WorldWideScience

Sample records for based diagnostic model

  1. Topological Modeling Based Diagnostic Tests Selection

    OpenAIRE

    Eriņš, M

    2014-01-01

    This article covers the process of software testing. Test management and creation methods are described within the scope of the research. The process of test selection through several stages of project development is discussed and practical examples of appliance are given for the test organization and decision making with the help of topological models of software. The criteria of test ranging are described within scope of each of the testing levels. The paper indicates the use of topological...

  2. Topological Modeling Based Diagnostic Tests Selection

    OpenAIRE

    Erins, Matiss

    2015-01-01

    This article covers the process of software testing. Test management and creation methods are described within the scope of the research. The process of test selection through several stages of project development is discussed and practical examples of appliance are given for the test organization and decision making with the help of topological models of software. The criteria of test ranging are described within scope of each of the testing levels. The paper indicates the use of topological...

  3. Stage Separation Failure: Model Based Diagnostics and Prognostics

    Science.gov (United States)

    Luchinsky, Dmitry; Hafiychuk, Vasyl; Kulikov, Igor; Smelyanskiy, Vadim; Patterson-Hine, Ann; Hanson, John; Hill, Ashley

    2010-01-01

    Safety of the next-generation space flight vehicles requires development of an in-flight Failure Detection and Prognostic (FD&P) system. Development of such system is challenging task that involves analysis of many hard hitting engineering problems across the board. In this paper we report progress in the development of FD&P for the re-contact fault between upper stage nozzle and the inter-stage caused by the first stage and upper stage separation failure. A high-fidelity models and analytical estimations are applied to analyze the following sequence of events: (i) structural dynamics of the nozzle extension during the impact; (ii) structural stability of the deformed nozzle in the presence of the pressure and temperature loads induced by the hot gas flow during engine start up; and (iii) the fault induced thrust changes in the steady burning regime. The diagnostic is based on the measurements of the impact torque. The prognostic is based on the analysis of the correlation between the actuator signal and fault-induced changes in the nozzle structural stability and thrust.

  4. A model based diagnostic system for the identification of malfunctioning components using a constraint propagation paradigm

    International Nuclear Information System (INIS)

    A commonly recognized failing of traditional rule-based diagnostic expert systems is the inability to recognize problems outside the range of expertise. In turn, the capability of such expert systems is limited to well-known problems. Contrary to the traditional approach, a model-based system has a potential to diagnose unexpected malfunctions. In this paper, a model-based diagnostic system for the isolation of malfunctioning components using constraint propagation paradigm - the CBDS, the Constraint Based Diagnostic System - is presented. The CBDS consists of (1) symbolic representation of plant model as a knowledge base, and (2) constraint propagation paradigm as a diagnostic inference engine. In the CBDS, a plant model contains information about intended behaviour of components that are organized in a component model library, as well as information about how the components are interconnected. As a diagnostic inference engine, the CBDS uses the general idea of model-based diagnosis to identify malfunctioning components. (author). 15 refs, 8 figs

  5. Automated extraction of knowledge for model-based diagnostics

    Science.gov (United States)

    Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

    1990-01-01

    The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

  6. Model-based Diagnostics for Propellant Loading Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — The loading of spacecraft propellants is a complex, risky operation. Therefore, diagnostic solutions are neces- sary to quickly identify when a fault occurs, so...

  7. PROcess Based Diagnostics PROBE

    Science.gov (United States)

    Clune, T.; Schmidt, G.; Kuo, K.; Bauer, M.; Oloso, H.

    2013-01-01

    Many of the aspects of the climate system that are of the greatest interest (e.g., the sensitivity of the system to external forcings) are emergent properties that arise via the complex interplay between disparate processes. This is also true for climate models most diagnostics are not a function of an isolated portion of source code, but rather are affected by multiple components and procedures. Thus any model-observation mismatch is hard to attribute to any specific piece of code or imperfection in a specific model assumption. An alternative approach is to identify diagnostics that are more closely tied to specific processes -- implying that if a mismatch is found, it should be much easier to identify and address specific algorithmic choices that will improve the simulation. However, this approach requires looking at model output and observational data in a more sophisticated way than the more traditional production of monthly or annual mean quantities. The data must instead be filtered in time and space for examples of the specific process being targeted.We are developing a data analysis environment called PROcess-Based Explorer (PROBE) that seeks to enable efficient and systematic computation of process-based diagnostics on very large sets of data. In this environment, investigators can define arbitrarily complex filters and then seamlessly perform computations in parallel on the filtered output from their model. The same analysis can be performed on additional related data sets (e.g., reanalyses) thereby enabling routine comparisons between model and observational data. PROBE also incorporates workflow technology to automatically update computed diagnostics for subsequent executions of a model. In this presentation, we will discuss the design and current status of PROBE as well as share results from some preliminary use cases.

  8. Diagnostic models based on personalized analysis of trends (PAT).

    Science.gov (United States)

    Hudson, Donna L; Cohen, Maurice E

    2010-07-01

    Many changes have taken place in medicine over the last century. In the first-half of the 20th century physicians were faced with the challenge of making diagnoses with too little information, often resorting to exploratory surgery to confirm the presence or absence of a condition. Due to rapid technological advances during the second-half of the 20th century, and continuing to this day, the position of the physician has now shifted from an information-poor environment to an environment with too much information, often exceeding the limits of human decision-making capabilities. To take full advantage of all available information, a new approach based on refined automated decision support methods is needed to assist the physician in the decision-making process. Medical decision support systems need to evolve from stand-alone systems to cooperative systems in which the physician becomes the decision maker, but relies on the decision support system to sift through information to determine relevant trends. In this paper, a decision support system that combines a number of methodologies for trend analysis is described, along with examples in cardiology. The methods have also been used in applications in neurology as well as cancer diagnosis and prognosis. PMID:19775973

  9. Artificial Neural Network based Diagnostic Model For Causes of Success and Failures

    OpenAIRE

    Kaur, Bikrampal; Aggarwal, Himanshu

    2010-01-01

    In this paper an attempt has been made to identify most important human resource factors and propose a diagnostic model based on the back-propagation and connectionist model approaches of artificial neural network (ANN). The focus of the study is on the mobile -communication industry of India. The ANN based approach is particularly important because conventional approaches (such as algorithmic) to the problem solving have their inherent disadvantages. The algorithmic approach is well-suited t...

  10. The control structure of team-based organizations : A diagnostic model for empowerment

    NARCIS (Netherlands)

    Kuipers, Benjamin; de Witte, M.C.

    2005-01-01

    This article describes a diagnostic model for empowerment in team-based organizations that portrays four dimensions of the organization's control structure: the level of routine, the nature of expertise, the level of dependence and the line of command. The combined positions of the set of job regula

  11. Calibration diagnostic and updating strategy based on quantitative modeling of near-infrared spectral residuals.

    Science.gov (United States)

    Yu, Hua; Small, Gary W

    2015-02-01

    A diagnostic and updating strategy is explored for multivariate calibrations based on near-infrared spectroscopy. For use with calibration models derived from spectral fitting or decomposition techniques, the proposed method constructs models that relate the residual concentrations remaining after a prediction to the residual spectra remaining after the information associated with the calibration model has been extracted. This residual modeling approach is evaluated for use with partial least-squares (PLS) models for predicting physiological levels of glucose in a simulated biological matrix. Residual models are constructed with both PLS and a hybrid technique based on the use of PLS scores as inputs to support vector regression. Calibration and residual models are built with both absorbance and single-beam data collected over 416 days. Effective models for the spectral residuals are built with both types of data and demonstrate the ability to diagnose and correct deviations in performance of the calibration model with time. PMID:25473807

  12. A segmental hidden semi-Markov model (HSMM)-based diagnostics and prognostics framework and methodology

    Science.gov (United States)

    Dong, Ming; He, David

    2007-07-01

    Diagnostics and prognostics are two important aspects in a condition-based maintenance (CBM) program. However, these two tasks are often separately performed. For example, data might be collected and analysed separately for diagnosis and prognosis. This practice increases the cost and reduces the efficiency of CBM and may affect the accuracy of the diagnostic and prognostic results. In this paper, a statistical modelling methodology for performing both diagnosis and prognosis in a unified framework is presented. The methodology is developed based on segmental hidden semi-Markov models (HSMMs). An HSMM is a hidden Markov model (HMM) with temporal structures. Unlike HMM, an HSMM does not follow the unrealistic Markov chain assumption and therefore provides more powerful modelling and analysis capability for real problems. In addition, an HSMM allows modelling the time duration of the hidden states and therefore is capable of prognosis. To facilitate the computation in the proposed HSMM-based diagnostics and prognostics, new forward-backward variables are defined and a modified forward-backward algorithm is developed. The existing state duration estimation methods are inefficient because they require a huge storage and computational load. Therefore, a new approach is proposed for training HSMMs in which state duration probabilities are estimated on the lattice (or trellis) of observations and states. The model parameters are estimated through the modified forward-backward training algorithm. The estimated state duration probability distributions combined with state-changing point detection can be used to predict the useful remaining life of a system. The evaluation of the proposed methodology was carried out through a real world application: health monitoring of hydraulic pumps. In the tests, the recognition rates for all states are greater than 96%. For each individual pump, the recognition rate is increased by 29.3% in comparison with HMMs. Because of the temporal

  13. Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

    Science.gov (United States)

    Lu, Feng; Huang, Jinquan; Xing, Yaodong

    2012-01-01

    Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient. PMID:23112645

  14. Fault Diagnostics for Turbo-Shaft Engine Sensors Based on a Simplified On-Board Model

    Directory of Open Access Journals (Sweden)

    Yaodong Xing

    2012-08-01

    Full Text Available Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can’t be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

  15. Artificial Neural Network based Diagnostic Model For Causes of Success and Failures

    CERN Document Server

    Kaur, Bikrampal

    2010-01-01

    In this paper an attempt has been made to identify most important human resource factors and propose a diagnostic model based on the back-propagation and connectionist model approaches of artificial neural network (ANN). The focus of the study is on the mobile -communication industry of India. The ANN based approach is particularly important because conventional approaches (such as algorithmic) to the problem solving have their inherent disadvantages. The algorithmic approach is well-suited to the problems that are well-understood and known solution(s). On the other hand the ANNs have learning by example and processing capabilities similar to that of a human brain. ANN has been followed due to its inherent advantage over conversion algorithmic like approaches and having capabilities, training and human like intuitive decision making capabilities. Therefore, this ANN based approach is likely to help researchers and organizations to reach a better solution to the problem of managing the human resource. The stud...

  16. Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool

    Directory of Open Access Journals (Sweden)

    Swagata Payra

    2014-01-01

    Full Text Available The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions.

  17. Cardiovascular modeling and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Kangas, L.J.; Keller, P.E.; Hashem, S.; Kouzes, R.T. [Pacific Northwest Lab., Richland, WA (United States)

    1995-12-31

    In this paper, a novel approach to modeling and diagnosing the cardiovascular system is introduced. A model exhibits a subset of the dynamics of the cardiovascular behavior of an individual by using a recurrent artificial neural network. Potentially, a model will be incorporated into a cardiovascular diagnostic system. This approach is unique in that each cardiovascular model is developed from physiological measurements of an individual. Any differences between the modeled variables and the variables of an individual at a given time are used for diagnosis. This approach also exploits sensor fusion to optimize the utilization of biomedical sensors. The advantage of sensor fusion has been demonstrated in applications including control and diagnostics of mechanical and chemical processes.

  18. Dynamic Bayesian Network Modeling of Game Based Diagnostic Assessments. CRESST Report 837

    Science.gov (United States)

    Levy, Roy

    2014-01-01

    Digital games offer an appealing environment for assessing student proficiencies, including skills and misconceptions in a diagnostic setting. This paper proposes a dynamic Bayesian network modeling approach for observations of student performance from an educational video game. A Bayesian approach to model construction, calibration, and use in…

  19. Model-based versus specific dosimetry in diagnostic context: Comparison of three dosimetric approaches

    International Nuclear Information System (INIS)

    Purpose: The dosimetric assessment of novel radiotracers represents a legal requirement in most countries. While the techniques for the computation of internal absorbed dose in a therapeutic context have made huge progresses in recent years, in a diagnostic scenario the absorbed dose is usually extracted from model-based lookup tables, most often derived from International Commission on Radiological Protection (ICRP) or Medical Internal Radiation Dose (MIRD) Committee models. The level of approximation introduced by these models may impact the resulting dosimetry. The aim of this work is to establish whether a more refined approach to dosimetry can be implemented in nuclear medicine diagnostics, by analyzing a specific case. Methods: The authors calculated absorbed doses to various organs in six healthy volunteers administered with flutemetamol (18F) injection. Each patient underwent from 8 to 10 whole body 3D PET/CT scans. This dataset was analyzed using a Monte Carlo (MC) application developed in-house using the toolkit GATE that is capable to take into account patient-specific anatomy and radiotracer distribution at the voxel level. They compared the absorbed doses obtained with GATE to those calculated with two commercially available software: OLINDA/EXM and STRATOS implementing a dose voxel kernel convolution approach. Results: Absorbed doses calculated with GATE were higher than those calculated with OLINDA. The average ratio between GATE absorbed doses and OLINDA’s was 1.38 ± 0.34 σ (from 0.93 to 2.23). The discrepancy was particularly high for the thyroid, with an average GATE/OLINDA ratio of 1.97 ± 0.83 σ for the six patients. Differences between STRATOS and GATE were found to be higher. The average ratio between GATE and STRATOS absorbed doses was 2.51 ± 1.21 σ (from 1.09 to 6.06). Conclusions: This study demonstrates how the choice of the absorbed dose calculation algorithm may introduce a bias when gamma radiations are of importance, as is the

  20. Model-based versus specific dosimetry in diagnostic context: Comparison of three dosimetric approaches

    Energy Technology Data Exchange (ETDEWEB)

    Marcatili, S., E-mail: sara.marcatili@inserm.fr; Villoing, D.; Mauxion, T.; Bardiès, M. [Inserm, UMR1037 CRCT, Toulouse F-31000, France and Université Toulouse III-Paul Sabatier, UMR1037 CRCT, Toulouse F-31000 (France); McParland, B. J. [Imaging Technology Group, GE Healthcare, Life Sciences, B22U The Grove Centre, White Lion Road, Amersham, England HP7 9LL (United Kingdom)

    2015-03-15

    Purpose: The dosimetric assessment of novel radiotracers represents a legal requirement in most countries. While the techniques for the computation of internal absorbed dose in a therapeutic context have made huge progresses in recent years, in a diagnostic scenario the absorbed dose is usually extracted from model-based lookup tables, most often derived from International Commission on Radiological Protection (ICRP) or Medical Internal Radiation Dose (MIRD) Committee models. The level of approximation introduced by these models may impact the resulting dosimetry. The aim of this work is to establish whether a more refined approach to dosimetry can be implemented in nuclear medicine diagnostics, by analyzing a specific case. Methods: The authors calculated absorbed doses to various organs in six healthy volunteers administered with flutemetamol ({sup 18}F) injection. Each patient underwent from 8 to 10 whole body 3D PET/CT scans. This dataset was analyzed using a Monte Carlo (MC) application developed in-house using the toolkit GATE that is capable to take into account patient-specific anatomy and radiotracer distribution at the voxel level. They compared the absorbed doses obtained with GATE to those calculated with two commercially available software: OLINDA/EXM and STRATOS implementing a dose voxel kernel convolution approach. Results: Absorbed doses calculated with GATE were higher than those calculated with OLINDA. The average ratio between GATE absorbed doses and OLINDA’s was 1.38 ± 0.34 σ (from 0.93 to 2.23). The discrepancy was particularly high for the thyroid, with an average GATE/OLINDA ratio of 1.97 ± 0.83 σ for the six patients. Differences between STRATOS and GATE were found to be higher. The average ratio between GATE and STRATOS absorbed doses was 2.51 ± 1.21 σ (from 1.09 to 6.06). Conclusions: This study demonstrates how the choice of the absorbed dose calculation algorithm may introduce a bias when gamma radiations are of importance, as is

  1. Enhancing Paper-Based Diagnostics through Quantitative Experimentation, Modeling, and Design

    OpenAIRE

    Mosley, Garrett

    2016-01-01

    Infectious diseases are a significant problem, accounting for 1 in every 4 deaths worldwide. The field of bioengineering is constantly innovating and advancing diagnostic technology; however, more often than not, these innovations are accessible only to communities with privileged resources. This has led to a growing focus on point-of-care (POC) diagnostics. Due to their ease of use, speed, and low cost, POC diagnostics can effectively test patients in resource-poor settings. One of the most ...

  2. New Assessment Model of Pulse Depth Based on Sensor Displacement in Pulse Diagnostic Devices

    OpenAIRE

    Jang-Han Bae; Young Ju Jeon; Jong Yeol Kim; Kim, Jaeuk U.

    2013-01-01

    An accurate assessment of the pulse depth in pulse diagnosis is vital to determine the floating and sunken pulse qualities (PQs), which are two of the four most basic PQs. In this work, we proposed a novel model of assessing the pulse depth based on sensor displacement (SD) normal to the skin surface and compared this model with two previous models which assessed the pulse depth using contact pressure (CP). In contrast to conventional stepwise CP variation tonometry, we applied a continuously...

  3. Model-based evaluation of the use of polycyclic aromatic hydrocarbons molecular diagnostic ratios as a source identification tool

    International Nuclear Information System (INIS)

    Polycyclic Aromatic Hydrocarbons (PAHs) molecular diagnostic ratios (MDRs) are unitless concentration ratios of pair-PAHs with the same molecular weight (MW); MDRs have long been used as a tool for PAHs source identification purposes. In the present paper, the efficiency of the MDR methodology is evaluated through the use of a multimedia fate model, the calculation of characteristic travel distances (CTD) and the estimation of air concentrations for individual PAHs as a function of distance from an initial point source. The results show that PAHs with the same MW are sometimes characterized by substantially different CTDs and therefore their air concentrations and hence MDRs are predicted to change as the distance from the original source increases. From the assessed pair-PAHs, the biggest CTD difference is seen for Fluoranthene (107 km) vs. Pyrene (26 km). This study provides a strong indication that MDRs are of limited use as a source identification tool. -- Highlights: • Model-based evaluation of the PAHs molecular diagnostic ratios efficiency. • Individual PAHs are characterized by different characteristic travel distances. • MDRs are proven to be a limited tool for source identification. • Use of MDRs for other environmental media is likely unfeasible. -- PAHs molecular diagnostic ratios which change greatly as a function of distance from the emitting source are improper for source identification purposes

  4. Knowledge based diagnostics in nuclear power plants

    International Nuclear Information System (INIS)

    In the paper to be given a special process diagnostic system (PDS) will be presented, taking into account corresponding user experiences. It must be seen the result of a long term work on computerized process surveillance and control on NPP; it includes a model based system for noise analysis of mechanical vibrations, which has been enhanced by using of knowledge based technique (expert systems). The paper will discuss the process diagnostic frame concept and emphasize the vibration analysis expertsystem RADEX, with the parts modelling (building a knowledge base), man-machine communication aspects, implementation. (author). 5 refs, 5 figs

  5. A network diagnostics method based on pattern recognition algorithms

    OpenAIRE

    Olizarovich, E. V.; Rodchenko, V. G.

    2009-01-01

    This report deals with the problem of designing and building of a computer network diagnostic system. Diagnostic content problems are reviewed, as well as ways of their solution based on mathematical and computer modelling methods. A traffic analysis-based diagnostic method is suggested for process statuses in a computer network. The method is based on algorithms of the mathematical pattern recognition theory. To build a diagnostic system, a multi-level model building and verification arrange...

  6. Cotton-based diagnostic devices.

    Science.gov (United States)

    Lin, Shang-Chi; Hsu, Min-Yen; Kuan, Chen-Meng; Wang, Hsi-Kai; Chang, Chia-Ling; Tseng, Fan-Gang; Cheng, Chao-Min

    2014-01-01

    A good diagnostic procedure avoids wasting medical resources, is easy to use, resists contamination, and provides accurate information quickly to allow for rapid follow-up therapies. We developed a novel diagnostic procedure using a "cotton-based diagnostic device" capable of real-time detection, i.e., in vitro diagnostics (IVD), which avoids reagent contamination problems common to existing biomedical devices and achieves the abovementioned goals of economy, efficiency, ease of use, and speed. Our research reinforces the advantages of an easy-to-use, highly accurate diagnostic device created from an inexpensive and readily available U.S. FDA-approved material (i.e., cotton as flow channel and chromatography paper as reaction zone) that adopts a standard calibration curve method in a buffer system (i.e., nitrite, BSA, urobilinogen and uric acid assays) to accurately obtain semi-quantitative information and limit the cross-contamination common to multiple-use tools. Our system, which specifically targets urinalysis diagnostics and employs a multiple biomarker approach, requires no electricity, no professional training, and is exceptionally portable for use in remote or home settings. This could be particularly useful in less industrialized areas. PMID:25393975

  7. Rocket engine diagnostics using qualitative modeling techniques

    Science.gov (United States)

    Binder, Michael; Maul, William; Meyer, Claudia; Sovie, Amy

    1992-01-01

    Researchers at NASA Lewis Research Center are presently developing qualitative modeling techniques for automated rocket engine diagnostics. A qualitative model of a turbopump interpropellant seal system has been created. The qualitative model describes the effects of seal failures on the system steady-state behavior. This model is able to diagnose the failure of particular seals in the system based on anomalous temperature and pressure values. The anomalous values input to the qualitative model are generated using numerical simulations. Diagnostic test cases include both single and multiple seal failures.

  8. Ultrafast Laser Diagnostics for Energetic-Material Ignition Mechanisms: Tools for Physics-Based Model Development.

    Energy Technology Data Exchange (ETDEWEB)

    Kearney, Sean Patrick; Jilek, Brook Anton; Kohl, Ian Thomas; Farrow, Darcie; Urayama, Junji

    2014-11-01

    We present the results of an LDRD project to develop diagnostics to perform fundamental measurements of material properties during shock compression of condensed phase materials at micron spatial scales and picosecond time scales. The report is structured into three main chapters, which each focus on a different diagnostic devel opment effort. Direct picosecond laser drive is used to introduce shock waves into thin films of energetic and inert materials. The resulting laser - driven shock properties are probed via Ultrafast Time Domain Interferometry (UTDI), which can additionally be used to generate shock Hugoniot data in tabletop experiments. Stimulated Raman scattering (SRS) is developed as a temperature diagnostic. A transient absorption spectroscopy setup has been developed to probe shock - induced changes during shock compressio n. UTDI results are presented under dynamic, direct - laser - drive conditions and shock Hugoniots are estimated for inert polystyrene samples and for the explosive hexanitroazobenzene, with results from both Sandia and Lawrence Livermore presented here. SRS a nd transient absorption diagnostics are demonstrated on static thin - film samples, and paths forward to dynamic experiments are presented.

  9. On-line experimental validation of a model-based diagnostic algorithm dedicated to a solid oxide fuel cell system

    Science.gov (United States)

    Polverino, Pierpaolo; Esposito, Angelo; Pianese, Cesare; Ludwig, Bastian; Iwanschitz, Boris; Mai, Andreas

    2016-02-01

    In the current energetic scenario, Solid Oxide Fuel Cells (SOFCs) exhibit appealing features which make them suitable for environmental-friendly power production, especially for stationary applications. An example is represented by micro-combined heat and power (μ-CHP) generation units based on SOFC stacks, which are able to produce electric and thermal power with high efficiency and low pollutant and greenhouse gases emissions. However, the main limitations to their diffusion into the mass market consist in high maintenance and production costs and short lifetime. To improve these aspects, the current research activity focuses on the development of robust and generalizable diagnostic techniques, aimed at detecting and isolating faults within the entire system (i.e. SOFC stack and balance of plant). Coupled with appropriate recovery strategies, diagnosis can prevent undesired system shutdowns during faulty conditions, with consequent lifetime increase and maintenance costs reduction. This paper deals with the on-line experimental validation of a model-based diagnostic algorithm applied to a pre-commercial SOFC system. The proposed algorithm exploits a Fault Signature Matrix based on a Fault Tree Analysis and improved through fault simulations. The algorithm is characterized on the considered system and it is validated by means of experimental induction of faulty states in controlled conditions.

  10. Vision-based building energy diagnostics and retrofit analysis using 3D thermography and building information modeling

    Science.gov (United States)

    Ham, Youngjib

    The emerging energy crisis in the building sector and the legislative measures on improving energy efficiency are steering the construction industry towards adopting new energy efficient design concepts and construction methods that decrease the overall energy loads. However, the problems of energy efficiency are not only limited to the design and construction of new buildings. Today, a significant amount of input energy in existing buildings is still being wasted during the operational phase. One primary source of the energy waste is attributed to unnecessary heat flows through building envelopes during hot and cold seasons. This inefficiency increases the operational frequency of heating and cooling systems to keep the desired thermal comfort of building occupants, and ultimately results in excessive energy use. Improving thermal performance of building envelopes can reduce the energy consumption required for space conditioning and in turn provide building occupants with an optimal thermal comfort at a lower energy cost. In this sense, energy diagnostics and retrofit analysis for existing building envelopes are key enablers for improving energy efficiency. Since proper retrofit decisions of existing buildings directly translate into energy cost saving in the future, building practitioners are increasingly interested in methods for reliable identification of potential performance problems so that they can take timely corrective actions. However, sensing what and where energy problems are emerging or are likely to emerge and then analyzing how the problems influence the energy consumption are not trivial tasks. The overarching goal of this dissertation focuses on understanding the gaps in knowledge in methods for building energy diagnostics and retrofit analysis, and filling these gaps by devising a new method for multi-modal visual sensing and analytics using thermography and Building Information Modeling (BIM). First, to address the challenges in scaling and

  11. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

    2016-08-01

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  12. Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings

    Energy Technology Data Exchange (ETDEWEB)

    Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

    2016-08-26

    Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energy models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.

  13. Automatic component calibration and error diagnostics for model-based accelerator control. Phase I final report

    International Nuclear Information System (INIS)

    Phase I work studied the feasibility of developing software for automatic component calibration and error correction in beamline optics models. A prototype application was developed that corrects quadrupole field strength errors in beamline models

  14. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

    2015-12-01

    Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the

  15. Growth curve models and statistical diagnostics

    CERN Document Server

    Pan, Jian-Xin

    2002-01-01

    Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.

  16. DNA Microarray-Based Diagnostics.

    Science.gov (United States)

    Marzancola, Mahsa Gharibi; Sedighi, Abootaleb; Li, Paul C H

    2016-01-01

    The DNA microarray technology is currently a useful biomedical tool which has been developed for a variety of diagnostic applications. However, the development pathway has not been smooth and the technology has faced some challenges. The reliability of the microarray data and also the clinical utility of the results in the early days were criticized. These criticisms added to the severe competition from other techniques, such as next-generation sequencing (NGS), impacting the growth of microarray-based tests in the molecular diagnostic market.Thanks to the advances in the underlying technologies as well as the tremendous effort offered by the research community and commercial vendors, these challenges have mostly been addressed. Nowadays, the microarray platform has achieved sufficient standardization and method validation as well as efficient probe printing, liquid handling and signal visualization. Integration of various steps of the microarray assay into a harmonized and miniaturized handheld lab-on-a-chip (LOC) device has been a goal for the microarray community. In this respect, notable progress has been achieved in coupling the DNA microarray with the liquid manipulation microsystem as well as the supporting subsystem that will generate the stand-alone LOC device.In this chapter, we discuss the major challenges that microarray technology has faced in its almost two decades of development and also describe the solutions to overcome the challenges. In addition, we review the advancements of the technology, especially the progress toward developing the LOC devices for DNA diagnostic applications. PMID:26614075

  17. Vision-based building energy diagnostics and retrofit analysis using 3D thermography and building information modeling

    Science.gov (United States)

    Ham, Youngjib

    The emerging energy crisis in the building sector and the legislative measures on improving energy efficiency are steering the construction industry towards adopting new energy efficient design concepts and construction methods that decrease the overall energy loads. However, the problems of energy efficiency are not only limited to the design and construction of new buildings. Today, a significant amount of input energy in existing buildings is still being wasted during the operational phase. One primary source of the energy waste is attributed to unnecessary heat flows through building envelopes during hot and cold seasons. This inefficiency increases the operational frequency of heating and cooling systems to keep the desired thermal comfort of building occupants, and ultimately results in excessive energy use. Improving thermal performance of building envelopes can reduce the energy consumption required for space conditioning and in turn provide building occupants with an optimal thermal comfort at a lower energy cost. In this sense, energy diagnostics and retrofit analysis for existing building envelopes are key enablers for improving energy efficiency. Since proper retrofit decisions of existing buildings directly translate into energy cost saving in the future, building practitioners are increasingly interested in methods for reliable identification of potential performance problems so that they can take timely corrective actions. However, sensing what and where energy problems are emerging or are likely to emerge and then analyzing how the problems influence the energy consumption are not trivial tasks. The overarching goal of this dissertation focuses on understanding the gaps in knowledge in methods for building energy diagnostics and retrofit analysis, and filling these gaps by devising a new method for multi-modal visual sensing and analytics using thermography and Building Information Modeling (BIM). First, to address the challenges in scaling and

  18. A Causal Model for Diagnostic Reasoning

    Institute of Scientific and Technical Information of China (English)

    PENG Guoqiang; CHENG Hu

    2000-01-01

    Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic reasoning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presented.

  19. Optimized diagnostic model combination for improving diagnostic accuracy

    Science.gov (United States)

    Kunche, S.; Chen, C.; Pecht, M. G.

    Identifying the most suitable classifier for diagnostics is a challenging task. In addition to using domain expertise, a trial and error method has been widely used to identify the most suitable classifier. Classifier fusion can be used to overcome this challenge and it has been widely known to perform better than single classifier. Classifier fusion helps in overcoming the error due to inductive bias of various classifiers. The combination rule also plays a vital role in classifier fusion, and it has not been well studied which combination rules provide the best performance during classifier fusion. Good combination rules will achieve good generalizability while taking advantage of the diversity of the classifiers. In this work, we develop an approach for ensemble learning consisting of an optimized combination rule. The generalizability has been acknowledged to be a challenge for training a diverse set of classifiers, but it can be achieved by an optimal balance between bias and variance errors using the combination rule in this paper. Generalizability implies the ability of a classifier to learn the underlying model from the training data and to predict the unseen observations. In this paper, cross validation has been employed during performance evaluation of each classifier to get an unbiased performance estimate. An objective function is constructed and optimized based on the performance evaluation to achieve the optimal bias-variance balance. This function can be solved as a constrained nonlinear optimization problem. Sequential Quadratic Programming based optimization with better convergence property has been employed for the optimization. We have demonstrated the applicability of the algorithm by using support vector machine and neural networks as classifiers, but the methodology can be broadly applicable for combining other classifier algorithms as well. The method has been applied to the fault diagnosis of analog circuits. The performance of the proposed

  20. Nanotechnology based diagnostics for neurological disorders

    International Nuclear Information System (INIS)

    Nanotechnology involves probing and manipulating matter at the molecular level. Nanotechnology based molecular diagnostics have the potential to alleviate the suffering caused by many diseases, including neurological disorders, due to the unique properties of nanomaterials. Most neurological illnesses are multifactorial conditions and many of these are also classified as neurobehavioral disorders. Alzheimer's disease, Parkinson's disease, Huntington disease, cerebral ischemia, epilepsy, schizophrenia and autism spectrum disorders like Rett syndrome are some examples of neurological disorders that could be better treated, diagnosed, prevented and possibly cured using nanotechnology. In order to improve the quality of life for disease afflicted people, a wide range of nanomaterials that include gold and silica nanoparticles, quantum dots and DNA along with countless other forms of nanotechnology have been investigated regarding their usefulness in advancing molecular diagnostics. Other small scaled materials like viruses and proteins also have potential for use as molecular diagnostic tools. Information obtained from nanotechnology based diagnostics can be stored and manipulated using bioinformatics software. More advanced nanotechnology based diagnostic procedures for the acquisition of even greater proteomic and genomic knowledge can then be developed along with better ways to fight various diseases. Nanotechnology also has numerous applications besides those related to biotechnology and medicine. In this article, we will discuss and analyze many novel nanotechnology based diagnostic techniques at our disposal today. (author)

  1. Nanotechnology based diagnostics for neurological disorders

    Energy Technology Data Exchange (ETDEWEB)

    Kurek, Nicholas S.; Chandra, Sathees B., E-mail: schandra@roosevelt.edu [Department of Biological, Chemical and Physical Sciences, Roosevelt University, Chicago, IL (United States)

    2012-07-01

    Nanotechnology involves probing and manipulating matter at the molecular level. Nanotechnology based molecular diagnostics have the potential to alleviate the suffering caused by many diseases, including neurological disorders, due to the unique properties of nanomaterials. Most neurological illnesses are multifactorial conditions and many of these are also classified as neurobehavioral disorders. Alzheimer's disease, Parkinson's disease, Huntington disease, cerebral ischemia, epilepsy, schizophrenia and autism spectrum disorders like Rett syndrome are some examples of neurological disorders that could be better treated, diagnosed, prevented and possibly cured using nanotechnology. In order to improve the quality of life for disease afflicted people, a wide range of nanomaterials that include gold and silica nanoparticles, quantum dots and DNA along with countless other forms of nanotechnology have been investigated regarding their usefulness in advancing molecular diagnostics. Other small scaled materials like viruses and proteins also have potential for use as molecular diagnostic tools. Information obtained from nanotechnology based diagnostics can be stored and manipulated using bioinformatics software. More advanced nanotechnology based diagnostic procedures for the acquisition of even greater proteomic and genomic knowledge can then be developed along with better ways to fight various diseases. Nanotechnology also has numerous applications besides those related to biotechnology and medicine. In this article, we will discuss and analyze many novel nanotechnology based diagnostic techniques at our disposal today. (author)

  2. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

    2013-12-01

    The latest Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with newly available global observations. The traditional approach to climate model evaluation, which compares a single parameter at a time, identifies symptomatic model biases and errors but fails to diagnose the model problems. The model diagnosis process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. To address these challenges, we are developing a parallel, distributed web-service system that enables the physics-based multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks (i.e., Flask, Gunicorn, and Tornado). The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation and (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, and (4) the calculation of difference between two variables. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use

  3. Field-based systems and advanced diagnostics

    International Nuclear Information System (INIS)

    Detection and characterization of anomalies in an industrial plant provide improved plant availability and plant efficiency thus yielding increased economic efficiency. Traditionally, detection of process anomalies is done at a high-level control system through various signal validation methods. These signal validation techniques rely on data from transmitters, which measure related process variables. Correlating these signals and deducing anomalies often is a very time consuming and a difficult task. Delays in detecting these anomalies can be costly during plant operation. Conventional centralized approaches also suffer from their dependence on detailed mathematical models of the processes. Smart field devices have the advantage of providing the necessary information directly to the control system as anomalies develop during operation of the processes enabling operators to take necessary steps to either prevent an unnecessary shut down before the problem becomes serious or schedule maintenance on the problematic loop. Fisher-Rosemount's PlantWebTM architecture addresses 'Enhanced Measurement, Advanced Diagnostics and Control in the Field'. PlantWebTM builds open process management systems by networking intelligent field devices, scalable control and systems platforms, and integrated modular software. A description of PlantWebTM and how it improves various process conditions and reduces operating cost of a plant as well as a high level description of 'Enhanced Measurement, Advanced Diagnostics and Control in the Field', will be provided in this paper. PlantWebTM is the trademark for Fisher-Rosemount's new field-based architecture that uses emerging technologies to utilize the power of intelligent field devices and deliver critical process and equipment information to improve plant performance. (author)

  4. Diagnostic and assessment models patterns

    Directory of Open Access Journals (Sweden)

    Maria Cristina Núñez Martínez

    2009-12-01

    Full Text Available A bibliographic review was carried out about the professional competence assessment of human resources in the Health System and the main characteristics of different models that contribute to their improvement, establishing direct links with the present context of National Health System in Cuba. We include trends and common practices related with assessment models, highlighting those aspects associated with professional competence assessment and its inclusion in the dynamic of a strategy to increase the quality of human resources in Health Services. It has been proved that the appropriate assessment of competences among these professionals assures, through its results, to make valuable decisions on the need of knowledge associated with skills and attitudes that should be present in their daily professional practice.

  5. Methodology, models and algorithms in thermographic diagnostics

    CERN Document Server

    Živčák, Jozef; Madarász, Ladislav; Rudas, Imre J

    2013-01-01

    This book presents  the methodology and techniques of  thermographic applications with focus primarily on medical thermography implemented for parametrizing the diagnostics of the human body. The first part of the book describes the basics of infrared thermography, the possibilities of thermographic diagnostics and the physical nature of thermography. The second half includes tools of intelligent engineering applied for the solving of selected applications and projects. Thermographic diagnostics was applied to problematics of paraplegia and tetraplegia and carpal tunnel syndrome (CTS). The results of the research activities were created with the cooperation of the four projects within the Ministry of Education, Science, Research and Sport of the Slovak Republic entitled Digital control of complex systems with two degrees of freedom, Progressive methods of education in the area of control and modeling of complex object oriented systems on aircraft turbocompressor engines, Center for research of control of te...

  6. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

    2014-12-01

    We have developed a cloud-enabled web-service system that empowers physics-based, multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks. The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the observational datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation, (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs, and (3) ECMWF reanalysis outputs for several environmental variables in order to supplement observational datasets. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, (4) the calculation of difference between two variables, and (5) the conditional sampling of one physical variable with respect to another variable. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use, avoiding the hassle of local software installation and environment incompatibility. CMDA will be used as an educational tool for the summer school organized by JPL's Center for Climate Science in 2014. In order to support 30+ simultaneous users during the school, we have deployed CMDA to the Amazon cloud environment. The cloud-enabled CMDA will provide each student with a virtual machine while the user interaction with the system will remain the same

  7. Surface CUrrents from a Diagnostic model (SCUD): Pacific

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The SCUD data product is an estimate of upper-ocean velocities computed from a diagnostic model (Surface CUrrents from a Diagnostic model). This model makes daily...

  8. Modelling of JET diagnostics using Bayesian Graphical Models

    Energy Technology Data Exchange (ETDEWEB)

    Svensson, J. [IPP Greifswald, Greifswald (Germany); Ford, O. [Imperial College, London (United Kingdom); McDonald, D.; Hole, M.; Nessi, G. von; Meakins, A.; Brix, M.; Thomsen, H.; Werner, A.; Sirinelli, A.

    2011-07-01

    The mapping between physics parameters (such as densities, currents, flows, temperatures etc) defining the plasma 'state' under a given model and the raw observations of each plasma diagnostic will 1) depend on the particular physics model used, 2) is inherently probabilistic, from uncertainties on both observations and instrumental aspects of the mapping, such as calibrations, instrument functions etc. A flexible and principled way of modelling such interconnected probabilistic systems is through so called Bayesian graphical models. Being an amalgam between graph theory and probability theory, Bayesian graphical models can simulate the complex interconnections between physics models and diagnostic observations from multiple heterogeneous diagnostic systems, making it relatively easy to optimally combine the observations from multiple diagnostics for joint inference on parameters of the underlying physics model, which in itself can be represented as part of the graph. At JET about 10 diagnostic systems have to date been modelled in this way, and has lead to a number of new results, including: the reconstruction of the flux surface topology and q-profiles without any specific equilibrium assumption, using information from a number of different diagnostic systems; profile inversions taking into account the uncertainties in the flux surface positions and a substantial increase in accuracy of JET electron density and temperature profiles, including improved pedestal resolution, through the joint analysis of three diagnostic systems. It is believed that the Bayesian graph approach could potentially be utilised for very large sets of diagnostics, providing a generic data analysis framework for nuclear fusion experiments, that would be able to optimally utilize the information from multiple diagnostics simultaneously, and where the explicit graph representation of the connections to underlying physics models could be used for sophisticated model testing. This

  9. Bayesian Diagnostic Network: A Powerful Model for Representation and Reasoning of Engineering Diagnostic Knowledge

    Institute of Scientific and Technical Information of China (English)

    HU Zhao-yong

    2005-01-01

    Engineering diagnosis is essential to the operation of industrial equipment. The key to successful diagnosis is correct knowledge representation and reasoning. The Bayesian network is a powerful tool for it. This paper utilizes the Bayesian network to represent and reason diagnostic knowledge, named Bayesian diagnostic network. It provides a three-layer topologic structure based on operating conditions, possible faults and corresponding symptoms. The paper also discusses an approximate stochastic sampling algorithm. Then a practical Bayesian network for gas turbine diagnosis is constructed on a platform developed under a Visual C++ environment. It shows that the Bayesian network is a powerful model for representation and reasoning of diagnostic knowledge. The three-layer structure and the approximate algorithm are effective also.

  10. Hierarchical diagnostic classification models morphing into unidimensional 'diagnostic' classification models-a commentary.

    Science.gov (United States)

    von Davier, Matthias; Haberman, Shelby J

    2014-04-01

    This commentary addresses the modeling and final analytical path taken, as well as the terminology used, in the paper "Hierarchical diagnostic classification models: a family of models for estimating and testing attribute hierarchies" by Templin and Bradshaw (Psychometrika, doi: 10.1007/s11336-013-9362-0, 2013). It raises several issues concerning use of cognitive diagnostic models that either assume attribute hierarchies or assume a certain form of attribute interactions. The issues raised are illustrated with examples, and references are provided for further examination. PMID:24478022

  11. Droplet Microfluidics for Chip-Based Diagnostics

    Directory of Open Access Journals (Sweden)

    Karan V. I. S. Kaler

    2014-12-01

    Full Text Available Droplet microfluidics (DMF is a fluidic handling technology that enables precision control over dispensing and subsequent manipulation of droplets in the volume range of microliters to picoliters, on a micro-fabricated device. There are several different droplet actuation methods, all of which can generate external stimuli, to either actively or passively control the shape and positioning of fluidic droplets over patterned substrates. In this review article, we focus on the operation and utility of electro-actuation-based DMF devices, which utilize one or more micro-/nano-patterned substrates to facilitate electric field-based handling of chemical and/or biological samples. The underlying theory of DMF actuations, device fabrication methods and integration of optical and opto-electronic detectors is discussed in this review. Example applications of such electro-actuation-based DMF devices have also been included, illustrating the various actuation methods and their utility in conducting chip-based laboratory and clinical diagnostic assays.

  12. Control and Diagnostic Model of Brushless Dc Motor

    Science.gov (United States)

    Abramov, Ivan V.; Nikitin, Yury R.; Abramov, Andrei I.; Sosnovich, Ella V.; Božek, Pavol

    2014-09-01

    A simulation model of brushless DC motor (BLDC) control and diagnostics is considered. The model has been developed using a freeware complex "Modeling in technical devices". Faults and diagnostic parameters of BLDC are analyzed. A logicallinguistic diagnostic model of BLDC has been developed on basis of fuzzy logic. The calculated rules determine dependence of technical condition on diagnostic parameters, their trends and utilized lifetime of BLDC. Experimental results of BLDC technical condition diagnostics are discussed. It is shown that in the course of BLDC degradation the motor condition change depends on diagnostic parameter values

  13. A general diagnostic model applied to language testing data.

    Science.gov (United States)

    von Davier, Matthias

    2008-11-01

    Probabilistic models with one or more latent variables are designed to report on a corresponding number of skills or cognitive attributes. Multidimensional skill profiles offer additional information beyond what a single test score can provide, if the reported skills can be identified and distinguished reliably. Many recent approaches to skill profile models are limited to dichotomous data and have made use of computationally intensive estimation methods such as Markov chain Monte Carlo, since standard maximum likelihood (ML) estimation techniques were deemed infeasible. This paper presents a general diagnostic model (GDM) that can be estimated with standard ML techniques and applies to polytomous response variables as well as to skills with two or more proficiency levels. The paper uses one member of a larger class of diagnostic models, a compensatory diagnostic model for dichotomous and partial credit data. Many well-known models, such as univariate and multivariate versions of the Rasch model and the two-parameter logistic item response theory model, the generalized partial credit model, as well as a variety of skill profile models, are special cases of this GDM. In addition to an introduction to this model, the paper presents a parameter recovery study using simulated data and an application to real data from the field test for TOEFL Internet-based testing. PMID:17535481

  14. Mixed Portmanteau Test for Diagnostic Checking of Time Series Models

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2014-01-01

    Full Text Available Model criticism is an important stage of model building and thus goodness of fit tests provides a set of tools for diagnostic checking of the fitted model. Several tests are suggested in literature for diagnostic checking. These tests use autocorrelation or partial autocorrelation in the residuals to criticize the adequacy of fitted model. The main idea underlying these portmanteau tests is to identify if there is any dependence structure which is yet unexplained by the fitted model. In this paper, we suggest mixed portmanteau tests based on autocorrelation and partial autocorrelation functions of the residuals. We derived the asymptotic distribution of the mixture test and studied its size and power using Monte Carlo simulations.

  15. Web4diagnostics - experience with web-based diagnostic systems in power plants

    International Nuclear Information System (INIS)

    At SMORN 8, a new web-based diagnostic system - web4diagnostics - was presented (Kunze, 2002). During the last two years, this system became the standard diagnostic system infrastructure for internal use in Siemens Power Generation, which integrates a large data archive of measured data and capabilities for data analysis and evaluation. Besides this internal use, today some 15 power plants worldwide use web4diagnostics in their companies communication network. Essential features are: monitoring and diagnostic information are provided in HTML page format; diagnosis can be performed on any suitable machine in the computer network; a 'central diagnostic laboratory' can be configured as a virtual facility using the existing IT infrastructure; analysis results can be accessed from any computer in the information network, only a web browser is required. The system employs well-known standard diagnostic modules and also owns tools such as operational based limit surveillance, automatic report generation and automatic information in case of deviations. (author)

  16. Diagnostic reliability of MMPI-2 computer-based test interpretations.

    Science.gov (United States)

    Pant, Hina; McCabe, Brian J; Deskovitz, Mark A; Weed, Nathan C; Williams, John E

    2014-09-01

    Reflecting the common use of the MMPI-2 to provide diagnostic considerations, computer-based test interpretations (CBTIs) also typically offer diagnostic suggestions. However, these diagnostic suggestions can sometimes be shown to vary widely across different CBTI programs even for identical MMPI-2 profiles. The present study evaluated the diagnostic reliability of 6 commercially available CBTIs using a 20-item Q-sort task developed for this study. Four raters each sorted diagnostic classifications based on these 6 CBTI reports for 20 MMPI-2 profiles. Two questions were addressed. First, do users of CBTIs understand the diagnostic information contained within the reports similarly? Overall, diagnostic sorts of the CBTIs showed moderate inter-interpreter diagnostic reliability (mean r = .56), with sorts for the 1/2/3 profile showing the highest inter-interpreter diagnostic reliability (mean r = .67). Second, do different CBTIs programs vary with respect to diagnostic suggestions? It was found that diagnostic sorts of the CBTIs had a mean inter-CBTI diagnostic reliability of r = .56, indicating moderate but not strong agreement across CBTIs in terms of diagnostic suggestions. The strongest inter-CBTI diagnostic agreement was found for sorts of the 1/2/3 profile CBTIs (mean r = .71). Limitations and future directions are discussed. PMID:24749753

  17. Understanding advances in the simulation of intraseasonal variability in the ECMWF model. Part II: the application of process-based diagnostics

    OpenAIRE

    L. C. Hirons; Inness, P.; F. Vitart; Bechtold , P.

    2013-01-01

    In Part I of this study it was shown that moving from a moisture-convergent- to a relative-humidity-dependent organized entrainment rate in the formulation for deep convection was responsible for significant advances in the simulation of the Madden – Julian Oscillation (MJO) in the ECMWF model. However, the application of traditional MJO diagnostics were not adequate to understand why changing the control on convection had such a pronounced impact on the representation of the ...

  18. CopulaDTA: An R Package for Copula Based Bivariate Beta-Binomial Models for Diagnostic Test Accuracy Studies in a Bayesian Framework

    OpenAIRE

    Nyaga, Victoria N; Arbyn, Marc; Aerts, Marc

    2016-01-01

    The current statistical procedures implemented in statistical software packages for pooling of diagnostic test accuracy data include hSROC regression and the bivariate random-effects meta-analysis model (BRMA). However, these models do not report the overall mean but rather the mean for a central study with random-effect equal to zero and have difficulties estimating the correlation between sensitivity and specificity when the number of studies in the meta-analysis is small and/or when the be...

  19. Atomic Models for Motional Stark Effects Diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Gu, M F; Holcomb, C; Jayakuma, J; Allen, S; Pablant, N A; Burrell, K

    2007-07-26

    We present detailed atomic physics models for motional Stark effects (MSE) diagnostic on magnetic fusion devices. Excitation and ionization cross sections of the hydrogen or deuterium beam traveling in a magnetic field in collisions with electrons, ions, and neutral gas are calculated in the first Born approximation. The density matrices and polarization states of individual Stark-Zeeman components of the Balmer {alpha} line are obtained for both beam into plasma and beam into gas models. A detailed comparison of the model calculations and the MSE polarimetry and spectral intensity measurements obtained at the DIII-D tokamak is carried out. Although our beam into gas models provide a qualitative explanation for the larger {pi}/{sigma} intensity ratios and represent significant improvements over the statistical population models, empirical adjustment factors ranging from 1.0-2.0 must still be applied to individual line intensities to bring the calculations into full agreement with the observations. Nevertheless, we demonstrate that beam into gas measurements can be used successfully as calibration procedures for measuring the magnetic pitch angle through {pi}/{sigma} intensity ratios. The analyses of the filter-scan polarization spectra from the DIII-D MSE polarimetry system indicate unknown channel and time dependent light contaminations in the beam into gas measurements. Such contaminations may be the main reason for the failure of beam into gas calibration on MSE polarimetry systems.

  20. Model-based comparison of maternal and foetal organ doses from 99mTc pertechnetate, DMSA, DTPA, HDP, MAA and MAG3 diagnostic intakes during pregnancy

    International Nuclear Information System (INIS)

    Organ residence times were calculated for diagnostic intakes of 99mTc pertechnetate, 2,3-dimercaptosuccinic acid (DMSA), diethylene triamine penta-acetic acid (DTPA), hydroxymethylene diphosphonate (HDP), macroaggregated albumin (MAA) and mercapto-acetyltriglycine (MAG3) during the 1st and 3rd stages of pregnancy and used with the MIRDOSE3 pregnant female phantoms for generation of dose estimates. At stage 3 individual foetal organ doses were estimated via a surrogate phantom based on that for the new-born but with mean dose/cumulated activity (S) values scaled for compatibility with foetal whole body S. Stage 1 or 3 whole foetus doses ranged from 5.2 to 0.77 μGy MBq-1 respectively, analogous to current ICRP estimates for these agents using similar in vivo biodistribution model databases. Most stage 3 maternal and foetal organ doses were similar within a factor of 3, being higher in the foetus than the mother with pertechnetate, DTPA and MAG3, and lower with DMSA, HDP and MAA. Doses were more uniformly distributed among foetal organs than in the mother. Placental transfer was greatest with pertechnetate, where dose to the stage 3 foetal thyroid was 60-140 μGy MBq-1. With each agent there was more placental transfer in stage 3 than in stage 1, but doses to stage 1 whole foetus were always higher, with the contribution from the mother dominant. For DMSA, HDP and MAG3 the maternal contribution to total foetal body dose exceeded 93% for both stages. (orig.)

  1. Molecular diagnostics: future probe-based strategies.

    Science.gov (United States)

    Marsh, Peter; Cardy, Donald L N

    2004-01-01

    Nucleic acid amplification technologies (NAATs) represent powerful tools in clinical microbiology, particularly in areas where traditional culture-based methods alone prove insufficient. A notable advantage is in reducing the time from taking samples to reporting results. This, and the specificity and sensitivity imparted by NAATs, can help to improve patient care. Both thermal and isothermal NAATs have been adapted to aid diagnosis in clinical laboratories. Current molecular diagnostic assays are generally high-tech, and are expensive to buy and perform. Easy-to-use NAATs are beginning to appear, not only facilitating acceptable throughput in clinical laboratories, but also allowing tests to move out of the laboratory, closer to the point of care. Demand for simpler, miniaturized equipment and assays, and the trend toward personalized medicine, is leading towards the development of fully integrated automation and home-use kits. The integration of diverse disciplines, such as genomics, molecular biology, microelectromechanical systems, microfluidics, microfabrication, and organic chemistry, is behind the emerging DNA microarray technology. Development of DNA microchips allows the simultaneous detection of potentially thousands of target sequences, not only favoring high throughput, but also the potential for genotyping patient subsets with respect to their response to particular drug types (pharmakogenomics). It is envisaged that the future of probe-based technologies will see the development of fully integrated assays and devices suitable for nonskilled users. PMID:15148419

  2. Advances in Optical Fiber-Based Faraday Rotation Diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    White, A D; McHale, G B; Goerz, D A

    2009-07-27

    In the past two years, we have used optical fiber-based Faraday Rotation Diagnostics (FRDs) to measure pulsed currents on several dozen capacitively driven and explosively driven pulsed power experiments. We have made simplifications to the necessary hardware for quadrature-encoded polarization analysis, including development of an all-fiber analysis scheme. We have developed a numerical model that is useful for predicting and quantifying deviations from the ideal diagnostic response. We have developed a method of analyzing quadrature-encoded FRD data that is simple to perform and offers numerous advantages over several existing methods. When comparison has been possible, we have seen good agreement with our FRDs and other current sensors.

  3. Advances in Optical Fiber-Based Faraday Rotation Diagnostics

    International Nuclear Information System (INIS)

    In the past two years, we have used optical fiber-based Faraday Rotation Diagnostics (FRDs) to measure pulsed currents on several dozen capacitively driven and explosively driven pulsed power experiments. We have made simplifications to the necessary hardware for quadrature-encoded polarization analysis, including development of an all-fiber analysis scheme. We have developed a numerical model that is useful for predicting and quantifying deviations from the ideal diagnostic response. We have developed a method of analyzing quadrature-encoded FRD data that is simple to perform and offers numerous advantages over several existing methods. When comparison has been possible, we have seen good agreement with our FRDs and other current sensors

  4. Physical Modeling for Anomaly Diagnostics and Prognostics Project

    Data.gov (United States)

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

  5. Introduction to DNA-Based Genetic Diagnostics

    OpenAIRE

    Glickman, Richard M.; Phillips, M. Ann; Glickman, Barry W.

    1988-01-01

    Molecular biology and recombinant DNA technology are beginning to have an effect on the medical health care field, particularly in the area of clinical genetics. Dramatic improvements in the prerequisite technology are in the process of being transferred from the research lab to routine clinical laboratories. The general practitioner, along with his genetic diagnostic colleagues, can soon expect to have access to accurate and reliable diagnostic assays for a wide variety of genetic disorders....

  6. Diagnostic reasoning using qualitative causal models

    International Nuclear Information System (INIS)

    The application of expert systems to reasoning problems involving real-time data from plant measurements has been a topic of much research, but few practical systems have been deployed. One obstacle to wider use of expert systems in applications involving real-time data is the lack of adequate knowledge representation methodologies for dynamic processes. Knowledge bases composed mainly of rules have disadvantages when applied to dynamic processes and real-time data. This paper describes a methodology for the development of qualitative causal models that can be used as knowledge bases for reasoning about process dynamic behavior. These models provide a systematic method for knowledge base construction, considerably reducing the engineering effort required. They also offer much better opportunities for verification and validation of the knowledge base, thus increasing the possibility of the application of expert systems to reasoning about mission critical systems. Starting with the Signed Directed Graph (SDG) method that has been successfully applied to describe the behavior of diverse dynamic processes, the paper shows how certain non-physical behaviors that result from abstraction may be eliminated by applying causal constraint to the models. The resulting Extended Signed Directed Graph (ESDG) may then be compiled to produce a model for use in process fault diagnosis. This model based reasoning methodology is used in the MOBIAS system being developed by Duke Power Company under EPRI sponsorship. 15 refs., 4 figs

  7. The SUCCESS model for laboratory performance and execution of rapid molecular diagnostics in patients with sepsis

    OpenAIRE

    Dekmezian, Mhair; Beal, Stacy G.; Damashek, Mary Jane; Benavides, Raul; Dhiman, Neelam

    2015-01-01

    Successful performance and execution of rapid diagnostics in a clinical laboratory hinges heavily on careful validation, accurate and timely communication of results, and real-time quality monitoring. Laboratories must develop strategies to integrate diagnostics with stewardship and evidence-based clinical practice guidelines. We present a collaborative SUCCESS model for execution and monitoring of rapid sepsis diagnostics to facilitate timely treatment. Six months after execution of the Veri...

  8. Diagnostic tests based on human basophils

    DEFF Research Database (Denmark)

    Kleine-Tebbe, Jörg; Erdmann, Stephan; Knol, Edward F;

    2006-01-01

    -maximal responses, termed 'intrinsic sensitivity'. These variables give rise to shifts in the dose-response curves which, in a diagnostic setting where only a single antigen concentration is employed, may produce false-negative data. Thus, in order to meaningfully utilize the current basophil activation tests for...

  9. Autofluorescence based diagnostic techniques for oral cancer

    OpenAIRE

    Balasubramaniam, A. Murali; Sriraman, Rajkumari; Sindhuja, P; Mohideen, Khadijah; Parameswar, R. Arjun; Muhamed Haris, K. T.

    2015-01-01

    Oral cancer is one of the most common cancers worldwide. Despite of various advancements in the treatment modalities, oral cancer mortalities are more, particularly in developing countries like India. This is mainly due to the delay in diagnosis of oral cancer. Delay in diagnosis greatly reduces prognosis of the treatment and also cause increased morbidity and mortality rates. Early diagnosis plays a key role in effective management of oral cancer. A rapid diagnostic technique can greatly aid...

  10. Data mining approach to model the diagnostic service management.

    Science.gov (United States)

    Lee, Sun-Mi; Lee, Ae-Kyung; Park, Il-Su

    2006-01-01

    Korea has National Health Insurance Program operated by the government-owned National Health Insurance Corporation, and diagnostic services are provided every two year for the insured and their family members. Developing a customer relationship management (CRM) system using data mining technology would be useful to improve the performance of diagnostic service programs. Under these circumstances, this study developed a model for diagnostic service management taking into account the characteristics of subjects using a data mining approach. This study could be further used to develop an automated CRM system contributing to the increase in the rate of receiving diagnostic services. PMID:17102454

  11. Development of a Model-tracing Intelligent Tutor in Diagnostic Pathology

    OpenAIRE

    Crowley, Rebecca S; Monaco, Valerie

    2001-01-01

    We report on the design and development of an intelligent tutoring system in diagnostic pathology. Based on a cognitive model of skill in this domain, the system provides individualized instruction to students. An underlying production-rule system models diagnostic skills as a set of production-rules and domain knowledge as a set of working-memory elements. The model-tracing aspect of the system guides the student to correctly search a slide, identify relevant evidence, and formulate and test...

  12. Google glass based immunochromatographic diagnostic test analysis

    Science.gov (United States)

    Feng, Steve; Caire, Romain; Cortazar, Bingen; Turan, Mehmet; Wong, Andrew; Ozcan, Aydogan

    2015-03-01

    Integration of optical imagers and sensors into recently emerging wearable computational devices allows for simpler and more intuitive methods of integrating biomedical imaging and medical diagnostics tasks into existing infrastructures. Here we demonstrate the ability of one such device, the Google Glass, to perform qualitative and quantitative analysis of immunochromatographic rapid diagnostic tests (RDTs) using a voice-commandable hands-free software-only interface, as an alternative to larger and more bulky desktop or handheld units. Using the built-in camera of Glass to image one or more RDTs (labeled with Quick Response (QR) codes), our Glass software application uploads the captured image and related information (e.g., user name, GPS, etc.) to our servers for remote analysis and storage. After digital analysis of the RDT images, the results are transmitted back to the originating Glass device, and made available through a website in geospatial and tabular representations. We tested this system on qualitative human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) RDTs. For qualitative HIV tests, we demonstrate successful detection and labeling (i.e., yes/no decisions) for up to 6-fold dilution of HIV samples. For quantitative measurements, we activated and imaged PSA concentrations ranging from 0 to 200 ng/mL and generated calibration curves relating the RDT line intensity values to PSA concentration. By providing automated digitization of both qualitative and quantitative test results, this wearable colorimetric diagnostic test reader platform on Google Glass can reduce operator errors caused by poor training, provide real-time spatiotemporal mapping of test results, and assist with remote monitoring of various biomedical conditions.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-09-01

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

  14. Performance-analysis-based gas turbine diagnostics: a review.

    OpenAIRE

    Li, Y.G.

    2002-01-01

    Gas turbine diagnostics has a history almost as long as gas turbine development itself. Early engine fault diagnosis was carried out based on manufacturer information supplied in a technical manual combined with maintenance experience. In the late 1960’s when Urban introduced Gas Path Analysis, gas turbine diagnostics made a big breakthrough. Since then different methods have been developed and used in both aero and industrial applications. Until now a substantial number of papers have been p...

  15. Diagnostic checking for conditional heteroscedasticity models

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    We suggest the score type tests for goodness-of-fit of conditional heteroscedasticity models in both univariate and multivariate time series.The tests can detect the alternatives converging to the null at a parametric rate.Weight functions are involved in the construction of the tests,which provides us with the flexibility to choose scores,especially under directional alternatives,for enhancing power performance.Furthermore,when the alternatives are not directional,we construct asymptotically distribution-free maximin tests for a large class of alternatives.A possibility to construct score-based omnibus tests is discussed when the alternative is saturated.The power performance is also investigated.A simulation study is carried out and a real data is analyzed.

  16. Research support for plasma diagnostics on Elmo Bumpy Torus - development of a multichannel Hall-probe based diamagnetic diagnostic instrument and observation and modeling of EBT electron rings. Final report, October 1, 1982-September 30, 1983

    International Nuclear Information System (INIS)

    Use of multiple Hall effect probes is a cost effective way to observe diamagnetic fields from the hot electron rings in the Elmo Bumpy Torus device at several locations simultaneously. A special diagnostic instrument has been developed having six Hall probe channels with the sensitivity and stability needed for the diamagnetic measurements. The instrument uses an AC carrier system with isolation transformers located remotely from the instrument and near the probe locations. Details of instrument design as well as operating instructions for it are included in this report

  17. Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle.

    Science.gov (United States)

    Linder, Ewert; Varjo, Sami; Thors, Cecilia

    2016-01-01

    Imaging at high resolution and subsequent image analysis with modified mobile phones have the potential to solve problems related to microscopy-based diagnostics of parasitic infections in many endemic regions. Diagnostics using the computing power of "smartphones" is not restricted by limited expertise or limitations set by visual perception of a microscopist. Thus diagnostics currently almost exclusively dependent on recognition of morphological features of pathogenic organisms could be based on additional properties, such as motility characteristics recognizable by computer vision. Of special interest are infectious larval stages and "micro swimmers" of e.g., the schistosome life cycle, which infect the intermediate and definitive hosts, respectively. The ciliated miracidium, emerges from the excreted egg upon its contact with water. This means that for diagnostics, recognition of a swimming miracidium is equivalent to recognition of an egg. The motility pattern of miracidia could be defined by computer vision and used as a diagnostic criterion. To develop motility pattern-based diagnostics of schistosomiasis using simple imaging devices, we analyzed Paramecium as a model for the schistosome miracidium. As a model for invasive nematodes, such as strongyloids and filaria, we examined a different type of motility in the apathogenic nematode Turbatrix, the "vinegar eel." The results of motion time and frequency analysis suggest that target motility may be expressed as specific spectrograms serving as "diagnostic fingerprints." PMID:27322330

  18. A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

    Science.gov (United States)

    Hong, Na; Jiang, Guoqian; Pathak, Jyotishiman; Chute, Christopher G

    2015-01-01

    The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning. PMID:26262392

  19. Applying the transferable belief model to diagnostic problems

    International Nuclear Information System (INIS)

    Short presentation of the most relevant elements of the transferable belief model and its use for two problems related to the diagnostic process. These examples are used to enhance the advantages of the transferable belief model over its contender, the bayesian model

  20. Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

    Directory of Open Access Journals (Sweden)

    W. Wang

    2015-03-01

    Full Text Available We perform a land surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP varies between 6 modern stand-alone land surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic. We also examine the variability in simulated permafrost area and distribution introduced by 5 different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes. There is good agreement (99–135 x 104 km2 between the two diagnostic methods based on air temperature which are also consistent with the best current observation-based estimate of actual permafrost area (101 x 104 km2. However the uncertainty (1–128 x 104 km2 using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index, while permafrost distribution using air temperature based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification and snow cover. Models are particularly poor at simulating permafrost distribution using definition that soil temperature remains at or below 0°C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in permafrost distribution can be made for the Tibetan

  1. Experimental data base of Tokamak KTM physical diagnostics

    International Nuclear Information System (INIS)

    The process of software creation of experimental data storage of Tokamak KTM physical diagnostics based on analysis of storage methods of operating Tokamaks data is considered. Task of specific kinds of information storage is solved; experimental data base that is thr part of system providing information analysis performance in the post-start period is developed.(author)

  2. Advances in nucleic acid-based diagnostics of bacterial infections

    DEFF Research Database (Denmark)

    Barken, Kim Bundvig; Haagensen, Janus Anders Juul; Tolker-Nielsen, Tim

    2007-01-01

    Methods for rapid detection of infectious bacteria and antimicrobial-resistant pathogens have evolved significantly over the last decade. Many of the new procedures are nucleic acid-based and replace conventional diagnostic methods like culturing which is time consuming especially with fastidious...... of these pathogens is important to isolate patients and prevent further spreading of the diseases. Newly developed diagnostic procedures are superior with respect to turnaround time, sensitivity and specificity. Methods like multiplex real time PCR and different array-based technologies offer the possibility...

  3. Status of the DNB based ITER CXRS and BES diagnostic

    International Nuclear Information System (INIS)

    A status report is given on recent joint activities on the ITER CXRS and BES diagnostic package. Expected measurement performances are reviewed as well as comprehensive discussions are led on an integral approach to the implementation of Core and Edge CXRS observation periscopes. The 'first mirror' location, its operational temperature, maintenance issues, and optimization of optical imaging are addressed. In parallel to more technical aspects, particular attention has also been given to the development of common evaluation and modeling tools. One part of this work is linked to the modeling of spectra for existing fusion devices and their CXRS diagnostics and extrapolation to the ITER environment. The purpose of this effort is to provide tools for the optimization of spectroscopic instrumentation, and moreover, the specifications of a suitable diagnostic beam

  4. Comparison of the diagnostic accuracy of commercial NS1-based diagnostic tests for early dengue infection

    OpenAIRE

    Villar Luis A; Bonelo Anilza; Ramirez Meleny; Osorio Lyda; Parra Beatriz

    2010-01-01

    Abstract Background We compared the diagnostic accuracy and reproducibility of commercially available NS1-based dengue tests and explored factors influencing their sensitivities. Methods Paired analysis of 310 samples previously characterized as positive (n = 218) and negative (n = 92) for viral isolation and/or RT-PCR and/or IgM seroconversion. Masked samples were tested by two observers with Platelia™ Dengue NS1 Ag, second generation Pan-E™ Dengue Early ELISA, SD Dengue NS1 Ag ELISA, Dengue...

  5. DIVA and DIAPO: two diagnostic knowledge based systems used for French nuclear power plants

    International Nuclear Information System (INIS)

    In order to improve monitoring and diagnosis capabilities in nuclear power plants, Electricite de France (EDF) has designed an integrated monitoring and diagnosis assistance system: PSAD-Poste de Surveillance et d'Aide au Diagnostic. The development of such a sophisticated monitoring and data processing systems has emphasized the need for the addition of analysis and diagnosis assistance capabilities. Therefore, diagnostic knowledge based systems have been added to the functions monitored in PSAD: DIVA for turbine generators, and DIAPO for reactor coolant pumps. These systems were designed from a representation of the diagnostic reasoning process of experts and of the supporting knowledge. Diagnosis in both systems relies on an abduction reasoning process applied to component fault models and observations derived from their actual behavior, as provided by the monitoring functions. The basic theoretical elements of this diagnostic model are summarized in a first part. In a second part, DIVA and DIAPO specific elements are described

  6. Extracting Synoptic-Scale Diagnostic Information from Mesoscale Models: The Eta Model, Gravity Waves, and Quasigeostrophic Diagnostics.

    Science.gov (United States)

    Barnes, Stanley L.; Caracena, Fernando; Marroquin, Adrian

    1996-03-01

    Fine-mesh models, such as the eta model, are producing increasingly detailed predictions about mesoscale atmospheric motions. Mesoscale systems typically produce stronger vertical motions than do synoptic-scale storms, making it more difficult for forecasters to assess the strength of the latter's dynamics when the signals are overwhelmed by mesoscale processes. This paper describes a method for extracting synoptic-scale information from mesoscale model data. Predicted height fields from the 29-km eta model are investigated to determine the filtering and smoothing requirements necessary to resolve synoptic-scale patterns of vertical motions using quasigeostrophic (QG) diagnostics. The selected late-fall case includes a jet stream that enters the continent over the Pacific Northwest, resulting in orographically induced troughs in the lee of the Cascade Range and Rocky Mountains. Gravity waves are found to emanate from this region in arcs that reach Hudson Bay to the northeast and extend to the Caribbean in the southeast. Individual gravity wave crests (240 km apart) are of sufficient amplitude (5 to 10 m at 500 mb) to dominate the expected synoptic-scale vertical motions by two orders of magnitude. A numerical filter based on a two-dimensional diffraction function is designed, tested, and found to eliminate the influence of the gravity waves effectively. The filtered model data are then able to reveal synoptic-scale vertical motion patterns in all areas except the vicinity of the lee troughs, which still dominate QG forcing near the jet axis.

  7. Towards intelligent diagnostic system employing integration of mathematical and engineering model

    Science.gov (United States)

    Isa, Nor Ashidi Mat

    2015-05-01

    as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.

  8. Towards intelligent diagnostic system employing integration of mathematical and engineering model

    Energy Technology Data Exchange (ETDEWEB)

    Isa, Nor Ashidi Mat [Imaging and Intelligent System Research Team (ISRT), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang (Malaysia)

    2015-05-15

    as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.

  9. Towards intelligent diagnostic system employing integration of mathematical and engineering model

    International Nuclear Information System (INIS)

    as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image

  10. Target Diagnostic Instrument-Based Controls Framework for the National Ignition Facility

    International Nuclear Information System (INIS)

    NIF target diagnostics are being developed to observe and measure the extreme physics of targets irradiated by the 192-beam laser. The response time of target materials can be on the order of 100ps--the time it takes light to travel 3 cm--temperatures more than 100 times hotter than the surface of the sun, and pressures that exceed 109 atmospheres. Optical and x-ray diagnostics were developed and fielded to observe and record the results of the first 4-beam experiments at NIF. Hard and soft x-ray spectra were measured, and time-integrated and gated x-ray images of hydrodynamics experiments were recorded. Optical diagnostics recorded backscatter from the target, and VISAR laser velocimetry measurements were taken of laser-shocked target surfaces. Additional diagnostics are being developed and commissioned to observe and diagnose ignition implosions, including various neutron and activation diagnostics. NIF's diagnostics are being developed at LLNL and with collaborators at other sites. To accommodate the growing number of target diagnostics, an Instrument-Based Controls hardware-software framework has been developed to facilitate development and ease integration into the NIF Integrated Computer Control System (ICCS). Individual WindowsXP PC controllers for each digitizer, power supply and camera (i.e., instruments) execute controls software unique to each instrument model. Each hardware-software controller manages a single instrument, in contrast to the complexity of combining all the controls software needed for a diagnostic into a single controller. Because of this simplification, controllers can be more easily tested on the actual hardware, evaluating all normal and off-normal conditions. Each target diagnostic is then supported by a number of instruments, each with its own hardware-software instrument-based controller. Advantages of the instrument-based control architecture and framework include reusability, testability, and improved reliability of the deployed

  11. Invariance Properties for General Diagnostic Classification Models

    Science.gov (United States)

    Bradshaw, Laine P.; Madison, Matthew J.

    2016-01-01

    In item response theory (IRT), the invariance property states that item parameter estimates are independent of the examinee sample, and examinee ability estimates are independent of the test items. While this property has long been established and understood by the measurement community for IRT models, the same cannot be said for diagnostic…

  12. MRI-based diagnostic imaging of the intratemporal facial nerve

    International Nuclear Information System (INIS)

    Detailed imaging of the five sections of the full intratemporal course of the facial nerve can be achieved by MRI and using thin tomographic section techniques and surface coils. Contrast media are required for tomographic imaging of pathological processes. Established methods are available for diagnostic evaluation of cerebellopontine angle tumors and chronic Bell's palsy, as well as hemifacial spasms. A method still under discussion is MRI for diagnostic evaluation of Bell's palsy in the presence of fractures of the petrous bone, when blood volumes in the petrous bone make evaluation even more difficult. MRI-based diagnostic evaluation of the idiopatic facial paralysis currently is subject to change. Its usual application cannot be recommended for routine evaluation at present. However, a quantitative analysis of contrast medium uptake of the nerve may be an approach to improve the prognostic value of MRI in acute phases of Bell's palsy. (orig./CB)

  13. FDA perspectives on potential microarray-based clinical diagnostics

    Directory of Open Access Journals (Sweden)

    Težak Živana

    2006-01-01

    Full Text Available Abstract The US Food and Drug Administration (FDA encourages the development of new technologies such as microarrays which may improve and streamline assessments of safety and the effectiveness of medical products for the benefit of public health. The FDA anticipates that these new technologies may offer the potential for more effective approaches to medical treatment and disease prevention and management. This paper discusses issues associated with the translation of nucleic acid microarray-based devices from basic research and target discovery to in vitro clinical diagnostic use, which the Office of In Vitro Diagnostic Device Evaluation and Safety in the Center for Devices and Radiological Health foresees will be important for assurance of safety and effectiveness of these types of devices. General technological points, assessment of potential concerns for transitioning microarrays into clinical diagnostic use and approaches for evaluating the performance of these types of devices will be discussed.

  14. Diagnostics and modeling of high pressure streamer induced discharges

    International Nuclear Information System (INIS)

    A great variety of diagnostic has been applied to gain information on basic parameter governing high pressure nonthermal filamentary plasmas (and namely streamer induced filamentary discharges). Apart from electrical diagnostics, gas discharge, in contrast with solid state physics, can greatly benefit from all optical techniques owing to its ''transparent'' state. Emission and absorption spectroscopy, as well as LIF or CARS (talk are given during this meeting on these two techniques) are among such specific possibilities. The figures gained from these diagnostic measurements has generally no meaning by itself. They must be worked out, by means of calibrated former results, and/or by using them as input in high pressure plasma modeling. Mixing experimental and modeling approach is necessary for reaching relevant physical knowledge of the high pressure filamentary discharges processes. It is shown that diffusion, and thermal space and time distribution, must fully be taken into account

  15. A Diagnostic HIV-1 Tropism System Based on Sequence Relatedness

    OpenAIRE

    Edwards, Suzanne; Stucki, Heinz; Bader, Joëlle; Vidal, Vincent; Kaiser, Rolf; Battegay, Manuel; Klimkait, Thomas

    2014-01-01

    Key clinical studies for HIV coreceptor antagonists have used the phenotyping-based Trofile test. Meanwhile various simpler-to-do genotypic tests have become available that are compatible with standard laboratory equipment and Web-based interpretation tools. However, these systems typically analyze only the most prominent virus sequence in a specimen. We present a new diagnostic HIV tropism test not needing DNA sequencing. The system, XTrack, uses physical properties of DNA duplexes after hyb...

  16. Can model observers be developed to reproduce radiologists' diagnostic performances? Our study says not so fast!

    Science.gov (United States)

    Lee, Juhun; Nishikawa, Robert M.; Reiser, Ingrid; Boone, John M.

    2016-03-01

    The purpose of this study was to determine radiologists' diagnostic performances on different image reconstruction algorithms that could be used to optimize image-based model observers. We included a total of 102 pathology proven breast computed tomography (CT) cases (62 malignant). An iterative image reconstruction (IIR) algorithm was used to obtain 24 reconstructions with different image appearance for each image. Using quantitative image feature analysis, three IIRs and one clinical reconstruction of 50 lesions (25 malignant) were selected for a reader study. The reconstructions spanned a range of smooth-low noise to sharp-high noise image appearance. The trained classifiers' AUCs on the above reconstructions ranged from 0.61 (for smooth reconstruction) to 0.95 (for sharp reconstruction). Six experienced MQSA radiologists read 200 cases (50 lesions times 4 reconstructions) and provided the likelihood of malignancy of each lesion. Radiologists' diagnostic performances (AUC) ranged from 0.7 to 0.89. However, there was no agreement among the six radiologists on which image appearance was the best, in terms of radiologists' having the highest diagnostic performances. Specifically, two radiologists indicated sharper image appearance was diagnostically superior, another two radiologists indicated smoother image appearance was diagnostically superior, and another two radiologists indicated all image appearances were diagnostically similar to each other. Due to the poor agreement among radiologists on the diagnostic ranking of images, it may not be possible to develop a model observer for this particular imaging task.

  17. Metabolomics-based discovery of diagnostic biomarkers for onchocerciasis.

    Directory of Open Access Journals (Sweden)

    Judith R Denery

    Full Text Available BACKGROUND: Development of robust, sensitive, and reproducible diagnostic tests for understanding the epidemiology of neglected tropical diseases is an integral aspect of the success of worldwide control and elimination programs. In the treatment of onchocerciasis, clinical diagnostics that can function in an elimination scenario are non-existent and desperately needed. Due to its sensitivity and quantitative reproducibility, liquid chromatography-mass spectrometry (LC-MS based metabolomics is a powerful approach to this problem. METHODOLOGY/PRINCIPAL FINDINGS: Analysis of an African sample set comprised of 73 serum and plasma samples revealed a set of 14 biomarkers that showed excellent discrimination between Onchocerca volvulus-positive and negative individuals by multivariate statistical analysis. Application of this biomarker set to an additional sample set from onchocerciasis endemic areas where long-term ivermectin treatment has been successful revealed that the biomarker set may also distinguish individuals with worms of compromised viability from those with active infection. Machine learning extended the utility of the biomarker set from a complex multivariate analysis to a binary format applicable for adaptation to a field-based diagnostic, validating the use of complex data mining tools applied to infectious disease biomarker discovery and diagnostic development. CONCLUSIONS/SIGNIFICANCE: An LC-MS metabolomics-based diagnostic has the potential to monitor the progression of onchocerciasis in both endemic and non-endemic geographic areas, as well as provide an essential tool to multinational programs in the ongoing fight against this neglected tropical disease. Ultimately this technology can be expanded for the diagnosis of other filarial and/or neglected tropical diseases.

  18. Diagnostic and model dependent uncertainty of simulated Tibetan permafrost area

    Science.gov (United States)

    Wang, A.; Moore, J.C.; Cui, Xingquan; Ji, D.; Li, Q.; Zhang, N.; Wang, C.; Zhang, S.; Lawrence, D.M.; McGuire, A.D.; Zhang, W.; Delire, C.; Koven, C.; Saito, K.; MacDougall, A.; Burke, E.; Decharme, B.

    2016-01-01

     We perform a land-surface model intercomparison to investigate how the simulation of permafrost area on the Tibetan Plateau (TP) varies among six modern stand-alone land-surface models (CLM4.5, CoLM, ISBA, JULES, LPJ-GUESS, UVic). We also examine the variability in simulated permafrost area and distribution introduced by five different methods of diagnosing permafrost (from modeled monthly ground temperature, mean annual ground and air temperatures, air and surface frost indexes). There is good agreement (99 to 135  ×  104 km2) between the two diagnostic methods based on air temperature which are also consistent with the observation-based estimate of actual permafrost area (101  × 104 km2). However the uncertainty (1 to 128  ×  104 km2) using the three methods that require simulation of ground temperature is much greater. Moreover simulated permafrost distribution on the TP is generally only fair to poor for these three methods (diagnosis of permafrost from monthly, and mean annual ground temperature, and surface frost index), while permafrost distribution using air-temperature-based methods is generally good. Model evaluation at field sites highlights specific problems in process simulations likely related to soil texture specification, vegetation types and snow cover. Models are particularly poor at simulating permafrost distribution using the definition that soil temperature remains at or below 0 °C for 24 consecutive months, which requires reliable simulation of both mean annual ground temperatures and seasonal cycle, and hence is relatively demanding. Although models can produce better permafrost maps using mean annual ground temperature and surface frost index, analysis of simulated soil temperature profiles reveals substantial biases. The current generation of land-surface models need to reduce biases in simulated soil temperature profiles before reliable contemporary permafrost maps and predictions of changes in future

  19. Development of electromagnetic induction diagnostics technology for condition based maintenance

    International Nuclear Information System (INIS)

    In ROKKASHO Reprocessing Plant (below, called 'RRP'), we have applied Condition Based Maintenance to rotating equipment with vibration diagnostics technology. However, a few rotating equipment are difficult to diagnose definitely, because have structural problems which exercise vibrational noise to peripheral and be impossible to install vibratory sensor. Electromagnetic induction diagnostics technology which measure magnetic fields to eddy current which is induced to rotary through static magnetic field, diagnose deterioration behavior such as abrasion and crack. As a result, it has possibilities to clear above problems. Therefore, we started our basic researches with this technology for Condition Based Maintenance. In this paper, it introduces basic data about 'Non-seal pump' that have installed in RRP. As a result, this technology is a possibility that be able to detect Condition Based Maintenance. (author)

  20. Synthesize battery degradation modes via a diagnostic and prognostic model

    Science.gov (United States)

    Dubarry, Matthieu; Truchot, Cyril; Liaw, Bor Yann

    2012-12-01

    Batteries are being used in increasingly complicated configurations with very demanding duty schedules. Such usage makes the use of batteries in multi-cell configurations to meet voltage, power, and energy demands in a very stressful manner. Thus, effective management and control of a battery system to allow efficient, reliable, and safe operation becomes vital, and diagnostic and prognostic tools are essential. Yet, developing these tools in practical applications is new to the industry, difficult and challenging. Here we present a novel mechanistic model that can enable battery diagnosis and prognosis. The model can simulate various “what-if” scenarios of battery degradation modes via a synthetic approach based on specific electrode behavior with proper adjustment of the loading ratio and the extent of degradation in and between the two electrodes. This approach is very different from the conventional empirical ones that correlate the cell parameters (such as impedance increases) with degradation in capacity or power fade to predict performance and life. This approach, with mechanistic understanding of battery degradation processes and failure mechanisms, offers unique high-fidelity simulation to address path dependence of the battery degradation.

  1. Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong

    2011-12-01

    Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

  2. Stochastic Modelling for Condition Based Maintenance

    OpenAIRE

    Han, Zehan

    2015-01-01

    This Master's thesis covers almost all aspects of Condition Based Maintenance (CBM). All objectives in Chapter 1 are met. The thesis is mainly comprised of three parts. First part introduces the world of CBM to readers. This part presents data acquisition, data processing and databases, which are the foundation to CBM. Then it highlights models which are divided into physics based models, data-driven models and hybrid models, for diagnostic and prognostic use. Three promising diagnostic and p...

  3. Intelligent DNA-based molecular diagnostics using linked genetic markers

    Energy Technology Data Exchange (ETDEWEB)

    Pathak, D.K.; Perlin, M.W.; Hoffman, E.P.

    1994-12-31

    This paper describes a knowledge-based system for molecular diagnostics, and its application to fully automated diagnosis of X-linked genetic disorders. Molecular diagnostic information is used in clinical practice for determining genetic risks, such as carrier determination and prenatal diagnosis. Initially, blood samples are obtained from related individuals, and PCR amplification is performed. Linkage-based molecular diagnosis then entails three data analysis steps. First, for every individual, the alleles (i.e., DNA composition) are determined at specified chromosomal locations. Second, the flow of genetic material among the individuals is established. Third, the probability that a given individual is either a carrier of the disease or affected by the disease is determined. The current practice is to perform each of these three steps manually, which is costly, time consuming, labor-intensive, and error-prone. As such, the knowledge-intensive data analysis and interpretation supersede the actual experimentation effort as the major bottleneck in molecular diagnostics. By examining the human problem solving for the task, we have designed and implemented a prototype knowledge-based system capable of fully automating linkage-based molecular diagnostics in X-linked genetic disorders, including Duchenne Muscular Dystrophy (DMD). Our system uses knowledge-based interpretation of gel electrophoresis images to determine individual DNA marker labels, a constraint satisfaction search for consistent genetic flow among individuals, and a blackboard-style problem solver for risk assessment. We describe the system`s successful diagnosis of DMD carrier and affected individuals from raw clinical data.

  4. Probabilistic methods of technical diagnostics based on expert knowledge

    International Nuclear Information System (INIS)

    A brief overview is given of the premises and theoretical starting points of various decision models that operate with the expert knowledge notion and are well suited to technical diagnostics purposes. With regard to their assets, probabilistic methods receive particular attention. It is demonstrated why expert systems are only suitable for consultations while the final decision must always (especially in vital problems) be left to man. (Z.M.). 1 fig., 23 refs

  5. Diagnostic markers of urothelial cancer based on DNA methylation analysis

    International Nuclear Information System (INIS)

    Early detection and risk assessment are crucial for treating urothelial cancer (UC), which is characterized by a high recurrence rate, and necessitates frequent and invasive monitoring. We aimed to establish diagnostic markers for UC based on DNA methylation. In this multi-center study, three independent sample sets were prepared. First, DNA methylation levels at CpG loci were measured in the training sets (tumor samples from 91 UC patients, corresponding normal-appearing tissue from these patients, and 12 normal tissues from age-matched bladder cancer-free patients) using the Illumina Golden Gate methylation assay to identify differentially methylated loci. Next, these methylated loci were validated by quantitative DNA methylation by pyrosequencing, using another cohort of tissue samples (Tissue validation set). Lastly, methylation of these markers was analyzed in the independent urine samples (Urine validation set). ROC analysis was performed to evaluate the diagnostic accuracy of these 12 selected markers. Of the 1303 CpG sites, 158 were hyper ethylated and 356 were hypo ethylated in tumor tissues compared to normal tissues. In the panel analysis, 12 loci showed remarkable alterations between tumor and normal samples, with 94.3% sensitivity and 97.8% specificity. Similarly, corresponding normal tissue could be distinguished from normal tissues with 76.0% sensitivity and 100% specificity. Furthermore, the diagnostic accuracy for UC of these markers determined in urine samples was high, with 100% sensitivity and 100% specificity. Based on these preliminary findings, diagnostic markers based on differential DNA methylation at specific loci can be useful for non-invasive and reliable detection of UC and epigenetic field defect

  6. Proteinuria: The diagnostic strategy based on urine proteins differentiation

    Directory of Open Access Journals (Sweden)

    Stojimirović Biljana B.

    2004-01-01

    Full Text Available Basal glomerular membrane represents mechanical and electrical barrier for passing of the plasma proteins. Mechanical barrier is composed of cylindrical pores and filtration fissure, and negative layer charge in exterior and interior side of basal glomerular membrane, made of heparan sulphate and sialoglicoproteine, provides certain electrical barrier. Diagnostic strategy based on different serum and urine proteins enables the differentiation of various types of proteinuria. Depending on etiology of proteinuria it can be prerenal, renal and postrenal. By analyzing albumin, armicroglobulin, immunoglobulin G and armacroglobulin, together with total protein in urine, it is possible to detect and differentiate causes of prerenal, renal (glomerular, tubular, glomerulo-tubular and postrenal proteinuria. The adequate and early differentiation of proteinuria type is of an immense diagnostic and therapeutic importance.

  7. Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

    Science.gov (United States)

    Kim, Jonnathan H.

    1995-01-01

    Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

  8. 基于机器学习算法的前列腺癌诊断模型研究%Diagnostic Model Research of Prostate Cancer Based on Machine Learning Algorithm

    Institute of Scientific and Technical Information of China (English)

    曹文哲; 应俊; 张亚慧; 马海洋; 陈广飞; 周丹

    2016-01-01

    目的:基于机器学习的3种算法建立诊断预测模型,比较3种模型对前列腺癌的诊断价值。方法选择2008~2014年在中国人民解放军总医院进行前列腺穿刺活检的患者956例(其中前列腺癌463例,前列腺增生493例),采用Logistic回归分析,筛选出预测因子(年龄、游离之前列腺特异抗原、游离之前列腺特异抗原百分比、前列腺体积和前列腺特异性抗原密度)。应用基于机器学习的BP神经网络、Logistic回归和随机森林算法构建诊断预测模型,比较3种模型对前列腺癌的预测准确性。结果 Logistic回归、BP神经网络和随机森林模型对前列腺癌的诊断能力比任一单项指标都高,3种模型的灵敏度分别为77.5%、77.4%、76.2%,特异度分别为74.8%、76.8%、76.9%,精确度分别为76%、77%、77%,受试者工作特征曲线下面积(AUC)分别为0.831、0.832、0.833,3种模型对前列腺癌的诊断能力没有显著性差异。结论上述结果验证了3种模型均具有较高的诊断有效性,可将模型纳入泌尿决策,协助临床医生对前列腺癌患者进行诊断和治疗,并减少不必要的活检。%Objective To establish diagnostic prediction models based on three machine learning algorithms and compare the value of the three models in the diagnosis of prostate cancer (PC).Methods The research selected the clinical data of 956 patients (including 463 cases of prostate cancer and 493 cases of benign prostatic hyperplasia) with prostate biopsy in the General Hospital of PLA during 2008~2014. Predictors were screened by Logistic regression which included age, free prostate-speciifc antigen (fPSA), the percentage of free prostate-speciifc antigen (free PSA/total PSA), prostate volume, and PSA density (PSAD). The paper further compared the diagnostic accuracy of three models in the prediction of prostate cancer by using BP neural network, Logistic regression (LR), and

  9. Variance Estimation for NAEP Data Using a Resampling-Based Approach: An Application of Cognitive Diagnostic Models. Research Report. ETS RR-10-26

    Science.gov (United States)

    Hsieh, Chueh-an; Xu, Xueli; von Davier, Matthias

    2010-01-01

    This paper presents an application of a jackknifing approach to variance estimation of ability inferences for groups of students, using a multidimensional discrete model for item response data. The data utilized to demonstrate the approach come from the National Assessment of Educational Progress (NAEP). In contrast to the operational approach…

  10. Case-based reasoning combined with statistics for diagnostics and prognosis

    International Nuclear Information System (INIS)

    Many approaches used for diagnostics today are based on a precise model. This excludes diagnostics of many complex types of machinery that cannot be modelled and simulated easily or without great effort. Our aim is to show that by including human experience it is possible to diagnose complex machinery when there is no or limited models or simulations available. This also enables diagnostics in a dynamic application where conditions change and new cases are often added. In fact every new solved case increases the diagnostic power of the system. We present a number of successful projects where we have used feature extraction together with case-based reasoning to diagnose faults in industrial robots, welding, cutting machinery and we also present our latest project for diagnosing transmissions by combining Case-Based Reasoning (CBR) with statistics. We view the fault diagnosis process as three consecutive steps. In the first step, sensor fault signals from machines and/or input from human operators are collected. Then, the second step consists of extracting relevant fault features. In the final diagnosis/prognosis step, status and faults are identified and classified. We view prognosis as a special case of diagnosis where the prognosis module predicts a stream of future features.

  11. Experimental and numerical studies on liquid wicking into filter papers for paper-based diagnostics

    International Nuclear Information System (INIS)

    Paper-based diagnostics have shown promising potential applications in human disease surveillance and food safety analysis at the point-of-care (POC). The liquid wicking behavior in diagnostic fibrous paper plays an important role in development of paper-based diagnostics. In the current study, we performed experimental and numerical research on the liquid wicking height and mass with three width strips into filter paper. The effective porosity could be conveniently measured in the light of the linear correlation between wicking height and mass by the experimental system. A modified model with considering evaporation effect was proposed to predict wicking height and mass. The predicted wicking height and mass using the evaporation model was much closer to the experimental data compared with the model without evaporation. The wicking speed initially decreased significantly and then maintained at a constant value at lower level. The evaporation effect tends to reduce the wicking flow speed. More wicking mass could be obtained at larger strip width but the corresponding reagent loss became significant. The proposed model with evaporation paved a way to understanding the fundamental of fluid flow in diagnostic paper and was essential to provide meaningful and useful reference for the research and development of paper-based diagnostics devices. - Highlights: • A model with considering evaporation was proposed to predict wicking height and mass. • Flow characteristics of filter paper were experimentally and theoretically studied. • Effective porosity could be conveniently measured by the experimental platform. • The evaporation effect tended to reduce the wicking flow speed

  12. Working Environment with Social and Personal Open Tools for inquiry based learning: Pedagogic and Diagnostic Frameworks

    OpenAIRE

    Protopsaltis, A; Seitlinger, P; Chaimala, Fotini; Firssova, Olga; Hetzner, Sonja; Kikis-Papadakis, K; Boytchev, Pavel

    2013-01-01

    Abstract: The weSPOT project aims at propagating scientific inquiry as the approach for science learning and teaching in combination with today’s curricula and teaching practices The project focuses on inquiry-based learning with a theoretically sound and technology supported personal inquiry approach and it contains three main development aspects: (a) define a reference model for inquiry-based learning skills, (b) create a diagnostic instrument for measuring inquiry skills, and (c) implement...

  13. Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas.

    Science.gov (United States)

    Hoyer, A; Kuss, O

    2015-05-20

    In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples. PMID:25712874

  14. FORWARD MODELING CAVITY DENSITY: A MULTI-INSTRUMENT DIAGNOSTIC

    International Nuclear Information System (INIS)

    The thermodynamic properties of coronal prominence cavities present a unique probe into the energy and mass budget of prominences. Using a three-dimensional morphological model, we forward model the polarization brightness and extreme-ultraviolet (EUV) emission of a cavity and its surrounding streamer. Using a genetic algorithm, we find the best-fit density model by comparing the models to Mauna Loa Solar Observatory MK4 and Hinode EUV Imaging Spectrometer data. The effect of temperature variations on the derived density is also measured. We have measured the density inside a cavity down to 1.05 Rsun with height-dependent error bars. Our forward modeling technique compensates for optically thin projection effects. This method provides a complementary technique to traditional line ratio diagnostics that is useful for diffuse off-limb coronal structures.

  15. A Ribeiroia spp. (Class: Trematoda) - Specific PCR-based diagnostic

    Science.gov (United States)

    Reinitz, D.M.; Yoshino, T.P.; Cole, R.A.

    2007-01-01

    Increased reporting of amphibian malformations in North America has been noted with concern in light of reports that amphibian numbers and species are declining worldwide. Ribeiroia ondatrae has been shown to cause a variety of types of malformations in amphibians. However, little is known about the prevalence of R. ondatrae in North America. To aid in conducting field studies of Ribeiroia spp., we have developed a polymerase chain reaction (PCR)-based diagnostic. Herein, we describe the development of an accurate, rapid, simple, and cost-effective diagnostic for detection of Ribeiroia spp. infection in snails (Planorbella trivolvis). Candidate oligonucleotide primers for PCR were designed via DNA sequence analyses of multiple ribosomal internal transcribed spacer-2 regions from Ribeiroia spp. and Echinostoma spp. Comparison of consensus sequences determined from both genera identified areas of sequence potentially unique to Ribeiroia spp. The PCR reliably produced a diagnostic 290-base pair (bp) product in the presence of a wide concentration range of snail or frog DNA. Sensitivity was examined with DNA extracted from single R. ondatrae cercaria. The single-tube PCR could routinely detect less than 1 cercariae equivalent, because DNA isolated from a single cercaria could be diluted at least 1:50 and still yield a positive result via gel electrophoresis. An even more sensitive nested PCR also was developed that routinely detected 100 fg of the 290-bp fragment. The assay did not detect furcocercous cercariae of certain Schistosomatidae, Echinostoma sp., or Sphaeridiotrema globulus nor adults of Clinostomum sp. or Cyathocotyle bushiensis. Field testing of 137 P. trivolvis identified 3 positives with no overt environmental cross-reactivity, and results concurred with microscopic examinations in all cases. ?? American Society of Parasitologists 2007.

  16. High frequency modeling of power transformers. Stresses and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Bjerkan, Eilert

    2005-05-15

    In this thesis a reliable, versatile and rigorous method for high frequency power transformer modeling is searched and established. The purpose is to apply this model to sensitivity analysis of FRA (Frequency Response Analysis) which is a quite new diagnostic method for assessing the mechanical integrity of power transformer windings on-site. The method should be versatile in terms of being able to estimate internal and external over voltages and resonances. Another important aspect is that the method chosen is suitable for real transformer geometries. In order to verify the suitability of the model for real transformers, a specific test-object is used. This is a 20MVA transformer, and details are given in chapter 1.4. The high frequency power transformer model is established from geometrical and constructional information from the manufacturer, together with available material characteristics. All circuit parameters in the lumped circuit representation are calculated based on these data. No empirical modifications need to be performed. Comparison shows capability of reasonable accuracy in the range from 10 khz to 1 MHz utilizing a disc-to-disc representation. A compromise between accuracy of model due to discretization and complexity of the model in a turn-to-turn representation is inevitable. The importance of the iron core is emphasized through a comparison of representations with/without the core included. Frequency-dependent phenomena are accurately represented using an isotropic equivalent for windings and core, even with a coarse mesh for the FEM-model. This is achieved through a frequency-dependent complex permeability representation of the materials. This permeability is deduced from an analytical solution of the frequency-dependent magnetic field inside the conductors and the core. The importance of dielectric losses in a transformer model is also assessed. Since published data on the high frequency properties of press board are limited, some initial

  17. Error field and magnetic diagnostic modeling for W7-X

    Energy Technology Data Exchange (ETDEWEB)

    Lazerson, Sam A. [PPPL; Gates, David A. [PPPL; NEILSON, GEORGE H. [PPPL; OTTE, M.; Bozhenkov, S.; Pedersen, T. S.; GEIGER, J.; LORE, J.

    2014-07-01

    The prediction, detection, and compensation of error fields for the W7-X device will play a key role in achieving a high beta (Β = 5%), steady state (30 minute pulse) operating regime utilizing the island divertor system [1]. Additionally, detection and control of the equilibrium magnetic structure in the scrape-off layer will be necessary in the long-pulse campaign as bootstrapcurrent evolution may result in poor edge magnetic structure [2]. An SVD analysis of the magnetic diagnostics set indicates an ability to measure the toroidal current and stored energy, while profile variations go undetected in the magnetic diagnostics. An additional set of magnetic diagnostics is proposed which improves the ability to constrain the equilibrium current and pressure profiles. However, even with the ability to accurately measure equilibrium parameters, the presence of error fields can modify both the plasma response and diverter magnetic field structures in unfavorable ways. Vacuum flux surface mapping experiments allow for direct measurement of these modifications to magnetic structure. The ability to conduct such an experiment is a unique feature of stellarators. The trim coils may then be used to forward model the effect of an applied n = 1 error field. This allows the determination of lower limits for the detection of error field amplitude and phase using flux surface mapping. *Research supported by the U.S. DOE under Contract No. DE-AC02-09CH11466 with Princeton University.

  18. From Present Fusion Devices to DEMO: a Changing Role between Diagnostics and Modeling

    OpenAIRE

    Donne, A. J. H.

    2013-01-01

    On present-day devices much effort is devoted to develop state-of-the-art diagnostics with a continuous drive towards higher accuracy, better spatial and temporal resolution and more diagnostic channels. Diagnostic innovations often lead to better physics insight and they are often a driver for improving theoretical models. In future fusion devices the operation of diagnostics is strongly limited by the hostile environment. In ITER many of the presently used diagnostics are still marginally a...

  19. ISHM-oriented adaptive fault diagnostics for avionics based on a distributed intelligent agent system

    Science.gov (United States)

    Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

    2015-10-01

    In this paper, an integrated system health management-oriented adaptive fault diagnostics and model for avionics is proposed. With avionics becoming increasingly complicated, precise and comprehensive avionics fault diagnostics has become an extremely complicated task. For the proposed fault diagnostic system, specific approaches, such as the artificial immune system, the intelligent agents system and the Dempster-Shafer evidence theory, are used to conduct deep fault avionics diagnostics. Through this proposed fault diagnostic system, efficient and accurate diagnostics can be achieved. A numerical example is conducted to apply the proposed hybrid diagnostics to a set of radar transmitters on an avionics system and to illustrate that the proposed system and model have the ability to achieve efficient and accurate fault diagnostics. By analyzing the diagnostic system's feasibility and pragmatics, the advantages of this system are demonstrated.

  20. Simulation of optical diagnostics for crystal growth: models and results

    Science.gov (United States)

    Banish, Michele R.; Clark, Rodney L.; Kathman, Alan D.; Lawson, Shelah M.

    1991-12-01

    A computer simulation of a two-color holographic interferometric (TCHI) optical system was performed using a physical (wave) optics model. This model accurately simulates propagation through time-varying, 2-D or 3-D concentration and temperature fields as a wave phenomenon. The model calculates wavefront deformations that can be used to generate fringe patterns. This simulation modeled a proposed TriGlycine sulphate TGS flight experiment by propagating through the simplified onion-like refractive index distribution of the growing crystal and calculating the recorded wavefront deformation. The phase of this wavefront was used to generate sample interferograms that map index of refraction variation. Two such fringe patterns, generated at different wavelengths, were used to extract the original temperature and concentration field characteristics within the growth chamber. This proves feasibility for this TCHI crystal growth diagnostic technique. This simulation provides feedback to the experimental design process.

  1. LED-based near infrared sensor for cancer diagnostics

    Science.gov (United States)

    Bogomolov, Andrey; Ageev, Vladimir; Zabarylo, Urszula; Usenov, Iskander; Schulte, Franziska; Kirsanov, Dmitry; Belikova, Valeria; Minet, Olaf; Feliksberger, E.; Meshkovsky, I.; Artyushenko, Viacheslav

    2016-03-01

    Optical spectroscopic technologies are increasingly used for cancer diagnostics. Feasibility of differentiation between malignant and healthy samples of human kidney using Fluorescence, Raman, MIR and NIR spectroscopy has been recently reported . In the present work, a simplification of NIR spectroscopy method has been studied. Traditional high-resolution NIR spectrometry was replaced by an optical sensor based on a set of light-emitting diodes at selected wavelengths as light sources and a photodiode. Two prototypes of the sensor have been developed and tested using 14 in-vitro samples of seven kidney tumor patients. Statistical evaluation of results using principal component analysis and partial least-squares discriminant analysis has been performed. Despite only partial discrimination between tumor and healthy tissue achieved by the presented new technique, the results evidence benefits of LED-based near-infrared sensing used for oncological diagnostics. Publisher's Note: This paper, originally published on 4 March, 2016, was replaced with a corrected/revised version on 7 April, 2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.

  2. Laser based diagnostics - from cultural heritage to human health

    Science.gov (United States)

    Svanberg, S.

    2008-09-01

    An overview of applied laser-based diagnostics as pursued at the Division of Atomic Physics, Lund University, is given. The fields of application range from environmental monitoring including cultural heritage assessment, to biomedical applications. General aspects of laser-based methods are non-intrusiveness, high spectral- and spatial resolution, and data production in real-time. Different applications are frequently generically very similar irrespective of the particular context, which, however, decides the spatial and temporal scales as well as the size of the optics employed. Thus, volcanic plume mapping by lidar, and optical mammography are two manifestations of the same principle, as is fluorescence imaging of a human bronchus by an endoscope, and the scanning of a cathedral using a fluorescence lidar system. Recent applications include remote laser-induced break-down spectroscopy (LIBS) and gas monitoring in scattering media (GASMAS). In particular, a powerful method for diagnostics of human sinus cavities was developed, where free oxygen and water molecules are monitored simultaneously.

  3. Translating sanger-based routine DNA diagnostics into generic massive parallel ion semiconductor sequencing

    NARCIS (Netherlands)

    Diekstra, A.; Bosgoed, E.A.J.; Rikken, A.; Lier, B. van; Kamsteeg, E.J.; Tychon, M.W.J.; Derks, R.C.; Soest, R.A.; Mensenkamp, A.R.; Scheffer, H.; Neveling, K.; Nelen, M.R.

    2015-01-01

    BACKGROUND: Dideoxy-based chain termination sequencing developed by Sanger is the gold standard sequencing approach and allows clinical diagnostics of disorders with relatively low genetic heterogeneity. Recently, new next generation sequencing (NGS) technologies have found their way into diagnostic

  4. Entropy-Based Clutter Rejection for Intrawall Diagnostics

    Directory of Open Access Journals (Sweden)

    Raffaele Solimene

    2012-01-01

    Full Text Available The intrawall diagnostic problem of detecting localized inhomogeneities possibly present within the wall is addressed. As well known, clutter arising from masonry structure can impair detection of embedded scatterers due to high amplitude reflections that wall front face introduces. Moreover, internal multiple reflections also can make it difficult ground penetrating radar images (radargramms interpretation. To counteract these drawbacks, a clutter rejection method, properly tailored on the wall features, is mandatory. To this end, here we employ a windowing strategy based on entropy measures of temporal traces “similarity.” Accordingly, instants of time for which radargramms exhibit entropy values greater than a prescribed threshold are “silenced.” Numerical results are presented in order to show the effectiveness of the entropy-based clutter rejection algorithm. Moreover, a comparison with the standard average trace subtraction is also included.

  5. Status of Real-Time Laser Based Ion Engine Diagnostics at NASA Glenn Research Center

    Science.gov (United States)

    Domonkos, Matthew T.; Williams, George J., Jr.

    2001-01-01

    The development status of laser based erosion diagnostics for ion engines at the NASA Glenn Research Center is discussed. The diagnostics are being developed to enhance component life-prediction capabilities. A direct measurement of the erosion product density using laser induced fluorescence (LIF) is described. Erosion diagnostics based upon evaluation of the ion dynamics are also under development, and the basic approach is presented. The planned implementation of the diagnostics is discussed.

  6. Reducing Diagnostic Error with Computer-Based Clinical Decision Support

    Science.gov (United States)

    Greenes, Robert A.

    2009-01-01

    Information technology approaches to delivering diagnostic clinical decision support (CDS) are the subject of the papers to follow in the proceedings. These will address the history of CDS and present day approaches (Miller), evaluation of diagnostic CDS methods (Friedman), and the role of clinical documentation in supporting diagnostic decision…

  7. Comparison of the diagnostic accuracy of commercial NS1-based diagnostic tests for early dengue infection

    Directory of Open Access Journals (Sweden)

    Villar Luis A

    2010-12-01

    Full Text Available Abstract Background We compared the diagnostic accuracy and reproducibility of commercially available NS1-based dengue tests and explored factors influencing their sensitivities. Methods Paired analysis of 310 samples previously characterized as positive (n = 218 and negative (n = 92 for viral isolation and/or RT-PCR and/or IgM seroconversion. Masked samples were tested by two observers with Platelia™ Dengue NS1 Ag, second generation Pan-E™ Dengue Early ELISA, SD Dengue NS1 Ag ELISA, Dengue NS1 Ag STRIP™, and SD BIOLINE™ Dengue Duo (NS1/IgM/IgG. Results SD BIOLINE™ NS1/IgM/IgG had the highest sensitivity (80.7% 95%CI 75-85.7 with likelihood ratios of 7.4 (95%CI 4.1-13.8 and 0.21 (95%CI 0.16-0.28. The ELISA-format tests showed comparable sensitivities; all below 75%. STRIP™ and SD NS1 had even lower sensitivities ( Conclusions The simultaneous detection of NS1/IgM/IgG would be potentially useful for dengue diagnosis in both endemic and non endemic areas. A negative result does not rule out dengue. Further studies are required to assess the performance and impact of early laboratory diagnosis of dengue in the routine clinical setting.

  8. The operative diagnostics to adaptation heart to physical load on the base of artificial neuron networks

    OpenAIRE

    Timoshchenko E.V.

    2010-01-01

    In article are considered questions of the revealing the breach of the warmhearted rhythm beside athlete and athlete during physical load. The estimation of the condition heart was defined as of electrocardiographically of the examination. Mathematical model is designed for interpreting electrocardiogram data on base artificial neuron networks. It is created software, which allows to conduct the diagnostics of the heart diseases in the field of discovery different arrhythmias. Introduction re...

  9. Introduction to a diagnostic approach for point processes based on weighted second-order statistics

    OpenAIRE

    Giada Adelfio; Frederic Paik Schoenberg

    2007-01-01

    A new diagnostic method for point processes is here presented. It is based on their second-order analysis, transforming the original point process by the inverse of its conditional intensity function in order to form a generalized estimate of various second-order point process properties. The result is generalized versions of the spectral density, R/S statistic, correlation integral and K-function, which can be used to test the fit of complex point process models with arbitrary conditional in...

  10. Impact of Diagnosticity on the Adequacy of Models for Cognitive Diagnosis under a Linear Attribute Structure: A Simulation Study

    Science.gov (United States)

    de La Torre, Jimmy; Karelitz, Tzur M.

    2009-01-01

    Compared to unidimensional item response models (IRMs), cognitive diagnostic models (CDMs) based on latent classes represent examinees' knowledge and item requirements using discrete structures. This study systematically examines the viability of retrofitting CDMs to IRM-based data with a linear attribute structure. The study utilizes a procedure…

  11. Image standards in Tissue-Based Diagnosis (Diagnostic Surgical Pathology

    Directory of Open Access Journals (Sweden)

    Vollmer Ekkehard

    2008-04-01

    Full Text Available Abstract Background Progress in automated image analysis, virtual microscopy, hospital information systems, and interdisciplinary data exchange require image standards to be applied in tissue-based diagnosis. Aims To describe the theoretical background, practical experiences and comparable solutions in other medical fields to promote image standards applicable for diagnostic pathology. Theory and experiences Images used in tissue-based diagnosis present with pathology – specific characteristics. It seems appropriate to discuss their characteristics and potential standardization in relation to the levels of hierarchy in which they appear. All levels can be divided into legal, medical, and technological properties. Standards applied to the first level include regulations or aims to be fulfilled. In legal properties, they have to regulate features of privacy, image documentation, transmission, and presentation; in medical properties, features of disease – image combination, human – diagnostics, automated information extraction, archive retrieval and access; and in technological properties features of image acquisition, display, formats, transfer speed, safety, and system dynamics. The next lower second level has to implement the prescriptions of the upper one, i.e. describe how they are implemented. Legal aspects should demand secure encryption for privacy of all patient related data, image archives that include all images used for diagnostics for a period of 10 years at minimum, accurate annotations of dates and viewing, and precise hardware and software information. Medical aspects should demand standardized patients' files such as DICOM 3 or HL 7 including history and previous examinations, information of image display hardware and software, of image resolution and fields of view, of relation between sizes of biological objects and image sizes, and of access to archives and retrieval. Technological aspects should deal with image

  12. Model performance metrics and process diagnostics for boreal summer intraseasonal variability

    Science.gov (United States)

    Neena, J. M.; Waliser, Duane; Jiang, Xianan

    2016-05-01

    Representation of the boreal summer intraseasonal oscillations (BSISO) is evaluated in the 20-year climate simulations from 27 general circulation models (GCMs), produced as part of a global multi-model evaluation project coordinated to study the vertical structure and physical processes of the Madden-Julian oscillation (MJO). Model performance metrics are developed to assess the simulated BSISO characteristics, with a special focus on its northward propagation over the Asian monsoon domain. Several process-oriented diagnostics developed by the MJO community are also tested for the BSISO. Simulating the phase speed and meridional extent of BSISO northward propagation, the northwest-southeast tilted rain-band structure and the quasi-biweekly mode are identified as some of the persisting problems for many GCMs. Interestingly, many of the GCMs, which capture BSISO eastward propagation, also show good fidelity in simulating BSISO northward propagation. Meridional vertical profiles of anomalous wind, temperature and diabatic heating of BSISO are better simulated in the GCMs that simulate the northward propagation. Process-oriented diagnostics based on seasonal mean vertical shear of zonal and meridional wind, large-scale rain fraction and relative humidity are also examined, but it still remains challenge to find a process diagnostic which is strongly linked to BSISO northward propagation. The complex spatial structure and presence of multi-scale disturbances, demand the development of more focused GCM evaluation metrics and process diagnostics specifically for the BSISO.

  13. Comparison of Prognostic and Diagnostic Approaches to Modeling Evapotranspiration in the Nile River Basin

    Science.gov (United States)

    Yilmaz, M.; Anderson, M. C.; Zaitchik, B. F.; Crow, W. T.; Hain, C.; Ozdogan, M.; Chun, J. A.

    2012-12-01

    Actual evapotranspiration (ET) can be estimated using both prognostic and diagnostic modeling approaches, providing independent yet complementary information for hydrologic applications. Both approaches have advantages and disadvantages. When provided with temporally continuous atmospheric forcing data, prognostic models offer continuous sub-daily ET information together with the full set of water and energy balance fluxes and states (i.e. soil moisture, runoff, sensible and latent heat). On the other hand, the diagnostic modeling approach provides ET estimates over regions where reliable information about available soil water is not known (e.g., due to irrigation practices or shallow ground water levels not included in the prognostic model structure, unknown soil texture or plant rooting depth, etc). Prognostic model-based ET estimates are of great interest whenever consistent and complete water budget information is required or when there is a need to project ET for climate or land use change scenarios. Diagnostic models establish a stronger link to remote sensing observations, can be applied in regions with limited or questionable atmospheric forcing data, and provide valuable observation-derived information about the current land-surface state. Analysis of independently obtained ET estimates is particularly important in data poor regions. Such comparisons can help to reduce the uncertainty in the modeled ET estimates and to exclude outliers based on physical considerations. The Nile river basin is home to tens of millions of people whose daily life depends on water extracted from the river Nile. Yet the complete basin scale water balance of the Nile has been studied only a few times, and the temporal and the spatial distribution of hydrological fluxes (particularly ET) are still a subject of active research. This is due in part to a scarcity of ground-based station data for validation. In such regions, comparison between prognostic and diagnostic model output

  14. Real-time Modelling, Diagnostics and Optimised MPPT for Residental PV Systems

    DEFF Research Database (Denmark)

    Sera, Dezso

    to diagnostic functions as an additional tool to maximise the energy yield of photovoltaic arrays (Chapter 4). Furthermore, mathematical models of PV panels and arrays have been developed and built (detailed in Chapter 3) for testing MPPT algorithms, and for diagnostic purposes. In Chapter 2 an overview...... and generic nature, and has the benefit of also being efficient in fast-changing conditions. Furthermore, the algorithm has been successfully implemented on a commercial PV inverter, currently on the market. In Chapter 3, an overview of the existing mathematical models used to describe the electrical...... responsible for yield-reduction of residential photovoltaic systems. Combining the model calculations with measurements, a method to detect changes in the panels’ series resistance based on the slope of the I − V curve in the vicinity of open-circuit conditions and scaled to Standard Test Conditions (STC...

  15. Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models

    OpenAIRE

    Baddeley, Adrian; Rubak, Ege; Møller, Jesper

    2012-01-01

    We develop new tools for formal inference and informal model validation in the analysis of spatial point pattern data. The score test is generalized to a "pseudo-score" test derived from Besag's pseudo-likelihood, and to a class of diagnostics based on point process residuals. The results lend theoretical support to the established practice of using functional summary statistics, such as Ripley's $K$-function, when testing for complete spatial randomness; and they provide new tools such as th...

  16. ANOVA model for network meta-analysis of diagnostic test accuracy data

    OpenAIRE

    Nyaga, Victoria; Aerts, Marc; Arbyn, Marc

    2016-01-01

    Network meta-analysis (NMA) allow combining efficacy information from multiple comparisons from trials assessing different therapeutic interventions for a given disease and to estimate unobserved comparisons from a network of observed comparisons. Applying NMA on diagnostic accuracy studies is a statistical challenge given the inherent correlation of sensitivity and specificity. A conceptually simple and novel hierarchical arm-based (AB) model which expresses the logit transformed sensitivity...

  17. OpenID connect as a security service in Cloud-based diagnostic imaging systems

    Science.gov (United States)

    Ma, Weina; Sartipi, Kamran; Sharghi, Hassan; Koff, David; Bak, Peter

    2015-03-01

    The evolution of cloud computing is driving the next generation of diagnostic imaging (DI) systems. Cloud-based DI systems are able to deliver better services to patients without constraining to their own physical facilities. However, privacy and security concerns have been consistently regarded as the major obstacle for adoption of cloud computing by healthcare domains. Furthermore, traditional computing models and interfaces employed by DI systems are not ready for accessing diagnostic images through mobile devices. RESTful is an ideal technology for provisioning both mobile services and cloud computing. OpenID Connect, combining OpenID and OAuth together, is an emerging REST-based federated identity solution. It is one of the most perspective open standards to potentially become the de-facto standard for securing cloud computing and mobile applications, which has ever been regarded as "Kerberos of Cloud". We introduce OpenID Connect as an identity and authentication service in cloud-based DI systems and propose enhancements that allow for incorporating this technology within distributed enterprise environment. The objective of this study is to offer solutions for secure radiology image sharing among DI-r (Diagnostic Imaging Repository) and heterogeneous PACS (Picture Archiving and Communication Systems) as well as mobile clients in the cloud ecosystem. Through using OpenID Connect as an open-source identity and authentication service, deploying DI-r and PACS to private or community clouds should obtain equivalent security level to traditional computing model.

  18. High frequency modeling of power transformers. Stresses and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Bjerkan, Eilert

    2005-05-15

    In this thesis a reliable, versatile and rigorous method for high frequency power transformer modeling is searched and established. The purpose is to apply this model to sensitivity analysis of FRA (Frequency Response Analysis) which is a quite new diagnostic method for assessing the mechanical integrity of power transformer windings on-site. The method should be versatile in terms of being able to estimate internal and external over voltages and resonances. Another important aspect is that the method chosen is suitable for real transformer geometries. In order to verify the suitability of the model for real transformers, a specific test-object is used. This is a 20MVA transformer, and details are given in chapter 1.4. The high frequency power transformer model is established from geometrical and constructional information from the manufacturer, together with available material characteristics. All circuit parameters in the lumped circuit representation are calculated based on these data. No empirical modifications need to be performed. Comparison shows capability of reasonable accuracy in the range from 10 khz to 1 MHz utilizing a disc-to-disc representation. A compromise between accuracy of model due to discretization and complexity of the model in a turn-to-turn representation is inevitable. The importance of the iron core is emphasized through a comparison of representations with/without the core included. Frequency-dependent phenomena are accurately represented using an isotropic equivalent for windings and core, even with a coarse mesh for the FEM-model. This is achieved through a frequency-dependent complex permeability representation of the materials. This permeability is deduced from an analytical solution of the frequency-dependent magnetic field inside the conductors and the core. The importance of dielectric losses in a transformer model is also assessed. Since published data on the high frequency properties of press board are limited, some initial

  19. Temporal diagnostic analysis of the SWAT model to detect dominant periods of poor model performance

    Science.gov (United States)

    Guse, Björn; Reusser, Dominik E.; Fohrer, Nicola

    2013-04-01

    Hydrological models generally include thresholds and non-linearities, such as snow-rain-temperature thresholds, non-linear reservoirs, infiltration thresholds and the like. When relating observed variables to modelling results, formal methods often calculate performance metrics over long periods, reporting model performance with only few numbers. Such approaches are not well suited to compare dominating processes between reality and model and to better understand when thresholds and non-linearities are driving model results. We present a combination of two temporally resolved model diagnostic tools to answer when a model is performing (not so) well and what the dominant processes are during these periods. We look at the temporal dynamics of parameter sensitivities and model performance to answer this question. For this, the eco-hydrological SWAT model is applied in the Treene lowland catchment in Northern Germany. As a first step, temporal dynamics of parameter sensitivities are analyzed using the Fourier Amplitude Sensitivity test (FAST). The sensitivities of the eight model parameters investigated show strong temporal variations. High sensitivities were detected for two groundwater (GW_DELAY, ALPHA_BF) and one evaporation parameters (ESCO) most of the time. The periods of high parameter sensitivity can be related to different phases of the hydrograph with dominances of the groundwater parameters in the recession phases and of ESCO in baseflow and resaturation periods. Surface runoff parameters show high parameter sensitivities in phases of a precipitation event in combination with high soil water contents. The dominant parameters give indication for the controlling processes during a given period for the hydrological catchment. The second step included the temporal analysis of model performance. For each time step, model performance was characterized with a "finger print" consisting of a large set of performance measures. These finger prints were clustered into

  20. Flotation process diagnostics and modelling by coal grain analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ofori, P; O' Brien, G.; Firth, B.; Jenkins, B. [CSIRO Energy Technology, Brisbane, Qld. (Australia)

    2006-05-15

    In coal flotation, particles of different components of the coal such as maceral groups and mineral matter and their associations have different hydrophobicities and therefore different flotation responses. By using a new coal grain analysis method for characterising individual grains, more detailed flotation performance analysis and modelling approaches have been developed. The method involves the use of microscopic imaging techniques to obtain estimates of size, compositional and density information on individual grains of fine coal. The density and composition partitioning of coal processed through different flotation systems provides an avenue to pinpoint the actual cause of poor process performance so that corrective action may be initiated. The information on grain size, density and composition is being used as input data to develop more detailed flotation process models to provide better predictions of process performance for both mechanical and column flotation devices. A number of approaches may be taken to flotation modelling such as the probability approach and the kinetic model approach or a combination of the two. In the work reported here, a simple probability approach has been taken, which will be further refined in due course. The use of grain data to map the responses of different types of coal grains through various fine coal cleaning processes provided a more advanced diagnostic capability for fine coal cleaning circuits. This enabled flotation performance curves analogous to partition curves for density separators to be produced for flotation devices.

  1. Changing Histopathological Diagnostics by Genome-Based Tumor Classification

    Directory of Open Access Journals (Sweden)

    Michael Kloth

    2014-05-01

    Full Text Available Traditionally, tumors are classified by histopathological criteria, i.e., based on their specific morphological appearances. Consequently, current therapeutic decisions in oncology are strongly influenced by histology rather than underlying molecular or genomic aberrations. The increase of information on molecular changes however, enabled by the Human Genome Project and the International Cancer Genome Consortium as well as the manifold advances in molecular biology and high-throughput sequencing techniques, inaugurated the integration of genomic information into disease classification. Furthermore, in some cases it became evident that former classifications needed major revision and adaption. Such adaptations are often required by understanding the pathogenesis of a disease from a specific molecular alteration, using this molecular driver for targeted and highly effective therapies. Altogether, reclassifications should lead to higher information content of the underlying diagnoses, reflecting their molecular pathogenesis and resulting in optimized and individual therapeutic decisions. The objective of this article is to summarize some particularly important examples of genome-based classification approaches and associated therapeutic concepts. In addition to reviewing disease specific markers, we focus on potentially therapeutic or predictive markers and the relevance of molecular diagnostics in disease monitoring.

  2. Ontology-oriented diagnostic system for traditional Chinese medicine based on relation refinement.

    Science.gov (United States)

    Gu, Peiqin; Chen, Huajun; Yu, Tong

    2013-01-01

    Although Chinese medicine treatments have become popular recently, the complicated Chinese medical knowledge has made it difficult to be applied in computer-aided diagnostics. The ability to model and use the knowledge becomes an important issue. In this paper, we define the diagnosis in Traditional Chinese Medicine (TCM) as discovering the fuzzy relations between symptoms and syndromes. An Ontology-oriented Diagnosis System (ODS) is created to address the knowledge-based diagnosis based on a well-defined ontology of syndromes. The ontology transforms the implicit relationships among syndromes into a machine-interpretable model. The clinical data used for feature selection is collected from a national TCM research institute in China, which serves as a training source for syndrome differentiation. The ODS analyzes the clinical cases to obtain a statistical mapping relation between each syndrome and associated symptom set, before rechecking the completeness of related symptoms via ontology refinement. Our diagnostic system provides an online web interface to interact with users, so that users can perform self-diagnosis. We tested 12 common clinical cases on the diagnosis system, and it turned out that, given the agree metric, the system achieved better diagnostic accuracy compared to nonontology method-92% of the results fit perfectly with the experts' expectations. PMID:23533534

  3. Case-based reasoning diagnostic technique based on multi-attribute similarity

    Energy Technology Data Exchange (ETDEWEB)

    Makoto, Takahashi [Tohoku University, Miyagi (Japan); Akio, Gofuku [Okayama University, Okayamaa (Japan)

    2014-08-15

    Case-based diagnostic technique has been developed based on the multi-attribute similarity. Specific feature of the developed system is to use multiple attributes of process signals for similarity evaluation to retrieve a similar case stored in a case base. The present technique has been applied to the measurement data from Monju with some simulated anomalies. The results of numerical experiments showed that the present technique can be utilizes as one of the methods for a hybrid-type diagnosis system.

  4. Diagnostic evaluation of regional models using chemical measurements made from aircraft

    International Nuclear Information System (INIS)

    During the summer of 1988, instrumented aircraft were used to gather data aloft to be used for diagnostic evaluation of regional Eulerian acid deposition models. One mission was designed to monitor pollutant distributions during a period of frontal passage. The purpose of the flights was to develop data to evaluate how well models handle pollutant redistribution and scavenging during a frontal event, and to assess how well the models handle buildup of pollutants in a high pressure system following cold front passage. This paper compares the aircraft measurements noted above with results from the Regional Acid Deposition Model (RADM). The model results are based on simulations using a 15 layer version of RADM covering the time period of interest. The authors will discuss comparisons of model results with pollutant concentrations measured within the mixed layer and above the mixed layer. Pollutant concentrations will be compared on an absolute basis, and also on a relative basis from one flight to the next. Important comparison species include H2O2, O3, SO2, NOy, HNO3, NO2, PAN, and SO4. Of particular interest in terms of diagnostic evaluation is the model's treatment of sulfur and nitrogen chemistry. This paper will discuss sulfur and nitrogen distribution and will evaluate the influence of model vertical resolution and nighttime chemistry on this model/measurement comparison

  5. An XML-based loose-schema approach to managing diagnostic data in heterogeneous formats

    Energy Technology Data Exchange (ETDEWEB)

    Naito, O., E-mail: naito.osamu@jaea.go.j [Japan Atomic Energy Agency, 801-1 Mukouyama, Naka, Ibaraki 311-0193 (Japan)

    2010-07-15

    An approach to managing diagnostic data in heterogenous formats by using XML-based (eXtensible Markup Language) tag files is discussed. The tag file functions like header information in ordinary data formats but it is separate from the main body of data, human readable, and self-descriptive. Thus all the necessary information for reading the contents of data can be obtained without prior information or reading the data body itself. In this paper, modeling of diagnostic data and its representation in XML are studied and a very primitive implementation of this approach in C++ is presented. The overhead of manipulating XML in a proof-of-principle code was found to be small. The merits, demerits, and possible extensions of this approach are also discussed.

  6. Magnetic nanoparticles for biomedical NMR-based diagnostics

    Directory of Open Access Journals (Sweden)

    Huilin Shao

    2010-12-01

    Full Text Available Rapid and accurate measurements of protein biomarkers, pathogens and cells in biological samples could provide useful information for early disease diagnosis, treatment monitoring, and design of personalized medicine. In general, biological samples have only negligible magnetic susceptibility. Thus, using magnetic nanoparticles for biosensing not only enhances sensitivity but also effectively reduces sample preparation needs. This review focuses on the use of magnetic nanoparticles for in vitro detection of biomolecules and cells based on magnetic resonance effects. This detection platform, termed diagnostic magnetic resonance (DMR, exploits magnetic nanoparticles as proximity sensors, which modulate the spin–spin relaxation time of water molecules surrounding molecularly-targeted nanoparticles. By developing more effective magnetic nanoparticle biosensors, DMR detection limits for various target moieties have been considerably improved over the last few years. Already, a library of magnetic nanoparticles has been developed, in which a wide range of targets, including DNA/mRNA, proteins, small molecules/drugs, bacteria, and tumor cells, have been quantified. More recently, the capabilities of DMR technology have been further advanced with new developments such as miniaturized nuclear magnetic resonance detectors, better magnetic nanoparticles and novel conjugational methods. These developments have enabled parallel and sensitive measurements to be made from small volume samples. Thus, the DMR technology is a highly attractive platform for portable, low-cost, and efficient biomolecular detection within a biomedical setting.

  7. Beam Diagnostics for Laser Undulator Based on Compton Backward Scattering

    CERN Document Server

    Kuroda, R

    2005-01-01

    A compact soft X-ray source is required in various research fields such as material and biological science. The laser undulator based on Compton backward scattering has been developed as a compact soft X-ray source for the biological observation at Waseda University. It is performed in a water window region (250eV - 500 eV) using the interaction between 1047 nm Nd:YLF laser (10ps FWHM) and about 5 MeV high quality electron beam (10ps FWHM) generated from rf gun system. The range of X-ray energy in the water window region has K-shell absorption edges of Oxygen, Carbon and Nitrogen, which mainly constitute of living body. Since the absorption coefficient of water is much smaller than the protein's coefficient in this range, a dehydration of the specimens is not necessary. To generate the soft X-ray pulse stably, the electron beam diagnostics have been developed such as the emittance measurement using double slit scan technique, the bunch length measurement using two frequency analysis technique. In this confere...

  8. A systematic review on diagnostic accuracy of CT-based detection of significant coronary artery disease

    International Nuclear Information System (INIS)

    Objectives: Systematic review of diagnostic accuracy of contrast enhanced coronary computed tomography (CE-CCT). Background: Noninvasive detection of coronary artery stenosis (CAS) by CE-CCT as an alternative to catheter-based coronary angiography (CCA) may improve patient management. Methods: Forty-one articles published between 1997 and 2006 were included that evaluated native coronary arteries for significant stenosis and used CE-CCT as diagnostic test and CCA as reference standard. Study group characteristics, study methodology and diagnostic outcomes were extracted. Pooled summary sensitivity and specificity of CE-CCT were calculated using a random effects model (1) for all coronary segments, (2) assessable segments, and (3) per patient. Results: The 41 studies totaled 2515 patients (75% males; mean age: 59 years, CAS prevalence: 59%). Analysis of all coronary segments yielded a sensitivity of 95% (80%, 89%, 86%, 98% for electron beam CT, 4/8-slice, 16-slice and 64-slice MDCT, respectively) for a specificity of 85% (77%, 84%, 95%, 91%). Analysis limited to segments deemed assessable by CT showed sensitivity of 96% (86%, 85%, 98%, 97%) for a specificity of 95% (90%, 96%, 96%, 96%). Per patient, sensitivity was 99% (90%, 97%, 99%, 98%) and specificity was 76% (59%, 81%, 83%, 92%). Heterogeneity was quantitatively important but not explainable by patient group characteristics or study methodology. Conclusions: Current diagnostic accuracy of CE-CCT is high. Advances in CT technology have resulted in increases in diagnostic accuracy and proportion of assessable coronary segments. However, per patient, accuracy may be lower and CT may have more limited clinical utility in populations at high risk for CAD

  9. Ring diagnostics and consistency test of the model for the AGS Booster

    International Nuclear Information System (INIS)

    From a systematic analysis of readings of the beam position monitors in the AGS Booster ring, combined with the transfer matrices between a few locations in the ring, calculated with MAD, the consistency of the model of the lattice has been tested. This technique has enabled us to (1) detect errors in the machine that subsequent survey during shutdown has confirmed, and (2) to measure the actual circulating beam momentum offset The method has proved rather general and convenient for accelerator diagnostics as part of a model-based accelerator control system and extensions are suggested

  10. A qualitative model construction method of nuclear power plants for effective diagnostic knowledge generation

    International Nuclear Information System (INIS)

    This paper discusses a method to construct a qualitative model of a nuclear power plant, in order to generate effective diagnostic knowledge. The proposed method is to prepare deep knowledge to be provided to a knowledge compiler based upon qualitative reasoning (QR). Necessity of knowledge compilation for nuclear plant diagnosis will be explained first, and conventionally-experienced problems in qualitative reasoning and a proposed method to overcome this problem is shown next, then a sample procedure to build a qualitative nuclear plant model is demonstrated. (author)

  11. Simulation-based expert system for nuclear reactor control and diagnostics. Progress report

    International Nuclear Information System (INIS)

    This research concerns the development of artificial intelligence (AI) techniques suitable for application to the diagnostics and control of nuclear power plant systems. The overall objective of the current effort is to build a prototype simulation-based expert system for diagnosing accidents in nuclear reactors. The system is being designed to analyze plant data heuristically using fuzzy logic to form a set of hypotheses about a particular transient. Hypothesis testing, fault magnitude estimation and transient analysis is performed using simulation programs to model plant behavior. An adaptive learning technique has been developed for achieving accurate simulations of plant dynamics using low-order physical models of plant components. The results of the diagnostics and simulation analysis of the plant transient are to be analyzed by an expert system for final diagnoses and control guidance. To date, significant progress has been made toward achieving the primary goals of this project. Based on a critical safety functions approach, an overall design for the nuclear plant expert system has been developed. The methodology for performing diagnostic reasoning on plant signals has been developed and the algorithms implemented and tested. A methodology for utilizing the information contained in the physical models of plant components has also been developed. This work included the derivation of a unique Kalman filtering algorithm for using power plant data to systematically improve on-line simulations through the judicious adjustment of key model parameters. A few simulation models of key plant components have been developed and implemented to demonstrate the method on a realistic accident scenario. The chosen transient is a loss of feed flow exasperated by a stuck open relief valve, similar to the initiating event of the Three Mile Island Unit 2 accident in 1979

  12. Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.

    Directory of Open Access Journals (Sweden)

    Athanasios Tsalatsanis

    Full Text Available Dual Processing Theories (DPT assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive and type 2 (deliberative. Based on DPT we have derived a Dual Processing Model (DPM to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.

  13. Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.

    Science.gov (United States)

    Tsalatsanis, Athanasios; Hozo, Iztok; Kumar, Ambuj; Djulbegovic, Benjamin

    2015-01-01

    Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice. PMID:26244571

  14. Numerical experimentation of a diagnostic model of 3-D circulation in the Arabian Sea

    Digital Repository Service at National Institute of Oceanography (India)

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

    Climatic circulation in the upper levels of the Arabian Sea and western equatorial Indian Ocean are computed using a 3-dimensional, 33 level diagnostic circulation model. A steady state solution is obtained within 30 days of model integration. Model...

  15. Impact and cost-effectiveness of current and future tuberculosis diagnostics: the contribution of modelling.

    Science.gov (United States)

    Dowdy, D W; Houben, R; Cohen, T; Pai, M; Cobelens, F; Vassall, A; Menzies, N A; Gomez, G B; Langley, I; Squire, S B; White, R

    2014-09-01

    The landscape of diagnostic testing for tuberculosis (TB) is changing rapidly, and stakeholders need urgent guidance on how to develop, deploy and optimize TB diagnostics in a way that maximizes impact and makes best use of available resources. When decisions must be made with only incomplete or preliminary data available, modelling is a useful tool for providing such guidance. Following a meeting of modelers and other key stakeholders organized by the TB Modelling and Analysis Consortium, we propose a conceptual framework for positioning models of TB diagnostics. We use that framework to describe modelling priorities in four key areas: Xpert(®) MTB/RIF scale-up, target product profiles for novel assays, drug susceptibility testing to support new drug regimens, and the improvement of future TB diagnostic models. If we are to maximize the impact and cost-effectiveness of TB diagnostics, these modelling priorities should figure prominently as targets for future research. PMID:25189546

  16. Model Diagnostics for the Department of Energy's Accelerated Climate Modeling for Energy (ACME) Project

    Science.gov (United States)

    Smith, B.

    2015-12-01

    In 2014, eight Department of Energy (DOE) national laboratories, four academic institutions, one company, and the National Centre for Atmospheric Research combined forces in a project called Accelerated Climate Modeling for Energy (ACME) with the goal to speed Earth system model development for climate and energy. Over the planned 10-year span, the project will conduct simulations and modeling on DOE's most powerful high-performance computing systems at Oak Ridge, Argonne, and Lawrence Berkeley Leadership Compute Facilities. A key component of the ACME project is the development of an interactive test bed for the advanced Earth system model. Its execution infrastructure will accelerate model development and testing cycles. The ACME Workflow Group is leading the efforts to automate labor-intensive tasks, provide intelligent support for complex tasks and reduce duplication of effort through collaboration support. As part of this new workflow environment, we have created a diagnostic, metric, and intercomparison Python framework, called UVCMetrics, to aid in the testing-to-production execution of the ACME model. The framework exploits similarities among different diagnostics to compactly support diagnosis of new models. It presently focuses on atmosphere and land but is designed to support ocean and sea ice model components as well. This framework is built on top of the existing open-source software framework known as the Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT). Because of its flexible framework design, scientists and modelers now can generate thousands of possible diagnostic outputs. These diagnostics can compare model runs, compare model vs. observation, or simply verify a model is physically realistic. Additional diagnostics are easily integrated into the framework, and our users have already added several. Diagnostics can be generated, viewed, and manipulated from the UV-CDAT graphical user interface, Python command line scripts and programs

  17. DIAGNOSTIC FEEDBACK MODEL IN DEVELOPING SPEAKING SKILLS IN ESL LEARNERS – AN EXPERIMENTAL STUDY

    Directory of Open Access Journals (Sweden)

    V. Rajesh, J. Jaya Parveen

    2013-01-01

    Full Text Available Engineering classrooms often contain mixed-ability students with less interest in language study. These students come from different backgrounds and different mediums of instruction. Grammar translation method, communicative approach, or multimedia fail to entertain one or the other group of students in the same classroom. Diagnostic Feedback Model can be utilised for effective language teaching in such mixed-ability classrooms. With a descriptive research design, an evaluative study is conducted in VV College of Engineering, Tisaiyanvilai. 200 students and 10 teachers are involved in the study. Meetings are conducted periodically. Tasks for the pre-tests and criteria for evaluation are designed by the teachers. The pre-assessment contains items to check listening, body language, fluency, and accuracy of the students in speaking. The criteria provides 5 – 1 range of marks for each sub-skill in speaking. The students are made to speak and are evaluated by the teachers using the criteria. Based on the diagnostic feedback model, data consolidation is done by the teachers. The diagnostic feedback model provide the teachers with the strengths and areas of improvement of the students. According to the overall scores, the students are classified into Beginner / Intermediate / Proficient instead of Below Average / Average / Above Average. Activities for each group are defined uniquely, and training is conducted separately for each group. At the end of the course, post-assessments are conducted using the same criteria. In the post-assessments, the average scores of 'Beginners' have increased from 20 to 35, the average scores of 'Intermediate' students have increased from 30 to 43, and the average scores of 'Proficient' students have increased from 40 to 48. This implies that diagnostic feedback model works well in mixed ability classrooms in engineering colleges.

  18. Models of partnership between the pharmaceutical and diagnostics industries around companion diagnostics for cancer and beyond.

    Science.gov (United States)

    Ensinger, Christian

    2011-03-01

    An increase of targeted anticancer therapies has led to the beginning of a new era of cancer treatment, partly by replacing classical chemotherapies, partly supplementing these. Whereas for some substances only clinical experiences are relevant for treatment decisions, for some major cancer groups predictive markers are known that indicate probable tumor responses. To identify the latter, a need for companion diagnostics is given, often already existing as successful cooperation between pharmaceutical and diagnostic industries. This editorial focuses on the impact of companion diagnostic tests in personalized anticancer medicine, reporting recent advances in identifying and characterizing tumor subgroups responding to selected drugs. The most successful targeted therapies are directed against the EGFR/Her-2/neu receptors with regard to their downstream molecules in major cancer groups, including breast, gastric, lung and colorectal carcinomas. The development of biomarkers provides great opportunities to identify subpopulations with differential drug responses. On the one hand patients themselves are gaining major advantages of personalized and better tolerable cancer treatment, on the other hand, owing to very focused targeted therapies, these developments make possible cost-intensive targeted drug investigations and trials, especially in a situation of limited healthcare budgets. PMID:23480583

  19. Learning Diagnostic Diagrams in Transport-Based Data-Collection Systems

    DEFF Research Database (Denmark)

    Tran, Vu The; Eklund, Peter; Cook, Chris

    2014-01-01

    Insights about service improvement in a transit network can be gained by studying transit service reliability. In this paper, a general procedure for constructing a transit service reliability diagnostic (Tsrd) diagram based on a Bayesian network is proposed to automatically build a behavioural...... model from Automatic Vehicle Location (AVL) and Automatic Passenger Counters (APC) data. Our purpose is to discover the variability of transit service attributes and their effects on traveller behaviour. A Tsrd diagram describes and helps to analyse factors affecting public transport by combining domain...... knowledge with statistical data....

  20. The operative diagnostics to adaptation heart to physical load on the base of artificial neuron networks

    Directory of Open Access Journals (Sweden)

    Timoshchenko E.V.

    2010-03-01

    Full Text Available In article are considered questions of the revealing the breach of the warmhearted rhythm beside athlete and athlete during physical load. The estimation of the condition heart was defined as of electrocardiographically of the examination. Mathematical model is designed for interpreting electrocardiogram data on base artificial neuron networks. It is created software, which allows to conduct the diagnostics of the heart diseases in the field of discovery different arrhythmias. Introduction result called on work can render the practical help at determination of the breaches of the warmhearted rhythm.

  1. CHERS software system: A microVAX-based diagnostic

    International Nuclear Information System (INIS)

    The charge exchange recombination spectroscopy (CHERS) diagnostic is the first tokamak fusion test reactor (TFTR) diagnostic to utilize a microVAX II computer for device control, data acquisition, analysis, and event-driven processing. The CHERS system is controlled from a single interactive menu-driven process, enabling the diagnostic physicist to perform interactive device control and monitoring, calibration and control file editing, and to control automatic device setup, data acquisition and display, and postshot analysis. All software is written in fortran. Device control is accomplished using the (ORNL) VAX CAMAC and TAU real-time image processing system (RTIPS) fortran subroutines. Standard VAX system services are utilized, including the use of event flags, global sections, logical names, security services, process control, and spawning of subprocesses

  2. A dynamical model for condition monitoring and fault diagnostics of spur gears

    International Nuclear Information System (INIS)

    The symptoms of condition monitoring and fault diagnostics of machinery based on the dynamic modelling of spur gears are discussed in this paper. The mathematical model presented in the earlier work, assumes two degree of freedom for each gear and the rotor, and also incorporates a varying gear tooth stiffness. This system is assumed to be in good condition (i.e. no fault present). The results obtained from this analytical model are compared with the ones obtained from an experimental model gearbox. This experimental gearbox consists of two meshing spur gears driven by an electric motor. The comparison of the results are encouraging as fundamental (dominant) frequencies of the analytical results correlates very closely to the experimental ones. It is shown that certain vibration frequency of a real gearbox such as the tooth meshing frequencies can be achieved from its mathematical model

  3. Intraoral fiber optic-based diagnostic for periodontal disease

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, P W; Gutierrez, D M; Everett, M J; Brown, S B; Langry, K C; Colston, B W; Roe, J N

    2000-01-21

    The purpose of this initial study was to begin development of a new, objective diagnostic instrument that will allow simultaneous quantitation of multiple proteases within a single periodontal pocket using a chemical fiber optic sensor. This approach could potentially be adapted to use specific antibodies and chemiluminescence to detect and quantitate virtually any compound and compare concentrations of different compounds within the same periodontal pocket. The device could also be used to assay secretions in salivary ducts or from a variety of wounds. The applicability is, therefore, not solely limited to dentistry and the device would be important both for clinical diagnostics and as a research tool.

  4. Diagnostic system based on vibration measurement for rotating machines

    International Nuclear Information System (INIS)

    Large scale electric power plants are equipped with a number of the rotating machines which occupy important positions in the plant system. Therefore, respective users assign several countermeasure to improve their reliability and availability as well, among which the maintenance of such equipment for efficient operation as well as the promotion and strengthening of precautions for safety have now become system requirements. In the above context, we have developed a machinery diagnostic system for rotating machinery, fully utilizing the experience and technology that we have so far developed. This paper indroduces this machinery diagnostic system which was installed at the Tsuruga Nuclear Power Plant of Japan Atomic Power Company. (author)

  5. Diagnostic system based on vibration measurement for rotating machines

    International Nuclear Information System (INIS)

    Large-scale electric power plants have a number of rotating machines which occupy important positions in the plant system. Therefore, respective users assign several countermeasures to improve their reliability and availability. Especially, the maintenance of rotating machines for efficient operation as well as the promotion and strengthening of precautions for safety have now become system requirements. In the above context, we have developed a machinery diagnostic system for rotating machinery, fully utilizing the experience and technology that we have so for developed. This paper introduces the various diagnostic systems for rotating machines. (author)

  6. Study design requirements for RNA sequencing-based breast cancer diagnostics.

    Science.gov (United States)

    Mer, Arvind Singh; Klevebring, Daniel; Grönberg, Henrik; Rantalainen, Mattias

    2016-01-01

    Sequencing-based molecular characterization of tumors provides information required for individualized cancer treatment. There are well-defined molecular subtypes of breast cancer that provide improved prognostication compared to routine biomarkers. However, molecular subtyping is not yet implemented in routine breast cancer care. Clinical translation is dependent on subtype prediction models providing high sensitivity and specificity. In this study we evaluate sample size and RNA-sequencing read requirements for breast cancer subtyping to facilitate rational design of translational studies. We applied subsampling to ascertain the effect of training sample size and the number of RNA sequencing reads on classification accuracy of molecular subtype and routine biomarker prediction models (unsupervised and supervised). Subtype classification accuracy improved with increasing sample size up to N = 750 (accuracy = 0.93), although with a modest improvement beyond N = 350 (accuracy = 0.92). Prediction of routine biomarkers achieved accuracy of 0.94 (ER) and 0.92 (Her2) at N = 200. Subtype classification improved with RNA-sequencing library size up to 5 million reads. Development of molecular subtyping models for cancer diagnostics requires well-designed studies. Sample size and the number of RNA sequencing reads directly influence accuracy of molecular subtyping. Results in this study provide key information for rational design of translational studies aiming to bring sequencing-based diagnostics to the clinic. PMID:26830453

  7. Laser manufacturing for multi-analyte paper-based diagnostic sensors

    OpenAIRE

    Katis, I.N.; He, P.J.W.; Eason, R. W.; Sones, C. L.

    2015-01-01

    We present here our work on the fabrication of paper-based multiplexed diagnostic sensors, using direct-write laser-based processes (Laser Induced Forward Transfer and photo-polymerisation), for the detection of glucose and proteins (BSA).

  8. An expert system for vibration based diagnostics of rotating machines

    International Nuclear Information System (INIS)

    Very often changes in the mechanical condition of the rotating machinery can be observed as changes in its vibration. This paper presents an expert system for vibration-based diagnosis of rotating machines by describing the architecture of the developed prototype system. The importance of modelling the problem solving knowledge as well as the domain knowledge is emphasized by presenting the knowledge in several levels

  9. Simulation-based diagnostics and control for nuclear power plants. Final report, April 15, 1992--April 14, 1995

    International Nuclear Information System (INIS)

    The objective of the project was to develop and test a simulation-based diagnostics and control guidance system that can be used to diagnose and manage off-normal transient events in nuclear power plants. The research has focused on developing two diagnostic approaches suitable for detection and identification of faults involving multiple components, subject to uncertainties in system modeling and observations. The first approach is based on a fuzzy logic framework that can diagnose binary failures using a single-failure diagnostic knowledge base. Construction of the binary-failure knowledge base is accomplished through the use of macroscopic conservation relationships and a fuzzy inference structure is developed to determine the magnitude of faults and the associated certainty. In the second diagnostic approach, an adaptive Kalman filter algorithm is derived to yield information on the type and magnitude of feasible component transitions that can account for system observations. To obtain the likelihood of feasible component failures or degradations, a general probabilistic formulation is developed where statistical distributions associated with component reliability data are explicitly represented. Testing of the diagnostic algorithms has been performed through the analysis of simulated transient events for light water reactor systems. Preliminary studies have been conducted to develop Monte Carlo algorithms for flexible control of transient events

  10. Fetal Implications of Diagnostic Radiation Exposure During Pregnancy: Evidence-based Recommendations.

    Science.gov (United States)

    Rimawi, Bassam H; Green, Victoria; Lindsay, Michael

    2016-06-01

    The purpose of this article is to review the fetal and long-term implications of diagnostic radiation exposure during pregnancy. Evidence-based recommendations for radiologic imaging modalities utilizing exposure of diagnostic radiation during pregnancy, including conventional screen-film mammography, digital mammography, tomosynthesis, and contrast-enhanced mammography are described. PMID:26982251

  11. Deletion diagnostics for the generalised linear mixed model with independent random effects.

    Science.gov (United States)

    Ganguli, B; Roy, S Sen; Naskar, M; Malloy, E J; Eisen, E A

    2016-04-30

    The Generalised linear mixed model (GLMM) is widely used for modelling environmental data. However, such data are prone to influential observations, which can distort the estimated exposure-response curve particularly in regions of high exposure. Deletion diagnostics for iterative estimation schemes commonly derive the deleted estimates based on a single iteration of the full system holding certain pivotal quantities such as the information matrix to be constant. In this paper, we present an approximate formula for the deleted estimates and Cook's distance for the GLMM, which does not assume that the estimates of variance parameters are unaffected by deletion. The procedure allows the user to calculate standardised DFBETAs for mean as well as variance parameters. In certain cases such as when using the GLMM as a device for smoothing, such residuals for the variance parameters are interesting in their own right. In general, the procedure leads to deleted estimates of mean parameters, which are corrected for the effect of deletion on variance components as estimation of the two sets of parameters is interdependent. The probabilistic behaviour of these residuals is investigated and a simulation based procedure suggested for their standardisation. The method is used to identify influential individuals in an occupational cohort exposed to silica. The results show that failure to conduct post model fitting diagnostics for variance components can lead to erroneous conclusions about the fitted curve and unstable confidence intervals. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26626135

  12. Serology-Based Diagnostics for the Control of Bovine Neosporosis.

    Science.gov (United States)

    Guido, Stefano; Katzer, Frank; Nanjiani, Ian; Milne, Elspeth; Innes, Elisabeth A

    2016-02-01

    The protozoan Neospora caninum is a primary infectious cause of abortion in cattle that causes significant economic losses worldwide. Because effective vaccines and licensed pharmacological treatments are currently unavailable, control measures rely on biosecurity and management practice. Serological diagnosis plays a crucial role in the identification of infected animals and several tests have been developed. However, owing to the particular dynamics of the host-parasite interaction and to the characteristics of the currently used diagnostic tools, a proportion of infected cattle may not be reliably identified, and can potentially undermine efforts towards the control of bovine neosporosis. Current diagnostic methods for N. caninum infection in cattle and the advances necessary to support effective control strategies are discussed. PMID:26711188

  13. A computerized data base system for medical diagnostic studies (Diastu).

    Science.gov (United States)

    Rosen, I I; Hall, T C; Mettler, F; Wicks, J; Kelsey, C A; Gustafson, D E

    1980-12-01

    A computerized database system (DIASTU) has been developed for the storage and selective retrieval of the results of medical diagnostic studies. The system is being used to analyze the disease process and the efficacy and yield of selected diagnostic studies. The system runs on a DEC PDP-11/60 computer. It consists of three FORTRAN IV programs linked to a general-purpose assembly language database handler. One program, DSENT, interactively modifies the information in the database. The second, DSLIST, prints all or portions of the database. The third program, DSTAT, interactively assembles the parameters for selective searches of the database and executes them. A query language is used that allows the use of time and size specifications and Boolean operators in nested loops. PMID:7249603

  14. Laser-based temperature diagnostics in practical combustion systems

    OpenAIRE

    Kronemayer, Helmut

    2007-01-01

    Today’s energy supply relies on the combustion of fossil fuels. This results in emissions of toxic pollutants and green-house gases that most likely influence the global climate. Hence, there is a large need for developing efficient combustion processes with low emissions. In order to achieve this, quantitative measurement techniques are required that allow accurate probing of important quantities, such as e.g. the gas temperature, in practical combustion devices. Diagnostic techniques: Ther...

  15. Web-based Diagnostic Imaging Service Using XML Forms

    OpenAIRE

    Hur, Wonchang; Lee, Jaebum; Kim, C. Young

    2006-01-01

    Traditionally, radiology has been conceived as a support department providing patient scanning services to the other clinical departments in a hospital. However, recent advancements in networking technology and related information systems such as picture archiving and communication system (PACS) and radiology information system (RIS) provide new opportunities for inventing different types of diagnostic imaging businesses such as teleradiology. In this article, we examined the business process...

  16. Fuzzy fault diagnostic system based on fault tree analysis

    OpenAIRE

    Yang, Zong Xiao; Suzuki, Kazuhiko; Shimada, Yukiyasu; Sayama, Hayatoshi

    1995-01-01

    A method is presented for process fault diagnosis using information from fault tree analysis and uncertainty/imprecision of data. Fault tree analysis, which has been used as a method of system reliability/safety analysis, provides a procedure for identifying failures within a process. A fuzzy fault diagnostic system is constructed which uses the fuzzy fault tree analysis to represent a knowledge of the causal relationships in process operation and control system. The proposed method is applie...

  17. Diagnostic System for 3D Ultrasonography Based on Gabor Filter

    OpenAIRE

    Wei-Ming Chen; Wen-Lin Chang; Chia-Chen Chang

    2010-01-01

    With the development of the times, people's lifestyle and eating habits are changed a lot. Worldwide, breast cancer is the second most common type of cancer after lung cancer and the fifth most common cause of cancer death. Diagnostic ultrasound (US) of breast cancer is currently the major clinical detection method. It is recognized as a safe, effective, and highly flexible imaging modality capable of providing clinically relevant information about most parts of the body in a rapid and cost-...

  18. Differential Item Functioning Assessment in Cognitive Diagnostic Modeling: Application of the Wald Test to Investigate DIF in the DINA Model

    Science.gov (United States)

    Hou, Likun; de la Torre, Jimmy; Nandakumar, Ratna

    2014-01-01

    Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This…

  19. The SUCCESS model for laboratory performance and execution of rapid molecular diagnostics in patients with sepsis.

    Science.gov (United States)

    Dekmezian, Mhair; Beal, Stacy G; Damashek, Mary Jane; Benavides, Raul; Dhiman, Neelam

    2015-04-01

    Successful performance and execution of rapid diagnostics in a clinical laboratory hinges heavily on careful validation, accurate and timely communication of results, and real-time quality monitoring. Laboratories must develop strategies to integrate diagnostics with stewardship and evidence-based clinical practice guidelines. We present a collaborative SUCCESS model for execution and monitoring of rapid sepsis diagnostics to facilitate timely treatment. Six months after execution of the Verigene Gram-Positive Blood Culture (BC-GP) and the AdvanDx PNA-FISH assays, data were collected on 579 and 28 episodes of bacteremia and fungemia, respectively. Clinical testing was executed using a SUCCESS model comprising the following components: stewardship, utilization of resources, core strategies, concierge services, education, support, and surveillance. Stewardship needs were identified by evaluating the specialty services benefiting from new testing. Utilization of resources was optimized by reviewing current treatment strategies and antibiogram and formulary options. Core strategies consisted of input from infectious disease leadership, pharmacy, and laboratory staff. Concierge services included automated Micro-eUpdate and physician-friendly actionable reports. Education modules were user-specific, and support was provided through a dedicated 24/7 microbiology hotline. Surveillance was performed by daily audit by the director. Using the SUCCESS model, the turnaround time for the detailed report with actionable guidelines to the physician was ∼3 hours from the time of culture positivity. The overall correlation between rapid methods and culture was 94% (546/579). Discrepant results were predominantly contaminants such as a coagulase-negative staphylococci or viridans streptococci in mixed cultures. SUCCESS is a cost-effective and easily adaptable model for clinical laboratories with limited stewardship resources. PMID:25829640

  20. Influence Diagnostics in GARCH Processes

    OpenAIRE

    Xibin Zhang; Maxwell L. King

    2002-01-01

    Influence diagnostics have become an important tool for statistical analysis since the seminal work by Cook (1986). In this paper we present a curvature-based diagnostic to access local influence of minor perturbations on the modified likelihood displacement in a regression model. Using the proposed diagnostic, we study the local influence in the GARCH model under two perturbation schemes which involve, respectively, model perturbation and data perturbation. We find that the curvature-based d...

  1. Flow diagnostics downstream of a tribladed rotor model

    DEFF Research Database (Denmark)

    Naumov, I. V.; Rahmanov, V. V.; Okulov, Valery;

    2012-01-01

    subsequently quantitative data were recorded through velocity field restoration from particle tracks using a stereo PIV system.The study supplied flow diagnostics and recovered the instantaneous 3D velocity fields in the longitudinal cross section behind a tribladed rotor at different values of tip speed ratio...

  2. Prevention of Disease Complications through Diagnostic Models: How to Tackle the Problem of Missing Data?

    OpenAIRE

    Marzban, M; Faramarzi, H; Baneshi, MR

    2012-01-01

    Background: Diagnostic models are frequently used to assess the role of risk factors on disease complications, and therefore to avoid them. Missing data is an issue that challenges the model making. The aim of this study was to develop a diagnostic model to predict death in HIV/AIDS patients when missing data exist. Methods: HIV patients (n=1460) referred to Voluntary Consoling and Testing Center (VCT) of Shiraz southern Iran during 2004–2009 were recruited. Univariate association between var...

  3. Dynamics model for real time diagnostics of Triga RC-1 system

    International Nuclear Information System (INIS)

    This paper presents dynamics model of TRIGA RC-1 reactor system. The model is dedicated to the real-time early fault detection during a reactor operation in one week exploitation cycle. The algorithms are specially suited for real-time, long time and also accelerated simulations with assumed diagnostic oriented accuracy. The approximations, modular structure, numerical methods and validation are discussed. The elaborated model will be build in the TRIGA Supervisor System and TRIGA Diagnostic Simulator

  4. Using a Web-Based Application to Define the Accuracy of Diagnostic Tests When the Gold Standard Is Imperfect

    OpenAIRE

    Lim, C; Wannapinij, P; White, L.; Day, NP; Cooper, BS; Peacock, SJ; Limmathurotsakul, D.

    2013-01-01

    BACKGROUND: Estimates of the sensitivity and specificity for new diagnostic tests based on evaluation against a known gold standard are imprecise when the accuracy of the gold standard is imperfect. Bayesian latent class models (LCMs) can be helpful under these circumstances, but the necessary analysis requires expertise in computational programming. Here, we describe open-access web-based applications that allow non-experts to apply Bayesian LCMs to their own data sets via a user-friendly in...

  5. Automatically Building Diagnostic Bayesian Networks from On-line Data Sources and the SMILE Web-based Interface

    OpenAIRE

    Tungkasthan, Anucha; Jongsawat, Nipat; Poompuang, Pittaya; Intarasema, Sarayut; Premchaiswadi, Wichian

    2010-01-01

    This paper presented a practical framework for automating the building of diagnostic BN models from data sources obtained from the WWW and demonstrates the use of a SMILE web-based interface to represent them. The framework consists of the following components: RSS agent, transformation/conversion tool, core reasoning engine, and the SMILE web-based interface. The RSS agent automatically collects and reads the provided RSS feeds according to the agent's predefined URLs. A transformation/conve...

  6. Air pollution and newly diagnostic autism spectrum disorders: a population-based cohort study in Taiwan.

    Directory of Open Access Journals (Sweden)

    Chau-Ren Jung

    Full Text Available There is limited evidence that long-term exposure to ambient air pollution increases the risk of childhood autism spectrum disorder (ASD. The objective of the study was to investigate the associations between long-term exposure to air pollution and newly diagnostic ASD in Taiwan. We conducted a population-based cohort of 49,073 children age less than 3 years in 2000 that were retrieved from Taiwan National Insurance Research Database and followed up from 2000 through 2010. Inverse distance weighting method was used to form exposure parameter for ozone (O3, carbon monoxide (CO, nitrogen dioxide (NO2, sulfur dioxide (SO2, and particles with aerodynamic diameter less than 10 µm (PM10. Time-dependent Cox proportional hazards (PH model was performed to evaluate the relationship between yearly average exposure air pollutants of preceding years and newly diagnostic ASD. The risk of newly diagnostic ASD increased according to increasing O3, CO, NO2, and SO2 levels. The effect estimate indicating an approximately 59% risk increase per 10 ppb increase in O3 level (95% CI 1.42-1.79, 37% risk increase per 10 ppb in CO (95% CI 1.31-1.44, 340% risk increase per 10 ppb increase in NO2 level (95% CI 3.31-5.85, and 17% risk increase per 1 ppb in SO2 level (95% CI 1.09-1.27 was stable with different combinations of air pollutants in the multi-pollutant models. Our results provide evident that children exposure to O3, CO, NO2, and SO2 in the preceding 1 year to 4 years may increase the risk of ASD diagnosis.

  7. Air pollution and newly diagnostic autism spectrum disorders: a population-based cohort study in Taiwan.

    Science.gov (United States)

    Jung, Chau-Ren; Lin, Yu-Ting; Hwang, Bing-Fang

    2013-01-01

    There is limited evidence that long-term exposure to ambient air pollution increases the risk of childhood autism spectrum disorder (ASD). The objective of the study was to investigate the associations between long-term exposure to air pollution and newly diagnostic ASD in Taiwan. We conducted a population-based cohort of 49,073 children age less than 3 years in 2000 that were retrieved from Taiwan National Insurance Research Database and followed up from 2000 through 2010. Inverse distance weighting method was used to form exposure parameter for ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particles with aerodynamic diameter less than 10 µm (PM10). Time-dependent Cox proportional hazards (PH) model was performed to evaluate the relationship between yearly average exposure air pollutants of preceding years and newly diagnostic ASD. The risk of newly diagnostic ASD increased according to increasing O3, CO, NO2, and SO2 levels. The effect estimate indicating an approximately 59% risk increase per 10 ppb increase in O3 level (95% CI 1.42-1.79), 37% risk increase per 10 ppb in CO (95% CI 1.31-1.44), 340% risk increase per 10 ppb increase in NO2 level (95% CI 3.31-5.85), and 17% risk increase per 1 ppb in SO2 level (95% CI 1.09-1.27) was stable with different combinations of air pollutants in the multi-pollutant models. Our results provide evident that children exposure to O3, CO, NO2, and SO2 in the preceding 1 year to 4 years may increase the risk of ASD diagnosis. PMID:24086549

  8. A Laser-Based Diagnostic Suite for Hypersonic Test Facilities Project

    Data.gov (United States)

    National Aeronautics and Space Administration — In this SBIR effort, Los Gatos Research (LGR) proposes to develop a suite of laser-based diagnostics for the study of reactive and non-reactive hypersonic flows....

  9. Forecast of the Economic- Financial Performance Based on Diagnostic Analysis

    Directory of Open Access Journals (Sweden)

    Daniela Solomon

    2010-12-01

    Full Text Available To ensure efficient financial management is necessary to achieve the forecast of economic and financial performance on the basis of diagnostic analysis, approach most often developed starting from the prediction of turnover and also necessary for shaping an organization's prospects. In financial management, the turnover’s increasing is considered an objective in itself, being interpreted as generating increased market share, profit. Sales condition therefore the entire activity of a company, their variation being considered the main risk factor of enterprise’s economic and financial performance and the staring point in their forecast.

  10. Diagnostics of enterprise bankruptcy occurrence probability in an anti-crisis management: modern approaches and classification of models

    Directory of Open Access Journals (Sweden)

    I.V. Zhalinska

    2015-09-01

    Full Text Available Diagnostics of enterprise bankruptcy occurrence probability is defined as an important tool ensuring the viability of an organization under conditions of unpredictable dynamic environment. The paper aims to define the basic features of diagnostics of bankruptcy occurrence probability models and their classification. The article grounds the objective increasing of crisis probability in modern enterprises where such increasing leads to the need to improve the efficiency of anti-crisis enterprise activities. The system of anti-crisis management is based on the subsystem of diagnostics of bankruptcy occurrence probability. Such a subsystem is the main one for further measures to prevent and overcome the crisis. The classification of existing models of enterprise bankruptcy occurrence probability has been suggested. The classification is based on methodical and methodological principles of models. The following main groups of models are determined: the models using financial ratios, aggregates and scores, the models of discriminated analysis, the methods of strategic analysis, informal models, artificial intelligence systems and the combination of the models. The classification made it possible to identify the analytical capabilities of each of the groups of models suggested.

  11. Gas turbine diagnostic system

    CERN Document Server

    Talgat, Shuvatov

    2011-01-01

    In the given article the methods of parametric diagnostics of gas turbine based on fuzzy logic is proposed. The diagnostic map of interconnection between some parts of turbine and changes of corresponding parameters has been developed. Also we have created model to define the efficiency of the compressor using fuzzy logic algorithms.

  12. Kaluza-Klein Gluons as a Diagnostic of Warped Models

    CERN Document Server

    Lillie, Benjamin Huntington; Tait, Tim M P

    2007-01-01

    We study the properties of $g^{1}$, the first excited state of the gluon in representative variants of the Randall Sundrum model with the Standard Model fields in the bulk. We find that measurements of the coupling to light quarks (from the inclusive cross-section for $pp\\to g^{1} \\to t\\bar t$), the coupling to bottom quarks (from the rate of $pp\\to g^{1} b$), as well as the overall width, can provide powerful discriminants between the models. In models with large brane kinetic terms, the $g^1$ resonance can even potentially be discovered decaying into dijets against the large QCD background. We also derive bounds based on existing Tevatron searches for resonant $t \\bar{t}$ production and find that they require $M_{g^{1}} \\gtrsim 950$ GeV. In addition we explore the pattern of interference between the $g^1$ signal and the non-resonant SM background, defining an asymmetry parameter for the invariant mass distribution. The interference probes the relative signs of the couplings of the $g^{1}$ to light quark pai...

  13. Novel Diagnostic Model for the Deficient and Excess Pulse Qualities

    Directory of Open Access Journals (Sweden)

    Jaeuk U. Kim

    2012-01-01

    Full Text Available The deficient and excess pulse qualities (DEPs are the two representatives of the deficiency and excess syndromes, respectively. Despite its importance in the objectification of pulse diagnosis, a reliable classification model for the DEPs has not been reported to date. In this work, we propose a classification method for the DEPs based on a clinical study. First, through factor analysis and Fisher's discriminant analysis, we show that all the pulse amplitudes obtained at various applied pressures at Chon, Gwan, and Cheok contribute on equal orders of magnitude in the determination of the DEPs. Then, we discuss that the pulse pressure or the average pulse amplitude is appropriate for describing the collective behaviors of the pulse amplitudes and a simple and reliable classification can be constructed from either quantity. Finally, we propose an enhanced classification model that combines the two complementary variables sequentially.

  14. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  15. A model and diagnostic measures for response time series on tests of concentration: Historical background, conceptual framework, and some applications

    OpenAIRE

    Breukelen, G.J.P.; Roskam, E.E.C.I.; Eling, P.A.T.M.; Jansen, R.W.T.L.; Souren, D.A.P.B.; Ickenroth, J.G.M.

    1995-01-01

    Based upon classical hypotheses about accumulating mental fatigue and distraction and its effect on response times, put forward in late 19th and early 20th century papers, a mathematical model is proposed for response times on tests of speed and concentration. The model assumes the random occurrence of very short distractions during information processing. It explains fluctuation and the increasing trend in response times on successive equivalent task units and leads to some simple diagnostic...

  16. Target Diagnostic Instrument-Based Controls Framework for the National Ignition Facility (NIF)

    International Nuclear Information System (INIS)

    The extreme physics of targets shocked by NIF's 192-beam laser are observed by a diverse suite of diagnostics including optical backscatter, time-integrated and gated X-ray sensors, and laser velocity interferometry. Diagnostics to diagnose fusion ignition implosion and neutron emissions are being planned. Many diagnostics will be developed by collaborators at other sites, but ad hoc controls could lead to unreliable and costly operations. An instrument-based controls (I-BC) framework for both hardware and software facilitates development and eases integration. Each complex diagnostic typically uses an ensemble of electronic instruments attached to sensors, digitizers, cameras, and other devices. In the I-BC architecture each instrument is interfaced to a low-cost Windows XP processor and Java application. Each instrument is aggregated with others as needed in the supervisory system to form an integrated diagnostic. The Java framework provides data management, control services and operator GUI generation. I-BCs are reusable by replication and reconfiguration for specific diagnostics in XML. Advantages include minimal application code, easy testing, and better reliability. Collaborators save costs by assembling diagnostics with existing I-BCs. This paper discusses target diagnostic instrumentation used on NIF and presents the I-BC architecture and framework

  17. Present status on atomic and molecular data relevant to fusion plasma diagnostics and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Tawara, H. [ed.

    1997-01-01

    This issue is the collection of the paper presented status on atomic and molecular data relevant to fusion plasma diagnostics and modeling. The 10 of the presented papers are indexed individually. (J.P.N.)

  18. Present status on atomic and molecular data relevant to fusion plasma diagnostics and modeling

    International Nuclear Information System (INIS)

    This issue is the collection of the paper presented status on atomic and molecular data relevant to fusion plasma diagnostics and modeling. The 10 of the presented papers are indexed individually. (J.P.N.)

  19. Diagnostic Evaluation of Ozone Production and Horizontal Transport in a Regional Photochemical Air Quality Modeling System

    Science.gov (United States)

    A diagnostic model evaluation effort has been performed to focus on photochemical ozone formation and the horizontal transport process since they strongly impact the temporal evolution and spatial distribution of ozone (O3) within the lower troposphere. Results from th...

  20. Synchrotron radiation based beam diagnostics at the Fermilab Tevatron

    CERN Document Server

    Thurman-Keup, R; Hahn, A; Hurh, P; Lorman, E; Lundberg, C; Meyer, T; Miller, D; Pordes, S; Valishev, A

    2011-01-01

    Synchrotron radiation has been used for many years as a beam diagnostic at electron accelerators. It is not normally associated with proton accelerators as the intensity of the radiation is too weak to make detection practical. However, if one utilizes the radiation originating near the edge of a bending magnet, or from a short magnet, the rapidly changing magnetic field serves to enhance the wavelengths shorter than the cutoff wavelength, which for more recent high energy proton accelerators such as Fermilab's Tevatron, tends to be visible light. This paper discusses the implementation at the Tevatron of two devices. A transverse beam profile monitor images the synchrotron radiation coming from the proton and antiproton beams separately and provides profile data for each bunch. A second monitor measures the low-level intensity of beam in the abort gaps which poses a danger to both the accelerator's superconducting magnets and the silicon detectors of the high energy physics experiments. Comparisons of measur...

  1. Diagnostic, Predictive and Compositional Modeling with Data Mining in Integrated Learning Environments

    Science.gov (United States)

    Lee, Chien-Sing

    2007-01-01

    Models represent a set of generic patterns to test hypotheses. This paper presents the CogMoLab student model in the context of an integrated learning environment. Three aspects are discussed: diagnostic and predictive modeling with respect to the issues of credit assignment and scalability and compositional modeling of the student profile in the…

  2. New advanced netted ground based and topside radio diagnostics for Space Weather Program

    Science.gov (United States)

    Rothkaehl, Hanna; Krankowski, Andrzej; Morawski, Marek; Atamaniuk, Barbara; Zakharenkova, Irina; Cherniak, Iurii

    2014-05-01

    To give a more detailed and complete understanding of physical plasma processes that govern the solar-terrestrial space, and to develop qualitative and quantitative models of the magnetosphere-ionosphere-thermosphere coupling, it is necessary to design and build the next generation of instruments for space diagnostics and monitoring. Novel ground- based wide-area sensor networks, such as the LOFAR (Low Frequency Array) radar facility, comprising wide band, and vector-sensing radio receivers and multi-spacecraft plasma diagnostics should help solve outstanding problems of space physics and describe long-term environmental changes. The LOw Frequency ARray - LOFAR - is a new fully digital radio telescope designed for frequencies between 30 MHz and 240 MHz located in Europe. The three new LOFAR stations will be installed until summer 2015 in Poland. The LOFAR facilities in Poland will be distributed among three sites: Lazy (East of Krakow), Borowiec near Poznan and Baldy near Olsztyn. All they will be connected via PIONIER dedicated links to Poznan. Each site will host one LOFAR station (96 high-band+96 low-band antennas). They will most time work as a part of European network, however, when less charged, they can operate as a national network The new digital radio frequency analyzer (RFA) on board the low-orbiting RELEC satellite was designed to monitor and investigate the ionospheric plasma properties. This two-point ground-based and topside ionosphere-located space plasma diagnostic can be a useful new tool for monitoring and diagnosing turbulent plasma properties. The RFA on board the RELEC satellite is the first in a series of experiments which is planned to be launched into the near-Earth environment. In order to improve and validate the large scales and small scales ionospheric structures we will used the GPS observations collected at IGS/EPN network employed to reconstruct diurnal variations of TEC using all satellite passes over individual GPS stations and the

  3. Model-based geostatistics

    CERN Document Server

    Diggle, Peter J

    2007-01-01

    Model-based geostatistics refers to the application of general statistical principles of modeling and inference to geostatistical problems. This volume provides a treatment of model-based geostatistics and emphasizes on statistical methods and applications. It also features analyses of datasets from a range of scientific contexts.

  4. Watershed modeling tools and data for prognostic and diagnostic

    Science.gov (United States)

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

    2009-04-01

    's widely used in the world. Watershed models can be characterized by the high number of processes associated simulated. The estimation of these processes is also data intensive, requiring data on topography, land use / land cover, agriculture practices, soil type, precipitation, temperature, relative humidity, wind and radiation. Every year new data is being made available namely by satellite, that has allow to improve the quality of model input and also the calibration of the models (Galvão et. al, 2004b). Tools to cope with the vast amount of data have been developed: data formatting, data retrieving, data bases, metadata bases. The high number of processes simulated in watershed models makes them very wide in terms of output. The SWAT model outputs were modified to produce MOHID compliant result files (time series and HDF). These changes maintained the integrity of the original model, thus guarantying that results remain equal to the original version of SWAT. This allowed to output results in MOHID format, thus making it possible to immediately process it with MOHID visualization and data analysis tools (Chambel-Leitão et. al 2007; Trancoso et. al, 2009). Besides SWAT was modified to produce results files in HDF5 format, this allows the visualization of watershed properties (modeled by SWAT) in animated maps using MOHID GIS. The modified version of SWAT described here has been applied to various national and European projects. Results of the application of this modified version of SWAT to estimate hydrology and nutrients loads to estuaries and water bodies will be shown (Chambel-Leitão, 2008; Yarrow & Chambel-Leitão 2008; Chambel-Leitão et. al 2008; Yarrow & P. Chambel-Leitão, 2007; Yarrow & P. Chambel-Leitão, 2007; Coelho et. al., 2008). Keywords: Watershed models, SWAT, MOHID LAND, Hydrology, Nutrient Loads Arnold, J. G. and Fohrer, N. (2005). SWAT2000: current capabilities and research opportunities in applied watershed modeling. Hydrol. Process. 19, 563

  5. Model-based sensor diagnosis

    International Nuclear Information System (INIS)

    Running a nuclear power plant involves monitoring data provided by the installation's sensors. Operators and computerized systems then use these data to establish a diagnostic of the plant. However, the instrumentation system is complex, and is not immune to faults and failures. This paper presents a system for detecting sensor failures using a topological description of the installation and a set of component models. This model of the plant implicitly contains relations between sensor data. These relations must always be checked if all the components are functioning correctly. The failure detection task thus consists of checking these constraints. The constraints are extracted in two stages. Firstly, a qualitative model of their existence is built using structural analysis. Secondly, the models are formally handled according to the results of the structural analysis, in order to establish the constraints on the sensor data. This work constitutes an initial step in extending model-based diagnosis, as the information on which it is based is suspect. This work will be followed by surveillance of the detection system. When the instrumentation is assumed to be sound, the unverified constraints indicate errors on the plant model. (authors). 8 refs., 4 figs

  6. There is need for antigen-based rapid diagnostic tests to identify common acute tropical illnesses.

    Science.gov (United States)

    Wilde, Henry; Suankratay, Chusana

    2007-01-01

    Enteric fever, typhus, leptospirosis, dengue, melioidosis, and tuberculous meningitis present urgent diagnostic problems that require experience and clinical judgment to make early evidence-based management decisions. Basic and applied research dealing with reliable antigen-based diagnostics has been published and confirmed for several of these infections. This should have initiated commercial production but has not. Established international firms see little profit in such diagnostic kits since they would be used in poor countries with little prospects for return of investment capital. We attempt to illustrate this issue, using common causes of acute febrile illnesses in the Southeast Asian region. We believe that rapid diagnostic technology could prevent significant delay in starting appropriate therapy, reduce hospital expenses, and even save lives. PMID:17617848

  7. Inter-Model Diagnostics for Two Snow Models Across Multiple Western U.S. Locations and Implications for Management

    Science.gov (United States)

    Houle, E. S.; Livneh, B.; Kasprzyk, J. R.

    2014-12-01

    In the western United States, water resource management is increasingly reliant on numerical modeling of hydrological processes, namely snow accumulation and ablation. We seek to advance a framework for providing model diagnostics for such systems by combining an improved understanding of model structural differences (i.e., conceptual vs. physically based) and parameter sensitivities. The two snow models used in this study are SNOW-17, a conceptual degree-day model, and the Variable Infiltration Capacity (VIC) snow model, which is physically based and solves the full water and energy balances. To better understand the performance of these models, several approaches will be used. For the conceptual model, global sensitivity analysis methods (e.g., Sobol' and Method of Morris), and a multi-objective calibration will be applied to identify important parameters and show calibrated parameter values. For the physically based model, we will contribute a novel exploration of some parameters that can be adjusted within the model, including the liquid water holding capacity, the density of newly fallen snow, and the snow roughness. Additionally, the VIC model will be run with explicit radiation inputs at selected sites. For each model run, snow sensitivities and errors (i.e., snow water equivalent results) will be translated into estimated changes in annual water yield for the study areas. Accurately predicting water yield is essential for water management, and it is used here as a practical measure to determine the importance of model parameter sensitivity and calibration. The analysis will be conducted across a range of snow-dominated locations representing a variety of climates across the western United States (e.g. continental, maritime, alpine).

  8. A diagnostic expert system for a boiling water reactor using a dynamic model

    International Nuclear Information System (INIS)

    A diagnostic expert system for abnormal disturbances in a BWR (Boiling Water Reactor) plant has been developed. The peculiar feature of this system is a diagnostic method which combines artificial intelligence technique with numerical analysis technique. The system has three diagnostic functions, 1) identification of anomaly position (device or sensor), 2) identification of anomaly mode and 3) identification of anomaly cause. Function 1) is implemented as follows. First, a hypothesis about anomaly propagation paths is built up by qualitative reasoning, using knowledge of causal relations among observed signals. Next, the abnormal device or sensor is found by applying model reference method and fuzzy set theory to test the hypothesis, using knowledge of plant structure and function, heuristic strategy of diagnosis and module type dynamic simulator. This simulator is composed of basic transfer function modules. The simulation model for the testing region is built up automatically, according to the requirement from the diagnostic task. Function 2) means identification of dynamic characteristics for an anomaly. It is realized by tuning model parameters so as to reproduce the abnormal signal behavior using the non-linear programing method. Function 3) derives probable anomaly causes from heuristic rules between anomaly mode and cause. A basic plant dynamic model was built up and adjusted to dynamic characteristics for one BWR plant (1100MWe). In order to verify the diagnostic functions of this system, data for several abnormal events was compiled by modifying this model. The diagnostic functions were proved useful, through the simulated abnormal data

  9. Advanced Ground Systems Maintenance Physics Models For Diagnostics Project

    Science.gov (United States)

    Perotti, Jose M.

    2015-01-01

    The project will use high-fidelity physics models and simulations to simulate real-time operations of cryogenic and systems and calculate the status/health of the systems. The project enables the delivery of system health advisories to ground system operators. The capability will also be used to conduct planning and analysis of cryogenic system operations. This project will develop and implement high-fidelity physics-based modeling techniques tosimulate the real-time operation of cryogenics and other fluids systems and, when compared to thereal-time operation of the actual systems, provide assessment of their state. Physics-modelcalculated measurements (called “pseudo-sensors”) will be compared to the system real-timedata. Comparison results will be utilized to provide systems operators with enhanced monitoring ofsystems' health and status, identify off-nominal trends and diagnose system/component failures.This capability can also be used to conduct planning and analysis of cryogenics and other fluidsystems designs. This capability will be interfaced with the ground operations command andcontrol system as a part of the Advanced Ground Systems Maintenance (AGSM) project to helpassure system availability and mission success. The initial capability will be developed for theLiquid Oxygen (LO2) ground loading systems.

  10. Diagnostic System for 3D Ultrasonography Based on Gabor Filter

    Directory of Open Access Journals (Sweden)

    Wei-Ming Chen

    2010-12-01

    Full Text Available 800x600 Normal 0 0 2 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 With the development of the times, people's lifestyle and eating habits are changed a lot. Worldwide, breast cancer is the second most common type of cancer after lung cancer and the fifth most common cause of cancer death. Diagnostic ultrasound (US of breast cancer is currently the major clinical detection method. It is recognized as a safe, effective, and highly flexible imaging modality capable of providing clinically relevant information about most parts of the body in a rapid and cost-effective fashion. However, ultrasound imaging usually contains a large number of noises and speckles. That will impact greatly on diagnosis by physicians. Therefore, we proposed a method to enhance the computer-aided diagnosis (CAD of the breast cancer tumors and to reduce detection time and error rate. Experimental investigations demonstrated that the texture variance of 3D ultrasound were effective and useful for differential diagnosis of breast tumors. Texture extraction with proposed method can find malignant more accurate than auto-correlation.

  11. Evaluation of biological sample preparation for immunosignature-based diagnostics.

    Science.gov (United States)

    Chase, Brian Andrew; Johnston, Stephen Albert; Legutki, Joseph Barten

    2012-03-01

    To address the need for a universal system to assess health status, we previously described a method termed "immunosignaturing" which splays the entire humoral antibody repertoire across a peptide microarray. Two important issues relative to the potential broad use of immunosignatures are sample preparation and stability. In the present study, we compared the immunosignatures developed from serum, plasma, saliva, and antibodies eluted from blood dried onto filter paper. We found that serum and plasma provide identical immunosignatures. Immunosignatures derived from dried blood also correlated well with those from nondried serum from the same individual. Immunosignatures derived from dried blood were capable of distinguishing naïve mice from those infected with influenza virus. Saliva was applied to the arrays, and the IgA immunosignature correlated strongly with that from dried blood. Finally, we demonstrate that dried blood retains immunosignature information even when exposed to high temperature. This work expands the potential diagnostic uses for immunosignatures. These features suggest that different forms of archival samples can be used for diagnosis development and that in prospective studies samples can be easily procured. PMID:22237890

  12. Plasma-edge diagnostics based on Pd-MOS diodes

    International Nuclear Information System (INIS)

    Pd metal-oxide-semiconductor (MOS) devices can be used to detect energetic hydrogen atoms. H isotopes implanted into a Pd-MOS diode quickly diffuse through the Pd layer and are accommodated at available Pd-SiO2 interface sites, causing an increase in the leakage current through the device. We find that a diode's response to energetic hydrogen is rapid, sensitive, dosimetric, and reproducible. Pd-MOS diodes can be regenerated when saturated with hydrogen by heating to 100-2000C for a few minutes. These properties make Pd-MOS diodes useful for plasma-edge diagnosis of hydrogen particle fluence when the energy distribution of the incident hydrogen is known. Pd-MOS diode sensors have been used in the laboratory and in the ZT-40M reversed-field pinch to measure energetic hydrogen fluxes. Their small size allows placement in locations inaccessible to conventional diagnostics and should provide a means for remote monitoring of hydrogen fluxes to plasma-facing surfaces. (orig.)

  13. Overview of the Diagnostic Cloud Forecast Model at the Air Force Weather Agency

    Science.gov (United States)

    Hildebrand, E. P.

    2014-12-01

    The Air Force Weather Agency (AFWA) is responsible for running and maintaining the Diagnostic Cloud Forecast (DCF) model to support DoD missions and those of their external partners. The DCF model generates three-dimensional cloud forecasts for global and regional domains at various resolutions. Regional domains are chosen based on Air Force mission needs. DCF is purely a statistical model that can be appended to any numerical weather prediction (NWP) model. Operationally, AFWA runs the DCF model deterministically using GFS data from NCEP and WRF data that are created in-house. In addition, AFWA also runs an ensemble version of the DCF model using the Mesoscale Ensemble Prediction System (MEPS). The deterministic DCF uses predictor variables from the WRF or GFS models, depending on whether the domain is regional or global, and statistically relates them to observed cloud cover from the World-Wide Merged Cloud Analysis (WWMCA). The forecast process of the model uses an ordinal logistic regression to predict membership in one of 101 groups (every 1% from 0-100%). The predicted group membership then is translated into a cloud amount. This is performed on 21 pressure levels ranging from 1000 hPa to 100 hPa. Cloud amount forecasts on these 21 levels are used along with the NWP geopotential height forecasts to estimate the base and top heights of cloud layers in the vertical. DCF also includes routines to estimate the amount and type of cloud within each layer. Forecasts of total cloud amount are verified using the WWMCA, as well as independent sources of cloud data. This presentation will include an overview of the DCF model and its use at AFWA. Results will be presented to show that DCF adds value over the raw cloud forecasts from NWP models. Ideas for future work also will be addressed.

  14. Cost Implications of Value-Based Pricing for Companion Diagnostic Tests in Precision Medicine.

    Science.gov (United States)

    Zaric, Gregory S

    2016-07-01

    Many interpretations of personalized medicine, also referred to as precision medicine, include discussions of companion diagnostic tests that allow drugs to be targeted to those individuals who are most likely to benefit or that allow treatment to be designed in a way such that individuals who are unlikely to benefit do not receive treatment. Many authors have commented on the clinical and competitive implications of companion diagnostics, but there has been relatively little formal analysis of the cost implications of companion diagnostics, although cost reduction is often cited as a significant benefit of precision medicine. We investigate the potential impact on costs of precision medicine implemented through the use of companion diagnostics. We develop a framework in which the costs of companion diagnostic tests are determined by considerations of profit maximization and cost effectiveness. We analyze four scenarios that are defined by the incremental cost-effectiveness ratio of the new drug in the absence of a companion diagnostic test. We find that, in most scenarios, precision medicine strategies based on companion diagnostics should be expected to lead to increases in costs in the short term and that costs would fall only in a limited number of situations. PMID:26899833

  15. Software architecture and design of the web services facilitating climate model diagnostic analysis

    Science.gov (United States)

    Pan, L.; Lee, S.; Zhang, J.; Tang, B.; Zhai, C.; Jiang, J. H.; Wang, W.; Bao, Q.; Qi, M.; Kubar, T. L.; Teixeira, J.

    2015-12-01

    Climate model diagnostic analysis is a computationally- and data-intensive task because it involves multiple numerical model outputs and satellite observation data that can both be high resolution. We have built an online tool that facilitates this process. The tool is called Climate Model Diagnostic Analyzer (CMDA). It employs the web service technology and provides a web-based user interface. The benefits of these choices include: (1) No installation of any software other than a browser, hence it is platform compatable; (2) Co-location of computation and big data on the server side, and small results and plots to be downloaded on the client side, hence high data efficiency; (3) multi-threaded implementation to achieve parallel performance on multi-core servers; and (4) cloud deployment so each user has a dedicated virtual machine. In this presentation, we will focus on the computer science aspects of this tool, namely the architectural design, the infrastructure of the web services, the implementation of the web-based user interface, the mechanism of provenance collection, the approach to virtualization, and the Amazon Cloud deployment. As an example, We will describe our methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks (i.e., Flask, Gunicorn, and Tornado). Another example is the use of Docker, a light-weight virtualization container, to distribute and deploy CMDA onto an Amazon EC2 instance. Our tool of CMDA has been successfully used in the 2014 Summer School hosted by the JPL Center for Climate Science. Students had positive feedbacks in general and we will report their comments. An enhanced version of CMDA with several new features, some requested by the 2014 students, will be used in the 2015 Summer School soon.

  16. Design and development of AXUV-based soft X-ray diagnostic camera for Aditya Tokamak

    International Nuclear Information System (INIS)

    The hot tokamak plasma emits Soft X-rays (SXR) in accordance with the temperature and density which are important to be studied. A silicon photo diode array (AXUV16ELG, Opto-diode, USA) based prototype SXR diagnostics is designed and developed for ADITYA tokamak for the study of SXR radial intensity profile, internal disruption (Saw-tooth crash), MHD instabilities. The diagnostic is having an array of 16 detector of millimeter dimension in a linear configuration. Absolute Extreme Ultra Violate (AXUV) detector offers compact size, improved time response with considerably good quantum efficiency in the soft X-ray range (200 eV to 10 keV). The diagnostic is designed in competence with the ADITYA tokamak protocol. The diagnostic design geometry allows detector view the plasma through a slot hole (0.5 cm X 0.05 cm), 10 μm Beryllium foil filter window, cutting off energies below 750 eV. The diagnostic was installed on Aditya vacuum vessel at radial port no 7 enabling the diagnostics to view the core plasma. The spatial resolution designed for diagnostic configuration is 1.3 cm at plasma centre. The signal generated from SXR detector is acquired with a dedicated single board computer based data acquisition system at 50 kHz. The diagnostic took observation for the ohmically heated plasma. The data was then processed to construct spatial and temporal profile of SXR intensity for Aditya plasma. This information was complimentary to the Silicon surface barrier detector (SBD) based array for the same plasma discharge. The cross calibration between the two was considerably satisfactory under the assumptions considered. (author)

  17. Current and future developments in nucleic acid-based diagnostics

    International Nuclear Information System (INIS)

    The detection and characterization of specific nucleic acids of medico-veterinary pathogens have proven invaluable for diagnostic purposes. Apart from hybridization and sequencing techniques, polymerase chain reaction (PCR) and numerous other methods have contributed significantly to this process. The integration of amplification and signal detection systems, including on-line real-time devices, have increased speed and sensitivity and greatly facilitated the quantification of target nucleic acids. They have also allowed for sequence characterization using melting or hybridization curves. Rugged portable real-time instruments for field use and robotic devices for processing samples are already available commercially. Various stem-loop DNA probes have been designed to have greater specificity for target recognition during real-time PCR. Various DNA fingerprinting techniques or post amplification sequencing are used to type pathogenic strains. Characterization according to DNA sequence is becoming more readily available as automated sequencers become more widely used. Reverse hybridization and to a greater degree DNA micro-arrays, are being used for genotyping related organisms and can allow for the detection of a large variety of different pathogens simultaneously. Non-radioactive labelling of DNA, especially using fluorophores and the principles of fluorescence resonance energy transfer, is now widely used, especially in real-time detection devices. Other detection methods include the use of surface plasmon resonance and MALDI-TOF mass spectrometry. In addition to these technological advances, contributions by bioinformatics and the description of unique signatures of DNA sequences from pathogens will contribute to the development of further assays for monitoring presence of pathogens. An important goal will be the development of robust devices capable of sensitively and specifically detecting a broad spectrum of pathogens that will be applicable for point

  18. Opportunities for improving pLDH-based malaria diagnostic tests

    Directory of Open Access Journals (Sweden)

    Choi Young

    2011-08-01

    Full Text Available Abstract Background Monoclonal antibodies to Plasmodium lactate dehydrogenase (pLDH have been previously used to format immunochromatographic tests for the diagnosis of malaria. Using pLDH as an antigen has several advantages as a sensitive measure of the presence of parasites within patient blood samples. However, variable results in terms of specificity and sensitivity among different commercially available diagnostic kits have been reported and it has not been clear from these studies whether the performance of an individual test is due simply to how it is engineered or whether it is due to the biochemical nature of the pLDH-antibody reaction itself. Methods A series of systematic studies to determine how various pLDH monoclonal antibodies work in combination was undertaken. Different combinations of anti-pLDH monoclonal antibodies were used in a rapid-test immunochromatographic assay format to determine parameters of sensitivity and specificity with regard to individual Plasmodium species. Results Dramatic differences were found in both species specificity and overall sensitivity depending on which antibody is used on the immunochromatographic strip and which is used on the colorimetric colloidal-gold used for visual detection. Discussion The results demonstrate the feasibility of different test formats for the detection and speciation of malarial infections. In addition, the data will enable the development of a universal rapid test algorithm that may potentially provide a cost-effective strategy to diagnose and manage patients in a wide range of clinical settings. Conclusion These data emphasize that using different anti-pLDH antibody combinations offers a tractable way to optimize immunochromatographic pLDH tests.

  19. [The Diagnostics of Detonation Flow External Field Based on Multispectral Absorption Spectroscopy Technology].

    Science.gov (United States)

    Lü, Xiao-jing; Li, Ning; Weng, Chun-sheng

    2016-03-01

    Compared with traditional sampling-based sensing method, absorption spectroscopy technology is well suitable for detonation flow diagnostics, since it can provide with us fast response, nonintrusive, sensitive solution for situ measurements of multiple flow-field parameters. The temperature and concentration test results are the average values along the laser path with traditional absorption spectroscopy technology, while the boundary of detonation flow external field is unknown and it changes all the time during the detonation engine works, traditional absorption spectroscopy technology is no longer suitable for detonation diagnostics. The trend of line strength with temperature varies with different absorption lines. By increasing the number of absorption lines in the test path, more information of the non-uniform flow field can be obtained. In this paper, based on multispectral absorption technology, the reconstructed model of detonation flow external field distribution was established according to the simulation results of space-time conservation element and solution element method, and a diagnostic method of detonation flow external field was given. The model deviation and calculation error of the least squares method adopted were studied by simulation, and the maximum concentration and temperature calculation error was 20.1% and 3.2%, respectively. Four absorption lines of H2O were chosen and detonation flow was scanned at the same time. The detonation external flow testing system was set up for the valveless gas-liquid continuous pulse detonation engine with the diameter of 80 mm. Through scanning H2O absorption lines with a high frequency of 10 kHz, the on-line detection of detonation external flow was realized by direct absorption method combined with time-division multiplexing technology, and the reconstruction of dynamic temperature distribution was realized as well for the first time, both verifying the feasibility of the test method. The test results

  20. Applying the Weisbord model as a diagnostic framework for organizational analysis

    OpenAIRE

    Kontić Ljiljana

    2012-01-01

    This study investigates the effectiveness of the Weisbord's Six Box Model as a diagnostic framework for assessing the factors affecting organizational development. The research area consisted of an international bank which operates in Serbia. In order to identify strengths and weaknesses in the bank, Weisbord's diagnostic questionnaire has been used. Respondents were 137 middle managers in the selected bank. The research results revealed that the bank has strengths in the areas of leadership,...

  1. Product qualification: a barrier to point-of-care microfluidic-based diagnostics?

    Science.gov (United States)

    Tantra, Ratna; van Heeren, Henne

    2013-06-21

    One of the most exciting applications of microfluidics-based diagnostics is its potential use in next generation point-of-care (POC) devices. Many prototypes are already in existence, but, as of yet, few have achieved commercialisation. In this article, we consider the issue surrounding product qualification as a potential barrier to market success. The study discusses, in the context of POC microfluidics-based diagnostics, what the generic issues are and potential solutions. Our findings underline the need for a community-based effort that is necessary to speed up the product qualification process. PMID:23652789

  2. Juvenile retinoschisis: a model for molecular diagnostic testing of X-linked ophthalmic disease.

    OpenAIRE

    Sieving, P A; Yashar, B M; Ayyagari, R

    1999-01-01

    BACKGROUND AND PURPOSE: X-linked juvenile retinoschisis (RS) provides a starting point to define clinical paradigms and understand the limitations of diagnostic molecular testing. The RS phenotype is specific, but the broad severity range is clinically confusing. Molecular diagnostic testing obviates unnecessary examinations for boys at-risk and identifies carrier females who otherwise show no clinical signs. METHODS: The XLRS1 gene has 6 exons of 26-196 base-pair size. Each exon is amplified...

  3. Study of Internet-based Open Remote Diagnostic System

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    With the wide application of information technologi es , Internet-based remote diagnosis (IRD) of plant will surely become the main se rvice mode of corporations in the future. Therefore, it has received a great dea l recognition from academia and the industry. The IRD technology, which is based upon database, computer, and network technologies is the focus of correlative r esearch all over the world. Although some scientific institutions have developed primary IRD systems, their functions are quite narro...

  4. Laser-direct-write methods for fabrication of paper-based medical diagnostic sensors

    OpenAIRE

    Sones, C. L.; Katis, I.N.; He, P.J.W.; Eason, R. W.

    2014-01-01

    We demonstrate the use of laser-based direct-write methods, namely laser-induced forward transfer and laser-induced photo-polymerization as printing and patterning tools for the fabrication of paper-based fluidic sensors that enable affordable point-of-care medical diagnostics

  5. Laser-direct-write technique for rapid prototyping of multiplexed paper-based diagnostic sensors

    OpenAIRE

    He, Peijun; Katis, Ioannis; Eason, Robert; Sones, Collin

    2015-01-01

    We report the successful demonstration of a laser-based direct-write technique for patterning of various porous materials to fabricate more diversified and multifunctional paper-based microfluidic devices that find applications in affordable point-of-care medical diagnostics

  6. Utility of low-order linear nuclear-power-plant models in plant diagnostics and control

    International Nuclear Information System (INIS)

    A low-order, linear model of a pressurized water reactor (PWR) plant is described and evaluated. The model consists of 23 linear, first-order difference equations and simulates all subsystems of both the primary and secondary sides of the plant. Comparisons between the calculated model response and available test data show the model to be an adequate representation of the actual plant dynamics. Suggested use for the model in an on-line digital plant diagnostics and control system are presented

  7. Interlaboratory diagnostic accuracy of a Salmonella specific PCR-based method

    DEFF Research Database (Denmark)

    Malorny, B.; Hoorfar, Jeffrey; Hugas, M.;

    2003-01-01

    A collaborative study involving four European laboratories was conducted to investigate the diagnostic accuracy of a Salmonella specific PCR-based method, which was evaluated within the European FOOD-PCR project (http://www.pcr.dk). Each laboratory analysed by the PCR a set of independent obtained...... presumably naturally contaminated samples and compared the results with the microbiological culture method. The PCR-based method comprised a preenrichment step in buffered peptone water followed by a thermal cell lysis using a closed tube resin-based method. Artificially contaminated minced beef and whole...... investigated. The interlaboratory diagnostic accuracy, i.e. diagnostic specificity and sensitivity, was shown to be 97.5%. The co-amplification of an internal amplification control indicated possible inhibitory substances derived from the sample. This work can contribute to the quality assurance of PCR...

  8. Observational constraints and diagnostics with error bars for time-dependent dark energy models

    CERN Document Server

    Zhang, Hongchao; Xu, Lixin

    2016-01-01

    In this work, three modified diagnostics with error bars via the error propagation equation are proposed and three time-dependent dark energy models are constrained by the cosmic observational data sets from $Planck$ 2015, SNIa, BAO, OHD. Then we distinguish and judge three time-dependent dark energy models by using two combinations of diagnostic, $S^{(1)}_3, S^{(1)}_4, \\epsilon$ and $S^{(1)}_5, S^{(2)}_5, \\epsilon$, with and without error bars respectively in terms of the new values of cosmological parameters. The diagnostics endowed with error bars contain more abundant information than those without error bars and should become a powerful instrument for models distinguishing and analysing. From the phase diagrams with error bars we can not only distinguish different models, but also compare their stability and robustness under the errors generating from the original parameters.

  9. Silicon drift detector based X-ray spectroscopy diagnostic system for the study of non-thermal electrons at Aditya tokamak.

    Science.gov (United States)

    Purohit, S; Joisa, Y S; Raval, J V; Ghosh, J; Tanna, R; Shukla, B K; Bhatt, S B

    2014-11-01

    Silicon drift detector based X-ray spectrometer diagnostic was developed to study the non-thermal electron for Aditya tokamak plasma. The diagnostic was mounted on a radial mid plane port at the Aditya. The objective of diagnostic includes the estimation of the non-thermal electron temperature for the ohmically heated plasma. Bi-Maxwellian plasma model was adopted for the temperature estimation. Along with that the study of high Z impurity line radiation from the ECR pre-ionization experiments was also aimed. The performance and first experimental results from the new X-ray spectrometer system are presented. PMID:25430326

  10. An Embedded Rule-Based Diagnostic Expert System in Ada

    Science.gov (United States)

    Jones, Robert E.; Liberman, Eugene M.

    1992-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  11. Magnetic-Particle-Sensing Based Diagnostic Protocols and Applications

    Directory of Open Access Journals (Sweden)

    Tsukasa Takamura

    2015-06-01

    Full Text Available Magnetic particle-labeled biomaterial detection has attracted much attention in recent years for a number of reasons; easy manipulation by external magnetic fields, easy functionalization of the surface, and large surface-to-volume ratio, to name but a few. In this review, we report on our recent investigations into the detection of nano-sized magnetic particles. First, the detection by Hall magnetic sensor with lock-in amplifier and alternative magnetic field is summarized. Then, our approach to detect sub-200 nm diameter target magnetic particles via relatively large micoro-sized “columnar particles” by optical microscopy is described. Subsequently, we summarize magnetic particle detection based on optical techniques; one method is based on the scattering of the magnetically-assembled nano-sized magnetic bead chain in rotating magnetic fields and the other one is based on the reflection of magnetic target particles and porous silicon. Finally, we report recent works with reference to more familiar industrial products (such as smartphone-based medical diagnosis systems and magnetic removal of unspecific-binded nano-sized particles, or “magnetic washing”.

  12. Infant Hip Joint Diagnostic Support System Based on Clinical Manifestations in X-ray Images

    OpenAIRE

    Honda, Mitsugi; Arita, Seizaburo; Mitani, Shigeru; TAKEDA, Yoshihiro; Ozaki,Toshifumi; Inamura, Keiji; Kanazawa, Susumu

    2010-01-01

    Plain X-ray radiography is frequently used for the diagnosis of developmental dislocation of the hip (DDH). The aim of this study was to construct a diagnostic support system for DDH based on clinical findings obtained from the X-ray images of 154 female infants with confirmed diagnoses made by orthopedists. The data for these subjects were divided into 2 groups. The Min-Max method of nonlinear analysis was applied to the data from Group 1 to construct the diagnostic support system based on t...

  13. Laser direct write techniques for the fabrication of paper-based diagnostic devices

    OpenAIRE

    Katis, Ioannis

    2015-01-01

    We report on the use of laser direct-write techniques for the fabrication of point-of-care paper-based diagnostic sensors. These include laser-based deposition, laser ablation and laser-induced photo-polymerisation. Firstly, Laser Induced Forward Transfer (LIFT) was employed to deposit biomolecules from a donor film onto paper receivers. Paper was chosen as the ideal receiver because of its inherent properties which make it an efficient and suitable platform for point-of-care diagnostic s...

  14. THE APPLICATION OF A DIAGNOSTIC MODEL: AN EMPIRICAL STUDY

    OpenAIRE

    ROXANA STEGEREAN; CORINA GAVREA; ANAMARIA MARIN

    2010-01-01

    The vast majority of managers and consultants use in conducting organizational diagnosis specific models to identify the organizational aspects that proved to be essential in the past. The object of this paper is to apply such a model within a Romanian organization. More specifically we extended the well known Six Box Model to include, besides the six variables (purpose, structure, rewards, mechanisms, relation and leadership), other interest variables such as external environment and organiz...

  15. The road map towards providing a robust Raman spectroscopy-based cancer diagnostic platform and integration into clinic

    Science.gov (United States)

    Lau, Katherine; Isabelle, Martin; Lloyd, Gavin R.; Old, Oliver; Shepherd, Neil; Bell, Ian M.; Dorney, Jennifer; Lewis, Aaran; Gaifulina, Riana; Rodriguez-Justo, Manuel; Kendall, Catherine; Stone, Nicolas; Thomas, Geraint; Reece, David

    2016-03-01

    Despite the demonstrated potential as an accurate cancer diagnostic tool, Raman spectroscopy (RS) is yet to be adopted by the clinic for histopathology reviews. The Stratified Medicine through Advanced Raman Technologies (SMART) consortium has begun to address some of the hurdles in its adoption for cancer diagnosis. These hurdles include awareness and acceptance of the technology, practicality of integration into the histopathology workflow, data reproducibility and availability of transferrable models. We have formed a consortium, in joint efforts, to develop optimised protocols for tissue sample preparation, data collection and analysis. These protocols will be supported by provision of suitable hardware and software tools to allow statistically sound classification models to be built and transferred for use on different systems. In addition, we are building a validated gastrointestinal (GI) cancers model, which can be trialled as part of the histopathology workflow at hospitals, and a classification tool. At the end of the project, we aim to deliver a robust Raman based diagnostic platform to enable clinical researchers to stage cancer, define tumour margin, build cancer diagnostic models and discover novel disease bio markers.

  16. Diagnostics of gas turbines based on changes in thermodynamics parameters

    OpenAIRE

    Hocko Marián; Klimko Marek

    2016-01-01

    This article is focused on solving the problems of determining the true state of gas turbine based on measured changes in thermodynamic parameters. Dependence between the real individual parts for gas turbines and changing the thermodynamic parameters were experimentally verified and confirmed on a small jet engine MPM-20 in the laboratory of the Department of Aviation Engineering at Technical University in Košice. The results of experiments confirm that the wear and tear of basic parts for g...

  17. Current Development of Saliva/Oral fluid-based Diagnostics

    OpenAIRE

    Yeh, Chih-Ko; Christodoulides, Nicolaos J.; Floriano, Pierre N.; Miller, Craig S.; Ebersole, Jeffrey L.; Weigum, Shannon E.; McDevitt, John; Redding, Spencer W.

    2010-01-01

    Saliva can be easily obtained in medical and non-medical settings, and contains numerous bio-molecules, including those typically found in serum for disease detection and monitoring. In the past two decades, the achievements of high-throughput approaches afforded by biotechnology and nanotechnology allow for disease-specific salivary biomarker discovery and establishment of rapid, multiplex, and miniaturized analytical assays. These developments have dramatically advanced saliva-based diagnos...

  18. Comprehensive examination of the trans-diagnostic cognitive behavioral model of eating disorders in males.

    Science.gov (United States)

    Dakanalis, Antonios; Timko, C Alix; Clerici, Massimo; Zanetti, M Assunta; Riva, Giuseppe

    2014-01-01

    The Trans-diagnostic Model (TM) of eating pathology describes how one or more of four hypothesized mechanisms (i.e., mood intolerance, core low self-esteem, clinical perfectionism and interpersonal difficulties) may interrelate with each other and with the core psychopathology of eating disorders (i.e., over-evaluation of weight and shape) to maintain the disordered behaviors. Although a cognitive behavioral treatment based on the TM has shown to be effective in treating eating disorders, the model itself has undergone only limited testing. This is the first study to both elaborate and test the validity of the TM in a large sample (N=605) of undergraduate men. Body mass index was controlled within structural equation modeling analyses. Although not all expected associations for the maintenance variables were significant, overall the validity of the model was supported. Concern about shape and weight directly led to exercise behaviors. There was a direct path from binge eating to exercise and other forms of compensatory behaviors (i.e., purging); but no significant path from restriction to binge eating. Of the maintaining factors, mood intolerance was the only maintaining variable directly linked to men's eating disorder symptoms. The other three maintaining factors of the TM indirectly impacted restriction through concerns about shape and weight, whereas only interpersonal difficulties predicted low self-esteem and binge eating. Potential implications for understanding and targeting eating disturbances in men are discussed. PMID:24411752

  19. Diagnostics of gas turbines based on changes in thermodynamics parameters

    Science.gov (United States)

    Hocko, Marián; Klimko, Marek

    2016-03-01

    This article is focused on solving the problems of determining the true state of gas turbine based on measured changes in thermodynamic parameters. Dependence between the real individual parts for gas turbines and changing the thermodynamic parameters were experimentally verified and confirmed on a small jet engine MPM-20 in the laboratory of the Department of Aviation Engineering at Technical University in Košice. The results of experiments confirm that the wear and tear of basic parts for gas turbines (turbo-compressor engines) to effect the change of thermodynamic parameters of the engine.

  20. Diagnostics of gas turbines based on changes in thermodynamics parameters

    Directory of Open Access Journals (Sweden)

    Hocko Marián

    2016-01-01

    Full Text Available This article is focused on solving the problems of determining the true state of gas turbine based on measured changes in thermodynamic parameters. Dependence between the real individual parts for gas turbines and changing the thermodynamic parameters were experimentally verified and confirmed on a small jet engine MPM-20 in the laboratory of the Department of Aviation Engineering at Technical University in Košice. The results of experiments confirm that the wear and tear of basic parts for gas turbines (turbo-compressor engines to effect the change of thermodynamic parameters of the engine.

  1. Statefinder Diagnostic for Phantom Model with V(φ)= V0exp(-λφ2)

    Institute of Scientific and Technical Information of China (English)

    CHANG Bao-Rong; LIU Hong-Ya; XU Li-Xin; ZHANG Cheng-Wu

    2007-01-01

    We investigate the phantom field with potential V(φ) = V0 exp(-λφ2) and dark matter in the spatially flat Friedman-Robertson-Walker model. It has been shown by numerical calculation that there is a attractor solution in this model. We also apply the statefinder diagnostic to this phantom model. It is shown that the evolving trajectories of this scenario in the s - r diagram is quite different from other dark energy models.

  2. A pilot study using laser-based technique for non-invasive diagnostics of hypertensive conditions in mice

    Science.gov (United States)

    Litvinova, Karina S.; Ahmad, Shakil; Wang, Keqing; Rafailov, Ilya E.; Sokolovski, Sergei G.; Zhang, Lin; Rafailov, Edik U.; Ahmed, Asif

    2016-02-01

    Endothelial dysfunction is directly linked to preeclampsia, a maternal hypertensive condition that is life threating for both the mother and the baby. Epidemiological studies show that women with a history of pre-eclampsia have an elevated risk for cardiovascular disease. Here we report a new non-invasive diagnostic test for preeclampsia in mice that allows us to non-invasively assess the condition of the animals during the experiment and treatment in established models of preeclampsia. A laser-based multifunctional diagnostics system (LAKK-M) was chosen to carry out non-invasive analysis of multiple parameters. The device was used to simultaneously record the microcirculatory blood flow and oxygen saturation, as well as fluorescence levels of endogenous fluorophores. Preliminary experiments were conducted on adenoviral (Ad-)- mediated overexpression of sFlt-1 (Ad-sFlt-1) to mimic preeclampsialike symptoms in mice. The recorded data displayed the ability of the LAKK-M diagnostics device to detect significant differences in perfusion measurements between the control and Ad-sFlt-1 treatment. Preliminary results provide a potential avenue to employ these diagnostics technology to monitor and aid in maintaining control of live animal conditions throughout the experiment and treatment.

  3. Diagnostic software and fault tolerant microprocessor based system architectures

    International Nuclear Information System (INIS)

    In numerous industrial applications including power generation, the availability of electronic systems to perform the tasks assigned has become a major issue. At the same time, the functional complexity of these systems has increased enormously. Fortunately, the arrival of cost effective microprocessor based hardware has given the system designer a cadre of techniques to ensure the desired degree of system integrity and availability. These include: dynamic redundancy, isolation, functional diversity, built-in self-tests, embedded test subsystems, communications, error checking and error correcting codes, etc. The choice among the available techniques is generally heuristic and depends greatly on the structure of major components and systems external to the electronic system itself as well as the postulated faults and their relative frequency. Indiscriminate use of these techniques will inevitably increase cost and reduce maintainability while actually reducing system availability and reliability. The issues and the application of these techniques are discussed by describing recent examples of fault tolerant microprocessor based system architectures which include the Plant Safety Monitoring System, the EAGLE-21 Process Protection System and the Advanced Rod Position Indication System for pressurized water reactors. Each of these systems utilize unique internal architectures that address the reliability, availability, and the communications issues while improving maintainability and man-machine interfaces

  4. ETHERNET BASED EMBEDDED SYSTEM FOR FEL DIAGNOSTICS AND CONTROLS

    International Nuclear Information System (INIS)

    An Ethernet based embedded system has been developed to upgrade the Beam Viewer and Beam Position Monitor (BPM) systems within the free-electron laser (FEL) project at Jefferson Lab. The embedded microcontroller was mounted on the front-end I/O cards with software packages such as Experimental Physics and Industrial Control System (EPICS) and Real Time Executive for Multiprocessor System (RTEMS) running as an Input/Output Controller (IOC). By cross compiling with the EPICS, the RTEMS kernel, IOC device supports, and databases all of these can be downloaded into the microcontroller. The first version of the BPM electronics based on the embedded controller was built and is currently running in our FEL system. The new version of BPM that will use a Single Board IOC (SBIOC), which integrates with an Field Programming Gate Array (FPGA) and a ColdFire embedded microcontroller, is presently under development. The new system has the features of a low cost IOC, an open source real-time operating system, plug and play-like ease of installation and flexibility, and provides a much more localized solution

  5. ETHERNET BASED EMBEDDED SYSTEM FOR FEL DIAGNOSTICS AND CONTROLS

    Energy Technology Data Exchange (ETDEWEB)

    Jianxun Yan; Daniel Sexton; Steven Moore; Albert Grippo; Kevin Jordan

    2006-10-24

    An Ethernet based embedded system has been developed to upgrade the Beam Viewer and Beam Position Monitor (BPM) systems within the free-electron laser (FEL) project at Jefferson Lab. The embedded microcontroller was mounted on the front-end I/O cards with software packages such as Experimental Physics and Industrial Control System (EPICS) and Real Time Executive for Multiprocessor System (RTEMS) running as an Input/Output Controller (IOC). By cross compiling with the EPICS, the RTEMS kernel, IOC device supports, and databases all of these can be downloaded into the microcontroller. The first version of the BPM electronics based on the embedded controller was built and is currently running in our FEL system. The new version of BPM that will use a Single Board IOC (SBIOC), which integrates with an Field Programming Gate Array (FPGA) and a ColdFire embedded microcontroller, is presently under development. The new system has the features of a low cost IOC, an open source real-time operating system, plug&play-like ease of installation and flexibility, and provides a much more localized solution.

  6. Residual diagnostics for cross-section time series regression models

    OpenAIRE

    Baum, Christopher F

    2001-01-01

    These routines support the diagnosis of groupwise heteroskedasticity and cross-sectional correlation in the context of a regression model fit to pooled cross-section time series (xt) data. Copyright 2001 by Stata Corporation.

  7. Analysis of Chronic Temporomandibular Disorders Based on the Latest Diagnostic Criteria

    Directory of Open Access Journals (Sweden)

    Svechtarov V.

    2015-05-01

    Full Text Available The objective of this study is to analyze the distribution of the most common diagnoses observed in patients with chronic temporomandibular disorders, based on the new diagnostic criteria (DC/TMD adopted in 2014. The previous Research Diagnostic Criteria (RDC/TMD adopted in 1992, consisted of three main groups of eight diagnostic subgroups and is currently transformed into two main groups and twelve subgroups, respectively. All subgroups correspond to the nomenclature of the ICD-10. The new clinical diagnostic indices are also modified. The analysis showed a prevalence of Pain-Related TMD compared with that of intra-articular disorders in ratio 57.89% to 42.10%. In Pain-Related TMD arthralgia was represented in 55% of cases; local myalgia - in 12%, myofascial pain - in 18%, myofascial pain with referral - in 14%, headache attributed to TMD - in 1%. In Intra-articular TMD disc displacement with reduction was found in 23% of the cases, disc displacement with reduction with intermittent locking - in 3%, disc displacement without reduction with limited opening - in 25%, disc displacement without reduction and without limited opening - in 8%. Degenerative diseases were found in 14.28%, and hypermobility and subluxations - in 26.98%. These analyzes differ and can only partly be compared with previous analyzes based on RDC system. The changes in the diagnostic criteria require new clinical studies in order to refine the picture of temporomandibular pathology in accordance with the modern views on the matter.

  8. EDGE2D modelling of edge profiles obtained in JET diagnostic optimized configuration

    Energy Technology Data Exchange (ETDEWEB)

    Kallenbach, A [MPI fuer Plasmaphysik, EURATOM Association, D-85748 Garching (Germany); Andrew, Y [EURATOM/UKAEA Fusion Association, Culham (United Kingdom); Beurskens, M [FOM-Rijnhuizen, Ass. Euratom-FOM, TEC (Netherlands); Corrigan, G [EURATOM/UKAEA Fusion Association, Culham (United Kingdom); Eich, T [MPI fuer Plasmaphysik, EURATOM Association, D-85748 Garching (Germany); Jachmich, S [ERM, Brussels (Belgium); Kempenaars, M [FOM-Rijnhuizen, Ass. Euratom-FOM, TEC (Netherlands); Korotkov, A [EURATOM/UKAEA Fusion Association, Culham (United Kingdom); Loarte, A [EFDA Close Support Unit, Garching (Germany); Matthews, G [EURATOM/UKAEA Fusion Association, Culham (United Kingdom); Monier-Garbet, P [CEA Cadarache (France); Saibene, G [EFDA Close Support Unit, Garching (Germany); Spence, J [EURATOM/UKAEA Fusion Association, Culham (United Kingdom); Suttrop, W [MPI fuer Plasmaphysik, EURATOM Association, D-85748 Garching (Germany)

    2004-03-01

    Nine type-I ELMy H-mode discharges in diagnostic optimized configuration in JET are analysed with the EDGE2D/NIMBUS package. EDGE2D solves the fluid equations for the conservation of particles, momentum and energy for hydrogenic and impurity ions, while neutrals are followed with the two-dimensional Monte Carlo module NIMBUS. Using external boundary conditions from the experiment, the perpendicular heat conductivities {chi}{sub i,e} and the particle transport coefficients D, v are varied until good agreement between code result and measured data is obtained. A step-like ansatz is used for the edge transport parameters for the outer core region, the edge transport barrier and the outer scrape-off layer. The time-dependent effect of edge localized modes on the edge profiles is simulated with an ad hoc ELM model based on the repetitive increase of the transport coefficients {chi}{sub i,e} and D. The values of the transport coefficients are matched to experimental data mapped to the outer midplane, in the course of which radial shifts of experimental profiles of the order of 1 cm caused by the accuracy limit of the equilibrium reconstruction are taken into account. Simulated divertor profiles obtained from the upstream transport ansatz and the experimental boundary conditions agree with measurements, except a small region localized at the separatrix strike points which is supposed to be affected by direct ion losses. The integrated analysis using EDGE2D modelling, although still limited by the marginal spatial resolution of individual diagnostics, allows the characterization of profiles in the edge/pedestal region and supplies additional information on the separatrix position. The steep density gradient zone inside the separatrix shrinks compared to the electron temperature with increasing density, indicating the effect of the neutral penetration depth becoming shorter than the region of reduced transport.

  9. Statefinder Diagnostic for Dark Energy Models in Bianchi I Universe

    CERN Document Server

    Sharif, M

    2013-01-01

    In this paper, we investigate the statefinder, the deceleration and equation of state parameters when universe is composed of generalized holographic dark energy or generalized Ricci dark energy for Bianchi I universe model. These parameters are found for both interacting as well as non-interacting scenarios of generalized holographic or generalized Ricci dark energy with dark matter and generalized Chaplygin gas. We explore these parameters graphically for different situations. It is concluded that these models represent accelerated expansion of the universe.

  10. Biomarkers in schizophrenia: A focus on blood based diagnostics and theranostics.

    Science.gov (United States)

    Lai, Chi-Yu; Scarr, Elizabeth; Udawela, Madhara; Everall, Ian; Chen, Wei J; Dean, Brian

    2016-03-22

    Identifying biomarkers that can be used as diagnostics or predictors of treatment response (theranostics) in people with schizophrenia (Sz) will be an important step towards being able to provide personalized treatment. Findings from the studies in brain tissue have not yet been translated into biomarkers that are practical in clinical use because brain biopsies are not acceptable and neuroimaging techniques are expensive and the results are inconclusive. Thus, in recent years, there has been search for blood-based biomarkers for Sz as a valid alternative. Although there are some encouraging preliminary data to support the notion of peripheral biomarkers for Sz, it must be acknowledged that Sz is a complex and heterogeneous disorder which needs to be further dissected into subtype using biological based and clinical markers. The scope of this review is to critically examine published blood-based biomarker of Sz, focusing on possible uses for diagnosis, treatment response, or their relationship with schizophrenia-associated phenotype. We sorted the studies into six categories which include: (1) brain-derived neurotrophic factor; (2) inflammation and immune function; (3) neurochemistry; (4) oxidative stress response and metabolism; (5) epigenetics and microRNA; and (6) transcriptome and proteome studies. This review also summarized the molecules which have been conclusively reported as potential blood-based biomarkers for Sz in different blood cell types. Finally, we further discusses the pitfall of current blood-based studies and suggest that a prediction model-based, Sz specific, blood oriented study design as well as standardize blood collection conditions would be useful for Sz biomarker development. PMID:27014601

  11. Current and future developments in nucleic acid-based diagnostics

    International Nuclear Information System (INIS)

    The detection and characterization of specific nucleic acids of protozoa, rickettsia, bacteria and viruses have proven to be particularly useful for detecting pathogens of human and veterinary importance. It is also proving an invaluable tool for surveillance purposes and as a means of ensuring food security. Previous approaches towards pathogen isolation have often been tedious or even impossible. PCR, first conceived by Mullis in 1983, has proven to be a revolutionary technique for the rapid and accurate detection of numerous pathogens. The discovery and cloning of thermostable DNA polymerases has further contributed to this technology. Many additional developments, based on the basic principles of PCR, have been described e.g. RT-PCR, NASBA, RAPD, AFLP, LCR, PCR ELISA, strand displacement amplification (SDA), transcription-mediated amplification (TMA), branched DNA (bDNA), hybrid capture, immunocapture PCR. This list continues to expand with new variations on basic PCR principles. Improvements in thermocyclers involve the development of integrated amplification and signal detection systems, including on-line real-time devices. In addition, rugged portable instruments have been designed for field use. These are particularly useful as systems for early warning in detecting biowarfare agents and outbreaks of cross-boundary and other pathogens. Fluorophores, utilising principles of fluorescence resonance energy transfer, are used as labels for probes in such real-time assays. Molecular beacon technology also utilises such mechanisms. Real-time thermocyclers allow the monitoring of amplified DNA as well as establishing sequence characteristics based on melting or hybridisation curves. Taqman chemistry makes use of such a system. Stem-loop DNA probes have been designed to have increased specificity for target recognition and include molecular beacon methodologies, suppression PCR approaches and hairpin probes in DNA microarrays. Automated sample processing or robotic

  12. A web-based test of residents' skills in diagnostic radiology

    International Nuclear Information System (INIS)

    To develop an objective, Web-based tool for evaluating residents' knowledge of diagnostic radiology. We developed and tested a Web-based evaluation tool (the Diagnostic Radiology Skills Test) that consists of 3 tests, one in each of 3 domains of diagnostic radiology: chest, gastrointestinal, and musculoskeletal imaging. Each test comprises 30 cases representing a range of difficulty in the domain, including normal states, normal variants, typical cases of common diagnoses, and cases with more subtle findings. Cases are presented with a long menu of domain-specific possible diagnoses (response options), each coded for diagnostic appropriateness. Our subjects were 21 residents in postgraduate year (PGY) 2 to 5 and 11 experts in diagnostic radiology. Subjects accessed the tool via a Web site on our Web server. Residents test results were compared for reliability and validity across domain, case, and training level. In addition, results were correlated with commonly used established and objective evaluation tools. The tool demonstrated consistent monotonic improvement in performance with training level. It showed acceptable reliability in discriminating between residents at different performance levels, both within and across training levels (r = 0.53 within level and 0.69 across levels). Test results also had concurrent validity against the American College of Radiology In-Training Examination, a widely accepted objective assessment tool (r = 0.65, P < 0.01), and 2 Objective Structured Clinical Examinations (OSCEs) focusing on diagnostic skills (r = 0.78 and r 0.69, P < 0.01, respectively). Our study demonstrates the feasibility of a Web-based, standardized, objective assessment method for evaluating residents' performance. (author)

  13. Neural-network-based state of health diagnostics for an automated radioxenon sampler/analyzer

    Science.gov (United States)

    Keller, Paul E.; Kangas, Lars J.; Hayes, James C.; Schrom, Brian T.; Suarez, Reynold; Hubbard, Charles W.; Heimbigner, Tom R.; McIntyre, Justin I.

    2009-05-01

    Artificial neural networks (ANNs) are used to determine the state-of-health (SOH) of the Automated Radioxenon Analyzer/Sampler (ARSA). ARSA is a gas collection and analysis system used for non-proliferation monitoring in detecting radioxenon released during nuclear tests. SOH diagnostics are important for automated, unmanned sensing systems so that remote detection and identification of problems can be made without onsite staff. Both recurrent and feed-forward ANNs are presented. The recurrent ANN is trained to predict sensor values based on current valve states, which control air flow, so that with only valve states the normal SOH sensor values can be predicted. Deviation between modeled value and actual is an indication of a potential problem. The feed-forward ANN acts as a nonlinear version of principal components analysis (PCA) and is trained to replicate the normal SOH sensor values. Because of ARSA's complexity, this nonlinear PCA is better able to capture the relationships among the sensors than standard linear PCA and is applicable to both sensor validation and recognizing off-normal operating conditions. Both models provide valuable information to detect impending malfunctions before they occur to avoid unscheduled shutdown. Finally, the ability of ANN methods to predict the system state is presented.

  14. Neural Network Based State of Health Diagnostics for an Automated Radioxenon Sampler/Analyzer

    International Nuclear Information System (INIS)

    Artificial neural networks (ANNs) are used to determine the state-of-health (SOH) of the Automated Radioxenon Analyzer/Sampler (ARSA). ARSA is a gas collection and analysis system used for non-proliferation monitoring in detecting radioxenon released during nuclear tests. SOH diagnostics are important for automated, unmanned sensing systems so that remote detection and identification of problems can be made without onsite staff. Both recurrent and feed-forward ANNs are presented. The recurrent ANN is trained to predict sensor values based on current valve states, which control air flow, so that with only valve states the normal SOH sensor values can be predicted. Deviation between modeled value and actual is an indication of a potential problem. The feed-forward ANN acts as a nonlinear version of principal components analysis (PCA) and is trained to replicate the normal SOH sensor values. Because of ARSA's complexity, this nonlinear PCA is better able to capture the relationships among the sensors than standard linear PCA and is applicable to both sensor validation and recognizing off-normal operating conditions. Both models provide valuable information to detect impending malfunctions before they occur to avoid unscheduled shutdown. Finally, the ability of ANN methods to predict the system state is presented

  15. Neural Network Based State of Health Diagnostics for an Automated Radioxenon Sampler/Analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Keller, Paul E.; Kangas, Lars J.; Hayes, James C.; Schrom, Brian T.; Suarez, Reynold; Hubbard, Charles W.; Heimbigner, Tom R.; McIntyre, Justin I.

    2009-05-13

    Artificial neural networks (ANNs) are used to determine the state-of-health (SOH) of the Automated Radioxenon Analyzer/Sampler (ARSA). ARSA is a gas collection and analysis system used for non-proliferation monitoring in detecting radioxenon released during nuclear tests. SOH diagnostics are important for automated, unmanned sensing systems so that remote detection and identification of problems can be made without onsite staff. Both recurrent and feed-forward ANNs are presented. The recurrent ANN is trained to predict sensor values based on current valve states, which control air flow, so that with only valve states the normal SOH sensor values can be predicted. Deviation between modeled value and actual is an indication of a potential problem. The feed-forward ANN acts as a nonlinear version of principal components analysis (PCA) and is trained to replicate the normal SOH sensor values. Because of ARSA’s complexity, this nonlinear PCA is better able to capture the relationships among the sensors than standard linear PCA and is applicable to both sensor validation and recognizing off-normal operating conditions. Both models provide valuable information to detect impending malfunctions before they occur to avoid unscheduled shutdown. Finally, the ability of ANN methods to predict the system state is presented.

  16. Prodiag--a hybrid artificial intelligence based reactor diagnostic system for process faults

    International Nuclear Information System (INIS)

    Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL) are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA), project to perform feasibility studies on a novel approach to Artificial Intelligence (Al) based diagnostics for component faults in nuclear power plants. Investigations are being performed in the construction of a first-principles physics-based plant level process diagnostic expert system (ES) and the identification of component-level fault patterns through operating component characteristics using artificial neural networks (ANNs). The purpose of the proof-of-concept project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use thermal hydraulic (T-H) signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance.To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. A full-scope operator training simulator representing the Commonwealth Edison Braidwood nuclear power plant is being used both as the source of development data and as the means to evaluate the advantages of the proposed diagnostic system. This is an ongoing multi-year project and this paper presents the results to date of the CRADA phase

  17. Polyethersulfone improves isothermal nucleic acid amplification compared to current paper-based diagnostics.

    Science.gov (United States)

    Linnes, J C; Rodriguez, N M; Liu, L; Klapperich, C M

    2016-04-01

    Devices based on rapid, paper-based, isothermal nucleic acid amplification techniques have recently emerged with the potential to fill a growing need for highly sensitive point-of-care diagnostics throughout the world. As this field develops, such devices will require optimized materials that promote amplification and sample preparation. Herein, we systematically investigated isothermal nucleic acid amplification in materials currently used in rapid diagnostics (cellulose paper, glass fiber, and nitrocellulose) and two additional porous membranes with upstream sample preparation capabilities (polyethersulfone and polycarbonate). We compared amplification efficiency from four separate DNA and RNA targets (Bordetella pertussis, Chlamydia trachomatis, Neisseria gonorrhoeae, and Influenza A H1N1) within these materials using two different isothermal amplification schemes, helicase dependent amplification (tHDA) and loop-mediated isothermal amplification (LAMP), and traditional PCR. We found that the current paper-based diagnostic membranes inhibited nucleic acid amplification when compared to membrane-free controls; however, polyethersulfone allowed for efficient amplification in both LAMP and tHDA reactions. Further, observing the performance of traditional PCR amplification within these membranes was not predicative of their effects on in situ LAMP and tHDA. Polyethersulfone is a new material for paper-based nucleic acid amplification, yet provides an optimal support for rapid molecular diagnostics for point-of-care applications. PMID:26906904

  18. Diagnostic value of radionuclides basing on the theory of taking decisions

    International Nuclear Information System (INIS)

    The most spread methodological approaches to the assessement of radionuclide tests basing on the decision making theory are considered. Described are: decision matrix, test index and index of specific use of a series of diagnostic tests. The above methods may be used for comparative evaluation of different tests ignoring assessment of the law distribution of digital values of the test investigated

  19. Tile concrete base materials as substitutes for lead shielding installations diagnostic X-ray

    International Nuclear Information System (INIS)

    In this paper we study the damping characteristics in the energy range of medical diagnostic X-ray product XRAD trade name manufactured by Construction Radiotherapy Techniques (CTRADC) consisting of different composition tile with concrete base, for its characterization as a substitute shielding material lead.

  20. Network design of data monitoring subsystem based on ethernet of technical diagnostic system for EAST tokamak

    International Nuclear Information System (INIS)

    This article introduces a network design of the data monitoring subsystem based on Ethernet of the technical diagnostic system for EAST Tokamak. How to realize network safety is mostly described. It has been proved a reliable network with good real-time and safe performance by experiments last year. (authors)

  1. Learning Diagnostic Diagrams in Transport-Based Data-Collection Systems

    DEFF Research Database (Denmark)

    Tran, Vu The; Eklund, Peter; Cook, Chris

    Insights about service improvement in a transit network can be gained by studying transit service reliability. In this paper, a general procedure for constructing a transit service reliability diagnostic (Tsrd) diagram based on a Bayesian network is proposed to automatically build a behavioural m...

  2. Diagnostics of Robust Growth Curve Modeling Using Student's "t" Distribution

    Science.gov (United States)

    Tong, Xin; Zhang, Zhiyong

    2012-01-01

    Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…

  3. Local Dependence Diagnostics in IRT Modeling of Binary Data

    Science.gov (United States)

    Liu, Yang; Maydeu-Olivares, Alberto

    2013-01-01

    Local dependence (LD) for binary IRT models can be diagnosed using Chen and Thissen's bivariate X[superscript 2] statistic and the score test statistics proposed by Glas and Suarez-Falcon, and Liu and Thissen. Alternatively, LD can be assessed using general purpose statistics such as bivariate residuals or Maydeu-Olivares and Joe's M[subscript r]…

  4. Semiempirical model for diagnostication Helicobacter pylori infection by use of 14C labelled urea

    International Nuclear Information System (INIS)

    The main aim of this study was to create a semiempirical model, helpful in estimating severity of the Helicobacter pylori (H.pylori) infection by using the urea breath test (UBT), when urea labelled 14C has been used for diagnostics. The model consists of four compartments representing stomach (1), blood vascular system (2), lungs (3) and urinary system (4). Mathematical model is based on the balance of radioactive 14C in compartments from 1 to 4. The histological investigations were used as reference methods. Comparison of the results obtained from simulation, which yields dependence of 14C activity on time, to experimental results of UBT, made it possible to determine the ranges of coefficient HB value, which characterized each degrees of severity of H. pylori infection: degree 0 (lack of infection) - hB below 0.025; degree 1 (not large) - hB in range 0.025-0.115; degree 2 (moderate) - hB in the range 0.115-0.300; degree 3 (significant) - hB above 0.300. It was possible to estimate severity of H.pylori infection in clinical practice on the basis of comparing the 14C activity value of experimental points as obtained from the breath test, to the results of simulation with suitable value of the fitted parameter hB indicating degree of severity of infection. (author)

  5. An intercomparison of several diagnostic meteorological processors used in mesoscale air quality modeling

    Energy Technology Data Exchange (ETDEWEB)

    Vimont, J.C. [National Park Service, Lakewood, CO (United States); Scire, J.S. [Sigma Research Corp., Concord, MA (United States)

    1994-12-31

    A major component, and area of uncertainty, in mesoscale air quality modeling, is the specification of the meteorological fields which affect the transport and dispersion of pollutants. Various options are available for estimating the wind and mixing depth fields over a mesoscale domain. Estimates of the wind field can be obtained from spatial and temporal interpolation of available observations or from diagnostic meteorological models, which estimate a meteorological field from available data and adjust those fields based on parameterizations of physical processes. A major weakness of these processors is their dependence on spatially and temporally sparse input data, particularly upper air data. These problems are exacerbated in regions of complex terrain and along the shorelines of large bodies of water. Similarly, the estimation of mixing depth is also reliant upon sparse observations and the parameterization of the convective and mechanical processes. The meteorological processors examined in this analysis were developed to drive different Lagrangian puff models. This paper describes the algorithms these processors use to estimate the wind fields and mixing depth fields.

  6. Prediction of stroke-related diagnostic and prognostic measures using robot-based evaluation.

    Science.gov (United States)

    Mostafavi, Sayyed Mostafa; Glasgow, Janice I; Dukelow, Sean P; Scott, Stephen H; Mousavi, Parvin

    2013-06-01

    Traditional clinical scores for assessment of impairments resulting from stroke are inherently subjective and limited by inter-rater and intra-rater reliability. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of motor performance of stroke subjects. Although use of robotic technologies has been widely suggested in the literature, they are not an established tool and their relationship to traditional clinical scales for stroke diagnosis and prognosis is mostly unknown. In this study we propose the application of two non-linear system identification methods, Parallel Cascade Identification and Fast Orthogonal Search, for prediction of stroke-related clinical scores using robot-based metrics. We show the suitability of these two methods for prediction of both diagnostic and prognostic scores. We compare our results with a previously applied approach based on linear regression and show the superiority of our modeling approach. Our results also underscore the importance of quantifying proprioceptive deficits in the prediction of motor-related prognosis scores. PMID:24187274

  7. A high-throughput pipeline for designing microarray-based pathogen diagnostic assays

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2008-04-01

    Full Text Available Abstract Background We present a methodology for high-throughput design of oligonucleotide fingerprints for microarray-based pathogen diagnostic assays. The oligonucleotide fingerprints, or DNA microarray probes, are designed for identifying target organisms in environmental or clinical samples. The design process is implemented in a high-performance computing software pipeline that incorporates major algorithmic improvements over a previous version to both reduce computation time and improve specificity assessment. Results The algorithmic improvements result in significant reduction in runtimes, with the updated pipeline being nearly up to five-times faster than the previous version. The improvements in specificity assessment, based on multiple specificity criteria, result in robust and consistent evaluation of cross-hybridization with nontarget sequences. In addition, the multiple criteria provide finer control on the number of resulting fingerprints, which helps in obtaining a larger number of fingerprints with high specificity. Simulation tests for Francisella tularensis and Yersinia pestis, using a well-established hybridization model to estimate cross-hybridization with nontarget sequences, show that the improved specificity criteria yield a larger number of fingerprints as compared to using a single specificity criterion. Conclusion The faster runtimes, achieved as the result of algorithmic improvements, are critical for extending the pipeline to process multiple target genomes. The larger numbers of identified fingerprints, obtained by considering broader specificity criteria, are essential for designing probes for hard-to-distinguish target sequences.

  8. Development and Testing of Atomic Beam-Based Plasma Edge Diagnostics in the CIEMAT Fusion Devices

    International Nuclear Information System (INIS)

    In this report the development of plasma edge diagnostic based on atomic beam techniques fir their application in the CIEMAT fusion devices is described. The characterisation of the beams in laboratory experiments at the CSIC, together with first results in the Torsatron TJ-II are reported. Two types of beam diagnostics have been developed: a thermal (effusive) Li and a supersonic, pulsed He beams. This work has been carried out in collaboration between the institutions mentioned above under partial financial support by EURATOM. (Author) 17 refs

  9. Remote monitoring and diagnostics of devices based on distributed database system

    Directory of Open Access Journals (Sweden)

    Jarosław FABIJAŃSKI

    2008-01-01

    Full Text Available The paper provides an overview of the problems connected with remote monitoring and diagnostics of rail signalling devices which are both distributed over a large area as well as highly diversified in terms of scope and format of the information that is made available. A diagnostic system, based on a distributed, relational database and a wireless data transmission system, has been presented in this paper as a solution to these problems. Moreover, the paper provides a description of the advantages of the solution in question that manifest themselves in the data collection, transmission, processing and presentation.

  10. Development and validation of a microRNA based diagnostic assay for primary tumor site classification of liver core biopsies

    DEFF Research Database (Denmark)

    Perell, Katharina; Vincent, Martin; Vainer, Ben;

    2015-01-01

    Identification of the primary tumor site in patients with metastatic cancer is clinically important, but remains a challenge. Hence, efforts have been made towards establishing new diagnostic tools. Molecular profiling is a promising diagnostic approach, but tissue heterogeneity and inadequacy may...... negatively affect the accuracy and usability of molecular classifiers. We have developed and validated a microRNA-based classifier, which predicts the primary tumor site of liver biopsies, containing a limited number of tumor cells. Concurrently we explored the influence of surrounding normal tissue on...... classification. MicroRNA profiling was performed using quantitative Real-Time PCR on formalin-fixed paraffin-embedded samples. 278 primary tumors and liver metastases, representing nine primary tumor classes, as well as normal liver samples were used as a training set. A statistical model was applied to adjust...

  11. Bivariate Random Effects Meta-analysis of Diagnostic Studies Using Generalized Linear Mixed Models

    OpenAIRE

    Chu, Haitao; Guo, Hongfei; Zhou, Yijie

    2009-01-01

    Bivariate random effect models are currently one of the main methods recommended to synthesize diagnostic test accuracy studies. However, only the logit-transformation on sensitivity and specificity has been previously considered in the literature. In this paper, we consider a bivariate generalized linear mixed model to jointly model the sensitivities and specificities, and discuss the estimation of the summary receiver operating characteristic curve (ROC) and the area under the ROC curve (AU...

  12. A diagnostic system to assess sustainability at farm level: the SOSTARE model

    OpenAIRE

    PARACCHINI Maria-Luisa; BULGHERONI CLAUDIA; BORREANI Giorgio; Tabacco, Ernesto; Banterle, Alessandro; BERTONI Danilo; Rossi, Graziano; PAROLO Gilberto; ORIGGI Roberto; DE PAOLA Claudio

    2013-01-01

    The paper presents a model for integrated sustainability assessment at a farm scale. The SOSTARE model (analysis of farm technical efficiency and impacts on environmental and economic sustainability), in fact, aims at providing a diagnostic tool to farmers and advisory services to assess the general performance of the farm, explore in detail any perceived weaknesses in farm management and to investigate the impact of changes that might improve efficiency. The model is derived from a survey of...

  13. Optimal linear combinations of multiple diagnostic biomarkers based on Youden index.

    Science.gov (United States)

    Yin, Jingjing; Tian, Lili

    2014-04-15

    In practice, usually multiple biomarkers are measured on the same subject for disease diagnosis. Combining these biomarkers into a single score could improve diagnostic accuracy. Many researchers have addressed the problem of finding the optimal linear combination based on maximizing the area under ROC curve (AUC). Actually, such combined score might have less than optimal property at the diagnostic threshold. In this paper, we propose the idea of using Youden index as an objective function for searching the optimal linear combination. The combined score directly achieves the maximum overall correct classification rate at the diagnostic threshold corresponding to Youden index; in other words, it is the optimal linear combination score for making the disease diagnosis. We present both empirical and numerical searching methods for the optimal linear combination. We carry out extensive simulation study to investigate the performance of the proposed methods. Additionally, we empirically compare the optimal overall classification rates between the proposed combination based on Youden index and the traditional one based on AUC and demonstrate a significant gain in diagnostic accuracy for the proposed combination. In the end, we apply the proposed methods to a real data set. PMID:24311111

  14. Plasma Fluctuation Studies in the TCV Tokamak: Modeling of Shaping Effects and Advanced Diagnostic Development

    International Nuclear Information System (INIS)

    One of the most important issues for magnetic-confinement fusion research is the so-called anomalous transport across magnetic field lines, i.e. transport that is in excess of that caused by collisional processes. The need to reduce anomalous transport in order to increase the efficiency of a prospective fusion reactor must be addressed through an investigation of its fundamental underlying causes. This thesis is divided into two distinct components: one experimental and instrumental, and the other theoretical and based on numerical modeling. The experimental part consists of the design and installation of a new diagnostic for core turbulence fluctuations in the TCV tokamak. An extensive conceptual investigation of a number of possible solutions, including Beam Emission Spectroscopy, Reflectometry, Cross Polarization, Collective Scattering and different Imaging techniques, was carried out at first. A number of criteria, such as difficulties in data interpretation, costs, variety of physics issues that could be addressed and expected performance, were used to compare the different techniques for specific application to the TCV tokamak. The expected signal to noise ratio and the required sampling frequency for TCV were estimated on the basis of a large number of linear, local gyrokinetic simulations of plasma fluctuations. This work led to the choice of a Zernike phase contrast imaging system in a tangential launching configuration. The diagnostic was specifically designed to provide information on turbulence features up to now unknown. In particular, it is characterized by an outstanding spatial resolution and by the capability to measure a very broad range of fluctuations, from ion to electron Larmor radius scales, thus covering the major part of the instabilities expected to be at play in TCV. The spectrum accessible covers the wavenumber region from 0.9 cm-1 to 60 cm-1 at 24 radial positions with 3 MHz bandwidth. The diagnostic is an imaging technique and is

  15. Predictive Modeling of Student Performances for Retention and Academic Support in a Diagnostic Medical Sonography Program

    Science.gov (United States)

    Borghese, Peter; Lacey, Sandi

    2014-01-01

    As part of a retention and academic support program, data was collected to develop a predictive model of student performances in core classes in a Diagnostic Medical Sonography (DMS) program. The research goal was to identify students likely to have difficulty with coursework and provide supplemental tutorial support. The focus was on the…

  16. An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models

    Science.gov (United States)

    Liu, Yanlou; Tian, Wei; Xin, Tao

    2016-01-01

    The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…

  17. NS1-based tests with diagnostic utility for confirming dengue infection: a meta-analysis

    OpenAIRE

    Hao Zhang; Wei Li; Junjie Wang; Hongjuan Peng; Xiaoyan Che; Xiaoguang Chen; Yuanping Zhou

    2014-01-01

    Objectives: Non-structural protein 1 (NS1)-based tests may offer a larger window of opportunity for dengue diagnosis and could constitute a very useful diagnostic tool. The aim of this study was to establish the overall accuracy of NS1-based tests for diagnosing dengue infection. Methods: A meta-analysis was conducted including 18 studies published up to October 1, 2012 identified using PubMed, ISI Web of Science, Google Scholar, and the Chinese National Knowledge Infrastructure (CNKI) dat...

  18. Probability-Based Diagnostic Imaging Technique Using Error Functions for Active Structural Health Monitoring

    OpenAIRE

    Rahim Gorgin; Zhanjun Wu

    2014-01-01

    This study presents a novel probability-based diagnostic imaging (PDI) technique using error functions for active structural health monitoring (SHM). To achieve this, first the changes between baseline and current signals of each sensing path are measured, and by taking the root mean square of such changes, the energy of the scattered signal at different times can be calculated. Then, for different pairs of signal acquisition paths, an error function based on the energy of the...

  19. Validation of Ten Noninvasive Diagnostic Models for Prediction of Liver Fibrosis in Patients with Chronic Hepatitis B

    OpenAIRE

    Cheng, Jieyao; Hou, Jinlin; Ding, Huiguo; Chen, Guofeng; Xie, Qing; Wang, Yuming; Zeng, Minde; Ou, Xiaojuan; Ma, Hong; Jia, Jidong

    2015-01-01

    Background and Aims Noninvasive models have been developed for fibrosis assessment in patients with chronic hepatitis B. However, the sensitivity, specificity and diagnostic accuracy in evaluating liver fibrosis of these methods have not been validated and compared in the same group of patients. The aim of this study was to verify the diagnostic performance and reproducibility of ten reported noninvasive models in a large cohort of Asian CHB patients. Methods The diagnostic performance of ten...

  20. Influence of the diagnostic wind field model on the results of calculation of the microscale atmospheric dispersion in moderately complex terrain

    Science.gov (United States)

    Kovalets, Ivan V.; Korolevych, Vladimir Y.; Khalchenkov, Alexander V.; Ievdin, Ievgen A.; Zheleznyak, Mark J.; Andronopoulos, Spyros

    2013-11-01

    The impact of diagnostic wind field model on the results of calculation of microscale atmospheric dispersion in moderately complex terrain conditions was investigated. The extensive radiological and meteorological data set collected at the site of the research reactor of the Chalk River Laboratories (CRL) in Canada had been compared with the results of calculations of the Local Scale Model Chain of the EU nuclear emergency response system JRODOS. The diagnostic wind field model based on divergence minimizing procedure and the atmospheric dispersion model RIMPUFF were used in calculations. Taking into account complex topography features with the use of diagnostic wind field model improved the results of calculations. For certain months, the level of improvement of the normalized mean squared error reached the factor of 2. For the whole simulation period (January-July, 2007) the level of improvement by taking into account terrain features with the diagnostic wind field model was about 9%. The use of diagnostic wind field model also significantly improved the fractional bias of the calculated results. Physical analysis of the selected cases of atmospheric dispersion at the CRL site had been performed.

  1. Diagnostic model of saliva protein finger print analysis of patients with gastric cancer

    Institute of Scientific and Technical Information of China (English)

    Zheng-Zhi Wu; Ji-Guo Wang; Xiao-Li Zhang

    2009-01-01

    AIM: To explore the method for early diagnosis of gastric cancer by screening the expression spectrum of saliva protein in gastric cancer patients using mass spectrometry for proteomics. METHODS: Proportional peptide mass fingerprints were obtained by analysis based on proteomics matrixassisted laser desorption ionization time-of-flight/mass spectrometry. A diagnosis model was established using weak cation exchange magnetic beads to test saliva specimens from gastric cancer patients and healthy subjects. RESULTS: Significant differences were observed in the mass to charge ratio (m/z) peaks of four proteins (1472.78 Da, 2936.49 Da, 6556.81 Da and 7081.17 Da) between gastric cancer patients and healthy subjects. CONCLUSION: The finger print mass spectrum of saliva protein in patients with gastric cancer can be established using gastric cancer proteomics. A diagnostic model for distinguishing protein expression mass spectra of gastric cancer from non-gastriccancer saliva can be established according to the different expression of proteins 1472.78 Da, 2936.49 Da, 6556.81 Da and 7081.17 Da. The method for early diagnosis of gastric cancer is of certain value for screening special biological markers.

  2. Guide waves-based multi-damage identification using a local probability-based diagnostic imaging method

    Science.gov (United States)

    Gao, Dongyue; Wu, Zhanjun; Yang, Lei; Zheng, Yuebin

    2016-04-01

    Multi-damage identification is an important and challenging task in the research of guide waves-based structural health monitoring. In this paper, a multi-damage identification method is presented using a guide waves-based local probability-based diagnostic imaging (PDI) method. The method includes a path damage judgment stage, a multi-damage judgment stage and a multi-damage imaging stage. First, damage imaging was performed by partition. The damage imaging regions are divided into beside damage signal paths. The difference in guide waves propagation characteristics between cross and beside damage paths is proposed by theoretical analysis of the guide wave signal feature. The time-of-flight difference of paths is used as a factor to distinguish between cross and beside damage paths. Then, a global PDI method (damage identification using all paths in the sensor network) is performed using the beside damage path network. If the global PDI damage zone crosses the beside damage path, it means that the discrete multi-damage model (such as a group of holes or cracks) has been misjudged as a continuum single-damage model (such as a single hole or crack) by the global PDI method. Subsequently, damage imaging regions are separated by beside damage path and local PDI (damage identification using paths in the damage imaging regions) is performed in each damage imaging region. Finally, multi-damage identification results are obtained by superimposing the local damage imaging results and the marked cross damage paths. The method is employed to inspect the multi-damage in an aluminum plate with a surface-mounted piezoelectric ceramic sensors network. The results show that the guide waves-based multi-damage identification method is capable of visualizing the presence, quantity and location of structural damage.

  3. New Features in Nuclear Diagnostic Modeling Using HYDRA

    Science.gov (United States)

    Sepke, S. M.; Cerjan, C.; Marinak, M.; Knauer, J.

    2013-10-01

    New methods in HYDRA have been developed to allow more accurate and flexible modeling of nuclear reactions with a focus on measurements at the National Ignition Facility. Two developments are highlighted: radiochemistry and compound nuclei. Low probability nuclear reactions in an ICF capsule are best simulated using radiochemistry techniques. HYDRA now has both an inline and a post-processing capability, which uses the new code KUDU. Calculation of the 4.4 MeV 12C(n, γn') γ is shown to be greatly improved relative to an analog Monte Carlo calculation. This γ measured along with the T(D, γn) γ in an ICF implosion provides a measurement of mix, areal density, and timing. HYDRA now also provides a facility to define the properties of a compound nucleus in a thermonuclear reaction. By using this new capability and recently measured γ and neutron spectra to inform the 5He state, the simulation of T(D,n γ) and TT fusion reactions that share the intermediate 5He state has been significantly improved. This work (LLNL-ABS-640612) performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  4. Spectroscopic diagnostics and modelling of silane microwave plasmas

    International Nuclear Information System (INIS)

    Low-pressure silane plasmas (2-20 Pa) diluted with the noble gases helium and argon as well as hydrogen were generated by microwave excitation in order to determine plasma parameters and absolute particle number densities. Specific silane radicals (SiH, Si, H2, H) were measured by means of optical emission spectroscopy, whereas particle densities of silane, disilane and molecular hydrogen were measured with mass spectroscopy. Experimental results confirm model calculations, which were carried out to determine number densities of all silane radicals and of higher silanes as well as electron temperature. The electron temperature varies from 1.5 to 4 eV depending on pressure and gas mixture. The temperature of heavy particles is 450 K and the electron number density is 9x1016m-3. The rotational temperatures of SiH are between room temperature and 2000 K due to increasing dissociative excitation. In the plasma the number density of silane is reduced, whereas the number density of molecular hydrogen is close to the silane density, which is fed in. Particle densities of SiH3, disilane and atomic hydrogen are in the range of a few per cent of the silane number density. At low pressure the SiH2 density is similar to SiH3 and decreases with increasing pressure due to heavy particle collisions with silane producing higher silanes. Particle densities of SiH and Si are only in the range of some 10-3 of the silane density decreasing with increasing collisions of heavy particles with silane and molecular hydrogen. In mixtures with argon Penning reactions increase the silane dissociation. (author)

  5. Fuzzy based method for project planning of the infrastructure design for the diagnostic in ITER

    Energy Technology Data Exchange (ETDEWEB)

    Piros, Attila, E-mail: attila.piros@gt3.bme.hu [Department of Machine and Product Design, Budapest University of Technology and Economics, Budapest (Hungary); Veres, Gábor [Department of Plasma Physics, Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest (Hungary)

    2013-10-15

    The long-term design projects need special preparation before the start of the execution. This preparation usually includes the drawing of the network diagram for the whole procedure. This diagram includes the time estimation of the individual subtasks and gives us information about the predicted dates of the milestones. The calculated critical path in this network characterizes a specific design project concerning to its duration very well. Several methods are available to support this step of preparation. This paper describes a new method to map the structure of the design process and clarify the milestones and predict the dates of these milestones. The method is based on the PERT (Project Evaluation and Review Technique) network but as a novelty it applies fuzzy logic to find out the concerning times in this graph. With the application of the fuzzy logic the handling of the different kinds of design uncertainties becomes feasible. Many kinds of design uncertainties exist from the possible electric blackout up to the illness of an engineer. In many cases these uncertainties are related with human errors and described with linguistic expressions. The fuzzy logic enables to transform these ambiguous expressions into numeric values for further mathematical evaluation. The method is introduced in the planning of the design project of the infrastructure for the diagnostic systems of ITER. The method not only helps the project in the planning phase, but it will be a powerful tool in mathematical modeling and monitoring of the project execution.

  6. Performance optimization of a diagnostic system based upon a simulated strain field for fatigue damage characterization

    Science.gov (United States)

    Sbarufatti, C.; Manes, A.; Giglio, M.

    2013-11-01

    The work presented hereafter is about the development of a diagnostic system for crack damage detection, localization and quantification on a typical metallic aeronautical structure (skin stiffened through riveted stringers). Crack detection and characterization are based upon strain field sensitivity to damage. The structural diagnosis is carried out by a dedicated smart algorithm (Artificial Neural Network) which is trained on a database of Finite Element simulations relative to damaged and undamaged conditions, providing the system with an accurate predictor at low overall cost. The algorithm, trained on numerical damage experience, is used in a simulated environment to provide reliable preliminary information concerning the algorithm performances for damage diagnosis, thus further reducing the experimental costs and efforts associated with the development and optimization of such systems. The same algorithm has been tested on real experimental strain patterns acquired during real fatigue crack propagation, thus verifying the capability of the numerically trained algorithm for anomaly detection, damage assessment and localization on a real complex structure. The load variability, the discrepancy between the Finite Element Model and the real structure, and the uncertainty in the algorithm training process have been addressed in order to enhance the robustness of the system inference process. Some further algorithm training strategies are discussed, aimed at minimizing the risk for false alarms while maintaining a high probability of damage detection.

  7. Fuzzy based method for project planning of the infrastructure design for the diagnostic in ITER

    International Nuclear Information System (INIS)

    The long-term design projects need special preparation before the start of the execution. This preparation usually includes the drawing of the network diagram for the whole procedure. This diagram includes the time estimation of the individual subtasks and gives us information about the predicted dates of the milestones. The calculated critical path in this network characterizes a specific design project concerning to its duration very well. Several methods are available to support this step of preparation. This paper describes a new method to map the structure of the design process and clarify the milestones and predict the dates of these milestones. The method is based on the PERT (Project Evaluation and Review Technique) network but as a novelty it applies fuzzy logic to find out the concerning times in this graph. With the application of the fuzzy logic the handling of the different kinds of design uncertainties becomes feasible. Many kinds of design uncertainties exist from the possible electric blackout up to the illness of an engineer. In many cases these uncertainties are related with human errors and described with linguistic expressions. The fuzzy logic enables to transform these ambiguous expressions into numeric values for further mathematical evaluation. The method is introduced in the planning of the design project of the infrastructure for the diagnostic systems of ITER. The method not only helps the project in the planning phase, but it will be a powerful tool in mathematical modeling and monitoring of the project execution

  8. Reference dosimetry during diagnostic CT examination using XR-QA radiochromic film model

    International Nuclear Information System (INIS)

    Purpose: The authors applied 2D reference dosimetry protocol for dose measurements using XR-QA radiochromic film model during diagnostic computed tomography (CT) examinations carried out on patients and humanoid Rando phantom. Methods: Response of XR-QA model GAFCHROMIC film reference dosimetry system was calibrated in terms of Air-Kerma in air. Four most commonly used CT protocols were selected on their CT scanner (GE Lightspeed VCT 64), covering three anatomical sites (head, chest, and abdomen). For each protocol, 25 patients ongoing planned diagnostic CT examination were recruited. Surface dose was measured using four or eight film strips taped on patients' skin and on Rando phantom. Film pieces were scanned prior to and after irradiation using Epson Expression 10000XL document scanner. Optical reflectance of the unexposed film piece was subtracted from exposed one to obtain final net reflectance change, which is subsequently converted to dose using previously established calibration curves. Results: The authors' measurements show that body skin dose variation has a sinusoidal pattern along the scanning axis due to the helical movement of the x-ray tube, and a comb pattern for head dose measurements due to its axial movement. Results show that the mean skin dose at anterior position for patients is (51 ± 6) mGy, (29 ± 11) mGy, (45 ± 13) mGy and (38 ± 20) mGy for head, abdomen, angio Abdomen, and chest and abdomen protocol (UP position), respectively. The obtained experimental dose length products (DLP) show higher values than CT based DLP taken from the scanner console for body protocols, but lower values for the head protocol. Internal dose measurements inside the phantom's head indicate nonuniformity of dose distribution within scanned volume. Conclusions: In this work, the authors applied an Air-Kerma in air based radiochromic film reference dosimetry protocol for in vivo skin dose measurements. In this work, they employed green channel extracted from the

  9. IGENPRO knowledge-based digital system for process transient diagnostics and management

    International Nuclear Information System (INIS)

    Verification and validation issues have been perceived as important factors in the large scale deployment of knowledge-based digital systems for plant transient diagnostics and management. Research and development (R and D) is being performed on the IGENPRO package to resolve knowledge base issues. The IGENPRO approach is to structure the knowledge bases on generic thermal-hydraulic (T-H) first principles and not use the conventional event-basis structure. This allows for generic comprehensive knowledge, relatively small knowledge bases and above all the possibility of T-H system/plant independence. To demonstrate concept feasibility the knowledge structure has been implemented in the diagnostic module PRODIAG. Promising laboratory testing results have been obtained using data from the full scope Braidwood PWR operator training simulator. This knowledge structure is now being implemented in the transient management module PROMANA to treat unanticipated events and the PROTREN module is being developed to process actual plant data. Achievement of the IGENPRO R and D goals should contribute to the acceptance of knowledge-based digital systems for transient diagnostics and management. (author)

  10. IGENPRO knowledge-based digital system for process transient diagnostics and management

    International Nuclear Information System (INIS)

    Verification and validation issues have been perceived as important factors in the large scale deployment of knowledge-based digital systems for plant transient diagnostics and management. Research and development (R ampersand D) is being performed on the IGENPRO package to resolve knowledge base issues. The IGENPRO approach is to structure the knowledge bases on generic thermal-hydraulic (T-H) first principles and not use the conventional event-basis structure. This allows for generic comprehensive knowledge, relatively small knowledge bases and above all the possibility of T-H system/plant independence. To demonstrate concept feasibility the knowledge structure has been implemented in the diagnostic module PRODIAG. Promising laboratory testing results have been obtained using data from the full scope Braidwood PWR operator training simulator. This knowledge structure is now being implemented in the transient management module PROMANA to treat unanticipated events and the PROTREN module is being developed to process actual plant data. Achievement of the IGENPRO R ampersand D goals should contribute to the acceptance of knowledge-based digital systems for transient diagnostics and management

  11. Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications

    Directory of Open Access Journals (Sweden)

    François Patou

    2016-09-01

    Full Text Available The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods.

  12. Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications.

    Science.gov (United States)

    Patou, François; AlZahra'a Alatraktchi, Fatima; Kjægaard, Claus; Dimaki, Maria; Madsen, Jan; Svendsen, Winnie E

    2016-01-01

    The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods. PMID:27598208

  13. Developing and Implementing Diagnostic Prediction Models for Vestibular Diseases in Primary Care.

    Science.gov (United States)

    Grill, Eva; Groezinger, Michael; Feil, Katharina; Strupp, Michael

    2016-01-01

    Diagnosing patients with vertigo and dizziness is a challenge in primary care settings where laboratory examinations are often not available. This study uses data from patients with confirmed diagnoses of vestibular syndromes to develop and validate simple diagnostic prediction models for the primary care physician. We describe the implementation of these models into an application that may assist the practitioners with their clinical decisions. PMID:27577483

  14. On diagnostics in conditionally heteroskedastic time series models under elliptical distributions

    OpenAIRE

    Liu, Shuangzhe

    2004-01-01

    In statistical diagnostics and sensitivity analysis, the local influence method plays an important rôle. In the present paper, we use this method to study financial time series data and conditionally heteroskedastic models under elliptical distributions. We start with a likelihood displacement, and consider data- and model-perturbation schemes. We obtain corresponding matrices of derivatives, and measures of slope and normal curvature, and then discuss the assessment of l...

  15. Influence diagnostics in exponentiated-Weibull regression models with censored data

    OpenAIRE

    Edwin M. M. Ortega; Cancho, Vicente G.; Bolfarine, Heleno

    2006-01-01

    Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance o...

  16. Smartphone-Based Fluorescent Diagnostic System for Highly Pathogenic H5N1 Viruses

    Science.gov (United States)

    Yeo, Seon-Ju; Choi, Kyunghan; Cuc, Bui Thi; Hong, Nguyen Ngoc; Bao, Duong Tuan; Ngoc, Nguyen Minh; Le, Mai Quynh; Hang, Nguyen Le Khanh; Thach, Nguyen Co; Mallik, Shyam Kumar; Kim, Hak Sung; Chong, Chom-Kyu; Choi, Hak Soo; Sung, Haan Woo; Yu, Kyoungsik; Park, Hyun

    2016-01-01

    Field diagnostic tools for avian influenza (AI) are indispensable for the prevention and controlled management of highly pathogenic AI-related diseases. More accurate, faster and networked on-site monitoring is demanded to detect such AI viruses with high sensitivity as well as to maintain up-to-date information about their geographical transmission. In this work, we assessed the clinical and field-level performance of a smartphone-based fluorescent diagnostic device with an efficient reflective light collection module using a coumarin-derived dendrimer-based fluorescent lateral flow immunoassay. By application of an optimized bioconjugate, a smartphone-based diagnostic device had a two-fold higher detectability as compared to that of the table-top fluorescence strip reader for three different AI subtypes (H5N3, H7N1, and H9N2). Additionally, in a clinical study of H5N1-confirmed patients, the smartphone-based diagnostic device showed a sensitivity of 96.55% (28/29) [95% confidence interval (CI): 82.24 to 99.91] and a specificity of 98.55% (68/69) (95% CI: 92.19 to 99.96). The measurement results from the distributed individual smartphones were wirelessly transmitted via short messaging service and collected by a centralized database system for further information processing and data mining. Smartphone-based diagnosis provided highly sensitive measurement results for H5N1 detection within 15 minutes. Because of its high sensitivity, portability and automatic reporting feature, the proposed device will enable agile identification of patients and efficient control of AI dissemination. PMID:26877781

  17. Feasibility of streamlining an interactive Bayesian-based diagnostic support tool designed for clinical practice

    Science.gov (United States)

    Chen, Po-Hao; Botzolakis, Emmanuel; Mohan, Suyash; Bryan, R. N.; Cook, Tessa

    2016-03-01

    In radiology, diagnostic errors occur either through the failure of detection or incorrect interpretation. Errors are estimated to occur in 30-35% of all exams and contribute to 40-54% of medical malpractice litigations. In this work, we focus on reducing incorrect interpretation of known imaging features. Existing literature categorizes cognitive bias leading a radiologist to an incorrect diagnosis despite having correctly recognized the abnormal imaging features: anchoring bias, framing effect, availability bias, and premature closure. Computational methods make a unique contribution, as they do not exhibit the same cognitive biases as a human. Bayesian networks formalize the diagnostic process. They modify pre-test diagnostic probabilities using clinical and imaging features, arriving at a post-test probability for each possible diagnosis. To translate Bayesian networks to clinical practice, we implemented an entirely web-based open-source software tool. In this tool, the radiologist first selects a network of choice (e.g. basal ganglia). Then, large, clearly labeled buttons displaying salient imaging features are displayed on the screen serving both as a checklist and for input. As the radiologist inputs the value of an extracted imaging feature, the conditional probabilities of each possible diagnosis are updated. The software presents its level of diagnostic discrimination using a Pareto distribution chart, updated with each additional imaging feature. Active collaboration with the clinical radiologist is a feasible approach to software design and leads to design decisions closely coupling the complex mathematics of conditional probability in Bayesian networks with practice.

  18. Appraising and applying evidence about a diagnostic test during a performance-based assessment

    Directory of Open Access Journals (Sweden)

    Franklin Ellen

    2004-10-01

    Full Text Available Abstract Background The practice of Evidence-based Medicine requires that clinicians assess the validity of published research and then apply the results to patient care. We wanted to assess whether our soon-to-graduate medical students could appraise and apply research about a diagnostic test within a clinical context and to compare our students with peers trained at other institutions. Methods 4th year medical students who previously had demonstrated competency at probability revision and just starting first-year Internal Medicine residents were used for this research. Following an encounter with a simulated patient, subjects critically appraised a paper about an applicable diagnostic test and revised the patient's pretest probability given the test result. Results The medical students and residents demonstrated similar skills at critical appraisal, correctly answering 4.7 and 4.9, respectively, of 6 questions (p = 0.67. Only one out of 28 (3% medical students and none of the 15 residents were able to correctly complete the probability revision task (p = 1.00. Conclusions This study found that most students completing medical school are able to appraise an article about a diagnostic test but few are able to apply the information from the article to a patient. These findings raise questions about the clinical usefulness of the EBM skills possessed by graduating medical students within the area of diagnostic testing.

  19. Application of Laser-based Diagnostics to a Prototype Gas Turbine Burner at Selected Pressures

    OpenAIRE

    Whiddon, Ronald

    2014-01-01

    The matured laser-diagnostic techniques of planar laser-induced fluorescence (PLIF) and particle image velocimetry (PIV) were applied to a prototype gas turbine burner operating on various fuels. The work was performed to provide verification of computational fluid dynamic (CFD) models of the combustion of atypical fuels in a gas turbine combustor. The burner was operated using methane and three synthesized fuels of interest- one with hydrogen as the principle component and two with a low hea...

  20. EEG Analysis during complex diagnostic tasks in Nuclear Power Plants - Simulator-based Experimental Study

    International Nuclear Information System (INIS)

    In literature, there are a lot of studies based on EEG signals during cognitive activities of human-beings but most of them dealt with simple cognitive activities such as transforming letters into Morse code, subtraction, reading, semantic memory search, visual search, memorizing a set of words and so on. In this work, EEG signals were analyzed during complex diagnostic tasks in NPP simulator-based environment. Investigated are the theta, alpha, beta, and gamma band EEG powers during the diagnostic tasks. The experimental design and procedure are represented in section 2 and the results are shown in section 3. Finally some considerations are discussed and the direction for the further work is proposed in section 4

  1. Infant Hip Joint Diagnostic Support System Based on Clinical Manifestations in X-ray Images

    Directory of Open Access Journals (Sweden)

    Honda,Mitsugi

    2010-06-01

    Full Text Available Plain X-ray radiography is frequently used for the diagnosis of developmental dislocation of the hip (DDH. The aim of this study was to construct a diagnostic support system for DDH based on clinical findings obtained from the X-ray images of 154 female infants with confirmed diagnoses made by orthopedists. The data for these subjects were divided into 2 groups. The Min-Max method of nonlinear analysis was applied to the data from Group 1 to construct the diagnostic support system based on the measurement of 4 items in X-ray images:the outward displacement rate, upward displacement rate, OE angle, and alpha angle. This system was then applied to the data from Group 2, and the results were compared between the 2 groups to verify the reliability of the system. We obtained good results that matched the confirmed diagnoses of orthopedists with an accuracy of 85.9%.

  2. IAEA consultants' meeting on He-beam data base for alpha particle diagnostics of fusion plasmas

    International Nuclear Information System (INIS)

    The present Report contains the Summary of the IAEA Consultants' Meeting on ''He-Beam Data Base for Alpha Particle Diagnostics of Fusion Plasmas'' which was organized by the Atomic and Molecular Data Unit and held on June 3-5, 1991 at the IAEA Headquarters in Vienna, Austria. The Meeting Proceedings are briefly described and the reports of the Working Groups on the electron- and ion-impact processes are reproduced. A survey on the atomic data needs and required cross section accuracies for helium beam stopping calculations and alpha particle diagnostics of JET- and ITER-like plasmas is included. The conclusions and recommendations of the Meeting regarding the status of present data base (availability and quality) and the needs for its improvement are also given in this Summary Report. (author). Refs, figs and tabs

  3. Improving plasma shaping accuracy through consolidation of control model maintenance, diagnostic calibration, and hardware change control

    International Nuclear Information System (INIS)

    With the advent of more sophisticated techniques for control of tokamak plasmas comes the requirement for increasingly more accurate models of plasma processes and tokamak systems. Development of accurate models for DIII-D power systems, vessel, and poloidal coils is already complete, while work continues in development of general plasma response modeling techniques. Increased accuracy in estimates of parameters to be controlled is also required. It is important to ensure that errors in supporting systems such as diagnostic and command circuits do not limit the accuracy of plasma parameter estimates or inhibit the ability to derive accurate plasma/tokamak system models. To address this issue, we have developed more formal power systems change control and power system/magnetic diagnostics calibration procedures. This paper discusses our approach to consolidating the tasks in these closely related areas. This includes, for example, defining criteria for when diagnostics should be re-calibrated along with required calibration tolerances, and implementing methods for tracking power systems hardware modifications and the resultant changes to control models

  4. Consistency of Cluster Analysis for Cognitive Diagnosis: The Reduced Reparameterized Unified Model and the General Diagnostic Model.

    Science.gov (United States)

    Chiu, Chia-Yi; Köhn, Hans-Friedrich

    2016-09-01

    The asymptotic classification theory of cognitive diagnosis (ACTCD) provided the theoretical foundation for using clustering methods that do not rely on a parametric statistical model for assigning examinees to proficiency classes. Like general diagnostic classification models, clustering methods can be useful in situations where the true diagnostic classification model (DCM) underlying the data is unknown and possibly misspecified, or the items of a test conform to a mix of multiple DCMs. Clustering methods can also be an option when fitting advanced and complex DCMs encounters computational difficulties. These can range from the use of excessive CPU times to plain computational infeasibility. However, the propositions of the ACTCD have only been proven for the Deterministic Input Noisy Output "AND" gate (DINA) model and the Deterministic Input Noisy Output "OR" gate (DINO) model. For other DCMs, there does not exist a theoretical justification to use clustering for assigning examinees to proficiency classes. But if clustering is to be used legitimately, then the ACTCD must cover a larger number of DCMs than just the DINA model and the DINO model. Thus, the purpose of this article is to prove the theoretical propositions of the ACTCD for two other important DCMs, the Reduced Reparameterized Unified Model and the General Diagnostic Model. PMID:27230079

  5. Predicting the Uncertain Future of Aptamer-Based Diagnostics and Therapeutics

    OpenAIRE

    Bruno, John G.

    2015-01-01

    Despite the great promise of nucleic acid aptamers in the areas of diagnostics and therapeutics for their facile in vitro development, lack of immunogenicity and other desirable properties, few truly successful aptamer-based products exist in the clinical or other markets. Core reasons for these commercial deficiencies probably stem from industrial commitment to antibodies including a huge financial investment in humanized monoclonal antibodies and a general ignorance about aptamers and their...

  6. Comparison of Diagnostic Cytomorphology of Atypical Squamous Cells in Liquid-Based Preparations and Conventional Smears

    OpenAIRE

    Lee, Jung Dal; Oh, Young-Ha; Lee, Seong Ok; Kim, Jong Yull

    2012-01-01

    Background The aims of this study were to compare the cytomorphologic features diagnostic of atypical squamous cells (ASC) in liquid-based preparations (LBPs) and conventional Pap (CP) smears and to cytomorphologically assess the performance of the Cell Scan 1500™ in cervical cytology practice. Methods Cervicovaginal smears were obtained from 938 women. Two smears were obtained simultaneously from each individual, one for an LBP and the other for a CP smear; the smears were independently exam...

  7. Computer-based diagnostic and prognostic approaches in medical research using brain MRI

    OpenAIRE

    Weygandt, Martin

    2016-01-01

    Die vorliegende Habilitationsschrift zu „Computer-based diagnostic and prognostic approaches in medical research using brain MRI“ ist in zwei Abschnitte gegliedert. Konkret wird im ersten Abschnitt eine Übersicht über verschiedene Aspekte des Computer- und MRT-basierten Vorhersageansatzes gegeben. Im zweiten Abschnitt werden die Artikel aus diesem Feld beschrieben, die ich für die Habilitation eingereicht habe. Konkret beginnt der erste Abschnitt der Habilitationsschrift damit, das grundlege...

  8. Computation of large scale currents in the Arabian Sea during winter using a semi-diagnostic model

    Digital Repository Service at National Institute of Oceanography (India)

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

    A 3-dimensional, semi-diagnostic model with 331 levels in the vertical has been used for the computation of climatic circulation in the western tropical Indian Ocean. Model is driven with the seasonal mean data on wind stress, temperature...

  9. Model-based segmentation

    OpenAIRE

    Heimann, Tobias; Delingette, Hervé

    2011-01-01

    This chapter starts with a brief introduction into model-based segmentation, explaining the basic concepts and different approaches. Subsequently, two segmentation approaches are presented in more detail: First, the method of deformable simplex meshes is described, explaining the special properties of the simplex mesh and the formulation of the internal forces. Common choices for image forces are presented, and how to evolve the mesh to adapt to certain structures. Second, the method of point...

  10. Diagnostic properties of nerve conduction tests in population-based carpal tunnel syndrome

    Directory of Open Access Journals (Sweden)

    Johnsson Ragnar

    2003-05-01

    Full Text Available Abstract Background Numerous nerve conduction tests are used for the electrodiagnosis of carpal tunnel syndrome (CTS, with a wide range of sensitivity and specificity reported for each test in clinical studies. The tests have not been assessed in population-based studies. Such information would be important when using electrodiagnosis in epidemiologic research. The purpose of this study was to compare the diagnostic accuracy of various nerve conduction tests in population-based CTS and determine the properties of the most accurate test. Methods In a population-based study a questionnaire was mailed to a random sample of 3,000 persons. Of 2,466 responders, 262 symptomatic (numbness/tingling in the radial fingers and 125 randomly selected asymptomatic responders underwent clinical and electrophysiologic examinations. A standardized hand diagram was administered to the symptomatic persons. At the clinical examination, the examining surgeon identified 94 symptomatic persons as having clinically certain CTS. Nerve conduction tests were then performed on the symptomatic and the asymptomatic persons by blinded examiners. Analysis with receiver operating characteristic (ROC curves was used to compare the diagnostic accuracy of the nerve conduction tests in distinguishing the persons with clinically certain CTS from the asymptomatic persons. Results No difference was shown in the diagnostic accuracy of median nerve distal motor latency, digit-wrist sensory latency, wrist-palm sensory conduction velocity, and wrist-palm/forearm sensory conduction velocity ratio (area under curve, 0.75–0.76. Median-ulnar digit-wrist sensory latency difference had a significantly higher diagnostic accuracy (area under curve, 0.80. Using the optimal cutoff value of 0.8 ms for abnormal sensory latency difference shown on the ROC curve the sensitivity was 70%, specificity 82%, positive predictive value 19% and negative predictive value 98%. Based on the clinical diagnosis

  11. Health facility-based malaria surveillance: The effects of age, area of residence and diagnostics on test positivity rates

    Directory of Open Access Journals (Sweden)

    Francis Damon

    2012-07-01

    Full Text Available Abstract Background The malaria test positivity rate (TPR is increasingly used as an indicator of malaria morbidity because TPR is based on laboratory-confirmed cases and is simple to incorporate into existing surveillance systems. However, temporal trends in TPR may reflect changes in factors associated with malaria rather than true changes in malaria morbidity. This study examines the effects of age, area of residence and diagnostic test on TPR at two health facilities in regions of Uganda with differing malaria endemicity. Methods The analysis included data from diagnostic blood smears performed at health facilities in Walukuba and Aduku between January 2009 and December 2010. The associations between age and time and between age and TPR were evaluated independently to determine the potential for age to confound temporal trends in TPR. Subsequently, differences between observed TPR and TPR adjusted for age were compared to determine if confounding was present. A similar analysis was performed for area of residence. Temporal trends in observed TPR were compared to trends in TPR expected using rapid diagnostic tests, which were modelled based upon sensitivity and specificity in prior studies. Results Age was independently associated with both TPR and time at both sites. At Aduku, age-adjusted TPR increased relative to observed TPR due to the association between younger age and TPR and the gradual increase in age distribution. At Walukuba, there were no clear differences between observed and age-adjusted TPR. Area of residence was independently associated with both TPR and time at both sites, though there were no clear differences in temporal trends in area of residence-adjusted TPR and observed TPR at either site. Expected TPR with pLDH- and HRP-2-based rapid diagnostic tests (RDTs was higher than observed TPR at all time points at both sites. Conclusions Adjusting for potential confounders such as age and area of residence can ensure that

  12. Beam-Based Diagnostics of RF-Breakdown in the Two-Beam Test-Stand in CTF3

    CERN Document Server

    Johnson, M

    2007-01-01

    The general outline of a beam-based diagnostic method of RF-breakdown, using BPMs, at the two-beam test-stand in CTF3 is discussed. The basic components of the set-up and their functions in the diagnostic are described. Estimations of the expected error in the measured parameters are performed.

  13. Final Report for "Modeling Electron Cloud Diagnostics for High-Intensity Proton Accelerators"

    Energy Technology Data Exchange (ETDEWEB)

    Seth A Veitzer

    2009-09-25

    Electron clouds in accelerators such as the ILC degrade beam quality and limit operating efficiency. The need to mitigate electron clouds has a direct impact on the design and operation of these accelerators, translating into increased cost and reduced performance. Diagnostic techniques for measuring electron clouds in accelerating cavities are needed to provide an assessment of electron cloud evolution and mitigation. Accurate numerical modeling of these diagnostics is needed to validate the experimental techniques. In this Phase I, we developed detailed numerical models of microwave propagation through electron clouds in accelerating cavities with geometries relevant to existing and future high-intensity proton accelerators such as Project X and the ILC. Our numerical techniques and simulation results from the Phase I showed that there was a high probability of success in measuring both the evolution of electron clouds and the effects of non-uniform electron density distributions in Phase II.

  14. Modelling, diagnostics and experimental analysis of plasma assisted processes for material treatment

    OpenAIRE

    Boselli, Marco

    2015-01-01

    This work presents results from experimental investigations of several different atmospheric pressure plasmas applications, such as Metal Inert Gas (MIG) welding and Plasma Arc Cutting (PAC) and Welding (PAW) sources, as well as Inductively Coupled Plasma (ICP) torches. The main diagnostic tool that has been used is High Speed Imaging (HSI), often assisted by Schlieren imaging to analyse non-visible phenomena. Furthermore, starting from thermo-fluid-dynamic models developed by the University ...

  15. Estimating the True Accuracy of Diagnostic Tests for Dengue Infection Using Bayesian Latent Class Models

    OpenAIRE

    Wirichada Pan-ngum; Blacksell, Stuart D; Yoel Lubell; Sasithon Pukrittayakamee; Bailey, Mark S.; Janaka de Silva, H.; David G Lalloo; Day, Nicholas P. J.; White, Lisa J; Direk Limmathurotsakul

    2013-01-01

    BACKGROUND: Accuracy of rapid diagnostic tests for dengue infection has been repeatedly estimated by comparing those tests with reference assays. We hypothesized that those estimates might be inaccurate if the accuracy of the reference assays is not perfect. Here, we investigated this using statistical modeling. METHODS/PRINCIPAL FINDINGS: Data from a cohort study of 549 patients suspected of dengue infection presenting at Colombo North Teaching Hospital, Ragama, Sri Lanka, that described the...

  16. Synthetic–schematic representation of the model of clinical diagnostic-therapeutic method

    OpenAIRE

    Luis Alberto Corona Martínez

    2010-01-01

    The use of a systemic approach in the theoretical analysis of the clinical method has allowed the elaboration of an schematic and synthetic representation of the new model of clinical diagnostic- therapeutic method developed from the conception of the medical assistance as a taking decisions process. The identification of the main components of the clinical method system, as well as of the interrelations established among these, facilitate the understanding of the medical attention process, a...

  17. Model Based Definition

    Science.gov (United States)

    Rowe, Sidney E.

    2010-01-01

    In September 2007, the Engineering Directorate at the Marshall Space Flight Center (MSFC) created the Design System Focus Team (DSFT). MSFC was responsible for the in-house design and development of the Ares 1 Upper Stage and the Engineering Directorate was preparing to deploy a new electronic Configuration Management and Data Management System with the Design Data Management System (DDMS) based upon a Commercial Off The Shelf (COTS) Product Data Management (PDM) System. The DSFT was to establish standardized CAD practices and a new data life cycle for design data. Of special interest here, the design teams were to implement Model Based Definition (MBD) in support of the Upper Stage manufacturing contract. It is noted that this MBD does use partially dimensioned drawings for auxiliary information to the model. The design data lifecycle implemented several new release states to be used prior to formal release that allowed the models to move through a flow of progressive maturity. The DSFT identified some 17 Lessons Learned as outcomes of the standards development, pathfinder deployments and initial application to the Upper Stage design completion. Some of the high value examples are reviewed.

  18. Computer based diagnostic and control system for a 120 keV neutral beam test stand

    International Nuclear Information System (INIS)

    The computer based system provides data acquisition, analysis, display, archival, and control functions for the 120 KEV test stand IIIa at Lawrence Berkeley Laboratory. The system supports calorimeter arrays and spectrometer diagnostics, controls all power supplies and provides 7 modes of control ranging from manual control with computer monitor to full auto conditioning with an auto sweep capability for parameter variation studies. This paper describes the software structure, I/O techniques, control algorithms, hardware configuration, and system performance. Conclusions based on system performance provide useful insight for design of neutral beam control systems for use on large plasma devices

  19. Rapid Immunoglobulin M-Based Dengue Diagnostic Test Using Surface Plasmon Resonance Biosensor

    OpenAIRE

    Peyman Jahanshahi; Erfan Zalnezhad; Shamala Devi Sekaran; Faisal Rafiq Mahamd Adikan

    2014-01-01

    Surface plasmon resonance (SPR) is a medical diagnosis technique with high sensitivity and specificity. In this research, a new method based on SPR is proposed for rapid, 10-minute detection of the anti-dengue virus in human serum samples. This novel technique, known as rapid immunoglobulin M (IgM)-based dengue diagnostic test, can be utilized quickly and easily at the point of care. Four dengue virus serotypes were used as ligands on a biochip. According to the results, a serum volume of onl...

  20. Management system of personnel dosimetry based on ISO 9001:2008 for medical diagnostic

    International Nuclear Information System (INIS)

    MDose is a computer management system of personal dosimetry in diagnostic radiology services physician based on ISO 9001:9008 management system. According to Brazilian law all service radiology should implement a control of personal dosimetry in addition to radiation doses greater than 1.5 mSv/year service should do research of high dose, which is to identify the causes the resulting dose increase professional. This work is based on the use of the PDCA cycle in a JAVA software developed as a management method in the analysis of high doses in order to promote systematic and continuous improvement within the organization of radiological protection of workers

  1. Cooperative research and development for artificial intelligence based reactor diagnostic system

    International Nuclear Information System (INIS)

    Artificial Intelligence (AI) techniques in the form of knowledge-based Expert Systems (ESs) have been proposed to provide on-line decision-making support for plant operators during both normal and emergency conditions. However, in spite of the great interest in these advanced techniques, their application in the diagnosis of large-scale processes has not yet reached its full potential because of limitations of the knowledge base. These limitations include problems with knowledge acquisition and the use of an event-oriented approach for process diagnosis. To investigate the capabilities of this two-level hierarchical knowledge structure, Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL)are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA) project to perform feasibility studies on the proposed diagnostic system. Investigations are being performed in the construction of a physics-based plant level process diagnostic ES and the characterization of component-level fault project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use T-H signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance. To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. This is an ongoing multi-year project and the remainder of this paper presents a mid-term status report

  2. Estimating the true accuracy of diagnostic tests for dengue infection using bayesian latent class models.

    Directory of Open Access Journals (Sweden)

    Wirichada Pan-ngum

    Full Text Available BACKGROUND: Accuracy of rapid diagnostic tests for dengue infection has been repeatedly estimated by comparing those tests with reference assays. We hypothesized that those estimates might be inaccurate if the accuracy of the reference assays is not perfect. Here, we investigated this using statistical modeling. METHODS/PRINCIPAL FINDINGS: Data from a cohort study of 549 patients suspected of dengue infection presenting at Colombo North Teaching Hospital, Ragama, Sri Lanka, that described the application of our reference assay (a combination of Dengue IgM antibody capture ELISA and IgG antibody capture ELISA and of three rapid diagnostic tests (Panbio NS1 antigen, IgM antibody and IgG antibody rapid immunochromatographic cassette tests were re-evaluated using bayesian latent class models (LCMs. The estimated sensitivity and specificity of the reference assay were 62.0% and 99.6%, respectively. Prevalence of dengue infection (24.3%, and sensitivities and specificities of the Panbio NS1 (45.9% and 97.9%, IgM (54.5% and 95.5% and IgG (62.1% and 84.5% estimated by bayesian LCMs were significantly different from those estimated by assuming that the reference assay was perfect. Sensitivity, specificity, PPV and NPV for a combination of NS1, IgM and IgG cassette tests on admission samples were 87.0%, 82.8%, 62.0% and 95.2%, respectively. CONCLUSIONS: Our reference assay is an imperfect gold standard. In our setting, the combination of NS1, IgM and IgG rapid diagnostic tests could be used on admission to rule out dengue infection with a high level of accuracy (NPV 95.2%. Further evaluation of rapid diagnostic tests for dengue infection should include the use of appropriate statistical models.

  3. Diagnostic model of 3-D circulation in the Arabian Sea and western equatorial Indian Ocean: Results of monthly mean sea surface topography

    Digital Repository Service at National Institute of Oceanography (India)

    Bahulayan, N.; Shaji, C.

    A three-dimensional diagnostic model has been developed to compute the monthly mean circulation and sea surface topography in the Western Tropical Indian Ocean north of 20 degrees S and west of 80 degrees E. The diagnostic model equations...

  4. Physics-Based Methods of Failure Analysis and Diagnostics in Human Space Flight

    Science.gov (United States)

    Smelyanskiy, Vadim N.; Luchinsky, Dmitry Georgievich; Hafiychuk, Vasyl Nmn; Osipov, Viatcheslav V.; Patterson-Hine, F. Ann

    2010-01-01

    The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier

  5. Prevention of Disease Complications Through Diagnostic Models: How to Tackle the Problem of Missing Data?

    Directory of Open Access Journals (Sweden)

    M Marzban

    2012-01-01

    Full Text Available Background: Diagnostic models are frequently used to assess the role of risk factors on disease complications, and therefore to avoid them. Missing data is an issue that challenges the model making. The aim of this study was to develop a diagnostic model to predict death in HIV/ AIDS patients when missing data exist.Methods: HIV patients (n=1460 referred to Voluntary Consoling and Testing Center (VCT of Shiraz southern Iran during 2004-2009 were recruited. Univariate association between variables and death was assessed. Only variables which had univariate P< 0.25 were selected to be offered to the Multifactorial models. First, patients with missing data on candidate variables were deleted (C-C model. Then, applying Multivariable Imputation via Chained Equations (MICE, missing data were imputed. Logistic regression was fitted to C-C and imputed data sets (MICE model. Models were compared in terms of number of variables retained in the final model, width of confidence intervals, and discrimination ability.Result: About 22% of data were lost in C-C model. Number of variables retained in the C-C and MICE models was 2 and 6 respectively. Confidence Intervals (C.I. corresponding to C-C model was wider than that of MICE. The MICE model showed greater discrimination ability than C-C model (70% versus 64%.Conclusion: The -C analysis resulted to loss of power and wide CI's. Once missing data were imputed, more variables reached significance level and C.I.'s were narrower. Therefore, we do recommend the application of the imputation method for handling missing data.

  6. Prevention of Disease Complications through Diagnostic Models: How to Tackle the Problem of Missing Data?

    Science.gov (United States)

    Baneshi, MR; Faramarzi, H; Marzban, M

    2012-01-01

    Background: Diagnostic models are frequently used to assess the role of risk factors on disease complications, and therefore to avoid them. Missing data is an issue that challenges the model making. The aim of this study was to develop a diagnostic model to predict death in HIV/AIDS patients when missing data exist. Methods: HIV patients (n=1460) referred to Voluntary Consoling and Testing Center (VCT) of Shiraz southern Iran during 2004–2009 were recruited. Univariate association between variables and death was assessed. Only variables which had univariate P< 0.25 were selected to be offered to the Multifactorial models. First, patients with missing data on candidate variables were deleted (C-C model). Then, applying Multivariable Imputation via Chained Equations (MICE), missing data were imputed. Logistic regression was fitted to C-C and imputed data sets (MICE model). Models were compared in terms of number of variables retained in the final model, width of confidence intervals, and discrimination ability. Result: About 22% of data were lost in C-C model. Number of variables retained in the C-C and MICE models was 2 and 6 respectively. Confidence Intervals (C.I.) corresponding to C-C model was wider than that of MICE. The MICE model showed greater discrimination ability than C-C model (70% versus 64%). Conclusion: The C-C analysis resulted to loss of power and wide CI's. Once missing data were imputed, more variables reached significance level and C.I.'s were narrower. Therefore, we do recommend the application of the imputation method for handling missing data. PMID:23113124

  7. Laser-based diagnostics for characterizing materials exposed to a plasma environment

    Science.gov (United States)

    Shaw, G. C.; Biewer, T. M.; Caughman, J. B. O.; Goulding, R.; Leonard, K.; Lore, J.; Martin, M.; Martin, R.; Rapp, J.; Wirth, B.

    2013-10-01

    To address the needs of fusion reactors, diagnostic techniques for plasma-material interactions (PMI) are being developed at ORNL. Laser-based diagnostic techniques (LBDT) will be used to both characterize the plasma environment and probe the material surface during plasma exposure. A Nd:YAG laser is needed for LBDT. Initial setup and diagnostic testing of the beam will be performed before installing it onto the ORNL device, PHISX (Prototype High Intensity Source Experiment). Installation of the Nd:YAG laser on PHISX, will enable Thomson Scattering (TS) measurements as well as Laser Induced Ablation/Breakdown/Desorption Spectroscopy (LIAS/LIBS/LIDS) to be performed in-situ on material targets. The material targets can be further characterized ex-situ by surface techniques available at ORNL; ex-situ results will be compared to the in-situ characterizations. This poster will show the initial setup and plans for LBDT on PHISX at ORNL. This work was supported by the US. D.O.E. contract DE-AC05-00OR22725.

  8. Image-based diagnostic aid for interstitial lung disease with secondary data integration

    Science.gov (United States)

    Depeursinge, Adrien; Müller, Henning; Hidki, Asmâa; Poletti, Pierre-Alexandre; Platon, Alexandra; Geissbuhler, Antoine

    2007-03-01

    Interstitial lung diseases (ILDs) are a relatively heterogeneous group of around 150 illnesses with often very unspecific symptoms. The most complete imaging method for the characterisation of ILDs is the high-resolution computed tomography (HRCT) of the chest but a correct interpretation of these images is difficult even for specialists as many diseases are rare and thus little experience exists. Moreover, interpreting HRCT images requires knowledge of the context defined by clinical data of the studied case. A computerised diagnostic aid tool based on HRCT images with associated medical data to retrieve similar cases of ILDs from a dedicated database can bring quick and precious information for example for emergency radiologists. The experience from a pilot project highlighted the need for detailed database containing high-quality annotations in addition to clinical data. The state of the art is studied to identify requirements for image-based diagnostic aid for interstitial lung disease with secondary data integration. The data acquisition steps are detailed. The selection of the most relevant clinical parameters is done in collaboration with lung specialists from current literature, along with knowledge bases of computer-based diagnostic decision support systems. In order to perform high-quality annotations of the interstitial lung tissue in the HRCT images an annotation software and its own file format is implemented for DICOM images. A multimedia database is implemented to store ILD cases with clinical data and annotated image series. Cases from the University & University Hospitals of Geneva (HUG) are retrospectively and prospectively collected to populate the database. Currently, 59 cases with certified diagnosis and their clinical parameters are stored in the database as well as 254 image series of which 26 have their regions of interest annotated. The available data was used to test primary visual features for the classification of lung tissue patterns

  9. Tuning, Diagnostics & Data Preparation for Generalized Linear Models Supervised Algorithm in Data Mining Technologies

    Directory of Open Access Journals (Sweden)

    Sachin Bhaskar

    2015-07-01

    Full Text Available Data mining techniques are the result of a long process of research and product development. Large amount of data are searched by the practice of Data Mining to find out the trends and patterns that go beyond simple analysis. For segmentation of data and also to evaluate the possibility of future events, complex mathematical algorithms are used here. Specific algorithm produces each Data Mining model. More than one algorithms are used to solve in best way by some Data Mining problems. Data Mining technologies can be used through Oracle. Generalized Linear Models (GLM Algorithm is used in Regression and Classification Oracle Data Mining functions. For linear modelling, GLM is one the popular statistical techniques. For regression and binary classification, GLM is implemented by Oracle Data Mining. Row diagnostics as well as model statistics and extensive co-efficient statistics are provided by GLM. It also supports confidence bounds.. This paper outlines and produces analysis of GLM algorithm, which will guide to understand the tuning, diagnostics & data preparation process and the importance of Regression & Classification supervised Oracle Data Mining functions and it is utilized in marketing, time series prediction, financial forecasting, overall business planning, trend analysis, environmental modelling, biomedical and drug response modelling, etc.

  10. Applying the Weisbord model as a diagnostic framework for organizational analysis

    Directory of Open Access Journals (Sweden)

    Kontić Ljiljana

    2012-06-01

    Full Text Available This study investigates the effectiveness of the Weisbord's Six Box Model as a diagnostic framework for assessing the factors affecting organizational development. The research area consisted of an international bank which operates in Serbia. In order to identify strengths and weaknesses in the bank, Weisbord's diagnostic questionnaire has been used. Respondents were 137 middle managers in the selected bank. The research results revealed that the bank has strengths in the areas of leadership, relations, purpose and helpful mechanisms. The weaker aspects were organizational structure and rewards. The options for improving structure, as well as rewards system, are suggested. The findings add to the existing literature on organizational diagnosis in cross-cultural contexts.

  11. Some analytic diagnostic models for transport processes in estuarine and coastal waters

    International Nuclear Information System (INIS)

    Advection and dispersion processes in estuarine and coastal waters are briefly reviewed. Beginning from the basic macroscopic equations of transport for a substance diluted or suspended in the considered body of water,several levels of filtering in time and space are described and applied to obtain suitable diagnostic mathematical models both with scale effects and gaussian.The solutions of the aforementioned models,for initial distributions and boundary conditions with enough symmetry,are discussed, as well as their applications to a parameter characterization of the transport properties of the receiving body of water

  12. The graphics-based human interface to the DISYS diagnostic/control guidance system at EBR-2

    International Nuclear Information System (INIS)

    An initial graphics based interface to the real-time DISYS diagnostic system has been developed using the multi-tasking capabilities of the UNIX operating system and X-Windows 11 Xlib graphics library. This system is interfaced to live plant data at the Experimental Breeder Reactor (EBR-2) for the Argon Cooling System of fuel handling operations and the steam plant. The interface includes an intelligent process schematic which highlights problematic components and sensors based on the results of the diagnostic computations. If further explanation of a faulted component is required, the user can call up a display of the diagnostic computations presented in a tree-like diagram. Numerical data on the process schematic and optional diagnostic tree are updated as new real-time data becomes available. The initial X-Windows 11 based interface will be further enhanced using VI Corporation DATAVIEWS graphical data base software. 5 refs., 6 figs

  13. Development and Evaluation of the Diagnostic Power for a Computer-Based Two-Tier Assessment

    Science.gov (United States)

    Lin, Jing-Wen

    2016-02-01

    This study adopted a quasi-experimental design with follow-up interview to develop a computer-based two-tier assessment (CBA) regarding the science topic of electric circuits and to evaluate the diagnostic power of the assessment. Three assessment formats (i.e., paper-and-pencil, static computer-based, and dynamic computer-based tests) using two-tier items were conducted on Grade 4 (n = 90) and Grade 5 (n = 86) students, respectively. One-way ANCOVA was conducted to investigate whether the different assessment formats affected these students' posttest scores on both the phenomenon and reason tiers, and confidence rating for an answer was assessed to diagnose the nature of students' responses (i.e., scientific answer, guessing, alternative conceptions, or knowledge deficiency). Follow-up interview was adopted to explore whether and how the various CBA representations influenced both graders' responses. Results showed that the CBA, in particular the dynamic representation format, allowed students who lacked prior knowledge (Grade 4) to easily understand the question stems. The various CBA representations also potentially encouraged students who already had learning experience (Grade 5) to enhance the metacognitive judgment of their responses. Therefore, CBA could reduce students' use of test-taking strategies and provide better diagnostic power for a two-tier instrument than the traditional paper-based version.

  14. Development and Evaluation of the Diagnostic Power for a Computer-Based Two-Tier Assessment

    Science.gov (United States)

    Lin, Jing-Wen

    2016-06-01

    This study adopted a quasi-experimental design with follow-up interview to develop a computer-based two-tier assessment (CBA) regarding the science topic of electric circuits and to evaluate the diagnostic power of the assessment. Three assessment formats (i.e., paper-and-pencil, static computer-based, and dynamic computer-based tests) using two-tier items were conducted on Grade 4 ( n = 90) and Grade 5 ( n = 86) students, respectively. One-way ANCOVA was conducted to investigate whether the different assessment formats affected these students' posttest scores on both the phenomenon and reason tiers, and confidence rating for an answer was assessed to diagnose the nature of students' responses (i.e., scientific answer, guessing, alternative conceptions, or knowledge deficiency). Follow-up interview was adopted to explore whether and how the various CBA representations influenced both graders' responses. Results showed that the CBA, in particular the dynamic representation format, allowed students who lacked prior knowledge (Grade 4) to easily understand the question stems. The various CBA representations also potentially encouraged students who already had learning experience (Grade 5) to enhance the metacognitive judgment of their responses. Therefore, CBA could reduce students' use of test-taking strategies and provide better diagnostic power for a two-tier instrument than the traditional paper-based version.

  15. Implementing an ultrasound-based protocol for diagnosingappendicitis while maintaining diagnostic accuracy

    Energy Technology Data Exchange (ETDEWEB)

    Van Atta, Angela J. [University of Utah School of Medicine, Salt Lake City, UT (United States); Baskin, Henry J.; Maves, Connie K.; Dansie, David M. [Primary Children' s Hospital, Department of Radiology, Salt Lake City, UT (United States); Rollins, Michael D. [University of Utah School of Medicine, Department of Surgery, Division of Pediatric Surgery, Salt Lake City, UT (United States); Bolte, Robert G. [University of Utah School of Medicine, Department of Pediatrics, Division of Pediatric Emergency Medicine, Salt Lake City, UT (United States); Mundorff, Michael B.; Andrews, Seth P. [Primary Children' s Hospital, Systems Improvement, Salt Lake City, UT (United States)

    2015-05-01

    The use of ultrasound to diagnose appendicitis in children is well-documented but not universally employed outside of pediatric academic centers, especially in the United States. Various obstacles make it difficult for institutions and radiologists to abandon a successful and accurate CT-based imaging protocol in favor of a US-based protocol. To describe how we overcame barriers to implementing a US-based appendicitis protocol among a large group of nonacademic private-practice pediatric radiologists while maintaining diagnostic accuracy and decreasing medical costs. A multidisciplinary team of physicians (pediatric surgery, pediatric emergency medicine and pediatric radiology) approved an imaging protocol using US as the primary modality to evaluate suspected appendicitis with CT for equivocal cases. The protocol addressed potential bias against US and accommodated for institutional limitations of radiologist and sonographer experience and availability. Radiologists coded US reports according to the probability of appendicitis. Radiology reports were compared with clinical outcomes to assess diagnostic accuracy. During the study period, physicians from each group were apprised of the interim US protocol accuracy results. Problematic cases were discussed openly. A total of 512 children were enrolled and underwent US for evaluation of appendicitis over a 30-month period. Diagnostic accuracy was comparable to published results for combined US/CT protocols. Comparing the first 12 months to the last 12 months of the study period, the proportion of children achieving an unequivocal US result increased from 30% (51/169) to 53% (149/282) and the proportion of children undergoing surgery based solely on US findings increased from 55% (23/42) to 84% (92/109). Overall, 63% (325/512) of patients in the protocol did not require a CT. Total patient costs were reduced by $30,182 annually. We overcame several barriers to implementing a US protocol. During the study period our

  16. MJO Simulation Diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Waliser, D; Sperber, K; Hendon, H; Kim, D; Maloney, E; Wheeler, M; Weickmann, K; Zhang, C; Donner, L; Gottschalck, J; Higgins, W; Kang, I; Legler, D; Moncrieff, M; Schubert, S; Stern, W; Vitart, F; Wang, B; Wang, W; Woolnough, S

    2008-06-02

    The Madden-Julian Oscillation (MJO) interacts with, and influences, a wide range of weather and climate phenomena (e.g., monsoons, ENSO, tropical storms, mid-latitude weather), and represents an important, and as yet unexploited, source of predictability at the subseasonal time scale. Despite the important role of the MJO in our climate and weather systems, current global circulation models (GCMs) exhibit considerable shortcomings in representing this phenomenon. These shortcomings have been documented in a number of multi-model comparison studies over the last decade. However, diagnosis of model performance has been challenging, and model progress has been difficult to track, due to the lack of a coherent and standardized set of MJO diagnostics. One of the chief objectives of the US CLIVAR MJO Working Group is the development of observation-based diagnostics for objectively evaluating global model simulations of the MJO in a consistent framework. Motivation for this activity is reviewed, and the intent and justification for a set of diagnostics is provided, along with specification for their calculation, and illustrations of their application. The diagnostics range from relatively simple analyses of variance and correlation, to more sophisticated space-time spectral and empirical orthogonal function analyses. These diagnostic techniques are used to detect MJO signals, to construct composite life-cycles, to identify associations of MJO activity with the mean state, and to describe interannual variability of the MJO.

  17. New Diagnostic, Launch and Model Control Techniques in the NASA Ames HFFAF Ballistic Range

    Science.gov (United States)

    Bogdanoff, David W.

    2012-01-01

    This report presents new diagnostic, launch and model control techniques used in the NASA Ames HFFAF ballistic range. High speed movies were used to view the sabot separation process and the passage of the model through the model splap paper. Cavities in the rear of the sabot, to catch the muzzle blast of the gun, were used to control sabot finger separation angles and distances. Inserts were installed in the powder chamber to greatly reduce the ullage volume (empty space) in the chamber. This resulted in much more complete and repeatable combustion of the powder and hence, in much more repeatable muzzle velocities. Sheets of paper or cardstock, impacting one half of the model, were used to control the amplitudes of the model pitch oscillations.

  18. Assessing FPAR Source and Parameter Optimization Scheme in Application of a Diagnostic Carbon Flux Model

    Energy Technology Data Exchange (ETDEWEB)

    Turner, D P; Ritts, W D; Wharton, S; Thomas, C; Monson, R; Black, T A

    2009-02-26

    The combination of satellite remote sensing and carbon cycle models provides an opportunity for regional to global scale monitoring of terrestrial gross primary production, ecosystem respiration, and net ecosystem production. FPAR (the fraction of photosynthetically active radiation absorbed by the plant canopy) is a critical input to diagnostic models, however little is known about the relative effectiveness of FPAR products from different satellite sensors nor about the sensitivity of flux estimates to different parameterization approaches. In this study, we used multiyear observations of carbon flux at four eddy covariance flux tower sites within the conifer biome to evaluate these factors. FPAR products from the MODIS and SeaWiFS sensors, and the effects of single site vs. cross-site parameter optimization were tested with the CFLUX model. The SeaWiFs FPAR product showed greater dynamic range across sites and resulted in slightly reduced flux estimation errors relative to the MODIS product when using cross-site optimization. With site-specific parameter optimization, the flux model was effective in capturing seasonal and interannual variation in the carbon fluxes at these sites. The cross-site prediction errors were lower when using parameters from a cross-site optimization compared to parameter sets from optimization at single sites. These results support the practice of multisite optimization within a biome for parameterization of diagnostic carbon flux models.

  19. Diagnostic study of errors in the simulation of tropical continental precipitation in general circulation models

    Directory of Open Access Journals (Sweden)

    J. Srinivasan

    Full Text Available A simple diagnostic model has been used to identify the parameters that induce large errors in the simulation of tropical precipitation in atmospheric General Circulation models (GCM. The GCM that have been considered are those developed by the National Center for Environmental Prediction (NCEP, the National Center for Atmospheric Research (NCAR and the Japanese Meteorological Agency (JMA. These models participated in the phase II of the Atmospheric Model Inter-comparison Project (AMIP II and simulated the climate for the period 1979 to 1995. The root mean-square error in the simulation of precipitation in tropical continents was larger in NCEP and NCAR simulations than in the JMA simulation. The large error in the simulation of precipitation in NCEP was due to errors in the vertical profile of water vapour. The large error in precipitation in NCAR in North Africa was due to an error in net radiation (at the top of the atmosphere. The simple diagnostic model predicts that the moisture converge is a nonlinear function of integrated water vapour. The large error in the interannual variance of rainfall in NCEP over India has been shown to be due to this nonlinearity.

    Key words. Meteorology and atmospheric dynamics (precipitation; tropical meteorology; convective processes

  20. Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

    Directory of Open Access Journals (Sweden)

    A. P. Palacz

    2013-11-01

    Full Text Available Modeling and monitoring plankton functional types (PFTs is challenged by the insufficient amount of field measurements of ground truths in both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom–coccolithophore coexistence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

  1. Accurate focal spot diagnostics based on a single shot coherent modulation imaging

    International Nuclear Information System (INIS)

    A single-shot method based on coherent modulation imaging is presented for the diagnostics of the focal spot of laser facilities. The laser beam to be measured first illuminates a highly random phase plate with a known structure and subsequently the intensity of the resulting diffraction pattern is recorded by a charge-coupled device positioned behind the phase plate. Intensity distribution at the focus of the laser beam is accurately reconstructed with the coherent modulation imaging method. The feasibility of this method is demonstrated with an experiment involving a He–Ne laser. (letter)

  2. Air Pollution and Newly Diagnostic Autism Spectrum Disorders: A Population-Based Cohort Study in Taiwan

    OpenAIRE

    Jung, Chau-Ren; Lin, Yu-Ting; Hwang, Bing-Fang

    2013-01-01

    There is limited evidence that long-term exposure to ambient air pollution increases the risk of childhood autism spectrum disorder (ASD). The objective of the study was to investigate the associations between long-term exposure to air pollution and newly diagnostic ASD in Taiwan. We conducted a population-based cohort of 49,073 children age less than 3 years in 2000 that were retrieved from Taiwan National Insurance Research Database and followed up from 2000 through 2010. Inverse distance w...

  3. A Pull-in Based Test Mechanism for Device Diagnostic and Process Characterization

    Directory of Open Access Journals (Sweden)

    L. A. Rocha

    2008-01-01

    Full Text Available A test technique for capacitive MEMS accelerometers and electrostatic microactuators, based on the measurement of pull-in voltages and resonance frequency, is described. Using this combination of measurements, one can estimate process-induced variations in the device layout dimensions as well as deviations from nominal value in material properties, which can be used either for testing or device diagnostics purposes. Measurements performed on fabricated devices confirm that the 250 nm overetch observed on SEM images can be correctly estimated using the proposed technique.

  4. A Turbidity Test Based Centrifugal Microfluidics Diagnostic System for Simultaneous Detection of HBV, HCV, and CMV

    Directory of Open Access Journals (Sweden)

    Hung-Cheng Chang

    2015-01-01

    Full Text Available This paper presents a LAMP- (loop-mediated isothermal amplification- based lab-on-disk optical system that allows the simultaneous detection of hepatitis B virus, hepatitis C virus, and cytomegalovirus. The various flow stages are controlled in the proposed system using different balance among centrifugal pumping, Coriolis pumping, and the capillary force. We have implemented a servo system for positioning and speed control for the heating and centrifugal pumping. We have also successfully employed a polymer light-emitting diode section for turbidity detection. The easy-to-use one-click system can perform diagnostics in less than 1 hour.

  5. Comprehensive evaluation of a somatostatin-based radiolabelled antagonist for diagnostic imaging and radionuclide therapy

    International Nuclear Information System (INIS)

    Targeting of tumours positive for somatostatin receptors (sst) with radiolabelled peptides is of interest for tumour localization, staging, therapy follow-up and targeted radionuclide therapy. The peptides used clinically are exclusively agonists, but recently we have shown that the radiolabelled somatostatin-based antagonist 111In-DOTA-sst2-ANT may be preferable to agonists. However, a comprehensive study of this radiolabelled antagonist to determine its significance was lacking. The present report describes the evaluation of this novel antagonist labelled with 111In and 177Lu in three different tumour models. Radiopeptide binding, internalization and dissociation studies were performed using cells expressing HEK293-rsst2. Biodistribution studies were performed in HEK293-rsst2, HEK293-hsst2 and HEK293-rsst3 xenografted mice. Saturation binding analysis confirmed earlier IC50 data for 111/natIn-DOTA-sst2-ANT and showed similar affinity of 177/natLu-DOTA-sst2-ANT for the sst2. Only low internalization was found in cell culture (6.68 ± 0.06 % at 4 h), which was not unexpected for an antagonist, and this could be further reduced by the addition of sucrose. No internalization was observed in HEK293 cells not expressing sst. Both results indicate that the internalization was specific. 111In-DOTA-sst2-ANT and 177Lu-DOTA-sst2-ANT were shown to target tumour xenografts expressing the rat and the human sst2 receptor with no differences in their uptake or pharmacokinetics. The uptake in rsst2 and hsst2 was high (about 30 %IA/g 4 h after injection) and surprisingly long-lasting (about 20-23 %IA/g 24 h after injection). Kidney uptake was blocked by approximately 50 % by lysine or Gelofusine. These results indicate that radiolabelled somatostatin-based antagonists may be superior to corresponding agonists. The long tumour retention time of 177Lu-DOTA-sst2-ANT indicates that this new class of compounds is of relevance not only in diagnostic imaging but also in targeted

  6. Comprehensive evaluation of a somatostatin-based radiolabelled antagonist for diagnostic imaging and radionuclide therapy

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xuejuan; Fani, Melpomeni [University Hospital Basel, Division of Radiological Chemistry, Basel (Switzerland); Schulz, Stefan [Jena University Hospital - Friedrich Schiller University Jena, Department of Pharmacology and Toxicology, Jena (Germany); Rivier, Jean [The Salk Institute for Biological Studies, The Clayton Foundation Laboratories for Peptide Biology, La Jolla, CA (United States); Reubi, Jean Claude [University of Bern, Division of Cell Biology and Experimental Cancer Research, Institute of Pathology, Bern (Switzerland); Maecke, Helmut R. [University Hospital Basel, Division of Radiological Chemistry, Basel (Switzerland); University Hospital Freiburg, Department of Nuclear Medicine, Freiburg (Germany)

    2012-12-15

    Targeting of tumours positive for somatostatin receptors (sst) with radiolabelled peptides is of interest for tumour localization, staging, therapy follow-up and targeted radionuclide therapy. The peptides used clinically are exclusively agonists, but recently we have shown that the radiolabelled somatostatin-based antagonist {sup 111}In-DOTA-sst2-ANT may be preferable to agonists. However, a comprehensive study of this radiolabelled antagonist to determine its significance was lacking. The present report describes the evaluation of this novel antagonist labelled with {sup 111}In and {sup 177}Lu in three different tumour models. Radiopeptide binding, internalization and dissociation studies were performed using cells expressing HEK293-rsst{sub 2}. Biodistribution studies were performed in HEK293-rsst{sub 2}, HEK293-hsst{sub 2} and HEK293-rsst{sub 3} xenografted mice. Saturation binding analysis confirmed earlier IC{sub 50} data for {sup 111/nat}In-DOTA-sst2-ANT and showed similar affinity of {sup 177/nat}Lu-DOTA-sst2-ANT for the sst{sub 2}. Only low internalization was found in cell culture (6.68 {+-} 0.06 % at 4 h), which was not unexpected for an antagonist, and this could be further reduced by the addition of sucrose. No internalization was observed in HEK293 cells not expressing sst. Both results indicate that the internalization was specific. {sup 111}In-DOTA-sst2-ANT and {sup 177}Lu-DOTA-sst2-ANT were shown to target tumour xenografts expressing the rat and the human sst{sub 2} receptor with no differences in their uptake or pharmacokinetics. The uptake in rsst{sub 2} and hsst{sub 2} was high (about 30 %IA/g 4 h after injection) and surprisingly long-lasting (about 20-23 %IA/g 24 h after injection). Kidney uptake was blocked by approximately 50 % by lysine or Gelofusine. These results indicate that radiolabelled somatostatin-based antagonists may be superior to corresponding agonists. The long tumour retention time of {sup 177}Lu-DOTA-sst2-ANT indicates that

  7. Gold-based hybrid nanomaterials for biosensing and molecular diagnostic applications.

    Science.gov (United States)

    Kim, Jung Eun; Choi, Ji Hye; Colas, Marion; Kim, Dong Ha; Lee, Hyukjin

    2016-06-15

    The properties of gold nanomaterials are particularly of interest to many researchers, since they show unique physiochemical properties such as optical adsorption of specific wavelength of light, high electrical conductance with rich surface electrons, and facile surface modification with sulfhydryl groups. These properties have facilitated the use of gold nanomaterials in the development of various hybrid systems for biosensors and molecular diagnostics. Combined with various synthetic materials such as fluorescence dyes, polymers, oligonucleotides, graphene oxides (GO), and quantum dots (QDs), the gold-based hybrid nanomaterials offer multi-functionalities in molecular detection with high specificity and sensitivity. These two aspects result in the increase of detection speed as well as the lower detection limits, having shown that this diagnosis method is more effective than other conventional ones. In this review, we have highlighted various examples of nanomaterials for biosensing and molecular diagnostics. The gold-based hybrid systems are categorized by three distinct detection approaches, in which include (1) optical, such as surface plasmon resonance (SPR), RAMAN, and surface-enhanced Raman scattering (SERS), (2) fluorescence, such as förster resonance energy transfer (FRET) and nanomaterial surface energy transfer (NSET), and (3) electrochemical, such as potentiometic, amperometric, and conductometric. Each example provides the detailed mechanism of molecular detection as well as the supporting experimental result with the limit of detection (LOD). Lastly, future perspective on novel development of gold-based hybrid nanomaterials is discussed as well as their challenges. PMID:26894985

  8. Opacity free and space resolved x-ray diagnostics based on satellite lines near H-like Lyα of highly charged ions

    International Nuclear Information System (INIS)

    Space resolved high resolution spectroscopic methods have shown that dielectronic satellite emission in high energy laser produced plasmas is confined to the area of highest density and temperature. Employing satellite transitions near Lyα we demonstrate, that opacity free temperature and density diagnostic can be based solely on the satellite transitions 2lnl' → 1snl' + hv. The exclusion of the resonance line transition in the analysis provides an opacity free diagnostic method with limited need for spatial deconvolution. For the interpretation of the experimental data we have developed a collisional-radiative model involving autoionising states with high n spectator electrons. The atomic data for dielectronic satellite transitions are calculated with different methods and compared also in view for diagnostic applications. For n = 2 satellite transitions we find in general good agreement, however, for higher quantum numbers n, the agreement of data is found to be not satisfactory. (author)

  9. An Integrated Model-Based Diagnostic and Prognostic Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — Systems health monitoring is essential in guar- anteeing the safe, efficient, and correct opera- tion of complex engineered systems. Diagnosis, which consists of...

  10. Navigating the Rapids : The Development of NGS-based Clinical Trial Assays and Companion Diagnostics

    Directory of Open Access Journals (Sweden)

    MatthewJohnMarton

    2014-04-01

    Full Text Available Over the past decade, next generation sequencing (NGS technology has experienced meteoric growth in the aspects of platform, technology and supporting bioinformatics development allowing its widespread and rapid uptake in research settings. More recently, NGS-based genomic data has been exploited to better understand disease development and patient characteristics that influence response to a given therapeutic intervention. Cancer, as a disease characterized by and driven by the tumor genetic landscape, is particularly amenable to NGS-based diagnostic approaches. NGS based technologies are particularly well suited to studying cancer disease development, progression and emergence of resistance, all key factors in the development of next generation cancer diagnostics. Yet, to achieve the promise of NGS based patient treatment, drug developers will need to overcome a number of operational, technical, regulatory and strategic challenges. Here we provide a succinct overview of the state of the clinical NGS field in terms of the available clinically targeted platforms and sequencing technologies. We discuss the various operational and practical aspects of clinical NGS testing that will facilitate or limit the uptake of such assays in routine clinical care. We examine the current strategies for analytical validation of NGS-based assays and ongoing efforts to standardize clinical NGS and build quality control standards for the same. The rapidly evolving CDx landscape for NGS-based assays will be reviewed, highlighting the key areas of concern and suggesting strategies to mitigate risk. The review will conclude with a series of strategic questions that face drug developers and a discussion of the likely future course of NGS-based Dx development efforts.

  11. Collisional-radiative modelling for the spectroscopic diagnostic of turbulent plasmas

    Energy Technology Data Exchange (ETDEWEB)

    Rosato, J.; Lefevre, T.; Escarguel, A.; Capes, H.; Catoire, F.; Marandet, Y.; Stamm, R. [PIIM, Universite de Provence, CNRS, Marseille (France); Rosmej, F.B. [Universite Pierre et Marie Curie, Paris (France)] [LULI, Palaiseau (France); Kadomtsev, M.B.; Levashova, M.G.; Lisitsa, V.S. [NFI, Russian Research Center, Kurchatov Institute, Moscow (Russian Federation); Bonhomme, G. [IJL, Universite de Nancy, CNRS, Vandoeuvre-les-Nancy (France)

    2011-07-01

    Spectroscopy is a diagnostic method widely used in plasma physics research, e.g. in laboratory experiments, in fusion devices or in astrophysics. Information on the plasma parameters (electron density, temperature etc.) can be obtained from the analysis of both line shapes and intensities through the use of suitable models. The aim of the present paper is to assess the role of turbulent fluctuations on line intensity ratios in the case of weakly radiating plasmas. This involves the use of collisional-radiative modelling. In the present work we address the radiation due to atomic lines in turbulent helium plasmas at low density/temperature. The statistical formalism previously used in line shape modelling is adapted in this way, and the atomic populations are calculated with a collisional-radiative code. Different regimes, according to the turbulence correlation time, have been considered. In the static case, which corresponds to low-frequency fluctuations, it has been shown that the turbulence can lead to an increase of the line intensities. An application to helium in realistic experimental conditions has revealed that line ratios are sensitive to the fluctuations, which offers a track to a diagnostic. In the dynamic case, the use of a reduced model in the case of an ideal two-level atom has revealed the possibility for a significant dependence of the atomic populations on the turbulence frequency

  12. Two-dimensional MHD models of solar magnetogranulation. Testing of the models and methods of Stokes diagnostics

    CERN Document Server

    Sheminova, V A

    2012-01-01

    We carried out the Stokes diagnostics of new two-dimensional magnetohydrodynamic models with a continuous evolution of magnetogranulation in the course of two hours of the hydrodynamic (solar) time. Our results agree satisfactorily with the results of Stokes diagnostics of the solar small-scale flux tubes observed in quiet network elements and active plages. The straightforward methods often used in the Stokes diagnostics of solar small-scale magnetic elements were tested by means of the magnetohydrodynamic models. We conclude that the most reliable methods are the determination of magnetic field strength from the separation of the peaks in the Stokes V profiles of the infrared Fe I line 1564.8 nm and the determination of the magnetic inclination angle from the ratio tan^2 gamma approx (Q^2 + U^2)^{1/2}/V^2. The lower limits for such determinations are about 20 mT and 10 degree, respectively. We also conclude that the 2D MHD models of solar magnetogranulation are in accord with observations and may be success...

  13. Scintillator-based diagnostic for fast ion loss measurements on DIII-D.

    Science.gov (United States)

    Fisher, R K; Pace, D C; García-Muñoz, M; Heidbrink, W W; Muscatello, C M; Van Zeeland, M A; Zhu, Y B

    2010-10-01

    A new scintillator-based fast ion loss detector has been installed on DIII-D with the time response (>100 kHz) needed to study energetic ion losses induced by Alfvén eigenmodes and other MHD instabilities. Based on the design used on ASDEX Upgrade, the diagnostic measures the pitch angle and gyroradius of ion losses based on the position of the ions striking the two-dimensional scintillator. For fast time response measurements, a beam splitter and fiberoptics couple a portion of the scintillator light to a photomultiplier. Reverse orbit following techniques trace the lost ions to their possible origin within the plasma. Initial DIII-D results showing prompt losses and energetic ion loss due to MHD instabilities are discussed. PMID:21033833

  14. The simulation of optical diagnostics for crystal growth - Models and results

    Science.gov (United States)

    Banish, M. R.; Clark, R. L.; Kathman, A. D.; Lawson, S. M.

    A computer simulation of a Two Color Holographic Interferometric (TCHI) optical system was performed using a physical (wave) optics model. This model accurately simulates propagation through time-varying, 2-D or 3-D concentration and temperature fields as a wave phenomenon. The model calculates wavefront deformations that can be used to generate fringe patterns. This simulation modeled a proposed TriGlycine sulphate TGS flight experiment by propagating through the simplified onion-like refractive index distribution of the growing crystal and calculating the recorded wavefront deformation. The phase of this wavefront was used to generate sample interferograms that map index of refraction variation. Two such fringe patterns, generated at different wavelengths, were used to extract the original temperature and concentration field characteristics within the growth chamber. This proves feasibility for this TCHI crystal growth diagnostic technique. This simulation provides feedback to the experimental design process.

  15. LSTM based Conversation Models

    OpenAIRE

    Luan, Yi; Ji, Yangfeng; Ostendorf, Mari

    2016-01-01

    In this paper, we present a conversational model that incorporates both context and participant role for two-party conversations. Different architectures are explored for integrating participant role and context information into a Long Short-term Memory (LSTM) language model. The conversational model can function as a language model or a language generation model. Experiments on the Ubuntu Dialog Corpus show that our model can capture multiple turn interaction between participants. The propos...

  16. EICT Based Diagnostic Tool and Monitoring System for EMF Radiation to Sustain Environmental Safety

    Directory of Open Access Journals (Sweden)

    K Parandham

    2013-10-01

    Full Text Available the adverse effects of electromagnetic radiation from mobile phones and communication towers on health issues are being well documented today. However, exact correlation between radiation of communication towers and their radiation levels, are not monitored. Aim of this paper is to study, analyze, apply networking and data mining technologies to develop an EICT based Diagnostic tool and Monitoring system for electromagnetic radiation levels into environment. This system is to network all mobile towers of each service provider as a single entity and then connect all service providers to a central monitoring agency online for continuous monitoring. Since very large numbers of mobile towers exist in India, each state can have its own regional network which is further networked with national central network. This can be enlarged to entire world for monitoring the EMF radiation levels near every mobile tower. For these regional national and international networks the connectivity is to be instituted by the respective service provider. In this paper an attempt is made to logically apply Data Mining and networking technologies to develop a central EICT based diagnostic tool and monitoring system for EMF radiation from each transmission tower. With this system regional, national and international agencies/authorities can monitor the EMF radiation at each and every transmission tower area continuously and verify them with exposure standards. It is proposed to display this information using Integrated Display System in front of monitoring authority at appropriate levels.

  17. Continued experimental evaluations of a diagnostic rule-based expert system for the nuclear industry

    International Nuclear Information System (INIS)

    This experiment which was the second in a series, conducted at the OECD Halden Reactor Project, Halden, Norway in the spring 1991, aimed to assess the effect on nuclear power plant operators diagnostic behaviour when using a rule based diagnostic expert system. The rule based expert system used in the experiment is called DISKET (Diagnosis System Using Knowledge Engineering Technique) and was originally developed by the Japan Atomic Energy Research Institute (JAERI). The experiment was performed in the Halden man-machine laboratory using a full scope pressurized water reactor simulator called NORS. Operator performance in terms of quality of diagnosis is improved by the use of SISKET. The use of the DISKET system also influences operators problem solving behaviour. The main difference between the two experimental conditions can be characterized as while the DISKET users during the diagnosis process are following a strategy which is direct and narrowed, the non-DISKET users are using a much broader and less focused search when trying to diagnose a disturbance. (author)

  18. The diagnostic rules of peripheral lung cancer preliminary study based on data mining technique

    Institute of Scientific and Technical Information of China (English)

    Yongqian Qiang; Youmin Guo; Xue Li; Qiuping Wang; Hao Chen; Duwu Cui

    2007-01-01

    Objective: To discuss the clinical and imaging diagnostic rules of peripheral lung cancer by data mining technique, and to explore new ideas in the diagnosis of peripheral lung cancer, and to obtain early-stage technology and knowledge support of computer-aided detecting (CAD). Methods: 58 cases of peripheral lung cancer confirmed by clinical pathology were collected. The data were imported into the database after the standardization of the clinical and CT findings attributes were identified. The data was studied comparatively based on Association Rules (AR) of the knowledge discovery process and the Rough Set (RS) reduction algorithm and Genetic Algorithm(GA) of the generic data analysis tool (ROSETTA), respectively. Results: The genetic classification algorithm of ROSETTA generates 5 000 or so diagnosis rules. The RS reduction algorithm of Johnson's Algorithm generates 51 diagnosis rules and the AR algorithm generates 123 diagnosis rules. Three data mining methods basically consider gender, age,cough, location, lobulation sign, shape, ground-glass density attributes as the main basis for the diagnosis of peripheral lung cancer. Conclusion: These diagnosis rules for peripheral lung cancer with three data mining technology is same as clinical diagnostic rules, and these rules also can be used to build the knowledge base of expert system. This study demonstrated the potential values of data mining technology in clinical imaging diagnosis and differential diagnosis.

  19. Diagnostics of helium plasma by collisional-radiative modeling and optical emission spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Wonwook; Kwon, Duck-Hee [KAERI, Daejeon (Korea, Republic of)

    2015-05-15

    Optical diagnostics for the electron temperature (T{sub e}) and the electron density (n{sub e}) of fusion plasma is important for understanding and controlling the edge and the divertor plasmas in tokamak. Since the line intensity ratio method using the collisional-radiative modeling and OES (optical emission spectroscopy) is simple and does not disturb the plasma, many fusion devices with TEXTOR, JET, JT-60U, LHD, and so on, have employed the line intensity ratio method as a basic diagnostic tool for neutral helium (He I). The accuracy of the line intensity ratio method depends on the reliability of the cross sections and rate coefficients. We performed state-of-the-art R-matrix calculations including couplings up to n=7 states and the distorted wave (DW) calculations for the electron-impact excitation (EIE) cross sections of He I using the flexible atomic code (FAC). The collisional-radiative model for He I was constructed using the calculated the cross sections. The helium collisional-radiative model for He I was constructed to diagnose the electron temperature and the electron density of the plasma. The electron temperature and density were determined by using the line intensity ratio method.

  20. Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer

    Directory of Open Access Journals (Sweden)

    Stobiecki Maciej

    2009-07-01

    Full Text Available Abstract Background Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry. Methods Blood samples were collected before the start of therapy in a group of 92 patients diagnosed at stages I and II of the disease, and in a group of age-matched healthy controls (104 women. Serum specimens were purified and the low-molecular-weight proteome fraction was examined using MALDI-ToF mass spectrometry after removal of albumin and other high-molecular-weight serum proteins. Protein ions registered in a mass range between 2,000 and 10,000 Da were analyzed using a new bioinformatic tool created in our group, which included modeling spectra as a sum of Gaussian bell-shaped curves. Results We have identified features of serum proteome patterns that were significantly different between blood samples of healthy individuals and early stage breast cancer patients. The classifier built of three spectral components that differentiated controls and cancer patients had 83% sensitivity and 85% specificity. Spectral components (i.e., protein ions that were the most frequent in such classifiers had approximate m/z values of 2303, 2866 and 3579 Da (a biomarker built from these three components showed 88% sensitivity and 78% specificity. Of note, we did not find a significant correlation between features of serum proteome patterns and established prognostic or predictive factors like tumor size, nodal involvement, histopathological grade, estrogen and progesterone receptor expression. In addition, we observed a significantly (p = 0

  1. Web-based tools for quality assurance and radiation protection in diagnostic radiology

    International Nuclear Information System (INIS)

    Practical and philosophical aspects of radiation protection in diagnostic radiology have changed very little over the past 50 y even though patient doses have continued to rise significantly in this period. This rise has been driven by technological developments, such as multi-slice computed tomography, that have been able to improve diagnostic accuracy but not necessarily provide the same level of risk-benefit to all patients or groups of patients given the dose levels involved. Can practical radiation protection strategies hope to keep abreast of these ongoing developments? A project was started in 1992 in Liverpool that aimed to develop IT driven quality assurance (QA)/radiation protection software tools based upon a modular quality assurance dose data system. One of the modules involved the assessment of the patient entrance surface air kerma (ESAK) for an X-ray examination that was based upon the use of calibrated X-ray tube exposure factors to calculate ESAK as well as collecting appropriate patient details (age, sex, weight, thickness etc). The package also contained modules for logging all necessary equipment performance QA data. This paper will outline the experience gained with this system through its transition from a local application on a stand alone PC within the department to the current web-based approach. Advantages of a web-based approach to delivering such an application as well as centrally storing data originating on many hospital sites will be discussed together with the scientific support processes that can be developed with such a system. This will include local, national and international considerations. The advantages of importing radiographic examination details directly from other electronic storage systems such as a hospital's radiology information system will be presented together with practical outcomes already achieved. This will include the application of statistical techniques to the very large data sets generated. The development

  2. Climate Model Diagnostic and Evaluation: With a Focus on Satellite Observations

    Science.gov (United States)

    Waliser, Duane

    2011-01-01

    Each year, we host a summer school that brings together the next generation of climate scientists - about 30 graduate students and postdocs from around the world - to engage with premier climate scientists from the Jet Propulsion Laboratory and elsewhere. Our yearly summer school focuses on topics on the leading edge of climate science research. Our inaugural summer school, held in 2011, was on the topic of "Using Satellite Observations to Advance Climate Models," and enabled students to explore how satellite observations can be used to evaluate and improve climate models. Speakers included climate experts from both NASA and the National Oceanic and Atmospheric Administration (NOAA), who provided updates on climate model diagnostics and evaluation and remote sensing of the planet. Details of the next summer school will be posted here in due course.

  3. The Signal Data Explorer: A high performance Grid based signal search tool for use in distributed diagnostic applications

    OpenAIRE

    Fletcher, Martyn; Jackson, Tom; Jessop, Mark; Liang, Bojian; Austin, Jim

    2006-01-01

    We describe a high performance Grid based signal search tool for distributed diagnostic applications developed in conjunction with Rolls-Royce plc for civil aero engine condition monitoring applications. With the introduction of advanced monitoring technology into engineering systems, healthcare, etc., the associated diagnostic processes are increasingly required to handle and consider vast amounts of data. An exemplar of such a diagnosis process was developed during the DAME project, which b...

  4. A knowledge based on-line diagnostic system for the fast breeder reactor KNKII

    International Nuclear Information System (INIS)

    In the nuclear research center at Karlsruhe, a diagnostic expert system is developed to supervise a fast breeder process (KNKII). The problem is to detect critical phases in the beginning state before fault propagation. The expert system itself is integrated in a computer network (realized by a local area network), where different computers are involved as special detection systems (for example acoustic noise, temperature noise, covergas monitoring and so on), which produce partial diagnoses, based on intelligent signal processing techniques like pattern recognition. Additional to the detection systems a process computer is integrated as well as a test computer, which simulates hypothetical and real fault data. On the logical top level the expert system manages the partial diagnoses of the detection systems with the operating data of the process computer and to produce a final diagnosis including the explanation part for operator support. The knowledge base is developed by typical Artificial Intelligence tools. Both fact based and rule based knowledge representations are stored in form of flavors and predications. The inference engine operates on a rule based approach. Specific detail knowledge, based on experience about any years, is available to influence the decision process by increasing or decreasing of the generated hypotheses. In a meta knowledge base, a rule master triggers the special domain experts and contributes the tasks to the specific rule complexes. Such a system management guarantees a problem solving strategy, which operates event triggered and situation specific in a local inference domain. (author). 3 refs, 6 figs, 2 tabs

  5. A diagnostic model incorporating P50 sensory gating and neuropsychological tests for schizophrenia.

    Directory of Open Access Journals (Sweden)

    Jia-Chi Shan

    Full Text Available OBJECTIVES: Endophenotypes in schizophrenia research is a contemporary approach to studying this heterogeneous mental illness, and several candidate neurophysiological markers (e.g. P50 sensory gating and neuropsychological tests (e.g. Continuous Performance Test (CPT and Wisconsin Card Sorting Test (WCST have been proposed. However, the clinical utility of a single marker appears to be limited. In the present study, we aimed to construct a diagnostic model incorporating P50 sensory gating with other neuropsychological tests in order to improve the clinical utility. METHODS: We recruited clinically stable outpatients meeting DSM-IV criteria of schizophrenia and age- and gender-matched healthy controls. Participants underwent P50 sensory gating experimental sessions and batteries of neuropsychological tests, including CPT, WCST and Wechsler Adult Intelligence Scale Third Edition (WAIS-III. RESULTS: A total of 106 schizophrenia patients and 74 healthy controls were enrolled. Compared with healthy controls, the patient group had significantly a larger S2 amplitude, and thus poorer P50 gating ratio (gating ratio = S2/S1. In addition, schizophrenia patients had a poorer performance on neuropsychological tests. We then developed a diagnostic model by using multivariable logistic regression analysis to differentiate patients from healthy controls. The final model included the following covariates: abnormal P50 gating (defined as P50 gating ratio >0.4, three subscales derived from the WAIS-III (Arithmetic, Block Design, and Performance IQ, sensitivity index from CPT and smoking status. This model had an adequate accuracy (concordant percentage = 90.4%; c-statistic = 0.904; Hosmer-Lemeshow Goodness-of-Fit Test, p = 0.64>0.05. CONCLUSION: To the best of our knowledge, this is the largest study to date using P50 sensory gating in subjects of Chinese ethnicity and the first to use P50 sensory gating along with other neuropsychological tests

  6. Diagnostic performance of line-immunoassay based algorithms for incident HIV-1 infection

    Directory of Open Access Journals (Sweden)

    Schüpbach Jörg

    2012-04-01

    Full Text Available Abstract Background Serologic testing algorithms for recent HIV seroconversion (STARHS provide important information for HIV surveillance. We have previously demonstrated that a patient's antibody reaction pattern in a confirmatory line immunoassay (INNO-LIA™ HIV I/II Score provides information on the duration of infection, which is unaffected by clinical, immunological and viral variables. In this report we have set out to determine the diagnostic performance of Inno-Lia algorithms for identifying incident infections in patients with known duration of infection and evaluated the algorithms in annual cohorts of HIV notifications. Methods Diagnostic sensitivity was determined in 527 treatment-naive patients infected for up to 12 months. Specificity was determined in 740 patients infected for longer than 12 months. Plasma was tested by Inno-Lia and classified as either incident ( Results The 10 best algorithms had a mean raw sensitivity of 59.4% and a mean specificity of 95.1%. Adjustment for overrepresentation of patients in the first quarter year of infection further reduced the sensitivity. In the preferred model, the mean adjusted sensitivity was 37.4%. Application of the 10 best algorithms to four annual cohorts of HIV-1 notifications totalling 2'595 patients yielded a mean IIR of 0.35 in 2005/6 (baseline and of 0.45, 0.42 and 0.35 in 2008, 2009 and 2010, respectively. The increase between baseline and 2008 and the ensuing decreases were highly significant. Other adjustment models yielded different absolute IIR, although the relative changes between the cohorts were identical for all models. Conclusions The method can be used for comparing IIR in annual cohorts of HIV notifications. The use of several different algorithms in combination, each with its own sensitivity and specificity to detect incident infection, is advisable as this reduces the impact of individual imperfections stemming primarily from relatively low sensitivities and

  7. Activity based costing of diagnostic procedures at a nuclear medicine center of a tertiary care hospital

    International Nuclear Information System (INIS)

    Escalating health care expenses pose a new challenge to the health care environment of becoming more cost-effective. There is an urgent need for more accurate data on the costs of health care procedures. Demographic changes, changing morbidity profile, and the rising impact of noncommunicable diseases are emphasizing the role of nuclear medicine (NM) in the future health care environment. However, the impact of emerging disease load and stagnant resource availability needs to be balanced by a strategic drive towards optimal utilization of available healthcare resources. The aim was to ascertain the cost of diagnostic procedures conducted at the NM Department of a tertiary health care facility by employing activity based costing (ABC) method. A descriptive cross-sectional study was carried out over a period of 1 year. ABC methodology was utilized for ascertaining unit cost of different diagnostic procedures and such costs were compared with prevalent market rates for estimating cost effectiveness of the department being studied. The cost per unit procedure for various procedures varied from Rs. 869 (USD 14.48) for a thyroid scan to Rs. 11230 (USD 187.16) for a meta-iodo-benzyl-guanidine (MIBG) scan, the most cost-effective investigations being the stress thallium, technetium-99 m myocardial perfusion imaging (MPI) and MIBG scan. The costs obtained from this study were observed to be competitive when compared to prevalent market rates. ABC methodology provides precise costing inputs and should be used for all future costing studies in NM Departments

  8. Laser based beam diagnostic for the RAL Front End Test Stand (FETS)

    International Nuclear Information System (INIS)

    For the diagnostic of high power particle beams, non-destructive measurement devices provide minimum influence on the beam and avoid various problems in connection with the high power density on surfaces. An H- ion beam offers the opportunity of non destructive beam diagnostics based on the effect of photo detachment. By the interaction of light with H- ions, the additional electron can be detached and a small number of neutrals will be produced. An additional magnetic dipole field can then be used to separate the detached electrons and neutrals from the ions. Using an integral detector the spatial distribution of the beam ion density can be derived, while the use of a spatial resolving detector enables to determine the phase space distribution. To investigate the measurement principle of the latter, a test stand was set up at the IAP in Frankfurt. This system will now be adopted to the requirements of the Front End Test Stand at CCLRC/ RAL. The aim of this FETS is to demonstrate a chopped H- beam of 60mA at 3MeV and 50pps with sufficiently high beam quality. The paper will present a detailed description of the proposed set up at RAL and discuss several results of simulations and experimental data gained in Frankfurt

  9. Spectrometer Based on a VLS Grating for Diagnostics of a Vacuum-Ultraviolet Free Electron Laser

    International Nuclear Information System (INIS)

    Photon beam diagnostics for vacuum-ultraviolet free electron lasers (VUV FEL) are critical to monitoring and understanding their performance characteristics. Due to the shot-to-shot fluctuations inherent in FELs based on the self amplified spontaneous emission (SASE) process, it is mandatory to use pulse-resolved diagnostics. We have designed a spectrograph based on a variable-line-spacing (VLS) plane grating and a phosphor/CCD to monitor single shot spectra of the free electron laser at DESY. The basic concept is to allow most of the beam to be reflected towards an experimental station while the first order light is dispersed and focused by the VLS grating onto the CCD. The spectrograph will cover the wavelength range 6.4-60 nm with the CCD accepting a bandwidth of ∼10%. The grazing angle of incidence on the grating is 2 deg., the central line density is 1200 l/mm, and the distance grating-CCD is approximately 2 m. The linear variation of the grating line spacing combined with positioning the detector at the focal curve, allows zeroing the defocus in the full spectrograph wavelength range. The correction of higher order grating aberrations yields a theoretical resolving power greater than 20000 over the full length of the 20 mm CCD when the CCD is positioned tangent to the focal plane. Based on power considerations, a shallow blazed grating is the preferred profile. Efficiency calculations over the spectrograph range show that with a carbon coating the absolute efficiency for zeroth order is higher than 0.85 and the first order efficiency varies between 0.5% and 8%

  10. Dose assessment for medical exposure from diagnostic X-rays using a human voxel model

    International Nuclear Information System (INIS)

    Korean voxel model, KORMAN, segmented from whole-body MR data of an adult male, was used to calculate organ equivalent doses and effective doses due to diagnostic X-ray examinations. Calculated doses were normalized to entrance air kerma and compared with those derived using a stylized mathematical model, MIRD5. General purposed Monte Carlo code, MCNPX 2.3 was used for simulation of X-ray procedure. Korean voxel model picked up 0.048 Sv/Gy of effective dose per unit air kerma from a single chest PA examination, and 0.277 Sv/Gy from abdomen AP examination. These calculated results are higher than those MIRD5. The difference of effective doses between Korean voxel model and MIRD5 was within 32%, which were caused by significant discrepancies of organ equivalent doses between the two models. As MIRD5 is representing reference man, whereas KORMAN is segmented from specific individual MR data, it is recognized that variation among individuals could be significant for dose assessment in X-ray examination. Substantial differences in calculated doses between voxel and mathematical models suggested that existing mathematical models should be revised. (author)

  11. On modelling the kinestatic charge detector for digital radiographic diagnostic and portal imaging.

    Science.gov (United States)

    Qi, G; Goloubev, M Y; DiBianca, F A; Samant, S

    2002-01-01

    The kinestatic charge detection (KCD) principle has been a digital radiography technique for more than a decade. The advances of the KCD technique have gone from diagnostic imaging to portal imaging. However, little work has been done on understanding the selection of key KCD parameters and relationships between them. In the present study, an engineering model was established that could be used to optimize the placements of key parameters in terms of KCD system mechanical design. In the proposed KCD engineering model, the basic energy conservation law was applied to the process of ion transmission. It allows for the computation of the KCD design parameters such as the optimum grid placement, high voltage board tilt angle and grid wire space, as well as to provide recommendations on high voltage board and electric potentials and their ratio. PMID:12487709

  12. Applying the Burke–Litwin model as a diagnostic framework for assessing organisational effectiveness

    Directory of Open Access Journals (Sweden)

    Nico Martins

    2009-04-01

    Full Text Available This exploratory study investigated the utility of the Burke–Litwin model as a diagnostic framework for assessing the factors affecting organisational effectiveness. The research setting consisted of an international company, with a population comprising representatives of more than 17 different nationalities. The purposive sampling method was used to  involve employee participants (N = 147  in  focus groups  and  executive managers  (N =  11  in semi- structured probing  interviews. The  factors identified related  to both  the  transformational and  transactional dimensions of  the Burke–Litwin model. The f ndings add to the existing literature on factors causing organisational effectiveness and ineffectiveness in cross-cultural organisational contexts.

  13. Model-Based Real Time Assessment of Capability Left for Spacecraft Under Failure Mode Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed project is aimed at developing a model based diagnostics system for spacecraft that will allow real time assessment of its state, while it is impacted...

  14. The development of a hassle-based diagnostic scale for predicting burnout in call centres

    Directory of Open Access Journals (Sweden)

    Willie A. Visser

    2009-04-01

    Full Text Available The aim of this study was to develop a brief daily hassle diagnostic questionnaire that could be used to identify daily hassles for customer service representatives within a call centre environment, and to investigate the relationship between daily hassles and burnout. A crosssectional survey was used with an accidental sample (N = 394 taken from a service and sales call centre. An exploratory factor analysis of the data resulted in a six-factor model of daily hassles consisting of daily demands, continuous change, co-worker hassles, demotivating work environment, transportation hassles and personal concerns. The internal consistency of one factor, namely personal concerns, was low. Exhaustion was best predicted by four categories of daily hassles, namely daily demands, continuous change, a demotivating work environment, and transportation hassles.

  15. Model-Based Reasoning

    Science.gov (United States)

    Ifenthaler, Dirk; Seel, Norbert M.

    2013-01-01

    In this paper, there will be a particular focus on mental models and their application to inductive reasoning within the realm of instruction. A basic assumption of this study is the observation that the construction of mental models and related reasoning is a slowly developing capability of cognitive systems that emerges effectively with proper…

  16. Model-based software design

    Science.gov (United States)

    Iscoe, Neil; Liu, Zheng-Yang; Feng, Guohui; Yenne, Britt; Vansickle, Larry; Ballantyne, Michael

    1992-01-01

    Domain-specific knowledge is required to create specifications, generate code, and understand existing systems. Our approach to automating software design is based on instantiating an application domain model with industry-specific knowledge and then using that model to achieve the operational goals of specification elicitation and verification, reverse engineering, and code generation. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model.

  17. Microprocessor-based control and diagnostic system for valve motor operators

    International Nuclear Information System (INIS)

    As part of a research and development effort initiated by the Electric Power Research Institute (EPRI), a newly developed microprocessor-based control and diagnostics system has been designed to alleviate many of the historical problems related to the performance of conventional valve motor operators (VMOs). The principal advantages of the new system are that: (1) it eliminates dependency on conventional electrochemical torque and limit switches. (2) It provides easy, accurate setpoint adjustments for position control, stem load control, and motor overload protection. (3) It provides an easily interpreted visual display of important system parameters, and informs the operator of changing operational characteristics. The last feature is considered to be of particular significance because it allows both instantaneous evaluation of the condition of a valve motor operator and diagnosis of abnormal VMO performance

  18. Aptamer-based radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of epithelial tumors

    Energy Technology Data Exchange (ETDEWEB)

    Missailidis, Sotiris [The Open University, Milton Keynes (United Kingdom). Dept. of Chemistry and Analytical Sciences]. E-mail: s.missailidis@open.ac.uk; Perkins, Alan [University of Nottingham (United Kingdom). Dept. of Medical Physics; Santos-Filho, Sebastiao David; Fonseca, Adenilson de Souza da; Bernardo-Filho, Mario [Universidade do Estado do Rio de Janeiro (UERJ), RJ (Brazil). Inst. de Biologia Roberto Alcantara Gomes. Dept. de Biofisica e Biometria

    2008-12-15

    In the continuous search for earlier diagnosis and improved therapeutic modalities against cancer, based on our constantly increasing knowledge of cancer biology, aptamers hold the promise to expand on current antibody success, but overcoming some of the problems faced with antibodies as therapeutic or delivery agents in cancer. However, as the first aptamer reached the market as an inhibitor against angiogenesis for the treatment of macular degeneration, aptamers have found only limited applications or interest in oncology, and even less as radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of tumours. Yet, the chemistry for the labelling of aptamers and the options to alter their pharmacokinetic properties, to make them suitable for use as radiopharmaceuticals is now available and recent advances in their development can demonstrate that these molecules would make them ideal delivery vehicles for the development of targeted radiopharmaceuticals that could deliver their radiation load with accuracy to the tumour site, offering improved therapeutic properties and reduced side effects. (author)

  19. Tomographic capabilities of the new GEM based SXR diagnostic of WEST

    Science.gov (United States)

    Jardin, A.; Mazon, D.; O'Mullane, M.; Mlynar, J.; Loffelmann, V.; Imrisek, M.; Chernyshova, M.; Czarski, T.; Kasprowicz, G.; Wojenski, A.; Bourdelle, C.; Malard, P.

    2016-07-01

    The tokamak WEST (Tungsten Environment in Steady-State Tokamak) will start operating by the end of 2016 as a test bed for the ITER divertor components in long pulse operation. In this context, radiative cooling of heavy impurities like tungsten (W) in the Soft X-ray (SXR) range [0.1 keV; 20 keV] is a critical issue for the plasma core performances. Thus reliable tools are required to monitor the local impurity density and avoid W accumulation. The WEST SXR diagnostic will be equipped with two new GEM (Gas Electron Multiplier) based poloidal cameras allowing to perform 2D tomographic reconstructions in tunable energy bands. In this paper tomographic capabilities of the Minimum Fisher Information (MFI) algorithm developed for Tore Supra and upgraded for WEST are investigated, in particular through a set of emissivity phantoms and the standard WEST scenario including reconstruction errors, influence of noise as well as computational time.

  20. Evaluation of User Performance in Simulation-Based Diagnostic Cerebral Angiography Training.

    Science.gov (United States)

    Zaika, Oleksiy; Nguyen, Ngan; Boulton, Mel; Eagleson, Roy; de Ribaupierre, Sandrine

    2016-01-01

    Simulation of anatomically complex procedures, such as angiography, is becoming more practical, however, computer-based modules require extensive research to assess their effectiveness. We organized two training schemas - alternating cases and consistent cases - and hypothesized that the alternating practice cases would be beneficial to test performance. Eight residents (4 radiology/4 neurosurgery) and 8 anatomy graduate students were trained on the SimbionixTM simulator in order to assess skill acquisition in diagnostic cerebral angiography over 8 sessions. We found that participants improve on total procedure time and total fluoroscopy time (p<0.05), but not on contrast injected or roadmaps created. There were no significant differences between alternating and consistent training types. Additional work needs to be done with higher sample numbers and visuospatial scores as criteria. PMID:27046624

  1. Luminescence-Based Diagnostics of Thermal Barrier Coating Health and Performance

    Science.gov (United States)

    Eldridge, Jeffrey I.

    2013-01-01

    Thermal barrier coatings (TBCs) are typically composed of translucent ceramic oxides that provide thermal protection for metallic components exposed to high-temperature environments in both air- and land-based turbine engines. For advanced turbine engines designed for higher temperature operation, a diagnostic capability for the health and performance of TBCs will be essential to indicate when a mitigating action needs to be taken before premature TBC failure threatens engine performance or safety. In particular, it is shown that rare-earth-doped luminescent sublayers can be integrated into the TBC structure to produce luminescence emission that can be monitored to assess TBC erosion and delamination progression, and to map surface and subsurface temperatures as a measure of TBC performance. The design and implementation of these TBCs with integrated luminescent sublayers are presented.

  2. Limitations of Label-Free Sensors in Serum Based Molecular Diagnostics

    CERN Document Server

    Varma, Manoj M

    2015-01-01

    Immunoassay formats applicable for clinical or point-of-care diagnostics fall into two broad classes. One which uses labeled secondary antibodies for signal transduction and the other which does not require the use of any labels. Comparison of the limits of detection (LoD) reported by these two sensing approaches over a wide range of detection techniques and target molecules in serum revealed that labeled techniques achieve 2-3 orders of magnitude better LoDs. Further, a vast majority of commercial tests and recent examples of technology translations are based on labeled assay formats. In light of this data, it is argued that extension of traditional labeled approaches and enhancing their functionality may have better clinical impact than the development of newer label-free techniques.

  3. Aptamer-based radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of epithelial tumors

    International Nuclear Information System (INIS)

    In the continuous search for earlier diagnosis and improved therapeutic modalities against cancer, based on our constantly increasing knowledge of cancer biology, aptamers hold the promise to expand on current antibody success, but overcoming some of the problems faced with antibodies as therapeutic or delivery agents in cancer. However, as the first aptamer reached the market as an inhibitor against angiogenesis for the treatment of macular degeneration, aptamers have found only limited applications or interest in oncology, and even less as radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of tumours. Yet, the chemistry for the labelling of aptamers and the options to alter their pharmacokinetic properties, to make them suitable for use as radiopharmaceuticals is now available and recent advances in their development can demonstrate that these molecules would make them ideal delivery vehicles for the development of targeted radiopharmaceuticals that could deliver their radiation load with accuracy to the tumour site, offering improved therapeutic properties and reduced side effects. (author)

  4. [Express diagnostics of bovine leucosis by immune sensor based on surface plasmon resonance].

    Science.gov (United States)

    Pyrohova, L V; Starodub, M F; Artiukh, V P; Nahaieva, L I; Dobrosol, H I

    2002-01-01

    An immune sensor based on the surface plasmon resonance (SPR) was developed for express diagnostics of bovine leucosis. The sensor was used for detection of the level of antibodies against bovine leukaemia virus (BLV) in the blood serum. The industrially manufactured BLV antigen for screening test in the agar gel immunodiffusion (AGID) required the additional purification in order to be used in immune sensor analysis. It was shown that immune sensor analysis was more sensitive, rapid and simple in comparison with the traditional AGID test. It was stated that the developed immune sensor was capable to be used for performance of bovine leucosis screening at the farms and the minimal dilution of the serum should be 1:500. PMID:12916242

  5. Model-based Software Engineering

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2010-01-01

    The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...

  6. Principles of models based engineering

    Energy Technology Data Exchange (ETDEWEB)

    Dolin, R.M.; Hefele, J.

    1996-11-01

    This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.

  7. From Present Fusion Devices to DEMO: a Changing Role between Diagnostics and Modeling

    NARCIS (Netherlands)

    Donne, A. J. H.

    2013-01-01

    On present-day devices much effort is devoted to develop state-of-the-art diagnostics with a continuous drive towards higher accuracy, better spatial and temporal resolution and more diagnostic channels. Diagnostic innovations often lead to better physics insight and they are often a driver for impr

  8. Knowledge-based process control and diagnostics for orbital cryogen transfer

    Science.gov (United States)

    Raymond, Eric A.

    1989-01-01

    AFDex is a rule based system designed to provide intelligent process control, diagnosis, and error recovery for a Shuttle based cryogenic experiment, SHOOT (Superfluid Helium On-Orbit Transfer). This paper describes the AFDex system in the context of traditional associative, model-based, and qualitative systems and discusses the implications of this first expert system in space.

  9. Model Construct Based Enterprise Model Architecture and Its Modeling Approach

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    In order to support enterprise integration, a kind of model construct based enterprise model architecture and its modeling approach are studied in this paper. First, the structural makeup and internal relationships of enterprise model architecture are discussed. Then, the concept of reusable model construct (MC) which belongs to the control view and can help to derive other views is proposed. The modeling approach based on model construct consists of three steps, reference model architecture synthesis, enterprise model customization, system design and implementation. According to MC based modeling approach a case study with the background of one-kind-product machinery manufacturing enterprises is illustrated. It is shown that proposal model construct based enterprise model architecture and modeling approach are practical and efficient.

  10. Indication-based diagnostic reference levels for adult CT-examinations in Finland

    International Nuclear Information System (INIS)

    A diagnostic reference level (DRL) is a predefined dose level, which should not be exceeded in an examination that is conducted appropriately on an average-sized patient. Since dose from only one examination should not be compared with a DRL, the average dose from a good sample of at least 10 average-sized patients should be compared. The previous DRLs for computed tomography (CT)-examinations for adults in Finland were issued in 2007 and only covered examinations conducted on a particular body region. Because the image quality requirements, and thus the dose needed, vary between different indications, there has been a call for indication-based DRLs for CT. The new indication-based DRLs for CT came into effect on June 2013. They are based on a dose survey performed in 2012. Doses were collected from examinations conducted on a particular body region, based on some indication and from some special examination types. The DRLs were set according to the third quartile approach. On average, the DRLs for a particular body region dropped ∼20 % from the previous DRLs. (authors)

  11. The use of deep knowledge qualitative models as a basis for real-time diagnostic support systems for power plant control room operators

    International Nuclear Information System (INIS)

    There is a need for diagnostic support systems in power stations to reduce the amount of information presented to the operator in order to prevent information overload and mindset during events in which a large number of plant measurements are changing rapidly. Existing alarm analysis systems have proved to be non-robust, inflexible and incomplete due principally to their event-based nature. Other approaches based on quantitative models are vulnerable to inaccurate measurements and uncertainties in system parameters, and would be both difficult and costly to apply to a whole plant. The recent commercial development of expert systems and artificial intelligence technology has opened up the possibility of new operator support systems with greater flexibility, robustness, improved man-machine interaction including dialogue and explanation of reasoning, and better transferability between similar applications. Most diagnostic expert systems already developed have been based on simple relationships between specific faults and specific symptoms. This type of knowledge is termed shallow to distinguish it from deep knowledge describing the behaviour of the plant. This project is concerned with the development of a diagnostic expert system based on a deep knowledge qualitative model. The system described is not intended to be an operational support system, merely to establish appropriate techniques to be used within such a system

  12. An interactive model for the assessment of the economic costs and benefits of different rapid diagnostic tests for malaria

    Directory of Open Access Journals (Sweden)

    Whitty Christopher JM

    2008-01-01

    Full Text Available Abstract Background Rapid diagnostic tests (RDTs for malaria are increasingly being considered for routine use in Africa. However, many RDTs are available and selecting the ideal test for a particular setting is challenging. The appropriateness of RDT choice depends in part on patient population and epidemiological setting, and on decision makers' priorities. The model presented (available online can be used by decision makers to evaluate alternative RDTs and assess the circumstances under which their use is justified on economic grounds. Methods An interactive model based on a decision-tree structure and a cost-benefit framework was designed to compare different diagnostic strategies. Variables included in the model can be modified by users, including RDT and treatment costs, test accuracies (sensitivity and specificity, probabilities for developing severe illness, case-fatality rates, and clinician response to negative test results. To illustrate how the model can be used, a comparison is made of presumptive treatment with two available RDTs, one detecting histidine-rich protein-2 (HRP2 and one detecting Plasmodium lactate dehydrogenase (pLDH. Data inputs were obtained from a study comparing the RDTs at seven sites in Uganda. Results Applying the model in the illustrative Ugandan context demonstrates that if only direct expenditures are considered, the pLDH test is the preferred option for adult patients except in high transmission settings, while young children are best treated presumptively in all settings. When health outcomes are considered, the HRP2 test gains an advantage in almost all settings and for all age groups. Introducing possible adverse consequences of using an antimalarial into the analysis, such as adverse drug reactions, or the development of resistance, considerably strengthens the case for using RDTs. When the model is adjusted to account for less than complete adherence to test results, the efficiency of using RDTs drops

  13. An XML-based Schema-less Approach to Managing Diagnostic Data in Heterogeneous Formats

    Energy Technology Data Exchange (ETDEWEB)

    Naito, O. [Japan Atomic Energy Agency, Ibaraki (Japan)

    2009-07-01

    Managing diagnostic data in heterogeneous formats is always a nuisance, especially when a new diagnostic technique requires a new data structure that does not fit in the existing data format. Ideally, it is best to have an all-purpose schema that can specify any data structures. But devising such a schema is a difficult task and the resultant data management system tends to be large and complicated. As a complementary approach, we can think of a system that has no specific schema but requires each of the data to describe itself without assuming any prior information. In this paper, a very primitive implementation of such a system based on extensible Markup Language (XML) is examined. The actual implementation is no more than an addition of a tiny XML meta-data file that describes the detailed format of the associated diagnostic data file. There are many ways to write and read such meta-data files. For example, if the data are in a standard format that is foreign to the existing system, just specify the name of the format and what interface to use for reading the data. If the data are in a non-standard arbitrary format, write what is written and how into the meta-data file at every occurrence of data output. And as a last resort, if the format of the data is too complicated, a code to read the data can be stored in the meta-data file. Of course, this schema-less approach has some drawbacks, two of which are the doubling of the number of files to be managed and the low performance of data handling, though the former can be a merit, when it is necessary to update the meta-data leaving the body data intact. The important point is that the necessary information to read the data is decoupled from data itself. The merits and demerits of this approach are discussed. This document is composed of an abstract followed by the presentation slides. (author)

  14. An informatics model for guiding assembly of telemicrobiology workstations for malaria collaborative diagnostics using commodity products and open-source software

    Directory of Open Access Journals (Sweden)

    Crandall Ian

    2009-07-01

    Full Text Available Abstract Background Deficits in clinical microbiology infrastructure exacerbate global infectious disease burdens. This paper examines how commodity computation, communication, and measurement products combined with open-source analysis and communication applications can be incorporated into laboratory medicine microbiology protocols. Those commodity components are all now sourceable globally. An informatics model is presented for guiding the use of low-cost commodity components and free software in the assembly of clinically useful and usable telemicrobiology workstations. Methods The model incorporates two general principles: 1 collaborative diagnostics, where free and open communication and networking applications are used to link distributed collaborators for reciprocal assistance in organizing and interpreting digital diagnostic data; and 2 commodity engineering, which leverages globally available consumer electronics and open-source informatics applications, to build generic open systems that measure needed information in ways substantially equivalent to more complex proprietary systems. Routine microscopic examination of Giemsa and fluorescently stained blood smears for diagnosing malaria is used as an example to validate the model. Results The model is used as a constraint-based guide for the design, assembly, and testing of a functioning, open, and commoditized telemicroscopy system that supports distributed acquisition, exploration, analysis, interpretation, and reporting of digital microscopy images of stained malarial blood smears while also supporting remote diagnostic tracking, quality assessment and diagnostic process development. Conclusion The open telemicroscopy workstation design and use-process described here can address clinical microbiology infrastructure deficits in an economically sound and sustainable manner. It can boost capacity to deal with comprehensive measurement of disease and care outcomes in individuals and

  15. Deformability based sorting of red blood cells improves diagnostic sensitivity for malaria caused by Plasmodium falciparum.

    Science.gov (United States)

    Guo, Quan; Duffy, Simon P; Matthews, Kerryn; Deng, Xiaoyan; Santoso, Aline T; Islamzada, Emel; Ma, Hongshen

    2016-02-21

    The loss of red blood cell (RBC) deformability is part of the pathology of many diseases. In malaria caused by Plasmodium falciparum infection, metabolism of hemoglobin by the parasite results in progressive reduction in RBC deformability that is directly correlated with the growth and development of the parasite. The ability to sort RBCs based on deformability therefore provides a means to isolate pathological cells and to study biochemical events associated with disease progression. Existing methods have not been able to sort RBCs based on deformability or to effectively enrich for P. falciparum infected RBCs at clinically relevant concentrations. Here, we develop a method to sort RBCs based on deformability and demonstrate the ability to enrich the concentration of ring-stage P. falciparum infected RBCs (Pf-iRBCs) by >100× from clinically relevant parasitemia (asymmetrical constrictions using oscillatory flow. This mechanism provides dramatically improved selectivity over previous biophysical methods by preventing the accumulation of cells in the filter microstructure to ensure that consistent filtration forces are applied to each cell. We show that our approach dramatically improves the sensitivity of malaria diagnosis performed using both microscopy and rapid diagnostic test by converting samples with difficult-to-detect parasitemia (0.1%). PMID:26768227

  16. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  17. Development of recombinant nucleoprotein-based diagnostic systems for Lassa fever.

    Science.gov (United States)

    Saijo, Masayuki; Georges-Courbot, Marie-Claude; Marianneau, Philippe; Romanowski, Victor; Fukushi, Shuetsu; Mizutani, Tetsuya; Georges, Alain-Jean; Kurata, Takeshi; Kurane, Ichiro; Morikawa, Shigeru

    2007-09-01

    Diagnostic systems for Lassa fever (LF), a viral hemorrhagic fever caused by Lassa virus (LASV), such as enzyme immunoassays for the detection of LASV antibodies and LASV antigens, were developed using the recombinant nucleoprotein (rNP) of LASV (LASV-rNP). The LASV-rNP was expressed in a recombinant baculovirus system. LASV-rNP was used as an antigen in the detection of LASV-antibodies and as an immunogen for the production of monoclonal antibodies. The LASV-rNP was also expressed in HeLa cells by transfection with the expression vector encoding cDNA of the LASV-NP gene. An immunoglobulin G enzyme-linked immunosorbent assay (ELISA) using LASV-rNP and an indirect immunofluorescence assay using LASV-rNP-expressing HeLa cells were confirmed to have high sensitivity and specificity in the detection of LASV-antibodies. A novel monoclonal antibody to LASV-rNP, monoclonal antibody 4A5, was established. A sandwich antigen capture (Ag-capture) ELISA using the monoclonal antibody and an anti-LASV-rNP rabbit serum as capture and detection antibodies, respectively, was then developed. Authentic LASV nucleoprotein in serum samples collected from hamsters experimentally infected with LASV was detected by the Ag-capture ELISA. The Ag-capture ELISA specifically detected LASV-rNP but not the rNPs of lymphocytic choriomeningitis virus or Junin virus. The sensitivity of the Ag-capture ELISA in detecting LASV antigens was comparable to that of reverse transcription-PCR in detecting LASV RNA. These LASV rNP-based diagnostics were confirmed to be useful in the diagnosis of LF even in institutes without a high containment laboratory, since the antigens can be prepared without manipulation of the infectious viruses. PMID:17634509

  18. Development of Recombinant Nucleoprotein-Based Diagnostic Systems for Lassa Fever▿

    Science.gov (United States)

    Saijo, Masayuki; Georges-Courbot, Marie-Claude; Marianneau, Philippe; Romanowski, Victor; Fukushi, Shuetsu; Mizutani, Tetsuya; Georges, Alain-Jean; Kurata, Takeshi; Kurane, Ichiro; Morikawa, Shigeru

    2007-01-01

    Diagnostic systems for Lassa fever (LF), a viral hemorrhagic fever caused by Lassa virus (LASV), such as enzyme immunoassays for the detection of LASV antibodies and LASV antigens, were developed using the recombinant nucleoprotein (rNP) of LASV (LASV-rNP). The LASV-rNP was expressed in a recombinant baculovirus system. LASV-rNP was used as an antigen in the detection of LASV-antibodies and as an immunogen for the production of monoclonal antibodies. The LASV-rNP was also expressed in HeLa cells by transfection with the expression vector encoding cDNA of the LASV-NP gene. An immunoglobulin G enzyme-linked immunosorbent assay (ELISA) using LASV-rNP and an indirect immunofluorescence assay using LASV-rNP-expressing HeLa cells were confirmed to have high sensitivity and specificity in the detection of LASV-antibodies. A novel monoclonal antibody to LASV-rNP, monoclonal antibody 4A5, was established. A sandwich antigen capture (Ag-capture) ELISA using the monoclonal antibody and an anti-LASV-rNP rabbit serum as capture and detection antibodies, respectively, was then developed. Authentic LASV nucleoprotein in serum samples collected from hamsters experimentally infected with LASV was detected by the Ag-capture ELISA. The Ag-capture ELISA specifically detected LASV-rNP but not the rNPs of lymphocytic choriomeningitis virus or Junin virus. The sensitivity of the Ag-capture ELISA in detecting LASV antigens was comparable to that of reverse transcription-PCR in detecting LASV RNA. These LASV rNP-based diagnostics were confirmed to be useful in the diagnosis of LF even in institutes without a high containment laboratory, since the antigens can be prepared without manipulation of the infectious viruses. PMID:17634509

  19. Diagnostic test

    International Nuclear Information System (INIS)

    A diagnostic test is provided based on competitive binding in which a partition coefficient is established for the substance whose concentration is to be determined and for the radioactive labeled form of the substance between liquid and solid phases. 10 claims

  20. Experimental guinea pig model of dermatophytosis: a simple and useful tool for the evaluation of new diagnostics and antifungals

    DEFF Research Database (Denmark)

    Saunte, D.M.; Hasselby, J.P.; Brillowska-Dabrowska, A.;

    2008-01-01

    The aim of this study was to establish a simple guinea pig model for the purpose of evaluating diagnostic principles and treatment modalities for dermatophytic infections. The following variables were evaluated; pre-treatment of the skin by shaving versus tape stripping, Microsporum canis or Tric....... In conclusion, we established a dermatophytosis animal model, which was proven useful for evaluating diagnostic methods and antifungal susceptibility testing Udgivelsesdato: 2008...... Trichophyton mentagrophytes test strains as etiologic agents, differences in inoculum concentrations, and inoculation with and without occlusion. The course of infection was evaluated clinically by redness and lesion scores and mycologically by microscopy, culture, and histopathology. The applicability of the...... model was evaluated with a recently developed diagnostic pan-dermatophyte PCR and antifungal treatment was tested with an oral solution of itraconazole, 10 mg/kg, once daily during days 3-14 of the test period. Pre-treatment of the skin with a manual razor was for practical reasons preferable to tape...

  1. Qualitative Event-based Diagnosis with Possible Conflicts: Case Study on the Third International Diagnostic Competition

    Data.gov (United States)

    National Aeronautics and Space Administration — We describe two model-based diagnosis algo- rithms entered into the Third International Diag- nostic Competition. We focus on the first diag- nostic problem of the...

  2. Application of Simulate Problem-Based Learning Teaching Model Combine with Role-Playing Method in the History-Taking Practices of Diagnostics%拟PBL教学模式加角色扮演法在诊断学问诊实践教学中的应用

    Institute of Scientific and Technical Information of China (English)

    杨波; 邹曲; 杨孟雪; 李娟; 聂永胜; 谭天海

    2015-01-01

    目的:探讨拟PBL教学模式+角色扮演法在诊断学问诊实践教学中的应用效果。方法:随机选择本院2012级临床医学专业97名学生为研究对象,所有同学均先后接受传统教学模式+SP教学法、拟PBL教学模式+角色扮演法进行问诊实践教学,每种方法实践学时均为4学时,通过学生问诊技能水平的比较和心得反馈评价两种教学方法的效果。结果:使用拟PBL教学模式+角色扮演法进行问诊实验教学时学生的各项问诊技能表现优于传统教学模式+SP教学法(P<0.05);90%以上的学生均认为使用拟PBL教学模式+角色扮演法进行问诊实验教学时对学习更感兴趣、课堂氛围更加活跃、对教学效果满意、有利于医患沟通能力的提高。结论:拟PBL教学模式+角色扮演教学法应用于问诊实践能调动学生的学习积极性,是培养学生问诊技能的好方法。%Objective:To evaluate the effect of simulate Problem-based learning (PBL) teaching model combine with Role-playing method in the history-taking practices of diagnostics.Method:97 students of grade 2012 clinical medicine specialty of Zunyi medical college were randomly selected.The traditional teaching model +standardized patient (SP) teaching method, simulate PBL teaching model + Role-playing method were applied in the history-taking practices teaching of all students successively, each method practice periods are for 4 hours.Two kinds of teaching methods effect was evaluated according to the results of history-taking skills test score and feelings of students after history-taking practices.Result:The score of history-taking skills test in the simulate PBL teaching model +Role-playing method were higher than traditional teaching model + SP teaching method group(P< 0.05), more than 90% of the students feel that the simulate PBL teaching model +Role-playing method was applied to history-taking practices teaching was more interested in

  3. Graph Model Based Indoor Tracking

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin

    2009-01-01

    The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...... infrastructure for different symbolic positioning technologies, e.g., Bluetooth and RFID. More specifically, the paper proposes a model of indoor space that comprises a base graph and mappings that represent the topology of indoor space at different levels. The resulting model can be used for one or several...... indoor positioning technologies. Focusing on RFID-based positioning, an RFID specific reader deployment graph model is built from the base graph model. This model is then used in several algorithms for constructing and refining trajectories from raw RFID readings. Empirical studies with implementations...

  4. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases the...... classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  5. Assessing the Nuclear Environment for ITER Port Plugs and Port-based Diagnostics

    International Nuclear Information System (INIS)

    Full text: ITER diagnostic systems will operate in a harsh nuclear environment. Component protection and nuclear shielding is realized by housing diagnostics inside massive steel port plug structures. The diagnostic port plugs must be optimized to provide adequate diagnostic throughput while minimizing the flux of escaping nuclear radiation and staying under a total dry weight of 45 metric tons. Most diagnostic systems are in the conceptual design phase and the optimization of this balance between performance, weight and shielding has not yet been realized. Sophisticated analysis tools are needed to predict the performance of components in ITER since actual measurements of the environment may not be realized for some time. The commercially available discrete-ordinates code Attila has been used for the conceptual phase analysis of several ITER diagnostics and diagnostic port plugs. Assessment of the diagnostic port plug nuclear environment with Attila is essentially a 3-step process involving a neutron transport run, a calculation of the activation and depletion in steel structures and finally the transport of the activated steel gamma rays. This paper will survey current neutronics results for a selection of Upper and Equatorial port plugs and the diagnostic systems in these ports. General port plug neutronics results like total nuclear heating and general shielding issues will be described. Specific diagnostic design studies will also be presented with a focus on meeting diagnostic measurement requirements while achieving adequate shielding. For example, the Core Imaging X-Ray Spectrometer diagnostic cannot use labyrinths to mitigate neutron and gamma flux. A multi-faceted solution approach was needed. This includes the use of radial baffles to limit streaming to only collimated neutrons and the narrowing of apertures that limits streaming while still allowing for minimum system performance. Many diagnostics have mirrors and shutters in the very front of the port

  6. A diagnostic strategy for pulmonary embolism based on standardised pretest probability and perfusion lung scanning: a management study

    Energy Technology Data Exchange (ETDEWEB)

    Miniati, Massimo; Monti, Simonetta; Bauleo, Carolina; Scoscia, Elvio; Tonelli, Lucia; Dainelli, Alba; Catapano, Giosue; Formichi, Bruno; Di Ricco, Giorgio; Prediletto, Renato; Carrozzi, Laura; Marini, Carlo [Istituto di Fisiologia, Clinica del Consiglio Nazionale delle Ricerche, Via G. Moruzzi 1, 56124, Pisa (Italy)

    2003-11-01

    Pulmonary embolism remains a challenging diagnostic problem. We developed a simple diagnostic strategy based on combination of assessment of the pretest probability with perfusion lung scan results to reduce the need for pulmonary angiography. We studied 390 consecutive patients (78% in-patients) with suspected pulmonary embolism. The pretest probability was rated low (<10%), intermediate (>10%, {<=}50%), moderately high (>50%, {<=}90%) or high (>90%) according to a structured clinical model. Perfusion lung scans were independently assigned to one of four categories: normal; near-normal; abnormal, suggestive of pulmonary embolism (wedge-shaped perfusion defects); abnormal, not suggestive of pulmonary embolism (perfusion defects other than wedge shaped). Pulmonary embolism was diagnosed in patients with abnormal scans suggestive of pulmonary embolism and moderately high or high pretest probability. Patients with normal or near-normal scans and those with abnormal scans not suggestive of pulmonary embolism and low pretest probability were deemed not to have pulmonary embolism. All other patients were allocated to pulmonary angiography. Patients in whom pulmonary embolism was excluded were left untreated. All patients were followed up for 1 year. Pulmonary embolism was diagnosed non-invasively in 132 patients (34%), and excluded in 191 (49%). Pulmonary angiography was required in 67 patients (17%). The prevalence of pulmonary embolism was 41% (n=160). Patients in whom pulmonary embolism was excluded had a thrombo-embolic risk of 0.4% (95% confidence interval: 0.0%-2.8%). Our strategy permitted a non-invasive diagnosis or exclusion of pulmonary embolism in 83% of the cases (95% confidence interval: 79%-86%), and appeared to be safe. (orig.)

  7. A diagnostic strategy for pulmonary embolism based on standardised pretest probability and perfusion lung scanning: a management study

    International Nuclear Information System (INIS)

    Pulmonary embolism remains a challenging diagnostic problem. We developed a simple diagnostic strategy based on combination of assessment of the pretest probability with perfusion lung scan results to reduce the need for pulmonary angiography. We studied 390 consecutive patients (78% in-patients) with suspected pulmonary embolism. The pretest probability was rated low (10%, ≤50%), moderately high (>50%, ≤90%) or high (>90%) according to a structured clinical model. Perfusion lung scans were independently assigned to one of four categories: normal; near-normal; abnormal, suggestive of pulmonary embolism (wedge-shaped perfusion defects); abnormal, not suggestive of pulmonary embolism (perfusion defects other than wedge shaped). Pulmonary embolism was diagnosed in patients with abnormal scans suggestive of pulmonary embolism and moderately high or high pretest probability. Patients with normal or near-normal scans and those with abnormal scans not suggestive of pulmonary embolism and low pretest probability were deemed not to have pulmonary embolism. All other patients were allocated to pulmonary angiography. Patients in whom pulmonary embolism was excluded were left untreated. All patients were followed up for 1 year. Pulmonary embolism was diagnosed non-invasively in 132 patients (34%), and excluded in 191 (49%). Pulmonary angiography was required in 67 patients (17%). The prevalence of pulmonary embolism was 41% (n=160). Patients in whom pulmonary embolism was excluded had a thrombo-embolic risk of 0.4% (95% confidence interval: 0.0%-2.8%). Our strategy permitted a non-invasive diagnosis or exclusion of pulmonary embolism in 83% of the cases (95% confidence interval: 79%-86%), and appeared to be safe. (orig.)

  8. Probability-Based Diagnostic Imaging Technique Using Error Functions for Active Structural Health Monitoring

    Directory of Open Access Journals (Sweden)

    Rahim Gorgin,

    2014-07-01

    Full Text Available This study presents a novel probability-based diagnostic imaging (PDI technique using error functions for active structural health monitoring (SHM. To achieve this, first the changes between baseline and current signals of each sensing path are measured, and by taking the root mean square of such changes, the energy of the scattered signal at different times can be calculated. Then, for different pairs of signal acquisition paths, an error function based on the energy of the scattered signals is introduced. Finally, the resultant error function is fused to the final estimation of the probability of damage presence in the monitoring area. As for applications, developed methods were employed to various damage identification cases, including cracks located in regions among an active sensor network with different configurations (pulse-echo and pitch-catch, and holes located in regions outside active network sensors with pitch-catch configuration. The results identified using experimental Lamb wave signals at different central frequencies corroborated that the developed PDI technique using error functions is capable of monitoring structural damage, regardless of its shape, size and location. The developed method doesn’t need direct interpretation of overlaid and dispersed lamb wave components for damage identification and can monitor damage located anywhere in the structure. These bright advantages, qualify the above presented PDI method for online structural health monitoring.

  9. Perspective ground-based method for diagnostics of the lower ionosphere and the neutral atmosphere

    Science.gov (United States)

    Bakhmetieva, N. V.; Grigoriev, G. I.; Tolmacheva, A. V.

    We present a new perspective ground-based method for diagnostics of the ionosphere and atmosphere parameters. The method uses one of the numerous physical phenomena observed in the ionosphere illuminated by high-power radio waves. It is a generation of the artificial periodic irregularities (APIs) in the ionospheric plasma. The APIs were found while studying the effects of ionospheric high-power HF modification. It was established that the APIs are formed by a standing wave that occurs due to interference between the upwardly radiated radio wave and its reflection off the ionosphere. The API studies are based upon observation of the Bragg backscatter of the pulsed probe radio wave from the artificial periodic structure. Bragg backscatter occurs if the spatial period of the irregularities is equal to half a wavelength of the probe signal. The API techniques makes it possible to obtain the following information: the profiles of electron density from the lower D-region up to the maximum of the F-layer; the irregular structure of the ionosphere including split of the regular E-layer, the sporadic layers; the vertical velocities in the D- and E-regions of the ionosphere; the turbulent velocities, turbulent diffusion coefficients and the turbopause altitude; the neutral temperatures and densities at the E-region altitudes; the parameters of the internal gravity waves and their spectral characteristics; the relative concentration of negative oxygen ions in the D-region. Some new results obtained by the API technique are discussed .

  10. Analysis of Renal Cell Carcinoma as a First Step for Developing Mass Spectrometry-Based Diagnostics

    Science.gov (United States)

    Yoshimura, Kentaro; Chen, Lee Chuin; Mandal, Mridul Kanti; Nakazawa, Tadao; Yu, Zhan; Uchiyama, Takahito; Hori, Hirokazu; Tanabe, Kunio; Kubota, Takeo; Fujii, Hideki; Katoh, Ryohei; Hiraoka, Kenzo; Takeda, Sen

    2012-10-01

    Immediate diagnosis of human specimen is an essential prerequisites in medical routines. This study aimed to establish a novel cancer diagnostics system based on probe electrospray ionization-mass spectrometry (PESI-MS) combined with statistical data processing. PESI-MS uses a very fine acupuncture needle as a probe for sampling as well as for ionization. To demonstrate the applicability of PESI-MS for cancer diagnosis, we analyzed nine cases of clear cell renal cell carcinoma (ccRCC) by PESI-MS and processed the data by principal components analysis (PCA). Our system successfully delineated the differences in lipid composition between non-cancerous and cancerous regions. In this case, triacylglycerol (TAG) was reproducibly detected in the cancerous tissue of nine different individuals, the result being consistent with well-known profiles of ccRCC. Moreover, this system enabled us to detect the boundaries of cancerous regions based on the expression of TAG. These results strongly suggest that PESI-MS will be applicable to cancer diagnosis, especially when the number of data is augmented.

  11. PEP-on-DEP: A competitive peptide-based disposable electrochemical aptasensor for renin diagnostics.

    Science.gov (United States)

    Biyani, Manish; Kawai, Keiko; Kitamura, Koichiro; Chikae, Miyuki; Biyani, Madhu; Ushijima, Hiromi; Tamiya, Eiichi; Yoneda, Takashi; Takamura, Yuzuru

    2016-10-15

    Antibody-based immunosensors are relatively less accessible to a wide variety of unreachable targets, such as low-molecular-weight biomarkers that represent a rich untapped source of disease-specific diagnostic information. Here, we present a peptide aptamer-based electrochemical sensor technology called 'PEP-on-DEP' to detect less accessible target molecules, such as renin, and to improve the quality of life. Peptide-based aptamers represent a relatively smart class of affinity binders and show great promise in biosensor development. Renin is involved in the regulation of arterial blood pressure and is an emerging biomarker protein for predicting cardiovascular risk and prognosis. To our knowledge, no studies have described aptamer molecules that can be used as new potent probes for renin. Here, we describe a portable electrochemical biosensor platform based on the newly identified peptide aptamer molecules for renin. We constructed a randomized octapeptide library pool with diversified sequences and selected renin specific peptide aptamers using cDNA display technology. We identified a few peptide aptamer sequences with a KD in the µM binding affinity range for renin. Next, we grafted the selected peptide aptamers onto gold nanoparticles and detected renin in a one-step competitive assay using our originally developed DEP (Disposable Electrochemical Printed) chip and a USB powered portable potentiostat system. We successfully detected renin in as little as 300ngmL(-1) using the PEP-on-DEP method. Thus, the generation and characterization of novel probes for unreachable target molecules by merging a newly identified peptide aptamer with electrochemical transduction allowed for the development of a more practical biosensor that, in principle, can be adapted to develop a portable, low-cost and mass-producible biosensor for point-of-care applications. PMID:26746799

  12. Computer-aided diagnostics of screening mammography using content-based image retrieval

    Science.gov (United States)

    Deserno, Thomas M.; Soiron, Michael; de Oliveira, Júlia E. E.; de A. Araújo, Arnaldo

    2012-03-01

    Breast cancer is one of the main causes of death among women in occidental countries. In the last years, screening mammography has been established worldwide for early detection of breast cancer, and computer-aided diagnostics (CAD) is being developed to assist physicians reading mammograms. A promising method for CAD is content-based image retrieval (CBIR). Recently, we have developed a classification scheme of suspicious tissue pattern based on the support vector machine (SVM). In this paper, we continue moving towards automatic CAD of screening mammography. The experiments are based on in total 10,509 radiographs that have been collected from different sources. From this, 3,375 images are provided with one and 430 radiographs with more than one chain code annotation of cancerous regions. In different experiments, this data is divided into 12 and 20 classes, distinguishing between four categories of tissue density, three categories of pathology and in the 20 class problem two categories of different types of lesions. Balancing the number of images in each class yields 233 and 45 images remaining in each of the 12 and 20 classes, respectively. Using a two-dimensional principal component analysis, features are extracted from small patches of 128 x 128 pixels and classified by means of a SVM. Overall, the accuracy of the raw classification was 61.6 % and 52.1 % for the 12 and the 20 class problem, respectively. The confusion matrices are assessed for detailed analysis. Furthermore, an implementation of a SVM-based CBIR system for CADx in screening mammography is presented. In conclusion, with a smarter patch extraction, the CBIR approach might reach precision rates that are helpful for the physicians. This, however, needs more comprehensive evaluation on clinical data.

  13. Improvement of thomson scattering diagnostics using stimulated-Brillouin-scattering-based phase conjugate mirrors

    International Nuclear Information System (INIS)

    In order to improve the measurement performance of incoherent Thomson scattering diagnostics, a high performance phase conjugate mirror based on stimulated Brillouin scattering (SBS-PCM) is applied to a Thomson scattering system for the first time in the JT-60U tokamak. We have demonstrated that a SBS-PCM which uses heavy-fluorocarbon liquid showed a high reflectivity of 95% at a high input-power of 145 W. Using the SBS-PCM, two newly developed methods were employed to increase the amount of scattered light. In the first method, we first developed a new optical design to provide a double-pass scattering scheme with the SBS-PCM. In this new optical design, a laser beam passing through the plasma is reflected by the SBS-PCM, and the reflected beam is returned via the same path by means of the phase conjugate effect, and is then passed through the plasma again, in order to increase the scattered light. A double-pass Thomson scattering scheme using the SBS-PCM was demonstrated in JT-60U ohmic plasma, resulting in an increase of the scattered light by a factor of 1.6, and the reduction of relative error by 2/3 for electron temperature measurement in contrast to single-pass scattering. A multi-pass Thomson scattering scheme is also proposed based on the results of double-pass scattering. It is estimated that multi-pass scattering allows the generation of several times the amount of scattered light, and the reduction of the relative error for electron temperature measurement by 37% in contrast to single-pass scattering. Regarding the second method, a high average-power of YAG laser system was developed by applying the SBS-PCM to a existent diagnostic laser. As a result, the average-power was increased by over 8 times in contrast to the average power of the original system, achieving up to 368 W (7.4 J x 50 Hz). (author)

  14. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP: overview and description of models, simulations and climate diagnostics

    Directory of Open Access Journals (Sweden)

    J.-F. Lamarque

    2012-08-01

    Full Text Available The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP consists of a series of timeslice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting radiative forcing and the associated composition changes. Here we introduce the various simulations performed under ACCMIP and the associated model output. The ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions lead to a significant range in emissions, mostly for ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind reveals biases consistent with state-of-the-art climate models. The model-to-model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results, but with outliers different enough to possibly affect their representation of climate impact on chemistry.

  15. Complex diagnostic investigations of energetic boiler elements as a base for modernization and safe exploitation time belonging

    International Nuclear Information System (INIS)

    Different methods for energetic boiler testing have been described for assessing safety of their exploitation. The results for typical boiler steels have been presented. The recommendations concerning exploitation time and conditions, modernization proposals or emergency repairs needs can be done on the base of results analysis of complex diagnostic testing. 14 refs, 7 figs

  16. Multi-Seconds Diagnostic Neutral Beam Injector Based on Arc-Discharge with LaB6 Hollow Cathode

    International Nuclear Information System (INIS)

    The diagnostic neutral beam injector based on arc-discharge plasma source with LaB6 hollow cathode is described.The ion source of the diagnostic injector provides a proton beam with a current up to 2.5A, the particle energy up to 50 keV, the beam divergence is ∼0.5 deg. The beam species at the 2 A ion current are: H+-83%, H2+-5%, H3+-12%. The injector was tested at pulse duration up to 2 seconds

  17. Developed of a high performance motor-operated valve (MOV) diagnostic system for effective condition-based maintenance

    International Nuclear Information System (INIS)

    The motor-operated valve (MOV) diagnostic system widely used at nuclear power plants is the system that can diagnose the set torque and amounts of abrasion with the analysis of acquired signal data of several sensors detecting the status, which is incorporated into a part of MOV. In order to introduce effective condition-based maintenance, higher precision, lower cost and labor saving of the diagnosis must be prerequisite and the MOV diagnostic system developed to realize this has been introduced into Ikata nuclear power plant. (T. Tanaka)

  18. Diagnostics of separately excited DC motor based on analysis and recognition of signals using FFT and Bayes classifier

    Directory of Open Access Journals (Sweden)

    Glowacz Witold

    2015-03-01

    Full Text Available In this article results of diagnostic investigations of separately excited DC motor were presented. In diagnostics were applied a Fourier analysis method based on the fast Fourier transform (FFT and a recognition method using Bayes classifier. In training process a set of the most important frequencies has been determined for which differences of corresponding signals in two states are the largest. Three categories of signals have been recognized in identification process: faultless state, state of the rotor broken one coil and state of the rotor shorted three coils.

  19. Means-End based Functional Modeling for Intelligent Control: Modeling and Experiments with an Industrial Heat Pump System

    DEFF Research Database (Denmark)

    Saleem, Arshad

    2007-01-01

    The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used in...... several diagnostic experiments analyzing different fault scenarios. The model and results of the experiments are explained and it is shown how MFM based intelligent modeling and automated reasoning can improve the fault diagnosis process significantly....

  20. Teaching dual-process diagnostic reasoning to doctor of nursing practice students: problem-based learning and the illness script.

    Science.gov (United States)

    Durham, Catherine O; Fowler, Terri; Kennedy, Sally

    2014-11-01

    Accelerating the development of diagnostic reasoning skills for nurse practitioner students is high on the wish list of many faculty. The purpose of this article is to describe how the teaching strategy of problem-based learning (PBL) that drills the hypothetico-deductive or analytic reasoning process when combined with an assignment that fosters pattern recognition (a nonanalytic process) teaches and reinforces the dual process of diagnostic reasoning. In an online Doctor of Nursing Practice program, four PBL cases that start with the same symptom unfold over 2 weeks. These four cases follow different paths as they unfold leading to different diagnoses. Culminating each PBL case, a unique assignment called an illness script was developed to foster the development of pattern recognition. When combined with hypothetico-deductive reasoning drilled during the PBL case, students experience the dual process approach to diagnostic reasoning used by clinicians. PMID:25350904

  1. Toward development of a surface-enhanced Raman scattering (SERS)-based cancer diagnostic immunoassay panel.

    Science.gov (United States)

    Granger, Jennifer H; Granger, Michael C; Firpo, Matthew A; Mulvihill, Sean J; Porter, Marc D

    2013-01-21

    Proteomic analyses of readily obtained human fluids (e.g., serum, urine, and saliva) indicate that the diagnosis of complex diseases will be enhanced by the simultaneous measurement of multiple biomarkers from such samples. This paper describes the development of a nanoparticle-based multiplexed platform that has the potential for simultaneous read-out of large numbers of biomolecules. For this purpose, we have chosen pancreatic adenocarcinoma (PA) as a test bed for diagnosis and prognosis. PA is a devastating form of cancer in which an estimated 86% of diagnoses resulted in death in the United States in 2010. The high mortality rate is due, in part, to the asymptomatic development of the disease and the dearth of sensitive diagnostics available for early detection. One promising route lies in the development of a serum biomarker panel that can generate a signature unique to early stage PA. We describe the design and development of a proof-of-concept PA biomarker immunoassay array coupled with surface-enhanced Raman scattering (SERS) as a sensitive readout method. PMID:23150876

  2. TADPOLE for longitudinal electron-bunch diagnostics based on electro-optic upconversion

    Energy Technology Data Exchange (ETDEWEB)

    Schwinkendorf, Jan-Patrick, E-mail: jan-patrick.schwinkendorf@desy.de; Wunderlich, Steffen, E-mail: steffen.wunderlich@desy.de; Schaper, Lucas; Schmidt, Bernhard; Osterhoff, Jens

    2014-03-11

    Electron-bunch diagnostics are desired to utilize unambiguous, non-destructive, single-shot techniques. Various methods fulfill the latter two demands, but feature significant ambiguities and constraints in the reconstruction of time-domain electron-bunch profiles, e.g. uncertainties arising from the phase retrieval of coherent radiation using the Kramers–Kronig relation. We present a novel method of measuring the spectral phase. The measurement is based on upconversion in an electro-optic crystal, where the THz-field spectrum of fs-electron bunches is shifted to the near-infrared. This technique allows the single-shot detection of its longitudinal form factor in both, amplitude and phase. The spectral phase and amplitude information is measured and thus the temporal profile reconstructed using temporal analysis by dispersing a pair of light E-fields, also known as TADPOLE. This is a combination of frequency resolved optical gating (FROG) and spectral interferometry, enabling the temporal measurement of low-power laser pulses. In this procedure, a narrow-bandwidth laser pulse detecting the longitudinal variations in the transverse electric field of an electron bunch via frequency mixing is interfered with a broadband and FROG-characterized reference pulse. The longitudinal beam profile may therefore be unambiguously inferred from the generated interferogram and the detected spectral-phase-information of the reference pulse.

  3. An engineering approach to knowledge-based systems, the alarm processing and diagnostic system

    International Nuclear Information System (INIS)

    The number of alarms that may be initiated during transients or accidents in nuclear-generating control rooms may temporarily exceed an operator's ability to assimilate and respond. This phenomenon is characterized as Cognitive Overload. The Alarm Processing and Diagnostic System (APDS) was designed to deal with this problem through a unique and operationally sensitive method of alarm prioritization and filtration. The approach taken attempts to parallel the operator's situation assessment methodology when dealing with transient conditions. A strong criteria for the development methodology employed was its ultimate acceptance by parties engaged in the operation of nuclear power facilities. As such, the methodology used had to be easily understood and consistent with the acceptance standards of nuclear power. This necessitated the verifiable practices found in engineering design. While APDS remains rooted in artificial intelligence or expert systems, it goes beyond the paradigm of rules and inferencing to an object-oriented structure that allows traditional and well-documented engineering-based decision methods to be applied. These features have important consequences when considering final acceptance, implementation, and maintenance. 3 refs., 1 tab

  4. Diagnostics of pigmented skin tumors based on laser-induced autofluorescence and diffuse reflectance spectroscopy

    International Nuclear Information System (INIS)

    Results of investigation of cutaneous benign and malignant pigmented lesions by laser-induced autofluorescence spectroscopy (LIAFS) and diffuse reflectance spectroscopy (DRS) are presented. The autofluorescence of human skin was excited by a 337-nm nitrogen laser. A broadband halogen lamp (400-900 nm) was used for diffuse reflectance measurements. A microspectrometer detected in vivo the fluorescence and reflectance signals from human skin. The main spectral features of benign (dermal nevi, compound nevi, dysplastic nevi) and malignant (melanoma) lesions are discussed. The combined usage of the fluorescence and reflectance spectral methods to determine the type of the lesion, which increases the total diagnostic accuracy, is compared with the usage of LIAFS or DRS only. We also applied colorimetric transformation of the reflectance spectra detected and received additional evaluation criteria for determination of type of the lesion under study. Spectra from healthy skin areas near the lesion were detected and changes between healthy and lesion skin spectra were revealed. The influence of the main skin pigments on the detected spectra is discussed and evaluation of possibilities for differentiation between malignant and benign lesions is performed based on their spectral properties. This research shows that the non-invasive and high-sensitive in vivo detection by means of appropriate light sources and detectors should be possible, related to the real-time determination of existing pathological conditions. (special issue devoted to application of laser technologies in biophotonics and biomedical studies)

  5. Agent-based station for on-line diagnostics by self-adaptive laser Doppler vibrometry

    Science.gov (United States)

    Serafini, S.; Paone, N.; Castellini, P.

    2013-12-01

    A self-adaptive diagnostic system based on laser vibrometry is proposed for quality control of mechanical defects by vibration testing; it is developed for appliances at the end of an assembly line, but its characteristics are generally suited for testing most types of electromechanical products. It consists of a laser Doppler vibrometer, equipped with scanning mirrors and a camera, which implements self-adaptive bahaviour for optimizing the measurement. The system is conceived as a Quality Control Agent (QCA) and it is part of a Multi Agent System that supervises all the production line. The QCA behaviour is defined so to minimize measurement uncertainty during the on-line tests and to compensate target mis-positioning under guidance of a vision system. Best measurement conditions are reached by maximizing the amplitude of the optical Doppler beat signal (signal quality) and consequently minimize uncertainty. In this paper, the optimization strategy for measurement enhancement achieved by the down-hill algorithm (Nelder-Mead algorithm) and its effect on signal quality improvement is discussed. Tests on a washing machine in controlled operating conditions allow to evaluate the efficacy of the method; significant reduction of noise on vibration velocity spectra is observed. Results from on-line tests are presented, which demonstrate the potential of the system for industrial quality control.

  6. A collisional radiative model of hydrogen plasmas developed for diagnostic purposes of negative ion sources

    Energy Technology Data Exchange (ETDEWEB)

    Iordanova, Snejana, E-mail: snejana@phys.uni-sofia.bg; Paunska, Tsvetelina [Faculty of Physics, Sofia University, BG-1164 Sofia (Bulgaria)

    2016-02-15

    A collisional radiative model of low-pressure hydrogen plasmas is elaborated and applied in optical emission spectroscopy diagnostics of a single element of a matrix source of negative hydrogen ions. The model accounts for the main processes determining both the population densities of the first ten states of the hydrogen atom and the densities of the positive hydrogen ions H{sup +}, H{sub 2}{sup +}, and H{sub 3}{sup +}. In the calculations, the electron density and electron temperature are varied whereas the atomic and molecular temperatures are included as experimentally obtained external parameters. The ratio of the H{sub α} to H{sub β} line intensities is calculated from the numerical results for the excited state population densities, obtained as a solution of the set of the steady-state rate balance equations. The comparison of measured and theoretically obtained ratios of line intensities yields the values of the electron density and temperature as well as of the degree of dissociation, i.e., of the parameters which have a crucial role for the volume production of the negative ions.

  7. Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes.

    Science.gov (United States)

    Sze, N N; Wong, S C

    2007-11-01

    This study attempts to evaluate the injury risk of pedestrian casualties in traffic crashes and to explore the factors that contribute to mortality and severe injury, using the comprehensive historical crash record that is maintained by the Hong Kong Transport Department. The injury, demographic, crash, environmental, geometric, and traffic characteristics of 73,746 pedestrian casualties that were involved in traffic crashes from 1991 to 2004 are considered. Binary logistic regression is used to determine the associations between the probability of fatality and severe injury and all contributory factors. A consideration of the influence of implicit attributes on the trend of pedestrian injury risk, temporal confounding, and interaction effects is progressively incorporated into the predictive model. To verify the goodness-of-fit of the proposed model, the Hosmer-Lemeshow test and logistic regression diagnostics are conducted. It is revealed that there is a decreasing trend in pedestrian injury risk, controlling for the influences of demographic, road environment, and other risk factors. In addition, the influences of pedestrian behavior, traffic congestion, and junction type on pedestrian injury risk are subject to temporal variation. PMID:17920851

  8. A collisional radiative model of hydrogen plasmas developed for diagnostic purposes of negative ion sources

    International Nuclear Information System (INIS)

    A collisional radiative model of low-pressure hydrogen plasmas is elaborated and applied in optical emission spectroscopy diagnostics of a single element of a matrix source of negative hydrogen ions. The model accounts for the main processes determining both the population densities of the first ten states of the hydrogen atom and the densities of the positive hydrogen ions H+, H2+, and H3+. In the calculations, the electron density and electron temperature are varied whereas the atomic and molecular temperatures are included as experimentally obtained external parameters. The ratio of the Hα to Hβ line intensities is calculated from the numerical results for the excited state population densities, obtained as a solution of the set of the steady-state rate balance equations. The comparison of measured and theoretically obtained ratios of line intensities yields the values of the electron density and temperature as well as of the degree of dissociation, i.e., of the parameters which have a crucial role for the volume production of the negative ions

  9. Hepatic trauma: CT findings and considerations based on our experience in emergency diagnostic imaging

    International Nuclear Information System (INIS)

    and peritoneal fluid evaluation may be used to make a first differentiation of severity of lesions, but haemodynamic parameters may help the clinician to prefer a conservative treatment. In emergency based hospitals and also in our experience, positive benefits spring from diagnostic accuracy and consequent correct therapeutic management

  10. Hepatic trauma: CT findings and considerations based on our experience in emergency diagnostic imaging

    Energy Technology Data Exchange (ETDEWEB)

    Romano, Luigia; Giovine, Sabrina; Guidi, Guido; Tortora, Giovanni; Cinque, Teresa; Romano, Stefania E-mail: stefromano@libero.it

    2004-04-01

    findings and peritoneal fluid evaluation may be used to make a first differentiation of severity of lesions, but haemodynamic parameters may help the clinician to prefer a conservative treatment. In emergency based hospitals and also in our experience, positive benefits spring from diagnostic accuracy and consequent correct therapeutic management.

  11. Base Flow Model Validation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The program focuses on turbulence modeling enhancements for predicting high-speed rocket base flows. A key component of the effort is the collection of...

  12. Clinical Diagnostic Biomarkers from the Personalization of Computational Models of Cardiac Physiology.

    Science.gov (United States)

    Lamata, Pablo; Cookson, Andrew; Smith, Nic

    2016-01-01

    Computational modelling of the heart is rapidly advancing to the point of clinical utility. However, the difficulty of parameterizing and validating models from clinical data indicates that the routine application of truly predictive models remains a significant challenge. We argue there is significant value in an intermediate step towards prediction. This step is the use of biophysically based models to extract clinically useful information from existing patient data. Specifically in this paper we review methodologies for applying modelling frameworks for this goal in the areas of quantifying cardiac anatomy, estimating myocardial stiffness and optimizing measurements of coronary perfusion. Using these indicative examples of the general overarching approach, we finally discuss the value, ongoing challenges and future potential for applying biophysically based modelling in the clinical context. PMID:26399986

  13. In-cylinder pressure-based direct techniques and time frequency analysis for combustion diagnostics in IC engines

    International Nuclear Information System (INIS)

    Highlights: • Direct pressure-based techniques have been applied successfully to spark-ignition engines. • The burned mass fraction of pressure-based techniques has been compared with that of 2- and 3-zone combustion models. • The time frequency analysis has been employed to simulate complex diesel combustion events. - Abstract: In-cylinder pressure measurement and analysis has historically been a key tool for off-line combustion diagnosis in internal combustion engines, but online applications for real-time condition monitoring and combustion management have recently become popular. The present investigation presents and compares different low computing-cost in-cylinder pressure based methods for the analyses of the main features of combustion, that is, the start of combustion, the end of combustion and the crankshaft angle that responds to half of the overall burned mass. The instantaneous pressure in the combustion chamber has been used as an input datum for the described analytical procedures and it has been measured by means of a standard piezoelectric transducer. Traditional pressure-based techniques have been shown to be able to predict the burned mass fraction time history more accurately in spark ignition engines than in diesel engines. The most suitable pressure-based techniques for both spark ignition and compression ignition engines have been chosen on the basis of the available experimental data. Time–frequency analysis has also been applied to the analysis of diesel combustion, which is richer in events than spark ignited combustion. Time frequency algorithms for the calculation of the mean instantaneous frequency are computationally efficient, allow the main events of the diesel combustion to be identified and provide the greatest benefits in the presence of multiple injection events. These algorithms can be optimized and applied to onboard diagnostics tools designed for real control, but can also be used as an advanced validation tool for

  14. A novel molecule integrating therapeutic and diagnostic activities reveals multiple aspects of stem cell-based therapy.

    Science.gov (United States)

    Hingtgen, Shawn D; Kasmieh, Randa; van de Water, Jeroen; Weissleder, Ralph; Shah, Khalid

    2010-04-01

    Stem cells are promising therapeutic delivery vehicles; however pre-clinical and clinical applications of stem cell-based therapy would benefit significantly from the ability to simultaneously determine therapeutic efficacy and pharmacokinetics of therapies delivered by engineered stem cells. In this study, we engineered and screened numerous fusion variants that contained therapeutic (TRAIL) and diagnostic (luciferase) domains designed to allow simultaneous investigation of multiple events in stem cell-based therapy in vivo. When various stem cell lines were engineered with the optimized molecule, SRL(O)L(2)TR, diagnostic imaging showed marked differences in the levels and duration of secretion between stem cell lines, while the therapeutic activity of the molecule showed the different secretion levels translated to significant variability in tumor cell killing. In vivo, simultaneous diagnostic and therapeutic monitoring revealed that stem cell-based delivery significantly improved pharmacokinetics and anti-tumor effectiveness of the therapy compared to intravenous or intratumoral delivery. As treatment for highly malignant brain tumor xenografts, tracking SRL(O)L(2)TR showed stable stem cell-mediated delivery significantly regressed peripheral and intracranial tumors. Together, the integrated diagnostic and therapeutic properties of SRL(O)L(2)TR answer critical questions necessary for successful utilization of stem cells as novel therapeutic vehicles. PMID:20127797

  15. Modular microfluidic cartridge-based universal diagnostic system for global health applications

    Science.gov (United States)

    Becker, Holger; Klemm, Richard; Dietze, William; White, Wallace; Hlawatsch, Nadine; Freyberg, Susanne; Moche, Christian; Dailey, Peter; Gärtner, Claudia

    2016-03-01

    Current microfluidics-enabled point-of-care diagnostic systems are typically designed specifically for one assay type, e.g. a molecular diagnostic assay for a single disease of a class of diseases. This approach often leads to high development cost and a significant training requirement for users of different instruments. We have developed an open platform diagnostic system which allows to run molecular, immunological and clinical assays on a single instrument platform with a standardized microfluidic cartridge architecture in an automated sample-in answer-out fashion. As examples, a molecular diagnostic assay for tuberculosis, an immunoassay for HIV p24 and a clinical chemistry assay for ALT liver function have been developed and results of their pre-clinical validation are presented.

  16. Modeling Guru: Knowledge Base for NASA Modelers

    Science.gov (United States)

    Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

    2009-05-01

    Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the

  17. New approach in multipurpose optical diagnostics: fluorescence based assay for simultaneous determination of physicochemical parameters

    OpenAIRE

    Moczko, Ewa

    2009-01-01

    The development of sensors assays for comprehensive characterisation of biological samples and effective minimal-invasive diagnostics is highly prioritised. Last decade this research area has been actively developing due to possibility of simultaneous, real- time, in vivo detection and monitoring of diverse physicochemical parameters and analytes. The new approach which has been introduced in this thesis was to develop and examine an optical diagnostic assay consisting of a ...

  18. Nanotechnology-Based Surface Plasmon Resonance Affinity Biosensors for In Vitro Diagnostics.

    Science.gov (United States)

    Antiochia, Riccarda; Bollella, Paolo; Favero, Gabriele; Mazzei, Franco

    2016-01-01

    In the last decades, in vitro diagnostic devices (IVDDs) became a very important tool in medicine for an early and correct diagnosis, a proper screening of targeted population, and also assessing the efficiency of a specific therapy. In this review, the most recent developments regarding different configurations of surface plasmon resonance affinity biosensors modified by using several nanostructured materials for in vitro diagnostics are critically discussed. Both assembly and performances of the IVDDs tested in biological samples are reported and compared. PMID:27594884

  19. Development and optimization of the LHC and the SPS beam diagnostics based on synchrotron radiation monitoring

    International Nuclear Information System (INIS)

    Measuring the beam transverse emittance is fundamental in every accelerator, in particular for colliders, where its precise determination is essential to maximize the luminosity and thus the performance of the colliding beams. Synchrotron Radiation (SR) is a versatile tool for non-destructive beam diagnostics, since its characteristics are closely related to those of the source beam. At CERN, being the only available diagnostics at high beam intensity and energy, SR monitors are exploited as the proton beam size monitor of the two higher energy machines, the Super Proton Synchrotron (SPS) and the Large Hadron Collider (LHC). The thesis work documented in this report focused on the design, development, characterization and optimization of these beam size monitors. Such studies were based on a comprehensive set of theoretical calculations, numerical simulations and experiments. A powerful simulation tool has been developed combining conventional softwares for SR simulation and optics design, thus allowing the description of an SR monitor from its source up to the detector. The simulations were confirmed by direct observations, and a detailed performance studies of the operational SR imaging monitor in the LHC, where different techniques for experimentally validating the system were applied, such as cross-calibrations with the wire scanners at low intensity (that are considered as a reference) and direct comparison with beam sizes de-convoluted from the LHC luminosity measurements. In 2015, the beam sizes to be measured with the further increase of the LHC beam energy to 7 TeV will decrease down to ∼190 μm. In these conditions, the SR imaging technique was found at its limits of applicability since the error on the beam size determination is proportional to the ratio of the system resolution and the measured beam size. Therefore, various solutions were probed to improve the system's performance such as the choice of one light polarization, the reduction of

  20. Event-Based Activity Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2004-01-01

    We present and discuss a modeling approach that supports event-based modeling of information and activity in information systems. Interacting human actors and IT-actors may carry out such activity. We use events to create meaningful relations between information structures and the related...

  1. Laser-based imaging measurements in combustion: New results for fuel/air mixture and temperature diagnostics

    International Nuclear Information System (INIS)

    Advanced laser-based imaging diagnostics is an important tool for the development and optimization of modern combustion devices that can fulfil the future requirements in terms of energy efficiency maximization and pollutant minimization. The determination of the conditions prior to combustion in terms of fuel concentration, fuel/air equivalence ratio and temperature is crucial for the control of the subsequent combustion process. At the same time, fresh-gas and burned gas temperatures are important for modelling of combustion, spray evaporation and pollutant formation. These two tasks for diagnostics development have therefore been addressed recently. While laser-induced fluorescence of organic molecules in liquid fuels has frequently been carried out on a qualitative level, a more detailed understanding of individual molecules that are applied as 'fuel tracers' in an otherwise non-fluorescing fuel has developed in recent years (C Schulz and V Sick 2005 Tracer-LIF diagnostics: Quantitative measurement of fuel concentration, temperature and air/fuel ratio in practical combustion situations Prog. Energy Combust Sci. 31 75-121). The first applications were based on the pragmatic assumption that absorption cross-sections and fluorescence quantum yields were independent of temperature and pressure and that fluorescence was either independent of or inversely dependent (in the case of aromatic compounds) on oxygen partial pressure. Recent measurements of these interdependencies show that a quantitative interpretation of signals under combustion conditions (especially in internal-combustion-engines) requires a detailed understanding of the underlying photophysics (W Koban, J D Koch, V Sick, N Wermuth, R K Hanson and C Schulz 2005 Predicting LIF signal strength for toluene and 3-pentanone under engine-related temperature and pressure conditions Proc. Combust. Inst. 30 1545--53). The signal dependence on temperature and oxygen concentration, in turn, is strong enough to

  2. An MRI-based diagnostic framework for early diagnosis of dyslexia

    International Nuclear Information System (INIS)

    A computer-aided diagnosis (CAD) system for early diagnosis of dyslexia was developed and tested. Dyslexia can severely impair the learning abilities of children so improved diagnostic methods are needed. Neuropathological studies show abnormal anatomy of the cerebral white matter (CWM) in dyslexic brains. We sought to develop an MRI-based macroscopic neuropathological correlate to the minicolumnopathy of dyslexia that relates to cortical connectivity: the gyral window. The brains of dyslexic patients often exhibit decreased gyrifications, so the thickness of gyral CWM for dyslexic subjects is greater than for normal subjects. We developed an MRI-based method for assessment of gyral CWM thickness with automated recognition of abnormal (e.g., dyslexic) brains. In vivo data was collected from 16 right-handed dyslexic men aged 18-40 years, and a group of 14 controls matched for gender, age, educational level, socioeconomic background, handedness and general intelligence. All the subjects were physically healthy and free of history of neurological diseases and head injury. Images were acquired with the same 1.5T MRI scanner (GE, Milwaukee, WI, USA) with voxel resolution 0.9375 x 0.9375 x 1.5 mm using a T1-weighted imaging sequence protocol. The ''ground truth'' diagnosis to evaluate the classification accuracy for each patient was given by the clinicians. The accuracy of diagnosis/classification of both the training and test subjects was evaluated using the Chi-square test at the three confidence levels - 85, 90 and 95% - in order to examine significant differences in the Levy distances. As expected, the 85% confidence level yielded the best results, the system correctly classified 16 out of 16 dyslexic subjects (a 100% accuracy) and 14 out of 14 control subjects (a 100% accuracy). At the 90% confidence level, 16 out of 16 dyslexic subjects were still classified correctly; however, only 13 out of 14 control subjects were correct, bringing the accuracy rate for the

  3. An MRI-based diagnostic framework for early diagnosis of dyslexia

    Energy Technology Data Exchange (ETDEWEB)

    El-Baz, A. [University of Louisville, Bioengineering Department, Louisville, KY (United States); Casanova, M.; Mott, M.; Switala, A. [University of Louisville, Department of Psychiatry and Behavioral Science, Louisville, KY (United States); Gimel' farb, G. [University of Auckland, Computer Science Department, Auckland (New Zealand)

    2008-09-15

    A computer-aided diagnosis (CAD) system for early diagnosis of dyslexia was developed and tested. Dyslexia can severely impair the learning abilities of children so improved diagnostic methods are needed. Neuropathological studies show abnormal anatomy of the cerebral white matter (CWM) in dyslexic brains. We sought to develop an MRI-based macroscopic neuropathological correlate to the minicolumnopathy of dyslexia that relates to cortical connectivity: the gyral window. The brains of dyslexic patients often exhibit decreased gyrifications, so the thickness of gyral CWM for dyslexic subjects is greater than for normal subjects. We developed an MRI-based method for assessment of gyral CWM thickness with automated recognition of abnormal (e.g., dyslexic) brains. In vivo data was collected from 16 right-handed dyslexic men aged 18-40 years, and a group of 14 controls matched for gender, age, educational level, socioeconomic background, handedness and general intelligence. All the subjects were physically healthy and free of history of neurological diseases and head injury. Images were acquired with the same 1.5T MRI scanner (GE, Milwaukee, WI, USA) with voxel resolution 0.9375 x 0.9375 x 1.5 mm using a T1-weighted imaging sequence protocol. The ''ground truth'' diagnosis to evaluate the classification accuracy for each patient was given by the clinicians. The accuracy of diagnosis/classification of both the training and test subjects was evaluated using the Chi-square test at the three confidence levels - 85, 90 and 95% - in order to examine significant differences in the Levy distances. As expected, the 85% confidence level yielded the best results, the system correctly classified 16 out of 16 dyslexic subjects (a 100% accuracy) and 14 out of 14 control subjects (a 100% accuracy). At the 90% confidence level, 16 out of 16 dyslexic subjects were still classified correctly; however, only 13 out of 14 control subjects were correct, bringing the

  4. Application of new simulation algorithms for modeling rf diagnostics of electron clouds

    International Nuclear Information System (INIS)

    Traveling wave rf diagnostics of electron cloud build-up show promise as a non-destructive technique for measuring plasma density and the efficacy of mitigation techniques. However, it is very difficult to derive an absolute measure of plasma density from experimental measurements for a variety of technical reasons. Detailed numerical simulations are vital in order to understand experimental data, and have successfully modeled build-up. Such simulations are limited in their ability to reproduce experimental data due to the large separation of scales inherent to the problem. Namely, one must resolve both rf frequencies in the GHz range, as well as the plasma modulation frequency of tens of MHz, while running for very long simulations times, on the order of microseconds. The application of new numerical simulation techniques allow us to bridge the simulation scales in this problem and produce spectra that can be directly compared to experiments. The first method is to use a plasma dielectric model to measure plasma-induced phase shifts in the rf wave. The dielectric is modulated at a low frequency, simulating the effects of multiple bunch crossings. This allows simulations to be performed without kinetic particles representing the plasma, which both speeds up the simulations as well as reduces numerical noise from interpolation of particle charge and currents onto the computational grid. Secondly we utilize a port boundary condition model to simultaneously absorb rf at the simulation boundaries, and to launch the rf into the simulation. This method improves the accuracy of simulations by restricting rf frequencies better than adding an external (finite) current source to drive rf, and absorbing layers at the boundaries. We also explore the effects of non-uniform plasma densities on the simulated spectra.

  5. NIF neutron diagnostic concept based on n-p scattering from a thin CH2 converter foil

    International Nuclear Information System (INIS)

    The National Ignition Facility (NIF) is a 1.8 MJ glass laser which will initially be used to demonstrate ignition and gain in an inertially confined plasma. The present NIF target design is predicted to have a thermonuclear output of up to 10 MH for 1.8 MJ of 0.35 microm laser energy incident in a hohlraum with a peak radiation drive temperature of 300 eV. These levels of thermonuclear output open up the possibility of several new classes of neutron diagnostics. One such class of instruments is based on the measurement of proton recoils from the interaction of 2.45 MeV and 14.1 MeV neutrons in thin CH2 foils. The diagnostic would operate by detecting the proton recoils at near forward angles in either time-integrated detectors or time-resolved current mode detectors. The protons may be energy resolved using range filters or by magnetic analysis in a simple dipole magnet spectrography. This diagnostic technique offers a very clean measurement of neutron yield that can be almost entirely free of scattered neutron backgrounds. At higher neutron yields, measurements of time-resolved ion temperature and reaction burn time become possible. The paper discusses several possible diagnostic configurations based on this concept and presents calculations of the sensitivity of the technique

  6. Numerical Simulation and Analysis of the Localized Heavy Precipitation Event in South Korea based on diagnostic variables

    Science.gov (United States)

    Roh, Joon-Woo; Choi, Young-Jean

    2016-04-01

    Accurate prediction of precipitation is one of the most difficult and significant tasks in weather forecasting. Heavy precipitations in the Korean Peninsula are caused by various physical mechanisms, which are affected by shortwave trough, quasi-stationary moisture convergence zone among varying air masses, and a direct/indirect effect of tropical cyclone. Many previous studies have used observations, numerical modeling, and statistics to investigate the potential causes of warm-season heavy precipitation in South Korea. Especially, the frequency of warm-season torrential rainfall events more than 30 mm/h precipitation has increased threefold in Seoul, a metropolitan city in South Korea, in recent 30 years. Localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances along the Changma front, or from convective instabilities resulting from unstable air masses. In order to investigate localized heavy precipitation system in Seoul metropolitan area, analysis and numerical experiment were performed for a typical event in 20 June 2014. This case is described to a structure of baroclinic instability associated with a short-wave trough from the northwest and high moist and warm air by a thermal low from the southwest of the Korean Peninsula. We investigated localized heavy precipitation in narrow zone of the Seoul urban area using numerical simulations based on the Weather Research and Forecast (WRF) model with convective scale. The topography and land use data of the revised U.S. Geological Survey (USGS) data and the appropriate set of physical scheme options for WRF model simulation were deliberated. Simulation experiments showed patches of primary physical structures related to the localized heavy precipitation using the diagnostic fields, which are storm relative helicity (SRH), updraft helicity (UH), and instantaneous contraction rates (ICON). SRH and UH are dominantly related to

  7. Modelling Gesture Based Ubiquitous Applications

    CERN Document Server

    Zacharia, Kurien; Varghese, Surekha Mariam

    2011-01-01

    A cost effective, gesture based modelling technique called Virtual Interactive Prototyping (VIP) is described in this paper. Prototyping is implemented by projecting a virtual model of the equipment to be prototyped. Users can interact with the virtual model like the original working equipment. For capturing and tracking the user interactions with the model image and sound processing techniques are used. VIP is a flexible and interactive prototyping method that has much application in ubiquitous computing environments. Different commercial as well as socio-economic applications and extension to interactive advertising of VIP are also discussed.

  8. Modeling and diagnostic techniques applicable to the analysis of pressure noise in pressurized water reactors and pressure-sensing systems

    International Nuclear Information System (INIS)

    Pressure noise data from a PWR are interpreted by means of a computer-implemented model. The model's parameters, namely hydraulic impedances and noise sources, are either calculated or deduced from fits to data. Its accuracy is encouraging and raises the possibility of diagnostic assistance for nuclear plant monitoring. A number of specific applications of pressure noise in the primary system of a PWR and in a pressure sensing system are suggested

  9. A strategy for establishing diagnostic and related services to dairy farmers in developing countries based on radioimmunoassay of progesterone in milk

    International Nuclear Information System (INIS)

    The radioimmunoassay (RIA) for progesterone in milk samples collected from cattle has been used for monitoring ovarian activity, diagnosis of pregnancy and non-pregnancy, assessment of the accuracy of oestrus detection and for surveying efficiency of artificial insemination services. The establishment of a service to dairy farmers in developing countries based on this technique has not been previously reported but there are clear potential benefits in such a service. A strategy was therefore developed for the establishment of diagnostic and related services to dairy farmers in Morocco on a pilot basis, using RIA of progesterone in milk for possible adoption as a model for other developing countries. (author)

  10. Sketch-based geologic modeling

    Science.gov (United States)

    Rood, M. P.; Jackson, M.; Hampson, G.; Brazil, E. V.; de Carvalho, F.; Coda, C.; Sousa, M. C.; Zhang, Z.; Geiger, S.

    2015-12-01

    Two-dimensional (2D) maps and cross-sections, and 3D conceptual models, are fundamental tools for understanding, communicating and modeling geology. Yet geologists lack dedicated and intuitive tools that allow rapid creation of such figures and models. Standard drawing packages produce only 2D figures that are not suitable for quantitative analysis. Geologic modeling packages can produce 3D models and are widely used in the groundwater and petroleum communities, but are often slow and non-intuitive to use, requiring the creation of a grid early in the modeling workflow and the use of geostatistical methods to populate the grid blocks with geologic information. We present an alternative approach to rapidly create figures and models using sketch-based interface and modelling (SBIM). We leverage methods widely adopted in other industries to prototype complex geometries and designs. The SBIM tool contains built-in geologic rules that constrain how sketched lines and surfaces interact. These rules are based on the logic of superposition and cross-cutting relationships that follow from rock-forming processes, including deposition, deformation, intrusion and modification by diagenesis or metamorphism. The approach allows rapid creation of multiple, geologically realistic, figures and models in 2D and 3D using a simple, intuitive interface. The user can sketch in plan- or cross-section view. Geologic rules are used to extrapolate sketched lines in real time to create 3D surfaces. Quantitative analysis can be carried our directly on the models. Alternatively, they can be output as simple figures or imported directly into other modeling tools. The software runs on a tablet PC and can be used in a variety of settings including the office, classroom and field. The speed and ease of use of SBIM enables multiple interpretations to be developed from limited data, uncertainty to be readily appraised, and figures and models to be rapidly updated to incorporate new data or concepts.

  11. In-service diagnostic systems based on the on-line measurement of vibrations of nuclear power plant primary circuit components

    International Nuclear Information System (INIS)

    The VUEZ-DSS-86 diagnostic system consists of piezoelectric acceleration sensors, charge preamplifiers, a 16-channel unit of insulating amplifiers, a 16-channel filter unit, and a unit for diagnostic channels control. Technical parameters of the elements and units are given. The system has been installed at reactor unit 4 of the Dukovany nuclear power plant. Because of drawbacks of the measuring and evaluating instrumentation, a new microprocessor-based diagnostic system is being developed. (E.J.). 1 fig

  12. Cytokine and Antibody Based Diagnostic Algorithms for Sputum Culture-Positive Pulmonary Tuberculosis.

    Directory of Open Access Journals (Sweden)

    Tao Chen

    Full Text Available Tuberculosis (TB is one of the most serious infectious diseases globally and has high mortality rates. A variety of diagnostic tests are available, yet none are wholly reliable. Serum cytokines, although significantly and frequently induced by different diseases and thus good biomarkers for disease diagnosis and prognosis, are not sufficiently disease-specific. TB-specific antibody detection, on the other hand, has been reported to be highly specific but not sufficiently sensitive. In this study, our aim was to improve the sensitivity and specificity of TB diagnosis by combining detection of TB-related cytokines and TB-specific antibodies in peripheral blood samples.TB-related serum cytokines were screened using a human cytokine array. TB-related cytokines and TB-specific antibodies were detected in parallel with microarray technology. The diagnostic performance of the new protocol for active TB was systematically compared with other traditional methods.Here, we show that cytokines I-309, IL-8 and MIG are capable of distinguishing patients with active TB from healthy controls, patients with latent TB infection, and those with a range of other pulmonary diseases, and that these cytokines, and their presence alongside antibodies for TB-specific antigens Ag14-16kDa, Ag32kDa, Ag38kDa and Ag85B, are specific markers for active TB. The diagnostic protocol for active TB developed here, which combines the detection of three TB-related cytokines and TB-specific antibodies, is highly sensitive (91.03%, specific (90.77% and accurate (90.87%.Our results show that combining detection of TB-related cytokines and TB-specific antibodies significantly enhances diagnostic accuracy for active TB, providing greater accuracy than conventional diagnostic methods such as interferon gamma release assays (IGRAs, TB antibody Colloidal Gold Assays and microbiological culture, and suggest that this diagnostic protocol has potential for clinical application.

  13. A Clinical Analysis of 293 FUO Patients, A Diagnostic Model Discriminating infectious Diseases from Non-infectious Diseases

    Institute of Scientific and Technical Information of China (English)

    2014-01-01

    Objective A diagnostic model was established to discriminate infectious diseases from non-infectious diseases. Methods The clinical data of patients with fever of unknown origin (FUO) hospitalized in Xiangya Hospital Central South University, from January, 2006 to April, 2011 were retrospectively analyzed. Patients enrolled were divided into two groups. The ifrst group was used to develop a diagnostic model: independent variables were recorded and considered in a logistic regression analysis to identify infectious and non-infectious diseases (αin= 0.05, αout= 0.10). The second group was used to evaluate the diagnostic model and make ROC analysis. Results The diagnostic rate of 143 patients in the ifrst group was 87.4%, the diagnosis included infectious disease (52.4%), connective tissue diseases (16.8%), neoplastic disease (16.1%) and miscellaneous (2.1%). The diagnostic rate of 168 patients in the second group was 88.4%, and the diagnosis was similar to the ifrst group. Logistic regression analysis showed that decreased white blood cell count (WBC 320 U/L) and lymphadenectasis were independent risk factors associated with non-infectious diseases. The odds ratios were 14.74, 5.84 and 5.11 (P≤ 0.01) , respectively. In ROC analysis, the sensitivity and speciifcity of the positive predictive values was 62.1% and 89.1%, respectively, while that of negative predicting values were 75% and 81.7%, respectively (AUC = 0.76,P = 0.00). Conclusions The combination of WBC 320 U/L and lymphadenectasis may be useful in discriminating infectious diseases from non-infectious diseases in patients hospitalized as FUO.

  14. AN EXAMPLE - BASED, DIAGNOSTIC INVESTIGATION OF VALUE CREATION AND VALUE DESTRUCTION BY CORPORATE ACTIVISTS

    OpenAIRE

    GABURICI Matei

    2014-01-01

    This paper investigates, through an example-based scenario, the extent to which corporate activists create or destroy shareholder value; there are five high-profile campaigns analyzed related to four major players. The foundation of the analysis is a variant of DCF model which examines the cash flows to equity. In 4 out of 5 cases the financial metrics are computed in order to assess the performance of the subject company ex-ante and ex-post activists’ involvement.

  15. HMM-based Trust Model

    DEFF Research Database (Denmark)

    ElSalamouny, Ehab; Nielsen, Mogens; Sassone, Vladimiro

    2010-01-01

    Probabilistic trust has been adopted as an approach to taking security sensitive decisions in modern global computing environments. Existing probabilistic trust frameworks either assume fixed behaviour for the principals or incorporate the notion of ‘decay' as an ad hoc approach to cope with thei...... the major limitation of existing Beta trust model. We show the consistency of the HMM-based trust model and contrast it against the well known Beta trust model with the decay principle in terms of the estimation precision....

  16. A microcomputer-based data acquisition system for diagnostic monitoring and control of high-speed electric motors

    OpenAIRE

    Moyers, Kevin Keith

    1987-01-01

    A microcomputer-based data acquisition and control system was designed for the diagnostic monitoring and control of high-speed electric motors. The system was utilized in high-speed bearing life-testing, using an electric motor as a test vehicle. Bearing vibration and outer race temperature were continuously monitored for each ball bearing in the motor. In addition, the stator winding and motor casing temperature were monitored. The monitoring system was successful i...

  17. Deletion Diagnostics for Alternating Logistic Regressions

    OpenAIRE

    Preisser, John S; By, Kunthel; Perin, Jamie; Qaqish, Bahjat F.

    2012-01-01

    Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditi...

  18. DNA-Aptamer optical biosensors based on a LPG-SPR optical fiber platform for point-of-care diagnostic

    Science.gov (United States)

    Coelho, L.; Queirós, R. B.; Santos, J. L.; Martins, M. Cristina L.; Viegas, D.; Jorge, P. A. S.

    2014-03-01

    Surface Plasmon Resonance (SPR) is the base for some of the most sensitive label free optical fiber biosensors. However, most solutions presented to date require the use of fragile fiber optic structure such as adiabatic tapers or side polished fibers. On the other hand, long-period fiber gratings (LPG) present themselves as an interesting solution to attain an evanescent wave refractive index sensor platform while preserving the optical fiber integrity. The combination of these two approaches constitute a powerful platform that can potentially reach the highest sensitivities as it was recently demonstrated by detailed theoretical study [1, 2]. In this work, a LPG-SPR platform is explored in different configurations (metal coating between two LPG - symmetric and asymmetric) operating in the telecom band (around 1550 nm). For this purpose LPGs with period of 396 μm are combined with tailor made metallic thin films. In particular, the sensing regions were coated with 2 nm of chromium to improve the adhesion to the fiber and 16 nm of gold followed by a 100 nm thick layer of TiO2 dielectric material strategically chosen to attain plasmon resonance in the desired wavelength range. The obtained refractometric platforms were then validated as a biosensor. For this purpose the detection of thrombin using an aptamer based probe was used as a model system for protein detection. The surface of the sensing fibers were cleaned with isopropanol and dried with N2 and then the aminated thrombin aptamer (5'-[NH2]- GGTTGGTGTGGTTGG-3') was immobilized by physisorption using Poly-L-Lysine (PLL) as cationic polymer. Preliminary results indicate the viability of the LPFG-SPR-APTAMER as a flexible platforms point of care diagnostic biosensors.

  19. Diagnostic method for photovoltaic systems based on light I-V measurements

    DEFF Research Database (Denmark)

    Spataru, Sergiu; Sera, Dezso; Kerekes, Tamas;

    2015-01-01

    Improving PV system reliability and reducing maintenance and operating costs have become important factors in increasing the competitiveness of PV. Addressing these issues requires diagnostic methods that can detect and identify the occurrence and cause of power loss in the PV system, be it exter...

  20. Nanostructured tracers for laser-based diagnostics in high-speed flows

    NARCIS (Netherlands)

    Ghaemi, S.; Schmidt-Ott, A.; Scarano, F.

    2010-01-01

    The potential application of aggregates of nanoparticles for high-speed flow diagnostics is investigated. Aluminum nanoparticles around 10 nm in diameter are produced by spark discharge in argon gas. Through rapid coagulation and oxidation, aggregates of small effective density are formed. They are

  1. Evidence-based medical research on diagnostic criteria and screening technique of vascular mild cognitive impairment

    Directory of Open Access Journals (Sweden)

    Xia-wei LIU

    2015-07-01

    Full Text Available Background Vascular mild cognitive impairment (VaMCI is the prodromal syndrome of vascular dementia (VaD and key target for drug treatment. There is controversy over the diagnostic criteria and screening tools of VaMCI, which affects its clinical diagnosis. This paper aims to explore the clinical features, diagnostic criteria and screening technique of VaMCI.  Methods Taking "vascular mild cognitive impairment OR vascular cognitive impairment no dementia" as retrieval terms, search in PubMed database from January 1997 to March 2015 and screen relevant literatures concerning VaMCI. According to Guidance for the Preparation of Neurological Management Guidelines revised by European Federation of Neurological Societies (EFNS in 2004, evidence grading was performed on literatures. Results A total of 32 literatures in English were selected according to inclusion and exclusion criteria, including 3 guidelines and consensus and 29 clinical studies. Seven literatures (2 on Level Ⅰ, 5 on Level Ⅱ studied on neuropsychological features in VaMCI patients and found reduced processing speed and executive function impairment were main features. Two literatures reported the diagnostic criteria of VaMCI, including VaMCI criteria published by American Heart Association (AHA/American Stroke Association (ASA in 2011 and "Diagnostic Criteria for Vascular Cognitive Disorders" published by International Society for Vascular Behavioral and Cognitive Disorders (VASCOG in 2014. Fifteen literatures (4 on LevelⅠ, 11 on Level Ⅱ described the diagnostic criteria of VaMCI used in clinical research, from which 6 operational diagnostic items were extracted. Fourteen literatures (4 on Level Ⅰ, 10 on Level Ⅱ described neuropsychological assessment tools for VaMCI screening, and found the 5-minute protocol recommended by National Institute of Neurological Disorders and Stroke-Canadian Stroke Network (NINDS-CSN was being good consistency with other neuropsychological

  2. Observationally derived transport diagnostics for the lowermost stratosphere and their application to the GMI chemistry and transport model

    Directory of Open Access Journals (Sweden)

    S. E. Strahan

    2007-01-01

    Full Text Available Transport from the surface to the lowermost stratosphere can occur on timescales of a few months or less, making it possible for short-lived tropospheric pollutants to influence stratospheric composition and chemistry. Models used to study this influence must demonstrate the credibility of their chemistry and transport in the upper troposphere and lower stratosphere (UT/LS. Data sets from satellite and aircraft instruments measuring CO, O3, N2O, and CO2 in the UT/LS are used to create a suite of diagnostics of the seasonally-varying transport into and within the lowermost stratosphere, and of the coupling between the troposphere and stratosphere in the extratropics. The diagnostics are used to evaluate a version of the Global Modeling Initiative (GMI Chemistry and Transport Model that uses a combined tropospheric and stratospheric chemical mechanism and meteorological fields from the GEOS-4 general circulation model. The diagnostics derived from N2O and O3 show that the model lowermost stratosphere (LMS has realistic input from the overlying high latitude stratosphere in all seasons. Diagnostics for the LMS show two distinct layers. The upper layer (~350 K–380 K has a strong annual cycle in its composition, while the lower layer, just above the tropopause, shows no seasonal variation in the degree of tropospheric coupling or composition. The GMI CTM agrees closely with the observations in both layers and is realistically coupled to the UT in all seasons. This study demonstrates the credibility of the GMI CTM for the study of the impact of tropospheric emissions on the stratosphere.

  3. Diagnostic procedure on brake pad assembly based on Young's modulus estimation

    International Nuclear Information System (INIS)

    Quality control of brake pads is an important issue, since the pad is a key component of the braking system. Typical damage of a brake pad assembly is the pad–backing plate detachment that affects and modifies the mechanical properties of the whole system. The most sensitive parameter to the damage is the effective Young's modulus, since the damage induces a decrease of the pad assembly stiffness and therefore of its effective Young's modulus: indeed its variation could be used for diagnostic purposes. The effective Young's modulus can be estimated from the first bending resonance frequency identified from the frequency response function measured on the pad assembly. Two kinds of excitation methods, i.e. conventional impulse excitation and magnetic actuation, will be presented and two different measurement sensors, e.g. laser Doppler vibrometer and microphone, analyzed. The robustness of the effective Young's modulus as a diagnostic feature will be demonstrated in comparison to the first bending resonance frequency, which is more sensitive to geometrical dimensions. Variability in the sample dimension, in fact, will induce a variation of the resonance frequency which could be mistaken for damage. The diagnostic approach has been applied to a set of undamaged and damaged pad assemblies showing good performance in terms of damage identification. The environmental temperature can be an important interfering input for the diagnostic procedure, since it influences the effective Young's modulus of the assembly. For that reason, a test at different temperatures in the range between 15 °C and 30 °C has been performed, evidencing that damage identification technique is efficient at any temperature. The robustness of the Young's modulus as a diagnostic feature with respect to damping is also presented. (paper)

  4. A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears.

    Directory of Open Access Journals (Sweden)

    Nina Linder

    Full Text Available INTRODUCTION: Microscopy is the gold standard for diagnosis of malaria, however, manual evaluation of blood films is highly dependent on skilled personnel in a time-consuming, error-prone and repetitive process. In this study we propose a method using computer vision detection and visualization of only the diagnostically most relevant sample regions in digitized blood smears. METHODS: Giemsa-stained thin blood films with P. falciparum ring-stage trophozoites (n = 27 and uninfected controls (n = 20 were digitally scanned with an oil immersion objective (0.1 µm/pixel to capture approximately 50,000 erythrocytes per sample. Parasite candidate regions were identified based on color and object size, followed by extraction of image features (local binary patterns, local contrast and Scale-invariant feature transform descriptors used as input to a support vector machine classifier. The classifier was trained on digital slides from ten patients and validated on six samples. RESULTS: The diagnostic accuracy was tested on 31 samples (19 infected and 12 controls. From each digitized area of a blood smear, a panel with the 128 most probable parasite candidate regions was generated. Two expert microscopists were asked to visually inspect the panel on a tablet computer and to judge whether the patient was infected with P. falciparum. The method achieved a diagnostic sensitivity and specificity of 95% and 100% as well as 90% and 100% for the two readers respectively using the diagnostic tool. Parasitemia was separately calculated by the automated system and the correlation coefficient between manual and automated parasitemia counts was 0.97. CONCLUSION: We developed a decision support system for detecting malaria parasites using a computer vision algorithm combined with visualization of sample areas with the highest probability of malaria infection. The system provides a novel method for blood smear screening with a significantly reduced need for

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

    Directory of Open Access Journals (Sweden)

    Jaume Pérez-Sánchez

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

  6. Mucins as Diagnostic and Prognostic Biomarkers in a Fish-Parasite Model: Transcriptional and Functional Analysis

    Science.gov (United States)

    Pérez-Sánchez, Jaume; Estensoro, Itziar; Redondo, María José; Calduch-Giner, Josep Alvar; Kaushik, Sadasivam; Sitjà-Bobadilla, Ariadna

    2013-01-01

    Mucins are O-glycosylated glycoproteins present on the apex of all wet-surfaced epithelia with a well-defined expression pattern, which is disrupted in response to a wide range of injuries or challenges. The aim of this study was to identify mucin gene sequences of gilthead sea bream (GSB), to determine its pattern of distribution in fish tissues and to analyse their transcriptional regulation by dietary and pathogenic factors. Exhaustive search of fish mucins was done in GSB after de novo assembly of next-generation sequencing data hosted in the IATS transcriptome database (www.nutrigroup-iats.org/seabreamdb). Six sequences, three categorized as putative membrane-bound mucins and three putative secreted-gel forming mucins, were identified. The transcriptional tissue screening revealed that Muc18 was the predominant mucin in skin, gills and stomach of GSB. In contrast, Muc19 was mostly found in the oesophagus and Muc13 was along the entire intestinal tract, although the posterior intestine exhibited a differential pattern with a high expression of an isoform that does not share a clear orthologous in mammals. This mucin was annotated as intestinal mucin (I-Muc). Its RNA expression was highly regulated by the nutritional background, whereas the other mucins, including Muc2 and Muc2-like, were expressed more constitutively and did not respond to high replacement of fish oil (FO) by vegetable oils (VO) in plant protein-based diets. After challenge with the intestinal parasite Enteromyxum leei, the expression of a number of mucins was decreased mainly in the posterior intestine of infected fish. But, interestingly, the highest down-regulation was observed for the I-Muc. Overall, the magnitude of the changes reflected the intensity and progression of the infection, making mucins and I-Muc, in particular, reliable markers of prognostic and diagnostic value of fish intestinal health. PMID:23776483

  7. A model-based display

    International Nuclear Information System (INIS)

    A model-based display is identified, discussed, and illustrated. The model used in the display is based upon the Rankine Cycle, a heat engine cycle. Plant process data from the loss of main and auxiliary feedwater event at the Davis-Besse Plant on June 9, l985 is used to illustrate the display. The model used in the display fuses individual process variables into process functions. It also serves as a medium to communicate status of the process to human users. The human users may evaluate the goals of operation from the displayed process functions. Because of these display features, the user's cognitive workload is minimized. The opinions expressed herein are the author's personal ones and do not necessarily reflect criteria, requirements, and guidelines of the U.S. Nuclear Regulatory Commission

  8. Image-based medical expert teleconsultation in acute care of injuries. A systematic review of effects on information accuracy, diagnostic validity, clinical outcome, and user satisfaction.

    Directory of Open Access Journals (Sweden)

    Marie Hasselberg

    Full Text Available OBJECTIVE: To systematically review the literature on image-based telemedicine for medical expert consultation in acute care of injuries, considering system, user, and clinical aspects. DESIGN: Systematic review of peer-reviewed journal articles. DATA SOURCES: Searches of five databases and in eligible articles, relevant reviews, and specialized peer-reviewed journals. ELIGIBILITY CRITERIA: Studies were included that covered teleconsultation systems based on image capture and transfer with the objective of seeking medical expertise for the diagnostic and treatment of acute injury care and that presented the evaluation of one or several aspects of the system based on empirical data. Studies of systems not under routine practice or including real-time interactive video conferencing were excluded. METHOD: The procedures used in this review followed the PRISMA Statement. Predefined criteria were used for the assessment of the risk of bias. The DeLone and McLean Information System Success Model was used as a framework to synthesise the results according to system quality, user satisfaction, information quality and net benefits. All data extractions were done by at least two reviewers independently. RESULTS: Out of 331 articles, 24 were found eligible. Diagnostic validity and management outcomes were often studied; fewer studies focused on system quality and user satisfaction. Most systems were evaluated at a feasibility stage or during small-scale pilot testing. Although the results of the evaluations were generally positive, biases in the methodology of evaluation were concerning selection, performance and exclusion. Gold standards and statistical tests were not always used when assessing diagnostic validity and patient management. CONCLUSIONS: Image-based telemedicine systems for injury emergency care tend to support valid diagnosis and influence patient management. The evidence relates to a few clinical fields, and has substantial methodological

  9. A model for understanding diagnostic imaging referrals and complex interaction processes within the bigger picture of a healthcare system

    International Nuclear Information System (INIS)

    Using experiences from the South African public healthcare system with limited resources, this review proposes a model that captures a holistic perspective of diagnostic imaging services embedded in a network of negotiated decision-making processes. Professional interdependency and interprofessional collaboration, cooperation and coordination are built around the central notion of integration in order to achieve a seamless transition through the continuum of various types of services needed to come to a diagnosis. Health-system role players interact with patients who enter the system from the perspective of their life-world. The distribution of diagnostic imaging services – within one setting or at multiple levels of care – demonstrates how fragments of information are filtered, interpreted and transformed at each point of care. The proposed model could contribute to alignment towards a common goal: services providing holistic quality of care within and beyond a complex healthcare system

  10. Towards literature-based feature selection for diagnostic classification: A meta-analysis of resting-state fMRI in depression

    Directory of Open Access Journals (Sweden)

    Benedikt Sundermann

    2014-09-01

    Full Text Available Information derived from functional magnetic resonance imaging (fMRI during wakeful rest has been introduced as a candidate diagnostic biomarker in unipolar major depressive disorder (MDD. Multiple reports of resting state fMRI in MDD describe group effects. Such prior knowledge can be adopted to pre-select potentially discriminating features for diagnostic classification models with the aim to improve diagnostic accuracy. Purpose of this analysis was to consolidate spatial information about alterations of spontaneous brain activity in MDD, primarily to serve as feature selection for multivariate pattern analysis techniques (MVPA. 32 studies were included in final analyses. Coordinates extracted from the original reports were assigned to two categories based on directionality of findings. Meta-analyses were calculated using the non-additive activation likelihood estimation approach with coordinates organized by subject group to account for non-independent samples. Converging evidence revealed a distributed pattern of brain regions with increased or decreased spontaneous activity in MDD. The most distinct finding was hyperactivity/hyperconnectivity presumably reflecting the interaction of cortical midline structures (posterior default mode network components including the precuneus and neighboring posterior cingulate cortices associated with self-referential processing and the subgenual anterior cingulate and neighboring medial frontal cortices with lateral prefrontal areas related to externally-directed cognition. Other areas of hyperactivity/hyperconnectivity include the left lateral parietal cortex, right hippocampus and right cerebellum whereas hypoactivity/hypoconnectivity was observed mainly in the left temporal cortex, the insula, precuneus, superior frontal gyrus, lentiform nucleus and thalamus. Results are made available in two different data formats to be used as spatial hypotheses in future studies, particularly for diagnostic

  11. High resolution transmission spectroscopy as a diagnostic for Jovian exoplanet atmospheres: constraints from theoretical models

    Energy Technology Data Exchange (ETDEWEB)

    Kempton, Eliza M.-R. [Department of Physics, Grinnell College, Grinnell, IA 50112 (United States); Perna, Rosalba [Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794 (United States); Heng, Kevin, E-mail: kemptone@grinnell.edu [University of Bern, Center for Space and Habitability, Sidlerstrasse 5, CH-3012 Bern (Switzerland)

    2014-11-01

    We present high resolution transmission spectra of giant planet atmospheres from a coupled three-dimensional (3D) atmospheric dynamics and transmission spectrum model that includes Doppler shifts which arise from winds and planetary motion. We model Jovian planets covering more than two orders of magnitude in incident flux, corresponding to planets with 0.9-55 day orbital periods around solar-type stars. The results of our 3D dynamical models reveal certain aspects of high resolution transmission spectra that are not present in simple one-dimensional (1D) models. We find that the hottest planets experience strong substellar to anti-stellar (SSAS) winds, resulting in transmission spectra with net blueshifts of up to 3 km s{sup –1}, whereas less irradiated planets show almost no net Doppler shifts. We find only minor differences between transmission spectra for atmospheres with temperature inversions and those without. Compared to 1D models, peak line strengths are significantly reduced for the hottest atmospheres owing to Doppler broadening from a combination of rotation (which is faster for close-in planets under the assumption of tidal locking) and atmospheric winds. Finally, high resolution transmission spectra may be useful in studying the atmospheres of exoplanets with optically thick clouds since line cores for very strong transitions should remain optically thick to very high altitude. High resolution transmission spectra are an excellent observational test for the validity of 3D atmospheric dynamics models, because they provide a direct probe of wind structures and heat circulation. Ground-based exoplanet spectroscopy is currently on the verge of being able to verify some of our modeling predictions, most notably the dependence of SSAS winds on insolation. We caution that interpretation of high resolution transmission spectra based on 1D atmospheric models may be inadequate, as 3D atmospheric motions can produce a noticeable effect on the absorption

  12. Modelling magnetic fields diagnostic coils using a 3D free-boundary equilibrium code

    International Nuclear Information System (INIS)

    A project to interpret the magnetic field diagnostics of the W VII-X stellarator is summarized. The NEMEC free-boundary equilibrium code is used to calculate 3D ideal-MHD equilibria which are consistent with the fields due to external currents. The signals of the diagnostic coils are related to the plasma equilibrium by combining the NEMEC code with a technique for calculating the magnetic field outside the plasma due to the plasma currents alone. These techniques will be used to design the diagnostic coils on the W VII-X device. Test run results are shown. The arrow plot for a beta value of 0.9 % shows the characteristic dipole-like field of the plasma currents. The signals of three flux loops as a function of beta produce curves which are quite smooth for moderate beta values

  13. Survivors of early childhood trauma: evaluating a two-dimensional diagnostic model of the impact of trauma and neglect

    OpenAIRE

    Wildschut, Marleen; Langeland, Willemien; Jan H Smit; Draijer, Nel

    2014-01-01

    Background: A two-dimensional diagnostic model for (complex) trauma-related and personality disorders has been proposed to assess the severity and prognosis of the impact of early childhood trauma and emotional neglect. An important question that awaits empirical examination is whether a distinction between trauma-related disorders and personality disorders reflects reality when focusing on survivors of early childhood trauma. And, is a continuum of trauma diagnoses a correct assumption and, ...

  14. Operational experiences on the Borssele nuclear power plant using computer based surveillance and diagnostic system on-line

    International Nuclear Information System (INIS)

    The on-line monitoring and diagnostics system of Borssele nuclear power plant (NPP), designed and established by the ECN Energy Research Foundation, has been operating continuously since 1983. The system is extended in form of multiprocessing, multi-tasking structure performing real-time monitoring, on-line reactor parameters' calculation, data-base preparation for expert systems and providing early information on possible malfunctions even in the incipient stage making alert by passive alarms. The system realized has already been operating in the course of 7 fuel cycles of the reactor starting from start-up through normal power operation. An expert system operating on the VAX work station is added to the surveillance and diagnostics system for data base management of the observed physical parameters relevant to the NPP under supervision. The paper highlights the surveillance and diagnostic modules involved, in their actual hierarchical form in use, presents theoretical considerations applied to the design of the surveillance system together with the results obtained through the 12th to 17th fuel cycles of the NPP including start-ups and shut-downs and reveals the experience thus gained by both utility and ECN through the application of the system described. (author). 19 refs.; 4 figs

  15. DNA Barcode-Based PCR-RFLP and Diagnostic PCR for Authentication of Jinqian Baihua She (Bungarus Parvus).

    Science.gov (United States)

    Li, Xiaolei; Zeng, Weiping; Liao, Jing; Liang, Zhenbiao; Huang, Shuhua; Chao, Zhi

    2015-01-01

    We established polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and diagnostic PCR based on cytochrome C oxidase subunit I (COI) barcodes of Bungarus multicinctus, genuine Jinqian Baihua She (JBS), and adulterant snake species. The PCR-RFLP system utilizes the specific restriction sites of SpeI and BstEII in the COI sequence of B. multicinctus to allow its cleavage into 3 fragments (120 bp, 230 bp, and 340 bp); the COI sequences of the adulterants do not contain these restriction sites and therefore remained intact after digestion with SpeI and BstEII (except for that of Zaocys dhumnades, which could be cleaved into a 120 bp and a 570 bp fragment). For diagnostic PCR, a pair of species-specific primers (COI37 and COI337) was designed to amplify a specific 300 bp amplicon from the genomic DNA of B. multicinctus; no such amplicons were found in other allied species. We tested the two methods using 11 commercial JBS samples, and the results demonstrated that barcode-based PCR-RFLP and diagnostic PCR both allowed effective and accurate authentication of JBS. PMID:26078770

  16. DNA Barcode-Based PCR-RFLP and Diagnostic PCR for Authentication of Jinqian Baihua She (Bungarus Parvus

    Directory of Open Access Journals (Sweden)

    Xiaolei Li

    2015-01-01

    Full Text Available We established polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP and diagnostic PCR based on cytochrome C oxidase subunit I (COI barcodes of Bungarus multicinctus, genuine Jinqian Baihua She (JBS, and adulterant snake species. The PCR-RFLP system utilizes the specific restriction sites of SpeI and BstEII in the COI sequence of B. multicinctus to allow its cleavage into 3 fragments (120 bp, 230 bp, and 340 bp; the COI sequences of the adulterants do not contain these restriction sites and therefore remained intact after digestion with SpeI and BstEII (except for that of Zaocys dhumnades, which could be cleaved into a 120 bp and a 570 bp fragment. For diagnostic PCR, a pair of species-specific primers (COI37 and COI337 was designed to amplify a specific 300 bp amplicon from the genomic DNA of B. multicinctus; no such amplicons were found in other allied species. We tested the two methods using 11 commercial JBS samples, and the results demonstrated that barcode-based PCR-RFLP and diagnostic PCR both allowed effective and accurate authentication of JBS.

  17. Flyer-Plate-Based Current Diagnostic for Magnetized Liner Inertial Fusion Experiments

    Science.gov (United States)

    Reneker, Joseph; Gomez, Matthew; Hess, Mark; Jennings, Christopher

    2015-11-01

    Accurate measurements of the current delivered to Magnetized Liner Inertial Fusion (MagLIF) loads on the Z machine are important for understanding the dynamics of liner implosions. Difficulty acquiring a reliable load current measurement with the standard Z load B-dots has spurred the development of alternative load current diagnostics. Velocimetry of an electromagnetically-accelerated flyer plate can be used to infer the drive current on a flyer surface. A load current diagnostic design is proposed using a cylindrical flyer plate in series with the MagLIF target. Aspects of the flyer plate design were optimized using magnetohydrodynamic simulations. Design and preliminary results will be presented. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  18. Consensus-based reporting standards for diagnostic test accuracy studies for paratuberculosis in ruminants

    DEFF Research Database (Denmark)

    Gardner, Ian A.; Nielsen, Søren Saxmose; Whittington, Richard;

    2011-01-01

    studies such as herd tests, potential use of experimental challenge studies, a more diverse group of testing purposes and sampling designs, and the widespread lack of an ante-mortem reference standard with high sensitivity and specificity. The objective of the present study was to develop a modified...... Reporting of Animal Diagnostic Accuracy Studies for paratuberculosis), should facilitate improved quality of reporting of the design, conduct and results of paratuberculosis test accuracy studies which were identified as “poor” in a review published in 2008 in Veterinary Microbiology......The Standards for Reporting of Diagnostic Accuracy (STARD) statement (www.stard-statement.org) was developed to encourage complete and transparent reporting of key elements of test accuracy studies in human medicine. The statement was motivated by widespread evidence of bias in test accuracy...

  19. Score, pseudo-score and residual diagnostics for goodness-of-fit of spatial point process models

    OpenAIRE

    Baddeley, Adrian; Rubak, Ege Holger; Møller, Jesper

    2010-01-01

    We develop newtools for formal inference and informalmodel validation in the analysis of spatial point pattern data. The score test is generalised to a ‘pseudo-score’ test derived from Besag’s pseudolikelihood, and to a class of diagnostics based on point process residuals. The results lend theoretical support to the established practice of using functional summary statistics such as Ripley’s K-function, when testing for complete spatial randomness; and they provide new tools such as the comp...

  20. Experience with the SNS LabVIEW/EPICS-Based Diagnostics Instruments

    International Nuclear Information System (INIS)

    The SNS Diagnostics Group uses rack-mounted PCs running LabVIEW and EPICS to implement its instruments as network attached devices. Many of these instruments, such as wire scanners and beam position monitors, come from the partner labs. The final integration and testing is done at SNS. We have now gone through several commissioning runs with success. This paper describes the integration, the commissioning, and the physics performance of the devices

  1. PCA3 and PCA3-Based Nomograms Improve Diagnostic Accuracy in Patients Undergoing First Prostate Biopsy

    OpenAIRE

    Virginie Vlaeminck-Guillem; Paul Perrin; Philippe Paparel; Claire Rodriguez-Lafrasse; Myriam Decaussin-Petrucci; Alain Ruffion; Denis Champetier; Marian Devonec

    2013-01-01

    While now recognized as an aid to predict repeat prostate biopsy outcome, the urinary PCA3 (prostate cancer gene 3) test has also been recently advocated to predict initial biopsy results. The objective is to evaluate the performance of the PCA3 test in predicting results of initial prostate biopsies and to determine whether its incorporation into specific nomograms reinforces its diagnostic value. A prospective study included 601 consecutive patients addressed for initial prostate biopsy. Th...

  2. Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics

    OpenAIRE

    Quinn, John A.; Nakasi, Rose; Mugagga, Pius K. B.; Byanyima, Patrick; Lubega, William; Andama, Alfred

    2016-01-01

    Point of care diagnostics using microscopy and computer vision methods have been applied to a number of practical problems, and are particularly relevant to low-income, high disease burden areas. However, this is subject to the limitations in sensitivity and specificity of the computer vision methods used. In general, deep learning has recently revolutionised the field of computer vision, in some cases surpassing human performance for other object recognition tasks. In this paper, we evaluate...

  3. Sub-millimeter Bunch Length Non-invasive Diagnostic Based on the Diffraction and Cherenkov Radiation

    International Nuclear Information System (INIS)

    A layout for the investigation the coherent Cherenkov radiation from a dielectric target with a large spectral dispersion and the coherent diffraction radiation from a conducting screen as a tool for non-invasive longitudinal electron beam profile diagnostics are proposed for the 20∼30MeV Linac at Shanghai Institute of Applied Physics (SINAP). In this paper the status of the joint experiment and future plans are presented.

  4. Nanomaterials—Tools, Technology and Methodology of Nanotechnology Based Biomedical Systems for Diagnostics and Therapy

    Directory of Open Access Journals (Sweden)

    Christian Schmidt

    2015-07-01

    Full Text Available Nanomedicine helps to fight diseases at the cellular and molecular level by utilizing unique properties of quasi-atomic particles at a size scale ranging from 1 to 100 nm. Nanoparticles are used in therapeutic and diagnostic approaches, referred to as theranostics. The aim of this review is to illustrate the application of general principles of nanotechnology to select examples of life sciences, molecular medicine and bio-assays. Critical aspects relating to those examples are discussed.

  5. AN EXAMPLE - BASED, DIAGNOSTIC INVESTIGATION OF VALUE CREATION AND VALUE DESTRUCTION BY CORPORATE ACTIVISTS

    Directory of Open Access Journals (Sweden)

    GABURICI Matei

    2014-06-01

    Full Text Available This paper investigates, through an example-based scenario, the extent to which corporate activists create or destroy shareholder value; there are five high-profile campaigns analyzed related to four major players. The foundation of the analysis is a variant of DCF model which examines the cash flows to equity. In 4 out of 5 cases the financial metrics are computed in order to assess the performance of the subject company ex-ante and ex-post activists’ involvement.

  6. Analytical Redundancy Design for Aeroengine Sensor Fault Diagnostics Based on SROS-ELM

    Directory of Open Access Journals (Sweden)

    Jun Zhou

    2016-01-01

    Full Text Available Analytical redundancy technique is of great importance to guarantee the reliability and safety of aircraft engine system. In this paper, a machine learning based aeroengine sensor analytical redundancy technique is developed and verified through hardware-in-the-loop (HIL simulation. The modified online sequential extreme learning machine, selective updating regularized online sequential extreme learning machine (SROS-ELM, is employed to train the model online and estimate sensor measurements. It selectively updates the output weights of neural networks according to the prediction accuracy and the norm of output weight vector, tackles the problems of singularity and ill-posedness by regularization, and adopts a dual activation function in the hidden nodes combing neural and wavelet theory to enhance prediction capability. The experimental results verify the good generalization performance of SROS-ELM and show that the developed analytical redundancy technique for aeroengine sensor fault diagnosis based on SROS-ELM is effective and feasible.

  7. Next generation of optical diagnostics for bladder cancer using probe-based confocal laser endomicroscopy

    Science.gov (United States)

    Liu, Jen-Jane; Chang, Timothy C.; Pan, Ying; Hsiao, Shelly T.; Mach, Kathleen E.; Jensen, Kristin C.; Liao, Joseph C.

    2012-02-01

    Real-time imaging with confocal laser endomicroscopy (CLE) probes that fit in standard endoscopes has emerged as a clinically feasible technology for optical biopsy of bladder cancer. Confocal images of normal, inflammatory, and neoplastic urothelium obtained with intravesical fluorescein can be differentiated by morphologic characteristics. We compiled a confocal atlas of the urinary tract using these diagnostic criteria to be used in a prospective diagnostic accuracy study. Patients scheduled to undergo transurethral resection of bladder tumor underwent white light cystoscopy (WLC), followed by CLE, and histologic confirmation of resected tissue. Areas that appeared normal by WLC were imaged and biopsied as controls. We imaged and prospectively analyzed 135 areas in 57 patients. We show that CLE improves the diagnostic accuracy of WLC for diagnosing benign tissue, low and high grade cancer. Interobserver studies showed a moderate level of agreement by urologists and nonclinical researchers. Despite morphologic differences between inflammation and cancer, real-time differentiation can still be challenging. Identification of bladder cancer-specific contrast agents could provide molecular specificity to CLE. By using fluorescently-labeled antibodies or peptides that bind to proteins expressed in bladder cancer, we have identified putative molecular contrast agents for targeted imaging with CLE. We describe one candidate agent - anti-CD47 - that was instilled into bladder specimens. The tumor and normal urothelium were imaged with CLE, with increased fluorescent signal demonstrated in areas of tumor compared to normal areas. Thus, cancer-specificity can be achieved using molecular contrast agents ex vivo in conjunction with CLE.

  8. Molecular diagnostics of foodborne pathogens

    DEFF Research Database (Denmark)

    Hansen, Trine

    of pathogens are needed. The introduction of the molecular diagnostics methods based on detection of the organisms nucleic acids have made detection, identification and characterization of foodborne pathogens faster and with greater specificity and sensitivity. The objectives of research in this thesis were...... to investigate the use of different nucleic acid based methods for molecular diagnostics of foodborne pathogens focusing on Salmonellaand Bacillus cereuswith respect to improve food safety. The work represents two parts of molecular diagnostics; the characterization Salmonellafor better understanding of its...... for screening of unknown bacteria in bottled water without prior cultivation. B. cereusartificially inoculated in bottled water was used as a model. The results revealed that the method was able to detect B. cereusat levels of 105-106 CFU/L, a detection level low enough for detection in outbreaks situations...

  9. Model-based requirements engineering

    CERN Document Server

    Holt, Jon

    2012-01-01

    This book provides a hands-on introduction to model-based requirementsengineering and management by describing a set of views that form the basisfor the approach. These views take into account each individual requirement interms of its description, but then also provide each requirement with meaning byputting it into the correct 'context'. A requirement that has been put into a contextis known as a 'use case' and may be based upon either stakeholders or levelsof hierarchy in a system. Each use case must then be analysed and validated bydefining a combination of scenarios and formal mathematica

  10. Diagnostic model for assessing traceability system performance in fish processing plants

    NARCIS (Netherlands)

    Mgonja, J.T.; Luning, P.A.; Vorst, van der J.G.A.J.

    2013-01-01

    This paper introduces a diagnostic tool that can be used by fish processing companies to evaluate their own traceability systems in a systematic manner. The paper begins with discussions on the rationale of traceability systems in food manufacturing companies, followed by a detailed analysis of the

  11. Diagnostic, Explanatory, and Detection Models of Munchausen by Proxy: Extrapolations from Malingering and Deception

    Science.gov (United States)

    Rogers, Richard

    2004-01-01

    Objective: The overriding objective is a critical examination of Munchausen syndrome by proxy (MSBP) and its closely-related alternative, factitious disorder by proxy (FDBP). Beyond issues of diagnostic validity, assessment methods and potential detection strategies are explored. Methods: A painstaking analysis was conducted of the MSBP and FDBP…

  12. Model-based tomographic reconstruction

    Science.gov (United States)

    Chambers, David H.; Lehman, Sean K.; Goodman, Dennis M.

    2012-06-26

    A model-based approach to estimating wall positions for a building is developed and tested using simulated data. It borrows two techniques from geophysical inversion problems, layer stripping and stacking, and combines them with a model-based estimation algorithm that minimizes the mean-square error between the predicted signal and the data. The technique is designed to process multiple looks from an ultra wideband radar array. The processed signal is time-gated and each section processed to detect the presence of a wall and estimate its position, thickness, and material parameters. The floor plan of a building is determined by moving the array around the outside of the building. In this paper we describe how the stacking and layer stripping algorithms are combined and show the results from a simple numerical example of three parallel walls.

  13. Differential Geometry Based Multiscale Models

    OpenAIRE

    Wei, Guo-Wei

    2010-01-01

    Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descript...

  14. A real time zero-dimensional diagnostic model for the calculation of in-cylinder temperatures, HRR and nitrogen oxides in diesel engines

    International Nuclear Information System (INIS)

    Highlights: • Real-time zero-dimensional three-zone diagnostic combustion model. • Capable of evaluating in-cylinder temperatures, HRR and NOx in DI diesel engines. • Able to be integrated in the engine ECU for control applications. • Able to be integrated in the test bed acquisition software for calibration tasks. • Tested under both steady state and fast transient conditions. - Abstract: A real-time zero-dimensional diagnostic combustion model has been developed and assessed to evaluate in-cylinder temperatures, HRR (heat release rate) and NOx (nitrogen oxides) in DI (Direct Injection) diesel engines under steady state and transient conditions. The approach requires very little computational time, that is, of the order of a few milliseconds, and is therefore suitable for real-time applications. It could, for example, be implemented in an ECU (Engine Control Unit) for the on-board diagnostics of combustion and emission formation processes, or it could be integrated in acquisition software installed on an engine test bench for indicated analysis. The model could also be used for post-processing analysis of previously acquired experimental data. The methodology is based on a three-zone thermodynamic model: the combustion chamber is divided into a fuel zone, an unburned gas zone and a stoichiometric burned gas zone, to which the energy and mass conservation equations are applied. The main novelty of the proposed method is that the equations can be solved in closed form, thus making the approach suitable for real-time applications. The evaluation of the temperature of burned gases allows the in-cylinder NOx concentration to be calculated, on the basis of prompt and Zeldovich thermal mechanisms. The procedure also takes into account the NOx level in the intake charge, and is therefore suitable for engines equipped with traditional short-route EGR (Exhaust Gas Recirculation) systems, and engines equipped with SCR (Selective Catalytic Reduction) and long

  15. A Diagnostic Procedure for Transformative Change Based on Transitions, Resilience, and Institutional Thinking

    Directory of Open Access Journals (Sweden)

    Briony C. Ferguson

    2013-12-01

    Full Text Available Urban water governance regimes around the world have traditionally planned large-scale, centralized infrastructure systems that aim to control variables and reduce uncertainties. There is growing sectoral awareness that a transition toward sustainable alternatives is necessary if systems are to meet society's future water needs in the context of drivers such as climate change and variability, demographic changes, environmental degradation, and resource scarcity. However, there is minimal understanding of how the urban water sector should operationalize its strategic planning for such change to facilitate the transition to a sustainable water future. We have integrated concepts from transitions, resilience, and institutional theory to develop a diagnostic procedure for revealing insights into which types of strategic action are most likely to influence the direction and pace of change in the overall system toward a desired trajectory. The procedure used the multipattern approach, from transition theory, to identify the system conditions and type of changes necessary for enabling system transformation. It incorporated the adaptive cycle, from resilience theory, to identify the current phase of change for different parts of the system. Finally, it drew on the concepts of institutional pillars and institutional work to identify mechanisms that are likely to be most effective in influencing the transformative dynamics of the system toward a desired trajectory. We have demonstrated application of the proposed diagnostic procedure on a case study of recent transformative change in the urban water system of Melbourne, Australia. We have proposed that an operational diagnostic procedure provides a useful platform from which planners, policy analysts, and decision makers could follow a process of deduction that identifies which types of strategic action best fit the current system conditions.

  16. Development of Recombinant Nucleoprotein-Based Diagnostic Systems for Lassa Fever▿

    OpenAIRE

    Saijo, Masayuki; Georges-Courbot, Marie-Claude; Marianneau, Philippe; Romanowski, Victor; Fukushi, Shuetsu; Mizutani, Tetsuya; Georges, Alain-Jean; Kurata, Takeshi; Kurane, Ichiro; Morikawa, Shigeru

    2007-01-01

    Diagnostic systems for Lassa fever (LF), a viral hemorrhagic fever caused by Lassa virus (LASV), such as enzyme immunoassays for the detection of LASV antibodies and LASV antigens, were developed using the recombinant nucleoprotein (rNP) of LASV (LASV-rNP). The LASV-rNP was expressed in a recombinant baculovirus system. LASV-rNP was used as an antigen in the detection of LASV-antibodies and as an immunogen for the production of monoclonal antibodies. The LASV-rNP was also expressed in HeLa ce...

  17. Crowdsourcing Based 3d Modeling

    Science.gov (United States)

    Somogyi, A.; Barsi, A.; Molnar, B.; Lovas, T.

    2016-06-01

    Web-based photo albums that support organizing and viewing the users' images are widely used. These services provide a convenient solution for storing, editing and sharing images. In many cases, the users attach geotags to the images in order to enable using them e.g. in location based applications on social networks. Our paper discusses a procedure that collects open access images from a site frequently visited by tourists. Geotagged pictures showing the image of a sight or tourist attraction are selected and processed in photogrammetric processing software that produces the 3D model of the captured object. For the particular investigation we selected three attractions in Budapest. To assess the geometrical accuracy, we used laser scanner and DSLR as well as smart phone photography to derive reference values to enable verifying the spatial model obtained from the web-album images. The investigation shows how detailed and accurate models could be derived applying photogrammetric processing software, simply by using images of the community, without visiting the site.

  18. An Agent Based Classification Model

    CERN Document Server

    Gu, Feng; Greensmith, Julie

    2009-01-01

    The major function of this model is to access the UCI Wisconsin Breast Can- cer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classifi cation can be referred as anomaly detection, which discriminates anomalous behaviour from normal behaviour in computer systems. One popular solution for anomaly detection is Artifi cial Immune Sys- tems (AIS). AIS are adaptive systems inspired by theoretical immunology and observed immune functions, principles and models which are applied to prob- lem solving. The Dendritic Cell Algorithm (DCA)[2] is an AIS algorithm that is developed specifi cally for anomaly detection. It has been successfully applied to intrusion detection in computer security. It is believed that agent-based mod- elling is an ideal approach for implementing AIS, as intelligent agents could be the perfect representations of immune entities in AIS. This model evaluates the feasibility of re-implementing the DCA in an agent-based simulation environ- ...

  19. Comparing Tuberculosis Diagnostic Yield in Smear/Culture and Xpert® MTB/RIF-Based Algorithms Using a Non-Randomised Stepped-Wedge Design

    Science.gov (United States)

    Naidoo, Pren; Dunbar, Rory; Lombard, Carl; du Toit, Elizabeth; Caldwell, Judy; Detjen, Anne; Squire, S. Bertel; Enarson, Donald A.; Beyers, Nulda

    2016-01-01

    Setting Primary health services in Cape Town, South Africa. Study Aim To compare tuberculosis (TB) diagnostic yield in an existing smear/culture-based and a newly introduced Xpert® MTB/RIF-based algorithm. Methods TB diagnostic yield (the proportion of presumptive TB cases with a laboratory diagnosis of TB) was assessed using a non-randomised stepped-wedge design as sites transitioned to the Xpert® based algorithm. We identified the full sequence of sputum tests recorded in the electronic laboratory database for presumptive TB cases from 60 primary health sites during seven one-month time-points, six months apart. Differences in TB yield and temporal trends were estimated using a binomial regression model. Results TB yield was 20.9% (95% CI 19.9% to 22.0%) in the smear/culture-based algorithm compared to 17.9% (95%CI 16.4% to 19.5%) in the Xpert® based algorithm. There was a decline in TB yield over time with a mean risk difference of -0.9% (95% CI -1.2% to -0.6%) (p<0.001) per time-point. When estimates were adjusted for the temporal trend, TB yield was 19.1% (95% CI 17.6% to 20.5%) in the smear/culture-based algorithm compared to 19.3% (95% CI 17.7% to 20.9%) in the Xpert® based algorithm with a risk difference of 0.3% (95% CI -1.8% to 2.3%) (p = 0.796). Culture tests were undertaken for 35.5% of smear-negative compared to 17.9% of Xpert® negative low MDR-TB risk cases and for 82.6% of smear-negative compared to 40.5% of Xpert® negative high MDR-TB risk cases in respective algorithms. Conclusion Introduction of an Xpert® based algorithm did not produce the expected increase in TB diagnostic yield. Studies are required to assess whether improving adherence to the Xpert® negative algorithm for HIV-infected individuals will increase yield. In light of the high cost of Xpert®, a review of its role as a screening test for all presumptive TB cases may be warranted. PMID:26930400

  20. Comparing Tuberculosis Diagnostic Yield in Smear/Culture and Xpert® MTB/RIF-Based Algorithms Using a Non-Randomised Stepped-Wedge Design.

    Directory of Open Access Journals (Sweden)

    Pren Naidoo

    Full Text Available Primary health services in Cape Town, South Africa.To compare tuberculosis (TB diagnostic yield in an existing smear/culture-based and a newly introduced Xpert® MTB/RIF-based algorithm.TB diagnostic yield (the proportion of presumptive TB cases with a laboratory diagnosis of TB was assessed using a non-randomised stepped-wedge design as sites transitioned to the Xpert® based algorithm. We identified the full sequence of sputum tests recorded in the electronic laboratory database for presumptive TB cases from 60 primary health sites during seven one-month time-points, six months apart. Differences in TB yield and temporal trends were estimated using a binomial regression model.TB yield was 20.9% (95% CI 19.9% to 22.0% in the smear/culture-based algorithm compared to 17.9% (95%CI 16.4% to 19.5% in the Xpert® based algorithm. There was a decline in TB yield over time with a mean risk difference of -0.9% (95% CI -1.2% to -0.6% (p<0.001 per time-point. When estimates were adjusted for the temporal trend, TB yield was 19.1% (95% CI 17.6% to 20.5% in the smear/culture-based algorithm compared to 19.3% (95% CI 17.7% to 20.9% in the Xpert® based algorithm with a risk difference of 0.3% (95% CI -1.8% to 2.3% (p = 0.796. Culture tests were undertaken for 35.5% of smear-negative compared to 17.9% of Xpert® negative low MDR-TB risk cases and for 82.6% of smear-negative compared to 40.5% of Xpert® negative high MDR-TB risk cases in respective algorithms.Introduction of an Xpert® based algorithm did not produce the expected increase in TB diagnostic yield. Studies are required to assess whether improving adherence to the Xpert® negative algorithm for HIV-infected individuals will increase yield. In light of the high cost of Xpert®, a review of its role as a screening test for all presumptive TB cases may be warranted.