant life. Even though sophisticated assessments require engineering capacity, many good ideas may arise from plant staff. For that reason, increasing lifetime awareness of plant

  11. Integrated services and maintenance in nuclear power plants

    International Nuclear Information System (INIS)

    Roos, Georg

    2001-01-01

    The general situation concerning services and nuclear power maintenance is reviewed following liberalization of Europa's power market. Issues relating to outsourcing maintenance services, effectiveness and reducing cost structure of maintenance are addressed on the cases of power markets in northern countries, Spain, Switzerland, Germany and Hungary. A special attention is paid on range of maintenance activity offered and performanced by Framatome. Ways of reducing costs in the field of maintenance as well as of reducing outage time are indicated. In conclusion, the following items are emphasized: - liberalization of Europe's power market in eastern Europe at its beginning; - in-house service in eastern Europe with numerous personnel; - Framatome ANP covers the entire range of maintenance competence; - consultance can be the first approach for a common co-operation

  12. Interspecific gene flow and maintenance of species integrity in oaks

    Directory of Open Access Journals (Sweden)

    Oliver Gailing

    2014-07-01

    Full Text Available Oak species show a wide variation in morphological and physiological characters, and species boundaries between closely related species are often not clear-cut. Still, despite frequent interspecific gene flow, oaks maintain distinct morphological and physiological adaptations. In sympatric stands, spatial distribution of species with different ecological requirements is not random but constrained by soil and other microenvironmental factors. Pre-zygotic isolation (e.g. cross incompatibilities, asynchrony in flowering, pollen competition and post-zygotic isolation (divergent selection contribute to the maintenance of species integrity in sympatric oak stands. The antagonistic effects of interspecific gene flow and divergent selection are reflected in the low genetic differentiation between hybridizing oak species at most genomic regions interspersed by regions with signatures of divergent selection (outlier regions. In the near future, the availability of high-density genetic linkage maps anchored to scaffolds of a sequenced Q. robur genome will allow to characterize the underlying genes in these outlier regions and their putative role in reproductive isolation between species. Reciprocal transplant experiments of seedlings between parental environments can be used to characterize selection on outlier genes. High transferability of gene-based markers will enable comparative outlier screens in different oak species.

  13. Maintenance modeling and optimization integrating human and material resources

    International Nuclear Information System (INIS)

    Martorell, S.; Villamizar, M.; Carlos, S.; Sanchez, A.

    2010-01-01

    Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.

  14. Maintenance modeling and optimization integrating human and material resources

    Energy Technology Data Exchange (ETDEWEB)

    Martorell, S., E-mail: smartore@iqn.upv.e [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Villamizar, M.; Carlos, S. [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Sanchez, A. [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia (Spain)

    2010-12-15

    Maintenance planning is a subject of concern to many industrial sectors as plant safety and business depend on it. Traditionally, the maintenance planning is formulated in terms of a multi-objective optimization (MOP) problem where reliability, availability, maintainability and cost (RAM+C) act as decision criteria and maintenance strategies (i.e. maintenance tasks intervals) act as the only decision variables. However the appropriate development of each maintenance strategy depends not only on the maintenance intervals but also on the resources (human and material) available to implement such strategies. Thus, the effect of the necessary resources on RAM+C needs to be modeled and accounted for in formulating the MOP affecting the set of objectives and constraints. In this paper RAM+C models to explicitly address the effect of human resources and material resources (spare parts) on RAM+C criteria are proposed. This extended model allows accounting for explicitly how the above decision criteria depends on the basic model parameters representing the type of strategies, maintenance intervals, durations, human resources and material resources. Finally, an application case is performed to optimize the maintenance plan of a motor-driven pump equipment considering as decision variables maintenance and test intervals and human and material resources.

  15. Development of the predictive maintenance system prototype for the rod control system

    International Nuclear Information System (INIS)

    Lim, H. S.; Hong, H. P.; Koo, J. M.; Kim, Y. B.; Han, H. W.

    2003-01-01

    The demand for safety and reliability of Nuclear Power Plants (NPPs) has been constantly increasing and economical operation is also an important issue. Developing and adopting predictive maintenance technology for the major systems or equipment is considered as a way to achieve these goals. This paper describes the development of a predictive maintenance system prototype for the Rod Control System, which adopts an advanced methodology. Bayesian Belief Networks (BBN) has been adopted for the real time fault diagnosis and prediction of the system. Through a simulation test, it was confirmed that the prototype monitors and secures sound operability of rod drive mechanism and its control system, and also provides the predictive maintenance information

  16. Development of a prototype system for prediction of the group error at the maintenance work

    International Nuclear Information System (INIS)

    Yoshino, Kenji; Hirotsu, Yuuko

    2001-01-01

    This paper described on development and performance evaluation of a prototype system for prediction of the group error at the maintenance work. The results so far are as follows. (1) When a user inputs the existence and the grade of the feature factor of the maintenance work as a prediction object, an organization and an organization factor and a group PSF put into the system. The maintenance group error to target can be predicted through the prediction model which consists of a class of seven stages. (2) This system by utilizing the information on a prediction result database, it can be use not only for prediction of a maintenance group but for various safe Activity, such as KYT(Kiken Yochi Training) and TBM(Tool Box Meeting). (3) This system predicts a cooperation error at highest rate, and subsequently. Predicts the detection error at a high rate. and to the decision-making. Error, the transfer error and the state cognitive error, and state error, it has the characteristics predicted at almost same rate. (4) if it has full knowledge even if the feature, such as the enforcement conditions of maintenance work, and organization, even if the user has neither the knowledge about a human factor, users experience, anyone of this system is slight about the extent, generating of a maintenance group error made difficult from the former logically and systematically, it can predict with business time for about 15 minutes. (author)

  17. Predictive maintenance policy for a gradually deteriorating system subject to stress

    Energy Technology Data Exchange (ETDEWEB)

    Deloux, E. [IRCCyN/Ecole des Mines de Nantes, Nantes (France); Castanier, B. [IRCCyN/Ecole des Mines de Nantes, Nantes (France)], E-mail: bruno.castanier@emn.fr; Berenguer, C. [Universite de Technologie de Troyes/CNRS, Troyes (France)

    2009-02-15

    This paper deals with a predictive maintenance policy for a continuously deteriorating system subject to stress. We consider a system with two failure mechanisms which are, respectively, due to an excessive deterioration level and a shock. To optimize the maintenance policy of the system, an approach combining statistical process control (SPC) and condition-based maintenance (CBM) is proposed. CBM policy is used to inspect and replace the system according to the observed deterioration level. SPC is used to monitor the stress covariate. In order to assess the performance of the proposed maintenance policy and to minimize the long-run expected maintenance cost per unit of time, a mathematical model for the maintained system cost is derived. Analysis based on numerical results are conducted to highlight the properties of the proposed maintenance policy in respect to the different maintenance parameters.

  18. Predictive maintenance policy for a gradually deteriorating system subject to stress

    International Nuclear Information System (INIS)

    Deloux, E.; Castanier, B.; Berenguer, C.

    2009-01-01

    This paper deals with a predictive maintenance policy for a continuously deteriorating system subject to stress. We consider a system with two failure mechanisms which are, respectively, due to an excessive deterioration level and a shock. To optimize the maintenance policy of the system, an approach combining statistical process control (SPC) and condition-based maintenance (CBM) is proposed. CBM policy is used to inspect and replace the system according to the observed deterioration level. SPC is used to monitor the stress covariate. In order to assess the performance of the proposed maintenance policy and to minimize the long-run expected maintenance cost per unit of time, a mathematical model for the maintained system cost is derived. Analysis based on numerical results are conducted to highlight the properties of the proposed maintenance policy in respect to the different maintenance parameters

  19. Guidance for the design and management of a maintenance plan to assure safety and improve the predictability of a DOE nuclear irradiation facility. Final report

    International Nuclear Information System (INIS)

    Booth, R.S.; Kryter, R.C.; Shepard, R.L.; Smith, O.L.; Upadhyaya, B.R.; Rowan, W.J.

    1994-10-01

    A program is recommended for planning the maintenance of DOE nuclear facilities that will help safety and enhance availability throughout a facility's life cycle. While investigating the requirements for maintenance activities, a major difference was identified between the strategy suitable for a conventional power reactor and one for a research reactor facility: the latter should provide a high degree of predicted availability (referred to hereafter as ''predictability'') to its users, whereas the former should maximize total energy production. These differing operating goals necessitate different maintenance strategies. A strategy for scheduling research reactor facility operation and shutdown for maintenance must balance safety, reliability,and predicted availability. The approach developed here is based on three major elements: (1) a probabilistic risk analysis of the balance between assured reliability and predictability (presented in Appendix C), (2) an assessment of the safety and operational impact of maintenance activities applied to various components of the facility, and (3) a data base of historical and operational information on the performance and requirements for maintenance of various components. These factors are integrated into a set of guidelines for designing a new highly maintainable facility, for preparing flexible schedules for improved maintenance of existing facilities, and for anticipating the maintenance required to extend the life of an aging facility. Although tailored to research reactor facilities, the methodology has broader applicability and may therefore be used to improved the maintenance of power reactors, particularly in anticipation of peak load demands

  20. Motivational indictors predicting the engagement, frequency and adequacy of rainwater tank maintenance

    Science.gov (United States)

    Mankad, Aditi; Greenhill, Murni

    2014-01-01

    Rainwater tank maintenance is a key social behavior in our changing environment, as tanks are being adopted worldwide to augment household water supplies and reduce urban water stress. The maintenance of rainwater tanks in urban areas is an important pro-environmental behavior that prevents public health issues arising from unhygienic tank use. This study examined motivational differences in maintenance behavior between householders with retrofitted and mandated (compulsory) rainwater tanks on their property (N = 1988). Results showed that retrofitted tank owners were more self-determined in their motivation than mandated owners. Amotivation and integrated regulation were both dominant predictors of engagement in tank maintenance, frequency and adequacy of tank maintenance activities. Those involved in more maintenance activity were likely driven to do so because of feelings of adherence to personal goals and values (e.g., as "sustainable" citizens), whereas individuals who experienced a lack of control and alienation from the activity were likely to view maintenance as meaningless. Thus, people with higher integrated regulation engaged in more tank maintenance activities, whereas more amotivated individuals engaged in less maintenance. As cities begin relying more on citizen self-sufficiency with respect to water and energy resources, issues relating to infrastructure maintenance and operation become paramount. Results show that motivation is important in the impetus to engage in a pro-environmental behavior as well as the frequency and accuracy with which that behavior is undertaken. Policy implications are further discussed.

  1. 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.

  2. A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem

    DEFF Research Database (Denmark)

    Rahmati, Seyed Habib A.; Ahmadi, Abbas; Govindan, Kannan

    2018-01-01

    the level of the system optimization. By means of this equipment, managers can benefit from a condition-based maintenance (CBM) for monitoring and managing their system. The chief aim of the paper is to develop a stochastic maintenance problem based on CBM activities engaged with a complex applied......Integrated consideration of production planning and maintenance processes is a real world assumption. Specifically, by improving the monitoring equipment such as various sensors or product-embedded information devices in recent years, joint assessment of these processes is inevitable for enhancing...... production problem called flexible job shop scheduling problem (FJSP). This integrated problem considers two maintenance scenarios in terms of corrective maintenance (CM) and preventive maintenance (PM). The activation of scenario is done by monitoring the degradation condition of the system and comparing...

  3. An evaluation system of the setting up of predictive maintenance programmes

    International Nuclear Information System (INIS)

    Carnero, MaCarmen

    2006-01-01

    Predictive Maintenance can provide an increase in safety, quality and availability in industrial plants. However, the setting up of a Predictive Maintenance Programme is a strategic decision that until now has lacked analysis of questions related to its setting up, management and control. In this paper, an evaluation system is proposed that carries out the decision making in relation to the feasibility of the setting up. The evaluation system uses a combination of tools belonging to operational research such as: Analytic Hierarchy Process, decision rules and Bayesian tools. This system is a help tool available to the managers of Predictive Maintenance Programmes which can both increase the number of Predictive Maintenance Programmes set up and avoid the failure of these programmes. The Evaluation System has been tested in a petrochemical plant and in a food industry

  4. Developing a Predictive for Unscheduled Maintenance Requirements on United States Air Force Installations

    National Research Council Canada - National Science Library

    Kovich, Matthew D; Norton, J. D

    2008-01-01

    .... This paper develops one such method by using linear regression and time series analysis to develop a predictive model to forecast future year man-hour and funding requirements for unscheduled maintenance...

  5. Developing a Predictive Model for Unscheduled Maintenance Requirements on United States Air Force Installations

    National Research Council Canada - National Science Library

    Kovich, Matthew D; Norton, J. D

    2008-01-01

    .... This paper develops one such method by using linear regression and time series analysis to develop a predictive model to forecast future year man-hour and funding requirements for unscheduled maintenance...

  6. Preventative and predictive maintenance as a function of spare part management

    International Nuclear Information System (INIS)

    LaRose, R.; Sloski, P.

    2006-01-01

    Preventive and predictive maintenance has many aspects, such as vibration monitoring, lubricating oil analysis, thermography etc. This presentation focuses on the material and design application of sealing devices. (author)

  7. Optimization of maintenance for power system equipment using a predictive health model

    NARCIS (Netherlands)

    Bajracharya, G.; Koltunowicz, T.; Negenborn, R.R.; Papp, Z.; Djairam, D.; Schutter, B.D. de; Smit, J.J.

    2009-01-01

    In this paper, a model-predictive control based framework is proposed for modeling and optimization of the health state of power system equipment. In the framework, a predictive health model is proposed that predicts the health state of the equipment based on its usage and maintenance actions. Based

  8. An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning

    Directory of Open Access Journals (Sweden)

    Néstor Rodríguez-Padial

    2017-01-01

    Full Text Available The uncertainty of demand has led production systems to become increasingly complex; this can affect the availability of the machines and thus their maintenance. Therefore, it is necessary to adequately manage the information that facilitates decision-making. This paper presents a system for making decisions related to the design of customized maintenance plans in a production plant. This paper addresses this tactical goal and aims to provide greater knowledge and better predictions by projecting reliable behavior in the medium-term, integrating this new functionality into classic Balance Scorecards, and making it possible to extend their current measuring function to a new aptitude: predicting evolution based on historical data. In the proposed Custom Balance Scorecard design, an exploratory data phase is integrated with another analysis and prediction phase using Principal Component Analysis algorithms and Machine Learning that uses Artificial Neural Network algorithms. This new extension allows better control over the maintenance function of an industrial plant in the medium-term with a yearly horizon taken over monthly intervals which allows the measurement of the indicators of strategic productive areas and the discovery of hidden behavior patterns in work orders. In addition, this extension enables the prediction of indicator outcomes such as overall equipment efficiency and mean time to failure.

  9. Surveying the elements of successful infrared predictive maintenance programs

    Science.gov (United States)

    Snell, John R., Jr.; Spring, Robert W.

    1991-03-01

    This paper summarizes the results of a survey of over three hundred maintenance personnel who use imaging equipment within their company or organization. All had previously participated in one or more of our training programs. The companies took in a broad range of industry, including, among other, power generation, pulp and paper, metals, mining, petrochemical, automotive and general manufacturing. The organizations were mainly quite large, either commercial or public, and included governmental agencies, military, colleges and universities, municipalities, and utilities. Although we had a very tight time line for the survey, we were pleased to have a 15% response rate. The results show that some of the causes of success and failure in infrared programs are not unlike those associated with any type of program in an organizational structure, i.e. the need for accurate and timely communications; justification requirements; etc. Another set of problems was shared more closely with other startup maintenance technologies (for example, vibration monitoring), such as the need for trending data; providing appropriate technical training; achieving reproducible results; etc. Finally, some of the driving mechanisms are more specific to this technology, such as re-designing equipment so that it can be thermally inspected; establishing effective documentation strategies; etc.

  10. Intelligent Assistants for Distributed Knowledge Acquisition, Integration, Validation, and Maintenance

    National Research Council Canada - National Science Library

    Tecuci, Gheorghe; Boicu, Mihai

    2008-01-01

    This research has developed an integrated set of tools, called Disciple 2008 learning agent shell, for continuous acquisition of knowledge directly from subject matter experts, and for the integration...

  11. Predictive factors for relapse in patients on buprenorphine maintenance.

    Science.gov (United States)

    Ferri, Michael; Finlayson, Alistair J Reid; Wang, Li; Martin, Peter R

    2014-01-01

    Despite the dramatic increase in the use of buprenorphine for the treatment of opioid dependence, clinical outcomes of this treatment approach continue to need evaluation. This study examines factors associated with relapse and retention during buprenorphine treatment in a sample of opioid dependent outpatients. In a retrospective chart review of 62 patients with opioid dependence, relapse was determined by self-report, urine toxicology screens, and by checking the state controlled substance monitoring database. Data was analyzed using two-way tests of association and logistic regression. Patients with comorbid anxiety disorders, active benzodiazepine use (contrary to clinic policy), or active alcohol abuse, were significantly more likely to relapse. Patients who relapsed were also more likely to be on a higher buprenorphine maintenance dose. This study identifies relapse risk factors during buprenorphine treatment for opioid dependence. Future research is needed to determine whether modifying these factors may lead to improved treatment outcomes. © American Academy of Addiction Psychiatry.

  12. The application and practice of predictive maintenance at CANDU equipment management

    International Nuclear Information System (INIS)

    Yu Guangting

    2014-01-01

    The equipment in Qinshan CANDU unit is characterized by large number and complex structure. Some equipment failure has no relation with the operation time, it is impossible to avoid the failure of these equipment only by periodical maintenance. To improve the equipment reliability, increase the equipment usability and decrease the maintenance cost, for important equipment related to nuclear safety and generating electricity, it is required to perform condition monitoring and the predictive maintenance (PdM). According to different characteristics of equipment, it is required to use suitable equipment condition monitoring method, content and frequency. In this way, some potential equipment failure can be found, preventive maintenance can be arranged in advance, and equipment maintenance management can be optimized. (author)

  13. HIV integration sites and implications for maintenance of the reservoir.

    Science.gov (United States)

    Symons, Jori; Cameron, Paul U; Lewin, Sharon R

    2018-03-01

    To provide an overview of recent research of how HIV integration relates to productive and latent infection and implications for cure strategies. How and where HIV integrates provides new insights into how HIV persists on antiretroviral therapy (ART). Clonal expansion of infected cells with the same integration site demonstrates that T-cell proliferation is an important factor in HIV persistence, however, the driver of proliferation remains unclear. Clones with identical integration sites harbouring defective provirus can accumulate in HIV-infected individuals on ART and defective proviruses can express RNA and produce protein. HIV integration sites differ in clonally expanded and nonexpanded cells and in latently and productively infected cells and this influences basal and inducible transcription. There is a growing number of cellular proteins that can alter the pattern of integration to favour latency. Understanding these pathways may identify new interventions to eliminate latently infected cells. Using advances in analysing HIV integration sites, T-cell proliferation of latently infected cells is thought to play a major role in HIV persistence. Clonal expansion has been demonstrated with both defective and intact viruses. Production of viral RNA and protein from defective viruses may play a role in driving chronic immune activation. The site of integration may determine the likelihood of proliferation and the degree of basal and induced transcription. Finally, host factors and gene expression at the time of infection may determine the integration site. Together these new insights may lead to novel approaches to elimination of latently infected cells.

  14. Predicting Use and Maintenance of Use of Substances in Scottish Adolescents.

    Science.gov (United States)

    Karatzias, A.; Power, K. G.; Swanson, V.

    2001-01-01

    Studied the roles of demographic, school, nonschool, and personality factors in predicting the use of tobacco, alcohol, and illicit drugs and maintenance of this use. Findings for 425 Scottish secondary school students show different predictive factors. Discusses implications of the findings for decreasing the prevalence of substance use. (SLD)

  15. Nuclear power plant maintenance personnel reliability prediction (NPP/MPRP) effort at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Knee, H.E.; Haas, P.M.; Siegel, A.I.

    1981-01-01

    Human errors committed during maintenance activities are potentially a major contribution to the overall risk associated with the operation of a nuclear power plant (NPP). An NRC-sponsored program at Oak Ridge National Laboratory is attempting to develop a quantitative predictive technique to evaluate the contribution of maintenance errors to the overall NPP risk. The current work includes a survey of the requirements of potential users to ascertain the need for and content of the proposed quantitative model, plus an initial job/task analysis to determine the scope and applicability of various maintenance tasks. In addition, existing human reliability prediction models are being reviewed and assessed with respect to their applicability to NPP maintenance tasks. This paper discusses the status of the program and summarizes the results to date

  16. An integrated production, inventory and preventive maintenance model for a multi-product production system

    International Nuclear Information System (INIS)

    Liu, Xuejuan; Wang, Wenbin; Peng, Rui

    2015-01-01

    This paper considers a production system that can produce multiple products alternately. Products go through the system in a sequence and a complete run of all products forms a production cycle. An integrated production, inventory and preventive maintenance model is constructed, which is characterized by the delay-time concept. Two different situations are studied based on whether the unqualified products and downtime caused by the failures of the system, set-up and preventive maintenance can be ignored or not. Three cases are considered for each situation, depending on the position of the preventive maintenance epochs: the first case, where preventive maintenance is carried out at the end of each production cycle; the second case, where preventive maintenance is carried out at each set-up time of the products; and the third case, where preventive maintenance is carried out at some set-up times only, since it may not always be optimal to carry out preventive maintenance at the end of the production cycle or at each set-up time. The modeling objectives are to find the optimal number of production cycles per year and the optimal position of preventive maintenance that will maximize the expected profit per unit time. Numerical examples, using real data, are presented to illustrate the model. - Highlights: • We propose an integrated economic production quantity and preventive maintenance model. • The situation that multiple products are produced on the same system alternately is studied. • Two situations are studied based on whether the downtime and the product quality can be ignored or not. • We use enumeration method and analytical method to select the optimal preventive maintenance policy, respectively. • We use the delay-time concept to model the preventive maintenance policy

  17. 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

  18. A Markov deterioration model for predicting recurrent maintenance ...

    African Journals Online (AJOL)

    The parameters of the Markov chain model for predicting the condition of the road at a design · period for· the flexible pavement failures of wheel track rutting, cracks and pot holes were developed for the Niger State· road network . in Nigeria. Twelve sampled candidate roads were each subjected to standard inventory, traffic ...

  19. A framework to practical predictive maintenance modeling for multi-state systems

    International Nuclear Information System (INIS)

    Cher Ming Tan; Raghavan, Nagarajan

    2008-01-01

    A simple practical framework for predictive maintenance (PdM)-based scheduling of multi-state systems (MSS) is developed. The maintenance schedules are derived from a system-perspective using the failure times of the overall system as estimated from its performance degradation trends. The system analyzed in this work is a flow transmission water pipe system. The various factors influencing PdM-based scheduling are identified and their impact on the system reliability and performance are quantitatively studied. The estimated times to replacement of the MSS may also be derived from the developed model. The results of the model simulation demonstrate the significant impact of maintenance quality and the criteria for the call for maintenance (user demand) on the system reliability and mean performance characteristics. A slight improvement in maintenance quality is found to postpone the system replacement time by manifold. The consistency in the quality of maintenance work with minimal variance is also identified as a very important factor that enhances the system's future operational and downtime event predictability. The studies also reveal that in order to reduce the frequency of maintenance actions, it is necessary to lower the minimum user demand from the system if possible, ensuring at the same time that the system still performs its intended function effectively. The model proposed can be utilized to implement a PdM program in the industry with a few modifications to suit the individual industrial systems' needs

  20. Predictive maintenance and inspection through airborne ultrasound technology

    Energy Technology Data Exchange (ETDEWEB)

    Bandes, A [UE Systems, Inc., Elmsford, NY (United States)

    1998-12-31

    Airborne ultrasound can be considered an ideal integrating technology in that these instruments can stand alone to detect a variety of potential problems or they can be used to support vibration and infrared inspection programs. Usually portable, these instruments detect leaks in both pressurized gas systems or vacuum systems and related equipment such as tanks, pipes, heat exchangers, valves and steam traps. Additional applications include inspection of high voltage apparatus for corona, arcing and tracking. They are used to trend bearing failure as well as to detect conditions such as lack of lubrication and rubbing. A brief overview of the technology, its applications and suggested inspection techniques are explained. (orig.) 2 refs.

  1. Predictive maintenance and inspection through airborne ultrasound technology

    Energy Technology Data Exchange (ETDEWEB)

    Bandes, A. [UE Systems, Inc., Elmsford, NY (United States)

    1997-12-31

    Airborne ultrasound can be considered an ideal integrating technology in that these instruments can stand alone to detect a variety of potential problems or they can be used to support vibration and infrared inspection programs. Usually portable, these instruments detect leaks in both pressurized gas systems or vacuum systems and related equipment such as tanks, pipes, heat exchangers, valves and steam traps. Additional applications include inspection of high voltage apparatus for corona, arcing and tracking. They are used to trend bearing failure as well as to detect conditions such as lack of lubrication and rubbing. A brief overview of the technology, its applications and suggested inspection techniques are explained. (orig.) 2 refs.

  2. Weight Suppression Predicts Maintenance and Onset of Bulimic Syndromes at 10-Year Follow-up

    Science.gov (United States)

    Keel, Pamela K.; Heatherton, Todd F.

    2010-01-01

    Conflicting results have emerged regarding the prognostic significance of weight suppression for maintenance of bulimic symptoms. This study examined whether the magnitude of weight suppression would predict bulimic syndrome maintenance and onset in college-based samples of men (n=369) and women (n=968) at 10-year follow-up. Data come from a longitudinal study of body weight and disordered eating with high retention (80%). Among those with a bulimic syndrome at baseline, greater weight suppression significantly predicted maintenance of the syndrome, and, among those without a bulimic syndrome at baseline, greater weight suppression predicted onset of a bulimic syndrome at 10-year follow-up in multivariate models that included baseline body mass index, diet frequency, and weight perception. Future research should address mechanisms that could account for the effects of weight suppression over a long duration of follow-up. PMID:20455599

  3. Application of Dr. Mainte, integrated simulator of maintenance optimization, to LWRs

    International Nuclear Information System (INIS)

    Isobe, Yoshihiro; Sagisaka, Mitsuyuki; Etoh, Junji; Matsunaga, Takashi; Kosaka, Toru; Matsumoto, Satoshi; Yoshimura, Shinobu

    2015-01-01

    Dr. Mainte, an integrated simulator for maintenance optimization of LWRs (Light Water Reactors) is based on PFM (Probabilistic Fracture Mechanics) analyses. The concept of the simulator is to provide a decision-making system to optimize maintenance activities for typical components and piping systems in nuclear power plants totally and quantitatively in terms of safety, availability, economic rationality, environmental impact and social acceptance. For the further improvement of the safety and availability of nuclear power plants, the effect of human error and its reduction on the optimization of maintenance activities have been studied. In addition, an approach of reducing human error is proposed. (author)

  4. Advanced remote handling for future applications: The advanced integrated maintenance system

    International Nuclear Information System (INIS)

    Herndon, J.N.; Kring, C.T.; Rowe, J.C.

    1986-01-01

    The Consolidated Fuel Reprocessing Program at Oak Ridge National Laboratory has been developing advanced techniques for remote maintenance of future US fuel reprocessing plants. The developed technology has a wide spectrum of application for other hazardous environments. These efforts are based on the application of teleoperated, force-reflecting servomanipulators for dexterous remote handling with television viewing for large-volume hazardous applications. These developments fully address the nonrepetitive nature of remote maintenance in the unstructured environments encountered in fuel reprocessing. This paper covers the primary emphasis in the present program; the design, fabrication, installation, and operation of a prototype remote handling system for reprocessing applications, the Advanced Integrated Maintenance System

  5. Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool.

    Science.gov (United States)

    Saffian, Shamin M; Duffull, Stephen B; Roberts, Rebecca L; Tait, Robert C; Black, Leanne; Lund, Kirstin A; Thomson, Alison H; Wright, Daniel F B

    2016-12-01

    A previously established Bayesian dosing tool for warfarin was found to produce biased maintenance dose predictions. In this study, we aimed (1) to determine whether the biased warfarin dose predictions previously observed could be replicated in a new cohort of patients from 2 different clinical settings, (2) to explore the influence of CYP2C9 and VKORC1 genotype on predictive performance of the Bayesian dosing tool, and (3) to determine whether the previous population used to develop the kinetic-pharmacodynamic model underpinning the Bayesian dosing tool was sufficiently different from the test (posterior) population to account for the biased dose predictions. The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values. The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations. Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.

  6. Integrity Checking and Maintenance with Active Rules in XML Databases

    DEFF Research Database (Denmark)

    Christiansen, Henning; Rekouts, Maria

    2007-01-01

    While specification languages for integrity constraints for XML data have been considered in the literature, actual technologies and methodologies for checking and maintaining integrity are still in their infancy. Triggers, or active rules, which are widely used in previous technologies for the p...... updates, the method indicates trigger conditions and correctness criteria to be met by the trigger code supplied by a developer or possibly automatic methods. We show examples developed in the Sedna XML database system which provides a running implementation of XML triggers....

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

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

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

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

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

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

  9. 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.

  10. Machine and lubricant condition monitoring for extended equipment lifetimes and predictive maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Lukas, M; Anderson, D P [Spectro Incorporated, Littleton, Massachusetts (United States)

    1998-12-31

    Predictive maintenance has gained wide acceptance as a cost cutting strategy in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In today`s modern power generation, manufacturing, refinery, transportation, mining, and military operations, the cost of equipment maintenance, service, and lubricants are ever increasing. Parts, labor, equipment downtime and lubricant prices and disposal costs are a primary concern in a well run maintenance management program. Machine condition monitoring based on oil analysis has become a prerequisite in most maintenance programs. Few operations can afford not to implement a program if they wish to remain competitive, and in some cases, profitable. This presentation describes a comprehensive Machine Condition Monitoring Program based on oil analysis. Actual operational condition monitoring programs will be used to review basic components and analytical requirements. Case histories will be cited as examples of cost savings, reduced equipment downtime and increased efficiencies of maintenance programs through a well managed oil analysis program. (orig.)

  11. Machine and lubricant condition monitoring for extended equipment lifetimes and predictive maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Lukas, M.; Anderson, D.P. [Spectro Incorporated, Littleton, Massachusetts (United States)

    1997-12-31

    Predictive maintenance has gained wide acceptance as a cost cutting strategy in modern industry. Condition monitoring by lubricant analysis is one of the basic tools of a predictive maintenance program along with vibration monitoring, performance monitoring and thermography. In today`s modern power generation, manufacturing, refinery, transportation, mining, and military operations, the cost of equipment maintenance, service, and lubricants are ever increasing. Parts, labor, equipment downtime and lubricant prices and disposal costs are a primary concern in a well run maintenance management program. Machine condition monitoring based on oil analysis has become a prerequisite in most maintenance programs. Few operations can afford not to implement a program if they wish to remain competitive, and in some cases, profitable. This presentation describes a comprehensive Machine Condition Monitoring Program based on oil analysis. Actual operational condition monitoring programs will be used to review basic components and analytical requirements. Case histories will be cited as examples of cost savings, reduced equipment downtime and increased efficiencies of maintenance programs through a well managed oil analysis program. (orig.)

  12. Integrated management of information inside maintenance processes. From the building registry to BIM systems

    Directory of Open Access Journals (Sweden)

    Cinzia Talamo

    2014-10-01

    Full Text Available The paper presents objec- tives, methods and results of two researches dealing with the improvement of integrated information management within maintenance processes. Focusing on information needs regarding the last phases of the building process, the two researches draft approaches characterizing a path of progressive improve- ment of strategies for integration: from a building registry, unique for the whole construction process, to an integrated management of the building process with the support of BIM systems.

  13. Advanced safety management systems for maintenance of pipeline integrity

    International Nuclear Information System (INIS)

    Borysiewicz, M.; Potempski, S.

    2005-01-01

    One of the duties of the pipeline's operator is to introduce means for protection of human safety and the environment. This should be reflected in preparation of comprehensive Risk Management System with its key element Activity Programme for Management of Pipeline Integrity. In the paper such programme has been described taking into account law regulations and practical activities undertaken in technologically advanced countries (mainly USA and EU), where such solutions are implemented in routine operations. Possible solutions of realization of all elements of the programme, as well as information on utilization of computer aided support have been also included. (authors)

  14. GAPIT: genome association and prediction integrated tool.

    Science.gov (United States)

    Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

    2012-09-15

    Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

  15. On line performance monitoring for predictive maintenance [Paper No.: VIA - 2

    International Nuclear Information System (INIS)

    Gupta, R.K.; Chandra, Rajesh

    1981-01-01

    There will always be progressive deterioration in the performance of dynamic equipment due to normal inevitable wear, malfunctions, failures and other reasons. In most cases it is possible to monitor some parameters of a system which would get progressively affected with the deterioration in the health of the system. By on-line monitoring of such predetermined parameters, compared with preset base data generated for a healthy system earlier, would prove very helpful in avoiding breakdowns and in proper planning of preventive and predictive maintenance. With increasing use of on-line computerised controls the generation of design base data and also the in-built self checking feature of monitoring the equipment health can be achieved by incorporating suitable software. This type of system will be helpful in: (a) predicting the life of component, (b) prewarning the operator about impending malfunctions, (c) establishing a maintenance schedule and spare inventory, and (d) analysing the failures. This type of centralised predictive maintenance is increasingly becoming important where: (a) the number of equipments are large, (b) the operation of equipment is critical from safety criteria, and (c) the minimum safety margin in the performance of the component is to be maintained. Keeping this in mind, the Fuel Handling System of Narora Atomic Power Project and the future power plants having computerised controls will have facility for on-line performance monitoring for predictive maintenance. The paper also describes methodology of the technique in detail, with a few representative cases. (author)

  16. 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.

  17. Predicting cycle time distributions for integrated processing workstations : an aggregate modeling approach

    NARCIS (Netherlands)

    Veeger, C.P.L.; Etman, L.F.P.; Lefeber, A.A.J.; Adan, I.J.B.F.; Herk, van J.; Rooda, J.E.

    2011-01-01

    To predict cycle time distributions of integrated processing workstations, detailed simulation models are almost exclusively used; these models require considerable development and maintenance effort. As an alternative, we propose an aggregate model that is a lumped-parameter representation of the

  18. Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities

    Directory of Open Access Journals (Sweden)

    Peyman Babashamsi

    2016-03-01

    Full Text Available Maintenance activities and pavement rehabilitation require the allocation of massive finances. Yet due to budget shortfalls, stakeholders and decision-makers must prioritize projects in maintenance and rehabilitation. This article addresses the prioritization of pavement maintenance alternatives by integrating the fuzzy analytic hierarchy process (AHP with the VIKOR method (which stands for ‘VlseKriterijumska Optimizacija I Kompromisno Resenje,’ meaning multi-criteria optimization and compromise solution for the process of multi-criteria decision analysis (MCDA by considering various pavement network indices. The indices selected include the pavement condition index (PCI, traffic congestion, pavement width, improvement and maintenance costs, and the time required to operate. In order to determine the weights of the indices, the fuzzy AHP is used. Subsequently, the alternatives’ priorities are ranked according to the indices weighted with the VIKOR model. The choice of these two independent methods was motivated by the fact that integrating fuzzy AHP with the VIKOR model can assist decision makers with solving MCDA problems. The case study was conducted on a pavement network within the same particular region in Tehran; three main streets were chosen that have an empirically higher maintenance demand. The most significant factors were evaluated and the project with the highest priority was selected for urgent maintenance. By comparing the index values of the alternative priorities, Delavaran Blvd. was revealed to have higher priority over the other streets in terms of maintenance and rehabilitation activities. Keywords: Maintenance and rehabilitation prioritization, Fuzzy analysis hierarchy process, VIKOR model, Pavement condition index, Multi-criteria decision analysis

  19. CD4 T cell autophagy is integral to memory maintenance.

    Science.gov (United States)

    Murera, Diane; Arbogast, Florent; Arnold, Johan; Bouis, Delphine; Muller, Sylviane; Gros, Frédéric

    2018-04-13

    Studies of mice deficient for autophagy in T cells since thymic development, concluded that autophagy is integral to mature T cell homeostasis. Basal survival and functional impairments in vivo, limited the use of these models to delineate the role of autophagy during the immune response. We generated Atg5 f/f distal Lck (dLck)-cre mice, with deletion of autophagy only at a mature stage. In this model, autophagy deficiency impacts CD8 + T cell survival but has no influence on CD4 + T cell number and short-term activation. Moreover, autophagy in T cells is dispensable during early humoral response but critical for long-term antibody production. Autophagy in CD4 + T cells is required to transfer humoral memory as shown by injection of antigen-experienced cells in naive mice. We also observed a selection of autophagy-competent cells in the CD4 + T cell memory compartment. We performed in vitro differentiation of memory CD4 + T cells, to better characterize autophagy-deficient memory cells. We identified mitochondrial and lipid load defects in differentiated memory CD4 + T cells, together with a compromised survival, without any collapse of energy production. We then propose that memory CD4 + T cells rely on autophagy for their survival to regulate toxic effects of mitochondrial activity and lipid overload.

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

    DEFF Research Database (Denmark)

    Asgarpour, Masoud

    2017-01-01

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

  1. Integrated service engineers and spare parts planning in the maintenance logistics

    NARCIS (Netherlands)

    Al Hanbali, Ahmad; Zijm, Willem H.M.

    2016-01-01

    We analyze the integrated tactical capacity planning of spare parts supply and workforce allocation in maintenance logistics of advanced equipment. The equipment time-to-failure, spare parts replenishment time, and equipment repair time are random and independent of each other.

  2. Analogical reasoning in working memory: resources shared among relational integration, interference resolution, and maintenance.

    Science.gov (United States)

    Cho, Soohyun; Holyoak, Keith J; Cannon, Tyrone D

    2007-09-01

    We report a series of experiments using a pictorial analogy task designed to manipulate relational integration, interference resolution, and active maintenance simultaneously. The difficulty of the problems was varied in terms of the number of relations to be integrated, the need for interference resolution, and the duration of maintenance required to correctly solve the analogy. The participants showed decreases in performance when integrating multiple relations, as compared with a single relation, and when interference resolution was required in solving the analogy. When the participants were required to integrate multiple relations while simultaneously engaged in interference resolution, performance was worse, as compared with problems that incorporated either of these features alone. Maintenance of information across delays in the range of 1-4.5 sec led to greater decrements in visual memory, as compared with analogical reasoning. Misleading information caused interference when it had been necessarily attended to and maintained in working memory and, hence, had to be actively suppressed. However, sources of conflict within information that had not been attended to or encoded into working memory did not interfere with the ongoing controlled information processing required for relational integration. The findings provide evidence that relational integration and interference resolution depend on shared cognitive resources in working memory during analogical reasoning.

  3. Prediction accident triangle in maintenance of underground mine facilities using Poisson distribution analysis

    Science.gov (United States)

    Khuluqi, M. H.; Prapdito, R. R.; Sambodo, F. P.

    2018-04-01

    In Indonesia, mining is categorized as a hazardous industry. In recent years, a dramatic increase of mining equipment and technological complexities had resulted in higher maintenance expectations that accompanied by the changes in the working conditions, especially on safety. Ensuring safety during the process of conducting maintenance works in underground mine is important as an integral part of accident prevention programs. Accident triangle has provided a support to safety practitioner to draw a road map in preventing accidents. Poisson distribution is appropriate for the analysis of accidents at a specific site in a given time period. Based on the analysis of accident statistics in the underground mine maintenance of PT. Freeport Indonesia from 2011 through 2016, it is found that 12 minor accidents for 1 major accident and 66 equipment damages for 1 major accident as a new value of accident triangle. The result can be used for the future need for improving the accident prevention programs.

  4. Integrated Program of Experimental Diagnostics at the NNSS: An Integrated, Prioritized Work Plan for Diagnostic Development and Maintenance and Supporting Capability

    International Nuclear Information System (INIS)

    2010-01-01

    This Integrated Program of Experimental Diagnostics at the NNSS is an integrated prioritized work plan for the Nevada National Security Site (NNSS), formerly the Nevada Test Site (NTS), program that is independent of individual National Security Enterprise Laboratories (Labs) requests or specific Subprograms being supported. This prioritized work plan is influenced by national priorities presented in the Predictive Capability Framework (PCF) and other strategy documents (Primary and Secondary Assessment Technologies Plans and the Plutonium Experiments Plan). This document satisfies completion criteria for FY 2010 MRT milestone No.3496: Document an integrated, prioritized work plan for diagnostic development, maintenance, and supporting capability. This document is an update of the 3-year NNSS plan written a year ago, September 21, 2009, to define and understand Lab requests for diagnostic implementation. This plan is consistent with Lab interpretations of the PCF, Primary Assessment Technologies, and Plutonium Experiment plans.

  5. Predictive maintenance technology development at G.A. Siwabessy multipurpose reactor

    Energy Technology Data Exchange (ETDEWEB)

    Jupiter Sitorus Pane; Imron, M.; Sapto Hartoko; Sentot Alibasya Harahap [Multipurpose Research Reactor G.A. Siwabessy, National Nuclear Energy Agency (Indonesia)

    1999-10-01

    Safe operation of reactor is certainly influenced by condition of system and component equipped to the reactor's system. In order to maintain the condition of that systems and components, RSG-GAS has arranged maintenance program with time-basis. All 6 (six) groups of reactor systems are maintained within interval of weekly, monthly, three monthly, six-monthly, yearly, five-yearly appropriately. The experience showed that event though the maintenance was performed persistently, the condition of system and component are still not able to determine exactly. The possibility of accidental failure is open since the failure factor are varied and complicated. In order to limit an uncertainty of the component condition a based maintenance shall be introduced. An infrared investigation and manual vibration analysis had been used to diagnose the condition of some RSG-GAS' components. In addition, other alternative technology for predictive maintenance was developed. It is started by computerizing the database maintenance and doing historical review for its aging management, and developing data acquisition and processing equipment using Lab View computer program for collecting and processing signal data from dynamics system. This paper describes briefly the status of those development results. (author)

  6. Predictive maintenance technology development at G.A. Siwabessy multipurpose reactor

    International Nuclear Information System (INIS)

    Jupiter Sitorus Pane; Imron, M.; Sapto Hartoko; Sentot Alibasya Harahap

    1999-01-01

    Safe operation of reactor is certainly influenced by condition of system and component equipped to the reactor's system. In order to maintain the condition of that systems and components, RSG-GAS has arranged maintenance program with time-basis. All 6 (six) groups of reactor systems are maintained within interval of weekly, monthly, three monthly, six-monthly, yearly, five-yearly appropriately. The experience showed that event though the maintenance was performed persistently, the condition of system and component are still not able to determine exactly. The possibility of accidental failure is open since the failure factor are varied and complicated. In order to limit an uncertainty of the component condition a based maintenance shall be introduced. An infrared investigation and manual vibration analysis had been used to diagnose the condition of some RSG-GAS' components. In addition, other alternative technology for predictive maintenance was developed. It is started by computerizing the database maintenance and doing historical review for its aging management, and developing data acquisition and processing equipment using Lab View computer program for collecting and processing signal data from dynamics system. This paper describes briefly the status of those development results. (author)

  7. Molecular constraints on synaptic tagging and maintenance of long-term potentiation: a predictive model.

    Directory of Open Access Journals (Sweden)

    Paul Smolen

    Full Text Available Protein synthesis-dependent, late long-term potentiation (LTP and depression (LTD at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of protein kinase M ζ (PKMζ is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC and cross capture hypotheses. Only synapses that have been "tagged" by a stimulus sufficient for LTP and learning can "capture" PKMζ. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKMζ, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKMζ. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKMζ enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKMζ. Second, cross capture requires the induction of LTD to induce dendritic PKMζ synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKMζ inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.

  8. Molecular constraints on synaptic tagging and maintenance of long-term potentiation: a predictive model.

    Science.gov (United States)

    Smolen, Paul; Baxter, Douglas A; Byrne, John H

    2012-01-01

    Protein synthesis-dependent, late long-term potentiation (LTP) and depression (LTD) at glutamatergic hippocampal synapses are well characterized examples of long-term synaptic plasticity. Persistent increased activity of protein kinase M ζ (PKMζ) is thought essential for maintaining LTP. Additional spatial and temporal features that govern LTP and LTD induction are embodied in the synaptic tagging and capture (STC) and cross capture hypotheses. Only synapses that have been "tagged" by a stimulus sufficient for LTP and learning can "capture" PKMζ. A model was developed to simulate the dynamics of key molecules required for LTP and LTD. The model concisely represents relationships between tagging, capture, LTD, and LTP maintenance. The model successfully simulated LTP maintained by persistent synaptic PKMζ, STC, LTD, and cross capture, and makes testable predictions concerning the dynamics of PKMζ. The maintenance of LTP, and consequently of at least some forms of long-term memory, is predicted to require continual positive feedback in which PKMζ enhances its own synthesis only at potentiated synapses. This feedback underlies bistability in the activity of PKMζ. Second, cross capture requires the induction of LTD to induce dendritic PKMζ synthesis, although this may require tagging of a nearby synapse for LTP. The model also simulates the effects of PKMζ inhibition, and makes additional predictions for the dynamics of CaM kinases. Experiments testing the above predictions would significantly advance the understanding of memory maintenance.

  9. Integrating Preventive Maintenance Scheduling As Probability Machine Failure And Batch Production Scheduling

    Directory of Open Access Journals (Sweden)

    Zahedi Zahedi

    2016-06-01

    Full Text Available This paper discusses integrated model of batch production scheduling and machine maintenance scheduling. Batch production scheduling uses minimize total actual flow time criteria and machine maintenance scheduling uses the probability of machine failure based on Weibull distribution. The model assumed no nonconforming parts in a planning horizon. The model shows an increase in the number of the batch (length of production run up to a certain limit will minimize the total actual flow time. Meanwhile, an increase in the length of production run will implicate an increase in the number of PM. An example was given to show how the model and algorithm work.

  10. Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

    Directory of Open Access Journals (Sweden)

    Amber Watts PhD

    2015-08-01

    Full Text Available Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD, we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status adjusting for age, sex, education, and self-reported walking. Results : Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion : Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function.

  11. Low-complexity Behavioral Model for Predictive Maintenance of Railway Turnouts

    DEFF Research Database (Denmark)

    Barkhordari, Pegah; Galeazzi, Roberto; Tejada, Alejandro de Miguel

    2017-01-01

    together with the Eigensystem Realization Algorithm – a type of subspace identification – to identify a fourth order model of the infrastructure. The robustness and predictive capability of the low-complexity behavioral model to reproduce track responses under different types of train excitations have been......Maintenance of railway infrastructures represents a major cost driver for any infrastructure manager since reliability and dependability must be guaranteed at all times. Implementation of predictive maintenance policies relies on the availability of condition monitoring systems able to assess...... the infrastructure health state. The core of any condition monitoring system is the a-priori knowledge about the process to be monitored, in the form of either mathematical models of different complexity or signal features characterizing the healthy/faulty behavior. This study investigates the identification...

  12. Integrating Safety in the Aviation System: Interdepartmental Training for Pilots and Maintenance Technicians

    Science.gov (United States)

    Mattson, Marifran; Petrin, Donald A.; Young, John P.

    2001-01-01

    The study of human factors has had a decisive impact on the aviation industry. However, the entire aviation system often is not considered in researching, training, and evaluating human factors issues especially with regard to safety. In both conceptual and practical terms, we argue for the proactive management of human error from both an individual and organizational systems perspective. The results of a multidisciplinary research project incorporating survey data from professional pilots and maintenance technicians and an exploratory study integrating students from relevant disciplines are reported. Survey findings suggest that latent safety errors may occur during the maintenance discrepancy reporting process because pilots and maintenance technicians do not effectively interact with one another. The importance of interdepartmental or cross-disciplinary training for decreasing these errors and increasing safety is discussed as a primary implication.

  13. Failure time series prediction in industrial maintenance using neural networks; Previsao de series temporais de falhas em manutencao industrial usando redes neurais

    Energy Technology Data Exchange (ETDEWEB)

    Torres Junior, Rubiao G.; Machado, Maria Augusta S. [Instituto Brasileiro de Mercado de Capitais (IBMEC), Rio de Janeiro, RJ (Brazil); Souza, Reinaldo C. [Pontificia Univ. Catolica do Rio de Janeiro, RJ (Brazil)

    2005-07-01

    The objective of this work is the application of two failure prediction models in industrial maintenance with the use of Artificial Neural Networks (ANN). A characteristic of the modern industrial environment is a strong competition which leads companies to search for costs minimization methods. Thus, dada gathering and maintenance dada treatment becomes extremely important in this scenario for it aims the equipment and plant systems real repair necessity. Therefore, the objective becomes the widening of the system's full activity in a continuous manner, in the required period, without problems in their integrating parts. A daily time series is modeled based on maintenance interventions pauses dada from a five years period derived form many productive systems in the finalization areas of PETROFLEX Ind. and Com. S.A. Thus, the purpose is to introduce models based on neural networks and verify its system's pauses prediction capacity, so as to intervene with adequate timing before the system fails, extend the operational period and consequently increase its availability. The results obtained in this work demonstrate the employment of Neural Networks in the prediction of pauses in PETROFLEX industrial area maintenance. The ANN's prediction capacity in a group of dada with strong non-linear component where other statistical techniques have shown little efficient has also been confirmed. Discover neural models to predict failure systems time series has enable a breakthrough in the research field, especially due to the market demand. It's no doubt a technique that will evolve in the industrial maintenance area financing important managing decision. Prediction techniques, such as the ones illustrated in this study, work side by side maintenance planning and if carefully implemented and followed up can in the medium run supply a substantial increase in the available operational hours. (author)

  14. Two Different Maintenance Strategies in the Hospital Environment: Preventive Maintenance for Older Technology Devices and Predictive Maintenance for Newer High-Tech Devices

    OpenAIRE

    Sezdi, Mana

    2016-01-01

    A maintenance program generated through the consideration of characteristics and failures of medical equipment is an important component of technology management. However, older technology devices and newer high-tech devices cannot be efficiently managed using the same strategies because of their different characteristics. This study aimed to generate a maintenance program comprising two different strategies to increase the efficiency of device management: preventive maintenance for older tec...

  15. Spectrotemporal dynamics of the EEG during working memory encoding and maintenance predicts individual behavioral capacity.

    Science.gov (United States)

    Bashivan, Pouya; Bidelman, Gavin M; Yeasin, Mohammed

    2014-12-01

    We investigated the effect of memory load on encoding and maintenance of information in working memory. Electroencephalography (EEG) signals were recorded while participants performed a modified Sternberg visual memory task. Independent component analysis (ICA) was used to factorise the EEG signals into distinct temporal activations to perform spectrotemporal analysis and localisation of source activities. We found 'encoding' and 'maintenance' operations were correlated with negative and positive changes in α-band power, respectively. Transient activities were observed during encoding of information in the bilateral cuneus, precuneus, inferior parietal gyrus and fusiform gyrus, and a sustained activity in the inferior frontal gyrus. Strong correlations were also observed between changes in α-power and behavioral performance during both encoding and maintenance. Furthermore, it was also found that individuals with higher working memory capacity experienced stronger neural oscillatory responses during the encoding of visual objects into working memory. Our results suggest an interplay between two distinct neural pathways and different spatiotemporal operations during the encoding and maintenance of information which predict individual differences in working memory capacity observed at the behavioral level. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  16. Impact logistics-technique study of generating predictive maintenance in SME sin Milagro, Ecuador

    Directory of Open Access Journals (Sweden)

    Erik Rolando Cedeño Anchundia

    2016-06-01

    Full Text Available This article is to discern the organizational culture regarding the acceptance of monitoring techniques and predictive inspections that help reduce the problems arising in the infrastructure of production processes within an industrial plant and thus optimize downtime that they occur due to ignorance or little attention and in some cases due to lack of awareness of operators or direct users of these computers. SMEs currently are optimizing their processes, automating their production line which implies that there should be better controls, to be more competitive because the increase in technology, greatly improves productivity. Before the technology boom happening in terms of machinery and processes, corrective measures were used to eliminate problems and these generated high rates in terms of costs for equipment maintenance, in the XXI century predictive maintenance techniques, consisting develops diagnose and maintain installed both in the electrical part and mechanical non-stop operational teams, allowing the reduction of lost production time and costs, costs of obtaining the most competitive end products in the market infrastructure. Also analyze the type of maintenance they currently possess SMEs in the city of Milagro-Ecuador and how it is influencing their productivity in order to develop proposals for improvements and recommendations in order to optimize their processes and increase profitability.

  17. Establishing a predictive maintenance (PdM) program at the Hanford Site

    International Nuclear Information System (INIS)

    Murray, W.A.; Winslow, R.G.

    1994-02-01

    The production reactors have been shut down for some time. But for the rest of the site, there is currently about 16,000 people engaged in a multi-billion dollar effort to safely process wastes which have been stored at the site since the 1940's. This effort also includes demolition of some older facilities and environmental restoration of much of the site. This is expected to take approximately 30 to 40 years. The concept of a site-wide predictive maintenance (PdM) program began to form in early 1993. Several informal studies showed that the stand alone predictive maintenance groups which had prevailed on site to date were less than 15% effective at trending equipment conditions and predicting failures. To improve the effectiveness of PdM within the company, an engineering analysis by Rick Winslow confirmed that utilization of software networking technology which was now available would significantly overcome many of these built in handicaps. A site-wide predictive maintenance network would make PdM technology accessible to all of the areas and facilities at the site regardless of geographical distances and company division lines. Site resident vibration experts can easily be located and provide consultations on the network. However, it was recognized that strong leadership and management skills would be required within each of the two organizations for effective implementation. To start this process, a letter of understanding and agreement between the facilities and Tank Farm divisions was drafted and endorsed by company management. The agreement assigned the primary responsibility of acquiring the network software and licensee to the Tank Farms division. The acquisition and installation of the network server would be the responsibility of the facilities division. This paper describes the rest of the network development and implementation process

  18. Integrated batch production and maintenance scheduling for multiple items processed on a deteriorating machine to minimize total production and maintenance costs with due date constraint

    Directory of Open Access Journals (Sweden)

    Zahedi Zahedi

    2016-04-01

    Full Text Available This paper discusses an integrated model of batch production and maintenance scheduling on a deteriorating machine producing multiple items to be delivered at a common due date. The model describes the trade-off between total inventory cost and maintenance cost as the increase of production run length. The production run length is a time bucket between two consecutive preventive maintenance activities. The objective function of the model is to minimize total cost consisting of in process and completed part inventory costs, setup cost, preventive and corrective maintenance costs and rework cost. The problem is to determine the optimal production run length and to schedule the batches obtained from determining the production run length in order to minimize total cost.

  19. Kalman-predictive-proportional-integral-derivative (KPPID)

    International Nuclear Information System (INIS)

    Fluerasu, A.; Sutton, M.

    2004-01-01

    With third generation synchrotron X-ray sources, it is possible to acquire detailed structural information about the system under study with time resolution orders of magnitude faster than was possible a few years ago. These advances have generated many new challenges for changing and controlling the state of the system on very short time scales, in a uniform and controlled manner. For our particular X-ray experiments on crystallization or order-disorder phase transitions in metallic alloys, we need to change the sample temperature by hundreds of degrees as fast as possible while avoiding over or under shooting. To achieve this, we designed and implemented a computer-controlled temperature tracking system which combines standard Proportional-Integral-Derivative (PID) feedback, thermal modeling and finite difference thermal calculations (feedforward), and Kalman filtering of the temperature readings in order to reduce the noise. The resulting Kalman-Predictive-Proportional-Integral-Derivative (KPPID) algorithm allows us to obtain accurate control, to minimize the response time and to avoid over/under shooting, even in systems with inherently noisy temperature readings and time delays. The KPPID temperature controller was successfully implemented at the Advanced Photon Source at Argonne National Laboratories and was used to perform coherent and time-resolved X-ray diffraction experiments.

  20. Westinghouse integrated protection system. An overview of the software design and maintenance features

    International Nuclear Information System (INIS)

    Gibson, R.J.

    1995-01-01

    The Westinghouse Integrated Protection System was designed with the goal of providing a system which can be easily verified, validated, and maintained. The software design and structure promote the ease of translation from functional requirements to applications function software while also improving the ability to verify and maintain the applications function software. The use of independent, reusable, common functions software modules focuses the design, verification, and validation of the software and reduces the likelihood of errors occurring during the application and maintenance of the software. The simple continuous loop method of operation used throughout the IPS provides a standard deterministic method of operation. The IPS design also incorporates the use of embedded self-diagnostics to perform continuous hardware oriented tests of the system and the use of an independent subsystem to automatically perform a functional test of the system. Maintenance interfaces also exist to readily identify and locate faults as well as providing other maintenance capabilities. These testing and maintenance features enhance the overall reliability and availability of the system. (orig.) (2 refs., 2 figs.)

  1. A decision-making framework to integrate maintenance contract conditions with critical spares management

    International Nuclear Information System (INIS)

    Godoy, David R.; Pascual, Rodrigo; Knights, Peter

    2014-01-01

    Maintenance outsourcing is a strategic driver for asset intensive industries pursuing to enhance supply chain performance. Spare parts management plays a relevant role in this premise since its significant impact on equipment availability, and hence on business success. Designing critical spares policies might therefore seriously affect maintenance contracts profitability, yet service receivers and external providers traditionally attempt to benefit separately. To coordinate both chain parties, we investigated whether the spare components pool should be managed in-house or contracted out. This paper provides a decision-making framework to efficiently integrate contractual conditions with critical spares stockholding. Using an imperfect maintenance strategy over a finite horizon, the scheme maximizes chain returns whilst evaluating the impact of an additional part to stock. As result, an original joint value – preventive interval and stock level – sets the optimal agreement to profitably allocate the components pool within the service contract. Subsidization bonuses on preventive interventions and pooling costs are also estimated to induce the service provider to adjust its policy when needed. The proposed contractual conditions motivate stakeholders to continuously improve maintenance performance and supply practices, thus obtaining higher joint benefits

  2. Predictive modeling for corrective maintenance of imaging devices from machine logs.

    Science.gov (United States)

    Patil, Ravindra B; Patil, Meru A; Ravi, Vidya; Naik, Sarif

    2017-07-01

    In the cost sensitive healthcare industry, an unplanned downtime of diagnostic and therapy imaging devices can be a burden on the financials of both the hospitals as well as the original equipment manufacturers (OEMs). In the current era of connectivity, it is easier to get these devices connected to a standard monitoring station. Once the system is connected, OEMs can monitor the health of these devices remotely and take corrective actions by providing preventive maintenance thereby avoiding major unplanned downtime. In this article, we present an overall methodology of predicting failure of these devices well before customer experiences it. We use data-driven approach based on machine learning to predict failures in turn resulting in reduced machine downtime, improved customer satisfaction and cost savings for the OEMs. One of the use-case of predicting component failure of PHILIPS iXR system is explained in this article.

  3. Development of standardized component\\0x2010based equipment specifications and transition plan into a predictive maintenance strategy.

    Science.gov (United States)

    2015-12-01

    This project investigated INDOT equipment records and equipment industry standards to produce standard equipment specifications : and a predictive maintenance schedule for the more than 1100 single and tandem axle trucks in use at INDOT. The research...

  4. Development of standardized component\\0x2010based equipment specifications and transition plan into a predictive maintenance strategy : final report.

    Science.gov (United States)

    2015-12-01

    This project investigated INDOT equipment records and equipment industry standards to produce standard equipment specifications : and a predictive maintenance schedule for the more than 1100 single and tandem axle trucks in use at INDOT. The research...

  5. Pigging the unpiggable: a total integrated maintenance approach of the Progreso Process Pipelines in Yucatan, Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez Graciano, Luis [PEMEX Refinacion, Mexico, MX (Mexico); Gonzalez, Oscar L. [NDT Systems and Services, Stutensee (Germany)

    2009-07-01

    Pemex Refinacion and NDT Systems and Services, executed a Total Integrated Maintenance Program of the Process Pipeline System in the Yucatan Peninsula in Mexico, in order to modernize, enhance and bring the pipeline system up to the best industry standards and ensure the integrity, reliability and safe operation of the system. This approach consisted in using multi-diameter ultrasonic inspection technology to determine the current status of the pipelines, repair every 'integrity diminishing' feature present on the system and establish a Certified Maintenance Program to ensure the future reliability and safety of the pipelines. Due to the complex nature of the pipeline construction, dated from 1984, several special modifications, integrations and solutions were necessary to improve the in line inspection survey as for all traditionally unpiggable systems. The Progreso Pipeline System consists in 3 major pipelines which transport diesel, jet fuel and gasoline respectively. The outside diameter of two pipelines varies along its length between 12 inches - 14 inches - 16 inches, making the inspection survey more difficult and particularly demanding an Inspection Tool solution. It is located on the coast of the Yucatan Peninsula, at the Mexican Caribbean, and its main purpose is to transport the product from the docked tanker ships to the Pemex Storage and Distribution Terminal. (author)

  6. Application of integrated logistic techniques to operation, maintenance and re engineering processes in Nuclear Power plants

    International Nuclear Information System (INIS)

    Santiago Diez, P.

    1997-01-01

    This paper addresses the advisability of adapting and applying management and Integrated Logistic engineering techniques to nuclear power plants instead of using more traditional maintenance management methods. It establishes a historical framework showing the origins of integrated approaches based on traditional logistic support concepts, their phases and the real results obtained in the aeronautic world where they originated. It reviews the application of integrated management philosophy, and logistic support and engineering analysis techniques regarding Availability, Reliability and Maintainability (ARM) and shows their inter dependencies in different phases of the system's life (Design, Development and Operation). It describes how these techniques are applied to nuclear power plant operation, their impact on plant availability and the optimisation of maintenance and replacement plans. The paper analyses the need for data (type and volume), which will have to be collected, and the different tools to manage such data. It examines the different CALS tools developed by EA for engineering and for logistic management. It also explains the possibility of using these tools for process and data operations through the INTERNET. It also focuses on the qualities of some simple examples of possible applications, and how they would be used in the framework of Integrated Logistic Support (ILS). (Author)

  7. Study on the methodology for predicting and preventing errors to improve reliability of maintenance task in nuclear power plant

    International Nuclear Information System (INIS)

    Hanafusa, Hidemitsu; Iwaki, Toshio; Embrey, D.

    2000-01-01

    The objective of this study was to develop and effective methodology for predicting and preventing errors in nuclear power plant maintenance tasks. A method was established by which chief maintenance personnel can predict and reduce errors when reviewing the maintenance procedures and while referring to maintenance supporting systems and methods in other industries including aviation and chemical plant industries. The method involves the following seven steps: 1. Identification of maintenance tasks. 2. Specification of important tasks affecting safety. 3. Assessment of human errors occurring during important tasks. 4. Identification of Performance Degrading Factors. 5. Dividing important tasks into sub-tasks. 6. Extraction of errors using Predictive Human Error Analysis (PHEA). 7. Development of strategies for reducing errors and for recovering from errors. By way of a trial, this method was applied to the pump maintenance procedure in nuclear power plants. This method is believed to be capable of identifying the expected errors in important tasks and supporting the development of error reduction measures. By applying this method, the number of accidents resulting form human errors during maintenance can be reduced. Moreover, the maintenance support base using computers was developed. (author)

  8. The role of romantic attraction and conflict resolution in predicting shorter and longer relationship maintenance among adolescents.

    Science.gov (United States)

    Appel, Israel; Shulman, Shmuel

    2015-04-01

    This study examined the role of romantic attraction and conflict resolution patterns in shorter and longer relationship maintenance among adolescent couples. Data were used from 55 couples aged 15-18 years. Partners completed the Romantic Attraction scale and were observed negotiating a disagreement. Three and 6 months later, they were asked to report whether they were still together. Findings indicated that partners' romantic attraction and the tendency to minimize disagreements during interaction predicted shorter relationship maintenance. In contrast, longer relationship maintenance was predicted by partners' capability to resolve conflicts constructively in a positive atmosphere. Findings are embedded and discussed within Fisher's (2004) evolutionary theory of love.

  9. Development and performance evaluation of a prototype system for prediction of the group error at the maintenance work

    International Nuclear Information System (INIS)

    Yoshino, Kenji; Hirotsu, Yuko

    2000-01-01

    In order to attain zero-izing of much more error rather than it can set to a nuclear power plant, Authors development and its system-izing of the error prediction causal model which predicts group error action at the time of maintenance work were performed. This prototype system has the following feature. (1) When a user inputs the existence and the grade of the existence of the 'feature factor of the maintenance work' as a prediction object, 'an organization and an organization factor', and a 'group PSF (Performance Shaping Factor) factor' into this system. The maintenance group error to target can be predicted through the prediction model which consists of a class of seven stages. (2) This system by utilizing the information on a prediction result database, it can use not only for prediction of a maintenance group error but for various safe activity, such as KYT (dangerous forecast training) and TBM (Tool Box Meeting). (3) This system predicts a cooperation error' at highest rate, and, subsequently predicts the detection error' at a high rate. And to the 'decision-making error', the transfer error' and the 'state cognitive error', it has the characteristic predicted at almost same rate. (4) If it has full knowledge even of the features, such as the enforcement conditions of maintenance work, and organization, even if the user has neither the knowledge about a human factor, nor experience, anyone of this system is slight about the existence, its extent, etc. of generating of a maintenance group error made difficult from the former logically and systematically easily, it can predict in business time for about 15 minutes. (author)

  10. A review of a priori regression models for warfarin maintenance dose prediction.

    Directory of Open Access Journals (Sweden)

    Ben Francis

    Full Text Available A number of a priori warfarin dosing algorithms, derived using linear regression methods, have been proposed. Although these dosing algorithms may have been validated using patients derived from the same centre, rarely have they been validated using a patient cohort recruited from another centre. In order to undertake external validation, two cohorts were utilised. One cohort formed by patients from a prospective trial and the second formed by patients in the control arm of the EU-PACT trial. Of these, 641 patients were identified as having attained stable dosing and formed the dataset used for validation. Predicted maintenance doses from six criterion fulfilling regression models were then compared to individual patient stable warfarin dose. Predictive ability was assessed with reference to several statistics including the R-square and mean absolute error. The six regression models explained different amounts of variability in the stable maintenance warfarin dose requirements of the patients in the two validation cohorts; adjusted R-squared values ranged from 24.2% to 68.6%. An overview of the summary statistics demonstrated that no one dosing algorithm could be considered optimal. The larger validation cohort from the prospective trial produced more consistent statistics across the six dosing algorithms. The study found that all the regression models performed worse in the validation cohort when compared to the derivation cohort. Further, there was little difference between regression models that contained pharmacogenetic coefficients and algorithms containing just non-pharmacogenetic coefficients. The inconsistency of results between the validation cohorts suggests that unaccounted population specific factors cause variability in dosing algorithm performance. Better methods for dosing that take into account inter- and intra-individual variability, at the initiation and maintenance phases of warfarin treatment, are needed.

  11. A review of a priori regression models for warfarin maintenance dose prediction.

    Science.gov (United States)

    Francis, Ben; Lane, Steven; Pirmohamed, Munir; Jorgensen, Andrea

    2014-01-01

    A number of a priori warfarin dosing algorithms, derived using linear regression methods, have been proposed. Although these dosing algorithms may have been validated using patients derived from the same centre, rarely have they been validated using a patient cohort recruited from another centre. In order to undertake external validation, two cohorts were utilised. One cohort formed by patients from a prospective trial and the second formed by patients in the control arm of the EU-PACT trial. Of these, 641 patients were identified as having attained stable dosing and formed the dataset used for validation. Predicted maintenance doses from six criterion fulfilling regression models were then compared to individual patient stable warfarin dose. Predictive ability was assessed with reference to several statistics including the R-square and mean absolute error. The six regression models explained different amounts of variability in the stable maintenance warfarin dose requirements of the patients in the two validation cohorts; adjusted R-squared values ranged from 24.2% to 68.6%. An overview of the summary statistics demonstrated that no one dosing algorithm could be considered optimal. The larger validation cohort from the prospective trial produced more consistent statistics across the six dosing algorithms. The study found that all the regression models performed worse in the validation cohort when compared to the derivation cohort. Further, there was little difference between regression models that contained pharmacogenetic coefficients and algorithms containing just non-pharmacogenetic coefficients. The inconsistency of results between the validation cohorts suggests that unaccounted population specific factors cause variability in dosing algorithm performance. Better methods for dosing that take into account inter- and intra-individual variability, at the initiation and maintenance phases of warfarin treatment, are needed.

  12. The role of data fusion in predictive maintenance using digital twin

    Science.gov (United States)

    Liu, Zheng; Meyendorf, Norbert; Mrad, Nezih

    2018-04-01

    Modern aerospace industry is migrating from reactive to proactive and predictive maintenance to increase platform operational availability and efficiency, extend its useful life cycle and reduce its life cycle cost. Multiphysics modeling together with data-driven analytics generate a new paradigm called "Digital Twin." The digital twin is actually a living model of the physical asset or system, which continually adapts to operational changes based on the collected online data and information, and can forecast the future of the corresponding physical counterpart. This paper reviews the overall framework to develop a digital twin coupled with the industrial Internet of Things technology to advance aerospace platforms autonomy. Data fusion techniques particularly play a significant role in the digital twin framework. The flow of information from raw data to high-level decision making is propelled by sensor-to-sensor, sensor-to-model, and model-to-model fusion. This paper further discusses and identifies the role of data fusion in the digital twin framework for aircraft predictive maintenance.

  13. Prediction of warfarin maintenance dose in Han Chinese patients using a mechanistic model based on genetic and non-genetic factors.

    Science.gov (United States)

    Lu, Yuan; Yang, Jinbo; Zhang, Haiyan; Yang, Jin

    2013-07-01

    Many attempts have been made to predict the warfarin maintenance dose in patients beginning warfarin therapy using a descriptive model based on multiple linear regression. Here we report the first attempt to develop a comprehensive mechanistic model integrating in vitro-in vivo extrapolation (IVIVE) with a pharmacokinetic-pharmacodynamic model to predict the warfarin maintenance dose in Han Chinese patients. The model incorporates demographic factors [sex, age, body weight (BW)] and the genetic polymorphisms of cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1). Information on the various factors, mean warfarin daily dose and International Normalized Ratio (INR) was available for a cohort of 197 Han Chinese patients. Based on in vitro enzyme kinetic parameters for S-warfarin metabolism, demographic data for Han Chinese and some scaling factors, the S-warfarin clearance (CL) was predicted for patients in the cohort with different CYP2C9 genotypes using IVIVE. The plasma concentration of S-warfarin after a single oral dose was simulated using a one-compartment pharmacokinetic model with first-order absorption and a lag time and was combined with a mechanistic coagulation model to simulate the INR response. The warfarin maintenance dose was then predicted based on the demographic data and genotypes of CYP2C9 and VKORC1 for each patient and using the observed steady-state INR (INRss) as a target value. Finally, sensitivity analysis was carried out to determine which factor(s) affect the warfarin maintenance dose most strongly. The predictive performance of this mechanistic model is not inferior to that of our previous descriptive model. There were significant differences in the mean warfarin daily dose in patients with different CYP2C9 and VKORC1 genotypes. Using IVIVE, the predicted mean CL of S-warfarin for patients with CYP2C9*1/*3 (0.092 l/h, n = 11) was 57 % less than for those with wild-type *1/*1 (0.215 l/h, n

  14. Nucleolar integrity is required for the maintenance of long-term synaptic plasticity.

    Directory of Open Access Journals (Sweden)

    Kim D Allen

    Full Text Available Long-term memory (LTM formation requires new protein synthesis and new gene expression. Based on our work in Aplysia, we hypothesized that the rRNA genes, stimulation-dependent targets of the enzyme Poly(ADP-ribose polymerase-1 (PARP-1, are primary effectors of the activity-dependent changes in synaptic function that maintain synaptic plasticity and memory. Using electrophysiology, immunohistochemistry, pharmacology and molecular biology techniques, we show here, for the first time, that the maintenance of forskolin-induced late-phase long-term potentiation (L-LTP in mouse hippocampal slices requires nucleolar integrity and the expression of new rRNAs. The activity-dependent upregulation of rRNA, as well as L-LTP expression, are poly(ADP-ribosylation (PAR dependent and accompanied by an increase in nuclear PARP-1 and Poly(ADP ribose molecules (pADPr after forskolin stimulation. The upregulation of PARP-1 and pADPr is regulated by Protein kinase A (PKA and extracellular signal-regulated kinase (ERK--two kinases strongly associated with long-term plasticity and learning and memory. Selective inhibition of RNA Polymerase I (Pol I, responsible for the synthesis of precursor rRNA, results in the segmentation of nucleoli, the exclusion of PARP-1 from functional nucleolar compartments and disrupted L-LTP maintenance. Taken as a whole, these results suggest that new rRNAs (28S, 18S, and 5.8S ribosomal components--hence, new ribosomes and nucleoli integrity--are required for the maintenance of long-term synaptic plasticity. This provides a mechanistic link between stimulation-dependent gene expression and the new protein synthesis known to be required for memory consolidation.

  15. Full scale test platform for European TBM systems integration and maintenance

    Energy Technology Data Exchange (ETDEWEB)

    Vála, Ladislav, E-mail: ladislav.vala@cvrez.cz; Reungoat, Mathieu; Vician, Martin

    2016-11-01

    Highlights: • A platform for EU-TBS maintenance and integration tests is described. • Its modular design allows adaptation to non-EU TBSs. • Assembling of the facility will be followed by initial tests in 2016. - Abstract: This article deals with description and current status of a project of a non-nuclear, full size (1:1 scale) test platform dedicated to tests, optimization and validation of integration and maintenance operations for the European TBM systems in the ITER port cell #16. The facility called TBM platform reproduces the ITER port cell #16 and port interspace with all the relevant interfaces and mock-ups of the corresponding main components. Thanks to the modular design of the platform, it is possible to adapt or change completely the interfaces in the future if needed or required according to the updated configuration of TBSs. In the same way, based on customer requirements, it will be possible to adapt the interfaces and piping inside the mock-ups in order to represent also the other, non-EU configurations of TBM systems designed for port cells #02 and #18. Construction of this test platform is realized and funded within the scope of the SUSEN project.

  16. Application of an integrated risk management system for improved maintenance in industrial plants

    Energy Technology Data Exchange (ETDEWEB)

    Jovanovic, A.; Balos, D.T.; Vinod, G.; Balos, D. [Steinbeis Advanced Risk Technologies, Stuttgart (Germany); Stanojevic, P. [NIS - Petroleum Industry of Serbia, Novi Sad (Serbia)

    2007-06-15

    The paper presents the application of the Integrated Risk Management System (iRiS) and its application to the areas of Risk Based Inspection (RBI), Reliability Centered Maintenance (RCM), Root Cause Failure Analysis (RCFA) and Health, Safety and Environment (HSE). The web-based system integrates also the aspects of risk management related to data acquisition and management and interactive reporting and controlled use of single parts of the system by various individual users and/or user levels. A complementing part of the system is a tool for project management including the documentation and activity management, as well as scheduling and e-education and e-training. The complementing parts of the system are the CMMS part (maintenance management), the extension of HSE to HSSE (including the 'security' aspects and providing links to the disaster management system) and further interfacing towards general management system and process modeling and management systems. Experiences from the applications of system in Hungary (at over 60 units) and in Serbia, for several refineries and further units in upstream and downstream, are presented in the paper. (orig.)

  17. The nuclear power plant maintenance personnel reliability prediction (NPP/MPRP) effort at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Knee, H.E.; Haas, P.M.; Siegel, A.I.

    1982-01-01

    Human errors committed during maintenance activities are potentially a major contribution to the overall risk associated with the operation of a nuclear power plant (NPP). An NRC-sponsored program at Oak Ridge National Laboratory is attempting to develop a quantitative predictive technique to evaluate the contribution of maintenance errors to the overall NPP risk. The current work includes a survey of the requirements of potential users to ascertain the need for and content of the proposed quantitative model, plus an initial job/task analysis to determine the scope and applicability of various maintenance tasks. In addition, existing human reliability prediction models are being reviewed and assessed with respect to their applicability to NPP maintenance tasks. This paper discusses the status of the program and summarizes the results to date

  18. [Echocardiographic factors predictive of restoration and maintenance of sinus rhythm after reduction of atrial fibrillation].

    Science.gov (United States)

    Ben Khalfallah, A; Sanaa, I

    2007-09-01

    Atrial fibrillation (AF) is the most common cardiac arrhythmia. While the arrhythmia was initially thought to be little more than a nuisance, it is now clear that AF has a significant negative impact on quality of life and a corresponding increase in both morbidity and mortality. The aim of this study was to identify Doppler echographic patterns that allow prediction of atrial fibrillation reduction and maintenance of sinus rhythm within 12 months. One hundred and thirty patients having permanent atrial fibrillation, recent (51) or chronic (79) are included in the study, excepting those with valvular heart disease or thyroid dysfunction. The mean age was 63.5 +/- 11.3 years. Both transthoracic and transoesophageal echocardiography was performed using a Philips SONOS 5500 Echograph, before cardioversion. Were studied: end diastolic and systolic left ventricular diameters, left ventricular ejectionnal fraction, left atrial area (LAA), left atrial diameter, left atrial appendage area and peak emptying velocities of the left atrial appendage (PeV). Sinus rhythm was re-established in 102 patients (44 having recent and 58 chronic atrial fibrillation). Sinus rhythm was maintained for 12 months in 79 patients. Within the echographic parameters studied, the left atrial area (LAA) and peak emptying velocities of left atrial appendage (PeV) before cardioversion were the best predictors of restoration of sinus rhythm. On monovariate analysis, SOG is significantly lower and PicV is significantly higher in patients whose sinus rhythm had been restored in comparison with those with permanent atrial fibrillation. (Mean SOG: 27.7 +/- 7.62 vs. 34 +/- 7,6 cm2, ppredict on mono and multivariate analysis (p=0.05, OR=0.5, IC=0.36 à 3.56), re-establishing of sinus rhythm whereas in patients with chronic atrial fibrillation, peak emptying velocity of left atrial appendage predict better re-establishing of sinus rhythm (p=0.04, OR=1.29, IC=0.12 à 4.23). The threshold values of LAA and Pe

  19. Using predictive maintenance methods at Hanford Engineering Development Laboratory (HEDL) to increase equipment availability and reduce overall managed costs

    International Nuclear Information System (INIS)

    Stanton, G.A.; Grygiel, M.L.

    1986-08-01

    This paper describes the predictive maintenance program that is presently in place at Hanford Engineering Development Laboratory using vibration analysis and oil sampling techniques. A pilot program at the Fast Flux Test Facility (FFTF) has been established using reliability-based maintenance concepts such as trend and failure analysis techniques. The first system being analyzed at FFTF will be the electrical distribution system. 2 figs

  20. Evaluation of implementation an Integrated Safety and Preventive Maintenance System for Improving of Safety Indexes

    Directory of Open Access Journals (Sweden)

    I mohammadfam

    2014-03-01

    Full Text Available Accident analysis shows that one of the main reasons for accidents is non-integration of maintenance units with safety. Merging these two processes through an integrated system can reduce and or eliminate accidents, diseases, and environmental pollution. These issues lead to improvement in organizational performance, as well. The aim of this study is to design and establish an integrated system for obtaining the aforementioned goal. Integration was carried out at Nirou Moharreke Machine Tools Company via Structured System Analysis & Design Method (SSADM. In order to measure the effectiveness of the system, selected indexes were compared using statistical methods prior and after system establishment. Results show that the accident severity index reduced from 135.46 in 2010, to 43.85 in 2012. Moreover, system effectiveness improved equipment reliability and availability (e.g. reliability of the Pfeiffer Milling machine (P (t>50 increased from 0.89 in 2010, to 0.9 in 2012. This system by forecasting various failures, and planning and designing the required operations for preventing occurrence of these failures, plays an important role in improving safety conditions of equipment, and increasing organizational performance, and is capable of presenting an excellent accident prevention program.

  1. Development of a predictive energy equation for maintenance hemodialysis patients: a pilot study.

    Science.gov (United States)

    Byham-Gray, Laura; Parrott, J Scott; Ho, Wai Yin; Sundell, Mary B; Ikizler, T Alp

    2014-01-01

    The study objectives were to explore the predictors of measured resting energy expenditure (mREE) among a sample of maintenance hemodialysis (MHD) patients, to generate a predictive energy equation (MHDE), and to compare such models to another commonly used predictive energy equation in nutritional care, the Mifflin-St. Jeor equation (MSJE). The study was a retrospective, cross-sectional cohort design conducted at the Vanderbilt University Medical Center. Study subjects were adult MHD patients (N = 67). Data collected from several clinical trials were analyzed using Pearson's correlation and multivariate linear regression procedures. Demographic, anthropometric, clinical, and laboratory data were examined as potential predictors of mREE. Limits of agreement between the MHDE and the MSJE were evaluated using Bland-Altman plots. The a priori α was set at P lean body mass [LBM]) of mREE included (R(2) = 0.489) FFM, ALB, age, and CRP. Two additional models (MHDE-CRP and MHDE-CR) with acceptable predictability (R(2) = 0.460 and R(2) = 0.451) were derived to improve the clinical utility of the developed energy equation (MHDE-LBM). Using Bland-Altman plots, the MHDE over- and underpredicted mREE less often than the MSJE. Predictive models (MHDE) including selective demographic, clinical, and anthropometric data explained less than 50% variance of mREE but had better precision in determining energy requirements for MHD patients when compared with MSJE. Further research is necessary to improve predictive models of mREE in the MHD population and to test its validity and clinical application. Copyright © 2014 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  2. Integrated internist - addiction medicine - hepatology model for hepatitis C management for individuals on methadone maintenance.

    Science.gov (United States)

    Martinez, A D; Dimova, R; Marks, K M; Beeder, A B; Zeremski, M; Kreek, M J; Talal, A H

    2012-01-01

    Despite a high prevalence of hepatitis C virus (HCV) among drug users, HCV evaluation and treatment acceptance are extremely low among these patients when referred from drug treatment facilities for HCV management. We sought to increase HCV treatment effectiveness among patients from a methadone maintenance treatment program (MMTP) by maintaining continuity of care. We developed, instituted and retrospectively assessed the effectiveness of an integrated, co-localized care model in which an internist-addiction medicine specialist from MMTP was embedded in the hepatitis clinic. Methadone maintenance treatment program patients were referred, evaluated by the internist and hepatologist in hepatitis clinic and provided HCV treatment with integration between both sites. Of 401 evaluated patients, anti-HCV antibody was detected in 257, 86% of whom were older than 40 years. Hepatitis C virus RNA levels were measured in 222 patients, 65 of whom were aviremic. Of 157 patients with detectable HCV RNA, 125 were eligible for referral to the hepatitis clinic, 76 (61%) of whom accepted and adhered with the referral. Men engaged in MMTP <36 months were significantly less likely to be seen in hepatitis clinic than men in MMTP more than 36 months (odds ratio = 7.7; 95% confidence interval 2.6-22.9) or women. We evaluated liver histology in 63 patients, and 83% had moderate to advanced liver disease. Twenty-four patients initiated treatment with 19 completing and 13 (54%) achieving sustained response. In conclusion, integrated care between the MMTP and the hepatitis clinic improves adherence with HCV evaluation and treatment compared to standard referral practices. © 2010 Blackwell Publishing Ltd.

  3. Prediction of L70 lumen maintenance and chromaticity for LEDs using extended Kalman filter models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, Lynn

    2013-09-30

    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

  4. Integrated approach to optimize operation and maintenance costs for operating nuclear power plants

    International Nuclear Information System (INIS)

    2006-06-01

    In the context of increasingly open electricity markets and the 'unbundling' of generating companies from former utility monopolies, an area of major concern is the economic performance of the existing fleet of nuclear power plants. Nuclear power, inevitably, must compete directly with other electricity generation sources. Coping with this competitive pressure is a challenge that the nuclear industry should meet if the nuclear option is to remain a viable one. This competitive environment has significant implications for nuclear plant operations, including, among others, the need for the more cost effective management of plant activities, and the greater use of analytical tools to balance the costs and benefits of proposed activities, in order to optimize operation and maintenance costs, and thus insure the economic competitiveness of existing nuclear power plants. In the framework of the activities on Nuclear Economic Performance Information System (NEPIS), the IAEA embarked in developing guidance on optimization of operation and maintenance costs for nuclear power plants. The report was prepared building on the fundamental that optimization of operation and maintenance costs of a nuclear power plant is a key component of a broader integrated business strategic planning process, having as overall result achievement of organization's business objectives. It provides advice on optimization of O and M costs in the framework of strategic business planning, with additional details on operational planning and controlling. This TECDOC was elaborated in 2004-2005 in the framework of the IAEA's programme on Nuclear Power Plant Operating Performance and Life Cycle Management, with the support of two consultants meetings and one technical meeting and based on contributions provided by participants. It can serve as a useful reference for the management and operation staff within utilities, nuclear power plant operators and regulators and other organizations involved in

  5. Operational control and maintenance integrity of typical and atypical coil tube steam generating systems

    Energy Technology Data Exchange (ETDEWEB)

    Beardwood, E.S.

    1999-07-01

    Coil tube steam generators are low water volume to boiler horsepower (bhp) rating, rapid steaming units which occupy substantially less space per boiler horsepower than equivalent conventional tire tube and water tube boilers. These units can be retrofitted into existing steam systems with relative ease and are more efficient than the generators they replace. During the early 1970's they became a popular choice for steam generation in commercial, institutional and light to medium industrial applications. Although these boiler designs do not require skilled or certified operators, an appreciation for a number of the operational conditions that result in lower unscheduled maintenance, increased reliability and availability cycles would be beneficial to facility owners, managers, and operators. Conditions which afford lower operating and maintenance costs will be discussed from a practical point of view. An overview of boiler design and operation is also included. Pitfalls are provided for operational and idle conditions. Water treatment application, as well as steam system operations not conducive to maintaining long term system integrity; with resolutions, will be addressed.

  6. An application of oscillation damped motion for suspended payloads to the advanced integrated maintenance system

    International Nuclear Information System (INIS)

    Noakes, M.W.; Petterson, B.J.; Werner, J.C.

    1990-01-01

    Transportation of objects using overhead cranes can induce pendulum motion of the object, which usually must be damped or allowed to decay before the next process can take place. Recent work at Sandia National Laboratories (SNL) has shown that oscillation damped transport and swing-free stops are possible by properly programming the acceleration of the transporting crane. This paper reviews the theory associated with oscillation-damped trajectories for simply suspended objects and describes a specific, full-scale implementation of the damped oscillation methods for the Oak Ridge National Laboratory (ORNL) Advanced Integrated Maintenance System (AIMS). Hardware and software requirements and constraints for proper operation are discussed. Finally, test results and lessons learned are presented. 5 refs., 4 figs

  7. Plant life management. An integral part of operation and maintenance policy

    International Nuclear Information System (INIS)

    Faidy, C.; Hutin, J.-P.

    2002-01-01

    Electricite de France is now operating 58 PWR nuclear power plants that produce 75% of electricity in France. Besides maintaining safety and availability on a routine basis, it is outmost important to protect the investment. That is the reason why EDF is devoting important resources to implement ageing management concern as an integral part of operation and maintenance programs (for example through appropriate data collection and analysis, specific repair and replacement projects and important anticipation efforts, taking in account the high level of standardisation of the units). A particular organisation has been set up to continuously observe and analyse all activities so as to make sure that ageing concern is correctly taken in account in strategies and that no decisions are susceptible to impair plant lifetime. This 'lifetime program' is paying attention to technical issues associated with main components but is also dealing with issues related to economics and industry situation. (orig.)

  8. Comparison of a Handheld Indirect Calorimetry Device and Predictive Energy Equations Among Individuals on Maintenance Hemodialysis.

    Science.gov (United States)

    Morrow, Ellis A; Marcus, Andrea; Byham-Gray, Laura

    2017-11-01

    Practical methods for determining resting energy expenditure (REE) among individuals on maintenance hemodialysis (MHD) are needed because of the limitations of indirect calorimetry. Two disease-specific predictive energy equations (PEEs) have been developed for this metabolically complex population. The aim of this study was to compare estimated REE (eREE) by PEEs to measured REE (mREE) with a handheld indirect calorimetry device (HICD). A prospective pilot study of adults on MHD (N = 40) was conducted at 2 dialysis clinics in Houston and Texas City, Texas. mREE by an HICD was compared with eREE determined by 6 PEEs using Bland-Altman analysis with a band of acceptable agreement of ±10% of the group mean mREE. Paired t-test and the intraclass correlation coefficient were also used to compare the alternate methods of measuring REE. A priori alpha was set at P Maintenance Hemodialysis Equation-Creatinine version (MHCD-CR) was the most accurate PEE with 52.5% of values within the band of acceptable agreement, followed by the Mifflin-St. Jeor Equation and the Vilar et al. Equation at 45.0% and 42.5%, respectively. When compared with mREE by the HICD, the MHDE-CR was more accurate and precise than other PEEs evaluated; however, this must be interpreted with caution as mREE was consistently lower than eREE from all PEEs. Further research is needed to validate the MHDE-CR and other practical methods for determining REE among individuals on MHD. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

  9. Maintenance treatment with azathioprine in ulcerative colitis: outcome and predictive factors after drug withdrawal.

    Science.gov (United States)

    Cassinotti, Andrea; Actis, Giovanni C; Duca, Piergiorgio; Massari, Alessandro; Colombo, Elisabetta; Gai, Elisa; Annese, Vito; D'Albasio, Giuseppe; Manes, Gianpiero; Travis, Simon; Porro, Gabriele Bianchi; Ardizzone, Sandro

    2009-11-01

    Whether the duration of maintenance treatment with azathioprine (AZA) affects the outcome of ulcerative colitis (UC) is unclear. We investigated clinical outcomes and any predictive factors after withdrawal of AZA in UC. In this multicenter observational retrospective study, 127 Italian UC patients, who were in steroid-free remission at the time of withdrawal of AZA, were followed-up for a median of 55 months or until relapse. The frequency of clinical relapse or colectomy after AZA withdrawal was analyzed according to demographic, clinical, and endoscopic variables. After drug withdrawal, a third of the patients relapsed within 12 months, half within 2 years and two-thirds within 5 years. After multivariable analysis, predictors of relapse after drug withdrawal were lack of sustained remission during AZA maintenance (hazard ratio, HR 2.350, confidence interval, CI 95% 1.434-3.852; P=0.001), extensive colitis (HR 1.793, CI 95% 1.064-3.023, P=0.028 vs. left-sided colitis; HR 2.024, CI 95% 1.103-3.717, P=0.023 vs. distal colitis), and treatment duration, with short treatments (3-6 months) more disadvantaged than >48-month treatments (HR 2.783, CI 95% 1.267-6.114, P=0.008). Concomitant aminosalicylates were the only predictors of sustained remission during AZA therapy (P=0.009). The overall colectomy rate was 10%. Predictors of colectomy were drug-related toxicity as the cause of AZA withdrawal (P=0.041), no post-AZA drug therapy (P=0.031), and treatment duration (P<0.0005). Discontinuation of AZA while UC is in remission is associated with a high relapse rate. Disease extent, lack of sustained remission during AZA, and discontinuation due to toxicity could stratify relapse risk. Concomitant aminosalicylates were advantageous. Prospective randomized controlled trials are needed to confirm whether treatment duration is inversely associated with outcome.

  10. Preventive and Predictive Maintenance, Warehousing of Spares, Periodic Testing and In-Service Inspection Activities at the Nigerian Research Reactor-1 Facility

    Energy Technology Data Exchange (ETDEWEB)

    Yusuf, I.; Mati, A. A.; Dewu, B. B.M., [Centre for Energy Research and Training, Ahmadu Bello University, Zaria (Nigeria)

    2014-08-15

    The Nigerian Research Reactor–1, or NIRR-1, is sited at Centre for Energy Research and Training, Ahmadu Bello University, Zaria, Nigeria. Activities on preventive or routine maintenance have been institutionalized since the commissioning of the reactor in February 2004. This has grossly reduced the rates of corrective maintenance activities and helped the reactor management a great deal in predicting failure rates of reactor components and other auxiliary units. Routine maintenance of systems and components are being carried out on a weekly, quarterly and annual basis based on manufacturer’s recommendations, which have been reviewed and improved over the years. The paper presents the implementation of maintenance activities in NIRR-1 from its initial criticality in 2004 till today and the new scheme for periodic testing and in-service-inspection developed after an IAEA Integrated Safety Assessment of Research Reactors mission. The measures put in place are envisaged to reduce the negative impact of ageing on NIRR-1 and its auxiliary systems. (author)

  11. Applying theory of planned behavior to predict exercise maintenance in sarcopenic elderly

    Science.gov (United States)

    Ahmad, Mohamad Hasnan; Shahar, Suzana; Teng, Nur Islami Mohd Fahmi; Manaf, Zahara Abdul; Sakian, Noor Ibrahim Mohd; Omar, Baharudin

    2014-01-01

    This study aimed to determine the factors associated with exercise behavior based on the theory of planned behavior (TPB) among the sarcopenic elderly people in Cheras, Kuala Lumpur. A total of 65 subjects with mean ages of 67.5±5.2 (men) and 66.1±5.1 (women) years participated in this study. Subjects were divided into two groups: 1) exercise group (n=34; 25 men, nine women); and 2) the control group (n=31; 22 men, nine women). Structural equation modeling, based on TPB components, was applied to determine specific factors that most contribute to and predict actual behavior toward exercise. Based on the TPB’s model, attitude (β=0.60) and perceived behavioral control (β=0.24) were the major predictors of intention to exercise among men at the baseline. Among women, the subjective norm (β=0.82) was the major predictor of intention to perform the exercise at the baseline. After 12 weeks, attitude (men’s, β=0.68; women’s, β=0.24) and subjective norm (men’s, β=0.12; women’s, β=0.87) were the predictors of the intention to perform the exercise. “Feels healthier with exercise” was the specific factor to improve the intention to perform and to maintain exercise behavior in men (β=0.36) and women (β=0.49). “Not motivated to perform exercise” was the main barrier among men’s intention to exercise. The intention to perform the exercise was able to predict actual behavior regarding exercise at the baseline and at 12 weeks of an intervention program. As a conclusion, TPB is a useful model to determine and to predict maintenance of exercise in the sarcopenic elderly. PMID:25258524

  12. New optimization strategies of pavement maintenance: A case study for national road network in Indonesia using integrated road management system

    Science.gov (United States)

    Hamdi, Hadiwardoyo, Sigit P.; Correia, A. Gomes; Pereira, Paulo

    2017-06-01

    A road network requires timely maintenance to keep the road surface in good condition onward better services to improve accessibility and mobility. Strategies and maintenance techniques must be chosen in order to maximize road service level through cost-effective interventions. This approach requires an updated database, which the road network in Indonesia is supported by a manual and visual survey, also using NAASRA profiler. Furthermore, in this paper, the deterministic model of deterioration was used. This optimization model uses life cycle cost analysis (LCCA), applied in an integrated manner, using IRI indicator, and allows determining the priority of treatment, type of treatment and its relation to the cost. The purpose of this paper was focussed on the aspects of road maintenance management, i.e., maintenance optimization models for different levels of traffic and various initial of road distress conditions on the national road network in Indonesia. The implementation of Integrated Road Management System (IRMS) can provide a solution to the problem of cost constraints in the maintenance of the national road network. The results from this study found that as the lowest as agency cost, it will affect the increasing of user cost. With the achievement of the target plan scenario Pl000 with initial value IRI 2, it was found that the routine management throughout the year and in early reconstruction and periodic maintenance with a 30 mm thick overlay, will simultaneously provide a higher net benefit value and has the lowest total cost of transportation.

  13. Integrated Technical Information for the Air Logistics Center: Enhancing Maintenance Technician Task Performance

    National Research Council Canada - National Science Library

    Mitta, Deborah

    1998-01-01

    This technical paper documents the final results of an analysis of the task environment under which depot maintenance technicians perform their jobs--specifically, programmed depot maintenance (PDM) for F-15 aircraft...

  14. Drosophila Sld5 is essential for normal cell cycle progression and maintenance of genomic integrity

    Energy Technology Data Exchange (ETDEWEB)

    Gouge, Catherine A. [Department of Biology, East Carolina University East Carolina University, Greenville, NC 27858 (United States); Christensen, Tim W., E-mail: christensent@ecu.edu [Department of Biology, East Carolina University East Carolina University, Greenville, NC 27858 (United States)

    2010-09-10

    Research highlights: {yields} Drosophila Sld5 interacts with Psf1, PPsf2, and Mcm10. {yields} Haploinsufficiency of Sld5 leads to M-phase delay and genomic instability. {yields} Sld5 is also required for normal S phase progression. -- Abstract: Essential for the normal functioning of a cell is the maintenance of genomic integrity. Failure in this process is often catastrophic for the organism, leading to cell death or mis-proliferation. Central to genomic integrity is the faithful replication of DNA during S phase. The GINS complex has recently come to light as a critical player in DNA replication through stabilization of MCM2-7 and Cdc45 as a member of the CMG complex which is likely responsible for the processivity of helicase activity during S phase. The GINS complex is made up of 4 members in a 1:1:1:1 ratio: Psf1, Psf2, Psf3, And Sld5. Here we present the first analysis of the function of the Sld5 subunit in a multicellular organism. We show that Drosophila Sld5 interacts with Psf1, Psf2, and Mcm10 and that mutations in Sld5 lead to M and S phase delays with chromosomes exhibiting hallmarks of genomic instability.

  15. Preventive Maintenance Interval Prediction: a Spare Parts Inventory Cost and Lost Earning Based Model

    Directory of Open Access Journals (Sweden)

    O. A. Adebimpe

    2015-06-01

    Full Text Available In this paper, some preventive maintenance parameters in manufacturing firms were identified and used to develop cost based functions in terms of machine preventive maintenance. The proposed cost based model considers system’s reliability, cost of keeping spare parts inventory and lost earnings in deriving optimal maintenance interval. A case of a manufacturing firm in Nigeria was observed and the data was used to evaluate the model.

  16. Advanced diagnostics and predictive maintenance to improve availability and reliability of ENEL plants

    Energy Technology Data Exchange (ETDEWEB)

    Cenci, V.; Ghironi, M.; Guidi, L.; Lauro, M.; Pestonesi, D. [ENEL (Italy). Generation and Energy Management Division

    2007-07-01

    This paper reviews the ENEL Generation and Energy Management strategy for diagnostics and predictive maintenance of power plants and provides a comprehensive description of effective applications and systems. Exploiting the most advanced information and communication technologies makes it possible to capture weak and hidden signals and powerful processing can be used to discover forewarning symptoms and identify anomalies both in the process and, above all, inside the devices. The following systems and applications are presented together with results and impact on plant profitability: expert system for the diagnostics of plant main machinery; advanced diagnostics of 'intelligent' fieldbus devices such as on/off valve motor-driven actuators, control-valve positioners and pneumatic actuators, transmitters; control loop and control valve diagnostics in order to investigate valve friction with an estimation of the residual time to failure; multisensorial diagnostics for coal transport and storage systems aimed at preventing firing and structural damages; and wireless sensor networks for the diagnostics of medium and small size components. 4 refs., 14 figs., 1 tab.

  17. Adalimumab Dose Tapering in Psoriasis: Predictive Factors for Maintenance of Complete Clearance.

    Science.gov (United States)

    Hansel, Katharina; Bianchi, Leonardo; Lanza, Francesco; Bini, Vittorio; Stingeni, Luca

    2017-03-10

    Psoriasis can be managed successfully with long-term biologics. Real-life clinical practice may require dose tapering as a therapeutic option to reduce the risk of drug-exposure and to increase cost-effectiveness. The responsiveness to extended intervals between adalimumab doses and the possible predictive factors of maintenance of complete clearance were studied in a retrospective 7-year single-centre analysis. Thirty patients who achieved complete clearance with adalimumab underwent dose tapering, progressively extending between-dose intervals (to 21-28 days). Sixty percent of subjects (group A) maintained complete clearance, whereas 40.0% (group B) relapsed and were switched back to the standard dosage to re-achieve complete clearance. Body mass index (BMI) and time to achieve Psoriasis Area Severity Index (PASI-100) with adalimumab standard treatment before dose tapering were significantly lower in group A than in group B (multi-variate Cox regression: p < 0.05, Kaplan-Meier analysis: p < 0.001, respectively). This study suggests that patients with lower BMI and shorter time to achieve PASI-100 with adalimumab standard dose were significantly more likely to be candidates for dose tapering.

  18. Using adaptive model predictive control to customize maintenance therapy chemotherapeutic dosing for childhood acute lymphoblastic leukemia.

    Science.gov (United States)

    Noble, Sarah L; Sherer, Eric; Hannemann, Robert E; Ramkrishna, Doraiswami; Vik, Terry; Rundell, Ann E

    2010-06-07

    Acute lymphoblastic leukemia (ALL) is a common childhood cancer in which nearly one-quarter of patients experience a disease relapse. However, it has been shown that individualizing therapy for childhood ALL patients by adjusting doses based on the blood concentration of active drug metabolite could significantly improve treatment outcome. An adaptive model predictive control (MPC) strategy is presented in which maintenance therapy for childhood ALL is personalized using routine patient measurements of red blood cell mean corpuscular volume as a surrogate for the active drug metabolite concentration. A clinically relevant mathematical model is developed and used to describe the patient response to the chemotherapeutic drug 6-mercaptopurine, with some model parameters being patient-specific. During the course of treatment, the patient-specific parameters are adaptively identified using recurrent complete blood count measurements, which sufficiently constrain the patient parameter uncertainty to support customized adjustments of the drug dose. While this work represents only a first step toward a quantitative tool for clinical use, the simulated treatment results indicate that the proposed mathematical model and adaptive MPC approach could serve as valuable resources to the oncologist toward creating a personalized treatment strategy that is both safe and effective. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  19. Prediction of attendance at fitness center: a comparison between the theory of planned behavior, the social cognitive theory, and the physical activity maintenance theory

    OpenAIRE

    Jekauc, Darko; Völkle, Manuel; Wagner, Matthias O.; Mess, Filip; Reiner, Miriam; Renner, Britta

    2015-01-01

    In the processes of physical activity (PA) maintenance specific predictors are effective, which differ from other stages of PA development. Recently, Physical Activity Maintenance Theory (PAMT) was specifically developed for prediction of PA maintenance. The aim of the present study was to evaluate the predictability of the future behavior by the PAMT and compare it with the Theory of Planned Behavior (TPB) and Social Cognitive Theory (SCT). Participation rate in a fitness center was observed...

  20. Applying theory of planned behavior to predict exercise maintenance in sarcopenic elderly

    Directory of Open Access Journals (Sweden)

    Ahmad MH

    2014-09-01

    to predict maintenance of exercise in the sarcopenic elderly.Keywords: theory planned behavior, aging, elderly, sarcopenic, exercise

  1. The predictive value of malnutrition - inflammation score on 1-year mortality in Turkish maintenance hemodialysis patients.

    Science.gov (United States)

    Kara, Ekrem; Sahutoglu, Tuncay; Ahbap, Elbis; Sakaci, Tamer; Koc, Yener; Basturk, Taner; Sevinc, Mustafa; Akgol, Cuneyt; Unsal, Abdulkadir

    2016-08-01

    The aim of this study was to evaluate the predictive value of malnutrition-inflammation score (MIS) on short-term mortality and to identify the best cut-off point in the Turkish maintenance hemodialysis (MHD) population. A total of 100 patients on MHD were included in this prospective single-center study. Demographic, anthropometric, and biochemical data were obtained from all patients. The study population was followed up as a 12-month prospective cohort to evaluate mortality as the primary outcome. Median (IQR) age and HD vintage of 100 patients (M/F: 52/48) were 53 (39.5 - 67) years and 53.5 (11 - 104.7) months, respectively. Deceased patients (n = 7) had significantly older age (years) (50 (38.5 - 63.5) vs. 70 (62 - 82), respectively, p = 0.001), lower spKt/V (1.60 (1.40 - 1.79) vs. 1.35 (0.90 - 1.50), respectively, p = 0.002), lower triceps skinfold thickness (14 (10 - 19) vs. 9 (7 - 11), respectively, p = 0.021) and higher MIS (5 (4 - 7) vs. 10 (7 - 11), respectively, p = 0.013). In the ROC analysis, we found that the optimal cut-off value of MIS for predicting death was 6.5 with 85.7% sensitivity and 62.4% specificity (positive and negative predictive values were 0.6951 and 0.8136, respectively). Advanced age, low spKt/V, and high MIS were found to be predictors of mortality in multivariate logistic regression analysis. The 1-year mortality rate was significantly higher in MIS > 6.5 group compared to the MIS ≤ 6.5 group (14,3% (6/41) vs. 1.6% (1/59), respectively). Compared to MIS ≤ 6.5 group, 1 year survival time of the patients with MIS > 6.5 was found to be significantly lower (47.8 ± 0.16 vs. 43.6 ± 1.63 weeks, respectively, p (log-rank) = 0.012). MIS is a robust and independent predictor of short-term mortality in MHD patients. Patients with MIS > 6.5 had a significant risk, and additional risk factors associated with short-term mortality were advanced age and low spKt/V.

  2. Predictive integrated modelling for ITER scenarios

    International Nuclear Information System (INIS)

    Artaud, J.F.; Imbeaux, F.; Aniel, T.; Basiuk, V.; Eriksson, L.G.; Giruzzi, G.; Hoang, G.T.; Huysmans, G.; Joffrin, E.; Peysson, Y.; Schneider, M.; Thomas, P.

    2005-01-01

    The uncertainty on the prediction of ITER scenarios is evaluated. 2 transport models which have been extensively validated against the multi-machine database are used for the computation of the transport coefficients. The first model is GLF23, the second called Kiauto is a model in which the profile of dilution coefficient is a gyro Bohm-like analytical function, renormalized in order to get profiles consistent with a given global energy confinement scaling. The package of codes CRONOS is used, it gives access to the dynamics of the discharge and allows the study of interplay between heat transport, current diffusion and sources. The main motivation of this work is to study the influence of parameters such plasma current, heat, density, impurities and toroidal moment transport. We can draw the following conclusions: 1) the target Q = 10 can be obtained in ITER hybrid scenario at I p = 13 MA, using either the DS03 two terms scaling or the GLF23 model based on the same pedestal; 2) I p = 11.3 MA, Q = 10 can be reached only assuming a very peaked pressure profile and a low pedestal; 3) at fixed Greenwald fraction, Q increases with density peaking; 4) achieving a stationary q-profile with q > 1 requires a large non-inductive current fraction (80%) that could be provided by 20 to 40 MW of LHCD; and 5) owing to the high temperature the q-profile penetration is delayed and q = 1 is reached about 600 s in ITER hybrid scenario at I p = 13 MA, in the absence of active q-profile control. (A.C.)

  3. Optimization of Two-Level Disassembly/Remanufacturing/Assembly System with an Integrated Maintenance Strategy

    Directory of Open Access Journals (Sweden)

    Zouhour Guiras

    2018-04-01

    Full Text Available With an increase of environmental pressure on economic activities, reverse flow is increasingly important. It seeks to save resources, eliminate waste, and improve productivity. This paper investigates the optimization of the disassembly, remanufacturing and assembly system, taking into account assembly-disassembly system degradation. An analytical model is developed to consider disassembly, remanufacturing of used/end-of-life product and assembly of the finished product. The finished product is composed of remanufactured and new components. A maintenance policy is sequentially integrated to reduce the system unavailability. The aim of this study is to help decision-makers, under certain conditions, choose the most cost-effective process for them to satisfy the customer as well as to adapt to the potential risk that can perturb the disassembly-assembly system. A heuristic is developed to determine the optimal ordered date of the used end-of-life product as well as the optimum release dates of new external components. The results reveal that considering some remanufacturing and purchase components costs, the proposed model is more economical in comparison with a model without remanufactured parts. Numerical results are provided to illustrate the impact of the variation of the ordering cost and quality of the used end-of-life product on the system profitability. Finally, the risk due to system repair periods is discussed, which has an impact on managerial decision-making.

  4. Integration of Signaling Pathways with the Epigenetic Machinery in the Maintenance of Stem Cells

    Directory of Open Access Journals (Sweden)

    Luca Fagnocchi

    2016-01-01

    Full Text Available Stem cells balance their self-renewal and differentiation potential by integrating environmental signals with the transcriptional regulatory network. The maintenance of cell identity and/or cell lineage commitment relies on the interplay of multiple factors including signaling pathways, transcription factors, and the epigenetic machinery. These regulatory modules are strongly interconnected and they influence the pattern of gene expression of stem cells, thus guiding their cellular fate. Embryonic stem cells (ESCs represent an invaluable tool to study this interplay, being able to indefinitely self-renew and to differentiate towards all three embryonic germ layers in response to developmental cues. In this review, we highlight those mechanisms of signaling to chromatin, which regulate chromatin modifying enzymes, histone modifications, and nucleosome occupancy. In addition, we report the molecular mechanisms through which signaling pathways affect both the epigenetic and the transcriptional state of ESCs, thereby influencing their cell identity. We propose that the dynamic nature of oscillating signaling and the different regulatory network topologies through which those signals are encoded determine specific gene expression programs, leading to the fluctuation of ESCs among multiple pluripotent states or to the establishment of the necessary conditions to exit pluripotency.

  5. Proteomic analysis of the dysferlin protein complex unveils its importance for sarcolemmal maintenance and integrity.

    Directory of Open Access Journals (Sweden)

    Antoine de Morrée

    Full Text Available Dysferlin is critical for repair of muscle membranes after damage. Mutations in dysferlin lead to a progressive muscular dystrophy. Recent studies suggest additional roles for dysferlin. We set out to study dysferlin's protein-protein interactions to obtain comprehensive knowledge of dysferlin functionalities in a myogenic context. We developed a robust and reproducible method to isolate dysferlin protein complexes from cells and tissue. We analyzed the composition of these complexes in cultured myoblasts, myotubes and skeletal muscle tissue by mass spectrometry and subsequently inferred potential protein functions through bioinformatics analyses. Our data confirm previously reported interactions and support a function for dysferlin as a vesicle trafficking protein. In addition novel potential functionalities were uncovered, including phagocytosis and focal adhesion. Our data reveal that the dysferlin protein complex has a dynamic composition as a function of myogenic differentiation. We provide additional experimental evidence and show dysferlin localization to, and interaction with the focal adhesion protein vinculin at the sarcolemma. Finally, our studies reveal evidence for cross-talk between dysferlin and its protein family member myoferlin. Together our analyses show that dysferlin is not only a membrane repair protein but also important for muscle membrane maintenance and integrity.

  6. Integrated Instrumentation and Sensor Systems Enabling Condition-Based Maintenance of Aerospace Equipment

    Directory of Open Access Journals (Sweden)

    Richard C. Millar

    2012-01-01

    Full Text Available The objective of the work reported herein was to use a systems engineering approach to guide development of integrated instrumentation/sensor systems (IISS incorporating communications, interconnections, and signal acquisition. These require enhanced suitability and effectiveness for diagnostics and health management of aerospace equipment governed by the principles of Condition-based maintenance (CBM. It is concluded that the systems engineering approach to IISS definition provided clear benefits in identifying overall system requirements and an architectural framework for categorizing and evaluating alternative architectures, relative to a bottom up focus on sensor technology blind to system level user needs. CBM IISS imperatives identified include factors such as tolerance of the bulk of aerospace equipment operational environments, low intrusiveness, rapid reconfiguration, and affordable life cycle costs. The functional features identified include interrogation of the variety of sensor types and interfaces common in aerospace equipment applications over multiplexed communication media with flexibility to allow rapid system reconfiguration to adapt to evolving sensor needs. This implies standardized interfaces at the sensor location (preferably to open standards, reduced wire/connector pin count in harnesses (or their elimination through use of wireless communications.

  7. Failure analysis for ultrasound machines in a radiology department after implementation of predictive maintenance method

    Directory of Open Access Journals (Sweden)

    Greg Chu

    2018-01-01

    Full Text Available Objective: The objective of the study was to perform quantitative failure and fault analysis to the diagnostic ultrasound (US scanners in a radiology department after the implementation of the predictive maintenance (PdM method; to study the reduction trend of machine failure; to understand machine operating parameters affecting the failure; to further optimize the method to maximize the machine clinically service time. Materials and Methods: The PdM method has been implemented to the 5 US machines since 2013. Log books were used to record machine failures and their root causes together with the time spent on repair, all of which were retrieved, categorized, and analyzed for the period between 2013 and 2016. Results: There were a total of 108 cases of failure occurred in these 5 US machines during the 4-year study period. The average number of failure per month for all these machines was 2.4. Failure analysis showed that there were 33 cases (30.5% due to software, 44 cases (40.7% due to hardware, and 31 cases (28.7% due to US probe. There was a statistically significant negative correlation between the time spent on regular quality assurance (QA by hospital physicists with the time spent on faulty parts replacement over the study period (P = 0.007. However, there was no statistically significant correlation between regular QA time and total yearly breakdown case (P = 0.12, although there has been a decreasing trend observed in the yearly total breakdown. Conclusion: There has been a significant improvement on the machine failure of US machines attributed to the concerted effort of sonographers and physicists in our department to practice the PdM method, in that system component repair time has been reduced, and a decreasing trend in the number of system breakdown has been observed.

  8. Transfer of infrared thermography predictive maintenance technologies to Soviet-designed nuclear power plants: experience at Chernobyl

    Science.gov (United States)

    Pugh, Ray; Huff, Roy

    1999-03-01

    The importance of infrared (IR) technology and analysis in today's world of predictive maintenance and reliability- centered maintenance cannot be understated. The use of infrared is especially important in facilities that are required to maintain a high degree of equipment reliability because of plant or public safety concerns. As with all maintenance tools, particularly those used in predictive maintenance approaches, training plays a key role in their effectiveness and the benefit gained from their use. This paper details an effort to transfer IR technology to Soviet- designed nuclear power plants in Russia, Ukraine, and Lithuania. Delivery of this technology and post-delivery training activities have been completed recently at the Chornobyl nuclear power plant in Ukraine. Many interesting challenges were encountered during this effort. Hardware procurement and delivery of IR technology to a sensitive country were complicated by United States regulations. Freight and shipping infrastructure and host-country customs policies complicated hardware transport. Training activities were complicated by special hardware, software and training material translation needs, limited communication opportunities, and site logistical concerns. These challenges and others encountered while supplying the Chornobyl plant with state-of-the-art IR technology are described in this paper.

  9. Application of data mining in a maintenance system for failure prediction

    OpenAIRE

    Bastos, Pedro; Lopes, Isabel; Pires, L.C.M.

    2014-01-01

    In industrial environment, data generated during equipment maintenance and monitoring activities has become increasingly overwhelming. Data mining presents an opportunity to increase significantly the rate at which the volume of data can be turned into useful information. This paper presents an architecture designed to gather data generated in industrial units on their maintenance activities, and to forecast future failures based on data analysis. Rapid Miner is used to apply diff...

  10. METHODS AND TECHNIQUES OF PREDICTION OF KEY PERFORMANCE INDICATORS FOR IMPLEMENTATION OF CHANGES IN MAINTENANCE ORGANISATION

    Directory of Open Access Journals (Sweden)

    Andrzej WIECZOREK

    2012-01-01

    Full Text Available The article presents the concept of how to assess the future state of the organization in the area of using and maintenance of technical means, basing on the combination of "classic" prognostic model with models ‐ components of the selected computer tools. Presentation of this concept was preceded by the definition and characteristics of maintenance key performance indicators. It also presents a requirements and method of KPIs selection.

  11. Developing Mobile- and BIM-Based Integrated Visual Facility Maintenance Management System

    Directory of Open Access Journals (Sweden)

    Yu-Cheng Lin

    2013-01-01

    Full Text Available Facility maintenance management (FMM has become an important topic for research on the operation phase of the construction life cycle. Managing FMM effectively is extremely difficult owing to various factors and environments. One of the difficulties is the performance of 2D graphics when depicting maintenance service. Building information modeling (BIM uses precise geometry and relevant data to support the maintenance service of facilities depicted in 3D object-oriented CAD. This paper proposes a new and practical methodology with application to FMM using BIM technology. Using BIM technology, this study proposes a BIM-based facility maintenance management (BIMFMM system for maintenance staff in the operation and maintenance phase. The BIMFMM system is then applied in selected case study of a commercial building project in Taiwan to verify the proposed methodology and demonstrate its effectiveness in FMM practice. Using the BIMFMM system, maintenance staff can access and review 3D BIM models for updating related maintenance records in a digital format. Moreover, this study presents a generic system architecture and its implementation. The combined results demonstrate that a BIMFMM-like system can be an effective visual FMM tool.

  12. Construction of a test platform for Test Blanket Module (TBM) systems integration and maintenance in ITER Port Cell #16

    Energy Technology Data Exchange (ETDEWEB)

    Vála, Ladislav, E-mail: ladislav.vala@cvrez.cz [Centrum výzkumu Řež, Hlavní 130, 250 68 Husinec-Řež (Czech Republic); Reungoat, Mathieu, E-mail: mathieu.reungoat@cvrez.cz [Centrum výzkumu Řež, Hlavní 130, 250 68 Husinec-Řež (Czech Republic); Vician, Martin [Centrum výzkumu Řež, Hlavní 130, 250 68 Husinec-Řež (Czech Republic); Poitevin, Yves; Ricapito, Italo; Zmitko, Milan; Panayotov, Dobromir [Fusion for Energy, Josep Pla 2, Torres Diagonal Litoral B3, 08019 Barcelona (Spain)

    2015-10-15

    Highlights: • A non-nuclear, full size facility – TBM platform – is under construction in CVR. • It is designed for tests, optimization and validation of TBS maintenance operations. • It will allow testing and validation of specific maintenance tools and RH equipment. • It reproduces ITER Port Cell #16, as well as the TBS interfaces and main equipment. • The TBM platform will be available for full operation in the first half of 2016. - Abstract: This paper describes a project of a non-nuclear, 1:1 scale testing platform dedicated to tests, optimization and validation of integration and maintenance operations for the European TBM systems in the ITER Port Cell #16. This TBM platform is currently under construction in Centrum výzkumu Řež, Czech Republic. The facility is realized within the scope of the SUSEN project and its full operation is foreseen in the first half of 2016.

  13. Integrated Design and Approach of Building Maintenance Management in the Built Environment

    Directory of Open Access Journals (Sweden)

    Md Azree Othuman Mydin

    2017-12-01

    Full Text Available Building maintenance is such a crucial aspect in the construction industry. The construction industry is characterized as a project-based industry that delivers one of a kind products and services. Thus, building maintenance can guarantee the safety of buildings including human health and property. To some extent, it plays as a guard to supervise the buildings protecting them being suffered collapse and deterioration. The most importantly, preparing for maintenance carried out on buildings is complex and it is related to procurement system dramatically, such as design-and-build, design-build-finance operate, and the private finance initiative and public/private partnerships, all of them need to give much consideration of operational and maintenance needs and costs which are ongoing.. This paper will focus on design and approach of building maintenance management in the construction industry.

  14. Music therapy-induced changes in salivary cortisol level are predictive of cardiovascular mortality in patients under maintenance hemodialysis.

    Science.gov (United States)

    Hou, Yi-Chou; Lin, Yen-Ju; Lu, Kuo-Cheng; Chiang, Han-Sun; Chang, Chia-Chi; Yang, Li-King

    2017-01-01

    Music therapy has been applied in hemodialysis (HD) patients for relieving mental stress. Whether the stress-relieving effect by music therapy is predictive of clinical outcome in HD patients is still unclear. We recruited a convenience sample of 99 patients on maintenance HD and randomly assigned them to the experimental (n=49) or control (n=50) group. The experimental group received relaxing music therapy for 1 week, whereas the control group received no music therapy. In the experimental group, we compared cardiovascular mortality in the patients with and without cortisol changes. The salivary cortisol level was lowered after 1 week of music therapy in the experimental group (-2.41±3.08 vs 1.66±2.11 pg/mL, P 0.6 pg/mL (83.8% vs 63.6%, P predict cardiovascular mortality in patients under maintenance HD.

  15. UK Environmental Prediction - integration and evaluation at the convective scale

    Science.gov (United States)

    Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor

    2016-04-01

    Traditionally, the simulation of regional ocean, wave and atmosphere components of the Earth System have been considered separately, with some information on other components provided by means of boundary or forcing conditions. More recently, the potential value of a more integrated approach, as required for global climate and Earth System prediction, for regional short-term applications has begun to gain increasing research effort. In the UK, this activity is motivated by an understanding that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system, including a new eddy-permitting resolution ocean component, and discuss progress and initial results from further development to integrate wave interactions in this relatively high resolution system. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

  16. The plant cell wall integrity maintenance mechanism--a case study of a cell wall plasma membrane signaling network.

    Science.gov (United States)

    Hamann, Thorsten

    2015-04-01

    Some of the most important functions of plant cell walls are protection against biotic/abiotic stress and structural support during growth and development. A prerequisite for plant cell walls to perform these functions is the ability to perceive different types of stimuli in both qualitative and quantitative manners and initiate appropriate responses. The responses in turn involve adaptive changes in cellular and cell wall metabolism leading to modifications in the structures originally required for perception. While our knowledge about the underlying plant mechanisms is limited, results from Saccharomyces cerevisiae suggest the cell wall integrity maintenance mechanism represents an excellent example to illustrate how the molecular mechanisms responsible for stimulus perception, signal transduction and integration can function. Here I will review the available knowledge about the yeast cell wall integrity maintenance system for illustration purposes, summarize the limited knowledge available about the corresponding plant mechanism and discuss the relevance of the plant cell wall integrity maintenance mechanism in biotic stress responses. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. An integrated artificial neural networks approach for predicting global radiation

    International Nuclear Information System (INIS)

    Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

    2009-01-01

    This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

  18. Region-specific role for Pten in maintenance of epithelial phenotype and integrity

    Science.gov (United States)

    Flodby, Per; Sunohara, Mitsuhiro; Castillo, Dan R.; McConnell, Alicia M.; Krishnaveni, Manda S.; Banfalvi, Agnes; Li, Min; Stripp, Barry; Zhou, Beiyun; Crandall, Edward D.; Minoo, Parviz

    2017-01-01

    Previous studies have demonstrated resistance to naphthalene-induced injury in proximal airways of mice with lung epithelial-specific deletion of the tumor-suppressor gene Pten, attributed to increased proliferation of airway progenitors. We tested effects of Pten loss following bleomycin injury, a model typically used to study distal lung epithelial injury, in conditional PtenSFTPC-cre knockout mice. Pten-deficient airway epithelium exhibited marked hyperplasia, particularly in small bronchioles and at bronchoalveolar duct junctions, with reduced E-cadherin and β-catenin expression between cells toward the luminal aspect of the hyperplastic epithelium. Bronchiolar epithelial and alveolar epithelial type II (AT2) cells in PtenSFTPC-cre mice showed decreased expression of epithelial markers and increased expression of mesenchymal markers, suggesting at least partial epithelial-mesenchymal transition at baseline. Surprisingly, and in contrast to previous studies, mutant mice were exquisitely sensitive to bleomycin, manifesting rapid weight loss, respiratory distress, increased early mortality (by day 5), and reduced dynamic lung compliance. This was accompanied by sloughing of the hyperplastic airway epithelium with occlusion of small bronchioles by cellular debris, without evidence of increased parenchymal lung injury. Increased airway epithelial cell apoptosis due to loss of antioxidant defenses, reflected by decreased expression of superoxide dismutase 3, in combination with deficient intercellular adhesion, likely predisposed to airway sloughing in knockout mice. These findings demonstrate an important role for Pten in maintenance of airway epithelial phenotype integrity and indicate that responses to Pten deletion in respiratory epithelium following acute lung injury are highly context-dependent and region-specific. PMID:27864284

  19. The CIDEM project for integrating availability, operating experience and maintenance in the design of future nuclear power plants

    International Nuclear Information System (INIS)

    Degrave, C.; Martin-Onraet, M.

    1998-01-01

    To minimize the kWh cost of future nuclear plants EDF has decided to implement the CIDEM project (French acronym for Design Integrating Availability, Operating Experience and Maintenance), an analytic and systematic process for studying new projects. The first CIDEM application is centered on the future French nuclear unit construction program, known as the REP 2000 Program but the approach could be applied to other Reactor type. The CIDEM studies at the beginning, were oriented to the issues strongly impacting the availability. They have concerned: planned outages, forced outages and preventive maintenance. The studies were carried out by a team grouping engineers from the 3 EDF's Divisions (Engineering-Generation-Research), and working together in a Concurrent Engineering-Mode. This team works in close collaboration with the vendors and the German Utilities involved in the REP 2000 EPR program. The implementation of the CIDEM process constitutes for EDF a new approach to the study of the new Nuclear Power Plant projects. The studies conducted in the availability field have already highlighted a number of critical points and have made it possible to establish a series of specifications for the REP 2000/EPR project. The integration in the design process of Preventive Maintenance and Logistic Support studies will allow a better control of the maintenance cost. The competitiveness of nuclear energy greatly depends on the success of such an approach. (author)

  20. Building and integrating reliability models in a Reliability-Centered-Maintenance approach

    International Nuclear Information System (INIS)

    Verite, B.; Villain, B.; Venturini, V.; Hugonnard, S.; Bryla, P.

    1998-03-01

    Electricite de France (EDF) has recently developed its OMF-Structures method, designed to optimize preventive maintenance of passive structures such as pipes and support, based on risk. In particular, reliability performances of components need to be determined; it is a two-step process, consisting of a qualitative sort followed by a quantitative evaluation, involving two types of models. Initially, degradation models are widely used to exclude some components from the field of preventive maintenance. The reliability of the remaining components is then evaluated by means of quantitative reliability models. The results are then included in a risk indicator that is used to directly optimize preventive maintenance tasks. (author)

  1. Uncertainty and sensitivity analyses for age-dependent unavailability model integrating test and maintenance

    International Nuclear Information System (INIS)

    Kančev, Duško; Čepin, Marko

    2012-01-01

    Highlights: ► Application of analytical unavailability model integrating T and M, ageing, and test strategy. ► Ageing data uncertainty propagation on system level assessed via Monte Carlo simulation. ► Uncertainty impact is growing with the extension of the surveillance test interval. ► Calculated system unavailability dependence on two different sensitivity study ageing databases. ► System unavailability sensitivity insights regarding specific groups of BEs as test intervals extend. - Abstract: The interest in operational lifetime extension of the existing nuclear power plants is growing. Consequently, plants life management programs, considering safety components ageing, are being developed and employed. Ageing represents a gradual degradation of the physical properties and functional performance of different components consequently implying their reduced availability. Analyses, which are being made in the direction of nuclear power plants lifetime extension are based upon components ageing management programs. On the other side, the large uncertainties of the ageing parameters as well as the uncertainties associated with most of the reliability data collections are widely acknowledged. This paper addresses the uncertainty and sensitivity analyses conducted utilizing a previously developed age-dependent unavailability model, integrating effects of test and maintenance activities, for a selected stand-by safety system in a nuclear power plant. The most important problem is the lack of data concerning the effects of ageing as well as the relatively high uncertainty associated to these data, which would correspond to more detailed modelling of ageing. A standard Monte Carlo simulation was coded for the purpose of this paper and utilized in the process of assessment of the component ageing parameters uncertainty propagation on system level. The obtained results from the uncertainty analysis indicate the extent to which the uncertainty of the selected

  2. Development of hardware system using temperature and vibration maintenance models integration concepts for conventional machines monitoring: A case study

    OpenAIRE

    Adeyeri, Michael Kanisuru; Mpofu, Khumbulani; Kareem, Buliaminu

    2016-01-01

    This article describes the integration of temperature and vibration models for maintenance monitoring of conventional machinery parts in which their optimal andbest functionalities are affected by abnormal changes in temperature and vibration values thereby resulting in machine failures, machines breakdown, poor quality of products, inability to meeting customers' demand, poor inventory control and just to mention a few. The work entails the use of temperature and vibration sensors as monitor...

  3. Development of an Integrated Moisture Index for predicting species composition

    Science.gov (United States)

    Louis R. Iverson; Charles T. Scott; Martin E. Dale; Anantha Prasad

    1996-01-01

    A geographic information system (GIS) approach was used to develop an Integrated Moisture Index (IMI), which was used to predict species composition for Ohio forests. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and the water-holding capacity of the soil) were derived from elevation and soils...

  4. Predictive maintenance systems in continuous mine transport installations. Case study from Puentes mine. Sistemas de mantenimiento predictivo en instalaciones mineras de transporte continuo. Casa mina de Puentes

    Energy Technology Data Exchange (ETDEWEB)

    Arechaga Rodriguez, F; Roda Vazquez, C [ENDESA, Madrid (Spain)

    1988-01-01

    At some complex mining installations it is necessary to complement the corrective and preventive maintenance with new systems that enable the detection of failures before they become evident and cause a breakdown. These systems, called predictive maintenance, use several techniques, such as: vibration control, lubricant analysis, wear control, etc. This kind of maintenance provides good results, and although it is not expensive, it requires qualified personnel and good organisation.

  5. Usefulness of a rapid faecal calprotectin test to predict relapse in Crohn's disease patients on maintenance treatment with adalimumab.

    Science.gov (United States)

    Ferreiro-Iglesias, Rocio; Barreiro-de Acosta, Manuel; Lorenzo-Gonzalez, Aurelio; Dominguez-Muñoz, Juan Enrique

    2016-01-01

    Predicting relapse in Crohn's disease (CD) patients by measuring non-invasive biomarkers could allow for early changes of treatment. Data are scarce regarding the utility of monitoring calprotectin to predict relapse. The aim of the study was to evaluate the predictive value of a rapid test of faecal calprotectin (FC) to predict for flares in CD patients on maintenance treatment with adalimumab (ADA). A prospective, observational cohort study was designed. Inclusion criteria were CD patients in clinical remission on a standard dose of ADA therapy. Fresh FC was measured using a rapid test. Thirty patients were included (median age 38 years, 56.7% female). After the 4 months follow-up, 70.0% patients remained in clinical remission and 30.0% had a relapse. FC concentration at inclusion was significantly higher in those patients who relapsed during the follow-up (625 μg/g) compared to those who stayed in remission (45 μg/g). The optimal cut-off for FC to predict relapse was 204 μg/g. The area under the receiver-operating characteristic curve was 0.968. Sensitivity, specificity, positive, and negative predictive value of FC to predict relapse were 100%, 85.7%, 74.1%, and 100%, respectively. In CD patients on ADA maintenance therapy, FC levels measured with a rapid test allow relapse over the following months to be predicted with high accuracy. Low FC levels exclude relapse within at least 4 months after testing, whereas high levels are associated with relapse in three out of every four patients.

  6. Development of predictive models for estimating warfarin maintenance dose based on genetic and clinical factors.

    Science.gov (United States)

    Yang, Lu; Linder, Mark W

    2013-01-01

    In this chapter, we use calculation of estimated warfarin maintenance dosage as an example to illustrate how to develop a multiple linear regression model to quantify the relationship between several independent variables (e.g., patients' genotype information) and a dependent variable (e.g., measureable clinical outcome).

  7. A New Biobjective Model to Optimize Integrated Redundancy Allocation and Reliability-Centered Maintenance Problems in a System Using Metaheuristics

    Directory of Open Access Journals (Sweden)

    Shima MohammadZadeh Dogahe

    2015-01-01

    Full Text Available A novel integrated model is proposed to optimize the redundancy allocation problem (RAP and the reliability-centered maintenance (RCM simultaneously. A system of both repairable and nonrepairable components has been considered. In this system, electronic components are nonrepairable while mechanical components are mostly repairable. For nonrepairable components, a redundancy allocation problem is dealt with to determine optimal redundancy strategy and number of redundant components to be implemented in each subsystem. In addition, a maintenance scheduling problem is considered for repairable components in order to identify the best maintenance policy and optimize system reliability. Both active and cold standby redundancy strategies have been taken into account for electronic components. Also, net present value of the secondary cost including operational and maintenance costs has been calculated. The problem is formulated as a biobjective mathematical programming model aiming to reach a tradeoff between system reliability and cost. Three metaheuristic algorithms are employed to solve the proposed model: Nondominated Sorting Genetic Algorithm (NSGA-II, Multiobjective Particle Swarm Optimization (MOPSO, and Multiobjective Firefly Algorithm (MOFA. Several test problems are solved using the mentioned algorithms to test efficiency and effectiveness of the solution approaches and obtained results are analyzed.

  8. Integrating the sequence dependent setup time open shop problem and preventive maintenance policies

    Directory of Open Access Journals (Sweden)

    K. Naboureh

    2016-09-01

    Full Text Available In most industrial environments, it is usually considered that machines are accessible throughout the planning horizon, but in real situation, machines may be unavailable due to a scheduled preventive maintenance where the periods of unavailability are known in advance. The main idea of this paper is to consider different preventive maintenance policies on machines regarding open shop scheduling problem (OSSP with sequence dependent setup times (SDST using immune algorithm. The preventive maintenance (PM policies are planned for maximizing availability of machines or keeping minimum level of reliability through the production horizon. The objective function of the paper is to minimize makespan. In total, the proposed algorithm extensively is compared with six adaptations of existing heuristic and meta-heuristic methods for the problem through data sets from benchmarks based on Taillard’s instances with some adjustments. The results show that the proposed algorithm outperforms other algorithms for this problem.

  9. Integrated vibration-based maintenance: an approach for continuous reduction in LCC. A case study

    Energy Technology Data Exchange (ETDEWEB)

    Najjar, B. [ER Konsult Utveckling AB, Vaexjoe (Sweden)

    1998-12-31

    The biggest thread in achieving and maintaining high equipment effectiveness can be stated as: whether the improved manufacturing processes capable of producing quality products at a competitive cost. The effect of a new vibration-based maintenance concept, called Total Quality Maintenance (TQMain), is introduced. It aims to make intensive use of the real-time data acquisition and analysis to detect causes behind product quality deviation and failures in machinery, and following defect development at an early stage to increase machine mean effective life and improve company`s economics. The effect of TQMain on LCC of machinery and company`s economics is discussed. A case study to reveal savings in maintenance cost when a vibration-based policy involved, is presented. Using TQMain, company`s economics can be improved effectively through continuous improvement of the technical and economic effectiveness of production processes. (orig.) 14 refs.

  10. Integrated vibration-based maintenance: an approach for continuous reduction in LCC. A case study

    Energy Technology Data Exchange (ETDEWEB)

    Najjar, B [ER Konsult Utveckling AB, Vaexjoe (Sweden)

    1999-12-31

    The biggest thread in achieving and maintaining high equipment effectiveness can be stated as: whether the improved manufacturing processes capable of producing quality products at a competitive cost. The effect of a new vibration-based maintenance concept, called Total Quality Maintenance (TQMain), is introduced. It aims to make intensive use of the real-time data acquisition and analysis to detect causes behind product quality deviation and failures in machinery, and following defect development at an early stage to increase machine mean effective life and improve company`s economics. The effect of TQMain on LCC of machinery and company`s economics is discussed. A case study to reveal savings in maintenance cost when a vibration-based policy involved, is presented. Using TQMain, company`s economics can be improved effectively through continuous improvement of the technical and economic effectiveness of production processes. (orig.) 14 refs.

  11. Inventory-transportation integrated optimization for maintenance spare parts of high-speed trains

    Science.gov (United States)

    Wang, Jiaxi; Wang, Huasheng; Wang, Zhongkai; Li, Jian; Lin, Ruixi; Xiao, Jie; Wu, Jianping

    2017-01-01

    This paper presents a 0–1 programming model aimed at obtaining the optimal inventory policy and transportation mode for maintenance spare parts of high-speed trains. To obtain the model parameters for occasionally-replaced spare parts, a demand estimation method based on the maintenance strategies of China’s high-speed railway system is proposed. In addition, we analyse the shortage time using PERT, and then calculate the unit time shortage cost from the viewpoint of train operation revenue. Finally, a real-world case study from Shanghai Depot is conducted to demonstrate our method. Computational results offer an effective and efficient decision support for inventory managers. PMID:28472097

  12. Brain Activation during Associative Short-Term Memory Maintenance is Not Predictive for Subsequent Retrieval

    Directory of Open Access Journals (Sweden)

    Heiko eBergmann

    2015-09-01

    Full Text Available Performance on working memory (WM tasks may partially be supported by long-term memory (LTM processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental LTM formation. We examined which brain regions actually support successful WM processing, rather than being confounded by LTM processes, during the maintenance and probe phase of a WM task. We administered a four-pair (faces and houses associative delayed-match-to-sample (WM task using event-related fMRI and a subsequent associative recognition LTM task, using the same stimuli. This enabled us to analyze subsequent memory effects for both the WM and the LTM test by contrasting correctly recognized pairs with incorrect pairs for either task. Critically, with respect to the subsequent WM effect, we computed this analysis exclusively for trials that were forgotten in the subsequent LTM recognition task. Hence, brain activity associated with successful WM processing was less likely to be confounded by incidental LTM formation. The subsequent LTM effect, in contrast, was analyzed exclusively for pairs that previously had been correctly recognized in the WM task, disclosing brain regions involved in successful LTM formation after successful WM processing. Results for the subsequent WM effect showed no significantly activated brain areas for WM maintenance, possibly due to an insensitivity of fMRI to mechanisms underlying active WM maintenance. In contrast, a correct decision at WM probe was linked to activation in the retrieval success network (anterior and posterior midline brain structures. The subsequent LTM analyses revealed greater activation in left dorsolateral prefrontal cortex and posterior parietal cortex in the early phase of the maintenance stage. No supra-threshold activation was found during the WM probe. Together, we obtained clearer insights in which brain regions support successful WM and LTM without the potential confound of the

  13. Brain activation during associative short-term memory maintenance is not predictive for subsequent retrieval.

    Science.gov (United States)

    Bergmann, Heiko C; Daselaar, Sander M; Beul, Sarah F; Rijpkema, Mark; Fernández, Guillén; Kessels, Roy P C

    2015-01-01

    Performance on working memory (WM) tasks may partially be supported by long-term memory (LTM) processing. Hence, brain activation recently being implicated in WM may actually have been driven by (incidental) LTM formation. We examined which brain regions actually support successful WM processing, rather than being confounded by LTM processes, during the maintenance and probe phase of a WM task. We administered a four-pair (faces and houses) associative delayed-match-to-sample (WM) task using event-related functional MRI (fMRI) and a subsequent associative recognition LTM task, using the same stimuli. This enabled us to analyze subsequent memory effects for both the WM and the LTM test by contrasting correctly recognized pairs with incorrect pairs for either task. Critically, with respect to the subsequent WM effect, we computed this analysis exclusively for trials that were forgotten in the subsequent LTM recognition task. Hence, brain activity associated with successful WM processing was less likely to be confounded by incidental LTM formation. The subsequent LTM effect, in contrast, was analyzed exclusively for pairs that previously had been correctly recognized in the WM task, disclosing brain regions involved in successful LTM formation after successful WM processing. Results for the subsequent WM effect showed no significantly activated brain areas for WM maintenance, possibly due to an insensitivity of fMRI to mechanisms underlying active WM maintenance. In contrast, a correct decision at WM probe was linked to activation in the "retrieval success network" (anterior and posterior midline brain structures). The subsequent LTM analyses revealed greater activation in left dorsolateral prefrontal cortex and posterior parietal cortex in the early phase of the maintenance stage. No supra-threshold activation was found during the WM probe. Together, we obtained clearer insights in which brain regions support successful WM and LTM without the potential confound of

  14. Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project.

    Science.gov (United States)

    Antonopoulos, Christos; Asimogloy, Katerina; Chiti, Sarah; D'Onofrio, Luca; Gianfranceschi, Simone; He, Danping; Iodice, Antonio; Koubias, Stavros; Koulamas, Christos; Lavagno, Luciano; Lazarescu, Mihai T; Mujica, Gabriel; Papadopoulos, George; Portilla, Jorge; Redondo, Luis; Riccio, Daniele; Riesgo, Teresa; Rodriguez, Daniel; Ruello, Giuseppe; Samoladas, Vasilis; Stoyanova, Tsenka; Touliatos, Gerasimos; Valvo, Angela; Vlahoy, Georgia

    2016-06-02

    In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN) application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes), and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site.

  15. Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project

    Directory of Open Access Journals (Sweden)

    Christos Antonopoulos

    2016-06-01

    Full Text Available In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes, and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site.

  16. Supervisory Model Predictive Control of the Heat Integrated Distillation Column

    DEFF Research Database (Denmark)

    Meyer, Kristian; Bisgaard, Thomas; Huusom, Jakob Kjøbsted

    2017-01-01

    This paper benchmarks a centralized control system based on model predictive control for the operation of the heat integrated distillation column (HIDiC) against a fully decentralized control system using the most complete column model currently available in the literature. The centralized control...... system outperforms the decentralized system, because it handles the interactions in the HIDiC process better. The integral absolute error (IAE) is reduced by a factor of 2 and a factor of 4 for control of the top and bottoms compositions, respectively....

  17. A modeling framework for deteriorating control system and predictive maintenance of actuators

    International Nuclear Information System (INIS)

    Langeron, Y.; Grall, A.; Barros, A.

    2015-01-01

    Actuators play a central role in industrial automation systems. They are costly, and therefore studying their dependability needs all attention. Usually, an actuator is inserted in a feedback control system, and its mission is to implement a control action delivered by a controller. In this paper, a monotonic actuator deterioration is considered and it is assumed that a relationship exists between the control action and the physical actuator's deterioration. A modeling framework is proposed including a non-decreasing stochastic degradation process driving the inability for an actuator to fully implement its role. The prognosis of the actuator's residual useful lifetime is derived and used to update the controller's setting. The controller reconfiguration completes the maintenance corrective and preventive actions. This new action is suggested as an alternative for maintenance strategy. - Highlights: • A degrading control system model is proposed focusing on actuator deterioration. • It is assumed a relationship between this degradation and its loss of efficiency. • The actuator RUL is quantified as a quantile of its conditional survival function. • RUL prognosis is used to reconfigure the control input law. • This new action is suggested as an alternative for maintenance strategy

  18. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  19. Intelligent control and maintenance of management integrated system based on multi-agents for coal preparation plant

    Energy Technology Data Exchange (ETDEWEB)

    Meng, F.; Wang, Y. [China University of Mining and technology, Xuzhou (China). School of Information and Electrical Engineering

    2006-06-15

    This paper discusses the progress of computer integrated processing (CIPS) of coal preparation and then presents an intelligence controlled production process, device-maintenance and production-management system of coal preparation based on multi-agents (IICMMS-CP). The construction of the IICMMS-CP, the distributed network control system based on live intelligence control stations and the strategy of implementing a distributed intelligence control system are studied in order to overcome the disadvantages brought about by the wide use of the PLC system by coal preparation plants. The software frame, based on a Multi-Agent Intelligence Control and Maintenance Management integrated system, is studied and the implementation methods of IICMMS-CP are discussed. The characteristics of distributed architecture, cooperation and parallel computing meet the needs of integrated control of coal preparation plants with large-scale spatial production distribution, densely-related processes and complex systems. Its application further improves the reliability and precision of process control, accuracy of fault identification and intelligence of production adjustment, establishes a technical basis for system integration and flexible production. The main function of the system has been tested in a coal preparation plant to good effect in stabilizing product quality, improving efficiency and reducing consumption. 17 refs., 4 figs.

  20. Integrating inventory control and capacity management at a maintenance service provider

    NARCIS (Netherlands)

    Buyukkaramikli, N.C.; Ooijen, van H.P.G.; Bertrand, J.W.M.

    2015-01-01

    In this paper, we study the capacity flexibility problem of a maintenance service provider, who is running a repair shop and is responsible for the availability of numerous specialized systems which contain a critical component that is prone to failure. Upon a critical component failure, the

  1. Pedagogical conditions of maintenance of integrity of process of socialization-individualization of children-orphans

    OpenAIRE

    Pronina A. N.

    2011-01-01

    Formation of the high-grade person of children of preschool age, without parental support should be carried out in complete process of socialization-individualization that assumes working out of the pedagogical conditions directed on maintenance of interrelation of processes of socialization and an individualization.

  2. Integration of Predictive Display and Aircraft Flight Control System

    Directory of Open Access Journals (Sweden)

    Efremov A.V.

    2017-01-01

    Full Text Available The synthesis of predictive display information and direct lift control system are considered for the path control tracking tasks (in particular landing task. The both solutions are based on pilot-vehicle system analysis and requirements to provide the highest accuracy and lowest pilot workload. The investigation was carried out for cases with and without time delay in aircraft dynamics. The efficiency of the both ways for the flying qualities improvement and their integration is tested by ground based simulation.

  3. Predicting Protein Function via Semantic Integration of Multiple Networks.

    Science.gov (United States)

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

    2016-01-01

    Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

  4. An integrated logistic formula for prediction of complications from radiosurgery

    International Nuclear Information System (INIS)

    Flickinger, J.C.

    1989-01-01

    An integrated logistic model for predicting the probability of complications when small volumes of tissue receive an inhomogeneous radiation dose is described. This model can be used with either an exponential or linear quadratic correction for dose per fraction and time. Both the exponential and linear quadratic versions of this integrated logistic formula provide reasonable estimates of the tolerance of brain to radiosurgical dose distributions where there are small volumes of brain receiving high radiation doses and larger volumes receiving lower doses. This makes it possible to predict the probability of complications from stereotactic radiosurgery, as well as combinations of fractionated large volume irradiation with a radiosurgical boost. Complication probabilities predicted for single fraction radiosurgery with the Leksell Gamma Unit using 4, 8, 14, and 18 mm diameter collimators as well as for whole brain irradiation combined with a radiosurgical boost are presented. The exponential and linear quadratic versions of the integrated logistic formula provide useful methods of calculating the probability of complications from radiosurgical treatment

  5. Age-related changes of frontal-midline theta is predictive of efficient memory maintenance.

    Science.gov (United States)

    Kardos, Z; Tóth, B; Boha, R; File, B; Molnár, M

    2014-07-25

    Frontal areas are thought to be the coordinators of working memory processes by controlling other brain areas reflected by oscillatory activities like frontal-midline theta (4-7 Hz). With aging substantial changes can be observed in the frontal brain areas, presumably leading to age-associated changes in cortical correlates of cognitive functioning. The present study aimed to test whether altered frontal-midline theta dynamics during working memory maintenance may underlie the capacity deficits observed in older adults. 33-channel EEG was recorded in young (18-26 years, N=20) and old (60-71 years, N=16) adults during the retention period of a visual delayed match-to-sample task, in which they had to maintain arrays of 3 or 5 colored squares. An additional visual odd-ball task was used to be able to measure the electrophysiological indices of sustained attentional processes. Old participants showed reduced frontal theta activity during both tasks compared to the young group. In the young memory maintenance-related frontal-midline theta activity was shown to be sensitive both to the increased memory demands and to efficient subsequent memory performance, whereas the old adults showed no such task-related difference in the frontal theta activity. The decrease of frontal-midline theta activity in the old group indicates that cerebral aging may alter the cortical circuitries of theta dynamics, thereby leading to age-associated decline of working memory maintenance function. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  6. Integrated Computational Solution for Predicting Skin Sensitization Potential of Molecules.

    Directory of Open Access Journals (Sweden)

    Konda Leela Sarath Kumar

    Full Text Available Skin sensitization forms a major toxicological endpoint for dermatology and cosmetic products. Recent ban on animal testing for cosmetics demands for alternative methods. We developed an integrated computational solution (SkinSense that offers a robust solution and addresses the limitations of existing computational tools i.e. high false positive rate and/or limited coverage.The key components of our solution include: QSAR models selected from a combinatorial set, similarity information and literature-derived sub-structure patterns of known skin protein reactive groups. Its prediction performance on a challenge set of molecules showed accuracy = 75.32%, CCR = 74.36%, sensitivity = 70.00% and specificity = 78.72%, which is better than several existing tools including VEGA (accuracy = 45.00% and CCR = 54.17% with 'High' reliability scoring, DEREK (accuracy = 72.73% and CCR = 71.44% and TOPKAT (accuracy = 60.00% and CCR = 61.67%. Although, TIMES-SS showed higher predictive power (accuracy = 90.00% and CCR = 92.86%, the coverage was very low (only 10 out of 77 molecules were predicted reliably.Owing to improved prediction performance and coverage, our solution can serve as a useful expert system towards Integrated Approaches to Testing and Assessment for skin sensitization. It would be invaluable to cosmetic/ dermatology industry for pre-screening their molecules, and reducing time, cost and animal testing.

  7. Prediction of rotor blade-vortex interaction using Volterra integrals

    Energy Technology Data Exchange (ETDEWEB)

    Wong, A.; Nitzsche, F. [Carleton Univ., Dept. of Mechanical and Aerospace Engineering, Ottawa, Ontario (Canada)]. E-mail: Fred_Nitzsche@carleton.ca; Khalid, M. [National Research Council Canada, Inst. for Aerospace Research, Ottawa, Ontario (Canada)

    2004-07-01

    The theory of Volterra integral equations for nonlinear system is applied to the prediction of the nonlinear aerodynamic response of an NACA 0012 airfoil experiencing blade-vortex interaction. The phenomenon is first modeled in two-dimensions using an Euler/Navier-Stoke code, and the resulting unsteady aerodynamic flow field sequences are appropriately combined to form a training dataset. The Volterra kernels are identified in the time-domain characteristics of the selected data, which is in turn used to predict the nonlinear aerodynamic response of the airfoil. The Volterra kernel based data is then compared against a standard airfoil response. The predicted lift time histories of the airfoil are shown to be in good agreement with the aerodynamic data. (author)

  8. Prediction of rotor blade-vortex interaction using Volterra integrals

    International Nuclear Information System (INIS)

    Wong, A.; Nitzsche, F.; Khalid, M.

    2004-01-01

    The theory of Volterra integral equations for nonlinear system is applied to the prediction of the nonlinear aerodynamic response of an NACA 0012 airfoil experiencing blade-vortex interaction. The phenomenon is first modeled in two-dimensions using an Euler/Navier-Stoke code, and the resulting unsteady aerodynamic flow field sequences are appropriately combined to form a training dataset. The Volterra kernels are identified in the time-domain characteristics of the selected data, which is in turn used to predict the nonlinear aerodynamic response of the airfoil. The Volterra kernel based data is then compared against a standard airfoil response. The predicted lift time histories of the airfoil are shown to be in good agreement with the aerodynamic data. (author)

  9. Optimizing preventive maintenance with maintenance templates

    International Nuclear Information System (INIS)

    Dozier, I.J.

    1996-01-01

    Rising operating costs has caused maintenance professionals to rethink their strategy for preventive maintenance (PM) programs. Maintenance Templates are pre-engineered PM task recommendations for a component type based on application of the component. Development of the maintenance template considers the dominant failure cause of the component and the type of preventive maintenance that can predict or prevent the failure from occurring. Maintenance template development also attempts to replace fixed frequency tasks with condition monitoring tasks such as vibration analysis or thermography. For those components that have fixed frequency PM intervals, consideration is given to the maintenance drivers such as criticality, environment and usage. This helps to maximize the PM frequency intervals and maximize the component availability. Maintenance Templates have been used at PECO Energy's Limerick Generating Station during the Reliability Centered Maintenance (RCM) Process to optimize their PM program. This paper describes the development and uses of the maintenance templates

  10. Perceptions That Influence the Maintenance of Scientific Integrity in Community-Based Participatory Research

    Science.gov (United States)

    Kraemer Diaz, Anne E.; Spears Johnson, Chaya R.; Arcury, Thomas A.

    2015-01-01

    Scientific integrity is necessary for strong science; yet many variables can influence scientific integrity. In traditional research, some common threats are the pressure to publish, competition for funds, and career advancement. Community-based participatory research (CBPR) provides a different context for scientific integrity with additional and…

  11. Fanconi anemia complementation group A (FANCA) localizes to centrosomes and functions in the maintenance of centrosome integrity.

    Science.gov (United States)

    Kim, Sunshin; Hwang, Soo Kyung; Lee, Mihee; Kwak, Heejin; Son, Kook; Yang, Jiha; Kim, Sung Hak; Lee, Chang-Hun

    2013-09-01

    Fanconi anemia (FA) proteins are known to play roles in the cellular response to DNA interstrand cross-linking lesions; however, several reports have suggested that FA proteins play additional roles. To elucidate novel functions of FA proteins, we used yeast two-hybrid screening to identify binding partners of the Fanconi anemia complementation group A (FANCA) protein. The candidate proteins included never-in-mitosis-gene A (NIMA)-related kinase 2 (Nek2), which functions in the maintenance of centrosome integrity. The interaction of FANCA and Nek2 was confirmed in human embryonic kidney (HEK) 293T cells. Furthermore, FANCA interacted with γ-tubulin and localized to centrosomes, most notably during the mitotic phase, confirming that FANCA is a centrosomal protein. Knockdown of FANCA increased the frequency of centrosomal abnormalities and enhanced the sensitivity of U2OS osteosarcoma cells to nocodazole, a microtubule-interfering agent. In vitro kinase assays indicated that Nek2 can phosphorylate FANCA at threonine-351 (T351), and analysis with a phospho-specific antibody confirmed that this phosphorylation occurred in response to nocodazole treatment. Furthermore, U2OS cells overexpressing the phosphorylation-defective T351A FANCA mutant showed numerical centrosomal abnormalities, aberrant mitotic arrest, and enhanced nocodazole sensitivity, implying that the Nek2-mediated T351 phosphorylation of FANCA is important for the maintenance of centrosomal integrity. Taken together, this study revealed that FANCA localizes to centrosomes and is required for the maintenance of centrosome integrity, possibly through its phosphorylation at T351 by Nek2. Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Business process modeling of industrial maintenance at TRANSPETRO: integrating oil pipeline and marine terminals activities

    Energy Technology Data Exchange (ETDEWEB)

    Arruda, Daniela Mendonca; Oliveira, Italo Luiz [TRANSPETRO - PETROBRAS Transporte S.A., Rio de Janeiro, RJ (Brazil). Diretoria de Terminais e Oleodutos; Almeida, Maria Fatima Ludovico de [Pontificia Universidade Catolica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ (Brazil). Programa de Pos-Graduacao em Metrologia para Qualidade e Inovacao

    2009-07-01

    This paper describes the experience of TRANSPETRO in remodeling industrial maintenance activities focusing on: preparing for business process modeling (BPM); mapping and analyzing 'As-Is' process; designing 'To-Be' process; implementing remodeled process; improving process continuously. The conceptual model and results achieved will contribute to several areas within the company as: reliability engineering; human resources, including employees' selective processes, training and development, and certifications; standardization process encompassing standard and operational procedures adoption according to up-dating external normative references and legal requirements; health, safety and environment (HSE) performance improvement. These are some of potential benefits from BPM focusing on TRANSPETRO's industrial maintenance area in the search of operational excellence. (author)

  13. An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart

    International Nuclear Information System (INIS)

    Panagiotidou, Sofia; Nenes, George

    2009-01-01

    This paper proposes a model for the economic design of a variable-parameter (Vp) Shewhart control chart used to monitor the mean in a process, where, apart from quality shifts, failures may also occur. Quality shifts result in poorer quality outcome, higher operational cost and higher failure rate. Thus, removal of such quality shifts, besides improving the quality of the outcome and reducing the quality cost, is also a preventive maintenance (PM) action since it reduces the probability of a failure and improves the equipment reliability. The proposed model allows the determination of the scheme parameters that minimize the total expected quality and maintenance cost of the procedure. The monitoring mechanism of the process employs an adaptive Vp-Shewhart control chart. To evaluate the effectiveness of the proposed model, its optimal expected cost is compared against the optimum cost of a fixed-parameter (Fp) chart

  14. Integrated Life-Cycle Framework for Maintenance, Monitoring and Reliability of Naval Ship Structures

    Science.gov (United States)

    2012-08-15

    uncertainty in quantitative risk and policy analysis, Cambridge Univer- sity Press. NEVES, L. C, FRANGOPOL, D. M., AND CRUZ , P. J. 2006 Probabilistic lifetime...L. C, FRANGOPOL, D. M., AND CRUZ , P. J. 2006 Probabilistic life- time-oriented multiobjective optimization of bridge maintenance: single...Wright Aeronautical Laboratory. Wright- Patterson Air Force Base, Dayton, Ohio; 1981. [5| Chung H-Y, Manuel L, Frank KH. Optimal inspection

  15. An application of oscillation-damped motion for suspended payloads to the advanced integrated maintenance system in fuel cycle facilities

    International Nuclear Information System (INIS)

    Noakes, M.W.; Petterson, B.J.; Werner, J.C.

    1990-01-01

    The transportation of objects using overhead cranes can induce pendular motion of the object, which usually must be damped or allowed to decay before the next process can take place. Recent work at Sandia National Laboratories has shown that oscillation-damped transport and swing-free stops are possible by properly programming the acceleration of the transporting crane. Initial studies have been completed using a CIMCORP XR6100 gantry robot. The Advanced Integrated Maintenance System (AIMS) is an engineering and operations test bed developed for remote maintenance and handling studies within the Consolidated Fuel Reprocessing Program (CFRP) at Oak Ridge National Laboratory. The goal of CFRP has been to advanced the technology of in-cell systems planned for future nuclear fuel cycle facilities. The AIMS provides the capabilities to examine the needs and constraints necessary for hot-cell remote maintenance and includes a force-reflecting master/slave teleoperator and overhead transporter system. The associated control system provides a flexible programming environment conducive to controls experimentation. This paper reviews the theory associated with oscillation-damped trajectories for simply suspended objects and describes a specific implementation of the oscillation damping methods for the AIMS transporter. Hardware and software requirements and constraints for proper operation are discussed

  16. A prediction method based on grey system theory in equipment condition based maintenance

    International Nuclear Information System (INIS)

    Yan, Shengyuan; Yan, Shengyuan; Zhang, Hongguo; Zhang, Zhijian; Peng, Minjun; Yang, Ming

    2007-01-01

    Grey prediction is a modeling method based on historical or present, known or indefinite information, which can be used for forecasting the development of the eigenvalues of the targeted equipment system and setting up the model by using less information. In this paper, the postulate of grey system theory, which includes the grey generating, the sorts of grey generating and the grey forecasting model, is introduced first. The concrete application process, which includes the grey prediction modeling, grey prediction, error calculation, equal dimension and new information approach, is introduced secondly. Application of a so-called 'Equal Dimension and New Information' (EDNI) technology in grey system theory is adopted in an application case, aiming at improving the accuracy of prediction without increasing the amount of calculation by replacing old data with new ones. The proposed method can provide a new way for solving the problem of eigenvalue data exploding in equal distance effectively, short time interval and real time prediction. The proposed method, which was based on historical or present, known or indefinite information, was verified by the vibration prediction of induced draft fan of a boiler of the Yantai Power Station in China, and the results show that the proposed method based on grey system theory is simple and provides a high accuracy in prediction. So, it is very useful and significant to the controlling and controllable management in safety production. (authors)

  17. Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

    Science.gov (United States)

    Zelinski, Shannon; Windhorst, Robert

    2016-01-01

    A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

  18. PRISMA: Program of Research to Integrate the Services for the Maintenance of Autonomy. A system-level integration model in Quebec

    Directory of Open Access Journals (Sweden)

    Margaret MacAdam

    2015-09-01

    Full Text Available The Program of Research to Integrate the Services for the Maintenance of Autonomy (PRISMA began in Quebec in 1999. Evaluation results indicated that the PRISMA Project improved the system of care for the frail elderly at no additional cost. In 2001, the Quebec Ministry of Health and Social Services made implementing the six features of the PRISMA approach a province-wide goal in the programme now known as RSIPA (French acronym. Extensive Province-wide progress has been made since then, but ongoing challenges include reducing unmet need for case management and home care services, creating incentives for increased physician participation in care planning and improving the computerized client chart, among others. PRISMA is the only evaluated international model of a coordination approach to integration and one of the few, if not the only, integration model to have been adopted at the system level by policy-makers.

  19. Perceptions that influence the maintenance of scientific integrity in community-based participatory research.

    Science.gov (United States)

    Kraemer Diaz, Anne E; Spears Johnson, Chaya R; Arcury, Thomas A

    2015-06-01

    Scientific integrity is necessary for strong science; yet many variables can influence scientific integrity. In traditional research, some common threats are the pressure to publish, competition for funds, and career advancement. Community-based participatory research (CBPR) provides a different context for scientific integrity with additional and unique concerns. Understanding the perceptions that promote or discourage scientific integrity in CBPR as identified by professional and community investigators is essential to promoting the value of CBPR. This analysis explores the perceptions that facilitate scientific integrity in CBPR as well as the barriers among a sample of 74 professional and community CBPR investigators from 25 CBPR projects in nine states in the southeastern United States in 2012. There were variations in perceptions associated with team member identity as professional or community investigators. Perceptions identified to promote and discourage scientific integrity in CBPR by professional and community investigators were external pressures, community participation, funding, quality control and supervision, communication, training, and character and trust. Some perceptions such as communication and training promoted scientific integrity whereas other perceptions, such as a lack of funds and lack of trust could discourage scientific integrity. These results demonstrate that one of the most important perceptions in maintaining scientific integrity in CBPR is active community participation, which enables a co-responsibility by scientists and community members to provide oversight for scientific integrity. Credible CBPR science is crucial to empower the vulnerable communities to be heard by those in positions of power and policy making. © 2015 Society for Public Health Education.

  20. Improving linear transport infrastructure efficiency by automated learning and optimised predictive maintenance techniques (INFRALERT)

    Science.gov (United States)

    Jiménez-Redondo, Noemi; Calle-Cordón, Alvaro; Kandler, Ute; Simroth, Axel; Morales, Francisco J.; Reyes, Antonio; Odelius, Johan; Thaduri, Aditya; Morgado, Joao; Duarte, Emmanuele

    2017-09-01

    The on-going H2020 project INFRALERT aims to increase rail and road infrastructure capacity in the current framework of increased transportation demand by developing and deploying solutions to optimise maintenance interventions planning. It includes two real pilots for road and railways infrastructure. INFRALERT develops an ICT platform (the expert-based Infrastructure Management System, eIMS) which follows a modular approach including several expert-based toolkits. This paper presents the methodologies and preliminary results of the toolkits for i) nowcasting and forecasting of asset condition, ii) alert generation, iii) RAMS & LCC analysis and iv) decision support. The results of these toolkits in a meshed road network in Portugal under the jurisdiction of Infraestruturas de Portugal (IP) are presented showing the capabilities of the approaches.

  1. Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

    Science.gov (United States)

    Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

    2013-01-01

    Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

  2. Reverse gyrase functions in genome integrity maintenance by protecting DNA breaks in vivo

    DEFF Research Database (Denmark)

    Han, Wenyuan; Feng, Xu; She, Qunxin

    2017-01-01

    Reverse gyrase introduces positive supercoils to circular DNA and is implicated in genome stability maintenance in thermophiles. The extremely thermophilic crenarchaeon Sulfolobus encodes two reverse gyrase proteins, TopR1 (topoisomerase reverse gyrase 1) and TopR2, whose functions in thermophilic...... and subsequent DNA degradation. The former occurred immediately after drug treatment, leading to chromosomal DNA degradation that concurred with TopR1 degradation, followed by chromatin protein degradation and DNA-less cell formation. To gain a further insight into TopR1 function, the expression of the enzyme...

  3. Predictive Solar-Integrated Commercial Building Load Control

    Energy Technology Data Exchange (ETDEWEB)

    Glasgow, Nathan [EdgePower Inc., Aspen, CO (United States)

    2017-01-31

    This report is the final technical report for the Department of Energy SunShot award number EE0007180 to EdgePower Inc., for the project entitled “Predictive Solar-Integrated Commercial Building Load Control.” The goal of this project was to successfully prove that the integration of solar forecasting and building load control can reduce demand charge costs for commercial building owners with solar PV. This proof of concept Tier 0 project demonstrated its value through a pilot project at a commercial building. This final report contains a summary of the work completed through he duration of the project. Clean Power Research was a sub-recipient on the award.

  4. Scale Expansion of Community Investigations and Integration of the Effects of Abiotic and Biotic Processes on Maintenance of Species Diversity

    Directory of Open Access Journals (Sweden)

    Zhenhong Wang

    2011-01-01

    Full Text Available Information on the maintenance of diversity patterns from regional to local scales is dispersed among academic fields due to the local focus of community ecology. To better understand these patterns, the study of ecological communities needs to be expanded to larger scales and the various processes affecting them need to be integrated using a suitable quantitative method. We determined a range of communities on a flora-subregional scale in Yunnan province, China (383210.02 km2. A series of species pools were delimited from the regional to plot scales. Plant diversity was evaluated and abiotic and biotic processes identified at each pool level. The species pool effect was calculated using an innovative model, and the contribution of these processes to the maintenance of plant species diversity was determined and integrated: climate had the greatest effect at the flora-subregional scale, with historical and evolutionary processes contributing ∼11%; climate and human disturbance had the greatest effect at the local site pool scale; competition exclusion and stress limitation explained strong filtering at the successional stage pool scale; biotic processes contributed more on the local community scale than on the regional scale. Scale expansion combined with the filtering model approach solves the local problem in community ecology.

  5. Vibration vector monitoring of rotating machinery: A predictive/preventative maintenance technique

    International Nuclear Information System (INIS)

    Humes, B.R.

    1990-01-01

    Monitoring of overall vibration amplitudes to indicate machinery faults is a standard practice in most industries. The appearance of shaft cracks in machines retrofitted for extended life have prompted development of higher levels of machinery monitoring. Part 1 of this paper discusses vibration vector monitoring for machinery malfunction prediction and failure prevention. Machinery faults which can be diagnosed by this type of monitoring, such as rotor rubs, loose parts, shaft cracks, ..., are presented along with their most common characteristics. The newest, most effective methods of permanent machinery monitoring are presented and critiqued. An extensive case history is presented in Part 2 in which a potentially disastrous machinery fault was predicted using vibration vector monitoring and analysis. The addition of vector monitoring to the normal, overall vibration monitoring proved more effective in diagnosing the machinery fault and predicting impending failure

  6. Integrated predictive modelling simulations of burning plasma experiment designs

    International Nuclear Information System (INIS)

    Bateman, Glenn; Onjun, Thawatchai; Kritz, Arnold H

    2003-01-01

    Models for the height of the pedestal at the edge of H-mode plasmas (Onjun T et al 2002 Phys. Plasmas 9 5018) are used together with the Multi-Mode core transport model (Bateman G et al 1998 Phys. Plasmas 5 1793) in the BALDUR integrated predictive modelling code to predict the performance of the ITER (Aymar A et al 2002 Plasma Phys. Control. Fusion 44 519), FIRE (Meade D M et al 2001 Fusion Technol. 39 336), and IGNITOR (Coppi B et al 2001 Nucl. Fusion 41 1253) fusion reactor designs. The simulation protocol used in this paper is tested by comparing predicted temperature and density profiles against experimental data from 33 H-mode discharges in the JET (Rebut P H et al 1985 Nucl. Fusion 25 1011) and DIII-D (Luxon J L et al 1985 Fusion Technol. 8 441) tokamaks. The sensitivities of the predictions are evaluated for the burning plasma experimental designs by using variations of the pedestal temperature model that are one standard deviation above and below the standard model. Simulations of the fusion reactor designs are carried out for scans in which the plasma density and auxiliary heating power are varied

  7. Prediction of Maintenance Period of Equipment Through Risk Assessment of Thermal Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    Song, Gee Wook; Kim, Bum Shin; Choi, Woo Song; Park, Myung Soo [KEPCO Research Institute, Daejeon (Korea, Republic of)

    2013-10-15

    Risk-based inspection (RBI) is a well-known method that is used to optimize inspection activities based on risk analysis in order to identify the high-risk components of major facilities such as power plants. RBI, when implemented and maintained properly, improves plant reliability and safety while reducing unplanned outages and repair costs. Risk is given by the product of the probability of failure (Pof) and the consequence of failure (COF). A semi-quantitative method is generally used for risk assessment. Semi-quantitative risk assessment complements the low accuracy of qualitative risk assessment and the high expense and long calculation time of quantitative risk assessment. The first step of RB I is to identify important failure modes and causes in the equipment. Once these are defined, the Pof and COF can be assessed for each failure. During Pof and COF assessment, an effective inspection method and range can be easily found. In this paper, the calculation of the Pof is improved for accurate risk assessment. A modified semi-quantitative risk assessment was carried out for boiler facilities of thermal power plants, and the next maintenance schedules for the equipment were decided.

  8. Prediction of Maintenance Period of Equipment Through Risk Assessment of Thermal Power Plants

    International Nuclear Information System (INIS)

    Song, Gee Wook; Kim, Bum Shin; Choi, Woo Song; Park, Myung Soo

    2013-01-01

    Risk-based inspection (RBI) is a well-known method that is used to optimize inspection activities based on risk analysis in order to identify the high-risk components of major facilities such as power plants. RBI, when implemented and maintained properly, improves plant reliability and safety while reducing unplanned outages and repair costs. Risk is given by the product of the probability of failure (Pof) and the consequence of failure (COF). A semi-quantitative method is generally used for risk assessment. Semi-quantitative risk assessment complements the low accuracy of qualitative risk assessment and the high expense and long calculation time of quantitative risk assessment. The first step of RB I is to identify important failure modes and causes in the equipment. Once these are defined, the Pof and COF can be assessed for each failure. During Pof and COF assessment, an effective inspection method and range can be easily found. In this paper, the calculation of the Pof is improved for accurate risk assessment. A modified semi-quantitative risk assessment was carried out for boiler facilities of thermal power plants, and the next maintenance schedules for the equipment were decided

  9. Initial Weight Loss after Restrictive Bariatric Procedures May Predict Mid-Term Weight Maintenance: Results From a 12-Month Pilot Trial

    OpenAIRE

    Nikolić, Marko; Kruljac, Ivan; Kirigin, Lora; Mirošević, Gorana; Ljubičić, Neven; Nikolić, Borka Pezo; Bekavac-Bešlin, Miroslav; Budimir, Ivan; Vrkljan, Milan

    2015-01-01

    Background: Bariatric procedures are effective options for weight loss (WL) in the morbidly obese. However, some patients fail to lose any weight after bariatric surgery, and mid-term weight maintenance is variable. The aim of this study was to investigate whether initial WL could predict mid-term weight maintenance. ----- Methods: Eighty patients were enrolled, of whom 44 were treated with the BioEnterics Intragastric Balloon (BIB), 21 with laparoscopic adjustable gastric lap-banding (LAGB),...

  10. User Feedback on RFID and Integrated Flightline Data for Maintenance Decisions

    National Research Council Canada - National Science Library

    Gallimore, Jennie J; Quill, Laurie; Cagle, Ron; Gruenke, Jessica; Hosman, Chris; Matthews, Elizabeth; Faas, Paul; Seyba, Jason; Young, Ian

    2006-01-01

    .... Real time sensing technologies are being investigated to improve logistics support. The purpose of this study was to investigate integrated Radio Frequency Identification/Real Time Location System (RFID/RTLS...

  11. Validation of the European Prototype for Integrated Care at Municipal Level in Savona: Updating and Maintenance

    National Research Council Canada - National Science Library

    Giacomini, M

    2001-01-01

    .... One of the validation site of EPIC was established in Savona (Italy). Subsequently the system in Savona has gone through successful validation and increasing integration with the region's health and social care system...

  12. A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions.

    Science.gov (United States)

    Cheung, C Y Maurice; Williams, Thomas C R; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

    2013-09-01

    Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance. © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

  13. Survival predictability of lean and fat mass in men and women undergoing maintenance hemodialysis.

    Science.gov (United States)

    Noori, Nazanin; Kovesdy, Csaba P; Dukkipati, Ramanath; Kim, Youngmee; Duong, Uyen; Bross, Rachelle; Oreopoulos, Antigone; Luna, Amanda; Benner, Debbie; Kopple, Joel D; Kalantar-Zadeh, Kamyar

    2010-11-01

    Larger body size is associated with greater survival in maintenance hemodialysis (MHD) patients. It is not clear how lean body mass (LBM) and fat mass (FM) compare in their associations with survival across sex in these patients. We examined the hypothesis that higher FM and LBM are associated with greater survival in MHD patents irrespective of sex. In 742 MHD patients, including 31% African Americans with a mean (± SD) age of 54 ± 15 y, we categorized men (n = 391) and women (n = 351) separately into 4 quartiles of near-infrared interactance-measured LBM and FM. Cox proportional hazards models estimated death hazard ratios (HRs) (and 95% CIs), and cubic spline models were used to examine associations with mortality over 5 y (2001-2006). After adjustment for case-mix and inflammatory markers, the highest quartiles of FM and LBM were associated with greater survival in women: HRs of 0.38 (95% CI: 0.20, 0.71) and 0.34 (95% CI: 0.17, 0.67), respectively (reference: first quartile). In men, the highest quartiles of FM and percentage FM (FM%) but not of LBM were associated with greater survival: HRs of 0.51 (95% CI: 0.27, 0.96), 0.45 (95% CI: 0.23, 0.88), and 1.17 (95% CI: 0.60, 2.27), respectively. Cubic spline analyses showed greater survival with higher FM% and higher "FM minus LBM percentiles" in both sexes, whereas a higher LBM was protective in women. In MHD patients, higher FM in both sexes and higher LBM in women appear to be protective. The survival advantage of FM appears to be superior to that of LBM. Clinical trials to examine the outcomes of interventions that modify body composition in MHD patients are indicated.

  14. Amygdala Reactivity and Anterior Cingulate Habituation Predict Posttraumatic Stress Disorder Symptom Maintenance After Acute Civilian Trauma.

    Science.gov (United States)

    Stevens, Jennifer S; Kim, Ye Ji; Galatzer-Levy, Isaac R; Reddy, Renuka; Ely, Timothy D; Nemeroff, Charles B; Hudak, Lauren A; Jovanovic, Tanja; Rothbaum, Barbara O; Ressler, Kerry J

    2017-06-15

    Studies suggest that exaggerated amygdala reactivity is a vulnerability factor for posttraumatic stress disorder (PTSD); however, our understanding is limited by a paucity of prospective, longitudinal studies. Recent studies in healthy samples indicate that, relative to reactivity, habituation is a more reliable biomarker of individual differences in amygdala function. We investigated reactivity of the amygdala and cortical areas to repeated threat presentations in a prospective study of PTSD. Participants were recruited from the emergency department of a large level I trauma center within 24 hours of trauma. PTSD symptoms were assessed at baseline and approximately 1, 3, 6, and 12 months after trauma. Growth curve modeling was used to estimate symptom recovery trajectories. Thirty-one individuals participated in functional magnetic resonance imaging around the 1-month assessment, passively viewing fearful and neutral face stimuli. Reactivity (fearful > neutral) and habituation to fearful faces was examined. Amygdala reactivity, but not habituation, 5 to 12 weeks after trauma was positively associated with the PTSD symptom intercept and predicted symptoms at 12 months after trauma. Habituation in the ventral anterior cingulate cortex was positively associated with the slope of PTSD symptoms, such that decreases in ventral anterior cingulate cortex activation over repeated presentations of fearful stimuli predicted increasing symptoms. Findings point to neural signatures of risk for maintaining PTSD symptoms after trauma exposure. Specifically, chronic symptoms were predicted by amygdala hyperreactivity, and poor recovery was predicted by a failure to maintain ventral anterior cingulate cortex activation in response to fearful stimuli. The importance of identifying patients at risk after trauma exposure is discussed. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  15. A Novel Role of Human Holliday Junction Resolvase GEN1 in the Maintenance of Centrosome Integrity

    DEFF Research Database (Denmark)

    Gao, M.; Danielsen, Jannie Michaela Rendtlew; Wei, L.-Z.

    2012-01-01

    but not catalytic activity of GEN1 is required for preventing centrosome hyper-amplification, formation of multiple mitotic spindles, and multi-nucleation. Our findings provide novel insight into the biological functions of GEN1 by uncovering an important role of GEN1 in the regulation of centrosome integrity....

  16. A new theoretical approach to the functional meaning of sleep and dreaming in humans based on the maintenance of 'predictive psychic homeostasis'.

    Science.gov (United States)

    Agnati, Luigi F; Barlow, Peter W; Baluška, František; Tonin, Paolo; Guescini, Michele; Leo, Giuseppina; Fuxe, Kjell

    2011-11-01

    Different theories have been put forward during the last decade to explain the functional meaning of sleep and dreaming in humans. In the present paper, a new theory is presented which, while taking advantage of these earlier theories, introduces the following new and original aspects:   • Circadian rhythms relevant to various organs of the body affect the reciprocal interactions which operate to maintain constancy of the internal milieu and thereby also affect the sleep/wakefulness cycle. Particular attention is given to the constancy of natraemia and osmolarity and to the permissive role that the evolution of renal function has had for the evolution of the central nervous system and its integrative actions. • The resetting of neuro-endocrine controls at the onset of wakefulness leads to the acquisition of new information and its integration within previously stored memories. This point is dealt with in relation to Moore-Ede's proposal for the existence of a 'predictive homeostasis'. • The concept of 'psychic homeostasis' is introduced and is considered as one of the most important states since it is aimed at the well-being, or eudemonia, of the human psyche. Sleep and dreaming in humans are discussed as important functions for the maintenance of a newly proposed composite state: that of 'predictive psychic homeostasis'. On the basis of these assumptions, and in accordance with the available neurobiological data, the present paper puts forward the novel hypothesis that sleep and dreaming play important functions in humans by compensating for psychic allostatic overloads. Hence, both consolatory dreams and disturbing nightmares can be part of the vis medicatrix naturae, the natural healing power, in this case, the state of eudemonia.

  17. Guide to integrated management systems for industrial maintenance contractors; Guia de sistemas de gestao integrada para contratadas de manutencao industrial

    Energy Technology Data Exchange (ETDEWEB)

    Ruella, Nildemar Correa [PETROBRAS, Rio de Janeiro, RJ (Brazil); Lima, Gilson Brito Alves [Universidade Federal Fluminense (UFF), Niteroi, RJ (Brazil)

    2004-07-01

    Presentation of an integrated management systems guide to hired of services of industrial maintenance with base in the management systems normative requisites and guides of the quality (ISO 9001, ISO 9004, ISO TS 29001 e API SPEC Q1), of environmental management systems (ISO 14001 and ISO 14004), of safety and occupational health management systems (BSI BS 8800, BSI OHSAS 18001, BSI OHSAS 18002 and ILO OSH 2001), of social accountability (SA 8000 and Implementation Guide of the SA 8000), publications and recommended practices (API RP 76, API RP 2220, API RP 2221, API Publ 9100 Publ A/B, API RP 760, API RP 761, AS/NZS 4581, CCS OAUPE009, ARPEL Guide N. 1, OGP Report No. 6.36/210, OGP Report No. 6.64/291, etc) and success experiences in the Brazil petroleum and gas industry. (author)

  18. Rac1 is crucial for hair follicle integrity but is not essential for maintenance of the epidermis

    DEFF Research Database (Denmark)

    Chrostek, Anna; Wu, Xunwei; Quondamatteo, Fabio

    2006-01-01

    Rac1 is a small GTPase that regulates the actin cytoskeleton but also other cellular processes. To investigate the function of Rac1 in skin, we generated mice with a keratinocyte-restricted deletion of the rac1 gene. Rac1-deficient mice lost nearly all of their hair within a few weeks after birth....... The nonpermanent part of mutant hair follicles developed constrictions; lost expression of hair follicle-specific keratins, E-cadherin, and alpha6 integrin; and was eventually removed by macrophages. The permanent part of hair follicles and the sebaceous glands were maintained, but no regrowth of full-length hair...... defect and slightly impaired adhesion. These data show that Rac1 plays an important role in sustaining the integrity of the lower part of hair follicles but not in maintenance of the epidermis....

  19. Thermal cracking performance prediction and asset management integration.

    Science.gov (United States)

    2011-03-01

    With shrinking maintenance budgets and the need to do more with less, accurate, robust asset management tools are greatly needed for the transportation engineering community. In addition, the increased use of recycled materials and low energy p...

  20. Calibration model maintenance in melamine resin production: Integrating drift detection, smart sample selection and model adaptation.

    Science.gov (United States)

    Nikzad-Langerodi, Ramin; Lughofer, Edwin; Cernuda, Carlos; Reischer, Thomas; Kantner, Wolfgang; Pawliczek, Marcin; Brandstetter, Markus

    2018-07-12

    The physico-chemical properties of Melamine Formaldehyde (MF) based thermosets are largely influenced by the degree of polymerization (DP) in the underlying resin. On-line supervision of the turbidity point by means of vibrational spectroscopy has recently emerged as a promising technique to monitor the DP of MF resins. However, spectroscopic determination of the DP relies on chemometric models, which are usually sensitive to drifts caused by instrumental and/or sample-associated changes occurring over time. In order to detect the time point when drifts start causing prediction bias, we here explore a universal drift detector based on a faded version of the Page-Hinkley (PH) statistic, which we test in three data streams from an industrial MF resin production process. We employ committee disagreement (CD), computed as the variance of model predictions from an ensemble of partial least squares (PLS) models, as a measure for sample-wise prediction uncertainty and use the PH statistic to detect changes in this quantity. We further explore supervised and unsupervised strategies for (semi-)automatic model adaptation upon detection of a drift. For the former, manual reference measurements are requested whenever statistical thresholds on Hotelling's T 2 and/or Q-Residuals are violated. Models are subsequently re-calibrated using weighted partial least squares in order to increase the influence of newer samples, which increases the flexibility when adapting to new (drifted) states. Unsupervised model adaptation is carried out exploiting the dual antecedent-consequent structure of a recently developed fuzzy systems variant of PLS termed FLEXFIS-PLS. In particular, antecedent parts are updated while maintaining the internal structure of the local linear predictors (i.e. the consequents). We found improved drift detection capability of the CD compared to Hotelling's T 2 and Q-Residuals when used in combination with the proposed PH test. Furthermore, we found that active

  1. Improvements to executive function during exercise training predict maintenance of physical activity over the following year

    Directory of Open Access Journals (Sweden)

    John eBest

    2014-05-01

    Full Text Available Previous studies have shown that exercise training benefits cognitive, neural, and physical health markers in older adults. It is likely that these positive effects will diminish if participants return to sedentary lifestyles following training cessation. Theory posits that that the neurocognitive processes underlying self-regulation, namely executive function (EF, are important to maintaining positive health behaviors. Therefore, we examined whether better EF performance in older women would predict greater adherence to routine physical activity (PA over 1 year following a 12-month resistance exercise training randomized controlled trial. The study sample consisted of 125 community-dwelling women aged 65 to 75 years old. Our primary outcome measure was self-reported PA, as measured by the Physical Activity Scale for the Elderly (PASE, assessed on a monthly basis from month 13 to month 25. Executive function was assessed using the Stroop Test at baseline (month 0 and post-training (month 12. Latent growth curve analyses showed that, on average, PA decreased during the follow-up period but at a decelerating rate. Women who made greater improvements to EF during the training period showed better adherence to PA during the 1-year follow-up period (β = -.36, p .10. Overall, these findings suggest that improving EF plays an important role in whether older women maintain higher levels of PA following exercise training and that this association is only apparent after training when environmental support for PA is low.

  2. Microgravity Disturbance Predictions in the Combustion Integrated Rack

    Science.gov (United States)

    Just, M.; Grodsinsky, Carlos M.

    2002-01-01

    This paper will focus on the approach used to characterize microgravity disturbances in the Combustion Integrated Rack (CIR), currently scheduled for launch to the International Space Station (ISS) in 2005. Microgravity experiments contained within the CIR are extremely sensitive to vibratory and transient disturbances originating on-board and off-board the rack. Therefore, several techniques are implemented to isolate the critical science locations from external vibration. A combined testing and analysis approach is utilized to predict the resulting microgravity levels at the critical science location. The major topics to be addressed are: 1) CIR Vibration Isolation Approaches, 2) Disturbance Sources and Characterization, 3) Microgravity Predictive Modeling, 4) Science Microgravity Requirements, 6) Microgravity Control, and 7) On-Orbit Disturbance Measurement. The CIR is using the Passive Rack Isolation System (PaRIS) to isolate the rack from offboard rack disturbances. By utilizing this system, CIR is connected to the U.S. Lab module structure by either 13 or 14 umbilical lines and 8 spring / damper isolators. Some on-board CIR disturbers are locally isolated by grommets or wire ropes. CIR's environmental and science on board support equipment such as air circulation fans, pumps, water flow, air flow, solenoid valves, and computer hard drives cause disturbances within the rack. These disturbers along with the rack structure must be characterized to predict whether the on-orbit vibration levels during experimentation exceed the specified science microgravity vibration level requirements. Both vibratory and transient disturbance conditions are addressed. Disturbance levels/analytical inputs are obtained for each individual disturber in a "free floating" condition in the Glenn Research Center (GRC) Microgravity Emissions Lab (MEL). Flight spare hardware is tested on an Orbital Replacement Unit (ORU) basis. Based on test and analysis, maximum disturbance level

  3. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  4. Predictive Maintenance of Power Substation Equipment by Infrared Thermography Using a Machine-Learning Approach

    Directory of Open Access Journals (Sweden)

    Irfan Ullah

    2017-12-01

    Full Text Available A variety of reasons, specifically contact issues, irregular loads, cracks in insulation, defective relays, terminal junctions and other similar issues, increase the internal temperature of electrical instruments. This results in unexpected disturbances and potential damage to power equipment. Therefore, the initial prevention measures of thermal anomalies in electrical tools are essential to prevent power-equipment failure. In this article, we address this initial prevention mechanism for power substations using a computer-vision approach by taking advantage of infrared thermal images. The thermal images are taken through infrared cameras without disturbing the working operations of power substations. Thus, this article augments the non-destructive approach to defect analysis in electrical power equipment using computer vision and machine learning. We use a total of 150 thermal pictures of different electrical equipment in 10 different substations in operating conditions, using 300 different hotspots. Our approach uses multi-layered perceptron (MLP to classify the thermal conditions of components of power substations into “defect” and “non-defect” classes. A total of eleven features, which are first-order and second-order statistical features, are calculated from the thermal sample images. The performance of MLP shows initial accuracy of 79.78%. We further augment the MLP with graph cut to increase accuracy to 84%. We argue that with the successful development and deployment of this new system, the Technology Department of Chongqing can arrange the recommended actions and thus save cost in repair and outages. This can play an important role in the quick and reliable inspection to potentially prevent power substation equipment from failure, which will save the whole system from breakdown. The increased 84% accuracy with the integration of the graph cut shows the efficacy of the proposed defect analysis approach.

  5. SU-E-T-205: MLC Predictive Maintenance Using Statistical Process Control Analysis.

    Science.gov (United States)

    Able, C; Hampton, C; Baydush, A; Bright, M

    2012-06-01

    MLC failure increases accelerator downtime and negatively affects the clinic treatment delivery schedule. This study investigates the use of Statistical Process Control (SPC), a modern quality control methodology, to retrospectively evaluate MLC performance data thereby predicting the impending failure of individual MLC leaves. SPC, a methodology which detects exceptional variability in a process, was used to analyze MLC leaf velocity data. A MLC velocity test is performed weekly on all leaves during morning QA. The leaves sweep 15 cm across the radiation field with the gantry pointing down. The leaf speed is analyzed from the generated dynalog file using quality assurance software. MLC leaf speeds in which a known motor failure occurred (8) and those in which no motor replacement was performed (11) were retrospectively evaluated for a 71 week period. SPC individual and moving range (I/MR) charts were used in the analysis. The I/MR chart limits were calculated using the first twenty weeks of data and set at 3 standard deviations from the mean. The MLCs in which a motor failure occurred followed two general trends: (a) no data indicating a change in leaf speed prior to failure (5 of 8) and (b) a series of data points exceeding the limit prior to motor failure (3 of 8). I/MR charts for a high percentage (8 of 11) of the non-replaced MLC motors indicated that only a single point exceeded the limit. These single point excesses were deemed false positives. SPC analysis using MLC performance data may be helpful in detecting a significant percentage of impending failures of MLC motors. The ability to detect MLC failure may depend on the method of failure (i.e. gradual or catastrophic). Further study is needed to determine if increasing the sampling frequency could increase reliability. Project was support by a grant from Varian Medical Systems, Inc. © 2012 American Association of Physicists in Medicine.

  6. 4'' + D VR technology for structural analysis and integrated maintenance of nuclear power plants

    International Nuclear Information System (INIS)

    Lee, I. S.; Yoon, S. H.; Shim, K. W.; Yu, Y. H.; Suh, K. Y.

    2002-01-01

    engineered structures but also for the on-line design modification. In this regard it is of utmost importance to employ the 4 + D VR technology for the nuclear power plants in their design stage as well as for the operating plants for optimal maintenance schedules and procedures. By using this technology one can perform structural design optimization needed for building the nuclear power plant. The 4 + D VR design and construction optimization may result in savings of 200∼300 million per month of reduced construction time for the two units

  7. Frontoparietal white matter integrity predicts haptic performance in chronic stroke

    Directory of Open Access Journals (Sweden)

    Alexandra L. Borstad

    2016-01-01

    . Age strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T–M1 MD and affected hand HASTe score (r = −0.62, p = 0.006 and less affected hand HASTe score (r = −0.53, p = 0.022. Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T–M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

  8. Frontoparietal white matter integrity predicts haptic performance in chronic stroke.

    Science.gov (United States)

    Borstad, Alexandra L; Choi, Seongjin; Schmalbrock, Petra; Nichols-Larsen, Deborah S

    2016-01-01

    strongly correlated with the shared variance across tracts in the control, but not in the poststroke participants. A moderate to good relationship was found between ipsilesional T-M1 MD and affected hand HASTe score (r = - 0.62, p = 0.006) and less affected hand HASTe score (r = - 0.53, p = 0.022). Regression analysis revealed approximately 90% of the variance in affected hand HASTe score was predicted by the white matter integrity in the frontoparietal network (as indexed by MD) in poststroke participants while 87% of the variance in HASTe score was predicted in control participants. This study demonstrates the importance of frontoparietal white matter in mediating haptic performance and specifically identifies that T-M1 and precuneus interhemispheric tracts may be appropriate targets for piloting rehabilitation interventions, such as noninvasive brain stimulation, when the goal is to improve poststroke haptic performance.

  9. Cyp26 Enzymes Facilitate Second Heart Field Progenitor Addition and Maintenance of Ventricular Integrity.

    Directory of Open Access Journals (Sweden)

    Ariel B Rydeen

    2016-11-01

    Full Text Available Although retinoic acid (RA teratogenicity has been investigated for decades, the mechanisms underlying RA-induced outflow tract (OFT malformations are not understood. Here, we show zebrafish embryos deficient for Cyp26a1 and Cyp26c1 enzymes, which promote RA degradation, have OFT defects resulting from two mechanisms: first, a failure of second heart field (SHF progenitors to join the OFT, instead contributing to the pharyngeal arch arteries (PAAs, and second, a loss of first heart field (FHF ventricular cardiomyocytes due to disrupted cell polarity and extrusion from the heart tube. Molecularly, excess RA signaling negatively regulates fibroblast growth factor 8a (fgf8a expression and positively regulates matrix metalloproteinase 9 (mmp9 expression. Although restoring Fibroblast growth factor (FGF signaling can partially rescue SHF addition in Cyp26 deficient embryos, attenuating matrix metalloproteinase (MMP function can rescue both ventricular SHF addition and FHF integrity. These novel findings indicate a primary effect of RA-induced OFT defects is disruption of the extracellular environment, which compromises both SHF recruitment and FHF ventricular integrity.

  10. Solid secondary waste testing for maintenance of the Hanford Integrated Disposal Facility Performance Assessment - FY 2017

    Energy Technology Data Exchange (ETDEWEB)

    Nichols, Ralph L. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Seitz, Roger R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Dixon, Kenneth L. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-08-01

    The Waste Treatment and Immobilization Plant (WTP) at Hanford is being constructed to treat 56 million gallons of radioactive waste currently stored in underground tanks at the Hanford site. Operation of the WTP will generate several solid secondary waste (SSW) streams including used process equipment, contaminated tools and instruments, decontamination wastes, high-efficiency particulate air filters (HEPA), carbon adsorption beds, silver mordenite iodine sorbent beds, and spent ion exchange resins (IXr) all of which are to be disposed in the Integrated Disposal Facility (IDF). An applied research and development program was developed using a phased approach to incrementally develop the information necessary to support the IDF PA with each phase of the testing building on results from the previous set of tests and considering new information from the IDF PA calculations. This report contains the results from the exploratory phase, Phase 1 and preliminary results from Phase 2. Phase 3 is expected to begin in the fourth quarter of FY17.

  11. Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

    Science.gov (United States)

    Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

    2016-04-01

    It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

  12. Advanced maintenance research programs

    International Nuclear Information System (INIS)

    Marston, T.U.; Gelhaus, F.; Burke, R.

    1985-01-01

    The purpose of this paper is to provide the reader with an idea of the advanced maintenance research program at the Electric Power Research Institute (EPRI). A brief description of the maintenance-related activities is provided as a foundation for the advanced maintenance research projects. The projects can be divided into maintenance planning, preventive maintenance program development and implementation, predictive (or conditional) maintenance, and innovative maintenance techniques. The projects include hardware and software development, human factors considerations, and technology promotion and implementation. The advanced concepts include: the incorporation of artificial intelligence into outage planning; turbine and pump maintenance; rotating equipment monitoring and diagnostics with the aid of expert systems; and the development of mobile robots for nuclear power plant maintenance

  13. Music therapy-induced changes in salivary cortisol level are predictive of cardiovascular mortality in patients under maintenance hemodialysis

    Directory of Open Access Journals (Sweden)

    Hou YC

    2017-02-01

    Full Text Available Yi-Chou Hou,1 Yen-Ju Lin,2 Kuo-Cheng Lu,1 Han-Sun Chiang,3 Chia-Chi Chang,4 Li-King Yang1 1Department of Internal Medicine, Cardinal Tien Hospital, School of Medicine, Fu-Jen Catholic University, 2Department of Nursing, Taipei Medical University, 3Graduate Institute of Basic Medicine, College of Medicine, Fu Jen Catholic University, New Taipei City, 4School of Gerontology Health Management, College of Nursing, Taipei Medical University, Taipei, Taiwan, Republic of China Background: Music therapy has been applied in hemodialysis (HD patients for relieving mental stress. Whether the stress-relieving effect by music therapy is predictive of clinical outcome in HD patients is still unclear.Methods: We recruited a convenience sample of 99 patients on maintenance HD and randomly assigned them to the experimental (n=49 or control (n=50 group. The experimental group received relaxing music therapy for 1 week, whereas the control group received no music therapy. In the experimental group, we compared cardiovascular mortality in the patients with and without cortisol changes.Results: The salivary cortisol level was lowered after 1 week of music therapy in the experimental group (−2.41±3.08 vs 1.66±2.11 pg/mL, P<0.05, as well as the frequency of the adverse reaction score (−3.35±5.76 vs −0.81±4.59, P<0.05, the severity of adverse reactions score (−1.93±2.73 vs 0.33±2.71, P<0.05, and hemodialysis stressor scale (HSS score (−6.00±4.68 vs −0.877±7.08, P<0.05. The difference in salivary cortisol correlated positively with HD stress score scales (r=0.231, P<0.05, systolic blood pressure (r=0.264, P<0.05, and respiratory rates (r=0.369, P<0.05 and negatively with finger temperature (r=−0.235, P<0.05 in the total study population. The 5-year cardiovascular survival in the experimental group was higher in patients whose salivary cortisol lowered by <0.6 pg/mL than that in patients whose salivary cortisol lowered by >0.6 pg/mL (83.8% vs

  14. Steam Generator Maintenance Measures as Part of an Integrated Management in PWRs

    International Nuclear Information System (INIS)

    Weiss, S.; Drexler, A.; Fandrich, J.

    2012-01-01

    The Steam generator condition is a key factor for plant performance, high plant availability, possible life time extension and plant safety. Its major safety function is to act as a barrier between the radioactive primary side and the non-radioactive secondary side of pressurized water reactors. Any degradation mechanism, which impairs this barrier function, is a significant safety concern. The main reason for SG tube failure is known to be the accumulation of deposits contributing to formation of local aggressive conditions. Furthermore deposits on primary as well as secondary side of SG tubes reduce the heat transfer performance. A SG cleanliness management program is therefore mandatory to ensure high plant performance regarding efficiency as well as component integrity. Cleaning measures of steam generator are essential parts of the cleanliness management program. Mechanical cleaning, e.g. tubesheet and inner bundle lancing or upper bundle flushing are efficient methods for removal of local loose deposits. But a chemical cleaning is the only method to remove deposits from the complete SG. AREVA is providing with its C 3 (customized chemical cleaning) concept a tool box of chemical cleaning methods, to adapt to plant specific needs and requirements. (author)

  15. Supervision and prognosis architecture based on dynamical classification method for the predictive maintenance of dynamical evolving systems

    International Nuclear Information System (INIS)

    Traore, M.; Chammas, A.; Duviella, E.

    2015-01-01

    In this paper, we are concerned by the improvement of the safety, availability and reliability of dynamical systems’ components subjected to slow degradations (slow drifts). We propose an architecture for efficient Predictive Maintenance (PM) according to the real time estimate of the future state of the components. The architecture is built on supervision and prognosis tools. The prognosis method is based on an appropriated supervision technique that consists in drift tracking of the dynamical systems using AUDyC (AUto-adaptive and Dynamical Clustering), that is an auto-adaptive dynamical classifier. Thus, due to the complexity and the dynamical of the considered systems, the Failure Mode Effect and Criticity Analysis (FMECA) is used to identify the key components of the systems. A component is defined as an element of the system that can be impacted by only one failure. A failure of a key component causes a long downtime of the system. From the FMECA, a Fault Tree Analysis (FTA) of the system are built to determine the propagation laws of a failure on the system by using a deductive method. The proposed architecture is implemented for the PM of a thermoregulator. The application on this real system highlights the interests and the performances of the proposed architecture

  16. Maintenance-based prognostics of nuclear plant equipment for long-term operation

    Energy Technology Data Exchange (ETDEWEB)

    Welz, Zachary; Coble, Jamie; Upadhyaya, Belle; Hines, Wes [University of Tennessee, Knoxville (United States)

    2017-08-15

    While industry understands the importance of keeping equipment operational and well maintained, the importance of tracking maintenance information in reliability models is often overlooked. Prognostic models can be used to predict the failure times of critical equipment, but more often than not, these models assume that all maintenance actions are the same or do not consider maintenance at all. This study investigates the influence of integrating maintenance information on prognostic model prediction accuracy. By incorporating maintenance information to develop maintenance-dependent prognostic models, prediction accuracy was improved by more than 40% compared with traditional maintenance-independent models. This study acts as a proof of concept, showing the importance of utilizing maintenance information in modern prognostics for industrial equipment.

  17. Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

    Science.gov (United States)

    Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

    2012-04-01

    Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

  18. Development of hardware system using temperature and vibration maintenance models integration concepts for conventional machines monitoring: a case study

    Science.gov (United States)

    Adeyeri, Michael Kanisuru; Mpofu, Khumbulani; Kareem, Buliaminu

    2016-03-01

    This article describes the integration of temperature and vibration models for maintenance monitoring of conventional machinery parts in which their optimal and best functionalities are affected by abnormal changes in temperature and vibration values thereby resulting in machine failures, machines breakdown, poor quality of products, inability to meeting customers' demand, poor inventory control and just to mention a few. The work entails the use of temperature and vibration sensors as monitoring probes programmed in microcontroller using C language. The developed hardware consists of vibration sensor of ADXL345, temperature sensor of AD594/595 of type K thermocouple, microcontroller, graphic liquid crystal display, real time clock, etc. The hardware is divided into two: one is based at the workstation (majorly meant to monitor machines behaviour) and the other at the base station (meant to receive transmission of machines information sent from the workstation), working cooperatively for effective functionalities. The resulting hardware built was calibrated, tested using model verification and validated through principles pivoted on least square and regression analysis approach using data read from the gear boxes of extruding and cutting machines used for polyethylene bag production. The results got therein confirmed related correlation existing between time, vibration and temperature, which are reflections of effective formulation of the developed concept.

  19. α-Xylosidase plays essential roles in xyloglucan remodelling, maintenance of cell wall integrity, and seed germination in Arabidopsis thaliana.

    Science.gov (United States)

    Shigeyama, Takuma; Watanabe, Asuka; Tokuchi, Konatsu; Toh, Shigeo; Sakurai, Naoki; Shibuya, Naoto; Kawakami, Naoto

    2016-10-01

    Regulation and maintenance of cell wall physical properties are crucial for plant growth and environmental response. In the germination process, hypocotyl cell expansion and endosperm weakening are prerequisites for dicot seeds to complete germination. We have identified the Arabidopsis mutant thermoinhibition-resistant germination 1 (trg1), which has reduced seed dormancy and insensitivity to unfavourable conditions for germination owing to a loss-of-function mutation of TRG1/XYL1, which encodes an α-xylosidase. Compared to those of wild type, the elongating stem of trg1 showed significantly lower viscoelasticity, and the fruit epidermal cells were longitudinally shorter and horizontally enlarged. Actively growing tissues of trg1 over-accumulated free xyloglucan oligosaccharides (XGOs), and the seed cell wall had xyloglucan with a greatly reduced molecular weight. These observations suggest that XGOs reduce xyloglucan size by serving as an acceptor in transglycosylation and eventually enhancing cell wall loosening. TRG1/XYL1 gene expression was abundant in growing wild-type organs and tissues but relatively low in cells at most actively elongating part of the tissues, suggesting that α-xylosidase contributes to maintaining the mechanical integrity of the primary cell wall in the growing and pre-growing tissues. In germinating seeds of trg1, expression of genes encoding specific abscisic acid and gibberellin metabolism enzymes was altered in accordance with the aberrant germination phenotype. Thus, cell wall integrity could affect seed germination not only directly through the physical properties of the cell wall but also indirectly through the regulation of hormone gene expression. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  20. Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

    Science.gov (United States)

    Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

    2016-02-01

    The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

  1. Accurate Holdup Calculations with Predictive Modeling & Data Integration

    Energy Technology Data Exchange (ETDEWEB)

    Azmy, Yousry [North Carolina State Univ., Raleigh, NC (United States). Dept. of Nuclear Engineering; Cacuci, Dan [Univ. of South Carolina, Columbia, SC (United States). Dept. of Mechanical Engineering

    2017-04-03

    Bayes’ Theorem, one must have a model y(x) that maps the state variables x (the solution in this case) to the measurements y. In this case, the unknown state variables are the configuration and composition of the heldup SNM. The measurements are the detector readings. Thus, the natural model is neutral-particle radiation transport where a wealth of computational tools exists for performing these simulations accurately and efficiently. The combination of predictive model and Bayesian inference forms the Data Integration with Modeled Predictions (DIMP) method that serves as foundation for this project. The cost functional describing the model-to-data misfit is computed via a norm created by the inverse of the covariance matrix of the model parameters and responses. Since the model y(x) for the holdup problem is nonlinear, a nonlinear optimization on Q is conducted via Newton-type iterative methods to find the optimal values of the model parameters x. This project comprised a collaboration between NC State University (NCSU), the University of South Carolina (USC), and Oak Ridge National Laboratory (ORNL). The project was originally proposed in seven main tasks with an eighth contingency task to be performed if time and funding permitted; in fact time did not permit commencement of the contingency task and it was not performed. The remaining tasks involved holdup analysis with gamma detection strategies and separately with neutrons based on coincidence counting. Early in the project, and upon consultation with experts in coincidence counting it became evident that this approach is not viable for holdup applications and this task was replaced with an alternative, but valuable investigation that was carried out by the USC partner. Nevertheless, the experimental 4 measurements at ORNL of both gamma and neutron sources for the purpose of constructing Detector Response Functions (DRFs) with the associated uncertainties were indeed completed.

  2. What Predicts Exercise Maintenance and Well-Being? Examining The Influence of Health-Related Psychographic Factors and Social Media Communication.

    Science.gov (United States)

    Zhou, Xin; Krishnan, Archana

    2018-01-26

    Habitual exercising is an important precursor to both physical and psychological well-being. There is, thus, a strong interest in identifying key factors that can best motivate individuals to sustain regular exercise regimen. In addition to the importance of psychographic factors, social media use may act as external motivator by allowing users to interact and communicate about exercise. In this study, we examined the influence of health consciousness, health-oriented beliefs, intrinsic motivation, as willingness to communicate about health on social media, social media activity on exercise, and online social support on exercise maintenance and well-being on a sample of 532 American adults. Employing structural equation modeling, we found that health-oriented beliefs mediated the effect of health consciousness on intrinsic motivation which in turn was a significant predictor of exercise maintenance. Exercise maintenance significantly predicted both physical and psychological well-being. Extrinsic motivators, as measured by willingness to communicate about health on social media, social media activity on exercise, and online social support did not however significantly influence exercise maintenance. These findings have implications for the design and implementation of exercise-promoting interventions by identifying underlying factors that influence exercise maintenance.

  3. Prediction of attendance at fitness center: a comparison between the theory of planned behavior, the social cognitive theory, and the physical activity maintenance theory.

    Science.gov (United States)

    Jekauc, Darko; Völkle, Manuel; Wagner, Matthias O; Mess, Filip; Reiner, Miriam; Renner, Britta

    2015-01-01

    In the processes of physical activity (PA) maintenance specific predictors are effective, which differ from other stages of PA development. Recently, Physical Activity Maintenance Theory (PAMT) was specifically developed for prediction of PA maintenance. The aim of the present study was to evaluate the predictability of the future behavior by the PAMT and compare it with the Theory of Planned Behavior (TPB) and Social Cognitive Theory (SCT). Participation rate in a fitness center was observed for 101 college students (53 female) aged between 19 and 32 years (M = 23.6; SD = 2.9) over 20 weeks using a magnetic card. In order to predict the pattern of participation TPB, SCT and PAMT were used. A latent class zero-inflated Poisson growth curve analysis identified two participation patterns: regular attenders and intermittent exercisers. SCT showed the highest predictive power followed by PAMT and TPB. Impeding aspects as life stress and barriers were the strongest predictors suggesting that overcoming barriers might be an important aspect for working out on a regular basis. Self-efficacy, perceived behavioral control, and social support could also significantly differentiate between the participation patterns.

  4. Maintenance cost avoidance through comprehensive condition monitoring

    International Nuclear Information System (INIS)

    Miller, G.P.; McClymonds, S.L.

    1990-01-01

    Condition monitoring, the measurement and trending of a critical parameter for predictive maintenance, has reached new levels of acceptance and application within the utility and manufacturing industry. Commercially available systems extend well beyond traditional vibration-monitoring systems to include such areas as online wear, crack and leak detection, and stress monitoring. The challenge facing industry is to integrate the information generated from condition monitoring. Current studies indicate that the effectiveness of predictive maintenance depends much more on the program that is established to apply the monitoring techniques than on the monitoring equipment itself. This paper presents a five-phase approach to developing a condition monitoring program

  5. A distinct adipose tissue gene expression response to caloric restriction predicts 6-mo weight maintenance in obese subjects

    DEFF Research Database (Denmark)

    Mutch, D. M.; Pers, Tune Hannes; Temanni, M. R.

    2011-01-01

    Background: Weight loss has been shown to reduce risk factors associated with cardiovascular disease and diabetes; however, successful maintenance of weight loss continues to pose a challenge. Objective: The present study was designed to assess whether changes in subcutaneous adipose tissue (scAT......-term weight maintenance. This trial was registered at clinicaltrials.gov as NCT00390637. ©American Society for Nutrition. All rights reserved....

  6. Predicting freshwater habitat integrity using land-use surrogates

    African Journals Online (AJOL)

    2007-04-02

    Apr 2, 2007 ... Quantification of potential surrogates of freshwater habitat integrity. We chose a series of land-use variables that might be suitable predictors for assessing freshwater habitat integrity from the land cover map (CSIR 2005) and added separate GIS surfaces for human population density and the distribution of ...

  7. Context mining and integration into predictive web analytics

    NARCIS (Netherlands)

    Kiseleva, Y.

    2013-01-01

    Predictive Web Analytics is aimed at understanding behavioural patterns of users of various web-based applications: e-commerce, ubiquitous and mobile computing, and computational advertising. Within these applications business decisions often rely on two types of predictions: an overall or

  8. The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

    Science.gov (United States)

    Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

    2011-07-01

    The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

  9. Maintenance of host DNA integrity in field-preserved mosquito (Diptera: Culicidae) blood meals for identification by DNA barcoding.

    Science.gov (United States)

    Reeves, Lawrence E; Holderman, Chris J; Gillett-Kaufman, Jennifer L; Kawahara, Akito Y; Kaufman, Phillip E

    2016-09-15

    Determination of the interactions between hematophagous arthropods and their hosts is a necessary component to understanding the transmission dynamics of arthropod-vectored pathogens. Current molecular methods to identify hosts of blood-fed arthropods require the preservation of host DNA to serve as an amplification template. During transportation to the laboratory and storage prior to molecular analysis, genetic samples need to be protected from nucleases, and the degradation effects of hydrolysis, oxidation and radiation. Preservation of host DNA contained in field-collected blood-fed specimens has an additional caveat: suspension of the degradative effects of arthropod digestion on host DNA. Unless effective preservation methods are implemented promptly after blood-fed specimens are collected, host DNA will continue to degrade. Preservation methods vary in their efficacy, and need to be selected based on the logistical constraints of the research program. We compared four preservation methods (cold storage at -20 °C, desiccation, ethanol storage of intact mosquito specimens and crushed specimens on filter paper) for field storage of host DNA from blood-fed mosquitoes across a range of storage and post-feeding time periods. The efficacy of these techniques in maintaining host DNA integrity was evaluated using a polymerase chain reaction (PCR) to detect the presence of a sufficient concentration of intact host DNA templates for blood meal analysis. We applied a logistic regression model to assess the effects of preservation method, storage time and post-feeding time on the binomial response variable, amplification success. Preservation method, storage time and post-feeding time all significantly impacted PCR amplification success. Filter papers and, to a lesser extent, 95 % ethanol, were the most effective methods for the maintenance of host DNA templates. Amplification success of host DNA preserved in cold storage at -20 °C and desiccation was poor. Our data

  10. Development of equipment reliability process using predictive technologies at Hamaoka Nuclear Power Station

    International Nuclear Information System (INIS)

    Taniguchi, Yuji; Sakuragi, Futoshi; Hamada, Seiichi

    2014-01-01

    Development of equipment reliability(ER) process, specifically for predictive maintenance (PdM) technologies integrated condition based maintenance (CBM) process, at Hamaoka Nuclear Power Station is introduced in this paper. Integration of predictive maintenance technologies such as vibration, oil analysis and thermo monitoring is more than important to establish strong maintenance strategies and to direct a specific technical development. In addition, a practical example of CBM is also presented to support the advantage of the idea. (author)

  11. Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

    Science.gov (United States)

    Sepehry-Fard, F.; Coulthard, Maurice H.

    1995-01-01

    The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

  12. Framework for Maintenance Planning

    DEFF Research Database (Denmark)

    Soares, C. Guedes; Duarte, J. Caldeira; Garbatov, Y.

    2010-01-01

    the design and during the whole life span of operational use, within an integrated framework founded on risk and reliability based techniques. The document addresses designers, decision makers and professionals responsible for or involved in establishing maintenance plans. The purpose of this document......The present document presents a framework for maintenance planning. Maintenance plays a fundamental role in counteracting degradation effects, which are present in all infrastructure and industrial products. Therefore, maintenance planning is a very critical aspect to consider both during...... is to present maintenance as an integrated approach that needs to be planned, designed, engineered, and controlled by proper qualitative and quantitative techniques. This document outlines the basic premises for maintenance planning and provides the general philosophies that can be followed and points to a best...

  13. Evaluating and Predicting Patient Safety for Medical Devices With Integral Information Technology

    Science.gov (United States)

    2005-01-01

    323 Evaluating and Predicting Patient Safety for Medical Devices with Integral Information Technology Jiajie Zhang, Vimla L. Patel, Todd R...errors are due to inappropriate designs for user interactions, rather than mechanical failures. Evaluating and predicting patient safety in medical ...the users on the identified trouble spots in the devices. We developed two methods for evaluating and predicting patient safety in medical devices

  14. Predicting freshwater habitat integrity using land-use surrogates

    CSIR Research Space (South Africa)

    Amis, MA

    2007-04-01

    Full Text Available Freshwater biodiversity is globally threatened due to human disturbances, but freshwater ecosystems have been accorded less protection than their terrestrial and marine counterparts. Few criteria exist for assessing the habitat integrity of rivers...

  15. Status of fusion maintenance

    International Nuclear Information System (INIS)

    Fuller, G.M.

    1984-01-01

    Effective maintenance will be an essential ingredient in determining fusion system productivity. This level of productivity will result only after close attention is paid to the entire system as an entity and appropriate integration of the elements is made. The status of fusion maintenance is reviewed in the context of the entire system. While there are many challenging developmental tasks ahead in fusion maintenance, the required technologies are available in several high-technology industries, including nuclear fission

  16. Prediction of thermo-mechanical integrity of wafer backend processes

    NARCIS (Netherlands)

    Gonda, V.; Toonder, den J.M.J.; Beijer, J.G.J.; Zhang, G.Q.; Hoofman, R.J.O.M.; Ernst, L.J.; Ernst, L.J.

    2003-01-01

    More than 65% of IC failures are related to thermal and mechanical problems. For wafer backend processes, thermo-mechanical failure is one of the major bottlenecks. The ongoing technological trends like miniaturization, introduction of new materials, and function/product integration will increase

  17. Preliminary background prediction for the INTEGRAL x-ray monitor

    DEFF Research Database (Denmark)

    Feroci, M.; Costa, E.; Budtz-Joergensen, C.

    1996-01-01

    The JEM-X (joint European x-ray monitor) experiment will be flown onboard the ESA's INTEGRAL satellite. The instrumental background level of the two JEM-X twin detectors will depend on several parameters, among which the satellite orbit and mass distribution, and the detectors materials play...

  18. Integrating models to predict regional haze from wildland fire.

    Science.gov (United States)

    D. McKenzie; S.M. O' Neill; N. Larkin; R.A. Norheim

    2006-01-01

    Visibility impairment from regional haze is a significant problem throughout the continental United States. A substantial portion of regional haze is produced by smoke from prescribed and wildland fires. Here we describe the integration of four simulation models, an array of GIS raster layers, and a set of algorithms for fire-danger calculations into a modeling...

  19. Tide Gauge and Satellite Altimetry Integration for Storm Surge Prediction

    DEFF Research Database (Denmark)

    Andersen, Ole Baltazar; Cheng, Yongcun; Deng, X.

    2013-01-01

    of the Northeast Australia, we have investigated several large cyclones causing much destruction when they hit the coast. One of these being the Cyclone Larry, which hit the Queensland coast in March 2006 and caused both losses of lives as well as huge devastation. Here we demonstrate the importance of integrating...

  20. Statistical timing for parametric yield prediction of digital integrated circuits

    NARCIS (Netherlands)

    Jess, J.A.G.; Kalafala, K.; Naidu, S.R.; Otten, R.H.J.M.; Visweswariah, C.

    2006-01-01

    Uncertainty in circuit performance due to manufacturing and environmental variations is increasing with each new generation of technology. It is therefore important to predict the performance of a chip as a probabilistic quantity. This paper proposes three novel path-based algorithms for statistical

  1. Predicting phenology by integrating ecology, evolution and climate science

    Science.gov (United States)

    Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.

    2011-01-01

    Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

  2. Accuracy of Consecutive Fecal Calprotectin Measurements to Predict Relapse in Inflammatory Bowel Disease Patients Under Maintenance With Anti-TNF Therapy: A Prospective Longitudinal Cohort Study.

    Science.gov (United States)

    Ferreiro-Iglesias, Rocio; Barreiro-de Acosta, Manuel; Lorenzo-Gonzalez, Aurelio; Dominguez-Muñoz, Juan E

    2018-03-01

    Predicting relapse in inflammatory bowel disease (IBD) patients could allow early changes in therapy. We aimed at evaluating the accuracy of consecutive fecal calprotectin (FC) measurements to predict flares in IBD patients under maintenance treatment with anti-tumor necrosis factor (TNF) drugs. A prospective longitudinal cohort study with 16-month follow-up period was designed. IBD patients in clinical remission for at least 6 months under anti-TNF therapy were included. FC was quantified at 4-month intervals for 1 year, and patients were clinically evaluated for relapse at 2-month intervals. Diagnostic accuracy of FC for predicting relapse was evaluated by receiver-operating characteristic curve analysis. In total, 95 of 106 included patients finalized the study and were analyzed (median age 44 y, 50.5% female, 75% with Crohn's disease). A total of 30 patients (31.6%) had a relapse over follow-up. FC concentration was significantly higher in patients who relapsed (477 μg/g) than in patients who maintained in remission (65 μg/g) (Ppredict remission was 130 μg/g (negative predictive value of 100%), and 300 μg/g to predict relapse (positive predictive value of 78.3%). FC is a good predictor of clinical relapse and a particularly good predictor of remission over the following 4 months in patients with IBD on maintenance therapy with anti-TNF drugs. FC levels 300 μg/g allow predicting relapse with a high probability at any time over the following 4 months.

  3. Edaphic history over seedling characters predicts integration and plasticity of integration across geologically variable populations of Arabidopsis thaliana.

    Science.gov (United States)

    Cousins, Elsa A; Murren, Courtney J

    2017-12-01

    Studies on phenotypic plasticity and plasticity of integration have uncovered functionally linked modules of aboveground traits and seedlings of Arabidopsis thaliana , but we lack details about belowground variation in adult plants. Functional modules can be comprised of additional suites of traits that respond to environmental variation. We assessed whether shoot and root responses to nutrient environments in adult A. thaliana were predictable from seedling traits or population-specific geologic soil characteristics at the site of origin. We compared 17 natural accessions from across the native range of A. thaliana using 14-day-old seedlings grown on agar or sand and plants grown to maturity across nutrient treatments in sand. We measured aboveground size, reproduction, timing traits, root length, and root diameter. Edaphic characteristics were obtained from a global-scale dataset and related to field data. We detected significant among-population variation in root traits of seedlings and adults and in plasticity in aboveground and belowground traits of adult plants. Phenotypic integration of roots and shoots varied by population and environment. Relative integration was greater in roots than in shoots, and integration was predicted by edaphic soil history, particularly organic carbon content, whereas seedling traits did not predict later ontogenetic stages. Soil environment of origin has significant effects on phenotypic plasticity in response to nutrients, and on phenotypic integration of root modules and shoot modules. Root traits varied among populations in reproductively mature individuals, indicating potential for adaptive and integrated functional responses of root systems in annuals. © 2017 Botanical Society of America.

  4. Improving protein function prediction methods with integrated literature data

    Directory of Open Access Journals (Sweden)

    Gabow Aaron P

    2008-04-01

    Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

  5. Integration of Fast Predictive Model and SLM Process Development Chamber, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This STTR project seeks to develop a fast predictive model for selective laser melting (SLM) processes and then integrate that model with an SLM chamber that allows...

  6. Integrating prediction, provenance, and optimization into high energy workflows

    Energy Technology Data Exchange (ETDEWEB)

    Schram, M.; Bansal, V.; Friese, R. D.; Tallent, N. R.; Yin, J.; Barker, K. J.; Stephan, E.; Halappanavar, M.; Kerbyson, D. J.

    2017-10-01

    We propose a novel approach for efficient execution of workflows on distributed resources. The key components of this framework include: performance modeling to quantitatively predict workflow component behavior; optimization-based scheduling such as choosing an optimal subset of resources to meet demand and assignment of tasks to resources; distributed I/O optimizations such as prefetching; and provenance methods for collecting performance data. In preliminary results, these techniques improve throughput on a small Belle II workflow by 20%.

  7. A Randomized Clinical Trial of Methadone Maintenance for Prisoners: Prediction of Treatment Entry and Completion in Prison.

    Science.gov (United States)

    Gordon, Michael S; Kinlock, Timothy W; Couvillion, Kathryn A; Schwartz, Robert P; O'Grady, Kevin

    2012-05-01

    The present report is an intent-to-treat analysis involving secondary data drawn from the first randomized clinical trial of prison-initiated methadone in the United States. This study examined predictors of treatment entry and completion in prison. A sample of 211 adult male prerelease inmates with preincarceration heroin dependence were randomly assigned to one of three treatment conditions: counseling only (counseling in prison; n= 70); counseling plus transfer (counseling in prison with transfer to methadone maintenance treatment upon release; n= 70); and counseling plus methadone (methadone maintenance in prison, continued in a community-based methadone maintenance program upon release; n= 71). Entered prison treatment (p prison treatment (pprison sentences may have better outcomes than younger individuals with shorter sentences, meaning they are more likely to enter and complete prison-based treatment. Furthermore, implications for the treatment of prisoners with prior heroin dependence and for conducting clinical trials may indicate the importance of examining individual characteristics and the possibility of the examination of patient preference.

  8. Improving Permafrost Hydrology Prediction Through Data-Model Integration

    Science.gov (United States)

    Wilson, C. J.; Andresen, C. G.; Atchley, A. L.; Bolton, W. R.; Busey, R.; Coon, E.; Charsley-Groffman, L.

    2017-12-01

    The CMIP5 Earth System Models were unable to adequately predict the fate of the 16GT of permafrost carbon in a warming climate due to poor representation of Arctic ecosystem processes. The DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic project aims to reduce uncertainty in the Arctic carbon cycle and its impact on the Earth's climate system by improved representation of the coupled physical, chemical and biological processes that drive how much buried carbon will be converted to CO2 and CH4, how fast this will happen, which form will dominate, and the degree to which increased plant productivity will offset increased soil carbon emissions. These processes fundamentally depend on permafrost thaw rate and its influence on surface and subsurface hydrology through thermal erosion, land subsidence and changes to groundwater flow pathways as soil, bedrock and alluvial pore ice and massive ground ice melts. LANL and its NGEE colleagues are co-developing data and models to better understand controls on permafrost degradation and improve prediction of the evolution of permafrost and its impact on Arctic hydrology. The LANL Advanced Terrestrial Simulator was built using a state of the art HPC software framework to enable the first fully coupled 3-dimensional surface-subsurface thermal-hydrology and land surface deformation simulations to simulate the evolution of the physical Arctic environment. Here we show how field data including hydrology, snow, vegetation, geochemistry and soil properties, are informing the development and application of the ATS to improve understanding of controls on permafrost stability and permafrost hydrology. The ATS is being used to inform parameterizations of complex coupled physical, ecological and biogeochemical processes for implementation in the DOE ACME land model, to better predict the role of changing Arctic hydrology on the global climate system. LA-UR-17-26566.

  9. Predictions of integrated circuit serviceability in space radiation fields

    Energy Technology Data Exchange (ETDEWEB)

    Khamidullina, N.M.; Kuznetsov, N.V.; Pichkhadze, K.M.; Popov, V.D

    1999-10-01

    The present paper suggests an approach to estimating and predicting the serviceability of on-board electronic equipment. It is based on the postulates of the reliability theory and accounts for total-dose and single-event radiation effects as well as other exterior destabilizing factors. The methods of determination of failure and upset rates for CMOS devices are considered. The probability of non-failure operation of a two CMOS RAM is calculated along the whole trajectory of the 'Solar Probe' spacecraft.

  10. Development of an integrated method for long-term water quality prediction using seasonal climate forecast

    Directory of Open Access Journals (Sweden)

    J. Cho

    2016-10-01

    Full Text Available The APEC Climate Center (APCC produces climate prediction information utilizing a multi-climate model ensemble (MME technique. In this study, four different downscaling methods, in accordance with the degree of utilizing the seasonal climate prediction information, were developed in order to improve predictability and to refine the spatial scale. These methods include: (1 the Simple Bias Correction (SBC method, which directly uses APCC's dynamic prediction data with a 3 to 6 month lead time; (2 the Moving Window Regression (MWR method, which indirectly utilizes dynamic prediction data; (3 the Climate Index Regression (CIR method, which predominantly uses observation-based climate indices; and (4 the Integrated Time Regression (ITR method, which uses predictors selected from both CIR and MWR. Then, a sampling-based temporal downscaling was conducted using the Mahalanobis distance method in order to create daily weather inputs to the Soil and Water Assessment Tool (SWAT model. Long-term predictability of water quality within the Wecheon watershed of the Nakdong River Basin was evaluated. According to the Korean Ministry of Environment's Provisions of Water Quality Prediction and Response Measures, modeling-based predictability was evaluated by using 3-month lead prediction data issued in February, May, August, and November as model input of SWAT. Finally, an integrated approach, which takes into account various climate information and downscaling methods for water quality prediction, was presented. This integrated approach can be used to prevent potential problems caused by extreme climate in advance.

  11. Integrated Simulation for HVAC Performance Prediction: State-of-the-Art Illustration

    NARCIS (Netherlands)

    Hensen, J.L.M.; Clarke, J.A.

    2000-01-01

    This paper aims to outline the current state-of-the-art in integrated building simulation for performance prediction of heating, ventilating and air-conditioning (HVAC) systems. The ESP-r system is used as an example where integrated simulation is a core philosophy behind the development. The

  12. Using Advanced Data Mining And Integration In Environmental Prediction Scenarios

    Directory of Open Access Journals (Sweden)

    Habala Ondrej

    2012-01-01

    Full Text Available We present one of the meteorological and hydrological experiments performed in the FP7 project ADMIRE. It serves as an experimental platform for hydrologists, and we have used it also as a testing platform for a suite of advanced data integration and data mining (DMI tools, developed within ADMIRE. The idea of ADMIRE is to develop an advanced DMI platform accessible even to users who are not familiar with data mining techniques. To this end, we have designed a novel DMI architecture, supported by a set of software tools, managed by DMI process descriptions written in a specialized high-level DMI language called DISPEL, and controlled via several different user interfaces, each performing a different set of tasks and targeting different user group.

  13. Predicted performance of an integrated modular engine system

    Science.gov (United States)

    Binder, Michael; Felder, James L.

    1993-01-01

    Space vehicle propulsion systems are traditionally comprised of a cluster of discrete engines, each with its own set of turbopumps, valves, and a thrust chamber. The Integrated Modular Engine (IME) concept proposes a vehicle propulsion system comprised of multiple turbopumps, valves, and thrust chambers which are all interconnected. The IME concept has potential advantages in fault-tolerance, weight, and operational efficiency compared with the traditional clustered engine configuration. The purpose of this study is to examine the steady-state performance of an IME system with various components removed to simulate fault conditions. An IME configuration for a hydrogen/oxygen expander cycle propulsion system with four sets of turbopumps and eight thrust chambers has been modeled using the Rocket Engine Transient Simulator (ROCETS) program. The nominal steady-state performance is simulated, as well as turbopump thrust chamber and duct failures. The impact of component failures on system performance is discussed in the context of the system's fault tolerant capabilities.

  14. Integrating chemical footprinting data into RNA secondary structure prediction.

    Directory of Open Access Journals (Sweden)

    Kourosh Zarringhalam

    Full Text Available Chemical and enzymatic footprinting experiments, such as shape (selective 2'-hydroxyl acylation analyzed by primer extension, yield important information about RNA secondary structure. Indeed, since the [Formula: see text]-hydroxyl is reactive at flexible (loop regions, but unreactive at base-paired regions, shape yields quantitative data about which RNA nucleotides are base-paired. Recently, low error rates in secondary structure prediction have been reported for three RNAs of moderate size, by including base stacking pseudo-energy terms derived from shape data into the computation of minimum free energy secondary structure. Here, we describe a novel method, RNAsc (RNA soft constraints, which includes pseudo-energy terms for each nucleotide position, rather than only for base stacking positions. We prove that RNAsc is self-consistent, in the sense that the nucleotide-specific probabilities of being unpaired in the low energy Boltzmann ensemble always become more closely correlated with the input shape data after application of RNAsc. From this mathematical perspective, the secondary structure predicted by RNAsc should be 'correct', in as much as the shape data is 'correct'. We benchmark RNAsc against the previously mentioned method for eight RNAs, for which both shape data and native structures are known, to find the same accuracy in 7 out of 8 cases, and an improvement of 25% in one case. Furthermore, we present what appears to be the first direct comparison of shape data and in-line probing data, by comparing yeast asp-tRNA shape data from the literature with data from in-line probing experiments we have recently performed. With respect to several criteria, we find that shape data appear to be more robust than in-line probing data, at least in the case of asp-tRNA.

  15. Integrating remotely sensed fires for predicting deforestation for REDD.

    Science.gov (United States)

    Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

    2017-06-01

    Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

  16. Individual capacity for DNA repair and maintenance of genomic integrity: a fertile ground for studies in the field of assisted reproduction

    Directory of Open Access Journals (Sweden)

    Radoslava Vazharova

    2016-05-01

    Full Text Available Many factors may affect the chances for successful pregnancy, especially at a later age. Fertility evaluations including genetic analysis are recommended to couples that have not achieved pregnancy within 6–12 months of unprotected intercourse. This review discusses some of the common polymorphisms in genes coding for proteins functioning in DNA damage identification and repair and maintenance of genomic integrity that may affect the chances of success in natural conception as well as in assisted reproduction (AR. Common polymorphisms in genes coding for proteins functioning in DNA damage identification and repair and maintenance of genomic integrity may affect the chances of success in assisted reproduction as well as in natural conception. The effects of carriership of different alleles of key genes of DNA repair may have differential effects in men and women and at different ages, suggesting complex interactions with the mechanisms controlling cell and tissue aging and programmed cell death. Future studies in the field are needed in order to elucidate the genotype–phenotype relationships and to translate the knowledge about individual repair capacity and maintenance of genomic integrity to potential clinical applications. Abbreviations: aCGH: microarray-based comparative genomic hybridization; AR: assisted reproduction; ATM: ataxia-telangiectasia mutated; ATP: adenosine triphosphate; BER: base excision repair; BFE: basic fertility evaluation; DMSO: dimethyl sulfoxide; FSH: follicle-stimulating hormone; GNRHR: gonadotropin-releasing hormone receptor; HMG: high-mobility group; ICSI: intracytoplasmic sperm injection; IUI: intrauterine insemination; IVF: in vitro fertilization; LH: luteinizing hormone; LIF: leukaemia inhibitory factor; MTR: methionine synthase; MTRR: methionine synthase reductase; NGS: next-generation sequencing; NER: nucleotide excision repair; NHEJ: non-homologous end joining; PAH: polycyclic aromatic hydrocarbons; PCOS

  17. A multimetric approach for predicting the ecological integrity of New Zealand streams

    Directory of Open Access Journals (Sweden)

    Clapcott J.E.

    2014-01-01

    Full Text Available Integrating multiple measures of stream health into a combined metric can provide a holistic assessment of the ecological integrity of a stream. The aim of this study was to develop a multimetric index (MMI of stream integrity based on predictive modelling of national data sets of water quality, macroinvertebrates, fish and ecosystem process metrics. We used a boosted regression tree approach to calculate an observed/expected score for each metric prior to combining metrics in a MMI based on data availability and the strength of predictive models. The resulting MMI provides a geographically meaningful prediction of the ecological integrity of rivers in New Zealand, but identifies limitations in data and approach, providing focus for ongoing research.

  18. Integrated Solid Oxide Fuel Cell Power System Characteristics Prediction

    Directory of Open Access Journals (Sweden)

    Marian GAICEANU

    2009-07-01

    Full Text Available The main objective of this paper is to deduce the specific characteristics of the CHP 100kWe Solid Oxide Fuel Cell (SOFC Power System from the steady state experimental data. From the experimental data, the authors have been developed and validated the steady state mathematical model. From the control room the steady state experimental data of the SOFC power conditioning are available and using the developed steady state mathematical model, the authors have been obtained the characteristic curves of the system performed by Siemens-Westinghouse Power Corporation. As a methodology the backward and forward power flow analysis has been employed. The backward power flow makes possible to obtain the SOFC power system operating point at different load levels, resulting as the load characteristic. By knowing the fuel cell output characteristic, the forward power flow analysis is used to predict the power system efficiency in different operating points, to choose the adequate control decision in order to obtain the high efficiency operation of the SOFC power system at different load levels. The CHP 100kWe power system is located at Gas Turbine Technologies Company (a Siemens Subsidiary, TurboCare brand in Turin, Italy. The work was carried out through the Energia da Ossidi Solidi (EOS Project. The SOFC stack delivers constant power permanently in order to supply the electric and thermal power both to the TurboCare Company and to the national grid.

  19. Integrated model for predicting rice yield with climate change

    Science.gov (United States)

    Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

    2018-04-01

    Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

  20. Industrial Maintenance Strategies

    International Nuclear Information System (INIS)

    Sajjad Akbar

    2006-01-01

    Industrial plants have become more complex due to technological advancement. This has made the task of maintenance more difficult. The maintenance costs in terms of resources and downtime loss are so high that maintenance function has become a critical factor in a plant's profitability. Industry should devote as much forethought to the management of maintenance function as to production. Maintenance has grown from an art to a precise, technical engineering science. Planning, organizing scheduling and control of maintenance using modern techniques pays dividends in the form of reduced costs and increased reliability. The magnitude and the dimension of maintenance have multiplied due to development in the engineering technologies. Production cost and capacities are directly affected by the breakdown time. Total operating cost including the maintenance cost plays an important role in replacement dimension. The integrated system approach would bring forth the desired results of high maintenance standards. The standards once achieved and sustained, would add to the reliability of the plan and relieve heavy stresses and strains on the engineering logistic support. (author)

  1. Maintenance methods

    International Nuclear Information System (INIS)

    Sanchis, H.; Aucher, P.

    1990-01-01

    The maintenance method applied at the Hague is summarized. The method was developed in order to solve problems relating to: the different specialist fields, the need for homogeneity in the maintenance work, the equipment diversity, the increase of the materials used at the Hague's new facilities. The aim of the method is to create a knowhow formalism, to facilitate maintenance, to ensure the running of the operations and to improve the estimation of the maintenance cost. One of the method's difficulties is the demonstration of the profitability of the maintenance operations [fr

  2. Towards an integrative model of visual short-term memory maintenance: Evidence from the effects of attentional control, load, decay, and their interactions in childhood.

    Science.gov (United States)

    Shimi, Andria; Scerif, Gaia

    2017-12-01

    Over the past decades there has been a surge of research aiming to shed light on the nature of capacity limits to visual short-term memory (VSTM). However, an integrative account of this evidence is currently missing. We argue that investigating parameters constraining VSTM in childhood suggests a novel integrative model of VSTM maintenance, and that this in turn informs mechanisms of VSTM maintenance in adulthood. Over 3 experiments with 7-year-olds and young adults (total N=206), we provide evidence for multiple cognitive processes interacting to constrain VSTM performance. While age-related increases in storage capacity are undisputable, we replicate the finding that attentional processes control what information will be encoded and maintained in VSTM in the face of increased competition. Therefore, a central process to the current model is attentional refreshment, a mechanism that it is thought to reactivate and strengthen the signal of the visual representations. Critically, here we also show that attentional influences on VSTM are further constrained by additional factors, traditionally studied to the exclusion of each other, such as memory load and temporal decay. We propose that these processes work synergistically in an elegant manner to capture the adult-end state, whereas their less refined efficiency and modulations in childhood account for the smaller VSTM capacity that 7-year-olds demonstrate compared to older individuals. We conclude that going beyond the investigation of single cognitive mechanisms, to their interactions, holds the promise to understand both developing and fully developed maintenance in VSTM. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

    Science.gov (United States)

    Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

    2016-12-01

    Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus

  4. Auditoria integral de mantenimiento en instalaciones hospitalarias, un análisis objetivo // Maintenance assesment in hospital, an objective analysis

    Directory of Open Access Journals (Sweden)

    Héctor Acosta-Palmer

    2011-05-01

    Full Text Available Conocer los problemas que atentan contra la disponibilidad y confiabilidad del equipamiento médico,de los sistemas tecnológicos y de los quirófanos, es imprescindible para brindar un serviciohospitalario seguro y eficiente.Es objetivo del presente trabajo mostrar una metodología aplicada en cuatro hospitales, que permiteidentificar las principales deficiencias de la gestión de mantenimiento; además, se muestra laimplementación de la metodología, el modelo matemático empleado y los resultados.Para su organización la metodología empleada toma algunos principios de la ISO 19011:2002, seapoya en la estructura de la función mantenimiento con el objetivo de que no queden espaciosvacíos sin evaluar. Para garantizar niveles de exactitud aceptables se emplean métodos de expertosen la definición del valor de las áreas funcionales. La base de datos es obtenida en las propiasinstalaciones mediante entrevistas, revisión de documentos y observación de los procesos.Los resultados indican qué se están haciendo las cosas correctamente a un nivel promedio de un26,57% en las cuatro instalaciones estudiadas. La aplicación de la metodología ha permitidoidentificar las principales deficiencias e insuficiencias de la función mantenimiento.Palabras claves: gestión, mantenimiento, metodología, hospital.___________________________________________________________________AbstractTo know availability and reliability problems of the medical equipment, of the technological systems,and the operating room is indispensable to offer a sure and efficient hospital service.It is objective of the present work to show a methodology applied in five hospitals, for to bring forththe main deficiencies of the maintenance management, it is shown the implementation of themethodology, the pattern mathematical employee and the results.For their organization the used methodology takes some principles of the ISO 19011:2002, it leans inthe structure of the maintenance

  5. The integration of weighted human gene association networks based on link prediction.

    Science.gov (United States)

    Yang, Jian; Yang, Tinghong; Wu, Duzhi; Lin, Limei; Yang, Fan; Zhao, Jing

    2017-01-31

    Physical and functional interplays between genes or proteins have important biological meaning for cellular functions. Some efforts have been made to construct weighted gene association meta-networks by integrating multiple biological resources, where the weight indicates the confidence of the interaction. However, it is found that these existing human gene association networks share only quite limited overlapped interactions, suggesting their incompleteness and noise. Here we proposed a workflow to construct a weighted human gene association network using information of six existing networks, including two weighted specific PPI networks and four gene association meta-networks. We applied link prediction algorithm to predict possible missing links of the networks, cross-validation approach to refine each network and finally integrated the refined networks to get the final integrated network. The common information among the refined networks increases notably, suggesting their higher reliability. Our final integrated network owns much more links than most of the original networks, meanwhile its links still keep high functional relevance. Being used as background network in a case study of disease gene prediction, the final integrated network presents good performance, implying its reliability and application significance. Our workflow could be insightful for integrating and refining existing gene association data.

  6. Psychological maintenance as an integrated approach to prevention and correction of professional burning out of the medical staff

    Directory of Open Access Journals (Sweden)

    V. S. Kucher

    2014-01-01

    Full Text Available The syndrome of professional burning out is a complex of symptoms and signs evidenced in various negative psychic conditions at individual, interpersonal and organizational levels. It is formed owing to a long mismatch between the requirements of the professional environment and the resources of the expert. Analysis of the preventive and correctional programs as a psychological assistance showed insufficiency of such approach. Creation of preventive and correctional programs within psychological maintenance from the position of involution of professional resources, taking into account the theoretical - methodological basis (the concept, the purposes, tasks, system approach, criteria of efficiency and the subjective-personal resources of counteraction directed at activization to burning out at all stages of professional development is progressive.

  7. Initial integration of accident safety, waste management, recycling, effluent, and maintenance considerations for low-activation materials

    International Nuclear Information System (INIS)

    Piet, S.J.; Herring, J.S.; Cheng, E.T.; Fetter, S.

    1991-01-01

    A true low-activation material should ideally achieve all of the following objectives: 1. The possible prompt dose at the site boundary from 100% release of the inventory should be <2 Sv (200 rem); hence, the design would be inherently safe in that no possible accident could result in prompt radiation fatalities. 2. The possible cancers from realistic releases should be limited such that the accident risk is <0.1%/yr of the existing background cancer risk to local residents. This includes consideration of elemental volatility. 3. The decay heat should be limited so that active mitigative measures are not needed to protect the investment from cooling transients; hence, the design would be passively safe with respect to decay heat. 4. Used materials could be either recycled or disposed of as near- surface waste. 5. Hands-on maintenance should be possible around coolant system piping and components such as the heat exchanger. 6. Effluent of activation products should be minor compared to the major challenge of limiting tritium effluents. The most recent studies in these areas are used to determine which individual elements and engineering materials are low activation. Grades from A (best) to G (worst) are given to each element in the areas of accident safety, recycling, and waste management. Structure/fluid combinations are examined for low-activation effluents and out-of-blanket maintenance. The lowest activation structural materials are silicon carbide, vanadium alloys, and ferritic steels. Impurities and minor alloying constituents must be carefully considered. The lowest activation coolants are helium, water, FLiBe, and lithium. The lowest activation breeders are lithium, lithium oxide, lithium silicate, and FLiBe. Designs focusing on these truly low-activation materials will help achieve the excellent safety and environmental potential of fusion energy

  8. Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

    Science.gov (United States)

    Hunter, H. E.

    1972-01-01

    The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

  9. Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

    Science.gov (United States)

    Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

    2013-01-01

    The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Predicting Examination Performance Using an Expanded Integrated Hierarchical Model of Test Emotions and Achievement Goals

    Science.gov (United States)

    Putwain, Dave; Deveney, Carolyn

    2009-01-01

    The aim of this study was to examine an expanded integrative hierarchical model of test emotions and achievement goal orientations in predicting the examination performance of undergraduate students. Achievement goals were theorised as mediating the relationship between test emotions and performance. 120 undergraduate students completed…

  11. COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.

    Science.gov (United States)

    Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier

    2016-01-01

    Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses.

  12. Factors Influencing College Women's Contraceptive Behavior: An Application of the Integrative Model of Behavioral Prediction

    Science.gov (United States)

    Sutton, Jazmyne A.; Walsh-Buhi, Eric R.

    2017-01-01

    Objective: This study investigated variables within the Integrative Model of Behavioral Prediction (IMBP) as well as differences across socioeconomic status (SES) levels within the context of inconsistent contraceptive use among college women. Participants: A nonprobability sample of 515 female college students completed an Internet-based survey…

  13. Testing Predictive Models of Technology Integration in Mexico and the United States

    Science.gov (United States)

    Velazquez, Cesareo Morales

    2008-01-01

    Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

  14. Predicting Elementary Education Candidates' Technology Integration during Their Field Placement Instruction.

    Science.gov (United States)

    Negishi, Meiko; Elder, Anastasia D.; Hamil, J. Burnette; Mzoughi, Taha

    A growing concern in teacher education programs is technology training. Research confirms that training positively affects perservice teachers' attitudes and technology proficiency. However, little is known about the kinds of factors that may predict preservice teachers' integration of technology into their own instruction. The goal of this study…

  15. Structural integrity of frontostriatal connections predicts longitudinal changes in self-esteem.

    Science.gov (United States)

    Chavez, Robert S; Heatherton, Todd F

    2017-06-01

    Diverse neurological and psychiatric conditions are marked by a diminished sense of positive self-regard, and reductions in self-esteem are associated with risk for these disorders. Recent evidence has shown that the connectivity of frontostriatal circuitry reflects individual differences in self-esteem. However, it remains an open question as to whether the integrity of these connections can predict self-esteem changes over larger timescales. Using diffusion magnetic resonance imaging and probabilistic tractography, we demonstrate that the integrity of white matter pathways linking the medial prefrontal cortex to the ventral striatum predicts changes in self-esteem 8 months after initial scanning in a sample of 30 young adults. Individuals with greater integrity of this pathway during the scanning session at Time 1 showed increased levels of self-esteem at follow-up, whereas individuals with lower integrity showed stifled or decreased levels of self-esteem. These results provide evidence that frontostriatal white matter integrity predicts the trajectory of self-esteem development in early adulthood, which may contribute to blunted levels of positive self-regard seen in multiple psychiatric conditions, including depression and anxiety.

  16. Maintenance simulation: Software issues

    Energy Technology Data Exchange (ETDEWEB)

    Luk, C.H.; Jette, M.A.

    1995-07-01

    The maintenance of a distributed software system in a production environment involves: (1) maintaining software integrity, (2) maintaining and database integrity, (3) adding new features, and (4) adding new systems. These issues will be discussed in general: what they are and how they are handled. This paper will present our experience with a distributed resource management system that accounts for resources consumed, in real-time, on a network of heterogenous computers. The simulated environments to maintain this system will be presented relate to the four maintenance areas.

  17. Integrative approaches to the prediction of protein functions based on the feature selection

    Directory of Open Access Journals (Sweden)

    Lee Hyunju

    2009-12-01

    Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

  18. Preventative Maintenance.

    Science.gov (United States)

    Migliorino, James

    Boards of education must be convinced that spending money up front for preventive maintenance will, in the long run, save districts' tax dollars. A good program of preventive maintenance can minimize disruption of service; reduce repair costs, energy consumption, and overtime; improve labor productivity and system equipment reliability; handle…

  19. Subtask 2.4 - Integration and Synthesis in Climate Change Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Jaroslav Solc

    2009-06-01

    The Energy & Environmental Research Center (EERC) completed a brief evaluation of the existing status of predictive modeling to assess options for integration of our previous paleohydrologic reconstructions and their synthesis with current global climate scenarios. Results of our research indicate that short-term data series available from modern instrumental records are not sufficient to reconstruct past hydrologic events or predict future ones. On the contrary, reconstruction of paleoclimate phenomena provided credible information on past climate cycles and confirmed their integration in the context of regional climate history is possible. Similarly to ice cores and other paleo proxies, acquired data represent an objective, credible tool for model calibration and validation of currently observed trends. It remains a subject of future research whether further refinement of our results and synthesis with regional and global climate observations could contribute to improvement and credibility of climate predictions on a regional and global scale.

  20. At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration.

    Science.gov (United States)

    Stegen, James C

    2018-01-01

    To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.

  1. Improving Allergen Prediction in Main Crops Using a Weighted Integrative Method.

    Science.gov (United States)

    Li, Jing; Wang, Jing; Li, Jing

    2017-12-01

    As a public health problem, food allergy is frequently caused by food allergy proteins, which trigger a type-I hypersensitivity reaction in the immune system of atopic individuals. The food allergens in our daily lives are mainly from crops including rice, wheat, soybean and maize. However, allergens in these main crops are far from fully uncovered. Although some bioinformatics tools or methods predicting the potential allergenicity of proteins have been proposed, each method has their limitation. In this paper, we built a novel algorithm PREAL W , which integrated PREAL, FAO/WHO criteria and motif-based method by a weighted average score, to benefit the advantages of different methods. Our results illustrated PREAL W has better performance significantly in the crops' allergen prediction. This integrative allergen prediction algorithm could be useful for critical food safety matters. The PREAL W could be accessed at http://lilab.life.sjtu.edu.cn:8080/prealw .

  2. [Integrity].

    Science.gov (United States)

    Gómez Rodríguez, Rafael Ángel

    2014-01-01

    To say that someone possesses integrity is to claim that that person is almost predictable about responses to specific situations, that he or she can prudentially judge and to act correctly. There is a closed interrelationship between integrity and autonomy, and the autonomy rests on the deeper moral claim of all humans to integrity of the person. Integrity has two senses of significance for medical ethic: one sense refers to the integrity of the person in the bodily, psychosocial and intellectual elements; and in the second sense, the integrity is the virtue. Another facet of integrity of the person is la integrity of values we cherish and espouse. The physician must be a person of integrity if the integrity of the patient is to be safeguarded. The autonomy has reduced the violations in the past, but the character and virtues of the physician are the ultimate safeguard of autonomy of patient. A field very important in medicine is the scientific research. It is the character of the investigator that determines the moral quality of research. The problem arises when legitimate self-interests are replaced by selfish, particularly when human subjects are involved. The final safeguard of moral quality of research is the character and conscience of the investigator. Teaching must be relevant in the scientific field, but the most effective way to teach virtue ethics is through the example of the a respected scientist.

  3. Integrated petrophysical and reservoir characterization workflow to enhance permeability and water saturation prediction

    Science.gov (United States)

    Al-Amri, Meshal; Mahmoud, Mohamed; Elkatatny, Salaheldin; Al-Yousef, Hasan; Al-Ghamdi, Tariq

    2017-07-01

    Accurate estimation of permeability is essential in reservoir characterization and in determining fluid flow in porous media which greatly assists optimize the production of a field. Some of the permeability prediction techniques such as Porosity-Permeability transforms and recently artificial intelligence and neural networks are encouraging but still show moderate to good match to core data. This could be due to limitation to homogenous media while the knowledge about geology and heterogeneity is indirectly related or absent. The use of geological information from core description as in Lithofacies which includes digenetic information show a link to permeability when categorized into rock types exposed to similar depositional environment. The objective of this paper is to develop a robust combined workflow integrating geology and petrophysics and wireline logs in an extremely heterogeneous carbonate reservoir to accurately predict permeability. Permeability prediction is carried out using pattern recognition algorithm called multi-resolution graph-based clustering (MRGC). We will bench mark the prediction results with hard data from core and well test analysis. As a result, we showed how much better improvements are achieved in the permeability prediction when geology is integrated within the analysis. Finally, we use the predicted permeability as an input parameter in J-function and correct for uncertainties in saturation calculation produced by wireline logs using the classical Archie equation. Eventually, high level of confidence in hydrocarbon volumes estimation is reached when robust permeability and saturation height functions are estimated in presence of important geological details that are petrophysically meaningful.

  4. Predicting co-complexed protein pairs using genomic and proteomic data integration

    Directory of Open Access Journals (Sweden)

    King Oliver D

    2004-04-01

    Full Text Available Abstract Background Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H and affinity purification coupled with mass spectrometry (APMS have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship. Results Using a supervised machine learning approach – probabilistic decision tree, we integrated high-throughput protein interaction datasets and other gene- and protein-pair characteristics to predict co-complexed pairs (CCP of proteins. Our predictions proved more sensitive and specific than predictions based on Y2H or APMS methods alone or in combination. Among the top predictions not annotated as CCPs in our reference set (obtained from the MIPS complex catalogue, a significant fraction was found to physically interact according to a separate database (YPD, Yeast Proteome Database, and the remaining predictions may potentially represent unknown CCPs. Conclusions We demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP pairs from other characteristics. Our top-scoring CCP predictions provide testable hypotheses for experimental validation.

  5. Predictive Coding and Multisensory Integration: An Attentional Account of the Multisensory Mind

    Directory of Open Access Journals (Sweden)

    Durk eTalsma

    2015-03-01

    Full Text Available Multisensory integration involves a host of different cognitive processes, occurring at different stages of sensory processing. Here I argue that, despite recent insights suggesting that multisensory interactions can occur at very early latencies, the actual integration of individual sensory traces into an internally consistent mental representation is dependent on both top-down and bottom-up processes. Moreover, I argue that this integration is not limited to just sensory inputs, but that internal cognitive processes also shape the resulting mental representation. Studies showing that memory recall is affected by the initial multisensory context in which the stimuli were presented will be discussed, as well as several studies showing that mental imagery can affect multisensory illusions. This empirical evidence will be discussed from a predictive coding perspective, in which a central top-down attentional process is proposed to play a central role in coordinating the integration of all these inputs into a coherent mental representation.

  6. Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

    Science.gov (United States)

    Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

    2017-06-15

    Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning

  7. Defining predictive values using three different platelet function tests for CYP2C19 phenotype status on maintenance dual antiplatelet therapy after PCI.

    Science.gov (United States)

    Zhang, Hong-Zhe; Kim, Moo Hyun; Han, Jin-Yeong; Jeong, Young-Hoon

    2014-01-01

    Published data suggests that the presence of CYP2C19*2 or *3 loss of function (LOF) alleles is indicative of increased platelet aggregation and a higher risk of adverse cardiovascular events after clopidogrel administration. We sought to determine cut-off values using three different assays for prediction of the CYP2C19 phenotype in Korean percutaneous coronary intervention (PCI) patients. We enrolled 244 patients with drug-eluting stent implantation who were receiving clopidogrel and aspirin maintenance therapy for one month or more. Platelet reactivity was assessed with light transmittance aggregometry (LTA), multiple electrode aggregometry (MEA) and the VerifyNow P2Y12 assay (VN). The CYP2C19 genotype was analyzed by polymerase chain reaction (PCR) and snapshot method. The frequency of CYP2C19 LOF allele carriers was 58.6%. The cut-off values from LTA, MEA and VerifyNow for the identification of LOF allele carriers were as follows: 10 µM ADP-induced LTA ≥ 48 %, VN>242 PRU and MEA ≥ 37 U. Between the three tests, correlation was higher between LTA vs. VN assays (r=0.69) and LTA vs. MEA (r=0.56), with moderate agreement (κ=0.46 and κ=0.46), but between VN assay and MEA, both devices using whole blood showed a lower correlation (r=0.42) and agreement (κ=0.3). Our results provide guidance regarding cut-off levels for LTA, VerifyNow and MEA assays to detect the CYP2C19 LOF allele in patients during dual antiplatelet maintenance therapy.

  8. An electrically actuated imperfect microbeam: Dynamical integrity for interpreting and predicting the device response

    KAUST Repository

    Ruzziconi, Laura

    2013-02-20

    In this study we deal with a microelectromechanical system (MEMS) and develop a dynamical integrity analysis to interpret and predict the experimental response. The device consists of a clamped-clamped polysilicon microbeam, which is electrostatically and electrodynamically actuated. It has non-negligible imperfections, which are a typical consequence of the microfabrication process. A single-mode reduced-order model is derived and extensive numerical simulations are performed in a neighborhood of the first symmetric natural frequency, via frequency response diagrams and behavior chart. The typical softening behavior is observed and the overall scenario is explored, when both the frequency and the electrodynamic voltage are varied. We show that simulations based on direct numerical integration of the equation of motion in time yield satisfactory agreement with the experimental data. Nevertheless, these theoretical predictions are not completely fulfilled in some aspects. In particular, the range of existence of each attractor is smaller in practice than in the simulations. This is because these theoretical curves represent the ideal limit case where disturbances are absent, which never occurs under realistic conditions. A reliable prediction of the actual (and not only theoretical) range of existence of each attractor is essential in applications. To overcome this discrepancy and extend the results to the practical case where disturbances exist, a dynamical integrity analysis is developed. After introducing dynamical integrity concepts, integrity profiles and integrity charts are drawn. They are able to describe if each attractor is robust enough to tolerate the disturbances. Moreover, they detect the parameter range where each branch can be reliably observed in practice and where, instead, becomes vulnerable, i.e. they provide valuable information to operate the device in safe conditions according to the desired outcome and depending on the expected disturbances

  9. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

    Science.gov (United States)

    Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

    2012-01-01

    Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

  10. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

    Science.gov (United States)

    Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

    2012-07-01

    Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

  11. Maintenance Mentor

    National Research Council Canada - National Science Library

    Jacobs, John

    2003-01-01

    Maintenance Mentor (MXM) is a research effort conducted by a joint AFRL/HESR and Northrop Grumman Information Technology team to identify the basic, high-level requirements necessary for improving flight line diagnostic capabilities...

  12. Analysis of predicted and measured performance of an integrated compound parabolic concentrator (ICPC)

    Energy Technology Data Exchange (ETDEWEB)

    Winston, R.; O' Gallagher, J.J.; Muschaweck, J.; Mahoney, A.R.; Dudley, V.

    1999-07-01

    A variety of configurations of evacuated Integrated Compound Parabolic Concentrator (ICPC) tubes have been under development for many years. A particularly favorable optical design corresponds to the unit concentration limit for a fin CPC solution which is then coupled to a practical, thin, wedge-shaped absorber. Prototype collector modules using tubes with two different fin orientations (horizontal and vertical) have been fabricated and tested. Comprehensive measurements of the optical characteristics of the reflector and absorber have been used together with a detailed ray trace analysis to predict the optical performance characteristics of these designs. The observed performance agrees well with the predicted performance.

  13. Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches

    Directory of Open Access Journals (Sweden)

    Reza Rawassizadeh

    2015-09-01

    Full Text Available As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

  14. Energy-Efficient Integration of Continuous Context Sensing and Prediction into Smartwatches.

    Science.gov (United States)

    Rawassizadeh, Reza; Tomitsch, Martin; Nourizadeh, Manouchehr; Momeni, Elaheh; Peery, Aaron; Ulanova, Liudmila; Pazzani, Michael

    2015-09-08

    As the availability and use of wearables increases, they are becoming a promising platform for context sensing and context analysis. Smartwatches are a particularly interesting platform for this purpose, as they offer salient advantages, such as their proximity to the human body. However, they also have limitations associated with their small form factor, such as processing power and battery life, which makes it difficult to simply transfer smartphone-based context sensing and prediction models to smartwatches. In this paper, we introduce an energy-efficient, generic, integrated framework for continuous context sensing and prediction on smartwatches. Our work extends previous approaches for context sensing and prediction on wrist-mounted wearables that perform predictive analytics outside the device. We offer a generic sensing module and a novel energy-efficient, on-device prediction module that is based on a semantic abstraction approach to convert sensor data into meaningful information objects, similar to human perception of a behavior. Through six evaluations, we analyze the energy efficiency of our framework modules, identify the optimal file structure for data access and demonstrate an increase in accuracy of prediction through our semantic abstraction method. The proposed framework is hardware independent and can serve as a reference model for implementing context sensing and prediction on small wearable devices beyond smartwatches, such as body-mounted cameras.

  15. Computerized system for the support of the predictive maintenance in thermoelectric power stations of Comision Federal de Electricidad; Sistema computarizado para el apoyo del mantenimiento predictivo en centrales termoelectricas de la Comision Federal de Electricidad

    Energy Technology Data Exchange (ETDEWEB)

    Aranda A, Segio; Garcia M, Raul; Poujol G, Francisco; Chairez C, Carlos; Dominguez M, Nely [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico)

    2002-07-01

    This paper describes the functionality of the Integral System of Information for the Diagnosis of Predictive Maintenance (SIIDMP) in the thermoelectric centrals, whose primary target is to give support to the personnel related with the maintenance and operation of the thermoelectric central to optimize the application of the inspection, maintenance and its associated costs. It is important to comment that in the generating power stations of Comision Federal de Electricidad (CFE) techniques and methodologies for the preventive and corrective maintenance are applied, in addition of which they count on electronic equipment of operation dedicated to the inspection and control of vibratory equipment. The architecture of the SIIDMP is of the client-server type and for its design and implantation Windows NT 4.0 was used as operating system, SQL Server 7.0 as server and manager of the database, Visual C++ for the programs of data mining, Vision Basic 6.0 for the codification of the application programs and Interface Man-Machine (IMM), the communication mechanism Open Data Base Connectivity (ODBC) to establish the connection with the different data sources, as well as libraries of symbols and graphs that were included in the interface of the user. The main objective of the SIIDMP is to take care of the own necessities on optimization, improvements and savings in the operation of the power stations. With systems like the SIIDMP, a reduction of the costs due to shutdowns by accidental failures of the main equipment is looked for, limiting the deterioration of the equipment, as well as to provide knowledge and aid to all the personnel who take part in the management of the operation and conservation of the facilities of the power station. [Spanish] Se describe la funcionalidad del Sistema Integral de Informacion para el Diagnostico de Mantenimiento Predictivo en las centrales termoelectricas (SIIDMP), cuyo objetivo principal es apoyar al personal relacionado con el

  16. Instrumentation maintenance

    International Nuclear Information System (INIS)

    Mack, D.A.

    1976-09-01

    It is essential to any research activity that accurate and efficient measurements be made for the experimental parameters under consideration for each individual experiment or test. Satisfactory measurements in turn depend upon having the necessary instruments and the capability of ensuring that they are performing within their intended specifications. This latter requirement can only be achieved by providing an adequate maintenance facility, staffed with personnel competent to understand the problems associated with instrument adjustment and repair. The Instrument Repair Shop at the Lawrence Berkeley Laboratory is designed to achieve this end. The organization, staffing and operation of this system is discussed. Maintenance policy should be based on studies of (1) preventive vs. catastrophic maintenance, (2) records indicating when equipment should be replaced rather than repaired and (3) priorities established to indicate the order in which equipment should be repaired. Upon establishing a workable maintenance policy, the staff should be instructed so that they may provide appropriate scheduled preventive maintenance, calibration and corrective procedures, and emergency repairs. The education, training and experience of the maintenance staff is discussed along with the organization for an efficient operation. The layout of the various repair shops is described in the light of laboratory space and financial constraints

  17. Managed maintenance, the next step in power plant maintenance

    International Nuclear Information System (INIS)

    Butterworth, G.; Anderson, T.M.

    1984-01-01

    The Westinghouse Nuclear Services Integration Division managed maintenance services are described. Essential to the management and control of a total plant maintenance programme is the development of a comprehensive maintenance specification. During recent years Westinghouse has jointly developed total plant engineering-based maintenance specifications with a number of utilities. The process employed and the experience to date are described. To efficiently implement the maintenance programme Westinghouse has developed a computer software program specifically designed for day to day use at the power plant by maintenance personnel. This program retains an equipment maintenance history, schedules maintenance activities, issues work orders and performs a number of sophisticated analyses of the maintenance backlog and forecast, equipment failure rates, etc. The functions of this software program are described and details of Westinghouse efforts to support the utilities in reducing outage times through development of predefined outage plans for critical report maintenance activities are given. Also described is the experience gained in the training of specialized maintenance personnel, employing competency-based training techniques and equipment mock-ups, and the benefits experienced, in terms of improved quality and productivity of maintenance performed. The success experienced with these methods has caused Westinghouse to expand the use of these training techniques to the more routine skill areas of power plant maintenance. A significant reduction in the operating costs of nuclear power plants will only be brought about by a significant improvement in the quality of maintenance. Westinghouse intends to effect this change by expanding its international service capabilities and to make major investments in order to promote technological developments in the area of power plant maintenance. (author)

  18. An integrated prediction and optimization model of biogas production system at a wastewater treatment facility.

    Science.gov (United States)

    Akbaş, Halil; Bilgen, Bilge; Turhan, Aykut Melih

    2015-11-01

    This study proposes an integrated prediction and optimization model by using multi-layer perceptron neural network and particle swarm optimization techniques. Three different objective functions are formulated. The first one is the maximization of methane percentage with single output. The second one is the maximization of biogas production with single output. The last one is the maximization of biogas quality and biogas production with two outputs. Methane percentage, carbon dioxide percentage, and other contents' percentage are used as the biogas quality criteria. Based on the formulated models and data from a wastewater treatment facility, optimal values of input variables and their corresponding maximum output values are found out for each model. It is expected that the application of the integrated prediction and optimization models increases the biogas production and biogas quality, and contributes to the quantity of electricity production at the wastewater treatment facility. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Condition based maintenance in the context of opportunistic maintenance

    NARCIS (Netherlands)

    Koochaki, Javid; Bokhorst, Jos A. C.; Wortmann, Hans; Klingenberg, Warse

    2012-01-01

    Condition based maintenance (CBM) uses the operating condition of a component to predict a failure event. Compared to age based replacement (ABR), CBM usually results in higher availability and lower maintenance costs, since it tries to prevent unplanned downtime and avoid unnecessary preventive

  20. A Life Cycle Assessment Framework for Pavement Maintenance and Rehabilitation Technologies : or An Integrated Life Cycle Assessment (LCA) – Life Cycle Cost Analysis (LCCA) Framework for Pavement Maintenance and Rehabilitation

    Science.gov (United States)

    2018-02-01

    Qing Lu (ORCID ID 0000-0002-9120-9218) Given a huge amount of annual investment and large inputs of energy and natural resources in pavement maintenance and rehabilitation (M&R) activities, significant environmental improvement and budget saving can ...

  1. The Prediction-Focused Approach: An opportunity for hydrogeophysical data integration and interpretation

    Science.gov (United States)

    Hermans, Thomas; Nguyen, Frédéric; Klepikova, Maria; Dassargues, Alain; Caers, Jef

    2017-04-01

    Hydrogeophysics is an interdisciplinary field of sciences aiming at a better understanding of subsurface hydrological processes. If geophysical surveys have been successfully used to qualitatively characterize the subsurface, two important challenges remain for a better quantification of hydrological processes: (1) the inversion of geophysical data and (2) their integration in hydrological subsurface models. The classical inversion approach using regularization suffers from spatially and temporally varying resolution and yields geologically unrealistic solutions without uncertainty quantification, making their utilization for hydrogeological calibration less consistent. More advanced techniques such as coupled inversion allow for a direct use of geophysical data for conditioning groundwater and solute transport model calibration. However, the technique is difficult to apply in complex cases and remains computationally demanding to estimate uncertainty. In a recent study, we investigate a prediction-focused approach (PFA) to directly estimate subsurface physical properties from geophysical data, circumventing the need for classic inversions. In PFA, we seek a direct relationship between the data and the subsurface variables we want to predict (the forecast). This relationship is obtained through a prior set of subsurface models for which both data and forecast are computed. A direct relationship can often be derived through dimension reduction techniques. PFA offers a framework for both hydrogeophysical "inversion" and hydrogeophysical data integration. For hydrogeophysical "inversion", the considered forecast variable is the subsurface variable, such as the salinity. An ensemble of possible solutions is generated, allowing uncertainty quantification. For hydrogeophysical data integration, the forecast variable becomes the prediction we want to make with our subsurface models, such as the concentration of contaminant in a drinking water production well. Geophysical

  2. Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage

    Directory of Open Access Journals (Sweden)

    Simon-Shlomo ePoil

    2013-10-01

    Full Text Available Alzheimer's disease (AD is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a two-year period. We followed 86 patients initially diagnosed with MCI for two years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30 Hz can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/. We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention.

  3. Risk-based Operation and Maintenance for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Nielsen, Jannie Jessen

    2011-01-01

    For offshore wind turbines, costs to Operation and Maintenance (OM) are substantial, and can be expected to increase when wind farms are placed at deeper water depths and in more harsh environments. Traditional strategies for OM include corrective and preventive (scheduled and condition...... statistics and costs of the different operations. The different OM strategies are described and compared in an illustrative example with focus on which types of information that are needed. Special focus is on comparison between risk-based maintenance strategies and the conventional maintenance planning...... and are often the driving mechanisms for failures / faults that need maintenance. Observations of the degree of damage can increase the reliability of predictions and decrease the costs of OM if integrated in a risk-based framework theoretically based on pre-posterior Bayesian decision theory. The mathematical...

  4. Maintenance of Blood-Brain Barrier Integrity in Hypertension: A Novel Benefit of Exercise Training for Autonomic Control

    Directory of Open Access Journals (Sweden)

    Leila Buttler

    2017-12-01

    Full Text Available The blood-brain barrier (BBB is a complex multicellular structure acting as selective barrier controlling the transport of substances between these compartments. Accumulating evidence has shown that chronic hypertension is accompanied by BBB dysfunction, deficient local perfusion and plasma angiotensin II (Ang II access into the parenchyma of brain areas related to autonomic circulatory control. Knowing that spontaneously hypertensive rats (SHR exhibit deficient autonomic control and brain Ang II hyperactivity and that exercise training is highly effective in correcting both, we hypothesized that training, by reducing Ang II content, could improve BBB function within autonomic brain areas of the SHR. After confirming the absence of BBB lesion in the pre-hypertensive SHR, but marked fluorescein isothiocyanate dextran (FITC, 10 kD leakage into the brain parenchyma of the hypothalamic paraventricular nucleus (PVN, nucleus of the solitary tract, and rostral ventrolateral medulla during the established phase of hypertension, adult SHR, and age-matched WKY were submitted to a treadmill training (T or kept sedentary (S for 8 weeks. The robust FITC leakage within autonomic areas of the SHR-S was largely reduced and almost normalized since the 2nd week of training (T2. BBB leakage reduction occurred simultaneously and showed strong correlations with both decreased LF/HF ratio to the heart and reduced vasomotor sympathetic activity (power spectral analysis, these effects preceding the appearance of resting bradycardia (T4 and partial pressure fall (T8. In other groups of SHR-T simultaneously infused with icv Ang II or saline (osmotic mini-pumps connected to a lateral ventricle cannula we proved that decreased local availability of this peptide and reduced microglia activation (IBA1 staining are crucial mechanisms conditioning the restoration of BBB integrity. Our data also revealed that Ang II-induced BBB lesion was faster within the PVN (T2, suggesting

  5. 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

  6. Arabidopsis thaliana gonidialess A/Zuotin related factors (GlsA/ZRF) are essential for maintenance of meristem integrity.

    Science.gov (United States)

    Guzmán-López, José Alfredo; Abraham-Juárez, María Jazmín; Lozano-Sotomayor, Paulina; de Folter, Stefan; Simpson, June

    2016-05-01

    Observation of a differential expression pattern, including strong expression in meristematic tissue of an Agave tequilana GlsA/ZRF ortholog suggested an important role for this gene during bulbil formation and developmental changes in this species. In order to better understand this role, the two GlsA/ZFR orthologs present in the genome of Arabidopsis thaliana were functionally characterized by analyzing expression patterns, double mutant phenotypes, promoter-GUS fusions and expression of hormone related or meristem marker genes. Patterns of expression for A. thaliana show that GlsA/ZFR genes are strongly expressed in SAMs and RAMs in mature plants and developing embryos and double mutants showed multiple changes in morphology related to both SAM and RAM tissues. Typical double mutants showed stunted growth of aerial and root tissue, formation of multiple ectopic meristems and effects on cotyledons, leaves and flowers. The KNOX genes STM and BP were overexpressed in double mutants whereas CLV3, WUSCHEL and AS1 were repressed and lack of AtGlsA expression was also associated with changes in localization of auxin and cytokinin. These results suggest that GlsA/ZFR is an essential component of the machinery that maintains the integrity of SAM and RAM tissue and underline the potential to identify new genes or gene functions based on observations in non-model plants.

  7. RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach

    Energy Technology Data Exchange (ETDEWEB)

    Novichkov, Pavel S.; Rodionov, Dmitry A.; Stavrovskaya, Elena D.; Novichkova, Elena S.; Kazakov, Alexey E.; Gelfand, Mikhail S.; Arkin, Adam P.; Mironov, Andrey A.; Dubchak, Inna

    2010-05-26

    RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.

  8. Integrating environmental and genetic effects to predict responses of tree populations to climate.

    Science.gov (United States)

    Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N

    2010-01-01

    Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.

  9. Brain systems for probabilistic and dynamic prediction: computational specificity and integration.

    Directory of Open Access Journals (Sweden)

    Jill X O'Reilly

    2013-09-01

    Full Text Available A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI we showed that activity in two brain systems (typically associated with reward learning and motor control could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.

  10. Online Sentence Comprehension in PPA: Verb-Based Integration and Prediction

    Directory of Open Access Journals (Sweden)

    Jennifer E Mack

    2015-05-01

    Full Text Available Introduction. Impaired language comprehension is frequently observed in primary progressive aphasia (PPA. Word comprehension deficits are characteristic of the semantic variant (PPA-S whereas sentence comprehension deficits are more prevalent in the agrammatic (PPA-G and logopenic (PPA-L variants (Amici et al., 2007; Gorno-Tempini et al., 2011; Thompson et al., 2013. Word and sentence comprehension deficits have also been shown to have distinct neural substrates in PPA (Mesulam, Thompson, Weintraub, & Rogalski, in press. However, little is known about the relationship between word and sentence comprehension processes in PPA, specifically how words are accessed, combined, and used to predict upcoming elements within a sentence. A previous study demonstrated that listeners with stroke-induced agrammatic aphasia rapidly access verb meanings and use them to semantically integrate verb-arguments; however, they show deficits in using verb meanings predictively (Mack, Ji, & Thompson, 2013. The present study tested whether listeners with PPA are able to access verb meanings and to use this information to integrate and predict verb-arguments. Methods. Fifteen adults with PPA (8 with PPA-G, 3 with PPA-L, and 4 with PPA-S and ten age-matched controls participated in two eyetracking experiments. In both experiments, participants heard sentences with restrictive verbs that were semantically compatible with only one object in a four-picture visual array (e.g., eat when the array included a cake and three non-edible objects and unrestrictive verbs (e.g., move that were compatible with all four objects. The verb-based integration experiment tested access to verb meaning and its effects on integration of the direct object (e.g., Susan will eat/move the cake; the verb-based prediction experiment examined prediction of the direct object (e.g., Susan will eat/move the …. The dependent variable was the rate of fixations on the target picture (e.g., the cake in the

  11. Understanding Eating Behaviors through Parental Communication and the Integrative Model of Behavioral Prediction.

    Science.gov (United States)

    Scheinfeld, Emily; Shim, Minsun

    2017-05-01

    Emerging adulthood (EA) is an important yet overlooked period for developing long-term health behaviors. During these years, emerging adults adopt health behaviors that persist throughout life. This study applies the Integrative Model of Behavioral Prediction (IMBP) to examine the role of childhood parental communication in predicting engagement in healthful eating during EA. Participants included 239 college students, ages 18 to 25, from a large university in the southern United States. Participants were recruited and data collection occurred spring 2012. Participants responded to measures to assess perceived parental communication, eating behaviors, attitudes, subjective norms, and behavioral control over healthful eating. SEM and mediation analyses were used to address the hypotheses posited. Data demonstrated that perceived parent-child communication - specifically, its quality and target-specific content - significantly predicted emerging adults' eating behaviors, mediated through subjective norm and perceived behavioral control. This study sets the stage for further exploration and understanding of different ways parental communication influences emerging adults' healthy behavior enactment.

  12. High-sensitivity C-reactive protein is predictive of successful cardioversion for atrial fibrillation and maintenance of sinus rhythm after conversion.

    Science.gov (United States)

    Watanabe, Eiichi; Arakawa, Tomoharu; Uchiyama, Tatsushi; Kodama, Itsuo; Hishida, Hitoshi

    2006-04-14

    Cardioversion for atrial fibrillation (AF) is the most effective treatment for the restoration of sinus rhythm (SR). Recently, an elevated level of hs-CRP has been shown to be associated with AF burden, suggesting that inflammation increases the propensity for persistence of AF. We examined whether the level of high-sensitivity C-reactive protein (hs-CRP) was predictive of the outcome of cardioversion for AF. One hundred and six patients with a history of symptomatic AF lasting > or =1 day (age 63+/-14 years, mean+/-S.D.) underwent cardioversion. Echocardiography and hs-CRP assay were performed immediately prior to cardioversion. SR was restored in 84 patients (79%). By using selected cutoff values, multiple discriminant analysis revealed significant associations between successful cardioversion and a shorter duration of AF (AF duration or =60%, OR 0.92, 95% CI 0.86-0.99), and lower hs-CRP level (hs-CRP or =0.06 mg/dL, Cox proportional-hazards regression model found that only hs-CRP level was an independent predictor of AF recurrence (OR 5.30, 95% CI 2.46-11.5) after adjustment for coexisting cardiovascular risks. When patients were divided by the hs-CRP level of 0.06 mg/dL, percentage of maintenance of SR below and above the cutoff was 53% and 4%, respectively (log-rank test, pmaintenance of SR after conversion.

  13. An integrative approach to ortholog prediction for disease-focused and other functional studies

    Directory of Open Access Journals (Sweden)

    Perrimon Norbert

    2011-08-01

    Full Text Available Abstract Background Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. Results We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt, for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM and genes in genome-wide association study (GWAS data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist. Conclusions DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

  14. An integrative approach to ortholog prediction for disease-focused and other functional studies.

    Science.gov (United States)

    Hu, Yanhui; Flockhart, Ian; Vinayagam, Arunachalam; Bergwitz, Clemens; Berger, Bonnie; Perrimon, Norbert; Mohr, Stephanie E

    2011-08-31

    Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt), for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM) and genes in genome-wide association study (GWAS) data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist). DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

  15. Estimating cross-validatory predictive p-values with integrated importance sampling for disease mapping models.

    Science.gov (United States)

    Li, Longhai; Feng, Cindy X; Qiu, Shi

    2017-06-30

    An important statistical task in disease mapping problems is to identify divergent regions with unusually high or low risk of disease. Leave-one-out cross-validatory (LOOCV) model assessment is the gold standard for estimating predictive p-values that can flag such divergent regions. However, actual LOOCV is time-consuming because one needs to rerun a Markov chain Monte Carlo analysis for each posterior distribution in which an observation is held out as a test case. This paper introduces a new method, called integrated importance sampling (iIS), for estimating LOOCV predictive p-values with only Markov chain samples drawn from the posterior based on a full data set. The key step in iIS is that we integrate away the latent variables associated the test observation with respect to their conditional distribution without reference to the actual observation. By following the general theory for importance sampling, the formula used by iIS can be proved to be equivalent to the LOOCV predictive p-value. We compare iIS and other three existing methods in the literature with two disease mapping datasets. Our empirical results show that the predictive p-values estimated with iIS are almost identical to the predictive p-values estimated with actual LOOCV and outperform those given by the existing three methods, namely, the posterior predictive checking, the ordinary importance sampling, and the ghosting method by Marshall and Spiegelhalter (2003). Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. CANDU plant maintenance: Recent developments

    International Nuclear Information System (INIS)

    Charlebois, P.

    2000-01-01

    CANDU units have long been recognized for their exceptional safety and reliability. Continuing development in the maintenance area has played a key role in achieving this performance level. For over two decades, safety system availability has been monitored closely and system maintenance programs adjusted accordingly to maintain high levels of performance. But as the plants approach mid life in a more competitive environment and component aging becomes a concern, new methods and techniques are necessary. As a result, recent developments are moving the maintenance program largely from a corrective and preventive approach to predictive and condition based maintenance. The application of these techniques is also being extended to safety related systems. These recent developments include use of reliability centred methods to define system maintenance requirements and strategies. This approach has been implemented on a number of systems at Canadian CANDU plants with positive results. The pilot projects demonstrated that the overall maintenance effort remained relatively constant while the system performance improved. It was also possible to schedule some of the redundant component maintenance during plant operation without adverse impact on system availability. The probabilistic safety assessment was found to be useful in determining the safety implications of component outages. These new maintenance strategies are now making use of predictive and condition based maintenance techniques to anticipate equipment breakdown and schedule preventive maintenance as the need arises rather than time based. Some of these techniques include valve diagnostics, vibration monitoring, oil analysis, thermography. Of course, these tools and techniques must form part of an overall maintenance management system to ensure that maintenance becomes a living program. To facilitate this process and contain costs, new information technology tools are being introduced to provide system engineers

  17. A multi-level maintenance policy for a multi-component and multifailure mode system with two independent failure modes

    International Nuclear Information System (INIS)

    Zhu, Wenjin; Fouladirad, Mitra; Bérenguer, Christophe

    2016-01-01

    This paper studies the maintenance modelling of a multi-component system with two independent failure modes with imperfect prediction signal in the context of a system of systems. Each individual system consists of multiple series components and the failure modes of all the components are divided into two classes due to their consequences: hard failure and soft failure, where the former causes system failure while the later results in inferior performance (production reduction) of system. Besides, the system is monitored and can be alerted by imperfect prediction signal before hard failure. Based on an illustration example of offshore wind farm, in this paper three maintenance strategies are considered: periodic routine, reactive and opportunistic maintenance. The periodic routine maintenance is scheduled at fixed period for each individual system in the perspective of system of systems. Between two successive routine maintenances, the reactive maintenance is instructed by the imperfect prediction signal according to two criterion proposed in this study for the system components. Due to the high setup cost and practical restraints of implementing maintenance activities, both routine and reactive maintenance can create the opportunities of maintenance for the other components of an individual system. The life cycle of the system and the cost of the proposed maintenance policies are analytically derived. Restrained by the complexity from both the system failure modelling and maintenance strategies, the performances and application scope of the proposed maintenance model are evaluated by numerical simulations. - Highlights: • We study the life behavior of a complex system with two failure modes. • We consider the imperfect prediction signal of potential failure by monitoring. • We propose an integrated maintenance policy with three levels based on wind turbine. • We derive the mathematical cost formulations for the proposed maintenance policy.

  18. Integrative Analysis of Gene Expression Data Including an Assessment of Pathway Enrichment for Predicting Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Pingzhao Hu

    2006-01-01

    biological pathways. In particular, we observed that by integrating information from the insulin signalling pathway into our prediction model, we achieved better prediction of prostate cancer. Conclusions: Our data integration methodology provides an efficient way to identify biologically sound and statistically significant pathways from gene expression data. The significant gene expression phenotypes identified in our study have the potential to characterize complex genetic alterations in prostate cancer.

  19. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    Science.gov (United States)

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-01-01

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435

  20. Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

    Energy Technology Data Exchange (ETDEWEB)

    Hao, Ming; Wang, Yanli, E-mail: ywang@ncbi.nlm.nih.gov; Bryant, Stephen H., E-mail: bryant@ncbi.nlm.nih.gov

    2016-02-25

    Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

  1. ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

    Directory of Open Access Journals (Sweden)

    Milos Bogdanovic

    2013-08-01

    Full Text Available Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

  2. ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.

    Science.gov (United States)

    Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja

    2013-08-15

    Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.

  3. Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

    International Nuclear Information System (INIS)

    Hao, Ming; Wang, Yanli; Bryant, Stephen H.

    2016-01-01

    Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.

  4. Proceedings of the third international conference on CANDU maintenance

    International Nuclear Information System (INIS)

    1995-01-01

    The third international conference on Candu maintenance included sessions on the following topics: predictive maintenance, reliability improvements, steam generator monitoring, tools and instrumentation, valve performance, fuel channel inspection and maintenance, steam generator maintenance, environmental qualification, predictive maintenance, instrumentation and control, steam generator cleaning, decontamination and radiation protection, inspection techniques, maintenance program strategies and valve packing experience, remote tooling/ robotics and fuel handling. The individual papers have been abstracted separately

  5. Proceedings of the third international conference on CANDU maintenance

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-12-31

    The third international conference on Candu maintenance included sessions on the following topics: predictive maintenance, reliability improvements, steam generator monitoring, tools and instrumentation, valve performance, fuel channel inspection and maintenance, steam generator maintenance, environmental qualification, predictive maintenance, instrumentation and control, steam generator cleaning, decontamination and radiation protection, inspection techniques, maintenance program strategies and valve packing experience, remote tooling/ robotics and fuel handling. The individual papers have been abstracted separately.

  6. Fast integration-based prediction bands for ordinary differential equation models.

    Science.gov (United States)

    Hass, Helge; Kreutz, Clemens; Timmer, Jens; Kaschek, Daniel

    2016-04-15

    To gain a deeper understanding of biological processes and their relevance in disease, mathematical models are built upon experimental data. Uncertainty in the data leads to uncertainties of the model's parameters and in turn to uncertainties of predictions. Mechanistic dynamic models of biochemical networks are frequently based on nonlinear differential equation systems and feature a large number of parameters, sparse observations of the model components and lack of information in the available data. Due to the curse of dimensionality, classical and sampling approaches propagating parameter uncertainties to predictions are hardly feasible and insufficient. However, for experimental design and to discriminate between competing models, prediction and confidence bands are essential. To circumvent the hurdles of the former methods, an approach to calculate a profile likelihood on arbitrary observations for a specific time point has been introduced, which provides accurate confidence and prediction intervals for nonlinear models and is computationally feasible for high-dimensional models. In this article, reliable and smooth point-wise prediction and confidence bands to assess the model's uncertainty on the whole time-course are achieved via explicit integration with elaborate correction mechanisms. The corresponding system of ordinary differential equations is derived and tested on three established models for cellular signalling. An efficiency analysis is performed to illustrate the computational benefit compared with repeated profile likelihood calculations at multiple time points. The integration framework and the examples used in this article are provided with the software package Data2Dynamics, which is based on MATLAB and freely available at http://www.data2dynamics.org helge.hass@fdm.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e

  7. Reliability Centered Maintenance - Methodologies

    Science.gov (United States)

    Kammerer, Catherine C.

    2009-01-01

    Journal article about Reliability Centered Maintenance (RCM) methodologies used by United Space Alliance, LLC (USA) in support of the Space Shuttle Program at Kennedy Space Center. The USA Reliability Centered Maintenance program differs from traditional RCM programs because various methodologies are utilized to take advantage of their respective strengths for each application. Based on operational experience, USA has customized the traditional RCM methodology into a streamlined lean logic path and has implemented the use of statistical tools to drive the process. USA RCM has integrated many of the L6S tools into both RCM methodologies. The tools utilized in the Measure, Analyze, and Improve phases of a Lean Six Sigma project lend themselves to application in the RCM process. All USA RCM methodologies meet the requirements defined in SAE JA 1011, Evaluation Criteria for Reliability-Centered Maintenance (RCM) Processes. The proposed article explores these methodologies.

  8. Paranal maintenance and CMMS experience

    Science.gov (United States)

    Montano, Nelson

    2004-10-01

    During the last four years of operations, low technical downtime has been one of the relevant records of the Paranal Observatory. From the beginning of the Very Large Telescope (VLT) project, European Southern Observatory (ESO) has considered the implementation of a proper maintenance strategy a fundamental point in order to ensure low technical down time and preserve the Observatory's assets. The implementation of the maintenance strategy was based on the following aspects: - Strong maintenance sense during the design stage. Line Replacement Unit (LRU) concept, standardization and modularity of the Observatory equipment - Creation of a dedicated team for Maintenance - The implementation of a Computerized Maintenance Management System After four operational years, the result of these aspects has exceeded the expectations; the Observatory has been operating with high availability under a sustainable strategy. The strengths of the maintenance strategy have been based on modern maintenance concepts applied by regular production companies, where any minute of down time involves high cost. The operation of the actual Paranal Maintenance System is based mainly on proactive activities, such as regular inspections, preventive maintenance (PM) and predictive maintenance (PdM) plans. Nevertheless, it has been necessary to implement a strong plan for corrective maintenance (CM). The Spare Parts Strategy has also been an important point linked to the Maintenance Strategy and CMMS implementation. At present, almost 4,000 items related to the Observatory spare parts are loaded into the CMMS database. Currently, we are studying the implementation of a Reliability Centered Maintenance (RCM) project in one of our critical systems The following document presents the actual status of the Paranal Maintenance Strategy and which have been the motivations to implement the established strategy.

  9. Predicting Athletes’ Pre-Exercise Fluid Intake: A Theoretical Integration Approach

    Directory of Open Access Journals (Sweden)

    Chunxiao Li

    2018-05-01

    Full Text Available Pre-exercise fluid intake is an important healthy behavior for maintaining athletes’ sports performances and health. However, athletes’ behavioral adherence to fluid intake and its underlying psychological mechanisms have not been investigated. This prospective study aimed to use a health psychology model that integrates the self-determination theory and the theory of planned behavior for understanding pre-exercise fluid intake among athletes. Participants (n = 179 were athletes from college sport teams who completed surveys at two time points. Baseline (Time 1 assessment comprised psychological variables of the integrated model (i.e., autonomous and controlled motivation, attitude, subjective norm, perceived behavioral control, and intention and fluid intake (i.e., behavior was measured prospectively at one month (Time 2. Path analysis showed that the positive association between autonomous motivation and intention was mediated by subjective norm and perceived behavioral control. Controlled motivation positively predicted the subjective norm. Intentions positively predicted pre-exercise fluid intake behavior. Overall, the pattern of results was generally consistent with the integrated model, and it was suggested that athletes’ pre-exercise fluid intake behaviors were associated with the motivational and social cognitive factors of the model. The research findings could be informative for coaches and sport scientists to promote athletes’ pre-exercise fluid intake behaviors.

  10. Stock return predictability and market integration: The role of global and local information

    Directory of Open Access Journals (Sweden)

    David G. McMillan

    2016-12-01

    Full Text Available This paper examines the predictability of a range of international stock markets where we allow the presence of both local and global predictive factors. Recent research has argued that US returns have predictive power for international stock returns. We expand this line of research, following work on market integration, to include a more general definition of the global factor, based on principal components analysis. Results identify three global expected returns factors, one related to the major stock markets of the US, UK and Asia and one related to the other markets analysed. The third component is related to dividend growth. A single dominant realised returns factor is also noted. A forecasting exercise comparing the principal components based factors to a US return factor and local market only factors, as well as the historical mean benchmark finds supportive evidence for the former approach. It is hoped that the results from this paper will be informative on three counts. First, to academics interested in understanding the dynamics asset price movement. Second, to market participants who aim to time the market and engage in portfolio and risk management. Third, to those (policy makers and others who are interested in linkages across international markets and the nature and degree of integration.

  11. The Clinical Obesity Maintenance Model: An Integration of Psychological Constructs including Mood, Emotional Regulation, Disordered Overeating, Habitual Cluster Behaviours, Health Literacy and Cognitive Function

    OpenAIRE

    Raman, Jayanthi; Smith, Evelyn; Hay, Phillipa

    2013-01-01

    Psychological distress and deficits in executive functioning are likely to be important barriers to effective weight loss maintenance. The purpose of this paper is twofold. First, in the light of recent evidence in the fields of neuropsychology and obesity, particularly on the deficits in the executive function in overweight and obese individuals, a conceptual and theoretical framework of obesity maintenance is introduced by way of a clinical obesity maintenance model (COMM). It is argued tha...

  12. Atomic Energy Control Board (AECB) staff assessment and views of current maintenance practices of a four unit CANDU plant

    International Nuclear Information System (INIS)

    Malek, I.

    1995-01-01

    This paper discusses the AECB practices in assessing maintenance activities at one four unit CANDU nuclear plant.-it outlines the authority of the AECB in enforcing the licence condition concerned with maintenance, and how this is interpreted by AECB site staff to measure and report maintenance activities. The AECB staff attaches great importance to proper maintenance as it affects safe operation. Programs used by the licensee staff to identify safety important components, or to predict degradations and failures are of particular interest. In our experience, the application of such programs has been generally good. However, their integration into an overall maintenance scheme can be improved, and the possibilities of integration are not well understood. This paper includes examples of such integration to illustrate our views and to highlight the resultant benefits that AECB staff believes are possible. (author)

  13. Maintenance for life management

    International Nuclear Information System (INIS)

    Hevia, F.

    1997-01-01

    Life Management is based on the detection, monitoring and control of long-term degradation that affects individual plant components and important populations. Experience has shown that in many cases current maintenance practices do not attend to ageing directly; instead they deal with the consequences when it is already too late, when good Life Management is no longer practical. This has brought about the need for specific Maintenance Evaluation and Improvement Programmes to adjust to the basic objective of Life Management which is to project against, monitor and mitigate ageing that can affect the safe and profitable operating life of the facility. New regulatory requirements for ageing monitoring and effective maintenance to ensure safety (Maintenance Rule) have made it even more necessary to implement the Maintenance Evaluation Programme to cope with ageing, and to integrate that tasks in both programmes to optimise effort and use of tools. This paper presents a brief description of the objectives and methodologies of these Programmes which has been applied to plants around the world and in Spain at the Garona and Vandellos II plants in Spain as part of the PIE project for developing a Remanent Life Evaluation System for nuclear power plants. (Author)

  14. Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients.

    Science.gov (United States)

    Isik, Zerrin; Ercan, Muserref Ece

    2017-10-01

    Integration of several types of patient data in a computational framework can accelerate the identification of more reliable biomarkers, especially for prognostic purposes. This study aims to identify biomarkers that can successfully predict the potential survival time of a cancer patient by integrating the transcriptomic (RNA-Seq), proteomic (RPPA), and protein-protein interaction (PPI) data. The proposed method -RPBioNet- employs a random walk-based algorithm that works on a PPI network to identify a limited number of protein biomarkers. Later, the method uses gene expression measurements of the selected biomarkers to train a classifier for the survival time prediction of patients. RPBioNet was applied to classify kidney renal clear cell carcinoma (KIRC), glioblastoma multiforme (GBM), and lung squamous cell carcinoma (LUSC) patients based on their survival time classes (long- or short-term). The RPBioNet method correctly identified the survival time classes of patients with between 66% and 78% average accuracy for three data sets. RPBioNet operates with only 20 to 50 biomarkers and can achieve on average 6% higher accuracy compared to the closest alternative method, which uses only RNA-Seq data in the biomarker selection. Further analysis of the most predictive biomarkers highlighted genes that are common for both cancer types, as they may be driver proteins responsible for cancer progression. The novelty of this study is the integration of a PPI network with mRNA and protein expression data to identify more accurate prognostic biomarkers that can be used for clinical purposes in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Integration of Tuyere, Raceway and Shaft Models for Predicting Blast Furnace Process

    Science.gov (United States)

    Fu, Dong; Tang, Guangwu; Zhao, Yongfu; D'Alessio, John; Zhou, Chenn Q.

    2018-06-01

    A novel modeling strategy is presented for simulating the blast furnace iron making process. Such physical and chemical phenomena are taking place across a wide range of length and time scales, and three models are developed to simulate different regions of the blast furnace, i.e., the tuyere model, the raceway model and the shaft model. This paper focuses on the integration of the three models to predict the entire blast furnace process. Mapping output and input between models and an iterative scheme are developed to establish communications between models. The effects of tuyere operation and burden distribution on blast furnace fuel efficiency are investigated numerically. The integration of different models provides a way to realistically simulate the blast furnace by improving the modeling resolution on local phenomena and minimizing the model assumptions.

  16. Predicting 2D target velocity cannot help 2D motion integration for smooth pursuit initiation.

    Science.gov (United States)

    Montagnini, Anna; Spering, Miriam; Masson, Guillaume S

    2006-12-01

    Smooth pursuit eye movements reflect the temporal dynamics of bidimensional (2D) visual motion integration. When tracking a single, tilted line, initial pursuit direction is biased toward unidimensional (1D) edge motion signals, which are orthogonal to the line orientation. Over 200 ms, tracking direction is slowly corrected to finally match the 2D object motion during steady-state pursuit. We now show that repetition of line orientation and/or motion direction does not eliminate the transient tracking direction error nor change the time course of pursuit correction. Nonetheless, multiple successive presentations of a single orientation/direction condition elicit robust anticipatory pursuit eye movements that always go in the 2D object motion direction not the 1D edge motion direction. These results demonstrate that predictive signals about target motion cannot be used for an efficient integration of ambiguous velocity signals at pursuit initiation.

  17. Maintenance and environmental qualification

    International Nuclear Information System (INIS)

    Martin, R.S.; Austin, D.G.

    1995-01-01

    The design of today's nuclear generating plants involves many detailed design considerations. This includes comprehensive look at aging effects on plant components over their expected lifetimes. This is important to ensuring that the plant operates safely throughout its life. The effects of aging are required to be documented in detail in today's designs. This documentation provides assurance that safe operating conditions are maintained throughout the station life cycle. This requirement is analogous to the longer standing requirement to ensure pressure boundary integrity. The pressure boundary integrity requirement has existed in the industry since its inception. The subject of plant aging effects and the maintenance of functionality is known as Environmental Qualification (EQ). This paper will attempt to explain the wisdom of EQ and the potential for optimizing maintenance activities (to move from reactive to proactive activities), within the context of the overall maintenance program. It is the author's intent to encourage the active involvement of maintenance professionals in the effective implementation of the ongoing EQ program so that the benefits are maximized

  18. A Distributed Model Predictive Control approach for the integration of flexible loads, storage and renewables

    DEFF Research Database (Denmark)

    Ferrarini, Luca; Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso

    2014-01-01

    This paper presents an innovative solution based on distributed model predictive controllers to integrate the control and management of energy consumption, energy storage, PV and wind generation at customer side. The overall goal is to enable an advanced prosumer to autoproduce part of the energy...... he needs with renewable sources and, at the same time, to optimally exploit the thermal and electrical storages, to trade off its comfort requirements with different pricing schemes (including real-time pricing), and apply optimal control techniques rather than sub-optimal heuristics....

  19. Model Predictive Control of Grid Connected Modular Multilevel Converter for Integration of Photovoltaic Power Systems

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; Shahirinia, Amir

    2017-01-01

    Investigation of an advanced control structure for integration of Photovoltaic Power Systems through Grid Connected-Modular Multilevel Converter (GC-MMC) is proposed in this paper. To achieve this goal, a non-linear model of MMC regarding considering of negative and positive sequence components has...... been presented. Then, due to existence of unbalance voltage faults in distribution grid, non-linarites and uncertainties in model, model predictive controller which is developed for GC-MMC. They are implemented based upon positive and negative components of voltage and current to mitigate the power...

  20. An integrated numerical model for the prediction of Gaussian and billet shapes

    DEFF Research Database (Denmark)

    Hattel, Jesper; Pryds, Nini; Pedersen, Trine Bjerre

    2004-01-01

    Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained...... by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency...

  1. Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

    Science.gov (United States)

    Chen, Tianle; Zeng, Donglin

    2015-01-01

    Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

  2. Predicting sugar consumption: Application of an integrated dual-process, dual-phase model.

    Science.gov (United States)

    Hagger, Martin S; Trost, Nadine; Keech, Jacob J; Chan, Derwin K C; Hamilton, Kyra

    2017-09-01

    Excess consumption of added dietary sugars is related to multiple metabolic problems and adverse health conditions. Identifying the modifiable social cognitive and motivational constructs that predict sugar consumption is important to inform behavioral interventions aimed at reducing sugar intake. We tested the efficacy of an integrated dual-process, dual-phase model derived from multiple theories to predict sugar consumption. Using a prospective design, university students (N = 90) completed initial measures of the reflective (autonomous and controlled motivation, intentions, attitudes, subjective norm, perceived behavioral control), impulsive (implicit attitudes), volitional (action and coping planning), and behavioral (past sugar consumption) components of the proposed model. Self-reported sugar consumption was measured two weeks later. A structural equation model revealed that intentions, implicit attitudes, and, indirectly, autonomous motivation to reduce sugar consumption had small, significant effects on sugar consumption. Attitudes, subjective norm, and, indirectly, autonomous motivation to reduce sugar consumption predicted intentions. There were no effects of the planning constructs. Model effects were independent of the effects of past sugar consumption. The model identified the relative contribution of reflective and impulsive components in predicting sugar consumption. Given the prominent role of the impulsive component, interventions that assist individuals in managing cues-to-action and behavioral monitoring are likely to be effective in regulating sugar consumption. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. An Integrated Model to Predict Corporate Failure of Listed Companies in Sri Lanka

    Directory of Open Access Journals (Sweden)

    Nisansala Wijekoon

    2015-07-01

    Full Text Available The primary objective of this study is to develop an integrated model to predict corporate failure of listed companies in Sri Lanka. The logistic regression analysis was employed to a data set of 70 matched-pairs of failed and non-failed companies listed in the Colombo Stock Exchange (CSE in Sri Lanka over the period 2002 to 2010. A total of fifteen financial ratios and eight corporate governance variables were used as predictor variables of corporate failure. Analysis of the statistical testing results indicated that model consists with both corporate governance variables and financial ratios improved the prediction accuracy to reach 88.57 per cent one year prior to failure. Furthermore, predictive accuracy of this model in all three years prior to failure is above 80 per cent. Hence model is robust in obtaining accurate results for up to three years prior to failure. It was further found that two financial ratios, working capital to total assets and cash flow from operating activities to total assets, and two corporate governance variables, outside director ratio and company audit committee are having more explanatory power to predict corporate failure. Therefore, model developed in this study can assist investors, managers, shareholders, financial institutions, auditors and regulatory agents in Sri Lanka to forecast corporate failure of listed companies.

  4. [Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

    Science.gov (United States)

    Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

    2012-02-01

    In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

  5. Integrated prediction based on GIS for sandstone-type uranium deposits in the northwest of Ordos Basin

    International Nuclear Information System (INIS)

    Han Shaoyang; Ke Dan; Hu Shuiqing; Guo Qingyin; Hou Huiqun

    2005-01-01

    The integrated prediction model of sandstone-type uranium deposits and its integrated evaluation methods as well as flow of the work based on GIS are studied. A software for extracting metallogenic information is also developed. A multi-source exploring information database is established in the northwest of Ordos Basin, and an integrated digital mineral deposit prospecting model of sandstone-type uranium deposits is designed based on GIS. The authors have completed metallogenic information extraction and integrated evaluation of sandstone-type uranium deposits based on GIS in the study area. Research results prove that the integrated prediction of sandstone-type uranium deposits based on GIS may further delineate prospective target areas rapidly and improve the predictive precision. (authors)

  6. A COMPUTER BASED MAINTENANCE MANAGEMENT SYSTEM ...

    African Journals Online (AJOL)

    ... programs to schedule for maintenance or replacement of machines has been designed such that it enables the maintenance department control all jobs associated with plant maintenance and breakdown. It predicts the time to failure of designated plants and caters for the replacement analysis of some capital equipment.

  7. Thought insertion as a self-disturbance: An integration of predictive coding and phenomenological approaches

    Directory of Open Access Journals (Sweden)

    Philipp Sterzer

    2016-10-01

    Full Text Available Current theories in the framework of hierarchical predictive coding propose that positive symptoms of schizophrenia, such as delusions and hallucinations, arise from an alteration in Bayesian inference, the term inference referring to a process by which learned predictions are used to infer probable causes of sensory data. However, for one particularly striking and frequent symptom of schizophrenia, thought insertion, no plausible account has been proposed in terms of the predictive-coding framework. Here we propose that thought insertion is due to an altered experience of thoughts as coming from nowhere, as is already indicated by the early 20th century phenomenological accounts by the early Heidelberg School of psychiatry. These accounts identified thought insertion as one of the self-disturbances (from German: Ichstörungen of schizophrenia and used mescaline as a model-psychosis in healthy individuals to explore the possible mechanisms. The early Heidelberg School (Gruhle, Mayer-Gross, Beringer first named and defined the self-disturbances, and proposed that thought insertion involves a disruption of the inner connectedness of thoughts and experiences, and a becoming sensory of those thoughts experienced as inserted. This account offers a novel way to integrate the phenomenology of thought insertion with the predictive coding framework. We argue that the altered experience of thoughts may be caused by a reduced precision of context-dependent predictions, relative to sensory precision. According to the principles of Bayesian inference, this reduced precision leads to increased prediction-error signals evoked by the neural activity that encodes thoughts. Thus, in analogy with the prediction-error related aberrant salience of external events that has been proposed previously, internal events such as thoughts (including volitions, emotions and memories can also be associated with increased prediction-error signaling and are thus imbued with

  8. Integrating sequence stratigraphy and rock-physics to interpret seismic amplitudes and predict reservoir quality

    Science.gov (United States)

    Dutta, Tanima

    This dissertation focuses on the link between seismic amplitudes and reservoir properties. Prediction of reservoir properties, such as sorting, sand/shale ratio, and cement-volume from seismic amplitudes improves by integrating knowledge from multiple disciplines. The key contribution of this dissertation is to improve the prediction of reservoir properties by integrating sequence stratigraphy and rock physics. Sequence stratigraphy has been successfully used for qualitative interpretation of seismic amplitudes to predict reservoir properties. Rock physics modeling allows quantitative interpretation of seismic amplitudes. However, often there is uncertainty about selecting geologically appropriate rock physics model and its input parameters, away from the wells. In the present dissertation, we exploit the predictive power of sequence stratigraphy to extract the spatial trends of sedimentological parameters that control seismic amplitudes. These spatial trends of sedimentological parameters can serve as valuable constraints in rock physics modeling, especially away from the wells. Consequently, rock physics modeling, integrated with the trends from sequence stratigraphy, become useful for interpreting observed seismic amplitudes away from the wells in terms of underlying sedimentological parameters. We illustrate this methodology using a comprehensive dataset from channelized turbidite systems, deposited in minibasin settings in the offshore Equatorial Guinea, West Africa. First, we present a practical recipe for using closed-form expressions of effective medium models to predict seismic velocities in unconsolidated sandstones. We use an effective medium model that combines perfectly rough and smooth grains (the extended Walton model), and use that model to derive coordination number, porosity, and pressure relations for P and S wave velocities from experimental data. Our recipe provides reasonable fits to other experimental and borehole data, and specifically

  9. Global identification predicts gay-male identity integration and well-being among Turkish gay men.

    Science.gov (United States)

    Koc, Yasin; Vignoles, Vivian L

    2016-12-01

    In most parts of the world, hegemonic masculinity requires men to endorse traditional masculine ideals, one of which is rejection of homosexuality. Wherever hegemonic masculinity favours heterosexuality over homosexuality, gay males may feel under pressure to negotiate their conflicting male gender and gay sexual identities to maintain positive self-perceptions. However, globalization, as a source of intercultural interaction, might provide a beneficial context for people wishing to create alternative masculinities in the face of hegemonic masculinity. Hence, we tested if global identification would predict higher levels of gay-male identity integration, and indirectly subjective well-being, via alternative masculinity representations for gay and male identities. A community sample of 219 gay and bisexual men from Turkey completed the study. Structural equation modelling revealed that global identification positively predicted gay-male identity integration, and indirectly subjective well-being; however, alternative masculinity representations did not mediate this relationship. Our findings illustrate how identity categories in different domains can intersect and affect each other in complex ways. Moreover, we discuss mental health and well-being implications for gay men living in cultures where they experience high levels of prejudice and stigma. © 2016 The British Psychological Society.

  10. Guidelineness of the parameters using integrated test in down syndrome risk prediction

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jin Won [Graduate School of Catholic University of Pusan, Busan (Korea, Republic of); Go, Sung Jin; Kang, Se Sik; Kim, Chang Soo [Dept. Radiological Science, College of Health Sciences, Catholic University of Pusan, Busan (Korea, Republic of)

    2016-12-15

    This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening.

  11. Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks.

    Science.gov (United States)

    Haibe-Kains, Benjamin; Olsen, Catharina; Djebbari, Amira; Bontempi, Gianluca; Correll, Mick; Bouton, Christopher; Quackenbush, John

    2012-01-01

    Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these 'known' interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/.

  12. Guidelineness of the parameters using integrated test in down syndrome risk prediction

    International Nuclear Information System (INIS)

    Lee, Jin Won; Go, Sung Jin; Kang, Se Sik; Kim, Chang Soo

    2016-01-01

    This study was an evaluation of the significance of each parameter through aimed at pregnant women subjected to screening test(integrated test) in predicting risk of Down syndrome. We retrospectively analysed the correlation of risk of Down's syndrome with Nuchal Translucency(NT) images measured by ultrasound, Pregnancy Associated Plasma Protein A(PAPP-A), alpha-fetoprotein(AFP), unconjugated estriol(uE3), human chorionic gonadotrophin(hCG) and Inhibin A by maternal serum. As a result, a significant correlation with NT, uE3, hCG, Inhibin A is revealed with Down's syndrome risk(P<.001). In ROC analysis, AUC of Inhibin A is analysed as the biggest predictor of Down's syndrome(0.859). And the criterion for cut-off was inhibin A 1.4 MoM(sensitivity 81.8%, specificity 75.9%). In conclusion, Inhibin A was the most useful in parameters to predict Down's syndrome in the integrated test. If we make up for the weakness based on the cut-off value of parameters they will be able to be used as an independent indicator in the risk of Down's syndrome screening

  13. An integrated Modelling framework to monitor and predict trends of agricultural management (iMSoil)

    Science.gov (United States)

    Keller, Armin; Della Peruta, Raneiro; Schaepman, Michael; Gomez, Marta; Mann, Stefan; Schulin, Rainer

    2014-05-01

    Agricultural systems lay at the interface between natural ecosystems and the anthroposphere. Various drivers induce pressures on the agricultural systems, leading to changes in farming practice. The limitation of available land and the socio-economic drivers are likely to result in further intensification of agricultural land management, with implications on fertilization practices, soil and pest management, as well as crop and livestock production. In order to steer the development into desired directions, tools are required by which the effects of these pressures on agricultural management and resulting impacts on soil functioning can be detected as early as possible, future scenarios predicted and suitable management options and policies defined. In this context, the use of integrated models can play a major role in providing long-term predictions of soil quality and assessing the sustainability of agricultural soil management. Significant progress has been made in this field over the last decades. Some of these integrated modelling frameworks include biophysical parameters, but often the inherent characteristics and detailed processes of the soil system have been very simplified. The development of such tools has been hampered in the past by a lack of spatially explicit soil and land management information at regional scale. The iMSoil project, funded by the Swiss National Science Foundation in the national research programme NRP68 "soil as a resource" (www.nrp68.ch) aims at developing and implementing an integrated modeling framework (IMF) which can overcome the limitations mentioned above, by combining socio-economic, agricultural land management, and biophysical models, in order to predict the long-term impacts of different socio-economic scenarios on the soil quality. In our presentation we briefly outline the approach that is based on an interdisciplinary modular framework that builds on already existing monitoring tools and model components that are

  14. Nuclear maintenance and management system

    International Nuclear Information System (INIS)

    Yamaji, Yoshihiro; Abe, Norihiko

    2000-01-01

    The Mitsubishi Electric Co., Ltd. has developed to introduce various computer systems for desk-top business assistance in a power plant such as system isolation assisting system, operation parameter management system, and so on under aiming at business effectiveness since these ten and some years. Recently, by further elapsed years of the plants when required for further cost reduction and together with change of business environment represented by preparation of individual personal computer, further effectiveness, preparation of the business environment, and upgrading of maintenance in power plant business have been required. Among such background, she has carried out various proposals and developments on construction of a maintenance and management system integrated the business assistant know-hows and the plant know-hows both accumulated previously. They are composed of three main points on rationalization of business management and document management in the further effectiveness, preparation of business environment, TBM maintenance, introduction of CBM maintenance and introduction of maintenance assistance in upgrading of maintenance. Here was introduced on system concepts aiming at the further effectiveness of the nuclear power plant business, preparation of business environment, upgrading of maintenance and maintenance, and so on, at a background of environment around maintenance business in the nuclear power plants (cost-down, highly elapsed year of the plant, change of business environment). (G.K)

  15. A vision for an ultra-high resolution integrated water cycle observation and prediction system

    Science.gov (United States)

    Houser, P. R.

    2013-05-01

    Society's welfare, progress, and sustainable economic growth—and life itself—depend on the abundance and vigorous cycling and replenishing of water throughout the global environment. The water cycle operates on a continuum of time and space scales and exchanges large amounts of energy as water undergoes phase changes and is moved from one part of the Earth system to another. We must move toward an integrated observation and prediction paradigm that addresses broad local-to-global science and application issues by realizing synergies associated with multiple, coordinated observations and prediction systems. A central challenge of a future water and energy cycle observation strategy is to progress from single variable water-cycle instruments to multivariable integrated instruments in electromagnetic-band families. The microwave range in the electromagnetic spectrum is ideally suited for sensing the state and abundance of water because of water's dielectric properties. Eventually, a dedicated high-resolution water-cycle microwave-based satellite mission may be possible based on large-aperture antenna technology that can harvest the synergy that would be afforded by simultaneous multichannel active and passive microwave measurements. A partial demonstration of these ideas can even be realized with existing microwave satellite observations to support advanced multivariate retrieval methods that can exploit the totality of the microwave spectral information. The simultaneous multichannel active and passive microwave retrieval would allow improved-accuracy retrievals that are not possible with isolated measurements. Furthermore, the simultaneous monitoring of several of the land, atmospheric, oceanic, and cryospheric states brings synergies that will substantially enhance understanding of the global water and energy cycle as a system. The multichannel approach also affords advantages to some constituent retrievals—for instance, simultaneous retrieval of vegetation

  16. Accurate diffraction data integration by the EVAL15 profile prediction method : Application in chemical and biological crystallography

    NARCIS (Netherlands)

    Xian, X.

    2009-01-01

    Accurate integration of reflection intensities plays an essential role in structure determination of the crystallized compound. A new diffraction data integration method, EVAL15, is presented in this thesis. This method uses the principle of general impacts to predict ab inito three-dimensional

  17. Observing others stay or switch - How social prediction errors are integrated into reward reversal learning.

    Science.gov (United States)

    Ihssen, Niklas; Mussweiler, Thomas; Linden, David E J

    2016-08-01

    Reward properties of stimuli can undergo sudden changes, and the detection of these 'reversals' is often made difficult by the probabilistic nature of rewards/punishments. Here we tested whether and how humans use social information (someone else's choices) to overcome uncertainty during reversal learning. We show a substantial social influence during reversal learning, which was modulated by the type of observed behavior. Participants frequently followed observed conservative choices (no switches after punishment) made by the (fictitious) other player but ignored impulsive choices (switches), even though the experiment was set up so that both types of response behavior would be similarly beneficial/detrimental (Study 1). Computational modeling showed that participants integrated the observed choices as a 'social prediction error' instead of ignoring or blindly following the other player. Modeling also confirmed higher learning rates for 'conservative' versus 'impulsive' social prediction errors. Importantly, this 'conservative bias' was boosted by interpersonal similarity, which in conjunction with the lack of effects observed in a non-social control experiment (Study 2) confirmed its social nature. A third study suggested that relative weighting of observed impulsive responses increased with increased volatility (frequency of reversals). Finally, simulations showed that in the present paradigm integrating social and reward information was not necessarily more adaptive to maximize earnings than learning from reward alone. Moreover, integrating social information increased accuracy only when conservative and impulsive choices were weighted similarly during learning. These findings suggest that to guide decisions in choice contexts that involve reward reversals humans utilize social cues conforming with their preconceptions more strongly than cues conflicting with them, especially when the other is similar. Copyright © 2016 The Authors. Published by Elsevier B

  18. An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

    Science.gov (United States)

    Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

    2016-01-01

    A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

  19. iSPUW: integrated sensing and prediction of urban water for sustainable cities

    Science.gov (United States)

    Noh, S. J.; Nazari, B.; Habibi, H.; Norouzi, A.; Nabatian, M.; Seo, D. J.; Bartos, M. D.; Kerkez, B.; Lakshman, L.; Zink, M.; Lee, J.

    2016-12-01

    Many cities face tremendous water-related challenges in this Century of the City. Urban areas are particularly susceptible not only to excesses and shortages of water but also to impaired water quality. To addresses these challenges, we synergistically integrate advances in computing and cyber-infrastructure, environmental modeling, geoscience, and information science to develop integrative solutions for urban water challenges. In this presentation, we describe the various efforts that are currently ongoing in the Dallas-Fort Worth Metroplex (DFW) area for iSPUW: real-time high-resolution flash flood forecasting, inundation mapping for large urban areas, crowdsourcing of water observations in urban areas, real-time assimilation of crowdsourced observations for street and river flooding, integrated control of lawn irrigation and rainwater harvesting for water conservation and stormwater management, feature mining with causal discovery for flood prediction, and development of the Arlington Urban Hydroinformatics Testbed. Analyzed is the initial data of sensor network for water level and lawn monitoring, and cellphone applications for crowdsourcing flood reports. New data assimilation approaches to deal with categorical and continuous observations are also evaluated via synthetic experiments.

  20. Integration of research infrastructures and ecosystem models toward development of predictive ecology

    Science.gov (United States)

    Luo, Y.; Huang, Y.; Jiang, J.; MA, S.; Saruta, V.; Liang, G.; Hanson, P. J.; Ricciuto, D. M.; Milcu, A.; Roy, J.

    2017-12-01

    The past two decades have witnessed rapid development in sensor technology. Built upon the sensor development, large research infrastructure facilities, such as National Ecological Observatory Network (NEON) and FLUXNET, have been established. Through networking different kinds of sensors and other data collections at many locations all over the world, those facilities generate large volumes of ecological data every day. The big data from those facilities offer an unprecedented opportunity for advancing our understanding of ecological processes, educating teachers and students, supporting decision-making, and testing ecological theory. The big data from the major research infrastructure facilities also provides foundation for developing predictive ecology. Indeed, the capability to predict future changes in our living environment and natural resources is critical to decision making in a world where the past is no longer a clear guide to the future. We are living in a period marked by rapid climate change, profound alteration of biogeochemical cycles, unsustainable depletion of natural resources, and deterioration of air and water quality. Projecting changes in future ecosystem services to the society becomes essential not only for science but also for policy making. We will use this panel format to outline major opportunities and challenges in integrating research infrastructure and ecosystem models toward developing predictive ecology. Meanwhile, we will also show results from an interactive model-experiment System - Ecological Platform for Assimilating Data into models (EcoPAD) - that have been implemented at the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in Northern Minnesota and Montpellier Ecotron, France. EcoPAD is developed by integrating web technology, eco-informatics, data assimilation techniques, and ecosystem modeling. EcoPAD is designed to streamline data transfer seamlessly from research infrastructure

  1. Revisiting EOR Projects in Indonesia through Integrated Study: EOR Screening, Predictive Model, and Optimisation

    KAUST Repository

    Hartono, A. D.; Hakiki, Farizal; Syihab, Z.; Ambia, F.; Yasutra, A.; Sutopo, S.; Efendi, M.; Sitompul, V.; Primasari, I.; Apriandi, R.

    2017-01-01

    EOR preliminary analysis is pivotal to be performed at early stage of assessment in order to elucidate EOR feasibility. This study proposes an in-depth analysis toolkit for EOR preliminary evaluation. The toolkit incorporates EOR screening, predictive, economic, risk analysis and optimisation modules. The screening module introduces algorithms which assimilates statistical and engineering notions into consideration. The United States Department of Energy (U.S. DOE) predictive models were implemented in the predictive module. The economic module is available to assess project attractiveness, while Monte Carlo Simulation is applied to quantify risk and uncertainty of the evaluated project. Optimization scenario of EOR practice can be evaluated using the optimisation module, in which stochastic methods of Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Evolutionary Strategy (ES) were applied in the algorithms. The modules were combined into an integrated package of EOR preliminary assessment. Finally, we utilised the toolkit to evaluate several Indonesian oil fields for EOR evaluation (past projects) and feasibility (future projects). The attempt was able to update the previous consideration regarding EOR attractiveness and open new opportunity for EOR implementation in Indonesia.

  2. Prediction of leisure-time walking: an integration of social cognitive, perceived environmental, and personality factors

    Directory of Open Access Journals (Sweden)

    Blanchard Chris M

    2007-10-01

    Full Text Available Abstract Background Walking is the primary focus of population-based physical activity initiatives but a theoretical understanding of this behaviour is still elusive. The purpose of this study was to integrate personality, the perceived environment, and planning into a theory of planned behaviour (TPB framework to predict leisure-time walking. Methods Participants were a random sample (N = 358 of Canadian adults who completed measures of the TPB, planning, perceived neighbourhood environment, and personality at Time 1 and self-reported walking behaviour two months later. Results Analyses using structural equation modelling provided evidence that leisure-time walking is largely predicted by intention (standardized effect = .42 with an additional independent contribution from proximity to neighbourhood retail shops (standardized effect = .18. Intention, in turn, was predicted by attitudes toward walking and perceived behavioural control. Effects of perceived neighbourhood aesthetics and walking infrastructure on walking were mediated through attitudes and intention. Moderated regression analysis showed that the intention-walking relationship was moderated by conscientiousness and proximity to neighbourhood recreation facilities but not planning. Conclusion Overall, walking behaviour is theoretically complex but may best be addressed at a population level by facilitating strong intentions in a receptive environment even though individual differences may persist.

  3. An integrated computational validation approach for potential novel miRNA prediction

    Directory of Open Access Journals (Sweden)

    Pooja Viswam

    2017-12-01

    Full Text Available MicroRNAs (miRNAs are short, non-coding RNAs between 17bp-24bp length that regulate gene expression by targeting mRNA molecules. The regulatory functions of miRNAs are known to be majorly associated with disease phenotypes such as cancer, cell signaling, cell division, growth and other metabolisms. Novel miRNAs are defined as sequences which does not have any similarity with the existing known sequences and void of any experimental evidences. In recent decades, the advent of next-generation sequencing allows us to capture the small RNA molecules form the cells and developing methods to estimate their expression levels. Several computational algorithms are available to predict the novel miRNAs from the deep sequencing data. In this work, we integrated three novel miRNA prediction programs miRDeep, miRanalyzer and miRPRo to compare and validate their prediction efficiency. The dicer cleavage sites, alignment density, seed conservation, minimum free energy, AU-GC percentage, secondary loop scores, false discovery rates and confidence scores will be considered for comparison and evaluation. Efficiency to identify isomiRs and base pair mismatches in a strand specific manner will also be considered for the computational validation. Further, the criteria and parameters for the identification of the best possible novel miRNA with minimal false positive rates were deduced.

  4. Performance prediction for silicon photonics integrated circuits with layout-dependent correlated manufacturing variability.

    Science.gov (United States)

    Lu, Zeqin; Jhoja, Jaspreet; Klein, Jackson; Wang, Xu; Liu, Amy; Flueckiger, Jonas; Pond, James; Chrostowski, Lukas

    2017-05-01

    This work develops an enhanced Monte Carlo (MC) simulation methodology to predict the impacts of layout-dependent correlated manufacturing variations on the performance of photonics integrated circuits (PICs). First, to enable such performance prediction, we demonstrate a simple method with sub-nanometer accuracy to characterize photonics manufacturing variations, where the width and height for a fabricated waveguide can be extracted from the spectral response of a racetrack resonator. By measuring the spectral responses for a large number of identical resonators spread over a wafer, statistical results for the variations of waveguide width and height can be obtained. Second, we develop models for the layout-dependent enhanced MC simulation. Our models use netlist extraction to transfer physical layouts into circuit simulators. Spatially correlated physical variations across the PICs are simulated on a discrete grid and are mapped to each circuit component, so that the performance for each component can be updated according to its obtained variations, and therefore, circuit simulations take the correlated variations between components into account. The simulation flow and theoretical models for our layout-dependent enhanced MC simulation are detailed in this paper. As examples, several ring-resonator filter circuits are studied using the developed enhanced MC simulation, and statistical results from the simulations can predict both common-mode and differential-mode variations of the circuit performance.

  5. Revisiting EOR Projects in Indonesia through Integrated Study: EOR Screening, Predictive Model, and Optimisation

    KAUST Repository

    Hartono, A. D.

    2017-10-17

    EOR preliminary analysis is pivotal to be performed at early stage of assessment in order to elucidate EOR feasibility. This study proposes an in-depth analysis toolkit for EOR preliminary evaluation. The toolkit incorporates EOR screening, predictive, economic, risk analysis and optimisation modules. The screening module introduces algorithms which assimilates statistical and engineering notions into consideration. The United States Department of Energy (U.S. DOE) predictive models were implemented in the predictive module. The economic module is available to assess project attractiveness, while Monte Carlo Simulation is applied to quantify risk and uncertainty of the evaluated project. Optimization scenario of EOR practice can be evaluated using the optimisation module, in which stochastic methods of Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Evolutionary Strategy (ES) were applied in the algorithms. The modules were combined into an integrated package of EOR preliminary assessment. Finally, we utilised the toolkit to evaluate several Indonesian oil fields for EOR evaluation (past projects) and feasibility (future projects). The attempt was able to update the previous consideration regarding EOR attractiveness and open new opportunity for EOR implementation in Indonesia.

  6. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

  7. A mitogen-activated protein kinase Tmk3 participates in high osmolarity resistance, cell wall integrity maintenance and cellulase production regulation in Trichoderma reesei.

    Directory of Open Access Journals (Sweden)

    Mingyu Wang

    Full Text Available The mitogen-activated protein kinase (MAPK pathways are important signal transduction pathways conserved in essentially all eukaryotes, but haven't been subjected to functional studies in the most important cellulase-producing filamentous fungus Trichoderma reesei. Previous reports suggested the presence of three MAPKs in T. reesei: Tmk1, Tmk2, and Tmk3. By exploring the phenotypic features of T. reesei Δtmk3, we first showed elevated NaCl sensitivity and repressed transcription of genes involved in glycerol/trehalose biosynthesis under higher osmolarity, suggesting Tmk3 participates in high osmolarity resistance via derepression of genes involved in osmotic stabilizer biosynthesis. We also showed significant downregulation of genes encoding chitin synthases and a β-1,3-glucan synthase, decreased chitin content, 'budded' hyphal appearance typical to cell wall defective strains, and increased sensitivity to calcofluor white/Congo red in the tmk3 deficient strain, suggesting Tmk3 is involved in cell wall integrity maintenance in T. reesei. We further observed the decrease of cellulase transcription and production in T. reesei Δtmk3 during submerged cultivation, as well as the presence of MAPK phosphorylation sites on known transcription factors involved in cellulase regulation, suggesting Tmk3 is also involved in the regulation of cellulase production. Finally, the expression of cell wall integrity related genes, the expression of cellulase coding genes, cellulase production and biomass accumulation were compared between T. reesei Δtmk3 grown in solid state media and submerged media, showing a strong restoration effect in solid state media from defects resulted from tmk3 deletion. These results showed novel physiological processes that fungal Hog1-type MAPKs are involved in, and present the first experimental investigation of MAPK signaling pathways in T. reesei. Our observations on the restoration effect during solid state cultivation suggest

  8. A Mitogen-Activated Protein Kinase Tmk3 Participates in High Osmolarity Resistance, Cell Wall Integrity Maintenance and Cellulase Production Regulation in Trichoderma reesei

    Science.gov (United States)

    Wang, Mingyu; Zhao, Qiushuang; Yang, Jinghua; Jiang, Baojie; Wang, Fangzhong; Liu, Kuimei; Fang, Xu

    2013-01-01

    The mitogen-activated protein kinase (MAPK) pathways are important signal transduction pathways conserved in essentially all eukaryotes, but haven't been subjected to functional studies in the most important cellulase-producing filamentous fungus Trichoderma reesei. Previous reports suggested the presence of three MAPKs in T. reesei: Tmk1, Tmk2, and Tmk3. By exploring the phenotypic features of T. reesei Δtmk3, we first showed elevated NaCl sensitivity and repressed transcription of genes involved in glycerol/trehalose biosynthesis under higher osmolarity, suggesting Tmk3 participates in high osmolarity resistance via derepression of genes involved in osmotic stabilizer biosynthesis. We also showed significant downregulation of genes encoding chitin synthases and a β-1,3-glucan synthase, decreased chitin content, ‘budded’ hyphal appearance typical to cell wall defective strains, and increased sensitivity to calcofluor white/Congo red in the tmk3 deficient strain, suggesting Tmk3 is involved in cell wall integrity maintenance in T. reesei. We further observed the decrease of cellulase transcription and production in T. reesei Δtmk3 during submerged cultivation, as well as the presence of MAPK phosphorylation sites on known transcription factors involved in cellulase regulation, suggesting Tmk3 is also involved in the regulation of cellulase production. Finally, the expression of cell wall integrity related genes, the expression of cellulase coding genes, cellulase production and biomass accumulation were compared between T. reesei Δtmk3 grown in solid state media and submerged media, showing a strong restoration effect in solid state media from defects resulted from tmk3 deletion. These results showed novel physiological processes that fungal Hog1-type MAPKs are involved in, and present the first experimental investigation of MAPK signaling pathways in T. reesei. Our observations on the restoration effect during solid state cultivation suggest that T. reesei

  9. Integrated genetic and epigenetic prediction of coronary heart disease in the Framingham Heart Study.

    Directory of Open Access Journals (Sweden)

    Meeshanthini V Dogan

    Full Text Available An improved method for detecting coronary heart disease (CHD could have substantial clinical impact. Building on the idea that systemic effects of CHD risk factors are a conglomeration of genetic and environmental factors, we use machine learning techniques and integrate genetic, epigenetic and phenotype data from the Framingham Heart Study to build and test a Random Forest classification model for symptomatic CHD. Our classifier was trained on n = 1,545 individuals and consisted of four DNA methylation sites, two SNPs, age and gender. The methylation sites and SNPs were selected during the training phase. The final trained model was then tested on n = 142 individuals. The test data comprised of individuals removed based on relatedness to those in the training dataset. This integrated classifier was capable of classifying symptomatic CHD status of those in the test set with an accuracy, sensitivity and specificity of 78%, 0.75 and 0.80, respectively. In contrast, a model using only conventional CHD risk factors as predictors had an accuracy and sensitivity of only 65% and 0.42, respectively, but with a specificity of 0.89 in the test set. Regression analyses of the methylation signatures illustrate our ability to map these signatures to known risk factors in CHD pathogenesis. These results demonstrate the capability of an integrated approach to effectively model symptomatic CHD status. These results also suggest that future studies of biomaterial collected from longitudinally informative cohorts that are specifically characterized for cardiac disease at follow-up could lead to the introduction of sensitive, readily employable integrated genetic-epigenetic algorithms for predicting onset of future symptomatic CHD.

  10. Network maintenance

    CERN Multimedia

    GS Department

    2009-01-01

    A site-wide network maintenance operation has been scheduled for Saturday 28 February. Most of the network devices of the general purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites throughout the day. This upgrade will not affect the Computer Centre itself, Building 613, the Technical Network and the LHC experiments, dedicated networks at the pits. For further details of this intervention, please contact Netops by phone 74927 or e-mail mailto:Netops@cern.ch. IT/CS Group

  11. Network maintenance

    CERN Multimedia

    IT Department

    2009-01-01

    A site wide network maintenance has been scheduled for Saturday 28 February. Most of the network devices of the General Purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites along this day. This upgrade will not affect: the Computer centre itself, building 613, the Technical Network and the LHC experiments dedicated networks at the pits. Should you need more details on this intervention, please contact Netops by phone 74927 or email mailto:Netops@cern.ch. IT/CS Group

  12. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

    Science.gov (United States)

    Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei

    2017-12-21

    In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.

  13. Rigorous assessment and integration of the sequence and structure based features to predict hot spots

    Directory of Open Access Journals (Sweden)

    Wang Yong

    2011-07-01

    classifiers are quite effective in predicting hot spots based on sequence features. Hot spots cannot be fully predicted through simple analysis based on physicochemical characteristics, but there is reason to believe that integration of features and machine learning methods can remarkably improve the predictive performance for hot spots.

  14. Prediction of the flooding process at the Ronneburg site - results of an integrated approach

    International Nuclear Information System (INIS)

    Paul, M.; Saenger, H.-J.; Snagowski, S.; Maerten, H.; Eckart, M.

    1998-01-01

    The flooding process of the Ronneburg uranium mine (WISMUT) was initiated at the turn of the year 1997 to 1998. In order to prepare the flooding process and to derive and optimize technological measures an integrated modelling approach was chosen which includes several coupled modules. The most important issues to be answered are: (1) prediction of the flooding time (2) prediction of the groundwater level at the post-flooding stage, assessment of amount, location and quality of flooding waters entering the receiving streams at the final stage (3) water quality prediction within the mine during the flooding process (4) definition of technological measures and assessment of their efficiency A box model which includes the three-dimensional distribution of the cavity volume in the mine represents the model core. The model considers the various types of dewatered cavity volumes for each mine level / mining field and the degree of vertical and horizontal connection between the mining fields. Different types of open mine space as well as the dewatered geological pore and joint volume are considered taking into account the contour of the depression cone prior to flooding and the characteristics of the different rock types. Based on the mine water balance and the flooding technology the model predicts the rise of the water table over time during the flooding process for each mine field separately. In order to predict the mine water quality and the efficiency of in-situ water treatment the box model was linked to a geochemical model (PHREEQC). A three-dimensional flow model is used to evaluate the post-flooding situation at the Ronneburg site. This model is coupled to the box model. The modelling results of various flooding scenarios show that a prediction of the post-flooding geohydraulic situation is possible despite of uncertainties concerning the input parameters which still exist. The post-flooding water table in the central part of the Ronneburg mine will be 270 m

  15. Rigorous assessment and integration of the sequence and structure based features to predict hot spots

    Science.gov (United States)

    2011-01-01

    effective in predicting hot spots based on sequence features. Hot spots cannot be fully predicted through simple analysis based on physicochemical characteristics, but there is reason to believe that integration of features and machine learning methods can remarkably improve the predictive performance for hot spots. PMID:21798070

  16. North American nuclear maintenance best practices compared to Japanese utility maintenance practices

    International Nuclear Information System (INIS)

    Harazim, M.L.; Ferguson, B.J.

    2003-01-01

    The purpose of this paper is to compare the best practices in North America concerning Preventive Maintenance, Predictive Maintenance and Reliability Centered Maintenance (RCM) or Preventive Maintenance Optimization (PMO) with the time-directed maintenance philosophies utilized by Japanese utilities, and how the Japanese utilities are considering (and some have begun) adopting North American ways of doing business. Preventive Maintenance Living Programs are also discussed, along with the Institute of Nuclear Power Operations AP-913 process, Equipment Reliability Process. Also, a cost benefit analysis will be demonstrated showing how major cost savings can be achieved by shifting from a predominantly time-directed maintenance philosophy to a predominantly predictive strategy utilizing vibration analysis, lubricating oil analysis, thermography and other predictive technologies to better utilize resources, reduce spare part consumption and to minimize maintenance induced errors. As a result of the strides made while incorporating these new philosophies, we no longer advocate tearing apart perfectly good equipment. (author)

  17. The degree of myelosuppression during maintenance therapy of adolescents with B-lineage intermediate risk acute lymphoblastic leukemia predicts risk of relapse

    DEFF Research Database (Denmark)

    Schmiegelow, K; Donovan, Martin Heyman; Sherson, Maiken Gustafsson

    2010-01-01

    Drug doses, blood levels of drug metabolites and myelotoxicity during 6-mercaptopurine/methotrexate (MTX) maintenance therapy were registered for 59 adolescents (10 years) and 176 non-adolescents (leukemia (ALL) and a white blood cell count (WBC......) diagnosis. Event-free survival was lower for adolescents than non-adolescents (pEFS12y:0.71 vs 0.83, P=0.04). For adolescents staying in remission, the mean WBC during maintenance therapy (mWBC) was related to age (rS=0.36, P=0.02), which became nonsignificant for those who relapsed (r...

  18. Medium term municipal solid waste generation prediction by autoregressive integrated moving average

    International Nuclear Information System (INIS)

    Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

    2014-01-01

    Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval

  19. Behaviors of impurity in ITER and DEMOs using BALDUR integrated predictive modeling code

    International Nuclear Information System (INIS)

    Onjun, Thawatchai; Buangam, Wannapa; Wisitsorasak, Apiwat

    2015-01-01

    The behaviors of impurity are investigated using self-consistent modeling of 1.5D BALDUR integrated predictive modeling code, in which theory-based models are used for both core and edge region. In these simulations, a combination of NCLASS neoclassical transport and Multi-mode (MMM95) anomalous transport model is used to compute a core transport. The boundary is taken to be at the top of the pedestal, where the pedestal values are described using a theory-based pedestal model. This pedestal temperature model is based on a combination of magnetic and flow shear stabilization pedestal width scaling and an infinite-n ballooning pressure gradient model. The time evolution of plasma current, temperature and density profiles is carried out for ITER and DEMOs plasmas. As a result, the impurity behaviors such as impurity accumulation and impurity transport can be investigated. (author)

  20. A model of integration among prediction tools: applied study to road freight transportation

    Directory of Open Access Journals (Sweden)

    Henrique Dias Blois

    Full Text Available Abstract This study has developed a scenery analysis model which has integrated decision-making tools on investments: prospective scenarios (Grumbach Method and systems dynamics (hard modeling, with the innovated multivariate analysis of experts. It was designed through analysis and simulation scenarios and showed which are the most striking events in the study object as well as highlighted the actions could redirect the future of the analyzed system. Moreover, predictions are likely to be developed through the generated scenarios. The model has been validated empirically with road freight transport data from state of Rio Grande do Sul, Brazil. The results showed that the model contributes to the analysis of investment because it identifies probabilities of events that impact on decision making, and identifies priorities for action, reducing uncertainties in the future. Moreover, it allows an interdisciplinary discussion that correlates different areas of knowledge, fundamental when you wish more consistency in creating scenarios.

  1. Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

    Science.gov (United States)

    Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

    2017-01-01

    Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

  2. Medium term municipal solid waste generation prediction by autoregressive integrated moving average

    Science.gov (United States)

    Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan

    2014-09-01

    Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

  3. An integrated numerical model for the prediction of Gaussian and billet shapes

    International Nuclear Information System (INIS)

    Hattel, J.H.; Pryds, N.H.; Pedersen, T.B.

    2004-01-01

    Separate models for the atomisation and the deposition stages were recently integrated by the authors to form a unified model describing the entire spray-forming process. In the present paper, the focus is on describing the shape of the deposited material during the spray-forming process, obtained by this model. After a short review of the models and their coupling, the important factors which influence the resulting shape, i.e. Gaussian or billet, are addressed. The key parameters, which are utilized to predict the geometry and dimension of the deposited material, are the sticking efficiency and the shading effect for Gaussian and billet shape, respectively. From the obtained results, the effect of these parameters on the final shape is illustrated

  4. Model predictive control system and method for integrated gasification combined cycle power generation

    Science.gov (United States)

    Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

    2013-04-09

    Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

  5. Medium term municipal solid waste generation prediction by autoregressive integrated moving average

    Energy Technology Data Exchange (ETDEWEB)

    Younes, Mohammad K.; Nopiah, Z. M.; Basri, Noor Ezlin A.; Basri, Hassan [Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor (Malaysia)

    2014-09-12

    Generally, solid waste handling and management are performed by municipality or local authority. In most of developing countries, local authorities suffer from serious solid waste management (SWM) problems and insufficient data and strategic planning. Thus it is important to develop robust solid waste generation forecasting model. It helps to proper manage the generated solid waste and to develop future plan based on relatively accurate figures. In Malaysia, solid waste generation rate increases rapidly due to the population growth and new consumption trends that characterize the modern life style. This paper aims to develop monthly solid waste forecasting model using Autoregressive Integrated Moving Average (ARIMA), such model is applicable even though there is lack of data and will help the municipality properly establish the annual service plan. The results show that ARIMA (6,1,0) model predicts monthly municipal solid waste generation with root mean square error equals to 0.0952 and the model forecast residuals are within accepted 95% confident interval.

  6. Integrating the ICF with positive psychology: Factors predicting role participation for mothers with multiple sclerosis.

    Science.gov (United States)

    Farber, Ruth S; Kern, Margaret L; Brusilovsky, Eugene

    2015-05-01

    Being a mother has become a realizable life role for women with disabilities and chronic illnesses, including multiple sclerosis (MS). Identifying psychosocial factors that facilitate participation in important life roles-including motherhood-is essential to help women have fuller lives despite the challenge of their illness. By integrating the International Classification of Functioning, Disability, and Health (ICF) and a positive psychology perspective, this study examined how environmental social factors and positive personal factors contribute to daily role participation and satisfaction with parental participation. One hundred and 11 community-dwelling mothers with MS completed Ryff's Psychological Well-Being Scales, the Medical Outcome Study Social Support Survey, the Short Form-36, and the Parental Participation Scale. Hierarchical regression analyses examined associations between social support and positive personal factors (environmental mastery, self-acceptance, purpose in life) with daily role participation (physical and emotional) and satisfaction with parental participation. One-way ANOVAs tested synergistic combinations of social support and positive personal factors. Social support predicted daily role participation (fewer limitations) and greater satisfaction with parental participation. Positive personal factors contributed additional unique variance. Positive personal factors and social support synergistically predicted better function and greater satisfaction than either alone. Integrating components of the ICF and positive psychology provides a useful model for understanding how mothers with MS can thrive despite challenge or impairment. Both positive personal factors and environmental social factors were important contributors to positive role functioning. Incorporating these paradigms into treatment may help mothers with MS participate more fully in meaningful life roles. (c) 2015 APA, all rights reserved).

  7. Reward and Cognition: Integrating Reinforcement Sensitivity Theory and Social Cognitive Theory to Predict Drinking Behavior.

    Science.gov (United States)

    Hasking, Penelope; Boyes, Mark; Mullan, Barbara

    2015-01-01

    Both Reinforcement Sensitivity Theory and Social Cognitive Theory have been applied to understanding drinking behavior. We propose that theoretical relationships between these models support an integrated approach to understanding alcohol use and misuse. We aimed to test an integrated model in which the relationships between reward sensitivity and drinking behavior (alcohol consumption, alcohol-related problems, and symptoms of dependence) were mediated by alcohol expectancies and drinking refusal self-efficacy. Online questionnaires assessing the constructs of interest were completed by 443 Australian adults (M age = 26.40, sd = 1.83) in 2013 and 2014. Path analysis revealed both direct and indirect effects and implicated two pathways to drinking behavior with differential outcomes. Drinking refusal self-efficacy both in social situations and for emotional relief was related to alcohol consumption. Sensitivity to reward was associated with alcohol-related problems, but operated through expectations of increased confidence and personal belief in the ability to limit drinking in social situations. Conversely, sensitivity to punishment operated through negative expectancies and drinking refusal self-efficacy for emotional relief to predict symptoms of dependence. Two pathways relating reward sensitivity, alcohol expectancies, and drinking refusal self-efficacy may underlie social and dependent drinking, which has implications for development of intervention to limit harmful drinking.

  8. An integrative typology of personality assessment for aggression: implications for predicting counterproductive workplace behavior.

    Science.gov (United States)

    Bing, Mark N; Stewart, Susan M; Davison, H Kristl; Green, Philip D; McIntyre, Michael D; James, Lawrence R

    2007-05-01

    This study presents an integrative typology of personality assessment for aggression. In this typology, self-report and conditional reasoning (L. R. James, 1998) methodologies are used to assess 2 separate, yet often congruent, components of aggressive personalities. Specifically, self-report is used to assess explicit components of aggressive tendencies, such as self-perceived aggression, whereas conditional reasoning is used to assess implicit components, in particular, the unconscious biases in reasoning that are used to justify aggressive acts. These 2 separate components are then integrated to form a new theoretical typology of personality assessment for aggression. Empirical tests of the typology were subsequently conducted using data gathered across 3 samples in laboratory and field settings and reveal that explicit and implicit components of aggression can interact in the prediction of counterproductive, deviant, and prosocial behaviors. These empirical tests also reveal that when either the self-report or conditional reasoning methodology is used in isolation, the resulting assessment of aggression may be incomplete. Implications for personnel selection, team composition, and executive coaching are discussed. 2007 APA, all rights reserved

  9. Integrated predictive modeling simulations of the Mega-Amp Spherical Tokamak

    International Nuclear Information System (INIS)

    Nguyen, Canh N.; Bateman, Glenn; Kritz, Arnold H.; Akers, Robert; Byrom, Calum; Sykes, Alan

    2002-01-01

    Integrated predictive modeling simulations are carried out using the BALDUR transport code [Singer et al., Comput. Phys. Commun. 49, 275 (1982)] for high confinement mode (H-mode) and low confinement mode (L-mode) discharges in the Mega-Amp Spherical Tokamak (MAST) [Sykes et al., Phys. Plasmas 8, 2101 (2001)]. Simulation results, obtained using either the Multi-Mode transport model (MMM95) or, alternatively, the mixed-Bohm/gyro-Bohm transport model, are compared with experimental data. In addition to the anomalous transport, neoclassical transport is included in the simulations and the ion thermal diffusivity in the inner third of the plasma is found to be predominantly neoclassical. The sawtooth oscillations in the simulations radially spread the neutral beam injection heating profiles across a broad sawtooth mixing region. The broad sawtooth oscillations also flatten the central temperature and electron density profiles. Simulation results for the electron temperature and density profiles are compared with experimental data to test the applicability of these models and the BALDUR integrated modeling code in the limit of low aspect ratio toroidal plasmas

  10. VEHICLE REPAIR AND MAINTENANCE COSTS IN NIGERIA ...

    African Journals Online (AJOL)

    A standard model was established for the prediction of repair and maintenance costs of vehicles in a non-profit making government parastatal. The model was derived based on data collected over a ten year period from a non-profit making government parastatal, and it predicts repair and maintenance costs as a linear ...

  11. Using NCAP to predict RFI effects in linear bipolar integrated circuits

    Science.gov (United States)

    Fang, T.-F.; Whalen, J. J.; Chen, G. K. C.

    1980-11-01

    Applications of the Nonlinear Circuit Analysis Program (NCAP) to calculate RFI effects in electronic circuits containing discrete semiconductor devices have been reported upon previously. The objective of this paper is to demonstrate that the computer program NCAP also can be used to calcuate RFI effects in linear bipolar integrated circuits (IC's). The IC's reported upon are the microA741 operational amplifier (op amp) which is one of the most widely used IC's, and a differential pair which is a basic building block in many linear IC's. The microA741 op amp was used as the active component in a unity-gain buffer amplifier. The differential pair was used in a broad-band cascode amplifier circuit. The computer program NCAP was used to predict how amplitude-modulated RF signals are demodulated in the IC's to cause undesired low-frequency responses. The predicted and measured results for radio frequencies in the 0.050-60-MHz range are in good agreement.

  12. Integrated Design Software Predicts the Creep Life of Monolithic Ceramic Components

    Science.gov (United States)

    1996-01-01

    Significant improvements in propulsion and power generation for the next century will require revolutionary advances in high-temperature materials and structural design. Advanced ceramics are candidate materials for these elevated-temperature applications. As design protocols emerge for these material systems, designers must be aware of several innate features, including the degrading ability of ceramics to carry sustained load. Usually, time-dependent failure in ceramics occurs because of two different, delayedfailure mechanisms: slow crack growth and creep rupture. Slow crack growth initiates at a preexisting flaw and continues until a critical crack length is reached, causing catastrophic failure. Creep rupture, on the other hand, occurs because of bulk damage in the material: void nucleation and coalescence that eventually leads to macrocracks which then propagate to failure. Successful application of advanced ceramics depends on proper characterization of material behavior and the use of an appropriate design methodology. The life of a ceramic component can be predicted with the NASA Lewis Research Center's Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design programs. CARES/CREEP determines the expected life of a component under creep conditions, and CARES/LIFE predicts the component life due to fast fracture and subcritical crack growth. The previously developed CARES/LIFE program has been used in numerous industrial and Government applications.

  13. MirZ: an integrated microRNA expression atlas and target prediction resource.

    Science.gov (United States)

    Hausser, Jean; Berninger, Philipp; Rodak, Christoph; Jantscher, Yvonne; Wirth, Stefan; Zavolan, Mihaela

    2009-07-01

    MicroRNAs (miRNAs) are short RNAs that act as guides for the degradation and translational repression of protein-coding mRNAs. A large body of work showed that miRNAs are involved in the regulation of a broad range of biological functions, from development to cardiac and immune system function, to metabolism, to cancer. For most of the over 500 miRNAs that are encoded in the human genome the functions still remain to be uncovered. Identifying miRNAs whose expression changes between cell types or between normal and pathological conditions is an important step towards characterizing their function as is the prediction of mRNAs that could be targeted by these miRNAs. To provide the community the possibility of exploring interactively miRNA expression patterns and the candidate targets of miRNAs in an integrated environment, we developed the MirZ web server, which is accessible at www.mirz.unibas.ch. The server provides experimental and computational biologists with statistical analysis and data mining tools operating on up-to-date databases of sequencing-based miRNA expression profiles and of predicted miRNA target sites in species ranging from Caenorhabditis elegans to Homo sapiens.

  14. Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

    Science.gov (United States)

    Wilkin, John L.; Rosenfeld, Leslie; Allen, Arthur; Baltes, Rebecca; Baptista, Antonio; He, Ruoying; Hogan, Patrick; Kurapov, Alexander; Mehra, Avichal; Quintrell, Josie; Schwab, David; Signell, Richard; Smith, Jane

    2017-01-01

    This paper outlines strategies that would advance coastal ocean modelling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the US Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of US-based researchers with a cross-section of coastal oceanography and ocean modelling expertise and community representation drawn from Regional and US Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation, and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modelling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3–8-year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, US Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal–academic partnerships benefiting IOOS stakeholders and end users.

  15. Integrating genomics and proteomics data to predict drug effects using binary linear programming.

    Science.gov (United States)

    Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo

    2014-01-01

    The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be

  16. Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System

    Science.gov (United States)

    Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.

    2017-12-01

    The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS

  17. The clinical obesity maintenance model: an integration of psychological constructs including mood, emotional regulation, disordered overeating, habitual cluster behaviours, health literacy and cognitive function.

    Science.gov (United States)

    Raman, Jayanthi; Smith, Evelyn; Hay, Phillipa

    2013-01-01

    Psychological distress and deficits in executive functioning are likely to be important barriers to effective weight loss maintenance. The purpose of this paper is twofold. First, in the light of recent evidence in the fields of neuropsychology and obesity, particularly on the deficits in the executive function in overweight and obese individuals, a conceptual and theoretical framework of obesity maintenance is introduced by way of a clinical obesity maintenance model (COMM). It is argued that psychological variables, that of habitual cluster Behaviors, emotional dysregulation, mood, and health literacy, interact with executive functioning and impact on the overeating/binge eating behaviors of obese individuals. Second, cognizant of this model, it is argued that the focus of obesity management should be extended to include a broader range of maintaining mechanisms, including but not limited to cognitive deficits. Finally, a discussion on potential future directions in research and practice using the COMM is provided.

  18. The Clinical Obesity Maintenance Model: An Integration of Psychological Constructs including Mood, Emotional Regulation, Disordered Overeating, Habitual Cluster Behaviours, Health Literacy and Cognitive Function

    Directory of Open Access Journals (Sweden)

    Jayanthi Raman

    2013-01-01

    Full Text Available Psychological distress and deficits in executive functioning are likely to be important barriers to effective weight loss maintenance. The purpose of this paper is twofold. First, in the light of recent evidence in the fields of neuropsychology and obesity, particularly on the deficits in the executive function in overweight and obese individuals, a conceptual and theoretical framework of obesity maintenance is introduced by way of a clinical obesity maintenance model (COMM. It is argued that psychological variables, that of habitual cluster Behaviors, emotional dysregulation, mood, and health literacy, interact with executive functioning and impact on the overeating/binge eating behaviors of obese individuals. Second, cognizant of this model, it is argued that the focus of obesity management should be extended to include a broader range of maintaining mechanisms, including but not limited to cognitive deficits. Finally, a discussion on potential future directions in research and practice using the COMM is provided.

  19. Prediction of irradiation damage effects by multi-scale modelling: EURATOM 3 Framework integrated project perfect

    International Nuclear Information System (INIS)

    Massoud, J.P.; Bugat, St.; Marini, B.; Lidbury, D.; Van Dyck, St.; Debarberis, L.

    2008-01-01

    Full text of publication follows. In nuclear PWRs, materials undergo degradation due to severe irradiation conditions that may limit their operational life. Utilities operating these reactors must quantify the aging and the potential degradations of reactor pressure vessels and also of internal structures to ensure safe and reliable plant operation. The EURATOM 6. Framework Integrated Project PERFECT (Prediction of Irradiation Damage Effects in Reactor Components) addresses irradiation damage in RPV materials and components by multi-scale modelling. This state-of-the-art approach offers potential advantages over the conventional empirical methods used in current practice of nuclear plant lifetime management. Launched in January 2004, this 48-month project is focusing on two main components of nuclear power plants which are subject to irradiation damage: the ferritic steel reactor pressure vessel and the austenitic steel internals. This project is also an opportunity to integrate the fragmented research and experience that currently exists within Europe in the field of numerical simulation of radiation damage and creates the links with international organisations involved in similar projects throughout the world. Continuous progress in the physical understanding of the phenomena involved in irradiation damage and continuous progress in computer sciences make possible the development of multi-scale numerical tools able to simulate the effects of irradiation on materials microstructure. The consequences of irradiation on mechanical and corrosion properties of materials are also tentatively modelled using such multi-scale modelling. But it requires to develop different mechanistic models at different levels of physics and engineering and to extend the state of knowledge in several scientific fields. And the links between these different kinds of models are particularly delicate to deal with and need specific works. Practically the main objective of PERFECT is to build

  20. Maintenance philosophy and program at Cernavoda NPP

    International Nuclear Information System (INIS)

    Bobos, M.; Enciu, G.

    1994-01-01

    Maintenance plays a key role in ensuring safe and reliable operation. An effective maintenance program should ensure that installed equipment operates when needed and the equipment malfunctions or deficiencies are corrected in time and rarely recur. Maintenance includes not only the activities traditionally associated with identifying or correcting current or potential equipment deficiencies but also extends to supporting technical functions for the conduct of these activities (for example, engineering, technical support, chemistry control, radiological protection, industrial safety and training). The maintenance management program should clearly define the relationship among these supporting groups as it is related to overall plant maintenance and promotes the concept of a successful integrated team effort. (Author)

  1. The Integrated Medical Model: A Probabilistic Simulation Model Predicting In-Flight Medical Risks

    Science.gov (United States)

    Keenan, Alexandra; Young, Millennia; Saile, Lynn; Boley, Lynn; Walton, Marlei; Kerstman, Eric; Shah, Ronak; Goodenow, Debra A.; Myers, Jerry G., Jr.

    2015-01-01

    The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting

  2. The Integrated Medical Model: A Probabilistic Simulation Model for Predicting In-Flight Medical Risks

    Science.gov (United States)

    Keenan, Alexandra; Young, Millennia; Saile, Lynn; Boley, Lynn; Walton, Marlei; Kerstman, Eric; Shah, Ronak; Goodenow, Debra A.; Myers, Jerry G.

    2015-01-01

    The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting

  3. Predicting Teacher Participation in a Classroom-Based, Integrated Preventive Intervention for Preschoolers.

    Science.gov (United States)

    Baker, Courtney N; Kupersmidt, Janis B; Voegler-Lee, Mary Ellen; Arnold, David H; Willoughby, Michael T

    2010-01-01

    Preschools provide a promising setting in which to conduct preventive interventions for childhood problems, but classroom programs can only be effective if teachers are willing and able to implement them. This study is one of the first to investigate predictors of the frequency of teacher participation in a classroom-based, randomized controlled trial of an integrated prevention program for preschoolers. The intervention was designed to promote school readiness with an integrated social and academic program, to be implemented by teachers with the support of classroom consultants. The current study is part of a larger project conducted with Head Start and community child care centers that serve primarily economically disadvantaged families; 49 teachers from 30 centers participated in this study. Overall, teachers conducted approximately 70% of the program activities. Participation decreased significantly over time from the first to the final week of the intervention, and also decreased within each week of the intervention, from the first to the final weekly activity. Teachers working at community child care centers implemented more intervention activities than did Head Start teachers. Teacher concerns about the intervention, assessed prior to training, predicted less participation. In addition, teachers' participation was positively related to their perception that their centers and directors were supportive, collegial, efficient, and fair, as well as their job satisfaction and commitment. Teacher experience, education, ethnicity, and self-efficacy were not significantly related to participation. In multi-level models that considered center as a level of analysis, substantial variance was accounted for by centers, pointing to the importance of considering center-level predictors in future research.

  4. Receipt of maintenance therapy is most predictive of survival in older acute lymphoblastic leukemia patients treated with intensive induction chemotherapy regimens.

    Science.gov (United States)

    Landsburg, Daniel J; Stadtmauer, Edward; Loren, Alison; Goldstein, Steven; Frey, Noelle; Nasta, Sunita D; Porter, David L; Tsai, Donald E; Perl, Alexander E; Hexner, Elizabeth O; Luger, Selina

    2013-08-01

    While the prognosis for older adults diagnosed with acute lymphoblastic leukemia (ALL) is frequently poor, long-term survival can be achieved in patients treated with curative intent. We reviewed the outcomes of 37 patients age ≥60 treated at our institution with either DVP- or hyperCVAD-based chemotherapy regimens from 2003-2011. In this patient population, a complete response rate of 92%, relapse rate of 56% and median overall survival of 18.1 months was experienced. Univariate analysis revealed that receipt of maintenance therapy vs. no maintenance therapy was associated with a statistically-significant impact on overall survival (p = 0.001, HR 0.15 for death), while disease-related characteristics including high-risk white blood cell count at diagnosis and Philadelphia chromosome status as well as treatment-related factors including chemotherapy regimen or completion of intensive therapy were not. Many patients were unable to initiate or remain on maintenance therapy due to toxicities including infections and cytopenias. Our analysis reveals the benefit of prolonged therapy in the treatment of older adults with ALL as well as the high incidence of treatment-related toxicity experienced by these patients. Copyright © 2013 Wiley Periodicals, Inc.

  5. A Bayesian network based approach for integration of condition-based maintenance in strategic offshore wind farm O&M simulation models

    DEFF Research Database (Denmark)

    Nielsen, Jannie Sønderkær; Sørensen, John Dalsgaard; Sperstad, Iver Bakken

    2018-01-01

    In the overall decision problem regarding optimization of operation and maintenance (O&M) for offshore wind farms, there are many approaches for solving parts of the overall decision problem. Simulation-based strategy models accurately capture system effects related to logistics, but model...... to generate failures and CBM tasks. An example considering CBM for wind turbine blades demonstrates the feasibility of the approach....

  6. Integrated Development and Maintenance of Software Products to Support Efficient Updating of Customer Configurations: A Case Study in Mass Market ERP Software

    NARCIS (Netherlands)

    Jansen, S.R.L.; Brinkkemper, S.; Ballintijn, G.; Nieuwland, Arco van

    2006-01-01

    The maintenance of enterprise application software at a customer site is a potentially complex task for software vendors. This complexity can unfortunately result in a significant amount of work and risk. This paper presents a case study of a product software vendor that tries to reduce this

  7. A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information.

    Science.gov (United States)

    Luo, Yunan; Zhao, Xinbin; Zhou, Jingtian; Yang, Jinglin; Zhang, Yanqing; Kuang, Wenhua; Peng, Jian; Chen, Ligong; Zeng, Jianyang

    2017-09-18

    The emergence of large-scale genomic, chemical and pharmacological data provides new opportunities for drug discovery and repositioning. In this work, we develop a computational pipeline, called DTINet, to predict novel drug-target interactions from a constructed heterogeneous network, which integrates diverse drug-related information. DTINet focuses on learning a low-dimensional vector representation of features, which accurately explains the topological properties of individual nodes in the heterogeneous network, and then makes prediction based on these representations via a vector space projection scheme. DTINet achieves substantial performance improvement over other state-of-the-art methods for drug-target interaction prediction. Moreover, we experimentally validate the novel interactions between three drugs and the cyclooxygenase proteins predicted by DTINet, and demonstrate the new potential applications of these identified cyclooxygenase inhibitors in preventing inflammatory diseases. These results indicate that DTINet can provide a practically useful tool for integrating heterogeneous information to predict new drug-target interactions and repurpose existing drugs.Network-based data integration for drug-target prediction is a promising avenue for drug repositioning, but performance is wanting. Here, the authors introduce DTINet, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations.

  8. Developing optimized prioritizing road maintenance

    Directory of Open Access Journals (Sweden)

    Ewadh Hussein Ali

    2018-01-01

    Full Text Available Increased demand for efficient maintenance of the existing roadway system needs optimal usage of the allocated funds. The paper demonstrates optimized methods for prioritizing maintenance implementation projects. A selected zone of roadway system in Kerbala city represents the study area to demonstrate the application of the developed prioritization process. Paver system PAVER integrated with GIS is used to estimate and display the pavement condition index PCI, thereby to establish a priority of maintenance. In addition to simple ranking method by PCI produced by the output of PAVER, the paper introduces PCI measure for each section of roadway. The paper introduces ranking by multiple measures investigated through expert knowledge about measures that affect prioritization and their irrespective weights due to a predesigned questionnaire. The maintenance priority index (MPI is related to cost of suitable proposed maintenance, easiness of proposed maintenance, average daily traffic and functional classification of the roadway in addition to PCI. Further, incremental benefit-cost analysis ranking provide an optimized process due to benefit and cost of maintenance. The paper introduces efficient display of layout and ranking for the selected zone of roadway system based on MPI index and incremental BCR method. Although the two developed methods introduce different layout display for priority, statistical test shows that no significant difference between ranking of all methods of prioritization.

  9. TECHNICAL MAINTENANCE EFFICIENCY OF THE AIRCRAFT MAINTENANCE-FREE ON-BOARD SYSTEM BETWEEN SCHEDULED MAINTENANCES

    Directory of Open Access Journals (Sweden)

    A. M. Bronnikov

    2017-01-01

    Full Text Available The avionics concept of the maintenance-free on-board equipment implies the absence of necessity to maintain onboard systems between scheduled maintenance, preserving the required operational and technical characteristics; it should be achieved by automatic diagnosis of the technical condition and the application of active means of ensuring a failsafe design, allowing to change the structure of the system to maintain its functions in case of failure. It is supposed that such equipment will reduce substantially and in the limit eliminate traditional maintenance of aircraft between scheduled maintenance, ensuring maximum readiness for use, along with improving safety. The paper proposes a methodology for evaluating the efficiency of maintenance-free between scheduled maintenance aircraft system with homogeneous redundancy. The excessive redundant elements allow the system to accumulate failures which are repaired during the routine maintenance. If the number of failures of any reserve is approaching a critical value, the recovery of the on-board system (elimination of all failures is carried out between scheduled maintenance by conducting rescue and recovery operations. It is believed that service work leads to the elimination of all failures and completely updates the on-board system. The process of system operational status changes is described with the discrete-continuous model in the flight time. The average losses in the sorties and the average cost of operation are used as integrated efficiency indicators of system operation. For example, the evaluation of the operation efficiency of formalized on-board system with homogeneous redundancy demonstrates the efficiency of the proposed methodology and the possibility of its use while analyzing the efficiency of the maintenance-free operation equipment between scheduled periods. As well as a comparative analysis of maintenance-free operation efficiency of the on-board system with excessive

  10. Influence of titration schedule and maintenance dose on the tolerability of adjunctive eslicarbazepine acetate: An integrated analysis of three randomized placebo-controlled trials.

    Science.gov (United States)

    Krauss, Gregory; Biton, Victor; Harvey, Jay H; Elger, Christian; Trinka, Eugen; Soares da Silva, Patrício; Gama, Helena; Cheng, Hailong; Grinnell, Todd; Blum, David

    2018-01-01

    To examine the influence of titration schedule and maintenance dose on the incidence and type of treatment-emergent adverse events (TEAEs) associated with adjunctive eslicarbazepine acetate (ESL). Data from three randomized, double-blind, placebo-controlled trials were analyzed. Patients with refractory partial-onset seizures were randomized to maintenance doses of ESL 400, 800, or 1200mg QD (dosing was initiated at 400 or 800mg QD) or placebo. The incidence of TEAEs was analyzed during the double-blind period (2-week titration phase; 12-week maintenance phase), according to the randomized maintenance dose and the titration schedule. 1447 patients were included in the analysis. During the first week of treatment, 62% of patients taking ESL 800mg QD had ≥1 TEAE, vs 35% of those taking 400mg QD and 32% of the placebo group; dizziness, somnolence, nausea, and headache were numerically more frequent in patients taking ESL 800mg than those taking ESL 400mg QD. During the double-blind period, the incidences of common TEAEs were lower in patients who initiated ESL at 400mg vs 800mg QD. For the 800 and 1200mg QD maintenance doses, rates of TEAEs leading to discontinuation were lower in patients who began treatment with 400mg than in those who began taking ESL 800mg QD. Initiation of ESL at 800mg QD is feasible. However, initiating treatment with ESL 400mg QD for 1 or 2 weeks is recommended, being associated with a lower incidence of TEAEs, and related discontinuations. For some patients, treatment may be initiated at 800mg QD, if the need for more immediate seizure reduction outweighs concerns about increased risk of adverse reactions during initiation. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  11. The dynamical integrity concept for interpreting/ predicting experimental behaviour: from macro- to nano-mechanics.

    Science.gov (United States)

    Lenci, Stefano; Rega, Giuseppe; Ruzziconi, Laura

    2013-06-28

    The dynamical integrity, a new concept proposed by J.M.T. Thompson, and developed by the authors, is used to interpret experimental results. After reviewing the main issues involved in this analysis, including the proposal of a new integrity measure able to capture in an easy way the safe part of basins, attention is dedicated to two experiments, a rotating pendulum and a micro-electro-mechanical system, where the theoretical predictions are not fulfilled. These mechanical systems, the former at the macro-scale and the latter at the micro-scale, permit a comparative analysis of different mechanical and dynamical behaviours. The fact that in both cases the dynamical integrity permits one to justify the difference between experimental and theoretical results, which is the main achievement of this paper, shows the effectiveness of this new approach and suggests its use in practical situations. The men of experiment are like the ant, they only collect and use; the reasoners resemble spiders, who make cobwebs out of their own substance. But the bee takes the middle course: it gathers its material from the flowers of the garden and field, but transforms and digests it by a power of its own. Not unlike this is the true business of philosophy (science); for it neither relies solely or chiefly on the powers of the mind, nor does it take the matter which it gathers from natural history and mechanical experiments and lay up in the memory whole, as it finds it, but lays it up in the understanding altered and digested. Therefore, from a closer and purer league between these two faculties, the experimental and the rational (such as has never been made), much may be hoped. (Francis Bacon 1561-1626) But are we sure of our observational facts? Scientific men are rather fond of saying pontifically that one ought to be quite sure of one's observational facts before embarking on theory. Fortunately those who give this advice do not practice what they preach. Observation and theory get

  12. Integrated and Total HIV-1 DNA Predict Ex Vivo Viral Outgrowth.

    Directory of Open Access Journals (Sweden)

    Maja Kiselinova

    2016-03-01

    Full Text Available The persistence of a reservoir of latently infected CD4 T cells remains one of the major obstacles to cure HIV. Numerous strategies are being explored to eliminate this reservoir. To translate these efforts into clinical trials, there is a strong need for validated biomarkers that can monitor the reservoir over time in vivo. A comprehensive study was designed to evaluate and compare potential HIV-1 reservoir biomarkers. A cohort of 25 patients, treated with suppressive antiretroviral therapy was sampled at three time points, with median of 2.5 years (IQR: 2.4-2.6 between time point 1 and 2; and median of 31 days (IQR: 28-36 between time point 2 and 3. Patients were median of 6 years (IQR: 3-12 on ART, and plasma viral load (<50 copies/ml was suppressed for median of 4 years (IQR: 2-8. Total HIV-1 DNA, unspliced (us and multiply spliced HIV-1 RNA, and 2LTR circles were quantified by digital PCR in peripheral blood, at 3 time points. At the second time point, a viral outgrowth assay (VOA was performed, and integrated HIV-1 DNA and relative mRNA expression levels of HIV-1 restriction factors were quantified. No significant change was found for long- and short-term dynamics of all HIV-1 markers tested in peripheral blood. Integrated HIV-1 DNA was associated with total HIV-1 DNA (p<0.001, R² = 0.85, us HIV-1 RNA (p = 0.029, R² = 0.40, and VOA (p = 0.041, R2 = 0.44. Replication-competent virus was detected in 80% of patients by the VOA and it correlated with total HIV-1 DNA (p = 0.039, R² = 0.54. The mean quantification difference between Alu-PCR and VOA was 2.88 log10, and 2.23 log10 between total HIV-1 DNA and VOA. The levels of usHIV-1 RNA were inver